Determination of benzo[a]pyrene in cigarette mainstream smoke by using mid-infrared spectroscopy associated with a novel chemometric algorithm.

PubMed

Zhang, Yan; Zou, Hong-Yan; Shi, Pei; Yang, Qin; Tang, Li-Juan; Jiang, Jian-Hui; Wu, Hai-Long; Yu, Ru-Qin

2016-01-01

Determination of benzo[a]pyrene (BaP) in cigarette smoke can be very important for the tobacco quality control and the assessment of its harm to human health. In this study, mid-infrared spectroscopy (MIR) coupled to chemometric algorithm (DPSO-WPT-PLS), which was based on the wavelet packet transform (WPT), discrete particle swarm optimization algorithm (DPSO) and partial least squares regression (PLS), was used to quantify harmful ingredient benzo[a]pyrene in the cigarette mainstream smoke with promising result. Furthermore, the proposed method provided better performance compared to several other chemometric models, i.e., PLS, radial basis function-based PLS (RBF-PLS), PLS with stepwise regression variable selection (Stepwise-PLS) as well as WPT-PLS with informative wavelet coefficients selected by correlation coefficient test (rtest-WPT-PLS). It can be expected that the proposed strategy could become a new effective, rapid quantitative analysis technique in analyzing the harmful ingredient BaP in cigarette mainstream smoke. Copyright © 2015 Elsevier B.V. All rights reserved.

Soil sail content estimation in the yellow river delta with satellite hyperspectral data

USGS Publications Warehouse

Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

2008-01-01

Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

Visual Analysis of North Atlantic Hurricane Trends Using Parallel Coordinates and Statistical Techniques

DTIC Science & Technology

2008-07-07

analyzing multivariate data sets. The system was developed using the Java Development Kit (JDK) version 1.5; and it yields interactive performance on a... script and captures output from the MATLAB’s “regress” and “stepwisefit” utilities that perform simple and stepwise regression, respectively. The MATLAB...Statistical Association, vol. 85, no. 411, pp. 664–675, 1990. [9] H. Hauser, F. Ledermann, and H. Doleisch, “ Angular brushing of extended parallel coordinates

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

What are the important surgical factors affecting the wound healing after primary total knee arthroplasty?

PubMed

Harato, Kengo; Tanikawa, Hidenori; Morishige, Yutaro; Kaneda, Kazuya; Niki, Yasuo

2016-01-13

Wound condition after primary total knee arthroplasty (TKA) is an important issue to avoid any postoperative adverse events. Our purpose was to investigate and to clarify the important surgical factors affecting wound score after TKA. A total of 139 knees in 128 patients (mean 73 years) without severe comorbidity were enrolled in the present study. All primary unilateral or bilateral TKAs were done using the same skin incision line, measured resection technique, and wound closure technique using unidirectional barbed suture. In terms of the wound healing, Hollander Wound Evaluation Score (HWES) was assessed on postoperative day 14. We performed multiple regression analysis using stepwise method to identify the factors affecting HWES. Variables considered in the analysis were age, sex, body mass index (kg/m(2)), HbA1C (%), femorotibial angle (degrees) on plain radiographs, intraoperative patella eversion during the cutting phase of the femur and the tibia in knee flexion, intraoperative anterior translation of the tibia, patella resurfacing, surgical time (min), tourniquet time (min), length of skin incision (cm), postoperative drainage (ml), patellar height on postoperative lateral radiographs, and HWES. HWES was treated as a dependent variable, and others were as independent variables. The average HWES was 5.0 ± 0.8 point. According to stepwise forward regression test, patella eversion during the cutting phase of the femur and the tibia in knee flexion and anterior translation of the tibia were entered in this model, while other factors were not entered. Standardized partial regression coefficient was as follows: 0.57 in anterior translation of the tibia and 0.38 in patella eversion. Fortunately, in the present study using the unidirectional barbed suture, major wound healing problem did not occur. As to the surgical technique, intraoperative patella eversion and anterior translation of the tibia should be avoided for quality cosmesis in primary TKA.

Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis

NASA Astrophysics Data System (ADS)

Zhang, Ningyu; Xu, Fuyun; Zhuang, Shidong; He, Changwei

2016-10-01

Heavy metal pollution in soils is one of the most critical problems in the global ecology and environment safety nowadays. Hyperspectral remote sensing and its application is capable of high speed, low cost, less risk and less damage, and provides a good method for detecting heavy metals in soil. This paper proposed a new idea of applying regression analysis of stepwise multiple regression between the spectral data and monitoring the amount of heavy metal Cr by sample points in soil for environmental protection. In the measurement, a FieldSpec HandHeld spectroradiometer is used to collect reflectance spectra of sample points over the wavelength range of 325-1075 nm. Then the spectral data measured by the spectroradiometer is preprocessed to reduced the influence of the external factors, and the preprocessed methods include first-order differential equation, second-order differential equation and continuum removal method. The algorithms of stepwise multiple regression are established accordingly, and the accuracy of each equation is tested. The results showed that the accuracy of first-order differential equation works best, which makes it feasible to predict the content of heavy metal Cr by using stepwise multiple regression.

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

NASA Astrophysics Data System (ADS)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

Memory for self-generated narration in the elderly.

PubMed

Drevenstedt, J; Bellezza, F S

1993-06-01

The story mnemonic technique, an effective encoding and retrieval strategy for young adults, was used as a procedure to study encoding and recall in elderly women. Experiment 1 (15 undergraduate and 14 elderly women) showed the technique to be reliable over 3 weeks and without practice effects in both age groups. In Experiment 2, 67 elderly women (mean age = 72 years) were found to make up 3 distinctive subgroupings in patterns of narration cohesiveness and recall accuracy, consistent with pilot data on the technique. A stepwise multiple regression equation found narration cohesiveness, an adaptation of the Daneman-Carpenter (1980) working-memory measure and vocabulary to predict word recall. Results suggested that a general memory factor differentiated the 3 elderly subgroups.

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

NASA Astrophysics Data System (ADS)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

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

Tang, Kunkun, E-mail: ktg@illinois.edu; Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence; Congedo, Pietro M.

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable formore » real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.« less

DFT study on oxidation of HS(CH2) m SH ( m = 1-8) in oxidative desulfurization

NASA Astrophysics Data System (ADS)

Song, Y. Z.; Song, J. J.; Zhao, T. T.; Chen, C. Y.; He, M.; Du, J.

2016-06-01

Density functional theory was employed for calculation of HS(CH2) m SH ( m = 1-8) and its derivatives at B3LYP method at 6-31++g ( d, p) level. Using eigenvalues of LUMO and HOMO for HS(CH2) m SH, the standard electrode potentials were estimated by a stepwise multiple regression techniques (MLR), and obtained as E° = 1.500 + 7.167 × 10-3 HOMO-0.229 LUMO with high correlation coefficients of 0.973 and F values of 43.973.

Application of LANDSAT to the surveillance and control of lake eutrophication in the Great Lakes basin. [Saginaw Bay, Michigan and Wisconsin

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Computer techniques were developed for mapping water quality parameters from LANDSAT data, using surface samples collected in an ongoing survey of water quality in Saginaw Bay. Chemical and biological parameters were measured on 31 July 1975 at 16 bay stations in concert with the LANDSAT overflight. Application of stepwise linear regression bands to nine of these parameters and corresponding LANDSAT measurements for bands 4 and 5 only resulted in regression correlation coefficients that varied from 0.94 for temperature to 0.73 for Secchi depth. Regression equations expressed with the pair of bands 4 and 5, rather than the ratio band 4/band 5, provided higher correlation coefficients for all the water quality parameters studied (temperature, Secchi depth, chloride, conductivity, total kjeldahl nitrogen, total phosphorus, chlorophyll a, total solids, and suspended solids).

A linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Goetz, Alexander F. H.

1992-01-01

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described.

Does Stepwise Voltage Ramping Protect the Kidney from Injury During Extracorporeal Shockwave Lithotripsy? Results of a Prospective Randomized Trial.

PubMed

Skuginna, Veronika; Nguyen, Daniel P; Seiler, Roland; Kiss, Bernhard; Thalmann, George N; Roth, Beat

2016-02-01

Renal damage is more frequent with new-generation lithotripters. However, animal studies suggest that voltage ramping minimizes the risk of complications following extracorporeal shock wave lithotripsy (SWL). In the clinical setting, the optimal voltage strategy remains unclear. To evaluate whether stepwise voltage ramping can protect the kidney from damage during SWL. A total of 418 patients with solitary or multiple unilateral kidney stones were randomized to receive SWL using a Modulith SLX-F2 lithotripter with either stepwise voltage ramping (n=213) or a fixed maximal voltage (n=205). SWL. The primary outcome was sonographic evidence of renal hematomas. Secondary outcomes included levels of urinary markers of renal damage, stone disintegration, stone-free rate, and rates of secondary interventions within 3 mo of SWL. Descriptive statistics were used to compare clinical outcomes between the two groups. A logistic regression model was generated to assess predictors of hematomas. Significantly fewer hematomas occurred in the ramping group(12/213, 5.6%) than in the fixed group (27/205, 13%; p=0.008). There was some evidence that the fixed group had higher urinary β2-microglobulin levels after SWL compared to the ramping group (p=0.06). Urinary microalbumin levels, stone disintegration, stone-free rate, and rates of secondary interventions did not significantly differ between the groups. The logistic regression model showed a significantly higher risk of renal hematomas in older patients (odds ratio [OR] 1.03, 95% confidence interval [CI] 1.00-1.05; p=0.04). Stepwise voltage ramping was associated with a lower risk of hematomas (OR 0.39, 95% CI 0.19-0.80; p=0.01). The study was limited by the use of ultrasound to detect hematomas. In this prospective randomized study, stepwise voltage ramping during SWL was associated with a lower risk of renal damage compared to a fixed maximal voltage without compromising treatment effectiveness. Lithotripsy is a noninvasive technique for urinary stone disintegration using ultrasonic energy. In this study, two voltage strategies are compared. The results show that a progressive increase in voltage during lithotripsy decreases the risk of renal hematomas while maintaining excellent outcomes. ISRCTN95762080. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Exploring the relationships between free-time management and boredom in leisure.

PubMed

Wang, Wei-Ching; Wu, Chung-Chi; Wu, Chang-Yang; Huan, Tzung-Cheng

2012-04-01

The purpose of the study was to examine the relations of five dimensions of free-time management (including goal setting and evaluating, technique, values, immediate response, and scheduling) with leisure boredom, and whether these factors could predict leisure boredom. A total of 500 undergraduates from a university in southern Taiwan were surveyed with 403 usable questionnaires was returned. Pearson correlation analysis revealed that five dimensions of free-time management had significant negative relationships with leisure boredom. Furthermore, the results of stepwise regression analysis revealed that four dimensions of free-time management were significant contributors to leisure boredom. Finally, we suggested students can avoid boredom by properly planning and organizing leisure time and applying techniques for managing leisure time.

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Congedo, Pietro M.; Abgrall, Rémi

2016-06-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

Application of remote sensing for fishery resources assessment and monitoring. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Savastano, K. J. (Principal Investigator)

1975-01-01

The author has identified the following significant results. The distribution and abundance of white marlin correlated with the chlorophyll, water temperature, and Secchi depth sea truth measurements. Results of correlation analyses for dolphin were inconclusive. Predicition models for white marlin were developed using stepwise multiple regression and discriminant function analysis techniques which demonstrated a potential for increasing the probability of game fishing success. The S190A and B imagery was density sliced/color enhanced with white marlin location superimposed on the image, but no density/white marlin relationship could be established.

Stepwise versus Hierarchical Regression: Pros and Cons

ERIC Educational Resources Information Center

Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

A Hybrid Approach of Stepwise Regression, Logistic Regression, Support Vector Machine, and Decision Tree for Forecasting Fraudulent Financial Statements

PubMed Central

Goo, Yeong-Jia James; Shen, Zone-De

2014-01-01

As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%. PMID:25302338

A hybrid approach of stepwise regression, logistic regression, support vector machine, and decision tree for forecasting fraudulent financial statements.

PubMed

Chen, Suduan; Goo, Yeong-Jia James; Shen, Zone-De

2014-01-01

As the fraudulent financial statement of an enterprise is increasingly serious with each passing day, establishing a valid forecasting fraudulent financial statement model of an enterprise has become an important question for academic research and financial practice. After screening the important variables using the stepwise regression, the study also matches the logistic regression, support vector machine, and decision tree to construct the classification models to make a comparison. The study adopts financial and nonfinancial variables to assist in establishment of the forecasting fraudulent financial statement model. Research objects are the companies to which the fraudulent and nonfraudulent financial statement happened between years 1998 to 2012. The findings are that financial and nonfinancial information are effectively used to distinguish the fraudulent financial statement, and decision tree C5.0 has the best classification effect 85.71%.

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

Associations between dietary and lifestyle risk factors and colorectal cancer in the Scottish population.

PubMed

Theodoratou, Evropi; Farrington, Susan M; Tenesa, Albert; McNeill, Geraldine; Cetnarskyj, Roseanne; Korakakis, Emmanouil; Din, Farhat V N; Porteous, Mary E; Dunlop, Malcolm G; Campbell, Harry

2014-01-01

Colorectal cancer (CRC) accounts for 9.7% of all cancer cases and for 8% of all cancer-related deaths. Established risk factors include personal or family history of CRC as well as lifestyle and dietary factors. We investigated the relationship between CRC and demographic, lifestyle, food and nutrient risk factors through a case-control study that included 2062 patients and 2776 controls from Scotland. Forward and backward stepwise regression was applied and the stability of the models was assessed in 1000 bootstrap samples. The variables that were automatically selected to be included by the forward or backward stepwise regression and whose selection was verified by bootstrap sampling in the current study were family history, dietary energy, 'high-energy snack foods', eggs, juice, sugar-sweetened beverages and white fish (associated with an increased CRC risk) and NSAIDs, coffee and magnesium (associated with a decreased CRC risk). Application of forward and backward stepwise regression in this CRC study identified some already established as well as some novel potential risk factors. Bootstrap findings suggest that examination of the stability of regression models by bootstrap sampling is useful in the interpretation of study findings. 'High-energy snack foods' and high-energy drinks (including sugar-sweetened beverages and fruit juices) as risk factors for CRC have not been reported previously and merit further investigation as such snacks and beverages are important contributors in European and North American diets.

Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

NASA Astrophysics Data System (ADS)

Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

2017-12-01

An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

Comparison of Nine Statistical Model Based Warfarin Pharmacogenetic Dosing Algorithms Using the Racially Diverse International Warfarin Pharmacogenetic Consortium Cohort Database

PubMed Central

Liu, Rong; Li, Xi; Zhang, Wei; Zhou, Hong-Hao

2015-01-01

Objective Multiple linear regression (MLR) and machine learning techniques in pharmacogenetic algorithm-based warfarin dosing have been reported. However, performances of these algorithms in racially diverse group have never been objectively evaluated and compared. In this literature-based study, we compared the performances of eight machine learning techniques with those of MLR in a large, racially-diverse cohort. Methods MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied in warfarin dose algorithms in a cohort from the International Warfarin Pharmacogenetics Consortium database. Covariates obtained by stepwise regression from 80% of randomly selected patients were used to develop algorithms. To compare the performances of these algorithms, the mean percentage of patients whose predicted dose fell within 20% of the actual dose (mean percentage within 20%) and the mean absolute error (MAE) were calculated in the remaining 20% of patients. The performances of these techniques in different races, as well as the dose ranges of therapeutic warfarin were compared. Robust results were obtained after 100 rounds of resampling. Results BART, MARS and SVR were statistically indistinguishable and significantly out performed all the other approaches in the whole cohort (MAE: 8.84–8.96 mg/week, mean percentage within 20%: 45.88%–46.35%). In the White population, MARS and BART showed higher mean percentage within 20% and lower mean MAE than those of MLR (all p values < 0.05). In the Asian population, SVR, BART, MARS and LAR performed the same as MLR. MLR and LAR optimally performed among the Black population. When patients were grouped in terms of warfarin dose range, all machine learning techniques except ANN and LAR showed significantly higher mean percentage within 20%, and lower MAE (all p values < 0.05) than MLR in the low- and high- dose ranges. Conclusion Overall, machine learning-based techniques, BART, MARS and SVR performed superior than MLR in warfarin pharmacogenetic dosing. Differences of algorithms’ performances exist among the races. Moreover, machine learning-based algorithms tended to perform better in the low- and high- dose ranges than MLR. PMID:26305568

Epidemiological analysis of factors influencing rate of progress in Echinococcus granulosus control in New Zealand.

PubMed Central

Burridge, M. J.; Schwabe, C. W.

1977-01-01

The factors influencing the rate of progress in Echinococcus granulosus control in New Zealand were analysed by hydatid control area using stepwise multiple regression techniques. The results indicated that the rate of progress was related positively to initial E. granulosus prevalence in dogs and the efficiency with which local authorities implemented national control policy, and negatively to the Maori proportion in the local population and the number of dogs per owner. Problems in analysis of the New Zealand data are discussed and improved methods of monitoring progress in hydatid disease control programmes are described. Images Fig. 1 PMID:265340

Computational technique for stepwise quantitative assessment of equation correctness

NASA Astrophysics Data System (ADS)

Othman, Nuru'l Izzah; Bakar, Zainab Abu

2017-04-01

Many of the computer-aided mathematics assessment systems that are available today possess the capability to implement stepwise correctness checking of a working scheme for solving equations. The computational technique for assessing the correctness of each response in the scheme mainly involves checking the mathematical equivalence and providing qualitative feedback. This paper presents a technique, known as the Stepwise Correctness Checking and Scoring (SCCS) technique that checks the correctness of each equation in terms of structural equivalence and provides quantitative feedback. The technique, which is based on the Multiset framework, adapts certain techniques from textual information retrieval involving tokenization, document modelling and similarity evaluation. The performance of the SCCS technique was tested using worked solutions on solving linear algebraic equations in one variable. 350 working schemes comprising of 1385 responses were collected using a marking engine prototype, which has been developed based on the technique. The results show that both the automated analytical scores and the automated overall scores generated by the marking engine exhibit high percent agreement, high correlation and high degree of agreement with manual scores with small average absolute and mixed errors.

[Associated factors in newborns with intrauterine growth retardation].

PubMed

Thompson-Chagoyán, Oscar C; Vega-Franco, Leopoldo

2008-01-01

To identify the risk factors implicated in the intrauterine growth retardation (IUGR) of neonates born in a social security institution. Case controls design study in 376 neonates: 188 with IUGR (weight < 10 percentile) and 188 without IUGR. When they born, information about 30 variables of risk for IUGR were obtained from mothers. Risk analysis and logistical regression (stepwise) were used. Odds ratios were significant for 12 of the variables. The model obtains by stepwise regression included: weight gain at pregnancy, prenatal care attendance, toxemia, chocolate ingestion, father's weight, and the environmental house. Must of the variables included in the model are related to socioeconomic disadvantages related to the risk of RCIU in the population.

Quantitative laser-induced breakdown spectroscopy data using peak area step-wise regression analysis: an alternative method for interpretation of Mars science laboratory results

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

Clegg, Samuel M; Barefield, James E; Wiens, Roger C

2008-01-01

The ChemCam instrument on the Mars Science Laboratory (MSL) will include a laser-induced breakdown spectrometer (LIBS) to quantify major and minor elemental compositions. The traditional analytical chemistry approach to calibration curves for these data regresses a single diagnostic peak area against concentration for each element. This approach contrasts with a new multivariate method in which elemental concentrations are predicted by step-wise multiple regression analysis based on areas of a specific set of diagnostic peaks for each element. The method is tested on LIBS data from igneous and metamorphosed rocks. Between 4 and 13 partial regression coefficients are needed to describemore » each elemental abundance accurately (i.e., with a regression line of R{sup 2} > 0.9995 for the relationship between predicted and measured elemental concentration) for all major and minor elements studied. Validation plots suggest that the method is limited at present by the small data set, and will work best for prediction of concentration when a wide variety of compositions and rock types has been analyzed.« less

Inhaler technique maintenance: gaining an understanding from the patient's perspective.

PubMed

Ovchinikova, Ludmila; Smith, Lorraine; Bosnic-Anticevich, Sinthia

2011-08-01

The aim of this study was to determine the patient-, education-, and device-related factors that predict inhaler technique maintenance. Thirty-one community pharmacists were trained to deliver inhaler technique education to people with asthma. Pharmacists evaluated (based on published checklists), and where appropriate, delivered inhaler technique education to patients (participants) in the community pharmacy at baseline (Visit 1) and 1 month later (Visit 2). Data were collected on participant demographics, asthma history, current asthma control, history of inhaler technique education, and a range of psychosocial aspects of disease management (including adherence to medication, motivation for correct technique, beliefs regarding the importance of maintaining correct technique, and necessity and concern beliefs regarding preventer therapy). Stepwise backward logistic regression was used to identify the predictors of inhaler technique maintenance at 1 month. In total 145 and 127 participants completed Visits 1 and 2, respectively. At baseline, 17% of patients (n = 24) demonstrated correct technique (score 11/11) which increased to 100% (n = 139) after remedial education by pharmacists. At follow-up, 61% (n = 77) of patients demonstrated correct technique. The predictors of inhaler technique maintenance based on the logistic regression model (X(2) (3, N = 125) = 16.22, p = .001) were use of a dry powder inhaler over a pressurized metered-dose inhaler (OR 2.6), having better asthma control at baseline (OR 2.3), and being more motivated to practice correct inhaler technique (OR 1.2). Contrary to what is typically recommended in previous research, correct inhaler technique maintenance may involve more than repetition of instructions. This study found that past technique education factors had no bearing on technique maintenance, whereas patient psychosocial factors (motivation) did.

Identification of molecular markers associated with mite resistance in coconut (Cocos nucifera L.).

PubMed

Shalini, K V; Manjunatha, S; Lebrun, P; Berger, A; Baudouin, L; Pirany, N; Ranganath, R M; Prasad, D Theertha

2007-01-01

Coconut mite (Aceria guerreronis 'Keifer') has become a major threat to Indian coconut (Coçcos nucifera L.) cultivators and the processing industry. Chemical and biological control measures have proved to be costly, ineffective, and ecologically undesirable. Planting mite-resistant coconut cultivars is the most effective method of preventing yield loss and should form a major component of any integrated pest management stratagem. Coconut genotypes, and mite-resistant and -susceptible accessions were collected from different parts of South India. Thirty-two simple sequence repeat (SSR) and 7 RAPD primers were used for molecular analyses. In single-marker analysis, 9 SSR and 4 RAPD markers associated with mite resistance were identified. In stepwise multiple regression analysis of SSRs, a combination of 6 markers showed 100% association with mite infestation. Stepwise multiple regression analysis for RAPD data revealed that a combination of 3 markers accounted for 83.86% of mite resistance in the selected materials. Combined stepwise multiple regression analysis of RAPD and SSR data showed that a combination of 5 markers explained 100% of the association with mite resistance in coconut. Markers associated with mite resistance are important in coconut breeding programs and will facilitate the selection of mite-resistant plants at an early stage as well as mother plants for breeding programs.

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

Hypnotism as a Function of Trance State Effects, Expectancy, and Suggestibility: An Italian Replication.

PubMed

Pekala, Ronald J; Baglio, Francesca; Cabinio, Monia; Lipari, Susanna; Baglio, Gisella; Mendozzi, Laura; Cecconi, Pietro; Pugnetti, Luigi; Sciaky, Riccardo

2017-01-01

Previous research using stepwise regression analyses found self-reported hypnotic depth (srHD) to be a function of suggestibility, trance state effects, and expectancy. This study sought to replicate and expand that research using a general state measure of hypnotic responsivity, the Phenomenology of Consciousness Inventory: Hypnotic Assessment Procedure (PCI-HAP). Ninety-five participants completed an Italian translation of the PCI-HAP, with srHD scores predicted from the PCI-HAP assessment items. The regression analysis replicated the previous research results. Additionally, stepwise regression analyses were able to predict the srHD score equally well using only the PCI dimension scores. These results not only replicated prior research but suggest how this methodology to assess hypnotic responsivity, when combined with more traditional neurophysiological and cognitive-behavioral methodologies, may allow for a more comprehensive understanding of that enigma called hypnosis.

An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling.

PubMed

Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady

2017-09-01

Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights reserved.

A statistical model for Windstorm Variability over the British Isles based on Large-scale Atmospheric and Oceanic Mechanisms

NASA Astrophysics Data System (ADS)

Kirchner-Bossi, Nicolas; Befort, Daniel J.; Wild, Simon B.; Ulbrich, Uwe; Leckebusch, Gregor C.

2016-04-01

Time-clustered winter storms are responsible for a majority of the wind-induced losses in Europe. Over last years, different atmospheric and oceanic large-scale mechanisms as the North Atlantic Oscillation (NAO) or the Meridional Overturning Circulation (MOC) have been proven to drive some significant portion of the windstorm variability over Europe. In this work we systematically investigate the influence of different large-scale natural variability modes: more than 20 indices related to those mechanisms with proven or potential influence on the windstorm frequency variability over Europe - mostly SST- or pressure-based - are derived by means of ECMWF ERA-20C reanalysis during the last century (1902-2009), and compared to the windstorm variability for the European winter (DJF). Windstorms are defined and tracked as in Leckebusch et al. (2008). The derived indices are then employed to develop a statistical procedure including a stepwise Multiple Linear Regression (MLR) and an Artificial Neural Network (ANN), aiming to hindcast the inter-annual (DJF) regional windstorm frequency variability in a case study for the British Isles. This case study reveals 13 indices with a statistically significant coupling with seasonal windstorm counts. The Scandinavian Pattern (SCA) showed the strongest correlation (0.61), followed by the NAO (0.48) and the Polar/Eurasia Pattern (0.46). The obtained indices (standard-normalised) are selected as predictors for a windstorm variability hindcast model applied for the British Isles. First, a stepwise linear regression is performed, to identify which mechanisms can explain windstorm variability best. Finally, the indices retained by the stepwise regression are used to develop a multlayer perceptron-based ANN that hindcasted seasonal windstorm frequency and clustering. Eight indices (SCA, NAO, EA, PDO, W.NAtl.SST, AMO (unsmoothed), EA/WR and Trop.N.Atl SST) are retained by the stepwise regression. Among them, SCA showed the highest linear coefficient, followed by SST in western Atlantic, AMO and NAO. The explanatory regression model (considering all time steps) provided a Coefficient of Determination (R^2) of 0.75. A predictive version of the linear model applying a leave-one-out cross-validation (LOOCV) shows an R2 of 0.56 and a relative RMSE of 4.67 counts/season. An ANN-based nonlinear hindcast model for the seasonal windstorm frequency is developed with the aim to improve the stepwise hindcast ability and thus better predict a time-clustered season over the case study. A 7 node-hidden layer perceptron is set, and the LOOCV procedure reveals a R2 of 0.71. In comparison to the stepwise MLR the RMSE is reduced a 20%. This work shows that for the British Isles case study, most of the interannual variability can be explained by certain large-scale mechanisms, considering also nonlinear effects (ANN). This allows to discern a time-clustered season from a non-clustered one - a key issue for applications e.g., in the (re)insurance industry.

Assessment and prediction of short term hospital admissions: the case of Athens, Greece

NASA Astrophysics Data System (ADS)

Kassomenos, P.; Papaloukas, C.; Petrakis, M.; Karakitsios, S.

The contribution of air pollution on hospital admissions due to respiratory and heart diseases is a major issue in the health-environmental perspective. In the present study, an attempt was made to run down the relationships between air pollution levels and meteorological indexes, and corresponding hospital admissions in Athens, Greece. The available data referred to a period of eight years (1992-2000) including the daily number of hospital admissions due to respiratory and heart diseases, hourly mean concentrations of CO, NO 2, SO 2, O 3 and particulates in several monitoring stations, as well as, meteorological data (temperature, relative humidity, wind speed/direction). The relations among the above data were studied through widely used statistical techniques (multivariate stepwise analyses) and Artificial Neural Networks (ANNs). Both techniques revealed that elevated particulate concentrations are the dominant parameter related to hospital admissions (an increase of 10 μg m -3 leads to an increase of 10.2% in the number of admissions), followed by O 3 and the rest of the pollutants (CO, NO 2 and SO 2). Meteorological parameters also play a decisive role in the formation of air pollutant levels affecting public health. Consequently, increased/decreased daily hospital admissions are related to specific types of meteorological conditions that favor/do not favor the accumulation of pollutants in an urban complex. In general, the role of meteorological factors seems to be underestimated by stepwise analyses, while ANNs attribute to them a more important role. Comparison of the two models revealed that ANN adaptation in complicate environmental issues presents improved modeling results compared to a regression technique. Furthermore, the ANN technique provides a reliable model for the prediction of the daily hospital admissions based on air quality data and meteorological indices, undoubtedly useful for regulatory purposes.

Estimating extent of mortality associated with the Douglas-fir beetle in the Central and Northern Rockies

Treesearch

Jose F. Negron; Willis C. Schaupp; Kenneth E. Gibson; John Anhold; Dawn Hansen; Ralph Thier; Phil Mocettini

1999-01-01

Data collected from Douglas-fir stands infected by the Douglas-fir beetle in Wyoming, Montana, Idaho, and Utah, were used to develop models to estimate amount of mortality in terms of basal area killed. Models were built using stepwise linear regression and regression tree approaches. Linear regression models using initial Douglas-fir basal area were built for all...

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Structure of perceived handicap in middle-aged males with noise-induced hearing loss, with and without tinnitus.

PubMed

Hallberg, L R; Johnsson, T; Axelsson, A

1993-01-01

By using a modified stepwise regression analysis technique, the structure of self-perceived handicap and tinnitus annoyance in 89 males with noise-induced hearing loss was described. Handicap was related to three clusters of variables, reflecting individual, environmental, and socioeconomic aspects, and 60% of the variance in self-perceived handicap was explained by the representatives of these clusters: i.e. 'acceptance of hearing problems', 'social support related to tinnitus' and 'years of education'. Tinnitus had no impact of its own on self-perceived handicap and only a modest portion (36%) of the variance in tinnitus annoyance was explained by 'sleep disturbance' and 'auditory perceptual difficulties'.

Covariate Selection for Multilevel Models with Missing Data

PubMed Central

Marino, Miguel; Buxton, Orfeu M.; Li, Yi

2017-01-01

Missing covariate data hampers variable selection in multilevel regression settings. Current variable selection techniques for multiply-imputed data commonly address missingness in the predictors through list-wise deletion and stepwise-selection methods which are problematic. Moreover, most variable selection methods are developed for independent linear regression models and do not accommodate multilevel mixed effects regression models with incomplete covariate data. We develop a novel methodology that is able to perform covariate selection across multiply-imputed data for multilevel random effects models when missing data is present. Specifically, we propose to stack the multiply-imputed data sets from a multiple imputation procedure and to apply a group variable selection procedure through group lasso regularization to assess the overall impact of each predictor on the outcome across the imputed data sets. Simulations confirm the advantageous performance of the proposed method compared with the competing methods. We applied the method to reanalyze the Healthy Directions-Small Business cancer prevention study, which evaluated a behavioral intervention program targeting multiple risk-related behaviors in a working-class, multi-ethnic population. PMID:28239457

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.

PubMed

Binder, Harald; Porzelius, Christine; Schumacher, Martin

2011-03-01

Analysis of molecular data promises identification of biomarkers for improving prognostic models, thus potentially enabling better patient management. For identifying such biomarkers, risk prediction models can be employed that link high-dimensional molecular covariate data to a clinical endpoint. In low-dimensional settings, a multitude of statistical techniques already exists for building such models, e.g. allowing for variable selection or for quantifying the added value of a new biomarker. We provide an overview of techniques for regularized estimation that transfer this toward high-dimensional settings, with a focus on models for time-to-event endpoints. Techniques for incorporating specific covariate structure are discussed, as well as techniques for dealing with more complex endpoints. Employing gene expression data from patients with diffuse large B-cell lymphoma, some typical modeling issues from low-dimensional settings are illustrated in a high-dimensional application. First, the performance of classical stepwise regression is compared to stage-wise regression, as implemented by a component-wise likelihood-based boosting approach. A second issues arises, when artificially transforming the response into a binary variable. The effects of the resulting loss of efficiency and potential bias in a high-dimensional setting are illustrated, and a link to competing risks models is provided. Finally, we discuss conditions for adequately quantifying the added value of high-dimensional gene expression measurements, both at the stage of model fitting and when performing evaluation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative structure-activity relationship of the curcumin-related compounds using various regression methods

NASA Astrophysics Data System (ADS)

Khazaei, Ardeshir; Sarmasti, Negin; Seyf, Jaber Yousefi

2016-03-01

Quantitative structure activity relationship were used to study a series of curcumin-related compounds with inhibitory effect on prostate cancer PC-3 cells, pancreas cancer Panc-1 cells, and colon cancer HT-29 cells. Sphere exclusion method was used to split data set in two categories of train and test set. Multiple linear regression, principal component regression and partial least squares were used as the regression methods. In other hand, to investigate the effect of feature selection methods, stepwise, Genetic algorithm, and simulated annealing were used. In two cases (PC-3 cells and Panc-1 cells), the best models were generated by a combination of multiple linear regression and stepwise (PC-3 cells: r2 = 0.86, q2 = 0.82, pred_r2 = 0.93, and r2m (test) = 0.43, Panc-1 cells: r2 = 0.85, q2 = 0.80, pred_r2 = 0.71, and r2m (test) = 0.68). For the HT-29 cells, principal component regression with stepwise (r2 = 0.69, q2 = 0.62, pred_r2 = 0.54, and r2m (test) = 0.41) is the best method. The QSAR study reveals descriptors which have crucial role in the inhibitory property of curcumin-like compounds. 6ChainCount, T_C_C_1, and T_O_O_7 are the most important descriptors that have the greatest effect. With a specific end goal to design and optimization of novel efficient curcumin-related compounds it is useful to introduce heteroatoms such as nitrogen, oxygen, and sulfur atoms in the chemical structure (reduce the contribution of T_C_C_1 descriptor) and increase the contribution of 6ChainCount and T_O_O_7 descriptors. Models can be useful in the better design of some novel curcumin-related compounds that can be used in the treatment of prostate, pancreas, and colon cancers.

Influence of storage conditions on the stability of monomeric anthocyanins studied by reversed-phase high-performance liquid chromatography.

PubMed

Morais, Helena; Ramos, Cristina; Forgács, Esther; Cserháti, Tibor; Oliviera, José

2002-04-25

The effect of light, storage time and temperature on the decomposition rate of monomeric anthocyanin pigments extracted from skins of grape (Vitis vinifera var. Red globe) was determined by reversed-phase high-performance liquid chromatography (RP-HPLC). The impact of various storage conditions on the pigment stability was assessed by stepwise regression analysis. RP-HPLC separated well the five anthocyanins identified and proved the presence of other unidentified pigments at lower concentrations. Stepwise regression analysis confirmed that the overall decomposition rate of monomeric anthocyanins, peonidin-3-glucoside and malvidin-3-glucoside significantly depended on the time and temperature of storage, the effect of storage time being the most important. The presence or absence of light exerted a negligible impact on the decomposition rate.

Estimation of longitudinal stability and control derivatives for an icing research aircraft from flight data

NASA Technical Reports Server (NTRS)

Batterson, James G.; Omara, Thomas M.

1989-01-01

The results of applying a modified stepwise regression algorithm and a maximum likelihood algorithm to flight data from a twin-engine commuter-class icing research aircraft are presented. The results are in the form of body-axis stability and control derivatives related to the short-period, longitudinal motion of the aircraft. Data were analyzed for the baseline (uniced) and for the airplane with an artificial glaze ice shape attached to the leading edge of the horizontal tail. The results are discussed as to the accuracy of the derivative estimates and the difference between the derivative values found for the baseline and the iced airplane. Additional comparisons were made between the maximum likelihood results and the modified stepwise regression results with causes for any discrepancies postulated.

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

PubMed

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

1997-09-01

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

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Remote Sensing as a Landscape Epidemiologic Tool to Identify Villages at High Risk for Malaria Transmission

NASA Technical Reports Server (NTRS)

Beck, Louisa R.; Rodriquez, Mario H.; Dister, Sheri W.; Rodriquez, Americo D.; Rejmankova, Eliska; Ulloa, Armando; Meza, Rosa A.; Roberts, Donald R.; Paris, Jack F.; Spanner, Michael A.;

QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

PubMed Central

Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

2009-01-01

A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

Cytopathologic differential diagnosis of low-grade urothelial carcinoma and reactive urothelial proliferation in bladder washings: a logistic regression analysis.

PubMed

Cakir, Ebru; Kucuk, Ulku; Pala, Emel Ebru; Sezer, Ozlem; Ekin, Rahmi Gokhan; Cakmak, Ozgur

2017-05-01

Conventional cytomorphologic assessment is the first step to establish an accurate diagnosis in urinary cytology. In cytologic preparations, the separation of low-grade urothelial carcinoma (LGUC) from reactive urothelial proliferation (RUP) can be exceedingly difficult. The bladder washing cytologies of 32 LGUC and 29 RUP were reviewed. The cytologic slides were examined for the presence or absence of the 28 cytologic features. The cytologic criteria showing statistical significance in LGUC were increased numbers of monotonous single (non-umbrella) cells, three-dimensional cellular papillary clusters without fibrovascular cores, irregular bordered clusters, atypical single cells, irregular nuclear overlap, cytoplasmic homogeneity, increased N/C ratio, pleomorphism, nuclear border irregularity, nuclear eccentricity, elongated nuclei, and hyperchromasia (p ˂ 0.05), and the cytologic criteria showing statistical significance in RUP were inflammatory background, mixture of small and large urothelial cells, loose monolayer aggregates, and vacuolated cytoplasm (p ˂ 0.05). When these variables were subjected to a stepwise logistic regression analysis, four features were selected to distinguish LGUC from RUP: increased numbers of monotonous single (non-umbrella) cells, increased nuclear cytoplasmic ratio, hyperchromasia, and presence of small and large urothelial cells (p = 0.0001). By this logistic model of the 32 cases with proven LGUC, the stepwise logistic regression analysis correctly predicted 31 (96.9%) patients with this diagnosis, and of the 29 patients with RUP, the logistic model correctly predicted 26 (89.7%) patients as having this disease. There are several cytologic features to separate LGUC from RUP. Stepwise logistic regression analysis is a valuable tool for determining the most useful cytologic criteria to distinguish these entities. © 2017 APMIS. Published by John Wiley & Sons Ltd.

Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy.

PubMed

Talpur, M Younis; Kara, Huseyin; Sherazi, S T H; Ayyildiz, H Filiz; Topkafa, Mustafa; Arslan, Fatma Nur; Naz, Saba; Durmaz, Fatih; Sirajuddin

2014-11-01

Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

A robust and efficient stepwise regression method for building sparse polynomial chaos expansions

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

Abraham, Simon, E-mail: Simon.Abraham@ulb.ac.be; Raisee, Mehrdad; Ghorbaniasl, Ghader

2017-03-01

Polynomial Chaos (PC) expansions are widely used in various engineering fields for quantifying uncertainties arising from uncertain parameters. The computational cost of classical PC solution schemes is unaffordable as the number of deterministic simulations to be calculated grows dramatically with the number of stochastic dimension. This considerably restricts the practical use of PC at the industrial level. A common approach to address such problems is to make use of sparse PC expansions. This paper presents a non-intrusive regression-based method for building sparse PC expansions. The most important PC contributions are detected sequentially through an automatic search procedure. The variable selectionmore » criterion is based on efficient tools relevant to probabilistic method. Two benchmark analytical functions are used to validate the proposed algorithm. The computational efficiency of the method is then illustrated by a more realistic CFD application, consisting of the non-deterministic flow around a transonic airfoil subject to geometrical uncertainties. To assess the performance of the developed methodology, a detailed comparison is made with the well established LAR-based selection technique. The results show that the developed sparse regression technique is able to identify the most significant PC contributions describing the problem. Moreover, the most important stochastic features are captured at a reduced computational cost compared to the LAR method. The results also demonstrate the superior robustness of the method by repeating the analyses using random experimental designs.« less

Reduction of time-resolved space-based CCD photometry developed for MOST Fabry Imaging data*

NASA Astrophysics Data System (ADS)

Reegen, P.; Kallinger, T.; Frast, D.; Gruberbauer, M.; Huber, D.; Matthews, J. M.; Punz, D.; Schraml, S.; Weiss, W. W.; Kuschnig, R.; Moffat, A. F. J.; Walker, G. A. H.; Guenther, D. B.; Rucinski, S. M.; Sasselov, D.

2006-04-01

The MOST (Microvariability and Oscillations of Stars) satellite obtains ultraprecise photometry from space with high sampling rates and duty cycles. Astronomical photometry or imaging missions in low Earth orbits, like MOST, are especially sensitive to scattered light from Earthshine, and all these missions have a common need to extract target information from voluminous data cubes. They consist of upwards of hundreds of thousands of two-dimensional CCD frames (or subrasters) containing from hundreds to millions of pixels each, where the target information, superposed on background and instrumental effects, is contained only in a subset of pixels (Fabry Images, defocused images, mini-spectra). We describe a novel reduction technique for such data cubes: resolving linear correlations of target and background pixel intensities. This step-wise multiple linear regression removes only those target variations which are also detected in the background. The advantage of regression analysis versus background subtraction is the appropriate scaling, taking into account that the amount of contamination may differ from pixel to pixel. The multivariate solution for all pairs of target/background pixels is minimally invasive of the raw photometry while being very effective in reducing contamination due to, e.g. stray light. The technique is tested and demonstrated with both simulated oscillation signals and real MOST photometry.

Using foreground/background analysis to determine leaf and canopy chemistry

NASA Technical Reports Server (NTRS)

Pinzon, J. E.; Ustin, S. L.; Hart, Q. J.; Jacquemoud, S.; Smith, M. O.

1995-01-01

Spectral Mixture Analysis (SMA) has become a well established procedure for analyzing imaging spectrometry data, however, the technique is relatively insensitive to minor sources of spectral variation (e.g., discriminating stressed from unstressed vegetation and variations in canopy chemistry). Other statistical approaches have been tried e.g., stepwise multiple linear regression analysis to predict canopy chemistry. Grossman et al. reported that SMLR is sensitive to measurement error and that the prediction of minor chemical components are not independent of patterns observed in more dominant spectral components like water. Further, they observed that the relationships were strongly dependent on the mode of expressing reflectance (R, -log R) and whether chemistry was expressed on a weight (g/g) or are basis (g/sq m). Thus, alternative multivariate techniques need to be examined. Smith et al. reported a revised SMA that they termed Foreground/Background Analysis (FBA) that permits directing the analysis along any axis of variance by identifying vectors through the n-dimensional spectral volume orthonormal to each other. Here, we report an application of the FBA technique for the detection of canopy chemistry using a modified form of the analysis.

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

PubMed

Ross, Elsie Gyang; Shah, Nigam H; Dalman, Ronald L; Nead, Kevin T; Cooke, John P; Leeper, Nicholas J

2016-11-01

A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aims of this study were to develop machine learning algorithms for the identification of disease and the prognostication of mortality risk and to determine whether such models perform better than classical statistical analyses. Focusing on peripheral artery disease (PAD), patient data were derived from a prospective, observational study of 1755 patients who presented for elective coronary angiography. We employed multiple supervised machine learning algorithms and used diverse clinical, demographic, imaging, and genomic information in a hypothesis-free manner to build models that could identify patients with PAD and predict future mortality. Comparison was made to standard stepwise linear regression models. Our machine-learned models outperformed stepwise logistic regression models both for the identification of patients with PAD (area under the curve, 0.87 vs 0.76, respectively; P = .03) and for the prediction of future mortality (area under the curve, 0.76 vs 0.65, respectively; P = .10). Both machine-learned models were markedly better calibrated than the stepwise logistic regression models, thus providing more accurate disease and mortality risk estimates. Machine learning approaches can produce more accurate disease classification and prediction models. These tools may prove clinically useful for the automated identification of patients with highly morbid diseases for which aggressive risk factor management can improve outcomes. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Identification of International Classification of Functioning, Disability and Health categories for patients with peripheral arterial disease.

PubMed

Vyskocil, Erich; Gruther, Wolfgang; Steiner, Irene; Schuhfried, Othmar

2014-07-01

Disease-specific categories of the International Classification of Functioning, Disability and Health have not yet been described for patients with chronic peripheral arterial obstructive disease (PAD). The authors examined the relationship between the categories of the Brief Core Sets for ischemic heart diseases with the Peripheral Artery Questionnaire and the ankle-brachial index to determine which International Classification of Functioning, Disability and Health categories are most relevant for patients with PAD. This is a retrospective cohort study including 77 patients with verified PAD. Statistical analyses of the relationship between International Classification of Functioning, Disability and Health categories as independent variables and the endpoints Peripheral Artery Questionnaire or ankle-brachial index were carried out by simple and stepwise linear regression models adjusting for age, sex, and leg (left vs. right). The stepwise linear regression model with the ankle-brachial index as dependent variable revealed a significant effect of the variables blood vessel functions and muscle endurance functions. Calculating a stepwise linear regression model with the Peripheral Artery Questionnaire as dependent variable, a significant effect of age, emotional functions, energy and drive functions, carrying out daily routine, as well as walking could be observed. This study identifies International Classification of Functioning, Disability and Health categories in the Brief Core Sets for ischemic heart diseases that show a significant effect on the ankle-brachial index and the Peripheral Artery Questionnaire score in patients with PAD. These categories provide fundamental information on functioning of patients with PAD and patient-centered outcomes for rehabilitation interventions.

Clinical utility of the AlphaFIM® instrument in stroke rehabilitation.

PubMed

Lo, Alexander; Tahair, Nicola; Sharp, Shelley; Bayley, Mark T

2012-02-01

The AlphaFIM instrument is an assessment tool designed to facilitate discharge planning of stroke patients from acute care, by extrapolating overall functional status from performance in six key Functional Independence Measure (FIM) instrument items. To determine whether acute care AlphaFIM rating is correlated to stroke rehabilitation outcomes. In this prospective observational study, data were analyzed from 891 patients referred for inpatient stroke rehabilitation through an Internet-based referral system. Simple linear and stepwise regression models determined correlations between rehabilitation-ready AlphaFIM rating and rehabilitation outcomes (admission and discharge FIM ratings, FIM gain, FIM efficiency, and length of stay). Covariates including demographic data, stroke characteristics, medical history, cognitive deficits, and activity tolerance were included in the stepwise regressions. The AlphaFIM instrument was significant in predicting admission and discharge FIM ratings at rehabilitation (adjusted R² 0.40 and 0.28, respectively; P < 0.0001) and was weakly correlated with FIM gain and length of stay (adjusted R² 0.04 and 0.09, respectively; P < 0.0001), but not FIM efficiency. AlphaFIM rating was inversely related to FIM gain. Age, bowel incontinence, left hemiparesis, and previous infarcts were negative predictors of discharge FIM rating on stepwise regression. Intact executive function and physical activity tolerance of 30 to 60 mins were predictors of FIM gain. The AlphaFIM instrument is a valuable tool for triaging stroke patients from acute care to rehabilitation and predicts functional status at discharge from rehabilitation. Patients with low AlphaFIM ratings have the potential to make significant functional gains and should not be denied admission to inpatient rehabilitation programs.

Development of a food frequency questionnaire for Sri Lankan adults

PubMed Central

2012-01-01

Background Food Frequency Questionnaires (FFQs) are commonly used in epidemiologic studies to assess long-term nutritional exposure. Because of wide variations in dietary habits in different countries, a FFQ must be developed to suit the specific population. Sri Lanka is undergoing nutritional transition and diet-related chronic diseases are emerging as an important health problem. Currently, no FFQ has been developed for Sri Lankan adults. In this study, we developed a FFQ to assess the regular dietary intake of Sri Lankan adults. Methods A nationally representative sample of 600 adults was selected by a multi-stage random cluster sampling technique and dietary intake was assessed by random 24-h dietary recall. Nutrient analysis of the FFQ required the selection of foods, development of recipes and application of these to cooked foods to develop a nutrient database. We constructed a comprehensive food list with the units of measurement. A stepwise regression method was used to identify foods contributing to a cumulative 90% of variance to total energy and macronutrients. In addition, a series of photographs were included. Results We obtained dietary data from 482 participants and 312 different food items were recorded. Nutritionists grouped similar food items which resulted in a total of 178 items. After performing step-wise multiple regression, 93 foods explained 90% of the variance for total energy intake, carbohydrates, protein, total fat and dietary fibre. Finally, 90 food items and 12 photographs were selected. Conclusion We developed a FFQ and the related nutrient composition database for Sri Lankan adults. Culturally specific dietary tools are central to capturing the role of diet in risk for chronic disease in Sri Lanka. The next step will involve the verification of FFQ reproducibility and validity. PMID:22937734

Traditional Admissions Variables as Predictors of Minority Students' Performance in Medical School — A Cause for Concern

PubMed Central

Johnson, Henry C.; Rosevear, G. Craig

1977-01-01

This study explored the relationship between traditional admissions criteria, performance in the first semester of medical school, and performance on the National Board of Medical Examiners' (NBME) Examination, Part 1 for minority medical students, non-minority medical students, and the two groups combined. Correlational analysis and step-wise multiple regression procedures were used as the analysis techniques. A different pattern of admissions variables related to National Board Part 1 performance for the two groups. The General Information section of the Medical College Admission Test (MCAT) contributed the most variance for the minority student group. MCAT-Science contributed the most variance for the non-minority student group. MCATs accounted for a substantial portion of the variance on the National Board examination. PMID:904005

Effects of wing modification on an aircraft's aerodynamic parameters as determined from flight data

NASA Technical Reports Server (NTRS)

Hess, R. A.

1986-01-01

A study of the effects of four wing-leading-edge modifications on a general aviation aircraft's stability and control parameters is presented. Flight data from the basic aircraft configuration and configurations with wing modifications are analyzed to determine each wing geometry's stability and control parameters. The parameter estimates and aerodynamic model forms are obtained using the stepwise regression and maximum likelihood techniques. The resulting parameter estimates and aerodynamic models are verified using vortex-lattice theory and by analysis of each model's ability to predict aircraft behavior. Comparisons of the stability and control derivative estimates from the basic wing and the four leading-edge modifications are accomplished so that the effects of each modification on aircraft stability and control derivatives can be determined.

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

PubMed Central

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site. PMID:29370230

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation.

PubMed

Illias, Hazlee Azil; Zhao Liang, Wee

2018-01-01

Early detection of power transformer fault is important because it can reduce the maintenance cost of the transformer and it can ensure continuous electricity supply in power systems. Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. The superiority of the modified PSO technique with SVM was evaluated by comparing the results with the actual fault diagnosis, unoptimised SVM and previous reported works. Data reduction was also applied using stepwise regression prior to the training process of SVM to reduce the training time. It was found that the proposed hybrid SVM-Modified EPSO (MEPSO)-Time Varying Acceleration Coefficient (TVAC) technique results in the highest correct identification percentage of faults in a power transformer compared to other PSO algorithms. Thus, the proposed technique can be one of the potential solutions to identify the transformer fault type based on DGA data on site.

CORRELATION PURSUIT: FORWARD STEPWISE VARIABLE SELECTION FOR INDEX MODELS

PubMed Central

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

2012-01-01

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

Synoptic and meteorological drivers of extreme ozone concentrations over Europe

NASA Astrophysics Data System (ADS)

Otero, Noelia Felipe; Sillmann, Jana; Schnell, Jordan L.; Rust, Henning W.; Butler, Tim

2016-04-01

The present work assesses the relationship between local and synoptic meteorological conditions and surface ozone concentration over Europe in spring and summer months, during the period 1998-2012 using a new interpolated data set of observed surface ozone concentrations over the European domain. Along with local meteorological conditions, the influence of large-scale atmospheric circulation on surface ozone is addressed through a set of airflow indices computed with a novel implementation of a grid-by-grid weather type classification across Europe. Drivers of surface ozone over the full distribution of maximum daily 8-hour average values are investigated, along with drivers of the extreme high percentiles and exceedances or air quality guideline thresholds. Three different regression techniques are applied: multiple linear regression to assess the drivers of maximum daily ozone, logistic regression to assess the probability of threshold exceedances and quantile regression to estimate the meteorological influence on extreme values, as represented by the 95th percentile. The relative importance of the input parameters (predictors) is assessed by a backward stepwise regression procedure that allows the identification of the most important predictors in each model. Spatial patterns of model performance exhibit distinct variations between regions. The inclusion of the ozone persistence is particularly relevant over Southern Europe. In general, the best model performance is found over Central Europe, where the maximum temperature plays an important role as a driver of maximum daily ozone as well as its extreme values, especially during warmer months.

A regression-kriging model for estimation of rainfall in the Laohahe basin

NASA Astrophysics Data System (ADS)

Wang, Hong; Ren, Li L.; Liu, Gao H.

2009-10-01

This paper presents a multivariate geostatistical algorithm called regression-kriging (RK) for predicting the spatial distribution of rainfall by incorporating five topographic/geographic factors of latitude, longitude, altitude, slope and aspect. The technique is illustrated using rainfall data collected at 52 rain gauges from the Laohahe basis in northeast China during 1986-2005 . Rainfall data from 44 stations were selected for modeling and the remaining 8 stations were used for model validation. To eliminate multicollinearity, the five explanatory factors were first transformed using factor analysis with three Principal Components (PCs) extracted. The rainfall data were then fitted using step-wise regression and residuals interpolated using SK. The regression coefficients were estimated by generalized least squares (GLS), which takes the spatial heteroskedasticity between rainfall and PCs into account. Finally, the rainfall prediction based on RK was compared with that predicted from ordinary kriging (OK) and ordinary least squares (OLS) multiple regression (MR). For correlated topographic factors are taken into account, RK improves the efficiency of predictions. RK achieved a lower relative root mean square error (RMSE) (44.67%) than MR (49.23%) and OK (73.60%) and a lower bias than MR and OK (23.82 versus 30.89 and 32.15 mm) for annual rainfall. It is much more effective for the wet season than for the dry season. RK is suitable for estimation of rainfall in areas where there are no stations nearby and where topography has a major influence on rainfall.

Use of a pretest strategy for physical therapist assistant programs to predict success rate on the national physical therapy exam.

PubMed

Sloas, Stacey B; Keith, Becky; Whitehead, Malcolm T

2013-01-01

This study investigated a pretest strategy that identified physical therapist assistant (PTA) students who were at risk of failure on the National Physical Therapy Examination (NPTE). Program assessment data from five cohorts of PTA students (2005-2009) were used to develop a stepwise multiple regression formula that predicted first-time NPTE licensure scores. Data used included the Nelson-Denny Reading Test, grades from eight core courses, grade point average upon admission to the program, and scores from three mock NPTE exams given during the program. Pearson correlation coefficients were calculated between each of the 15 variables and NPTE scores. Stepwise multiple regression analysis was performed using data collected at the ends of the first, second, and third (final) semesters of the program. Data from the class of 2010 were then used to validate the formula. The end-of-program formula accounted for the greatest variance (57%) in predicted scores. Those students scoring below a predicted scaled score of 620 were identified to be at risk of failure of the licensure exam. These students were counseled, and a remedial plan was developed based on regression predictions prior to them sitting for the licensure exam.

Greater association of peak neuromuscular performance with cortical bone geometry, bone mass and bone strength than bone density: A study in 417 older women.

PubMed

Belavý, Daniel L; Armbrecht, Gabriele; Blenk, Tilo; Bock, Oliver; Börst, Hendrikje; Kocakaya, Emine; Luhn, Franziska; Rantalainen, Timo; Rawer, Rainer; Tomasius, Frederike; Willnecker, Johannes; Felsenberg, Dieter

2016-02-01

We evaluated which aspects of neuromuscular performance are associated with bone mass, density, strength and geometry. 417 women aged 60-94years were examined. Countermovement jump, sit-to-stand test, grip strength, forearm and calf muscle cross-sectional area, areal bone mineral content and density (aBMC and aBMD) at the hip and lumbar spine via dual X-ray absorptiometry, and measures of volumetric vBMC and vBMD, bone geometry and section modulus at 4% and 66% of radius length and 4%, 38% and 66% of tibia length via peripheral quantitative computed tomography were performed. The first principal component of the neuromuscular variables was calculated to generate a summary neuromuscular variable. Percentage of total variance in bone parameters explained by the neuromuscular parameters was calculated. Step-wise regression was also performed. At all pQCT bone sites (radius, ulna, tibia, fibula), a greater percentage of total variance in measures of bone mass, cortical geometry and/or bone strength was explained by peak neuromuscular performance than for vBMD. Sit-to-stand performance did not relate strongly to bone parameters. No obvious differential in the explanatory power of neuromuscular performance was seen for DXA aBMC versus aBMD. In step-wise regression, bone mass, cortical morphology, and/or strength remained significant in relation to the first principal component of the neuromuscular variables. In no case was vBMD positively related to neuromuscular performance in the final step-wise regression models. Peak neuromuscular performance has a stronger relationship with leg and forearm bone mass and cortical geometry as well as proximal forearm section modulus than with vBMD. Copyright © 2015 Elsevier Inc. All rights reserved.

Prevalence of consistent condom use with various types of sex partners and associated factors among money boys in Changsha, China.

PubMed

Wang, Lian-Hong; Yan, Jin; Yang, Guo-Li; Long, Shuo; Yu, Yong; Wu, Xi-Lin

2015-04-01

Money boys with inconsistent condom use (less than 100% of the time) are at high risk of infection by human immunodeficiency virus (HIV) or sexually transmitted infection (STI), but relatively little research has examined their risk behaviors. We investigated the prevalence of consistent condom use (100% of the time) and associated factors among money boys. A cross-sectional study using a structured questionnaire was conducted among money boys in Changsha, China, between July 2012 and January 2013. Independent variables included socio-demographic data, substance abuse history, work characteristics, and self-reported HIV and STI history. Dependent variables included the consistent condom use with different types of sex partners. Among the participants, 82.4% used condoms consistently with male clients, 80.2% with male sex partners, and 77.1% with female sex partners in the past 3 months. A multiple stepwise logistic regression model identified four statistically significant factors associated with lower likelihoods of consistent condom use with male clients: age group, substance abuse, lack of an "employment" arrangement, and having no HIV test within the prior 6 months. In a similar model, only one factor associated significantly with lower likelihoods of consistent condom use with male sex partners was identified in multiple stepwise logistic regression analyses: having no HIV test within the prior six months. As for female sex partners, two significant variables were statistically significant in the multiple stepwise logistic regression analysis: having no HIV test within the prior 6 months and having STI history. Interventions which are linked with more realistic and acceptable HIV prevention methods are greatly warranted and should increase risk awareness and the behavior of consistent condom use in both commercial and personal relationship. © 2015 International Society for Sexual Medicine.

A model for predicting sulcus-to-sulcus diameter in posterior chamber phakic intraocular lens candidates: correlation between ocular biometric parameters.

PubMed

Ghoreishi, Mohammad; Abdi-Shahshahani, Mehdi; Peyman, Alireza; Pourazizi, Mohsen

2018-02-21

The aim of this study was to determine the correlation between ocular biometric parameters and sulcus-to-sulcus (STS) diameter. This was a cross-sectional study of preoperative ocular biometry data of patients who were candidates for phakic intraocular lens (IOL) surgery. Subjects underwent ocular biometry analysis, including refraction error evaluation using an autorefractor and Orbscan topography for white-to-white (WTW) corneal diameter and measurement. Pentacam was used to perform WTW corneal diameter and measurements of minimum and maximum keratometry (K). Measurements of STS and angle-to-angle (ATA) were obtained using a 50-MHz B-mode ultrasound device. Anterior optical coherence tomography was performed for anterior chamber depth measurement. Pearson's correlation test and stepwise linear regression analysis were used to find a model to predict STS. Fifty-eight eyes of 58 patients were enrolled. Mean age ± standard deviation of sample was 28.95 ± 6.04 years. The Pearson's correlation coefficient between STS with WTW, ATA, mean K was 0.383, 0.492, and - 0.353, respectively, which was statistically significant (all P < 0.001). Using stepwise linear regression analysis, there is a statistically significant association between STS with WTW (P = 0.011) and mean K (P = 0.025). The standardized coefficient was 0.323 and - 0.284 for WTW and mean K, respectively. The stepwise linear regression analysis equation was: (STS = 9.549 + 0.518 WTW - 0.083 mean K). Based on our result, given the correlation of STS with WTW and mean K and potential of direct and essay measurement of WTW and mean K, it seems that current IOL sizing protocols could be estimating with WTW and mean K.

Aerobic Fitness Does Not Contribute to Prediction of Orthostatic Intolerance

NASA Technical Reports Server (NTRS)

Convertino, Victor A.; Sather, Tom M.; Goldwater, Danielle J.; Alford, William R.

1986-01-01

Several investigations have suggested that orthostatic tolerance may be inversely related to aerobic fitness (VO (sub 2max)). To test this hypothesis, 18 males (age 29 to 51 yr) underwent both treadmill VO(sub 2max) determination and graded lower body negative pressures (LBNP) exposure to tolerance. VO(2max) was measured during the last minute of a Bruce treadmill protocol. LBNP was terminated based on pre-syncopal symptoms and LBNP tolerance (peak LBNP) was expressed as the cumulative product of LBNP and time (torr-min). Changes in heart rate, stroke volume cardiac output, blood pressure and impedance rheographic indices of mid-thigh-leg initial accumulation were measured at rest and during the final minute of LBNP. For all 18 subjects, mean (plus or minus SE) fluid accumulation index and leg venous compliance index at peak LBNP were 139 plus or minus 3.9 plus or minus 0.4 ml-torr-min(exp -2) x 10(exp 3), respectively. Pearson product-moment correlations and step-wise linear regression were used to investigate relationships with peak LBNP. Variables associated with endurance training, such as VO(sub 2max) and percent body fat were not found to correlate significantly (P is less than 0.05) with peak LBNP and did not add sufficiently to the prediction of peak LBNP to be included in the step-wise regression model. The step-wise regression model included only fluid accumulation index leg venous compliance index, and blood volume and resulted in a squared multiple correlation coefficient of 0.978. These data do not support the hypothesis that orthostatic tolerance as measured by LBNP is lower in individuals with high aerobic fitness.

Integrative Bayesian variable selection with gene-based informative priors for genome-wide association studies.

PubMed

Zhang, Xiaoshuai; Xue, Fuzhong; Liu, Hong; Zhu, Dianwen; Peng, Bin; Wiemels, Joseph L; Yang, Xiaowei

2014-12-10

Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases. To solve this "missing heritability" problem, we implemented a strategy called integrative Bayesian Variable Selection (iBVS), which is based on a hierarchical model that incorporates an informative prior by considering the gene interrelationship as a network. It was applied here to both simulated and real data sets. Simulation studies indicated that the iBVS method was advantageous in its performance with highest AUC in both variable selection and outcome prediction, when compared to Stepwise and LASSO based strategies. In an analysis of a leprosy case-control study, iBVS selected 94 SNPs as predictors, while LASSO selected 100 SNPs. The Stepwise regression yielded a more parsimonious model with only 3 SNPs. The prediction results demonstrated that the iBVS method had comparable performance with that of LASSO, but better than Stepwise strategies. The proposed iBVS strategy is a novel and valid method for Genome-wide Association Studies, with the additional advantage in that it produces more interpretable posterior probabilities for each variable unlike LASSO and other penalized regression methods.

Reference value of impulse oscillometry in taiwanese preschool children.

PubMed

Lai, Shen-Hao; Yao, Tsung-Chieh; Liao, Sui-Ling; Tsai, Ming-Han; Hua, Men-Chin; Yeh, Kuo-Wei; Huang, Jing-Long

2015-06-01

Impulse oscillometry is a potential technique for assessing the respiratory mechanism-which includes airway resistance and reactance during tidal breathing-in minimally cooperative young children. The reference values available in Asian preschool children are limited, especially in children of Chinese ethnicity. This study aimed to develop reference equations for lung function measurements using impulse oscillometry in Taiwanese children for future clinical application and research exploitation. Impulse oscillometry was performed in 150 healthy Taiwanese children (aged 2-6 years) to measure airway resistance and reactance at various frequencies. We used regression analysis to generate predictive equations separately by age, body height, body weight, and gender. The stepwise regression model revealed that body height was the most significant determinant of airway resistance and reactance in preschool young children. With the growth in height, a decrease in airway resistance and a paradoxical increase in reactance occurred at different frequencies. The regression curve of resistance at 5 Hz was comparable to previous reference values. This study provided reference values for several variables of the impulse oscillometry measurements in healthy Taiwanese children aged 2-6 years. With these reference data, clinical application of impulse oscillometry would be expedient in diagnosing respiratory diseases in preschool children. Copyright © 2014. Published by Elsevier B.V.

Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-04-29

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm(-1)) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice. Copyright © 2011 Elsevier B.V. All rights reserved.

Simple models for estimating local removals of timber in the northeast

Treesearch

David N. Larsen; David A. Gansner

1975-01-01

Provides a practical method of estimating subregional removals of timber and demonstrates its application to a typical problem. Stepwise multiple regression analysis is used to develop equations for estimating removals of softwood, hardwood, and all timber from selected characteristics of socioeconomic structure.

Predicting pork loin intramuscular fat using computer vision system.

PubMed

Liu, J-H; Sun, X; Young, J M; Bachmeier, L A; Newman, D J

2018-09-01

The objective of this study was to investigate the ability of computer vision system to predict pork intramuscular fat percentage (IMF%). Center-cut loin samples (n = 85) were trimmed of subcutaneous fat and connective tissue. Images were acquired and pixels were segregated to estimate image IMF% and 18 image color features for each image. Subjective IMF% was determined by a trained grader. Ether extract IMF% was calculated using ether extract method. Image color features and image IMF% were used as predictors for stepwise regression and support vector machine models. Results showed that subjective IMF% had a correlation of 0.81 with ether extract IMF% while the image IMF% had a 0.66 correlation with ether extract IMF%. Accuracy rates for regression models were 0.63 for stepwise and 0.75 for support vector machine. Although subjective IMF% has shown to have better prediction, results from computer vision system demonstrates the potential of being used as a tool in predicting pork IMF% in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Relationships between presenteeism and work-related musculoskeletal disorders among physical therapists in the Republic of Korea.

PubMed

Bae, Young-Hyeon

2017-12-14

This study investigated the relationship between presenteeism and work-related musculoskeletal disorders (WMSDs) among physical therapists (PTs) in the Republic of Korea. Questionnaires were given to 600 PTs in the Republic of Korea. General and occupational characteristics and the prevalence of presenteeism and absenteeism were self-reported on the questionnaire. Stepwise regression analyses were used to evaluate the effects of presenteeism and other variables on general and occupational characteristics. Of the 490 PTs who responded, 399 (81.4%) reported at least one WMSD. There was a low incidence rate of absenteeism, but work impairment scores indicate there was a high incidence of presenteeism. In the stepwise regression analyses, the incidence of WMSDs was highest in cases of presenteeism. The results of this study demonstrate that there is a high incidence rate of WMSDs in Republic of Korean PTs, that WMSDs are related to presenteeism and that PTs demonstrate high presenteeism and low absenteeism.

Maternal dietary intake and pregnancy outcome.

PubMed

Ferland, Suzanne; O'Brien, Huguette Turgeon

2003-02-01

To study the relationship between maternal diet and infant anthropometric measurements in 56 women, aged 28 +/- 5.1 years, with singleton pregnancies. The overall quality of the diet (three 24-hour recalls), including supplementation, was evaluated at 34 +/- 1.3 weeks using a total mean adequacy ratio (TMAR) of 12 nutrients. Specific interviewing techniques were used to minimize social desirability bias. Anthropometric measurements of both parents and maternal lifestyle practices were also obtained. Infant weight, crown-heel length and head circumference were measured 14.6 +/- 4.4 days after birth. Stepwise multiple regression analysis revealed that maternal diet quality (TMAR) was significantly related to infant weight (r = .039, P = .036) and crown-heel length (r = .071, P = .007). Other significant predictors included gestational age, maternal height, sex, smoking and physical activity. Maternal diet was positively associated with infant weight and crown-heel length.

Application of LANDSAT to the Surveillance and Control of Eutrophication in Saginaw Bay

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator)

1975-01-01

The author has identified the following significant results. LANDSAT digital data and ground truth measurements for Saginaw Bay (Lake Huron), Michigan, for 3 June 1974 can be correlated by stepwise linear regression technique and the resulting equations used to estimate invisible water quality parameters in nonsampled areas. Correlation of these parameters with each other indicates that the transport of Saginaw River water can now be traced by a number of water quality features, one or more of which are directly detected by LANDSAT. Five of the 12 water quality parameters are best correlated with LANDSAT band 6 measurements alone. One parameter (temperature) relates to band 5 alone and the remaining six may be predicted with varying degrees of accuracy from a combination of two bands (first band 6 and generally band 4 second).

Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores.

PubMed

Roy, Banibrata; Ripstein, Ira; Perry, Kyle; Cohen, Barry

2016-01-01

To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores. Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson's correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed. Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT. Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

Optimizing separate phase light hydrocarbon recovery from contaminated unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

A modeling approach is presented that optimizes separate phase recovery of light non-aqueous phase liquids (LNAPL) for a single dual-extraction well in a homogeneous, isotropic unconfined aquifer. A simulation/regression/optimization (S/R/O) model is developed to predict, analyze, and optimize the oil recovery process. The approach combines detailed simulation, nonlinear regression, and optimization. The S/R/O model utilizes nonlinear regression equations describing system response to time-varying water pumping and oil skimming. Regression equations are developed for residual oil volume and free oil volume. The S/R/O model determines optimized time-varying (stepwise) pumping rates which minimize residual oil volume and maximize free oil recovery while causing free oil volume to decrease a specified amount. This S/R/O modeling approach implicitly immobilizes the free product plume by reversing the water table gradient while achieving containment. Application to a simple representative problem illustrates the S/R/O model utility for problem analysis and remediation design. When compared with the best steady pumping strategies, the optimal stepwise pumping strategy improves free oil recovery by 11.5% and reduces the amount of residual oil left in the system due to pumping by 15%. The S/R/O model approach offers promise for enhancing the design of free phase LNAPL recovery systems and to help in making cost-effective operation and management decisions for hydrogeologists, engineers, and regulators.

Stepwise Iterative Fourier Transform: The SIFT

NASA Technical Reports Server (NTRS)

Benignus, V. A.; Benignus, G.

1975-01-01

A program, designed specifically to study the respective effects of some common data problems on results obtained through stepwise iterative Fourier transformation of synthetic data with known waveform composition, was outlined. Included in this group were the problems of gaps in the data, different time-series lengths, periodic but nonsinusoidal waveforms, and noisy (low signal-to-noise) data. Results on sinusoidal data were also compared with results obtained on narrow band noise with similar characteristics. The findings showed that the analytic procedure under study can reliably reduce data in the nature of (1) sinusoids in noise, (2) asymmetric but periodic waves in noise, and (3) sinusoids in noise with substantial gaps in the data. The program was also able to analyze narrow-band noise well, but with increased interpretational problems. The procedure was shown to be a powerful technique for analysis of periodicities, in comparison with classical spectrum analysis techniques. However, informed use of the stepwise procedure nevertheless requires some background of knowledge concerning characteristics of the biological processes under study.

Depression and Related Problems in University Students

ERIC Educational Resources Information Center

Field, Tiffany; Diego, Miguel; Pelaez, Martha; Deeds, Osvelia; Delgado, Jeannette

2012-01-01

Method: Depression and related problems were studied in a sample of 283 university students. Results: The students with high depression scores also had high scores on anxiety, intrusive thoughts, controlling intrusive thoughts and sleep disturbances scales. A stepwise regression suggested that those problems contributed to a significant proportion…

DEVELOPMENT OF RESIDENTIAL WOOD COMSUMPTION ESTIMATION MODELS

EPA Science Inventory

The report gives data on the distribution and usage of firewood, obtained from a pool of household wood use surveys. ased on a series of regression models developed using the STEPWISE procedure in the SAS statistical package, two variables appear to be most predictive of wood use...

An empirical study using permutation-based resampling in meta-regression

PubMed Central

2012-01-01

Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815

Stepwise introduction of laparoscopic liver surgery: validation of guideline recommendations.

PubMed

van der Poel, Marcel J; Huisman, Floor; Busch, Olivier R; Abu Hilal, Mohammad; van Gulik, Thomas M; Tanis, Pieter J; Besselink, Marc G

2017-10-01

Uncontrolled introduction of laparoscopic liver surgery (LLS) could compromise postoperative outcomes. A stepwise introduction of LLS combined with structured training is advised. This study aimed to evaluate the impact of such a stepwise introduction. A retrospective, single-center case series assessing short term outcomes of all consecutive LLS in the period November 2006-January 2017. The technique was implemented in a stepwise fashion. To evaluate the impact of this stepwise approach combined with structured training, outcomes of LLS before and after a laparoscopic HPB fellowship were compared. A total of 135 laparoscopic resections were performed. Overall conversion rate was 4% (n = 5), clinically relevant complication rate 13% (n = 18) and mortality 0.7% (n = 1). A significant increase in patients with major LLS, multiple liver resections, previous abdominal surgery, malignancies and lesions located in posterior segments was observed after the fellowship as well as a decrease in the use of hand-assistance. Increasing complexity in the post fellowship period was reflected by an increase in operating times, but without comprising other surgical outcomes. A stepwise introduction of LLS combined with structured training reduced the clinical impact of the learning curve, thereby confirming guideline recommendations. Copyright © 2017 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

Prediction of troponin-T degradation using color image texture features in 10d aged beef longissimus steaks.

PubMed

Sun, X; Chen, K J; Berg, E P; Newman, D J; Schwartz, C A; Keller, W L; Maddock Carlin, K R

2014-02-01

The objective was to use digital color image texture features to predict troponin-T degradation in beef. Image texture features, including 88 gray level co-occurrence texture features, 81 two-dimension fast Fourier transformation texture features, and 48 Gabor wavelet filter texture features, were extracted from color images of beef strip steaks (longissimus dorsi, n = 102) aged for 10d obtained using a digital camera and additional lighting. Steaks were designated degraded or not-degraded based on troponin-T degradation determined on d 3 and d 10 postmortem by immunoblotting. Statistical analysis (STEPWISE regression model) and artificial neural network (support vector machine model, SVM) methods were designed to classify protein degradation. The d 3 and d 10 STEPWISE models were 94% and 86% accurate, respectively, while the d 3 and d 10 SVM models were 63% and 71%, respectively, in predicting protein degradation in aged meat. STEPWISE and SVM models based on image texture features show potential to predict troponin-T degradation in meat. © 2013.

An Exploring Model of Intelligence and Personality in Different Culture

ERIC Educational Resources Information Center

Wu, Yufeng; Qian, Guoying

2005-01-01

Middle school subjects of 13-21 years (from 4 nationalities) were used for studying the relationship between progressive cognition and personality characteristics by Raven's Standard Progressive Matrices and Eysenk's Personality Questionnaire. The results showed: (1) the correlation and stepwise regression were completely identical: P score was…

Switchgrass biomass composition traits and their effects on its digestion by ruminants and bioconversion to ethanol

USDA-ARS?s Scientific Manuscript database

Six generations of divergent breeding in switchgrass (Panicum virgatum L.) for forage in vitro digestibility (IVDMD) resulted in significant changes in 20 biomass composition traits. Stepwise multi-regression was used to determine which of the 20 composition traits had largest significant effects on...

Spatial Representation in Blind Children. 3: Effects of Individual Differences.

ERIC Educational Resources Information Center

Fletcher, Janet F.

1981-01-01

Data from a study of spatial representation in blind children were subjected to two stepwise regression analyses to determine the relationships between several subject related variables and responses to "map" (cognitive map) and "route" (sequential memory) questions about the position of furniture in a recently explored room. (Author/SBH)

Juvenile Offender Recidivism: An Examination of Risk Factors

ERIC Educational Resources Information Center

Calley, Nancy G.

2012-01-01

One hundred and seventy three male juvenile offenders were followed two years postrelease from a residential treatment facility to assess recidivism and factors related to recidivism. The overall recidivism rate was 23.9%. Logistic regression with stepwise and backward variable selection methods was used to examine the relationship between…

Knowing When to Retire: The First Step towards Financial Planning in Malaysia

ERIC Educational Resources Information Center

Kock, Tan Hoe; Yoong, Folk Jee

2011-01-01

This article draws upon expected retirement age cohorts as a main determinant to financial planning preparation in Malaysia. The return rate was 55% from 600 questionnaires distributed. Five hypotheses were analyzed using hierarchical and stepwise regression analysis. The results revealed that expected retirement age cohort variables made…

The role of multicollinearity in landslide susceptibility assessment by means of Binary Logistic Regression: comparison between VIF and AIC stepwise selection

NASA Astrophysics Data System (ADS)

Cama, Mariaelena; Cristi Nicu, Ionut; Conoscenti, Christian; Quénéhervé, Geraldine; Maerker, Michael

2016-04-01

Landslide susceptibility can be defined as the likelihood of a landslide occurring in a given area on the basis of local terrain conditions. In the last decades many research focused on its evaluation by means of stochastic approaches under the assumption that 'the past is the key to the future' which means that if a model is able to reproduce a known landslide spatial distribution, it will be able to predict the future locations of new (i.e. unknown) slope failures. Among the various stochastic approaches, Binary Logistic Regression (BLR) is one of the most used because it calculates the susceptibility in probabilistic terms and its results are easily interpretable from a geomorphological point of view. However, very often not much importance is given to multicollinearity assessment whose effect is that the coefficient estimates are unstable, with opposite sign and therefore difficult to interpret. Therefore, it should be evaluated every time in order to make a model whose results are geomorphologically correct. In this study the effects of multicollinearity in the predictive performance and robustness of landslide susceptibility models are analyzed. In particular, the multicollinearity is estimated by means of Variation Inflation Index (VIF) which is also used as selection criterion for the independent variables (VIF Stepwise Selection) and compared to the more commonly used AIC Stepwise Selection. The robustness of the results is evaluated through 100 replicates of the dataset. The study area selected to perform this analysis is the Moldavian Plateau where landslides are among the most frequent geomorphological processes. This area has an increasing trend of urbanization and a very high potential regarding the cultural heritage, being the place of discovery of the largest settlement belonging to the Cucuteni Culture from Eastern Europe (that led to the development of the great complex Cucuteni-Tripyllia). Therefore, identifying the areas susceptible to landslides may lead to a better understanding and mitigation for government, local authorities and stakeholders to plan the economic activities, minimize the damages costs, environmental and cultural heritage protection. The results show that although the VIF Stepwise selection allows a more stable selection of the controlling factors, the AIC Stepwise selection produces better predictive performance. Moreover, when working with replicates the effect of multicollinearity are statistically reduced by the application of the AIC stepwise selection and the results are easily interpretable in geomorphologic terms.

Uncertainty and sensitivity analysis for two-phase flow in the vicinity of the repository in the 1996 performance assessment for the Waste Isolation Pilot Plant: Undisturbed conditions

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

HELTON,JON CRAIG; BEAN,J.E.; ECONOMY,K.

2000-05-19

Uncertainty and sensitivity analysis results obtained in the 1996 performance assessment for the Waste Isolation Pilot Plant are presented for two-phase flow the vicinity of the repository under undisturbed conditions. Techniques based on Latin hypercube sampling, examination of scatterplots, stepwise regression analysis, partial correlation analysis and rank transformation are used to investigate brine inflow, gas generation repository pressure, brine saturation and brine and gas outflow. Of the variables under study, repository pressure is potentially the most important due to its influence on spallings and direct brine releases, with the uncertainty in its value being dominated by the extent to whichmore » the microbial degradation of cellulose takes place, the rate at which the corrosion of steel takes place, and the amount of brine that drains from the surrounding disturbed rock zone into the repository.« less

Above-bottom biomass retrieval of aquatic plants with regression models and SfM data acquired by a UAV platform - A case study in Wild Duck Lake Wetland, Beijing, China

NASA Astrophysics Data System (ADS)

Jing, Ran; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Deng, Lei

2017-12-01

Above-bottom biomass (ABB) is considered as an important parameter for measuring the growth status of aquatic plants, and is of great significance for assessing health status of wetland ecosystems. In this study, Structure from Motion (SfM) technique was used to rebuild the study area with high overlapped images acquired by an unmanned aerial vehicle (UAV). We generated orthoimages and SfM dense point cloud data, from which vegetation indices (VIs) and SfM point cloud variables including average height (HAVG), standard deviation of height (HSD) and coefficient of variation of height (HCV) were extracted. These VIs and SfM point cloud variables could effectively characterize the growth status of aquatic plants, and thus they could be used to develop a simple linear regression model (SLR) and a stepwise linear regression model (SWL) with field measured ABB samples of aquatic plants. We also utilized a decision tree method to discriminate different types of aquatic plants. The experimental results indicated that (1) the SfM technique could effectively process high overlapped UAV images and thus be suitable for the reconstruction of fine texture feature of aquatic plant canopy structure; and (2) an SWL model based on point cloud variables: HAVG, HSD, HCV and two VIs: NGRDI, ExGR as independent variables has produced the best predictive result of ABB of aquatic plants in the study area, with a coefficient of determination of 0.84 and a relative root mean square error of 7.13%. In this analysis, a novel method for the quantitative inversion of a growth parameter (i.e., ABB) of aquatic plants in wetlands was demonstrated.

Stepwise group sparse regression (SGSR): gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors.

PubMed

Jang, In Sock; Dienstmann, Rodrigo; Margolin, Adam A; Guinney, Justin

2015-01-01

Complex mechanisms involving genomic aberrations in numerous proteins and pathways are believed to be a key cause of many diseases such as cancer. With recent advances in genomics, elucidating the molecular basis of cancer at a patient level is now feasible, and has led to personalized treatment strategies whereby a patient is treated according to his or her genomic profile. However, there is growing recognition that existing treatment modalities are overly simplistic, and do not fully account for the deep genomic complexity associated with sensitivity or resistance to cancer therapies. To overcome these limitations, large-scale pharmacogenomic screens of cancer cell lines--in conjunction with modern statistical learning approaches--have been used to explore the genetic underpinnings of drug response. While these analyses have demonstrated the ability to infer genetic predictors of compound sensitivity, to date most modeling approaches have been data-driven, i.e. they do not explicitly incorporate domain-specific knowledge (priors) in the process of learning a model. While a purely data-driven approach offers an unbiased perspective of the data--and may yield unexpected or novel insights--this strategy introduces challenges for both model interpretability and accuracy. In this study, we propose a novel prior-incorporated sparse regression model in which the choice of informative predictor sets is carried out by knowledge-driven priors (gene sets) in a stepwise fashion. Under regularization in a linear regression model, our algorithm is able to incorporate prior biological knowledge across the predictive variables thereby improving the interpretability of the final model with no loss--and often an improvement--in predictive performance. We evaluate the performance of our algorithm compared to well-known regularization methods such as LASSO, Ridge and Elastic net regression in the Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (Sanger) pharmacogenomics datasets, demonstrating that incorporation of the biological priors selected by our model confers improved predictability and interpretability, despite much fewer predictors, over existing state-of-the-art methods.

A new model for estimating total body water from bioelectrical resistance

NASA Technical Reports Server (NTRS)

Siconolfi, S. F.; Kear, K. T.

1992-01-01

Estimation of total body water (T) from bioelectrical resistance (R) is commonly done by stepwise regression models with height squared over R, H(exp 2)/R, age, sex, and weight (W). Polynomials of H(exp 2)/R have not been included in these models. We examined the validity of a model with third order polynomials and W. Methods: T was measured with oxygen-18 labled water in 27 subjects. R at 50 kHz was obtained from electrodes placed on the hand and foot while subjects were in the supine position. A stepwise regression equation was developed with 13 subjects (age 31.5 plus or minus 6.2 years, T 38.2 plus or minus 6.6 L, W 65.2 plus or minus 12.0 kg). Correlations, standard error of estimates and mean differences were computed between T and estimated T's from the new (N) model and other models. Evaluations were completed with the remaining 14 subjects (age 32.4 plus or minus 6.3 years, T 40.3 plus or minus 8 L, W 70.2 plus or minus 12.3 kg) and two of its subgroups (high and low) Results: A regression equation was developed from the model. The only significant mean difference was between T and one of the earlier models. Conclusion: Third order polynomials in regression models may increase the accuracy of estimating total body water. Evaluating the model with a larger population is needed.

Association Between Smartphone Use and Musculoskeletal Discomfort in Adolescent Students.

PubMed

Yang, Shang-Yu; Chen, Ming-De; Huang, Yueh-Chu; Lin, Chung-Ying; Chang, Jer-Hao

2017-06-01

Despite the substantial increase in the number of adolescent smartphone users, few studies have investigated the behavioural effects of smartphone use on adolescent students as it relates to musculoskeletal discomfort. The purpose of this study was to explore the association between smartphone use and musculoskeletal discomfort in students at a Taiwanese junior college. We hypothesised that the duration of smartphone use would be associated with increased instances of musculoskeletal discomfort in these students. This cross-sectional study employed a convenience sampling method to recruit students from a junior college in southern Taiwan. All the students (n = 315) were asked to answer questionnaires on smartphone use. A descriptive analysis, stepwise regression, and logistic regression were used to examine specific components of smartphone use and their relationship to musculoskeletal discomfort. Nearly half of the participants experienced neck and shoulder discomfort. The stepwise regression results indicated that the number of body parts with discomfort (F = 6.009, p < 0.05) increased with hours spent using ancillary smartphone functions. The logistic regression analysis showed that the students who talked on the phone >3 h/day had a higher risk of upper back discomfort than did those who talked on the phone <1 h/day [odds ratio (OR) = 4.23, p < 0.05]. This study revealed that the relationship between smartphone use and musculoskeletal discomfort is related to the duration of smartphone ancillary function use. Moreover, hours spent talking on the phone was a predictor of upper back discomfort.

Aerodynamic parameters of High-Angle-of attack Research Vehicle (HARV) estimated from flight data

NASA Technical Reports Server (NTRS)

Klein, Vladislav; Ratvasky, Thomas R.; Cobleigh, Brent R.

1990-01-01

Aerodynamic parameters of the High-Angle-of-Attack Research Aircraft (HARV) were estimated from flight data at different values of the angle of attack between 10 degrees and 50 degrees. The main part of the data was obtained from small amplitude longitudinal and lateral maneuvers. A small number of large amplitude maneuvers was also used in the estimation. The measured data were first checked for their compatibility. It was found that the accuracy of air data was degraded by unexplained bias errors. Then, the data were analyzed by a stepwise regression method for obtaining a structure of aerodynamic model equations and least squares parameter estimates. Because of high data collinearity in several maneuvers, some of the longitudinal and all lateral maneuvers were reanalyzed by using two biased estimation techniques, the principal components regression and mixed estimation. The estimated parameters in the form of stability and control derivatives, and aerodynamic coefficients were plotted against the angle of attack and compared with the wind tunnel measurements. The influential parameters are, in general, estimated with acceptable accuracy and most of them are in agreement with wind tunnel results. The simulated responses of the aircraft showed good prediction capabilities of the resulting model.

The minimal residual QR-factorization algorithm for reliably solving subset regression problems

NASA Technical Reports Server (NTRS)

Verhaegen, M. H.

1987-01-01

A new algorithm to solve test subset regression problems is described, called the minimal residual QR factorization algorithm (MRQR). This scheme performs a QR factorization with a new column pivoting strategy. Basically, this strategy is based on the change in the residual of the least squares problem. Furthermore, it is demonstrated that this basic scheme might be extended in a numerically efficient way to combine the advantages of existing numerical procedures, such as the singular value decomposition, with those of more classical statistical procedures, such as stepwise regression. This extension is presented as an advisory expert system that guides the user in solving the subset regression problem. The advantages of the new procedure are highlighted by a numerical example.

Rumination, Age, and Years of Experience: A Predictive Study of Burnout

ERIC Educational Resources Information Center

McDuffy, Moriel S.

2016-01-01

This study used a non-experimental design to examine whether job satisfaction, rumination, age and years of experience predict burnout among human service workers serving high-risk populations. The study also used a stepwise regression to assess whether job satisfaction, rumination, age, or years of experience predict burnout equally. Burnout was…

Ecological correlates of flying squirrel microhabitat use and density in temperate rainforests of southeastern Alaska

Treesearch

Winston P. Smith; Scott M. Gende; Jeffrey V. Nichols

2004-01-01

We studied habitat relations of the Prince of Wales flying squirrel (Glaucomys sabrinus griseifrons), an endemic of the temperate, coniferous rainforest of southeastern Alaska, because of concerns over population viability from extensive clear-cut logging in the region. We used stepwise logistic regression to examine relationships between...

Relationships of Reading, MCAT, and USMLE Step 1 Test Results for Medical Students

ERIC Educational Resources Information Center

Haught, Patricia; Walls, Richard

2004-01-01

Students (N = 730) took the Nelson-Denny Reading Test (current forms G or H) during orientation to medical school. Stepwise regression analyses showed the Nelson-Denny Reading Vocabulary, Comprehension, and Rate were significant predictors of MCAT (taken prior to admission to medical school) verbal reasoning. Reading Vocabulary was a significant…

Potential for Suicide and Aggression in Delinquents at Juvenile Court in a Southern City.

ERIC Educational Resources Information Center

Battile, Allen O.; And Others

1993-01-01

Questioned 263 Juvenile Court offenders about whether they wished to be dead, kill themselves, or kill others and about their existential experiences, thoughts, and feelings. Used stepwise multiple logistic regression to pinpoint experiences associated with high likelihood of verbalizing wish for destructive behavior. Found sexual abuse as risk…

Nondestructive detection of zebra chip disease in potatoes using near-infrared spectroscopy

USDA-ARS?s Scientific Manuscript database

Near-Infrared (NIR) spectroscopy in the wavelength region from 900 nm to 2600 nm was evaluated as the basis for a rapid, non-destructive method for the detection of Zebra Chip disease in potatoes and the measurement of sugar concentrations in affected tubers. Using stepwise regression in conjunction...

Student Physical Education Teachers' Well-Being: Contribution of Basic Psychological Needs

ERIC Educational Resources Information Center

Ciyin, Gülten; Erturan-Ilker, Gökçe

2014-01-01

This study adopted Self-Determination Theory tenets and aimed to explore whether student physical education (PE) teachers' satisfaction of the three basic psychological needs independently predicts well-being. 267 Turkish student PE teachers were recruited for the study. Two stepwise multiple regression analysis was performed in which each outcome…

Quality Curriculum for Under-Threes: The Impact of Structural Standards

ERIC Educational Resources Information Center

Wertfein, Monika; Spies-Kofler, Anita; Becker-Stoll, Fabienne

2009-01-01

The purpose of this study conducted in 36 infant-toddler centres ("Kinderkrippen") in the city of Munich in Bavaria/Germany was to explore structural characteristics of early child care and education and their effects on child care quality. Stepwise regressions and variance analysis (Manova) examined the relation between quality of care…

Scholarly Networking among Business Students: Structured Discussion Board Activity and Academic Outcomes

ERIC Educational Resources Information Center

Walker, Kristen; Curren, Mary T.; Kiesler, Tina; Lammers, H. Bruce; Goldenson, Jamie

2013-01-01

The authors' intent was to show the effect of student discussion board activity on academic outcomes, after accounting for past academic performance. Data were collected from 516 students enrolled in a junior-level required business course. Controlling for students' grade point average, stepwise regression showed a significant…

Factors Affecting Code Status in a University Hospital Intensive Care Unit

ERIC Educational Resources Information Center

Van Scoy, Lauren Jodi; Sherman, Michael

2013-01-01

The authors collected data on diagnosis, hospital course, and end-of-life preparedness in patients who died in the intensive care unit (ICU) with "full code" status (defined as receiving cardiopulmonary resuscitation), compared with those who didn't. Differences were analyzed using binary and stepwise logistic regression. They found no…

Variation in Environmentalism among University Students: Majoring in Outdoor Recreation, Parks, and Tourism Predicts Environmental Concerns and Behaviors

ERIC Educational Resources Information Center

Arnocky, Steven; Stroink, Mirella L.

2011-01-01

In a survey of Canadian university students (N = 205), the relationship between majoring in an outdoor recreation university program and environmental concern, cooperation, and behavior were examined. Stepwise linear regression indicated that enrollment in outdoor recreation was predictive of environmental behavior and ecological cooperation; and…

Identifying Pedophiles "Eligible" for Community Notification under Megan's Law: A Multivariate Model for Actuarially Anchored Decisions.

ERIC Educational Resources Information Center

Pallone, Nathaniel J.; Hennessy, James J.; Voelbel, Gerald T.

1998-01-01

A scientifically sound methodology for identifying offenders about whose presence the community should be notified is demonstrated. A stepwise multiple regression was calculated among incarcerated pedophiles (N=52) including both psychological and legal data; a precision-weighted equation produced 90.4% "true positives." This methodology can be…

[Aggression and related factors in elementary school students].

PubMed

Ji, Eun Sun; Jang, Mi Heui

2010-10-01

This study was done to explore the relationship between aggression and internet over-use, depression-anxiety, self-esteem, all of which are known to be behavior and psychological characteristics linked to "at-risk" children for aggression. Korean-Child Behavior Check List (K-CBCL), Korean-Internet Addiction Self-Test Scale, and Self-Esteem Scale by Rosenberg (1965) were used as measurement tools with a sample of 743, 5th-6th grade students from 3 elementary schools in Jecheon city. Chi-square, t-test, ANOVA, Pearson's correlation and stepwise multiple regression with SPSS/Win 13.0 version were used to analyze the collected data. Aggression for the elementary school students was positively correlated with internet over-use and depression-anxiety, whereas self-esteem was negatively correlated with aggression. Stepwise multiple regression analysis showed that 68.4% of the variance for aggression was significantly accounted for by internet over-use, depression-anxiety, and self-esteem. The most significant factor influencing aggression was depression-anxiety. These results suggest that earlier screening and intervention programs for depression-anxiety and internet over-use for elementary student will be helpful in preventing aggression.

Nucleated red blood cells in growth-restricted fetuses: associations with short-term neonatal outcome.

PubMed

Minior, V K; Bernstein, P S; Divon, M Y

2000-01-01

To determine the utility of the neonatal nucleated red blood cell (NRBC) count as an independent predictor of short-term perinatal outcome in growth-restricted fetuses. Hospital charts of neonates with a discharge diagnosis indicating a birth weight <10th percentile were reviewed for perinatal outcome. We studied all eligible neonates who had a complete blood count on the first day of life. After multiple gestations, anomalous fetuses and diabetic pregnancies were excluded; 73 neonates comprised the study group. Statistical analysis included ANOVA, simple and stepwise regression. Elevated NRBC counts were significantly associated with cesarean section for non-reassuring fetal status, neonatal intensive care unit admission and duration of neonatal intensive care unit stay, respiratory distress and intubation, thrombocytopenia, hyperbilirubinemia, intraventricular hemorrhage and neonatal death. Stepwise regression analysis including gestational age at birth, birth weight and NRBC count demonstrated that in growth-restricted fetuses, NRBC count was the strongest predictor of neonatal intraventricular hemorrhage, neonatal respiratory distress and neonatal death. An elevated NRBC count independently predicts adverse perinatal outcome in growth-restricted fetuses. Copyright 2000 S. Karger AG, Basel.

[Use of hypnosis in the treatment of combat post traumatic stress disorder (PTSD)].

PubMed

Abramowitz, Eitan G; Bonne, Omer

2013-08-01

Clinical reports and observations going back almost two centuries consistently indicate that hypnotherapy is an effective modality for the treatment of post traumatic stress disorder (PTSD). Pierre Janet was the first clinician to describe the successful initiation of stepwise hypnotic techniques in PTSD symptom reduction. Hypnotherapy may accelerate the formation of a therapeutic alliance and contribute to a positive treatment outcome. Hypnotic techniques may be valuable for patients with PTSD who exhibit symptoms such as anxiety, dissociation, widespread somatoform pain complaints and sleep disturbances. Hypnotic techniques may also facilitate the arduous tasks of working through traumatic memories, increasing coping skills, and promoting a sense of competency. In this review we will present guidelines for the stepwise implementation of hypnotherapy in PTSD. Since most data regarding the use of hypnotherapy in PTSD has been gathered from uncontrolled clinical observations, methodologically sound research demonstrating the efficacy of hypnotic techniques in PTSD is required for hypnotherapy to be officially added to the therapeutic armamentarium for this disorder.

Tibiofemoral contact forces during walking, running and sidestepping.

PubMed

Saxby, David J; Modenese, Luca; Bryant, Adam L; Gerus, Pauline; Killen, Bryce; Fortin, Karine; Wrigley, Tim V; Bennell, Kim L; Cicuttini, Flavia M; Lloyd, David G

2016-09-01

We explored the tibiofemoral contact forces and the relative contributions of muscles and external loads to those contact forces during various gait tasks. Second, we assessed the relationships between external gait measures and contact forces. A calibrated electromyography-driven neuromusculoskeletal model estimated the tibiofemoral contact forces during walking (1.44±0.22ms(-1)), running (4.38±0.42ms(-1)) and sidestepping (3.58±0.50ms(-1)) in healthy adults (n=60, 27.3±5.4years, 1.75±0.11m, and 69.8±14.0kg). Contact forces increased from walking (∼1-2.8 BW) to running (∼3-8 BW), sidestepping had largest maximum total (8.47±1.57 BW) and lateral contact forces (4.3±1.05 BW), while running had largest maximum medial contact forces (5.1±0.95 BW). Relative muscle contributions increased across gait tasks (up to 80-90% of medial contact forces), and peaked during running for lateral contact forces (∼90%). Knee adduction moment (KAM) had weak relationships with tibiofemoral contact forces (all R(2)<0.36) and the relationships were gait task-specific. Step-wise regression of multiple external gait measures strengthened relationships (0.20

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

Needs of the Learning Effect on Instructional Website for Vocational High School Students

ERIC Educational Resources Information Center

Lo, Hung-Jen; Fu, Gwo-Liang; Chuang, Kuei-Chih

2013-01-01

The purpose of study was to understand the correlation between the needs of the learning effect on instructional website for the vocational high school students. Our research applied the statistic methods of product-moment correlation, stepwise regression, and structural equation method to analyze the questionnaire with the sample size of 377…

Asynchronous Knowledge Sharing and Conversation Interaction Impact on Grade in an Online Business Course

ERIC Educational Resources Information Center

Strang, Kenneth David

2011-01-01

Student knowledge sharing and conversation theory interactions were coded from asynchronous discussion forums to measure the effect of learning-oriented utterances on academic performance. The sample was 3 terms of an online business course (in an accredited MBA program) at a U.S.-based university. Correlation, stepwise regression, and multiple…

Information Scent Determines Attention Allocation and Link Selection among Multiple Information Patches on a Webpage

ERIC Educational Resources Information Center

Blackmon, Marilyn Hughes

2012-01-01

This paper draws from cognitive psychology and cognitive neuroscience to develop a preliminary similarity-choice theory of how people allocate attention among information patches on webpages while completing search tasks in complex informational websites. Study 1 applied stepwise multiple regression to a large dataset and showed that success rate…

Advances in variable selection methods I: Causal selection methods versus stepwise regression and principal component analysis on data of known and unknown functional relationships

EPA Science Inventory

Hydrological predictions at a watershed scale are commonly based on extrapolation and upscaling of hydrological behavior at plot and hillslope scales. Yet, dominant hydrological drivers at a hillslope may not be as dominant at the watershed scale because of the heterogeneity of w...

Handling Missing Data: Analysis of a Challenging Data Set Using Multiple Imputation

ERIC Educational Resources Information Center

Pampaka, Maria; Hutcheson, Graeme; Williams, Julian

2016-01-01

Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…

Heterosexual Risk Behaviors Among Urban Young Adolescents

ERIC Educational Resources Information Center

O'Donnell, Lydia; Stueve, Ann; Wilson-Simmons, Renee; Dash, Kim; Agronick, Gail; JeanBaptiste, Varzi

2006-01-01

Urban 6th graders (n = 294) participate in a survey assessing early heterosexual risk behaviors as part of the Reach for Health Middle Childhood Study. About half the boys (47%) and 20% of girls report having a girlfriend or boyfriend; 42% of boys and 10% of girls report kissing and hugging for a long time. Stepwise regressions model the…

Beyond the Black-White Test Score Gap: Latinos' Early School Experiences and Literacy Outcomes

ERIC Educational Resources Information Center

Delgado, Enilda A.; Stoll, Laurie Cooper

2015-01-01

Data from the Early Childhood Longitudinal Survey-Birth Cohort are used to analyze the factors that lead to the reading readiness of children who participate in nonparental care the year prior to kindergarten (N = 4,550), with a specific focus on Latino children (N = 800). Stepwise multiple linear regression analysis demonstrates that reading…

Consequences of ignoring geologic variation in evaluating grazing impacts

Treesearch

Jonathan W. Long; Alvin L. Medina

2006-01-01

The geologic diversity of landforms in the Southwest complicates efforts to evaluate impacts of land uses such as livestock grazing. We examined a research study that evaluated relationships between trout biomass and stream habitat in the White Mountains of east-central Arizona. That study interpreted results of stepwise regressions and a nonparametric test of “grazed...

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.

2007-01-01

Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…

Age, Sex, and Body Composition as Predictors of Children's Performance on Basic Motor Abilities and Health-Related Fitness Items.

ERIC Educational Resources Information Center

Pissanos, Becky W.; And Others

1983-01-01

Step-wise linear regressions were used to relate children's age, sex, and body composition to performance on basic motor abilities including balance, speed, agility, power, coordination, and reaction time, and to health-related fitness items including flexibility, muscle strength and endurance and cardiovascular functions. Eighty subjects were in…

Disorganized Symptoms Predicted Worse Functioning Outcome in Schizophrenia Patients with Established Illness.

PubMed

Ortiz, Bruno Bertolucci; Gadelha, Ary; Higuchi, Cinthia Hiroko; Noto, Cristiano; Medeiros, Daiane; Pitta, José Cássio do Nascimento; de Araújo Filho, Gerardo Maria; Hallak, Jaime Eduardo Cecílio; Bressan, Rodrigo Affonseca

Most patients with schizophrenia will have subsequent relapses of the disorder, with continuous impairments in functioning. However, evidence is lacking on how symptoms influence functioning at different phases of the disease. This study aims to investigate the relationship between symptom dimensions and functioning at different phases: acute exacerbation, nonremission and remission. Patients with schizophrenia were grouped into acutely ill (n=89), not remitted (n=89), and remitted (n=69). Three exploratory stepwise linear regression analyses were performed for each phase of schizophrenia, in which the five PANSS factors and demographic variables were entered as the independent variables and the total Global Assessment of Functioning Scale (GAF) score was entered as the dependent variable. An additional exploratory stepwise logistic regression analysis was performed to predict subsequent remission at discharge in the inpatient population. The Disorganized factor was the most significant predictor for acutely ill patients (p<0.001), while the Hostility factor was the most significant for not-remitted patients and the Negative factor was the most significant for remitted patients (p=0.001 and p<0.001, respectively). In the logistic regression, the Disorganized factor score presented a significant negative association with remission (p=0.007). Higher disorganization symptoms showed the greatest impact in functioning at acute phase, and prevented patients from achieving remission, suggesting it may be a marker of symptom severity and worse outcome in schizophrenia.

Periodontitis in coronary heart disease patients: strong association between bleeding on probing and systemic biomarkers.

PubMed

Bokhari, Syed Akhtar H; Khan, Ayyaz A; Butt, Arshad K; Hanif, Mohammad; Izhar, Mateen; Tatakis, Dimitris N; Ashfaq, Mohammad

2014-11-01

Few studies have examined the relationship of individual periodontal parameters with individual systemic biomarkers. This study assessed the possible association between specific clinical parameters of periodontitis and systemic biomarkers of coronary heart disease risk in coronary heart disease patients with periodontitis. Angiographically proven coronary heart disease patients with periodontitis (n = 317), aged >30 years and without other systemic illness were examined. Periodontal clinical parameters of bleeding on probing (BOP), probing depth (PD), and clinical attachment level (CAL) and systemic levels of high-sensitivity C-reactive protein (CRP), fibrinogen (FIB) and white blood cells (WBC) were noted and analyzed to identify associations through linear and stepwise multiple regression analyses. Unadjusted linear regression showed significant associations between periodontal and systemic parameters; the strongest association (r = 0.629; p < 0.001) was found between BOP and CRP levels, the periodontal and systemic inflammation marker, respectively. Stepwise regression analysis models revealed that BOP was a predictor of systemic CRP levels (p < 0.0001). BOP was the only periodontal parameter significantly associated with each systemic parameter (CRP, FIB, and WBC). In coronary heart disease patients with periodontitis, BOP is strongly associated with systemic CRP levels; this association possibly reflects the potential significance of the local periodontal inflammatory burden for systemic inflammation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

PubMed

Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

2015-07-01

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

PubMed

Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

2017-07-01

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration.

LIVER ULTRASONOGRAPHY IN DOLPHINS: USE OF ULTRASONOGRAPHY TO ESTABLISH A TECHNIQUE FOR HEPATOBILIARY IMAGING AND TO EVALUATE METABOLIC DISEASE-ASSOCIATED LIVER CHANGES IN BOTTLENOSE DOLPHINS (TURSIOPS TRUNCATUS).

PubMed

Seitz, Kelsey E; Smith, Cynthia R; Marks, Stanley L; Venn-Watson, Stephanie K; Ivančić, Marina

2016-12-01

The objective of this study was to establish a comprehensive technique for ultrasound examination of the dolphin hepatobiliary system and apply this technique to 30 dolphins to determine what, if any, sonographic changes are associated with blood-based indicators of metabolic syndrome (insulin greater than 14 μIU/ml or glucose greater than 112 mg/dl) and iron overload (transferrin saturation greater than 65%). A prospective study of individuals in a cross-sectional population with and without elevated postprandial insulin levels was performed. Twenty-nine bottlenose dolphins ( Tursiops truncatus ) in a managed collection were included in the final data analysis. An in-water ultrasound technique was developed that included detailed analysis of the liver and pancreas. Dolphins with hyperinsulinemia concentrations had larger livers compared with dolphins with nonelevated concentrations. Using stepwise, multivariate regression including blood-based indicators of metabolic syndrome in dolphins, glucose was the best predictor of and had a positive linear association with liver size (P = 0.007, R 2 = 0.24). Bottlenose dolphins are susceptible to metabolic syndrome and associated complications that affect the liver, including fatty liver disease and iron overload. This study facilitated the establishment of a technique for a rapid, diagnostic, and noninvasive ultrasonographic evaluation of the dolphin liver. In addition, the study identified ultrasound-detectable hepatic changes associated primarily with elevated glucose concentration in dolphins. Future investigations will strive to detail the pathophysiological mechanisms for these changes.

Predictors of Global Self-Worth and Academic Performance among Regular Education, Learning Disabled, and Continuation High School Students.

ERIC Educational Resources Information Center

Wiest, Dudley J.; Wong, Eugene H.; Kreil, Dennis A.

1998-01-01

The ability of measures of perceived competence, control, and autonomy support to predict self-worth and academic performance was studied across groups of high school students. Stepwise regression analyses indicate these variables in model predict self-worth and grade point average. In addition, levels of school status and depression predict…

Tailoring Multimedia Instruction to Soldier Needs

DTIC Science & Technology

2014-12-01

Pretest Score (Mean % Items Correct) 39% 34% 48% 51% 51% 45% Posttest (Mean % Items Correct) 47% 44% 66% 60% 63% 56...Stepwise regression was used to examine the relationship between Soldiers’ posttest scores (criterion) and their pretest scores, training time, type of...differences among IMI types had no effect.) Pretest scores predicted posttest scores for both Adjust Indirect Fire (βstandardized = .66, t = 6.36

The Effect of College Selection Factors on Persistence: An Examination of Black and Latino Males in the Community College

ERIC Educational Resources Information Center

Wood, J. Luke; Harris, Frank, III

2015-01-01

The purpose of this study was to understand the relationship (if any) between college selection factors and persistence for Black and Latino males in the community college. Using data derived from the Educational Longitudinal Study, backwards stepwise logistic regression models were developed for both groups. Findings are contextualized in light…

Factors influencing storm-generated suspended-sediment concentrations and loads in four basins of contrasting land use, humid-tropical Puerto Rico

Treesearch

A. C. Gellis; NO-VALUE

2013-01-01

The significant characteristics controlling the variability in storm-generated suspended-sediment loads and concentrations were analyzed for four basins of differing land use (forest, pasture, cropland, and urbanizing) in humid-tropical Puerto Rico. Statistical analysis involved stepwise regression on factor scores. The explanatory variables were attributes of flow,...

Illuminating Tradespace Decisions Using Efficient Experimental Space-Filling Designs for the Engineered Resilient System Architecture

DTIC Science & Technology

2015-06-30

7. Building Statistical Metamodels using Simulation Experimental Designs ............................................... 34 7.1. Statistical Design...system design drivers across several different domain models, our methodology uses statistical metamodeling to approximate the simulations’ behavior. A...output. We build metamodels using a number of statistical methods that include stepwise regression, boosted trees, neural nets, and bootstrap forest

Illuminating Tradespace Decisions Using Efficient Experimental Space-Filling Designs for the Engineered Resilient System Architecture

DTIC Science & Technology

2015-06-01

7. Building Statistical Metamodels using Simulation Experimental Designs ............................................... 34 7.1. Statistical Design...system design drivers across several different domain models, our methodology uses statistical metamodeling to approximate the simulations’ behavior. A...output. We build metamodels using a number of statistical methods that include stepwise regression, boosted trees, neural nets, and bootstrap forest

Analysis of oscillatory motion of a light airplane at high values of lift coefficient

NASA Technical Reports Server (NTRS)

Batterson, J. G.

1983-01-01

A modified stepwise regression is applied to flight data from a light research air-plane operating at high angles at attack. The well-known phenomenon referred to as buckling or porpoising is analyzed and modeled using both power series and spline expansions of the aerodynamic force and moment coefficients associated with the longitudinal equations of motion.

"Hits" (Not "Discussion Posts") Predict Student Success in Online Courses: A Double Cross-Validation Study

ERIC Educational Resources Information Center

Ramos, Cheryl; Yudko, Errol

2008-01-01

The efficacy of individual components of an online course on positive course outcome was examined via stepwise multiple regression analysis. Outcome was measured as the student's total score on all exams given during the course. The predictors were page hits, discussion posts, and discussion reads. The vast majority of the variance of outcome was…

Factors Associated with Level of Living in Washington County, Mississippi. Technical Bulletin No. 1501.

ERIC Educational Resources Information Center

McCoy, John L.

Step-wise multiple regression and typological analysis were used to analyze the extent to which selected factors influence vertical mobility and achieved level of living. A sample of 418 male household heads who were 18 to 45 years old in Washington County, Mississippi were interviewed during 1971. A prescreening using census and local housing…

The Role of Perceived Learning and Communities of Inquiry in Predicting International Students' Course Grades in Computer-Mediated Graduate Courses

ERIC Educational Resources Information Center

Wendt, Jillian L.; Nisbet, Deanna L.

2017-01-01

This study examined the predictive relationship among international students' sense of community, perceived learning, and end-of-course grades in computer-mediated, U.S. graduate-level courses. The community of inquiry (CoI) framework served as the theoretical foundation for the study. Step-wise hierarchical multiple regression showed no…

Assessment of weather-associated causes of red spruce winter injury and consequences to aboveground carbon sequestration

Treesearch

Paul G. Schaberg; Brynne E. Lazarus; Gary J. Hawley; Joshua M. Halman; Catherine H. Borer; Christopher F. Hansen

2011-01-01

Despite considerable study, it remains uncertain what environmental factors contribute to red spruce (Picea rubens Sarg.) foliar winter injury and how much this injury influences tree C stores. We used a long-term record of winter injury in a plantation in New Hampshire and conducted stepwise linear regression analyses with local weather and regional...

Assessment of plant species diversity based on hyperspectral indices at a fine scale.

PubMed

Peng, Yu; Fan, Min; Song, Jingyi; Cui, Tiantian; Li, Rui

2018-03-19

Fast and nondestructive approaches of measuring plant species diversity have been a subject of excessive scientific curiosity and disquiet to environmentalists and field ecologists worldwide. In this study, we measured the hyperspectral reflectances and plant species diversity indices at a fine scale (0.8 meter) in central Hunshandak Sandland of Inner Mongolia, China. The first-order derivative value (FD) at each waveband and 37 hyperspectral indices were used to assess plant species diversity. Results demonstrated that the stepwise linear regression of FD can accurately estimate the Simpson (R 2  = 0.83), Pielou (R 2  = 0.87) and Shannon-Wiener index (R 2  = 0.88). Stepwise linear regression of FD (R 2  = 0.81, R 2  = 0.82) and spectral vegetation indices (R 2  = 0.51, R 2  = 0.58) significantly predicted the Margalef and Gleason index. It was proposed that the Simpson, Pielou and Shannon-Wiener indices, which are widely used as plant species diversity indicators, can be precisely estimated through hyperspectral indices at a fine scale. This research promotes the development of methods for assessment of plant diversity using hyperspectral data.

Comparison of bioavailable vanadium in alfalfa rhizosphere soil extracted by an improved BCR procedure and EDTA, HCl, and NaNO₃ single extractions in a pot experiment with V-Cd treatments.

PubMed

Yang, Jie; Teng, Yanguo; Zuo, Rui; Song, Liuting

2015-06-01

The BCR sequential extraction procedure was compared with EDTA, HCl, and NaNO3 single extractions for evaluating vanadium bioavailability in alfalfa rhizosphere soil. The amounts of vanadium extracted by these methods were in the following order: BCR (bioavailable V) > EDTA ≈ HCl > NaNO3. Both correlation analysis and stepwise regression were adopted to illustrate the extractable vanadium between different reagents. The correlation coefficients between extracted vanadium and the vanadium contents in alfalfa roots were R NaNO3 = 0.948, R HCl = 0.902, R EDTA = 0.816, and R bioavailable V = 0.819. The stepwise multiple regression equation of the NaNO3 extraction was the most significant at a 95 % confidence interval. The influence of pH, total organic carbon, and cadmium content of soil to vanadium bioavailability were not definite. In summary, both the BCR sequential extraction and the single extraction methods were valid approaches for predicting vanadium bioavailability in alfalfa rhizosphere soil, especially the single extractions.

Environmental influences on alcohol consumption practices of alcoholic beverage servers.

PubMed

Nusbaumer, Michael R; Reiling, Denise M

2002-11-01

Public drinking establishments have long been associated with heavy drinking among both their patrons and servers. Whether these environments represent locations where heavy drinking is learned (learning hypothesis) or simply places where already-heavy drinkers gather in a supportive environment (selection hypothesis) remains an important question. A sample of licensed alcoholic beverage servers in the state of Indiana, USA, was surveyed to better understand the drinking behaviors of servers within the alcohol service industry. Responses (N = 938) to a mailed questionnaire were analyzed to assess the relative influence of environmental and demographic factors on the drinking behavior of servers. Stepwise regression revealed "drinking on the job" as the most influential environmental factor on heavy drinking behaviors, followed by age and gender as influential demographic factors. Support was found for the selection hypothesis, but not for the learning hypothesis. Policy implications are discussed. factors on the drinking behavior of servers. Stepwise regression revealed "drinking on the job" as the most influential environmental factor on heavy drinking behaviors, followed by age and gender as influential demographic factors. Support was found for the selection hypothesis, but not for the learning hypothesis. Policy implications are discussed.

Handheld Tissue Hardness Meters for Assessing the Mechanical Properties of Skeletal Muscle: A Feasibility Study.

PubMed

Chino, Kentaro; Takahashi, Hideyuki

2016-09-01

The purpose of this study was to examine the feasibility of using handheld tissue hardness meters to assess the mechanical properties of skeletal muscle. This observational study included 33 healthy men (age, 22.4 ± 4.4 years) and 33 healthy women (age, 23.7 ± 4.2 years). Participants were placed in a supine position, and tissue hardness overlying the rectus femoris and the shear modulus of the muscle were measured on the right side of the body at 50% thigh length. In the same position, subcutaneous adipose tissue thickness and muscle thickness were measured using B-mode ultrasonography. To examine the associations of subcutaneous adipose tissue thickness, muscle thickness, and muscle shear modulus with tissue hardness, linear regression using a stepwise bidirectional elimination approach was performed. Stepwise linear regression revealed that subcutaneous adipose tissue thickness (r = -0.38, P = .002) and muscle shear modulus (r = 0.27, P = .03) were significantly associated with tissue hardness. Significant associations among adipose tissue thickness, muscle shear modulus, and tissue hardness show the limitations and feasibility of handheld tissue hardness meters for assessing the mechanical properties of skeletal muscles. Copyright © 2016. Published by Elsevier Inc.

Satisfaction among early and mid-career dentists in a metropolitan dental hospital in China

PubMed Central

Cui, Xiaoxi; Dunning, David G; An, Na

2017-01-01

A growing body of research has examined career satisfaction among dentists using a standardized instrument, dentist satisfaction survey (DSS). This project examined career satisfaction of early to mid-career dentists in China, a population whose career satisfaction, heretofore, has not been studied. This is an especially critical time to examine career satisfaction because of health care reform measures being implemented in China. A culturally sensitive Chinese-language version of the DSS (CDSS) was developed and electronically administered to 367 early and mid-career dentists in a tertiary dental hospital in Beijing, China. One hundred and seventy respondents completed the survey. The average total career score was 123, with a range of 82–157. Data analysis showed some significant differences in total career score and several subscales based on gender, working hours per week, and years in practice. A stepwise regression model revealed that two variables predicted total career score: working hours per week and gender. Stepwise regression also demonstrated that four subscales significantly predicted the overall professional satisfaction subscale score: respect, delivery of care, income and patient relations. Implications of these results are discussed in light of the health care delivery system and dentist career paths in China. PMID:29355243

Satisfaction among early and mid-career dentists in a metropolitan dental hospital in China.

PubMed

Cui, Xiaoxi; Dunning, David G; An, Na

2017-01-01

A growing body of research has examined career satisfaction among dentists using a standardized instrument, dentist satisfaction survey (DSS). This project examined career satisfaction of early to mid-career dentists in China, a population whose career satisfaction, heretofore, has not been studied. This is an especially critical time to examine career satisfaction because of health care reform measures being implemented in China. A culturally sensitive Chinese-language version of the DSS (CDSS) was developed and electronically administered to 367 early and mid-career dentists in a tertiary dental hospital in Beijing, China. One hundred and seventy respondents completed the survey. The average total career score was 123, with a range of 82-157. Data analysis showed some significant differences in total career score and several subscales based on gender, working hours per week, and years in practice. A stepwise regression model revealed that two variables predicted total career score: working hours per week and gender. Stepwise regression also demonstrated that four subscales significantly predicted the overall professional satisfaction subscale score: respect, delivery of care, income and patient relations. Implications of these results are discussed in light of the health care delivery system and dentist career paths in China.

Improved Variable Selection Algorithm Using a LASSO-Type Penalty, with an Application to Assessing Hepatitis B Infection Relevant Factors in Community Residents

PubMed Central

Guo, Pi; Zeng, Fangfang; Hu, Xiaomin; Zhang, Dingmei; Zhu, Shuming; Deng, Yu; Hao, Yuantao

2015-01-01

Objectives In epidemiological studies, it is important to identify independent associations between collective exposures and a health outcome. The current stepwise selection technique ignores stochastic errors and suffers from a lack of stability. The alternative LASSO-penalized regression model can be applied to detect significant predictors from a pool of candidate variables. However, this technique is prone to false positives and tends to create excessive biases. It remains challenging to develop robust variable selection methods and enhance predictability. Material and methods Two improved algorithms denoted the two-stage hybrid and bootstrap ranking procedures, both using a LASSO-type penalty, were developed for epidemiological association analysis. The performance of the proposed procedures and other methods including conventional LASSO, Bolasso, stepwise and stability selection models were evaluated using intensive simulation. In addition, methods were compared by using an empirical analysis based on large-scale survey data of hepatitis B infection-relevant factors among Guangdong residents. Results The proposed procedures produced comparable or less biased selection results when compared to conventional variable selection models. In total, the two newly proposed procedures were stable with respect to various scenarios of simulation, demonstrating a higher power and a lower false positive rate during variable selection than the compared methods. In empirical analysis, the proposed procedures yielding a sparse set of hepatitis B infection-relevant factors gave the best predictive performance and showed that the procedures were able to select a more stringent set of factors. The individual history of hepatitis B vaccination, family and individual history of hepatitis B infection were associated with hepatitis B infection in the studied residents according to the proposed procedures. Conclusions The newly proposed procedures improve the identification of significant variables and enable us to derive a new insight into epidemiological association analysis. PMID:26214802

Impact of livestock Scale on Rice Production in Battambang of Cambodia

NASA Astrophysics Data System (ADS)

Siek, D.; Xu, S. W.; Wyu; Ahmed, A.-G.

2017-10-01

Increasing the awareness of environmental protection especially in the rural regions is important as most the farmers reside in that region. Crop-livestock proudciton has proven in many ways to encourage environmental protection. This study analyzes among other factors the impacto of livestock scale on rice production. Two regressions: Ordinary Least Square (OLS) and stepwise regression was applied to investigate these interrelationship. The result stress of three factors encouraging livestock production namely size of farmland, scale of livestock and income acquired from other jobs. The study further provides recommends to the government based on the findings of the study.

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

DTIC Science & Technology

1990-05-01

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

Relationship between COMLEX-USA scores and performance on the American Osteopathic Board of Emergency Medicine Part I certifying examination.

PubMed

Li, Feiming; Gimpel, John R; Arenson, Ethan; Song, Hao; Bates, Bruce P; Ludwin, Fredric

2014-04-01

Few studies have investigated how well scores from the Comprehensive Osteopathic Medical Licensing Examination-USA (COMLEX-USA) series predict resident outcomes, such as performance on board certification examinations. To determine how well COMLEX-USA predicts performance on the American Osteopathic Board of Emergency Medicine (AOBEM) Part I certification examination. The target study population was first-time examinees who took AOBEM Part I in 2011 and 2012 with matched performances on COMLEX-USA Level 1, Level 2-Cognitive Evaluation (CE), and Level 3. Pearson correlations were computed between AOBEM Part I first-attempt scores and COMLEX-USA performances to measure the association between these examinations. Stepwise linear regression analysis was conducted to predict AOBEM Part I scores by the 3 COMLEX-USA scores. An independent t test was conducted to compare mean COMLEX-USA performances between candidates who passed and who failed AOBEM Part I, and a stepwise logistic regression analysis was used to predict the log-odds of passing AOBEM Part I on the basis of COMLEX-USA scores. Scores from AOBEM Part I had the highest correlation with COMLEX-USA Level 3 scores (.57) and slightly lower correlation with COMLEX-USA Level 2-CE scores (.53). The lowest correlation was between AOBEM Part I and COMLEX-USA Level 1 scores (.47). According to the stepwise regression model, COMLEX-USA Level 1 and Level 2-CE scores, which residency programs often use as selection criteria, together explained 30% of variance in AOBEM Part I scores. Adding Level 3 scores explained 37% of variance. The independent t test indicated that the 397 examinees passing AOBEM Part I performed significantly better than the 54 examinees failing AOBEM Part I in all 3 COMLEX-USA levels (P<.001 for all 3 levels). The logistic regression model showed that COMLEX-USA Level 1 and Level 3 scores predicted the log-odds of passing AOBEM Part I (P=.03 and P<.001, respectively). The present study empirically supported the predictive and discriminant validities of the COMLEX-USA series in relation to the AOBEM Part I certification examination. Although residency programs may use COMLEX-USA Level 1 and Level 2-CE scores as partial criteria in selecting residents, Level 3 scores, though typically not available at the time of application, are actually the most statistically related to performances on AOBEM Part I.

Estimating the global incidence of traumatic spinal cord injury.

PubMed

Fitzharris, M; Cripps, R A; Lee, B B

2014-02-01

Population modelling--forecasting. To estimate the global incidence of traumatic spinal cord injury (TSCI). An initiative of the International Spinal Cord Society (ISCoS) Prevention Committee. Regression techniques were used to derive regional and global estimates of TSCI incidence. Using the findings of 31 published studies, a regression model was fitted using a known number of TSCI cases as the dependent variable and the population at risk as the single independent variable. In the process of deriving TSCI incidence, an alternative TSCI model was specified in an attempt to arrive at an optimal way of estimating the global incidence of TSCI. The global incidence of TSCI was estimated to be 23 cases per 1,000,000 persons in 2007 (179,312 cases per annum). World Health Organization's regional results are provided. Understanding the incidence of TSCI is important for health service planning and for the determination of injury prevention priorities. In the absence of high-quality epidemiological studies of TSCI in each country, the estimation of TSCI obtained through population modelling can be used to overcome known deficits in global spinal cord injury (SCI) data. The incidence of TSCI is context specific, and an alternative regression model demonstrated how TSCI incidence estimates could be improved with additional data. The results highlight the need for data standardisation and comprehensive reporting of national level TSCI data. A step-wise approach from the collation of conventional epidemiological data through to population modelling is suggested.

Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies

NASA Astrophysics Data System (ADS)

Tootle, G.; Anderson, S.; Grissino-Mayer, H.

2012-12-01

Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.

An Enhanced Engineering Perspective of Global Climate Systems and Statistical Formulation of Terrestrial CO2 Exchanges

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

Dai, Yuanshun; Baek, Seung H.; Garcia-Diza, Alberto

2012-01-01

This paper designs a comprehensive approach based on the engineering machine/system concept, to model, analyze, and assess the level of CO2 exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO2 fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO2 fluxes.more » To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as Stochastic Filtering Analysis of Variance (SFANOVA). The CO2 flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction and globalization capabilities of the proposed engineering approach and the SF-ANOVA technology. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures.« less

Prediction of adult height in girls: the Beunen-Malina-Freitas method.

PubMed

Beunen, Gaston P; Malina, Robert M; Freitas, Duarte L; Thomis, Martine A; Maia, José A; Claessens, Albrecht L; Gouveia, Elvio R; Maes, Hermine H; Lefevre, Johan

2011-12-01

The purpose of this study was to validate and cross-validate the Beunen-Malina-Freitas method for non-invasive prediction of adult height in girls. A sample of 420 girls aged 10-15 years from the Madeira Growth Study were measured at yearly intervals and then 8 years later. Anthropometric dimensions (lengths, breadths, circumferences, and skinfolds) were measured; skeletal age was assessed using the Tanner-Whitehouse 3 method and menarcheal status (present or absent) was recorded. Adult height was measured and predicted using stepwise, forward, and maximum R (2) regression techniques. Multiple correlations, mean differences, standard errors of prediction, and error boundaries were calculated. A sample of the Leuven Longitudinal Twin Study was used to cross-validate the regressions. Age-specific coefficients of determination (R (2)) between predicted and measured adult height varied between 0.57 and 0.96, while standard errors of prediction varied between 1.1 and 3.9 cm. The cross-validation confirmed the validity of the Beunen-Malina-Freitas method in girls aged 12-15 years, but at lower ages the cross-validation was less consistent. We conclude that the Beunen-Malina-Freitas method is valid for the prediction of adult height in girls aged 12-15 years. It is applicable to European populations or populations of European ancestry.

Analysis of the Magnitude and Frequency of Peak Discharges for the Navajo Nation in Arizona, Utah, Colorado, and New Mexico

USGS Publications Warehouse

Waltemeyer, Scott D.

2006-01-01

Estimates of the magnitude and frequency of peak discharges are necessary for the reliable flood-hazard mapping in the Navajo Nation in Arizona, Utah, Colorado, and New Mexico. The Bureau of Indian Affairs, U.S. Army Corps of Engineers, and Navajo Nation requested that the U.S. Geological Survey update estimates of peak discharge magnitude for gaging stations in the region and update regional equations for estimation of peak discharge and frequency at ungaged sites. Equations were developed for estimating the magnitude of peak discharges for recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years at ungaged sites using data collected through 1999 at 146 gaging stations, an additional 13 years of peak-discharge data since a 1997 investigation, which used gaging-station data through 1986. The equations for estimation of peak discharges at ungaged sites were developed for flood regions 8, 11, high elevation, and 6 and are delineated on the basis of the hydrologic codes from the 1997 investigation. Peak discharges for selected recurrence intervals were determined at gaging stations by fitting observed data to a log-Pearson Type III distribution with adjustments for a low-discharge threshold and a zero skew coefficient. A low-discharge threshold was applied to frequency analysis of 82 of the 146 gaging stations. This application provides an improved fit of the log-Pearson Type III frequency distribution. Use of the low-discharge threshold generally eliminated the peak discharge having a recurrence interval of less than 1.4 years in the probability-density function. Within each region, logarithms of the peak discharges for selected recurrence intervals were related to logarithms of basin and climatic characteristics using stepwise ordinary least-squares regression techniques for exploratory data analysis. Generalized least-squares regression techniques, an improved regression procedure that accounts for time and spatial sampling errors, then was applied to the same data used in the ordinary least-squares regression analyses. The average standard error of prediction for a peak discharge have a recurrence interval of 100-years for region 8 was 53 percent (average) for the 100-year flood. The average standard of prediction, which includes average sampling error and average standard error of regression, ranged from 45 to 83 percent for the 100-year flood. Estimated standard error of prediction for a hybrid method for region 11 was large in the 1997 investigation. No distinction of floods produced from a high-elevation region was presented in the 1997 investigation. Overall, the equations based on generalized least-squares regression techniques are considered to be more reliable than those in the 1997 report because of the increased length of record and improved GIS method. Techniques for transferring flood-frequency relations to ungaged sites on the same stream can be estimated at an ungaged site by a direct application of the regional regression equation or at an ungaged site on a stream that has a gaging station upstream or downstream by using the drainage-area ratio and the drainage-area exponent from the regional regression equation of the respective region.

Age-related factors in the relationship between foot measurements and living stature and body weight.

PubMed

Atamturk, Derya; Duyar, Izzet

2008-11-01

The measurements of feet and footprints are especially important in forensic identification, as they have been used to predict the body height and weight of victims or suspects. It can be observed that the subjects of forensic-oriented studies are generally young adults. That is to say, researchers rarely take into consideration the body's proportional changes with age. Hence, the aim of this study is to generate equations which take age and sex into consideration, when stature and body weight are estimated from foot and footprints dimensions. With this aim in mind, we measured the stature, body weight, foot length and breadth, heel breadth, footprint length and breadth, and footprint heel breadth of 516 volunteers (253 males and 263 females) aged between 17.6 and 82.9 years using standard measurement techniques. The sample population was divided randomly into two groups. Group 1, the study group, consisted of 80% of the sample (n = 406); the remaining 20% were assigned to the cross-validation group or Group 2 (n = 110). In the first stage of the study, we produced equations for estimating stature and weight using a stepwise regression technique. Then, their reliability was tested on Group 2 members. Statistical analyses showed that the ratios of foot dimensions to stature and body weight change considerably with age and sex. Consequently, the regression equations which include these variables yielded more reliable results. Our results indicated that age and sex should be taken into consideration when predicting human body height and weight for forensic purposes.

Improving prediction of metal uptake by Chinese cabbage (Brassica pekinensis L.) based on a soil-plant stepwise analysis.

PubMed

Zhang, Sha; Song, Jing; Gao, Hui; Zhang, Qiang; Lv, Ming-Chao; Wang, Shuang; Liu, Gan; Pan, Yun-Yu; Christie, Peter; Sun, Wenjie

2016-11-01

It is crucial to develop predictive soil-plant transfer (SPT) models to derive the threshold values of toxic metals in contaminated arable soils. The present study was designed to examine the heavy metal uptake pattern and to improve the prediction of metal uptake by Chinese cabbage grown in agricultural soils with multiple contamination by Cd, Cu, Ni, Pb, and Zn. Pot experiments were performed with 25 historically contaminated soils to determine metal accumulation in different parts of Chinese cabbage. Different soil bioavailable metal fractions were determined using different extractants (0.43M HNO3, 0.01M CaCl2, 0.005M DTPA, and 0.01M LWMOAs), soil moisture samplers, and diffusive gradients in thin films (DGT), and the fractions were compared with shoot metal uptake using both direct and stepwise multiple regression analysis. The stepwise approach significantly improved the prediction of metal uptake by cabbage over the direct approach. Strongly pH dependent or nonlinear relationships were found for the adsorption of root surfaces and in root-shoot uptake processes. Metals were linearly translocated from the root surface to the root. Therefore, the nonlinearity of uptake pattern is an important explanation for the inadequacy of the direct approach in some cases. The stepwise approach offers an alternative and robust method to study the pattern of metal uptake by Chinese cabbage (Brassica pekinensis L.). Copyright © 2016. Published by Elsevier B.V.

Investigating a physical basis for spectroscopic estimates of leaf nitrogen concentration

USGS Publications Warehouse

Kokaly, R.F.

2001-01-01

The reflectance spectra of dried and ground plant foliage are examined for changes directly due to increasing nitrogen concentration. A broadening of the 2.1-??m absorption feature is observed as nitrogen concentration increases. The broadening is shown to arise from two absorptions at 2.054 ??m and 2.172 ??m. The wavelength positions of these absorptions coincide with the absorption characteristics of the nitrogen-containing amide bonds in proteins. The observed presence of these absorption features in the reflectance spectra of dried foliage is suggested to form a physical basis for high correlations established by stepwise multiple linear regression techniques between the reflectance of dry plant samples and their nitrogen concentration. The consistent change in the 2.1-??m absorption feature as nitrogen increases and the offset position of protein absorptions compared to those of other plant components together indicate that a generally applicable algorithm may be developed for spectroscopic estimates of nitrogen concentration from the reflectance spectra of dried plant foliage samples. ?? 2001 Published by Elsevier Science Ireland Ltd.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Sexual dimorphism of the mandible in a contemporary Chinese Han population.

PubMed

Dong, Hongmei; Deng, Mohong; Wang, WenPeng; Zhang, Ji; Mu, Jiao; Zhu, Guanghui

2015-10-01

A present limitation of forensic anthropology practice in China is the lack of population-specific criteria on contemporary human skeletons. In this study, a sample of 203 maxillofacial Cone beam computed tomography (CBCT) images, including 96 male and 107 female cases (20-65 years old), was analyzed to explore mandible sexual dimorphism in a population of contemporary adult Han Chinese to investigate the potential use of the mandible as sex indicator. A three-dimensional image from mandible CBCT scans was reconstructed using the SimPlant Pro 11.40 software. Nine linear and two angular parameters were measured. Discriminant function analysis (DFA) and logistic regression analysis (LRA) were used to develop the mathematics models for sex determination. All of the linear measurements studied and one angular measurement were found to be sexually dimorphic, with the maximum mandibular length and bi-condylar breadth being the most dimorphic by univariate DFA and LRA respectively. The cross-validated sex allocation accuracies on multivariate were ranged from 84.2% (direct DFA), 83.5% (direct LRA), 83.3% (stepwise DFA) to 80.5% (stepwise LRA). In general, multivariate DFA yielded a higher accuracy and LRA obtained a lower sex bias, and therefore both DFA and LRA had their own advantages for sex determination by the mandible in this sample. These results suggest that the mandible expresses sexual dimorphism in the contemporary adult Han Chinese population, indicating an excellent sexual discriminatory ability. Cone beam computed tomography scanning can be used as alternative source for contemporary osteometric techniques. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Inverse modelling for real-time estimation of radiological consequences in the early stage of an accidental radioactivity release.

PubMed

Pecha, Petr; Šmídl, Václav

2016-11-01

A stepwise sequential assimilation algorithm is proposed based on an optimisation approach for recursive parameter estimation and tracking of radioactive plume propagation in the early stage of a radiation accident. Predictions of the radiological situation in each time step of the plume propagation are driven by an existing short-term meteorological forecast and the assimilation procedure manipulates the model parameters to match the observations incoming concurrently from the terrain. Mathematically, the task is a typical ill-posed inverse problem of estimating the parameters of the release. The proposed method is designated as a stepwise re-estimation of the source term release dynamics and an improvement of several input model parameters. It results in a more precise determination of the adversely affected areas in the terrain. The nonlinear least-squares regression methodology is applied for estimation of the unknowns. The fast and adequately accurate segmented Gaussian plume model (SGPM) is used in the first stage of direct (forward) modelling. The subsequent inverse procedure infers (re-estimates) the values of important model parameters from the actual observations. Accuracy and sensitivity of the proposed method for real-time forecasting of the accident propagation is studied. First, a twin experiment generating noiseless simulated "artificial" observations is studied to verify the minimisation algorithm. Second, the impact of the measurement noise on the re-estimated source release rate is examined. In addition, the presented method can be used as a proposal for more advanced statistical techniques using, e.g., importance sampling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Topographic Controls on Soil Carbon Distribution in Iowa Croplands, USA

NASA Astrophysics Data System (ADS)

McCarty, Greg; Li, Xia

2017-04-01

Topography is a key factor affecting soil organic carbon (SOC) redistribution (erosion or deposition) because it influences several hydrological indices including soil moisture dynamics, runoff velocity and acceleration, and flow divergence and convergence. In this study, we examined the relationship between 15 topographic metrics derived from Light Detection and Ranging (Lidar) data and SOC redistribution in agricultural fields. We adopted the fallout 137Cesium (137Cs) technique to estimate SOC redistribution rates across 560 sampling plots in Iowa. Then, using stepwise ordinarily least square regression (SOLSR) and stepwise principle component analysis (SPCA), topography-based SOC models were developed to simulate spatial patterns of SOC content and redistribution. Results suggested that erosion and deposition of topsoil SOC were regulated by topography with SOC gain in lowland areas and SOC loss in sloping areas. Topographic wetness index (TWI) and slope were the most influential variables controlling SOC content and redistribution. The topography-based models exhibited good performances in simulating SOC content and redistribution across two crop sites with intensive samplings. SPCA models had slightly lower coefficients of determination and Nash-Sutcliffe efficiency values compared to SOLSR models at the field scale. However, significantly SPCA outperformed SOLAR in predicting SOC redistribution patterns at the watershed scale. Results of this study suggest that the topography-based SPCA model was more robust for scaling up models to the watershed scale because SPCA models may better represent the landscapes and are less subject to over fitting. This work suggests an improved method to sample and characterize landscapes for better prediction of soil property distribution.

[Contents of vitreous humor of dead body with different postmortem intervals].

PubMed

Tao, Tao; Xu, Jing; Luo, Tong-Xing; Liao, Zhi-Gang; Pan, Hong-Fu

2006-11-01

To establish regression correlations between postmortem interval (PMI) and contents of human vitreous humor of dead bodies for forensic purposes. The human vitreous humor were taken from 126 dead bodies between 0.5 to 216 hours after death, and 11 chemical elements were detected by the OLYMPUS AU400 auto-biochemistry instrument. (1) The glucose, natrium and chlorine in human vitreous humor decreased, while the urea, creatinine, uric acid, potassium, calcium, magnesium, phosphorus, and micro-protein increased after death. The change of glucose, potassium and phosphorus were well correlated with the PMI (r = 0.824, 0.967, 0.880). But the uric acid and micro-protein did not have a good correlation with the PMI(r = 0.350, 0.153). (2) The stepwise regression analysis established the following equations for the PMI (Y): Y = -35. 15+6.05X, R2 = 0.957 (X = potassium); Y = -27.83+ 5.49X(1) - 1.35X(2), R2 = 0.960 (X(1) = potassium, X(2) = glucose); Y = -6.37+3.93X(1) -2.29X(2) + 5.36X(3), R2 = 0.966 (X(1) = potassium, X(2) = glucose, X(3) = phosphorus). (1) Eleven chemical components in human vitreous humor change after death, among which postassium has the best linear correlation with the PMI within 72 hours after death. (2) The accuracy of the estimation of PMI could be improved by establishing a multi-variable equation through stepwise regression.

Predicting the demand of physician workforce: an international model based on "crowd behaviors".

PubMed

Tsai, Tsuen-Chiuan; Eliasziw, Misha; Chen, Der-Fang

2012-03-26

Appropriateness of physician workforce greatly influences the quality of healthcare. When facing the crisis of physician shortages, the correction of manpower always takes an extended time period, and both the public and health personnel suffer. To calculate an appropriate number of Physician Density (PD) for a specific country, this study was designed to create a PD prediction model, based on health-related data from many countries. Twelve factors that could possibly impact physicians' demand were chosen, and data of these factors from 130 countries (by reviewing 195) were extracted. Multiple stepwise-linear regression was used to derive the PD prediction model, and a split-sample cross-validation procedure was performed to evaluate the generalizability of the results. Using data from 130 countries, with the consideration of the correlation between variables, and preventing multi-collinearity, seven out of the 12 predictor variables were selected for entry into the stepwise regression procedure. The final model was: PD = (5.014 - 0.128 × proportion under age 15 years + 0.034 × life expectancy)2, with R2 of 80.4%. Using the prediction equation, 70 countries had PDs with "negative discrepancy", while 58 had PDs with "positive discrepancy". This study provided a regression-based PD model to calculate a "norm" number of PD for a specific country. A large PD discrepancy in a country indicates the needs to examine physician's workloads and their well-being, the effectiveness/efficiency of medical care, the promotion of population health and the team resource management.

Development of a Bayesian model to estimate health care outcomes in the severely wounded

PubMed Central

Stojadinovic, Alexander; Eberhardt, John; Brown, Trevor S; Hawksworth, Jason S; Gage, Frederick; Tadaki, Douglas K; Forsberg, Jonathan A; Davis, Thomas A; Potter, Benjamin K; Dunne, James R; Elster, E A

2010-01-01

Background: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations. Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN) and step-wise logistic regression (LR). Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC) from receiver operating characteristics (ROC) curves. Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79), intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81), and wound healing (AUC: LR, 0.91; BBN, 0.72) showed strong AUC. Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold cross-validation and further confirmed through logistic regression modeling. The method warrants further development and independent validation in other, more diverse patient populations. PMID:21197361

Estimation of standard liver volume in Chinese adult living donors.

PubMed

Fu-Gui, L; Lu-Nan, Y; Bo, L; Yong, Z; Tian-Fu, W; Ming-Qing, X; Wen-Tao, W; Zhe-Yu, C

2009-12-01

To determine a formula predicting the standard liver volume based on body surface area (BSA) or body weight in Chinese adults. A total of 115 consecutive right-lobe living donors not including the middle hepatic vein underwent right hemi-hepatectomy. No organs were used from prisoners, and no subjects were prisoners. Donor anthropometric data including age, gender, body weight, and body height were recorded prospectively. The weights and volumes of the right lobe liver grafts were measured at the back table. Liver weights and volumes were calculated from the right lobe graft weight and volume obtained at the back table, divided by the proportion of the right lobe on computed tomography. By simple linear regression analysis and stepwise multiple linear regression analysis, we correlated calculated liver volume and body height, body weight, or body surface area. The subjects had a mean age of 35.97 +/- 9.6 years, and a female-to-male ratio of 60:55. The mean volume of the right lobe was 727.47 +/- 136.17 mL, occupying 55.59% +/- 6.70% of the whole liver by computed tomography. The volume of the right lobe was 581.73 +/- 96.137 mL, and the estimated liver volume was 1053.08 +/- 167.56 mL. Females of the same body weight showed a slightly lower liver weight. By simple linear regression analysis and stepwise multiple linear regression analysis, a formula was derived based on body weight. All formulae except the Hong Kong formula overestimated liver volume compared to this formula. The formula of standard liver volume, SLV (mL) = 11.508 x body weight (kg) + 334.024, may be applied to estimate liver volumes in Chinese adults.

Generating linear regression model to predict motor functions by use of laser range finder during TUG.

PubMed

Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki

2017-05-01

The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P < 0.01), which was not significant higher correlation than TUG test time. We showed which TUG test parameters were associated with each motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Evaluating Disease Severity in Chronic Pain Patients with and without Fibromyalgia: A Comparison of the Symptom Impact Questionnaire and the Polysymptomatic Distress Scale.

PubMed

Friend, Ronald; Bennett, Robert M

2015-12-01

To compare the relative effectiveness of the Polysymptomatic Distress Scale (PSD) with the Symptom Impact Questionnaire (SIQR), the disease-neutral revision of the updated Fibromyalgia Impact Questionnaire (FIQR), in their ability to assess disease activity in patients with rheumatic disorders both with and without fibromyalgia (FM). The study included 321 patients from 8 clinical practices with some 16 different chronic pain disorders. Disease severity was assessed by the Medical Outcomes Study Short Form-36 (SF-36). Univariate analyses were used to assess the magnitude of PSD and SIQR correlations with SF-36 subscales. Hierarchical stepwise regression was used to evaluate the unique contribution of the PSD and SIQR to the SF-36. Random forest regression probed the relative importance of the SIQR and PSD components as predictors of SF-36. The correlations with the SF-36 subscales were significantly higher for the SIQR (0.48 to 0.78) than the PSD (0.29 to 0.56; p < 0.001). Stepwise regression revealed that the SIQR was contributing additional unique variance on SF-36 subscales, which was not the case for the PSD. Random forest regression showed SIQR Function, Symptoms, and Global Impact subscales were more important predictors of SF-36 than the PSD. The single SIQR pain item contributed 55% of SF-36 pain variance compared to 23% with the 19-point WPI (the Widespread Pain Index component of PSD). The SIQR, the disease-neutral revision of the updated FIQ, has several important advantages over the PSD in the evaluation of disease severity in chronic pain disorders.

Concurrent Validity of Hill's Educational Cognitive Style Model as a Prototype for Successful Academic Programs Among Lower-Class Students.

ERIC Educational Resources Information Center

London, David T.

Data from the stepwise multiple regression of four educational cognitive style predictor sets on each of six academic competence criteria were used to define the concurrent validity of Hill's educational cognitive style model. The purpose was to determine how appropriate it may be to use this model as a prototype for successful academic programs…

Do Basic Skills Predict Youth Unemployment (16- to 24-Year-Olds) Also when Controlled for Accomplished Upper-Secondary School? A Cross-Country Comparison

ERIC Educational Resources Information Center

Lundetrae, Kjersti; Gabrielsen, Egil; Mykletun, Reidar

2010-01-01

Basic skills and educational level are closely related, and both might affect employment. Data from the Adult Literacy and Life Skills Survey were used to examine whether basic skills in terms of literacy and numeracy predicted youth unemployment (16-24 years) while controlling for educational level. Stepwise logistic regression showed that in…

Objective Quantification of Pre-and Postphonosurgery Vocal Fold Vibratory Characteristics Using High-Speed Videoendoscopy and a Harmonic Waveform Model

ERIC Educational Resources Information Center

Ikuma, Takeshi; Kunduk, Melda; McWhorter, Andrew J.

2014-01-01

Purpose: The model-based quantitative analysis of high-speed videoendoscopy (HSV) data at a low frame rate of 2,000 frames per second was assessed for its clinical adequacy. Stepwise regression was employed to evaluate the HSV parameters using harmonic models and their relationships to the Voice Handicap Index (VHI). Also, the model-based HSV…

A statistical model of expansion in a colony of black-tailed prairie dogs

Treesearch

R. P. Cincotta; Daniel W. Uresk; R. M. Hansen

1988-01-01

To predict prairie dog establishment in areas adjacent to a colony we sample: (1) VISIBILITY through the vegetation using a target, (2) POPULATION DENSITY at the cology edge, (3) DISTANCE from the edge to the potential site of settlement, and (4) % FORB COVER. Step-wise regression analysis indicated that establishment of prairie dogs in adjacent prairie was most likely...

Factors that influence the efficacy of acarbose and metformin as initial therapy in Chinese patients with newly diagnosed type 2 diabetes: a subanalysis of the MARCH trial.

PubMed

Zhang, Jinping; Wang, Na; Xing, Xiaoyan; Yang, Zhaojun; Wang, Xin; Yang, Wenying

2016-01-01

To conduct a subanalysis of the randomized MARCH (Metformin and AcaRbose in Chinese as the initial Hypoglycemic treatment) trial to investigate whether specific characteristics are associated with the efficacy of either acarbose or metformin as initial therapy. A total of 657 type 2 diabetes patients who were randomly assigned to 48 weeks of therapy with either acarbose or metformin in the MARCH trial were divided into two groups based upon their hemoglobin A1c (HbA1c) levels at the end of follow-up: HbA1c <7% (<53 mmol/mol) and ≥7% (≥53 mmol/mol). Univariate, multivariate, and stepwise linear regression analyses were applied to identify the factors associated with treatment efficacy. Because this was a subanalysis, no measurement was performed. Univariate analysis showed that the efficacy of acarbose and metformin was influenced by HbA1c, fasting blood glucose (FBG), and 2 hour postprandial venous blood glucose (2hPPG) levels, as well as by changes in body mass index (BMI) (p ≤ 0.006). Multivariate analysis and stepwise linear regression analyses indicated that lower baseline 2hPPG values and greater changes in BMI were factors that positively influenced efficacy in both treatment groups (p ≤ 0.05). Stepwise regression model analysis also revealed that a lower baseline homeostasis model assessment-estimated insulin resistance (HOMA-IR) and higher serum insulin area under the curve (AUC) were factors positively influencing HbA1c normalization in all patients (p ≤ 0.032). Newly diagnosed type 2 diabetes patients with lower baseline 2hPPG and HOMA-IR values are more likely to achieve glucose control with acarbose or metformin treatment. Furthermore, the change in BMI after acarbose or metformin treatment is also a factor influencing HbA1c normalization. A prospective study with a larger sample size is necessary to confirm our results as well as measure β cell function and examine the influence of the patients' dietary habits.

Design and implementation of a novel mechanical testing system for cellular solids.

PubMed

Nazarian, Ara; Stauber, Martin; Müller, Ralph

2005-05-01

Cellular solids constitute an important class of engineering materials encompassing both man-made and natural constructs. Materials such as wood, cork, coral, and cancellous bone are examples of cellular solids. The structural analysis of cellular solid failure has been limited to 2D sections to illustrate global fracture patterns. Due to the inherent destructiveness of 2D methods, dynamic assessment of fracture progression has not been possible. Image-guided failure assessment (IGFA), a noninvasive technique to analyze 3D progressive bone failure, has been developed utilizing stepwise microcompression in combination with time-lapsed microcomputed tomographic imaging (microCT). This method allows for the assessment of fracture progression in the plastic region, where much of the structural deformation/energy absorption is encountered in a cellular solid. Therefore, the goal of this project was to design and fabricate a novel micromechanical testing system to validate the effectiveness of the stepwise IGFA technique compared to classical continuous mechanical testing, using a variety of engineered and natural cellular solids. In our analysis, we found stepwise compression to be a valid approach for IGFA with high precision and accuracy comparable to classical continuous testing. Therefore, this approach complements the conventional mechanical testing methods by providing visual insight into the failure propagation mechanisms of cellular solids. (c) 2005 Wiley Periodicals, Inc.

Explanation of the variance in quality of life and activity capacity of patients with heart failure by laboratory data.

PubMed

Athanasopoulos, Leonidas V; Dritsas, Athanasios; Doll, Helen A; Cokkinos, Dennis V

2010-08-01

This study was conducted to explain the variance in quality of life (QoL) and activity capacity of patients with congestive heart failure from pathophysiological changes as estimated by laboratory data. Peak oxygen consumption (peak VO2) and ventilation (VE)/carbon dioxide output (VCO2) slope derived from cardiopulmonary exercise testing, plasma N-terminal prohormone of B-type natriuretic peptide (NT-proBNP), and echocardiographic markers [left atrium (LA), left ventricular ejection fraction (LVEF)] were measured in 62 patients with congestive heart failure, who also completed the Minnesota Living with Heart Failure Questionnaire and the Specific Activity Questionnaire. All regression models were adjusted for age and sex. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.01, LVEF with P value less than 0.001, LA with P=0.001, and logNT-proBNP with P value less than 0.01 were found to be associated with QoL. On stepwise multiple linear regression, peak VO2 and LVEF continued to be predictive, accounting for 40% of the variability in Minnesota Living with Heart Failure Questionnaire score. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.001, LVEF with P value less than 0.05, LA with P value less than 0.001, and logNT-proBNP with P value less than 0.001 were found to be associated with activity capacity. On stepwise multiple linear regression, peak VO2 and LA continued to be predictive, accounting for 53% of the variability in Specific Activity Questionnaire score. Peak VO2 is independently associated both with QoL and activity capacity. In addition to peak VO2, LVEF is independently associated with QoL, and LA with activity capacity.

Preoperative galactose elimination capacity predicts complications and survival after hepatic resection.

PubMed

Redaelli, Claudio A; Dufour, Jean-François; Wagner, Markus; Schilling, Martin; Hüsler, Jürg; Krähenbühl, Lukas; Büchler, Markus W; Reichen, Jürg

2002-01-01

To analyze a single center's 6-year experience with 258 consecutive patients undergoing major hepatic resection for primary or secondary malignancy of the liver, and to examine the predictive value of preoperative liver function assessment. Despite the substantial improvements in diagnostic and surgical techniques that have made liver surgery a safer procedure, careful patient selection remains mandatory to achieve good results in patients with hepatic tumors. In this prospective study, 258 patients undergoing hepatic resection were enrolled: 111 for metastases, 78 for hepatocellular carcinoma (HCC), 21 for cholangiocellular carcinoma, and 48 for other primary hepatic tumors. One hundred fifty-eight patients underwent segment-oriented liver resection, including hemihepatectomies, and 100 had subsegmental resections. Thirty-two clinical and biochemical parameters were analyzed, including liver function assessment by the galactose elimination capacity (GEC) test, a measure of hepatic functional reserve, to predict postoperative (60-day) rates of death and complications and long-term survival. All variables were determined within 5 days before surgery. Data were subjected to univariate and multivariate analysis for two patient subgroups (HCC and non-HCC). The cutoffs for GEC in both groups were predefined. Long-term survival (>60 days) was subjected to Kaplan-Meier analysis and the Cox proportional hazard model. In the entire group of 258 patients, a GEC less than 6 mg/min/kg was the only preoperative biochemical parameter that predicted postoperative complications and death by univariate and stepwise regression analysis. A GEC of more than 6 mg/min/kg was also significantly associated with longer survival. This predictive value could also be shown in the subgroup of 180 patients with tumors other than HCC. In the subgroup of 78 patients with HCC, a GEC less than 4 mg/min/kg predicted postoperative complications and death by univariate and stepwise regression analysis. Further, a GEC of more than 4 mg/min/kg was also associated with longer survival. This prospective study establishes the preoperative determination of the hepatic reserve by GEC as a strong independent and valuable predictor for short- and long-term outcome in patients with primary and secondary hepatic tumors undergoing resection.

Preoperative Galactose Elimination Capacity Predicts Complications and Survival After Hepatic Resection

PubMed Central

Redaelli, Claudio A.; Dufour, Jean-François; Wagner, Markus; Schilling, Martin; Hüsler, Jürg; Krähenbühl, Lukas; Büchler, Markus W.; Reichen, Jürg

2002-01-01

Objective To analyze a single center’s 6-year experience with 258 consecutive patients undergoing major hepatic resection for primary or secondary malignancy of the liver, and to examine the predictive value of preoperative liver function assessment. Summary Background Data Despite the substantial improvements in diagnostic and surgical techniques that have made liver surgery a safer procedure, careful patient selection remains mandatory to achieve good results in patients with hepatic tumors. Methods In this prospective study, 258 patients undergoing hepatic resection were enrolled: 111 for metastases, 78 for hepatocellular carcinoma (HCC), 21 for cholangiocellular carcinoma, and 48 for other primary hepatic tumors. One hundred fifty-eight patients underwent segment-oriented liver resection, including hemihepatectomies, and 100 had subsegmental resections. Thirty-two clinical and biochemical parameters were analyzed, including liver function assessment by the galactose elimination capacity (GEC) test, a measure of hepatic functional reserve, to predict postoperative (60-day) rates of death and complications and long-term survival. All variables were determined within 5 days before surgery. Data were subjected to univariate and multivariate analysis for two patient subgroups (HCC and non-HCC). The cutoffs for GEC in both groups were predefined. Long-term survival (>60 days) was subjected to Kaplan-Meier analysis and the Cox proportional hazard model. Results In the entire group of 258 patients, a GEC less than 6 mg/min/kg was the only preoperative biochemical parameter that predicted postoperative complications and death by univariate and stepwise regression analysis. A GEC of more than 6 mg/min/kg was also significantly associated with longer survival. This predictive value could also be shown in the subgroup of 180 patients with tumors other than HCC. In the subgroup of 78 patients with HCC, a GEC less than 4 mg/min/kg predicted postoperative complications and death by univariate and stepwise regression analysis. Further, a GEC of more than 4 mg/min/kg was also associated with longer survival. Conclusions This prospective study establishes the preoperative determination of the hepatic reserve by GEC as a strong independent and valuable predictor for short- and long-term outcome in patients with primary and secondary hepatic tumors undergoing resection. PMID:11753045

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

Determination of physical height from crown dimensions of deciduous tooth: A dental morphometric study.

PubMed

Ramanna, C; Kamath, Venkatesh V; Sharada, C; Srikanth, N

2016-01-01

Dental morphometrics is a subject of great significance in forensic odontology in identification of an individual. Use of teeth to represent a physical profile is valuable for identification of an individual. The present study aims to assess the clinical crown length (CL) of erupted deciduous teeth and height of the child. A correlation of these parameters was attempted to arrive at a mathematical equation which would formulate a ratio of tooth CL to individual height that would support in estimating the probable height of the child. About 60 children (30 males and 30 females) of age ranged from 3-6 years were included in this study. Clinical vertical CLs of the deciduous dentition (tooth numbers 51, 52, 53, 54, and 55) were calculated using digital Vernier calipers (Aerospace Ltd., Bengaluru, Karnataka, India) on the cast models. Child height was measured using a standard measuring tape. Ratios of deciduous CL to height of the child were recorded. Linear stepwise forward regression analysis was applied to predict the probability of CL of a tooth most likely to support in prediction of physical height of the child. Tabulated results showed a probable correlation between tooth CL and height of the child. Tooth CLs of deciduous upper right second molar (55) among the males, lateral incisor (52) among females, and canine (53) using the combined male and female data were statistically significant, and they approximately predicted the child height with minimal variations. Mathematically derived equations based on linear stepwise forward regression analysis using sixty children data are height prediction (derived from combined data of male and female children) = 400.558 + 90.264 (53 CL), male child height prediction (derived from data of male children) = 660.290 + 72.970 (55 CL), and female child height prediction (derived from data of female children) = -187.942 + 194.818 (52 CL). In conclusion, clinical vertical CL is an important parameter in prediction of individual height and possible identification of the individual. An extension of the similar technique to all the deciduous dentition using a larger group of children would probably give us the best options available among vertical CLs for prediction of the child height.

Using steady-state equations for transient flow calculation in natural gas pipelines

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

Maddox, R.N.; Zhou, P.

1984-04-02

Maddox and Zhou have extended their technique for calculating the unsteady-state behavior of straight gas pipelines to complex pipeline systems and networks. After developing the steady-state flow rate and pressure profile for each pipe in the network, analysts can perform the transient-state analysis in the real-time step-wise manner described for this technique.

Influence of overstory on snow depth and density in hemlock-spruce stands: implications for management of deer habitat in Southeastern Alaska.

Treesearch

Thomas A. Hanley; Cathy L. Rose

1987-01-01

Snow depth and density were measured in 33 stands of western hemlock-Sitka spruce (Tsuga heterophylla [Rat] Sarg.-Picea sitchensis [Bong.] Carr.) over a 3-year period. The stands, near Juneau, Alaska, provided broad ranges of species composition, age, over-story canopy coverage, tree density, and wood volume. Stepwise multiple regression analyses indicated that both...

Patient satisfaction in Dental Healthcare Centers.

PubMed

Ali, Dena A

2016-01-01

This study aimed to (1) measure the degree of patient satisfaction among the clinical and nonclinical dental services offered at specialty dental centers and (2) investigate the factors associated with the degree of overall satisfaction. Four hundred and ninety-seven participants from five dental centers were recruited for this study. Each participant completed a self-administered questionnaire to measure patient satisfaction with clinical and nonclinical dental services. Analysis of variance, t-tests, a general linear model, and stepwise regression analysis was applied. The respondents were generally satisfied, but internal differences were observed. The exhibited highest satisfaction with the dentists' performance, followed by the dental assistants' services, and the lowest satisfaction with the center's physical appearance and accessibility. Females, participants with less than a bachelor's degree, and younger individuals were more satisfied with the clinical and nonclinical dental services. The stepwise regression analysis revealed that the coefficient of determination (R (2)) was 40.4%. The patient satisfaction with the performance of the dentists explained 42.6% of the overall satisfaction, whereas their satisfaction with the clinical setting explained 31.5% of the overall satisfaction. Additional improvements with regard to the accessibility and physical appearance of the dental centers are needed. In addition, interventions regarding accessibility, particularly when booking an appointment, are required.

Psychophysiological responses to competition and the big five personality traits.

PubMed

Binboga, Erdal; Guven, Senol; Catıkkaş, Fatih; Bayazıt, Onur; Tok, Serdar

2012-06-01

This study examines the relationship between psychophysiological arousal, cognitive anxiety, and personality traits in young taekwondo athletes. A total of 20 male and 10 female taekwondo athletes (mean age = 18.6 years; ± 1.8) volunteered for the study. The Five Factor Personality Inventory and the state scale of the Spielberger State-Trait Anxiety Inventory (STAI) were used to measure personality and cognitive state anxiety. Electrodermal activity (EDA) was measured twice, one day and approximately one hour prior to the competition, to determine psychophysiological arousal. Descriptive statistics, Pearson product-moment correlations, and stepwise regression were used to analyze the data. Several "Big Five" facets were related to the EDA delta scores that were measured both one day and one hour before the competition. Two stepwise regressions were conducted to examine whether personality traits could significantly predict both EDA delta scores. The final model, containing only neuroticism from the Big Five factors, can significantly explain the variations in the EDA delta scores measured one day before the competition. Agreeableness can significantly explain variations in the EDA delta scores measured one hour before the competition. No relationship was found between cognitive anxiety and the EDA delta scores measured one hour before the competition. In conclusion, personality traits, especially agreeableness and neuroticism, might be useful in understanding arousal responses to competition.

Feet deformities are correlated with impaired balance and postural stability in seniors over 75

PubMed Central

Puszczalowska-Lizis, Ewa; Bujas, Przemyslaw; Omorczyk, Jaroslaw; Jandzis, Slawomir

2017-01-01

Objective Understanding the factors and mechanisms that determine balance in seniors appears vital in terms of their self-reliance and overall safety. The study aimed to determine the relationship between the features of feet structure and the indicators of postural stability in the elderly. Methods The study group comprised 80 seniors (41F, 39M; aged 75–85 years). CQ-ST podoscope and the CQ-Stab 2P two-platform posturograph were used as primary research tools. The data were analyzed based on Spearman’s rank correlation and forward stepwise regression. Results Analysis of forward stepwise regression identified the left foot length in females and Clarke’s angle of the left foot in men as significant and independent predictors of postural up to 30% of the variance of dependent variables. Conclusions Longer feet provide older women with better stability, whereas in men, the lowering of the longitudinal arch results in postural deterioration. In the elderly, the left lower limb shows greater activity in the stabilizing processes in the standing position than the right one. In gerontological rehabilitation special attention should be paid to the individually tailored, gender-specific treatment, with a view to enhancing overall safety and quality of seniors’ lives. PMID:28877185

Psychophysiological Responses to Competition and the Big Five Personality Traits

PubMed Central

Binboga, Erdal; Guven, Senol; Çatıkkaş, Fatih; Bayazıt, Onur; Tok, Serdar

2012-01-01

This study examines the relationship between psychophysiological arousal, cognitive anxiety, and personality traits in young taekwondo athletes. A total of 20 male and 10 female taekwondo athletes (mean age = 18.6 years; ± 1.8) volunteered for the study. The Five Factor Personality Inventory and the state scale of the Spielberger State-Trait Anxiety Inventory (STAI) were used to measure personality and cognitive state anxiety. Electrodermal activity (EDA) was measured twice, one day and approximately one hour prior to the competition, to determine psychophysiological arousal. Descriptive statistics, Pearson product-moment correlations, and stepwise regression were used to analyze the data. Several “Big Five” facets were related to the EDA delta scores that were measured both one day and one hour before the competition. Two stepwise regressions were conducted to examine whether personality traits could significantly predict both EDA delta scores. The final model, containing only neuroticism from the Big Five factors, can significantly explain the variations in the EDA delta scores measured one day before the competition. Agreeableness can significantly explain variations in the EDA delta scores measured one hour before the competition. No relationship was found between cognitive anxiety and the EDA delta scores measured one hour before the competition. In conclusion, personality traits, especially agreeableness and neuroticism, might be useful in understanding arousal responses to competition. PMID:23486906

Motor Nerve Conduction Velocity In Postmenopausal Women with Peripheral Neuropathy.

PubMed

Singh, Akanksha; Asif, Naiyer; Singh, Paras Nath; Hossain, Mohd Mobarak

2016-12-01

The post-menopausal phase is characterized by a decline in the serum oestrogen and progesterone levels. This phase is also associated with higher incidence of peripheral neuropathy. To explore the relationship between the peripheral motor nerve status and serum oestrogen and progesterone levels through assessment of Motor Nerve Conduction Velocity (MNCV) in post-menopausal women with peripheral neuropathy. This cross-sectional study was conducted at Jawaharlal Nehru Medical College during 2011-2013. The study included 30 post-menopausal women with peripheral neuropathy (age: 51.4±7.9) and 30 post-menopausal women without peripheral neuropathy (control) (age: 52.5±4.9). They were compared for MNCV in median, ulnar and common peroneal nerves and serum levels of oestrogen and progesterone estimated through enzyme immunoassays. To study the relationship between hormone levels and MNCV, a stepwise linear regression analysis was done. The post-menopausal women with peripheral neuropathy had significantly lower MNCV and serum oestrogen and progesterone levels as compared to control subjects. Stepwise linear regression analysis showed oestrogen with main effect on MNCV. The findings of the present study suggest that while the post-menopausal age group is at a greater risk of peripheral neuropathy, it is the decline in the serum estrogen levels which is critical in the development of peripheral neuropathy.

STEP and STEPSPL: Computer programs for aerodynamic model structure determination and parameter estimation

NASA Technical Reports Server (NTRS)

Batterson, J. G.

1986-01-01

The successful parametric modeling of the aerodynamics for an airplane operating at high angles of attack or sideslip is performed in two phases. First the aerodynamic model structure must be determined and second the associated aerodynamic parameters (stability and control derivatives) must be estimated for that model. The purpose of this paper is to document two versions of a stepwise regression computer program which were developed for the determination of airplane aerodynamic model structure and to provide two examples of their use on computer generated data. References are provided for the application of the programs to real flight data. The two computer programs that are the subject of this report, STEP and STEPSPL, are written in FORTRAN IV (ANSI l966) compatible with a CDC FTN4 compiler. Both programs are adaptations of a standard forward stepwise regression algorithm. The purpose of the adaptation is to facilitate the selection of a adequate mathematical model of the aerodynamic force and moment coefficients of an airplane from flight test data. The major difference between STEP and STEPSPL is in the basis for the model. The basis for the model in STEP is the standard polynomial Taylor's series expansion of the aerodynamic function about some steady-state trim condition. Program STEPSPL utilizes a set of spline basis functions.

Relation between trinucleotide GAA repeat length and sensory neuropathy in Friedreich's ataxia.

PubMed

Santoro, L; De Michele, G; Perretti, A; Crisci, C; Cocozza, S; Cavalcanti, F; Ragno, M; Monticelli, A; Filla, A; Caruso, G

1999-01-01

To verify if GAA expansion size in Friedreich's ataxia could account for the severity of sensory neuropathy. Retrospective study of 56 patients with Friedreich's ataxia selected according to homozygosity for GAA expansion and availability of electrophysiological findings. Orthodromic sensory conduction velocity in the median nerve was available in all patients and that of the tibial nerve in 46 of them. Data of sural nerve biopsy and of a morphometric analysis were available in 12 of the selected patients. The sensory action potential amplitude at the wrist (wSAP) and at the medial malleolus (m mal SAP) and the percentage of myelinated fibres with diameter larger than 7, 9, and 11 microm in the sural nerve were correlated with disease duration and GAA expansion size on the shorter (GAA1) and larger (GAA2) expanded allele in each pair. Pearson's correlation test and stepwise multiple regression were used for statistical analysis. A significant inverse correlation between GAA1 size and wSAP, m mal SAP, and percentage of myelinated fibres was found. Stepwise multiple regression showed that GAA1 size significantly affects electrophysiological and morphometric data, whereas duration of disease has no effect. The data suggest that the severity of the sensory neuropathy is probably genetically determined and that it is not progressive.

Quantifying Parkinson's disease finger-tapping severity by extracting and synthesizing finger motion properties.

PubMed

Sano, Yuko; Kandori, Akihiko; Shima, Keisuke; Yamaguchi, Yuki; Tsuji, Toshio; Noda, Masafumi; Higashikawa, Fumiko; Yokoe, Masaru; Sakoda, Saburo

2016-06-01

We propose a novel index of Parkinson's disease (PD) finger-tapping severity, called "PDFTsi," for quantifying the severity of symptoms related to the finger tapping of PD patients with high accuracy. To validate the efficacy of PDFTsi, the finger-tapping movements of normal controls and PD patients were measured by using magnetic sensors, and 21 characteristics were extracted from the finger-tapping waveforms. To distinguish motor deterioration due to PD from that due to aging, the aging effect on finger tapping was removed from these characteristics. Principal component analysis (PCA) was applied to the age-normalized characteristics, and principal components that represented the motion properties of finger tapping were calculated. Multiple linear regression (MLR) with stepwise variable selection was applied to the principal components, and PDFTsi was calculated. The calculated PDFTsi indicates that PDFTsi has a high estimation ability, namely a mean square error of 0.45. The estimation ability of PDFTsi is higher than that of the alternative method, MLR with stepwise regression selection without PCA, namely a mean square error of 1.30. This result suggests that PDFTsi can quantify PD finger-tapping severity accurately. Furthermore, the result of interpreting a model for calculating PDFTsi indicated that motion wideness and rhythm disorder are important for estimating PD finger-tapping severity.

Patient satisfaction in Dental Healthcare Centers

PubMed Central

Ali, Dena A.

2016-01-01

Objectives: This study aimed to (1) measure the degree of patient satisfaction among the clinical and nonclinical dental services offered at specialty dental centers and (2) investigate the factors associated with the degree of overall satisfaction. Materials and Methods: Four hundred and ninety-seven participants from five dental centers were recruited for this study. Each participant completed a self-administered questionnaire to measure patient satisfaction with clinical and nonclinical dental services. Analysis of variance, t-tests, a general linear model, and stepwise regression analysis was applied. Results: The respondents were generally satisfied, but internal differences were observed. The exhibited highest satisfaction with the dentists’ performance, followed by the dental assistants’ services, and the lowest satisfaction with the center's physical appearance and accessibility. Females, participants with less than a bachelor's degree, and younger individuals were more satisfied with the clinical and nonclinical dental services. The stepwise regression analysis revealed that the coefficient of determination (R2) was 40.4%. The patient satisfaction with the performance of the dentists explained 42.6% of the overall satisfaction, whereas their satisfaction with the clinical setting explained 31.5% of the overall satisfaction. Conclusion: Additional improvements with regard to the accessibility and physical appearance of the dental centers are needed. In addition, interventions regarding accessibility, particularly when booking an appointment, are required. PMID:27403045

[Key physical parameters of hawthorn leaf granules by stepwise regression analysis method].

PubMed

Jiang, Qie-Ying; Zeng, Rong-Gui; Li, Zhe; Luo, Juan; Zhao, Guo-Wei; Lv, Dan; Liao, Zheng-Gen

2017-05-01

The purpose of this study was to investigate the effect of key physical properties of hawthorn leaf granule on its dissolution behavior. Hawthorn leaves extract was utilized as a model drug. The extract was mixed with microcrystalline cellulose or starch with the same ratio by using different methods. Appropriate amount of lubricant and disintegrating agent was added into part of the mixed powder, and then the granules were prepared by using extrusion granulation and high shear granulation. The granules dissolution behavior was evaluated by using equilibrium dissolution quantity and dissolution rate constant of the hypericin as the indicators. Then the effect of physical properties on dissolution behavior was analyzed through the stepwise regression analysis method. The equilibrium dissolution quantity of hypericin and adsorption heat constant in hawthorn leaves were positively correlated with the monolayer adsorption capacity and negatively correlated with the moisture absorption rate constant. The dissolution rate constants were decreased with the increase of Hausner rate, monolayer adsorption capacity and adsorption heat constant, and were increased with the increase of Carr index and specific surface area. Adsorption heat constant, monolayer adsorption capacity, moisture absorption rate constant, Carr index and specific surface area were the key physical properties of hawthorn leaf granule to affect its dissolution behavior. Copyright© by the Chinese Pharmaceutical Association.

Predicting Retention Times of Naturally Occurring Phenolic Compounds in Reversed-Phase Liquid Chromatography: A Quantitative Structure-Retention Relationship (QSRR) Approach

PubMed Central

Akbar, Jamshed; Iqbal, Shahid; Batool, Fozia; Karim, Abdul; Chan, Kim Wei

2012-01-01

Quantitative structure-retention relationships (QSRRs) have successfully been developed for naturally occurring phenolic compounds in a reversed-phase liquid chromatographic (RPLC) system. A total of 1519 descriptors were calculated from the optimized structures of the molecules using MOPAC2009 and DRAGON softwares. The data set of 39 molecules was divided into training and external validation sets. For feature selection and mapping we used step-wise multiple linear regression (SMLR), unsupervised forward selection followed by step-wise multiple linear regression (UFS-SMLR) and artificial neural networks (ANN). Stable and robust models with significant predictive abilities in terms of validation statistics were obtained with negation of any chance correlation. ANN models were found better than remaining two approaches. HNar, IDM, Mp, GATS2v, DISP and 3D-MoRSE (signals 22, 28 and 32) descriptors based on van der Waals volume, electronegativity, mass and polarizability, at atomic level, were found to have significant effects on the retention times. The possible implications of these descriptors in RPLC have been discussed. All the models are proven to be quite able to predict the retention times of phenolic compounds and have shown remarkable validation, robustness, stability and predictive performance. PMID:23203132

Predictors of competitive achievement among pubescent synchronized swimmers: an analysis of the solo-figure competition.

PubMed

Peric, M; Cavar, M; Zenic, N; Sekulic, D; Sajber, D

2014-02-01

This study examined the applicability of sport-specific fitness tests (SSTs), anthropometrics, and respiratory parameters in predicting competitive results among pubescent synchronized swimmers. A total of 25 synchronized swimmers (16-17 years; 166.2 ± 5.4 cm; and 58.4 ± 4.3 kg) volunteered for this study. The independent variables were body mass, body height, Body Mass Index (BMI), body fat percentage (BF%), lean body mass percentage, respiratory variables, and four SSTs (two specific power tests plus one aerobic- and one anaerobic-endurance test). The dependent variable was competitive achievement in the solo figure competition. The reliability analyses, Pearson's correlation coefficient and forward stepwise regression were calculated. The SSTs were reliable for testing fitness status among pubescent synchronized swimmers. The forward stepwise regression retained two SSTs, BF% and forced vital capacity (FVC, relative for age and stature) in a set of predictors of competitive achievement. Significant Beta coefficients are found for aerobic-endurance, SST and FVC. The sport-specific measure of aerobic endurance and FVC appropriately predicted competitive achievement with regard to the figures used in the competition when competitive results (the dependent variable) were obtained. Athletes and coaches should be aware of the probable negative influence of very low body fat levels on competitive achievement.

Analysis of Classical Time-Trial Performance and Technique-Specific Physiological Determinants in Elite Female Cross-Country Skiers.

PubMed

Sandbakk, Øyvind; Losnegard, Thomas; Skattebo, Øyvind; Hegge, Ann M; Tønnessen, Espen; Kocbach, Jan

2016-01-01

The present study investigated the contribution of performance on uphill, flat, and downhill sections to overall performance in an international 10-km classical time-trial in elite female cross-country skiers, as well as the relationships between performance on snow and laboratory-measured physiological variables in the double poling (DP) and diagonal (DIA) techniques. Ten elite female cross-country skiers were continuously measured by a global positioning system device during an international 10-km cross-country skiing time-trial in the classical technique. One month prior to the race, all skiers performed a 5-min submaximal and 3-min self-paced performance test while roller skiing on a treadmill, both in the DP and DIA techniques. The time spent on uphill (r = 0.98) and flat (r = 0.91) sections of the race correlated most strongly with the overall 10-km performance (both p < 0.05). Approximately 56% of the racing time was spent uphill, and stepwise multiple regression revealed that uphill time explained 95.5% of the variance in overall performance (p < 0.001). Distance covered during the 3-min roller-skiing test and body-mass normalized peak oxygen uptake (VO2peak) in both techniques showed the strongest correlations with overall time-trial performance (r = 0.66-0.78), with DP capacity tending to have greatest impact on the flat and DIA capacity on uphill terrain (all p < 0.05). Our present findings reveal that the time spent uphill most strongly determine classical time-trial performance, and that the major portion of the performance differences among elite female cross-country skiers can be explained by variations in technique-specific aerobic power.

Analysis of Classical Time-Trial Performance and Technique-Specific Physiological Determinants in Elite Female Cross-Country Skiers

PubMed Central

Sandbakk, Øyvind; Losnegard, Thomas; Skattebo, Øyvind; Hegge, Ann M.; Tønnessen, Espen; Kocbach, Jan

2016-01-01

The present study investigated the contribution of performance on uphill, flat, and downhill sections to overall performance in an international 10-km classical time-trial in elite female cross-country skiers, as well as the relationships between performance on snow and laboratory-measured physiological variables in the double poling (DP) and diagonal (DIA) techniques. Ten elite female cross-country skiers were continuously measured by a global positioning system device during an international 10-km cross-country skiing time-trial in the classical technique. One month prior to the race, all skiers performed a 5-min submaximal and 3-min self-paced performance test while roller skiing on a treadmill, both in the DP and DIA techniques. The time spent on uphill (r = 0.98) and flat (r = 0.91) sections of the race correlated most strongly with the overall 10-km performance (both p < 0.05). Approximately 56% of the racing time was spent uphill, and stepwise multiple regression revealed that uphill time explained 95.5% of the variance in overall performance (p < 0.001). Distance covered during the 3-min roller-skiing test and body-mass normalized peak oxygen uptake (VO2peak) in both techniques showed the strongest correlations with overall time-trial performance (r = 0.66–0.78), with DP capacity tending to have greatest impact on the flat and DIA capacity on uphill terrain (all p < 0.05). Our present findings reveal that the time spent uphill most strongly determine classical time-trial performance, and that the major portion of the performance differences among elite female cross-country skiers can be explained by variations in technique-specific aerobic power. PMID:27536245

Serum chemerin levels are independently associated with quality of life in colorectal cancer survivors: A pilot study

PubMed Central

Lee, Jee-Yon; Lee, Mi-Kyung; Kim, Nam-Kyu; Chu, Sang-Hui; Lee, Duk-Chul; Lee, Hye-Sun

2017-01-01

Background Colorectal cancer (CRC) survivors are known to experience various symptoms that significantly affect their quality of life (QOL); therefore, it is important to identify clinical markers related with CRC survivor QOL. Here we investigated the relationship between serum chemerin levels, a newly identified proinflammatory adipokine, and QOL in CRC survivors. Methods A data of total of 110 CRC survivors were analysed in the study. Serum chemerin levels were measured with an enzyme immunoassay analyser. Functional Assessment of Cancer Therapy (FACT) scores were used as an indicator of QOL in CRC survivors. Results Weak but not negligible relationships were observed between serum chemerin levels and FACT-General (G) (r = -0.22, p<0.02), FACT-Colorectal cancer (C) (r = -0.23, p<0.02) and FACT-Fatigue (F) scores (r = -0.27, p<0.01) after adjusting for confounding factors. Both stepwise and enter method multiple linear regression analyses confirmed that serum chemerin levels were independently associated with FACT-G (stepwise: β = -0.15, p<0.01; enter: β = -0.12, p = 0.02), FACT-C (stepwise: β = -0.19, p<0.01; enter; β = -0.14, p = 0.02) and FACT-F scores (stepwise: β = -0.23, p<0.01; enter: β = -0.20, p<0.01). Conclusions Our results demonstrate a weak inverse relationship between serum chemerin and CRC survivor QOL. Although it is impossible to determine causality, our findings suggest that serum chemerin levels may have a significant association with CRC survivor QOL. Further prospective studies are required to confirm the clinical significance of our pilot study. PMID:28475614

Stepwise and Pulse Transient Methods of Thermophysical Parameters Measurement

NASA Astrophysics Data System (ADS)

Malinarič, Svetozár; Dieška, Peter

2016-12-01

Stepwise transient and pulse transient methods are experimental techniques for measuring the thermal diffusivity and conductivity of solid materials. Theoretical models and experimental apparatus are presented, and the influence of the heat source capacity and the heat transfer coefficient is investigated using the experiment simulation. The specimens from low-density polyethylene (LDPE) and polymethylmethacrylate (PMMA) were measured by both methods. Coefficients of variation were better than 0.9 % for LDPE and 2.8 % for PMMA measurements. The time dependence of the temperature response to the input heat flux showed a small drop, which was caused by thermoelastic wave generated by thermal expansions of the heat source.

Predicting the need for muscle flap salvage after open groin vascular procedures: a clinical assessment tool.

PubMed

Fischer, John P; Nelson, Jonas A; Shang, Eric K; Wink, Jason D; Wingate, Nicholas A; Woo, Edward Y; Jackson, Benjamin M; Kovach, Stephen J; Kanchwala, Suhail

2014-12-01

Groin wound complications after open vascular surgery procedures are common, morbid, and costly. The purpose of this study was to generate a simple, validated, clinically usable risk assessment tool for predicting groin wound morbidity after infra-inguinal vascular surgery. A retrospective review of consecutive patients undergoing groin cutdowns for femoral access between 2005-2011 was performed. Patients necessitating salvage flaps were compared to those who did not, and a stepwise logistic regression was performed and validated using a bootstrap technique. Utilising this analysis, a simplified risk score was developed to predict the risk of developing a wound which would necessitate salvage. A total of 925 patients were included in the study. The salvage flap rate was 11.2% (n = 104). Predictors determined by logistic regression included prior groin surgery (OR = 4.0, p < 0.001), prosthetic graft (OR = 2.7, p < 0.001), coronary artery disease (OR = 1.8, p = 0.019), peripheral arterial disease (OR = 5.0, p < 0.001), and obesity (OR = 1.7, p = 0.039). Based upon the respective logistic coefficients, a simplified scoring system was developed to enable the preoperative risk stratification regarding the likelihood of a significant complication which would require a salvage muscle flap. The c-statistic for the regression demonstrated excellent discrimination at 0.89. This study presents a simple, internally validated risk assessment tool that accurately predicts wound morbidity requiring flap salvage in open groin vascular surgery patients. The preoperatively high-risk patient can be identified and selectively targeted as a candidate for a prophylactic muscle flap.

Comparison of Xenon-Enhanced Area-Detector CT and Krypton Ventilation SPECT/CT for Assessment of Pulmonary Functional Loss and Disease Severity in Smokers.

PubMed

Ohno, Yoshiharu; Fujisawa, Yasuko; Takenaka, Daisuke; Kaminaga, Shigeo; Seki, Shinichiro; Sugihara, Naoki; Yoshikawa, Takeshi

2018-02-01

The objective of this study was to compare the capability of xenon-enhanced area-detector CT (ADCT) performed with a subtraction technique and coregistered 81m Kr-ventilation SPECT/CT for the assessment of pulmonary functional loss and disease severity in smokers. Forty-six consecutive smokers (32 men and 14 women; mean age, 67.0 years) underwent prospective unenhanced and xenon-enhanced ADCT, 81m Kr-ventilation SPECT/CT, and pulmonary function tests. Disease severity was evaluated according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification. CT-based functional lung volume (FLV), the percentage of wall area to total airway area (WA%), and ventilated FLV on xenon-enhanced ADCT and SPECT/CT were calculated for each smoker. All indexes were correlated with percentage of forced expiratory volume in 1 second (%FEV 1 ) using step-wise regression analyses, and univariate and multivariate logistic regression analyses were performed. In addition, the diagnostic accuracy of the proposed model was compared with that of each radiologic index by means of McNemar analysis. Multivariate logistic regression showed that %FEV 1 was significantly affected (r = 0.77, r 2 = 0.59) by two factors: the first factor, ventilated FLV on xenon-enhanced ADCT (p < 0.0001); and the second factor, WA% (p = 0.004). Univariate logistic regression analyses indicated that all indexes significantly affected GOLD classification (p < 0.05). Multivariate logistic regression analyses revealed that ventilated FLV on xenon-enhanced ADCT and CT-based FLV significantly influenced GOLD classification (p < 0.0001). The diagnostic accuracy of the proposed model was significantly higher than that of ventilated FLV on SPECT/CT (p = 0.03) and WA% (p = 0.008). Xenon-enhanced ADCT is more effective than 81m Kr-ventilation SPECT/CT for the assessment of pulmonary functional loss and disease severity.

Soil Cd, Cr, Cu, Ni, Pb and Zn sorption and retention models using SVM: Variable selection and competitive model.

PubMed

González Costa, J J; Reigosa, M J; Matías, J M; Covelo, E F

2017-09-01

The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in soils. To that extent, the sorption and retention of these metals were studied and the soil characterization was performed separately. Multiple stepwise regression was used to produce multivariate models with linear techniques and with support vector machines, all of which included 15 explanatory variables characterizing soils. When the R-squared values are represented, two different groups are noticed. Cr, Cu and Pb sorption and retention show a higher R-squared; the most explanatory variables being humified organic matter, Al oxides and, in some cases, cation-exchange capacity (CEC). The other group of metals (Cd, Ni and Zn) shows a lower R-squared, and clays are the most explanatory variables, including a percentage of vermiculite and slime. In some cases, quartz, plagioclase or hematite percentages also show some explanatory capacity. Support Vector Machine (SVM) regression shows that the different models are not as regular as in multiple regression in terms of number of variables, the regression for nickel adsorption being the one with the highest number of variables in its optimal model. On the other hand, there are cases where the most explanatory variables are the same for two metals, as it happens with Cd and Cr adsorption. A similar adsorption mechanism is thus postulated. These patterns of the introduction of variables in the model allow us to create explainability sequences. Those which are the most similar to the selectivity sequences obtained by Covelo (2005) are Mn oxides in multiple regression and change capacity in SVM. Among all the variables, the only one that is explanatory for all the metals after applying the maximum parsimony principle is the percentage of sand in the retention process. In the competitive model arising from the aforementioned sequences, the most intense competitiveness for the adsorption and retention of different metals appears between Cr and Cd, Cu and Zn in multiple regression; and between Cr and Cd in SVM regression. Copyright © 2017 Elsevier B.V. All rights reserved.

A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes.

PubMed

Mushkudiani, Nino A; Hukkelhoven, Chantal W P M; Hernández, Adrián V; Murray, Gordon D; Choi, Sung C; Maas, Andrew I R; Steyerberg, Ewout W

2008-04-01

To describe the modeling techniques used for early prediction of outcome in traumatic brain injury (TBI) and to identify aspects for potential improvements. We reviewed key methodological aspects of studies published between 1970 and 2005 that proposed a prognostic model for the Glasgow Outcome Scale of TBI based on admission data. We included 31 papers. Twenty-four were single-center studies, and 22 reported on fewer than 500 patients. The median of the number of initially considered predictors was eight, and on average five of these were selected for the prognostic model, generally including age, Glasgow Coma Score (or only motor score), and pupillary reactivity. The most common statistical technique was logistic regression with stepwise selection of predictors. Model performance was often quantified by accuracy rate rather than by more appropriate measures such as the area under the receiver-operating characteristic curve. Model validity was addressed in 15 studies, but mostly used a simple split-sample approach, and external validation was performed in only four studies. Although most models agree on the three most important predictors, many were developed on small sample sizes within single centers and hence lack generalizability. Modeling strategies have to be improved, and include external validation.

An Evaluation Technique for an F/A-18 Aircraft Loads Model Using F/A-18 Systems Research Aircraft Flight Data

NASA Technical Reports Server (NTRS)

Olney, Candida D.; Hillebrandt, Heather; Reichenbach, Eric Y.

2000-01-01

A limited evaluation of the F/A-18 baseline loads model was performed on the Systems Research Aircraft at NASA Dryden Flight Research Center (Edwards, California). Boeing developed the F/A-18 loads model using a linear aeroelastic analysis in conjunction with a flight simulator to determine loads at discrete locations on the aircraft. This experiment was designed so that analysis of doublets could be used to establish aircraft aerodynamic and loads response at 20 flight conditions. Instrumentation on the right outboard leading edge flap, left aileron, and left stabilator measured the hinge moment so that comparisons could be made between in-flight-measured hinge moments and loads model-predicted values at these locations. Comparisons showed that the difference between the loads model-predicted and in-flight-measured hinge moments was up to 130 percent of the flight limit load. A stepwise regression technique was used to determine new loads derivatives. These derivatives were placed in the loads model, which reduced the error to within 10 percent of the flight limit load. This paper discusses the flight test methodology, a process for determining loads coefficients, and the direct comparisons of predicted and measured hinge moments and loads coefficients.

Estimation of both optical and nonoptical surface water quality parameters using Landsat 8 OLI imagery and statistical techniques

NASA Astrophysics Data System (ADS)

Sharaf El Din, Essam; Zhang, Yun

2017-10-01

Traditional surface water quality assessment is costly, labor intensive, and time consuming; however, remote sensing has the potential to assess surface water quality because of its spatiotemporal consistency. Therefore, estimating concentrations of surface water quality parameters (SWQPs) from satellite imagery is essential. Remote sensing estimation of nonoptical SWQPs, such as chemical oxygen demand (COD), biochemical oxygen demand (BOD), and dissolved oxygen (DO), has not yet been performed because they are less likely to affect signals measured by satellite sensors. However, concentrations of nonoptical variables may be correlated with optical variables, such as turbidity and total suspended sediments, which do affect the reflected radiation. In this context, an indirect relationship between satellite multispectral data and COD, BOD, and DO can be assumed. Therefore, this research attempts to develop an integrated Landsat 8 band ratios and stepwise regression to estimate concentrations of both optical and nonoptical SWQPs. Compared with previous studies, a significant correlation between Landsat 8 surface reflectance and concentrations of SWQPs was achieved and the obtained coefficient of determination (R2)>0.85. These findings demonstrated the possibility of using our technique to develop models to estimate concentrations of SWQPs and to generate spatiotemporal maps of SWQPs from Landsat 8 imagery.

Spatial and temporal variability of reference evapotranspiration and influenced meteorological factors in the Jialing River Basin, China

NASA Astrophysics Data System (ADS)

Herath, Imali Kaushalya; Ye, Xuchun; Wang, Jianli; Bouraima, Abdel-Kabirou

2018-02-01

Reference evapotranspiration (ETr) is one of the important parameters in the hydrological cycle. The spatio-temporal variation of ETr and other meteorological parameters that influence ETr were investigated in the Jialing River Basin (JRB), China. The ETr was estimated using the CROPWAT 8.0 computer model based on the Penman-Montieth equation for the period 1964-2014. Mean temperature (MT), relative humidity (RH), sunshine duration (SD), and wind speed (WS) were the main input parameters of CROPWAT while 12 meteorological stations were evaluated. Linear regression and Mann-Kendall methods were applied to study the spatio-temporal trends while the inverse distance weighted (IDW) method was used to identify the spatial distribution of ETr. Stepwise regression and partial correlation methods were used to identify the meteorological variables that most significantly influenced the changes in ETr. The highest annual ETr was found in the northern part of the basin, whereas the lowest rate was recorded in the western part. In the autumn, the highest ETr was recorded in the southeast part of JRB. The annual ETr reflected neither significant increasing nor decreasing trends. Except for the summer, ETr is slightly increasing in other seasons. The MT significantly increased whereas SD and RH were significantly decreased during the 50-year period. Partial correlation and stepwise regression methods found that the impact of meteorological parameters on ETr varies on an annual and seasonal basis while SD, MT, and RH contributed to the changes of annual and seasonal ETr in the JRB.

Reliability of a Bayesian network to predict an elevated aldosterone-to-renin ratio.

PubMed

Ducher, Michel; Mounier-Véhier, Claire; Lantelme, Pierre; Vaisse, Bernard; Baguet, Jean-Philippe; Fauvel, Jean-Pierre

2015-05-01

Resistant hypertension is common, mainly idiopathic, but sometimes related to primary aldosteronism. Thus, most hypertension specialists recommend screening for primary aldosteronism. To optimize the selection of patients whose aldosterone-to-renin ratio (ARR) is elevated from simple clinical and biological characteristics. Data from consecutive patients referred between 1 June 2008 and 30 May 2009 were collected retrospectively from five French 'European excellence hypertension centres' institutional registers. Patients were included if they had at least one of: onset of hypertension before age 40 years, resistant hypertension, history of hypokalaemia, efficient treatment by spironolactone, and potassium supplementation. An ARR>32 ng/L and aldosterone>160 ng/L in patients treated without agents altering the renin-angiotensin system was considered as elevated. Bayesian network and stepwise logistic regression were used to predict an elevated ARR. Of 334 patients, 89 were excluded (31 for incomplete data, 32 for taking agents that alter the renin-angiotensin system and 26 for other reasons). Among 245 included patients, 110 had an elevated ARR. Sensitivity reached 100% or 63.3% using Bayesian network or logistic regression, respectively, and specificity reached 89.6% or 67.2%, respectively. The area under the receiver-operating-characteristic curve obtained with the Bayesian network was significantly higher than that obtained by stepwise regression (0.93±0.02 vs. 0.70±0.03; P<0.001). In hypertension centres, Bayesian network efficiently detected patients with an elevated ARR. An external validation study is required before use in primary clinical settings. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland.

PubMed

Kolasa-Wiecek, Alicja

2015-04-01

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R2=0.90. For N2O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2O emission is the peat and wood fuel consumption. Copyright © 2015. Published by Elsevier B.V.

Differentiating major depressive disorder in youths with attention deficit hyperactivity disorder.

PubMed

Diler, Rasim Somer; Daviss, W Burleson; Lopez, Adriana; Axelson, David; Iyengar, Satish; Birmaher, Boris

2007-09-01

Youths with attention deficit hyperactivity disorders (ADHD) frequently have comorbid major depressive disorders (MDD) sharing overlapping symptoms. Our objective was to examine which depressive symptoms best discriminate MDD among youths with ADHD. One-hundred-eleven youths with ADHD (5.2-17.8 years old) and their parents completed interviews with the K-SADS-PL and respective versions of the child or the parent Mood and Feelings Questionnaire (MFQ-C, MFQ-P). Controlling for group differences, logistic regression was used to calculate odds ratios reflecting the accuracy with which various depressive symptoms on the MFQ-C or MFQ-P discriminated MDD. Stepwise logistic regression then identified depressive symptoms that best discriminated the groups with and without MDD, using cross-validated misclassification rate as the criterion. Symptoms that discriminated youths with MDD (n=18) from those without MDD (n=93) were 4 of 6 mood/anhedonia symptoms, all 14 depressed cognition symptoms, and only 3 of 11 physical/vegetative symptoms. Mild irritability, miserable/unhappy moods, and symptoms related to sleep, appetite, energy levels and concentration did not discriminate MDD. A stepwise logistic regression correctly classified 89% of the comorbid MDD subjects, with only age, anhedonia at school, thoughts about killing self, thoughts that bad things would happen, and talking more slowly remaining in the final model. Results of this study may not generalize to community samples because subjects were drawn largely from a university-based outpatient psychiatric clinic. These findings stress the importance of social withdrawal, anhedonia, depressive cognitions, suicidal thoughts, and psychomotor retardation when trying to identify MDD among ADHD youths.

Identification of Key Beliefs Explaining Male Circumcision Motivation Among Adolescent Boys in Zimbabwe: Targets for Behavior Change Communication.

PubMed

Kasprzyk, Danuta; Tshimanga, Mufuta; Hamilton, Deven T; Gorn, Gerald J; Montaño, Daniel E

2018-02-01

Male circumcision (MC) significantly reduces HIV acquisition among men, leading WHO/UNAIDS to recommend high HIV and low MC prevalence countries circumcise 80% of adolescents and men age 15-49. Despite significant investment to increase MC capacity only 27% of the goal has been achieved in Zimbabwe. To increase adoption, research to create evidence-based messages is greatly needed. The Integrated Behavioral Model (IBM) was used to investigate factors affecting MC motivation among adolescents. Based on qualitative elicitation study results a survey was designed and administered to a representative sample of 802 adolescent boys aged 13-17 in two urban and two rural areas in Zimbabwe. Multiple regression analysis found all six IBM constructs (2 attitude, 2 social influence, 2 personal agency) significantly explained MC intention (R 2  = 0.55). Stepwise regression analysis of beliefs underlying each IBM belief-based construct found 9 behavioral, 6 injunctive norm, 2 descriptive norm, 5 efficacy, and 8 control beliefs significantly explained MC intention. A final stepwise regression of all the significant IBM construct beliefs identified 12 key beliefs best explaining intention. Similar analyses were carried out with subgroups of adolescents by urban-rural and age. Different sets of behavioral, normative, efficacy, and control beliefs were significant for each sub-group. This study demonstrates the application of theory-driven research to identify evidence-based targets for the design of effective MC messages for interventions to increase adolescents' motivation. Incorporating these findings into communication campaigns is likely to improve demand for MC.

The effect of various factors on the dental arch relationship in non-syndromic unilateral cleft lip and palate children assessed by new approach: a retrospective study.

PubMed

Haque, Sanjida; Alam, Mohammad Khursheed; Khamis, Mohd Fadhli

2017-05-06

Cleft lip and palate (CLP) is one of the most common birth defects. Multiple factors are believed to be responsible for an unfavorable dental arch relationship in CLP. Facial growth (maxillary) retardation, which results in class III malocclusion, is the primary challenge that CLP patients face. Phenotype factors and postnatal treatment factors influence treatment outcomes in unilateral cleft lip and palate (UCLP) children, which has led to a great diversity in protocols and surgical techniques by various cleft groups worldwide. The aim of this study was to illustrate the dental arch relationship (DAR) and palatal morphology (PM) of UCLP in Bangladeshi children and to explore the various factors that are responsible for poor DAR and PM. Dental models of 84 subjects were taken before orthodontic treatment and alveolar bone grafting. The mean age was 7.69 (SD 2.46) years. The DAR and PM were assessed blindly by five raters using the EUROCRAN index (EI). Kappa statistics was used to evaluate the intra- and inter-examiner agreement, chi square was used to assess the associations, and logistic regression analysis was used to explore the responsible factors that affect DAR and PM. The mean EUROCRAN scores were 2.44 and 1.93 for DAR and PM, respectively. Intra- and inter-examiner agreement was moderate to very good. Using crude and stepwise backward regression analyses, significant associations were found between the modified Millard technique (P = 0.047, P = 0.034 respectively) of cheiloplasty and unfavorable DAR. Complete UCLP (P = 0.017) was also significantly correlated with unfavorable DAR. The PM showed a significant association with the type of cleft, type of cheiloplasty and type of palatoplasty. This multivariate study determined that the complete type of UCLP and the modified Millard technique of cheiloplasty had significantly unfavorable effects on both the DAR and PM.

Ecosystem-atmosphere exchange of CO2 in a temperate herbaceous peatland in the Sanjiang Plain of northeast China

USGS Publications Warehouse

Zhu, Xiaoyan; Song, Changchun; Swarzenski, Christopher M.; Guo, Yuedong; Zhang, Xinhow; Wang, Jiaoyue

2015-01-01

Northern peatlands contain a considerable share of the terrestrial carbon pool, which will be affected by future climatic variability. Using the static chamber technique, we investigated ecosystem respiration and soil respiration over two growing seasons (2012 and 2013) in a Carex lasiocarpa-dominated peatland in the Sanjiang Plain in China. We synchronously monitored the environmental factors controlling CO2 fluxes. Ecosystem respiration during these two growing seasons ranged from 33.3 to 506.7 mg CO2–C m−2 h−1. Through step-wise regression, variations in soil temperature at 10 cm depth alone explained 73.7% of the observed variance in log10(ER). The mean Q10 values ranged from 2.1 to 2.9 depending on the choice of depth where soil temperature was measured. The Q10 value at the 10 cm depth (2.9) appears to be a good representation for herbaceous peatland in the Sanjiang Plain when applying field-estimation based Q10values to current terrestrial ecosystem models due to the most optimized regression coefficient (63.2%). Soil respiration amounted to 57% of ecosystem respiration and played a major role in peatland carbon balance in our study. Emphasis on ecosystem respiration from temperate peatlands in the Sanjiang Plain will improve our basic understanding of carbon exchange between peatland ecosystem and the atmosphere.

Timescale dependence of environmental controls on methane efflux from Poyang Hu, China

NASA Astrophysics Data System (ADS)

Liu, Lixiang; Xu, Ming; Li, Renqiang; Shao, Rui

2017-04-01

Lakes are an important natural source of CH4 to the atmosphere. However, the multi-seasonal CH4 efflux from lakes has been rarely studied. In this study, the CH4 efflux from Poyang Hu, the largest freshwater lake in China, was measured monthly over a 4-year period by using the floating-chamber technique. The mean annual CH4 efflux throughout the 4 years was 0.54 mmol m-2 day-1, ranging from 0.47 to 0.60 mmol m-2 day-1. The CH4 efflux had a high seasonal variation with an average summer (June to August) efflux of 1.34 mmol m-2 day-1 and winter (December to February) efflux of merely 0.18 mmol m-2 day-1. The efflux showed no apparent diel pattern, although most of the peak effluxes appeared in the late morning, from 10:00 to 12:00 CST (GMT + 8). Multivariate stepwise regression on a seasonal scale showed that environmental factors, such as sediment temperature, sediment total nitrogen content, dissolved oxygen, and total phosphorus content in the water, mainly regulated the CH4 efflux. However, the CH4 efflux only showed a strong positive linear correlation with wind speed within 1 day on a bihourly scale in the multivariate regression analyses but almost no correlation with wind speed on diurnal and seasonal scales.

Bootstrap investigation of the stability of a Cox regression model.

PubMed

Altman, D G; Andersen, P K

1989-07-01

We describe a bootstrap investigation of the stability of a Cox proportional hazards regression model resulting from the analysis of a clinical trial of azathioprine versus placebo in patients with primary biliary cirrhosis. We have considered stability to refer both to the choice of variables included in the model and, more importantly, to the predictive ability of the model. In stepwise Cox regression analyses of 100 bootstrap samples using 17 candidate variables, the most frequently selected variables were those selected in the original analysis, and no other important variable was identified. Thus there was no reason to doubt the model obtained in the original analysis. For each patient in the trial, bootstrap confidence intervals were constructed for the estimated probability of surviving two years. It is shown graphically that these intervals are markedly wider than those obtained from the original model.

Nowcasting of Low-Visibility Procedure States with Ordered Logistic Regression at Vienna International Airport

NASA Astrophysics Data System (ADS)

Kneringer, Philipp; Dietz, Sebastian; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Low-visibility conditions have a large impact on aviation safety and economic efficiency of airports and airlines. To support decision makers, we develop a statistical probabilistic nowcasting tool for the occurrence of capacity-reducing operations related to low visibility. The probabilities of four different low visibility classes are predicted with an ordered logistic regression model based on time series of meteorological point measurements. Potential predictor variables for the statistical models are visibility, humidity, temperature and wind measurements at several measurement sites. A stepwise variable selection method indicates that visibility and humidity measurements are the most important model inputs. The forecasts are tested with a 30 minute forecast interval up to two hours, which is a sufficient time span for tactical planning at Vienna Airport. The ordered logistic regression models outperform persistence and are competitive with human forecasters.

RNA Viruses that Cause Hemorrhagic, Encephalitic, and Febrile Disease

DTIC Science & Technology

1990-01-01

doses to levels that are subopti- effective dose (ED,0) values for Rift Valley mal for cures in other bunyavirus mouse Fever ( RVF ) virus (ED,, = 80 g...serum protein and AST Etiologic Agent (SGOT) identified in the placebo group by logistic regression], utilizing a stepwise lo- RVF , an old-world...treatment of H FRS in this study. Treatment reduced mortality RVF , distributed throughout sub-Saharan and improved several important aspects of Africa

Population dynamics of pond zooplankton II Daphnia ambigua Scourfield

USGS Publications Warehouse

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

1973-01-01

Calcium was the most important of 27 environmental components affecting density for a 50 week period. Simultaneous stepwise regression accounted for more variability in total number/1 and in the number of ovigerous females/1 than did any of the lag analyses; 1-week lag accounted for the greatest amount of variability in clutch size. Total number and clutch size were little affected by measures of food. ?? 1973 Dr. W. Junk b.v. Publishers.

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

Penna, M.L.; Duchiade, M.P.

The authors report the results of an investigation into the possible association between air pollution and infant mortality from pneumonia in the Rio de Janeiro Metropolitan Area. This investigation employed multiple linear regression analysis (stepwise method) for infant mortality from pneumonia in 1980, including the study population's areas of residence, incomes, and pollution exposure as independent variables. With the income variable included in the regression, a statistically significant association was observed between the average annual level of particulates and infant mortality from pneumonia. While this finding should be accepted with caution, it does suggest a biological association between these variables.more » The authors' conclusion is that air quality indicators should be included in studies of acute respiratory infections in developing countries.« less

Associations between state economic and health systems capacities and service use by children with special health care needs.

PubMed

Margolis, Lewis H; Mayer, Michelle; Clark, Kathryn A; Farel, Anita M

2011-08-01

To examine the relationship between measures of state economic, political, health services, and Title V capacity and individual level measures of the well-being of CSHCN. We selected five measures of Title V capacity from the Title V Information System and 13 state capacity measures from a variety of data sources, and eight indicators of intermediate health outcomes from the National Survey of Children with Special Health Care Needs. To assess the associations between Title V capacity and health services outcomes, we used stepwise regression to identify significant capacity measures while accounting for the survey design and clustering of observations by state. To assess the associations between economic, political and health systems capacity and health outcomes we fit weighted logistic regression models for each outcome, using a stepwise procedure to reduce the models. Using statistically significant capacity measures from the stepwise models, we fit reduced random effects logistic regression models to account for clustering of observations by state. Few measures of Title V and state capacity were associated with health services outcomes. For health systems measures, a higher percentage of uninsured children was associated with decreased odds of receipt of early intervention services, decreased odds of receipt of professional care coordination, and increased odds of delayed or missed care. Parents in states with higher per capita Medicaid expenditures on children were more likely to report receipt of special education services. Only two state capacity measures were associated explicitly with Title V: states with higher generalist physician to population ratios were associated with a greater likelihood of parent report of having heard of Title V and states with higher per capita gross state product were less likely to be associated with a report of using Title V services, conditional on having heard of Title V. The state level measure of family participation in Title V governance was negatively associated with receipt of care coordination and having used Title V services. The measures of state economic, political, health systems, and Title V capacity that we have analyzed are only weakly associated with the well-being of children with special health care needs. If Congress and other policymakers increase the expectations of the states in assuring that the needs of CSHCN and their families are addressed, it is essential to be cognizant of the capacities of the states to undertake that role.

K/Ar dating of lunar soils. II

NASA Technical Reports Server (NTRS)

Alexander, E. C., Jr.; Bates, A.; Coscio, M. R., Jr.; Dragon, J. C.; Murthy, V. R.; Pepin, R. O.; Venkatesan, T. R.

1976-01-01

An attempt is made to identify those K/Ar techniques which extract the most reliable chronological information from lunar soils and to define the situations in which the best data are obtainable. Results are presented for determinations of the exposure and K/Ar ages of five lunar soil samples, which were performed by applying correlation techniques for a two-component argon structure to stepwise-heated and neutron-irradiated aliquots of grain-sized separates. It is found that ages deduced from Ar-40/surface-correlated Ar-36 vs K-40/surface-correlated Ar-36 and analogous plots of data from grain-sized separates appear to be the best available K/Ar ages of submature to mature lunar soils, that ages deduced from Ar-40 vs Ar-36 and analogous plots which assume a uniform K content can be significantly in error, and that stepwise-heating (Ar-40)-(Ar-39) experiments yield useful information only for simple immature soils where the K-Ar systematics are dominated by a single component.

Statistical Models for Predicting Automobile Driving Postures for Men and Women Including Effects of Age.

PubMed

Park, Jangwoon; Ebert, Sheila M; Reed, Matthew P; Hallman, Jason J

2016-03-01

Previously published statistical models of driving posture have been effective for vehicle design but have not taken into account the effects of age. The present study developed new statistical models for predicting driving posture. Driving postures of 90 U.S. drivers with a wide range of age and body size were measured in laboratory mockup in nine package conditions. Posture-prediction models for female and male drivers were separately developed by employing a stepwise regression technique using age, body dimensions, vehicle package conditions, and two-way interactions, among other variables. Driving posture was significantly associated with age, and the effects of other variables depended on age. A set of posture-prediction models is presented for women and men. The results are compared with a previously developed model. The present study is the first study of driver posture to include a large cohort of older drivers and the first to report a significant effect of age. The posture-prediction models can be used to position computational human models or crash-test dummies for vehicle design and assessment. © 2015, Human Factors and Ergonomics Society.

Benign-malignant mass classification in mammogram using edge weighted local texture features

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

2016-03-01

This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

Uncertainty and sensitivity analysis for two-phase flow in the vicinity of the repository in the 1996 performance assessment for the Waste Isolation Pilot Plant: Disturbed conditions

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

HELTON,JON CRAIG; BEAN,J.E.; ECONOMY,K.

2000-05-22

Uncertainty and sensitivity analysis results obtained in the 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) are presented for two-phase flow in the vicinity of the repository under disturbed conditions resulting from drilling intrusions. Techniques based on Latin hypercube sampling, examination of scatterplots, stepwise regression analysis, partial correlation analysis and rank transformations are used to investigate brine inflow, gas generation repository pressure, brine saturation and brine and gas outflow. Of the variables under study, repository pressure and brine flow from the repository to the Culebra Dolomite are potentially the most important in PA for the WIPP. Subsequentmore » to a drilling intrusion repository pressure was dominated by borehole permeability and generally below the level (i.e., 8 MPa) that could potentially produce spallings and direct brine releases. Brine flow from the repository to the Culebra Dolomite tended to be small or nonexistent with its occurrence and size also dominated by borehole permeability.« less

Motivation for change as a predictor of treatment response for dysthymia.

PubMed

Frías Ibáñez, Álvaro; González Vallespí, Laura; Palma Sevillano, Carol; Farriols Hernando, Núria

2016-05-01

Dysthymia constitutes a chronic, mild affective disorder characterized by heterogeneous treatment effects. Several predictors of clinical response and attendance have been postulated, although research on the role of the psychological variables involved in this mental disorder is still scarce. Fifty-four adult patients, who met criteria for dysthymia completed an ongoing naturalistic treatment based on the brief interpersonal psychotherapy (IPT-B), which was delivered bimonthly over 16 months. As potential predictor variables, the therapeutic alliance, coping strategies, perceived self-efficacy, and motivation for change were measured at baseline. Outcome variables were response to treatment (Clinical Global Impression and Beck’s Depression Inventory) and treatment attendance. Stepwise multiple linear regression analyses revealed that higher motivation for change predicted better response to treatment. Moreover, higher motivation for change also predicted treatment attendance. Therapeutic alliance was not a predictor variable of neither clinical response nor treatment attendance. These preliminary findings support the adjunctive use of motivational interviewing (MI) techniques in the treatment of dysthymia. Further research with larger sample size and follow-up assessment is warranted.

Relationship between serum bilirubin concentrations and diabetic nephropathy in Shanghai Han's patients with type 1 diabetes mellitus.

PubMed

Li, Xu; Zhang, Lei; Chen, Haibing; Guo, Kaifeng; Yu, Haoyong; Zhou, Jian; Li, Ming; Li, Qing; Li, Lianxi; Yin, Jun; Liu, Fang; Bao, Yuqian; Han, Junfeng; Jia, Weiping

2017-03-31

Recent studies highlight a negative association between total bilirubin concentrations and albuminuria in patients with type 2 diabetes mellitus. Our study evaluated the relationship between bilirubin concentrations and the prevalence of diabetic nephropathy (DN) in Chinese patients with type 1 diabetes mellitus (T1DM). A total of 258 patients with T1DM were recruited and bilirubin concentrations were compared between patients with or without diabetic nephropathy. Multiple stepwise regression analysis was used to examine the relationship between bilirubin concentrations and 24 h urinary microalbumin. Binary logistic regression analysis was performed to assess independent risk factors for diabetic nephropathy. Participants were divided into four groups according to the quartile of total bilirubin concentrations (Q1, 0.20-0.60; Q2, 0.60-0.80; Q3, 0.80-1.00; Q4, 1.00-1.90 mg/dL) and the chi-square test was used to compare the prevalence of DN in patients with T1DM. The median bilirubin level was 0.56 (interquartile: 0.43-0.68 mg/dL) in the DN group, significantly lower than in the non-DN group (0.70 [interquartile: 0.58-0.89 mg/dL], P < 0.001). Spearman's correlational analysis showed bilirubin concentrations were inversely correlated with 24 h urinary microalbumin (r = -0.13, P < 0.05) and multiple stepwise regression analysis showed bilirubin concentrations were independently associated with 24 h urinary microalbumin. In logistic regression analysis, bilirubin concentrations were significantly inversely associated with nephropathy. In addition, in stratified analysis, from the first to the fourth quartile group, increased bilirubin concentrations were associated with decreased prevalence of DN from 21.90% to 2.00%. High bilirubin concentrations are independently and negatively associated with albuminuria and the prevalence of DN in patients with T1DM.

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

PubMed

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation of stature from the foot and its segments in a sub-adult female population of North India

PubMed Central

2011-01-01

Background Establishing personal identity is one of the main concerns in forensic investigations. Estimation of stature forms a basic domain of the investigation process in unknown and co-mingled human remains in forensic anthropology case work. The objective of the present study was to set up standards for estimation of stature from the foot and its segments in a sub-adult female population. Methods The sample for the study constituted 149 young females from the Northern part of India. The participants were aged between 13 and 18 years. Besides stature, seven anthropometric measurements that included length of the foot from each toe (T1, T2, T3, T4, and T5 respectively), foot breadth at ball (BBAL) and foot breadth at heel (BHEL) were measured on both feet in each participant using standard methods and techniques. Results The results indicated that statistically significant differences (p < 0.05) between left and right feet occur in both the foot breadth measurements (BBAL and BHEL). Foot length measurements (T1 to T5 lengths) did not show any statistically significant bilateral asymmetry. The correlation between stature and all the foot measurements was found to be positive and statistically significant (p-value < 0.001). Linear regression models and multiple regression models were derived for estimation of stature from the measurements of the foot. The present study indicates that anthropometric measurements of foot and its segments are valuable in the estimation of stature. Foot length measurements estimate stature with greater accuracy when compared to foot breadth measurements. Conclusions The present study concluded that foot measurements have a strong relationship with stature in the sub-adult female population of North India. Hence, the stature of an individual can be successfully estimated from the foot and its segments using different regression models derived in the study. The regression models derived in the study may be applied successfully for the estimation of stature in sub-adult females, whenever foot remains are brought for forensic examination. Stepwise multiple regression models tend to estimate stature more accurately than linear regression models in female sub-adults. PMID:22104433

Estimation of stature from the foot and its segments in a sub-adult female population of North India.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Passi, Neelam

2011-11-21

Establishing personal identity is one of the main concerns in forensic investigations. Estimation of stature forms a basic domain of the investigation process in unknown and co-mingled human remains in forensic anthropology case work. The objective of the present study was to set up standards for estimation of stature from the foot and its segments in a sub-adult female population. The sample for the study constituted 149 young females from the Northern part of India. The participants were aged between 13 and 18 years. Besides stature, seven anthropometric measurements that included length of the foot from each toe (T1, T2, T3, T4, and T5 respectively), foot breadth at ball (BBAL) and foot breadth at heel (BHEL) were measured on both feet in each participant using standard methods and techniques. The results indicated that statistically significant differences (p < 0.05) between left and right feet occur in both the foot breadth measurements (BBAL and BHEL). Foot length measurements (T1 to T5 lengths) did not show any statistically significant bilateral asymmetry. The correlation between stature and all the foot measurements was found to be positive and statistically significant (p-value < 0.001). Linear regression models and multiple regression models were derived for estimation of stature from the measurements of the foot. The present study indicates that anthropometric measurements of foot and its segments are valuable in the estimation of stature. Foot length measurements estimate stature with greater accuracy when compared to foot breadth measurements. The present study concluded that foot measurements have a strong relationship with stature in the sub-adult female population of North India. Hence, the stature of an individual can be successfully estimated from the foot and its segments using different regression models derived in the study. The regression models derived in the study may be applied successfully for the estimation of stature in sub-adult females, whenever foot remains are brought for forensic examination. Stepwise multiple regression models tend to estimate stature more accurately than linear regression models in female sub-adults.

Destination bedside: using research findings to visualize optimal unit layouts and health information technology in support of bedside care.

PubMed

Watkins, Nicholas; Kennedy, Mary; Lee, Nelson; O'Neill, Michael; Peavey, Erin; Ducharme, Maria; Padula, Cynthia

2012-05-01

This study explored the impact of unit design and healthcare information technology (HIT) on nursing workflow and patient-centered care (PCC). Healthcare information technology and unit layout-related predictors of nursing workflow and PCC were measured during a 3-phase study involving questionnaires and work sampling methods. Stepwise multiple linear regressions demonstrated several HIT and unit layout-related factors that impact nursing workflow and PCC.

Predicting alienation in a sample of Nigerian Igbo subjects.

PubMed

Morah, E I

1990-08-01

Seeman in 1959 suggested that alienation is a multidimensional concept. Using two aspects of Seeman's concept of alienation, powerlessness and social alienation, and two concepts derived from Lachar's 1978 Minnesota Multiphasic Personality Inventory Cookbook, emotional and self-alienation, the present work was undertaken to ascertain which concept will more likely predict feelings of alienation. A stepwise multiple regression showed that among 160 Nigerian (Igbo) subjects the feeling of powerlessness predicted alienation more than did the other concept.

Prayer at Midlife is Associated with Reduced Risk of Cognitive Decline in Arabic Women

PubMed Central

Inzelberg, Rivka; Afgin, Anne E; Massarwa, Magda; Schechtman, Edna; Israeli-Korn, Simon D.; Strugatsky, Rosa; Abuful, Amin; Kravitz, Efrat; Farrer, Lindsay A.; Friedland, Robert P.

2013-01-01

Midlife habits may be important for the later development of Alzheimer's disease (AD). We estimated the contribution of midlife prayer to the development of cognitive decline. In a door-to-door survey, residents aged ≥65 years were systematically evaluated in Arabic including medical history, neurological, cognitive examination, and a midlife leisure-activities questionnaire. Praying was assessed by the number of monthly praying hours at midlife. Stepwise logistic regression models were used to evaluate the effect of prayer on the odds of mild cognitive impairment (MCI) and AD versus cognitively normal individuals. Of 935 individuals that were approached, 778 [normal controls (n=448), AD (n=92) and MCI (n=238)] were evaluated. A higher proportion of cognitively normal individuals engaged in prayer at midlife [(87%) versus MCI (71%) or AD (69%) (p<0.0001)]. Since 94% of males engaged in prayer, the effect on cognitive decline could not be assessed in men. Among women, stepwise logistic regression adjusted for age and education, showed that prayer was significantly associated with reduced risk of MCI (p=0.027, OR=0.55, 95% CI 0.33-0.94), but not AD. Among individuals endorsing prayer activity, the amount of prayer was not associated with MCI or AD in either gender. Praying at midlife is associated with lower risk of mild cognitive impairment in women. PMID:23116476

Quantitative evaluation of light scattering intensities of the crystalline lens for radiation related minimal change in interventional radiologists: a cross-sectional pilot study.

PubMed

Abe, Toshi; Furui, Shigeru; Sasaki, Hiroshi; Sakamoto, Yasuo; Suzuki, Shigeru; Ishitake, Tatsuya; Terasaki, Kinuyo; Kohtake, Hiroshi; Norbash, Alexander M; Behrman, Richard H; Hayabuchi, Naofumi

2013-03-01

To evaluate low-dose X-ray radiation effects on the eye by measuring the amount of light scattering in specific regions of the lens, we compared exposed subjects (interventional radiologists) with unexposed subjects (employees of medical service companies), as a pilot study. According to numerous exclusionary rules, subjects with confounding variables contributing to cataract formation were excluded. Left eye examinations were performed on 68 exposed subjects and 171 unexposed subjects. The eye examinations consisted of an initial screening examination, followed by Scheimpflug imaging of the lens using an anterior eye segment analysis system. The subjects were assessed for the quantity of light scattering intensities found in each of the six layers of the lens. Multiple stepwise regression analyses were performed with the stepwise regression for six variables: age, radiation exposure, smoking, drinking, wearing glasses and workplace. In addition, an age-matched comparison between exposed and unexposed subjects was performed. Minimal increased light scattering intensity in the posterior subcapsular region showed statistical significance. Our results indicate that occupational radiation exposure in interventional radiologists may affect the posterior subcapsular region of the lens. Since by its very nature this retrospective study had many limitations, further well-designed studies concerning minimal radiation-related lens changes should be carried out in a low-dose exposure group.

Biomechanical correlates of symptomatic and asymptomatic neurophysiological impairment in high school football.

PubMed

Breedlove, Evan L; Robinson, Meghan; Talavage, Thomas M; Morigaki, Katherine E; Yoruk, Umit; O'Keefe, Kyle; King, Jeff; Leverenz, Larry J; Gilger, Jeffrey W; Nauman, Eric A

2012-04-30

Concussion is a growing public health issue in the United States, and chronic traumatic encephalopathy (CTE) is the chief long-term concern linked to repeated concussions. Recently, attention has shifted toward subconcussive blows and the role they may play in the development of CTE. We recruited a cohort of high school football players for two seasons of observation. Acceleration sensors were placed in the helmets, and all contact activity was monitored. Pre-season computer-based neuropsychological tests and functional magnetic resonance imaging (fMRI) tests were also obtained in order to assess cognitive and neurophysiological health. In-season follow-up scans were then obtained both from individuals who had sustained a clinically-diagnosed concussion and those who had not. These changes were then related through stepwise regression to history of blows recorded throughout the football season up to the date of the scan. In addition to those subjects who had sustained a concussion, a substantial portion of our cohort who did not sustain concussions showed significant neurophysiological changes. Stepwise regression indicated significant relationships between the number of blows sustained by a subject and the ensuing neurophysiological change. Our findings reinforce the hypothesis that the effects of repetitive blows to the head are cumulative and that repeated exposure to subconcussive blows is connected to pathologically altered neurophysiology. Copyright © 2012 Elsevier Ltd. All rights reserved.

Simple Patchy-Based Simulators Used to Explore Pondscape Systematic Dynamics

PubMed Central

Fang, Wei-Ta; Chou, Jui-Yu; Lu, Shiau-Yun

2014-01-01

Thousands of farm ponds disappeared on the tableland in Taoyuan County, Taiwan since 1920s. The number of farm ponds that have disappeared is 1,895 (37%), 2,667 ponds remain (52%), and only 537 (11%) new ponds were created within a 757 km2 area in Taoyuan, Taiwan between 1926 and 1960. In this study, a geographic information system (GIS) and logistic stepwise regression model were used to detect pond-loss rates and to understand the driving forces behind pondscape changes. The logistic stepwise regression model was used to develop a series of relationships between pondscapes affected by intrinsic driving forces (patch size, perimeter, and patch shape) and external driving forces (distance from the edge of the ponds to the edges of roads, rivers, and canals). The authors concluded that the loss of ponds was caused by pond intrinsic factors, such as pond perimeter; a large perimeter increases the chances of pond loss, but also increases the possibility of creating new ponds. However, a large perimeter is closely associated with circular shapes (lower value of the mean pond-patch fractal dimension [MPFD]), which characterize the majority of newly created ponds. The method used in this study might be helpful to those seeking to protect this unique landscape by enabling the monitoring of patch-loss problems by using simple patchy-based simulators. PMID:24466281

The influence of attention deficits on functional recovery post stroke during the first 12 months after discharge from hospital.

PubMed

Hyndman, D; Pickering, R M; Ashburn, A

2008-06-01

Attention deficits have been linked to poor recovery after stroke and may predict outcome. We explored the influence of attention on functional recovery post stroke in the first 12 months after discharge from hospital. People with stroke completed measures of attention, balance, mobility and activities of daily living (ADL) ability at the point of discharge from hospital, and 6 and 12 months later. We used correlational analysis and stepwise linear regression to explore potential predictors of outcome. We recruited 122 men and women, mean age 70 years. At discharge, 56 (51%) had deficits of divided attention, 45 (37%) of sustained attention, 43 (36%) of auditory selective attention and 41 (37%) had visual selective attention deficits. Attention at discharge correlated with mobility, balance and ADL outcomes 12 months later. After controlling for the level of the outcome at discharge, correlations remained significant in only five of the 12 relationships. Stepwise linear regression revealed that the outcome measured at discharge, days until discharge and number of medications were better predictors of outcome: in no case was an attention variable at discharge selected as a predictor of outcome at 12 months. Although attention and function correlated significantly, this correlation was reduced after controlling for functional ability at discharge. Furthermore, side of lesion and the attention variables were not demonstrated as important predictors of outcome 12 months later.

Predicting psychopharmacological drug effects on actual driving performance (SDLP) from psychometric tests measuring driving-related skills.

PubMed

Verster, Joris C; Roth, Thomas

2012-03-01

There are various methods to examine driving ability. Comparisons between these methods and their relationship with actual on-road driving is often not determined. The objective of this study was to determine whether laboratory tests measuring driving-related skills could adequately predict on-the-road driving performance during normal traffic. Ninety-six healthy volunteers performed a standardized on-the-road driving test. Subjects were instructed to drive with a constant speed and steady lateral position within the right traffic lane. Standard deviation of lateral position (SDLP), i.e., the weaving of the car, was determined. The subjects also performed a psychometric test battery including the DSST, Sternberg memory scanning test, a tracking test, and a divided attention test. Difference scores from placebo for parameters of the psychometric tests and SDLP were computed and correlated with each other. A stepwise linear regression analysis determined the predictive validity of the laboratory test battery to SDLP. Stepwise regression analyses revealed that the combination of five parameters, hard tracking, tracking and reaction time of the divided attention test, and reaction time and percentage of errors of the Sternberg memory scanning test, together had a predictive validity of 33.4%. The psychometric tests in this test battery showed insufficient predictive validity to replace the on-the-road driving test during normal traffic.

Factors associated with fall-related fractures in Parkinson's disease.

PubMed

Cheng, Kuei-Yueh; Lin, Wei-Che; Chang, Wen-Neng; Lin, Tzu-Kong; Tsai, Nai-Wen; Huang, Chih-Cheng; Wang, Hung-Chen; Huang, Yung-Cheng; Chang, Hsueh-Wen; Lin, Yu-Jun; Lee, Lian-Hui; Cheng, Ben-Chung; Kung, Chia-Te; Chang, Ya-Ting; Su, Chih-Min; Chiang, Yi-Fang; Su, Yu-Jih; Lu, Cheng-Hsien

2014-01-01

Fall-related fracture is one of the most disabling features of idiopathic Parkinson's disease (PD). A better understanding of the associated factors is needed to predict PD patients who will require treatment. This prospective study enrolled 100 adult idiopathic PD patients. Stepwise logistic regressions were used to evaluate the relationships between clinical factors and fall-related fracture. Falls occurred in 56 PD patients, including 32 with fall-related fractures. The rate of falls in the study period was 2.2 ± 1.4 per 18 months. The percentage of osteoporosis was 34% (19/56) and 11% in PD patients with and without falls, respectively. Risk factors associated with fall-related fracture were sex, underlying knee osteoarthritis, mean Unified Parkinson's Disease Rating Scale score, mean Morse fall scale, mean Hoehn and Yahr stage, and exercise habit. By stepwise logistic regression, sex and mean Morse fall scale were independently associated with fall-related fracture. Females had an odds ratio of 3.8 compared to males and the cut-off value of the Morse fall scale for predicting fall-related fracture was 72.5 (sensitivity 72% and specificity 70%). Higher mean Morse fall scales (>72.5) and female sex are associated with higher risk of fall-related fractures. Preventing falls in the high-risk PD group is an important safety issue and highly relevant for their quality of life. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identification of factors that affect the adoption of an ergonomic intervention among Emergency Medical Service workers.

PubMed

Weiler, Monica R; Lavender, Steven A; Crawford, J Mac; Reichelt, Paul A; Conrad, Karen M; Browne, Michael W

2012-01-01

This study explored factors contributing to intervention adoption decisions among Emergency Medical Service (EMS) workers. Emergency Medical Service workers (n = 190), from six different organisations, participated in a two-month longitudinal study following the introduction of a patient transfer-board (also known as slide-board) designed to ease lateral transfers of patients to and from ambulance cots. Surveys administered at baseline, after one month and after two months sampled factors potentially influencing the EMS providers' decision process. 'Ergonomics Advantage' and 'Patient Advantage' entered into a stepwise regression model predicting 'intention to use' at the end of month one (R (2 )= 0.78). After the second month, the stepwise regression indicated only two factors were predictive of intention to use: 'Ergonomics Advantage,' and 'Endorsed by Champions' (R (2 )= 0.58). Actual use was predicted by: 'Ergonomics Advantage' and 'Previous Tool Experience.' These results relate to key concepts identified in the diffusion of innovation literature and have the potential to further ergonomics intervention adoption efforts. Practitioner Summary. This study explored factors that potentially facilitate the adoption of voluntarily used ergonomics interventions. EMS workers were provided with foldable transfer-boards (slideboards) designed to reduce the physical demands when laterally transferring patients. Factors predictive of adoption measures included perceived ergonomics advantage, the endorsement by champions, and prior tool experience.

Prayer at midlife is associated with reduced risk of cognitive decline in Arabic women.

PubMed

Inzelberg, Rivka; Afgin, Anne E; Massarwa, Magda; Schechtman, Edna; Israeli-Korn, Simon D; Strugatsky, Rosa; Abuful, Amin; Kravitz, Efrat; Farrer, Lindsay A; Friedland, Robert P

2013-03-01

Midlife habits may be important for the later development of Alzheimer's disease (AD). We estimated the contribution of midlife prayer to the development of cognitive decline. In a door-to-door survey, residents aged ≥65 years were systematically evaluated in Arabic including medical history, neurological, cognitive examination, and a midlife leisure-activities questionnaire. Praying was assessed by the number of monthly praying hours at midlife. Stepwise logistic regression models were used to evaluate the effect of prayer on the odds of mild cognitive impairment (MCI) and AD versus cognitively normal individuals. Of 935 individuals that were approached, 778 [normal controls (n=448), AD (n=92) and MCI (n=238)] were evaluated. A higher proportion of cognitively normal individuals engaged in prayer at midlife [(87%) versus MCI (71%) or AD (69%) (p<0.0001)]. Since 94% of males engaged in prayer, the effect on cognitive decline could not be assessed in men. Among women, stepwise logistic regression adjusted for age and education, showed that prayer was significantly associated with reduced risk of MCI (p=0.027, OR=0.55, 95% CI 0.33-0.94), but not AD. Among individuals endorsing prayer activity, the amount of prayer was not associated with MCI or AD in either gender. Praying at midlife is associated with lower risk of mild cognitive impairment in women.

Dietary acculturation and body composition predict American Hmong children's blood pressure.

PubMed

Smith, Chery; Franzen-Castle, Lisa

2012-01-01

Determine how dietary acculturation, anthropometric measures (height, weight, circumferences, and skinfolds), body mass index (BMI), and waist hip ratios (WHRs) are associated with blood pressure (BP) measures in Hmong children living in Minnesota. Acculturation was measured using responses to questions regarding language usage, social connections, and diet. Dietary assessment was completed using the multiple-pass 24-h dietary recall method on two different days. Anthropometric and BP measurement were taken using standard procedures, and BMI and WHR were calculated. Data analyses included descriptive statistics, ANOVA, and stepwise regression analyses. Using stepwise regression analysis, hip circumference (HC) predicted boys' systolic (S)BP (R(2) = 0.55). For girls' SBP, mid-upper arm circumference, WHR, low calcium consumption, and height percentile jointly explained 41% of the total variation. Mid upper arm circumference (MAC) and carbohydrate consumption predicted 35% of the variance for boys' diastolic (D)BP, and HC, dairy consumption, and calcium intake predicted 31% of the total variance for girls' DBP. Responses to dietary acculturation questions revealed between group differences for breakfast with half of the younger Born-Thailand/Laos (Born-T/L) consuming mostly Hmong food, while at dinner Born-US consumed a mixed diet and Born-T/L were more likely to consume Hmong food. Dietary acculturation and body composition predict Hmong children's BP. Copyright © 2012 Wiley Periodicals, Inc.

The investigation of the relationship between probability of suicide and reasons for living in psychiatric inpatients.

PubMed

Eskiyurt, Reyhan; Ozkan, Birgul

2017-01-01

This study was carried out to determine the reasons of the suicide probability and reasons for living of the inpatients hospitalized at the psychiatry clinic and to analyze the relationship between them. The sample of the study consisted of 192 patients who were hospitalized in psychiatric clinics between February and May 2016 and who agreed to participate in the study. In collecting data, personal information form, suicide probability scale (SPS), reasons for living inventory (RFL), and Beck's depression inventory (BDI) were used. Stepwise regression method was used to determine the factors that predict suicide probability. In the study, as a result of analyses made, the median score on the SPS was found 76.0, the median score on the RFL was found 137.0, the median score on the BDI of the patients was found 13.5, and it was found that patients with a high probability of suicide had less reasons for living and that their depression levels were very high. As a result of stepwise regression analysis, it was determined that suicidal ideation, reasons for living, maltreatment, education level, age, and income status were the predictors of suicide probability ( F = 61.125; P < 0.001). It was found that the patients who hospitalized in the psychiatric clinic have high suicide probability and the reasons of living are strong predictors of suicide probability in accordance with the literature.

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

Caries risk assessment in schoolchildren - a form based on Cariogram® software

PubMed Central

CABRAL, Renata Nunes; HILGERT, Leandro Augusto; FABER, Jorge; LEAL, Soraya Coelho

2014-01-01

Identifying caries risk factors is an important measure which contributes to best understanding of the cariogenic profile of the patient. The Cariogram® software provides this analysis, and protocols simplifying the method were suggested. Objectives The aim of this study was to determine whether a newly developed Caries Risk Assessment (CRA) form based on the Cariogram® software could classify schoolchildren according to their caries risk and to evaluate relationships between caries risk and the variables in the form. Material and Methods 150 schoolchildren aged 5 to 7 years old were included in this survey. Caries prevalence was obtained according to International Caries Detection and Assessment System (ICDAS) II. Information for filling in the form based on Cariogram® was collected clinically and from questionnaires sent to parents. Linear regression and a forward stepwise multiple regression model were applied to correlate the variables included in the form with the caries risk. Results Caries prevalence, in primary dentition, including enamel and dentine carious lesions was 98.6%, and 77.3% when only dentine lesions were considered. Eighty-six percent of the children were classified as at moderate caries risk. The forward stepwise multiple regression model result was significant (R2=0.904; p<0.00001), showing that the most significant factors influencing caries risk were caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources. Conclusion The use of the form based on the Cariogram® software enabled classification of the schoolchildren at low, moderate and high caries risk. Caries experience, oral hygiene, frequency of food consumption, sugar consumption and fluoride sources are the variables that were shown to be highly correlated with caries risk. PMID:25466473

Urinary Incontinence of Women in a Nationwide Study in Sri Lanka: Prevalence and Risk Factors.

PubMed

Pathiraja, Ramya; Prathapan, Shamini; Goonawardena, Sampatha

2017-05-23

Urinary incontinence, be stress incontinence or urge incontinence or a mixed type incontinence affects women of all ages. The aim of this study was to describe the prevalence and risk factors of urinary incontinence in Sri Lanka. A community based cross-sectional study was performed in Sri Lanka. The age group of the women in Sri Lanka was categorized into 3 age groups: Less than or equal to 35 years, 36 to 50 years of age and more than or equal to 51 years of age. A sample size of 675 women was obtained from each age category obtaining a total sample of 2025 from Sri Lanka. An interviewer-administered questionnaire consisting of two parts; Socio demographic factors, Medical and Obstetric History, and the King's Health Questionnaire (KHQ), was used for data collection. Stepwise logistic regression analysis was performed. The Prevalence of women with only stress incontinence was 10%, with urge incontinence was 15.6% and with stress and urge incontinence was 29.9%. Stepwise logistic regression analysis showed that the age groups of 36 - 50 years (OR = 2.03; 95% CI = 1.56 - 2.63) and 51 years and above (OR = 2.61; 95% CI= 1.95 - 3.48), Living in one of the districts in Sri Lanka (OR = 4.58; 95% CI = 3.35 - 6.27) and having given birth to multiple children (OR = 1.1; 95% CI = 1.02 - 1.21), diabetes mellitus (OR = 1.97; 95% CI = 1.19 - 3.23), and respiratory diseases (OR = 2.17; 95% CI = 1.48 - 3.19 ) showed a significant risk in the regression analysis. The risk factor, mostly modifiable, if prevented early, could help to reduce the symptoms of urinary incontinence.

Socio-economic factors associated with infant mortality in Italy: an ecological study.

PubMed

Dallolio, Laura; Di Gregori, Valentina; Lenzi, Jacopo; Franchino, Giuseppe; Calugi, Simona; Domenighetti, Gianfranco; Fantini, Maria Pia

2012-08-16

One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.

Evidence-based identification of key beliefs explaining adult male circumcision motivation in Zimbabwe: targets for behavior change messaging.

PubMed

Montaño, Daniel E; Kasprzyk, Danuta; Hamilton, Deven T; Tshimanga, Mufuta; Gorn, Gerald

2014-05-01

Male circumcision (MC) reduces HIV acquisition among men, leading WHO/UNAIDS to recommend a goal to circumcise 80 % of men in high HIV prevalence countries. Significant investment to increase MC capacity in priority countries was made, yet only 5 % of the goal has been achieved in Zimbabwe. The integrated behavioral model (IBM) was used as a framework to investigate the factors affecting MC motivation among men in Zimbabwe. A survey instrument was designed based on elicitation study results, and administered to a representative household-based sample of 1,201 men aged 18-30 from two urban and two rural areas in Zimbabwe. Multiple regression analysis found all five IBM constructs significantly explained MC Intention. Nearly all beliefs underlying the IBM constructs were significantly correlated with MC Intention. Stepwise regression analysis of beliefs underlying each construct respectively found that 13 behavioral beliefs, 5 normative beliefs, 4 descriptive norm beliefs, 6 efficacy beliefs, and 10 control beliefs were significant in explaining MC Intention. A final stepwise regression of the five sets of significant IBM construct beliefs identified 14 key beliefs that best explain Intention. Similar analyses were carried out with subgroups of men by urban-rural and age. Different sets of behavioral, normative, efficacy, and control beliefs were significant for each sub-group, suggesting communication messages need to be targeted to be most effective for sub-groups. Implications for the design of effective MC demand creation messages are discussed. This study demonstrates the application of theory-driven research to identify evidence-based targets for intervention messages to increase men's motivation to get circumcised and thereby improve demand for male circumcision.

Factors Associated With Work Ability in Patients Undergoing Surgery for Cervical Radiculopathy.

PubMed

Ng, Eunice; Johnston, Venerina; Wibault, Johanna; Löfgren, Håkan; Dedering, Åsa; Öberg, Birgitta; Zsigmond, Peter; Peolsson, Anneli

2015-08-15

Cross-sectional study. To investigate the factors associated with work ability in patients undergoing surgery for cervical radiculopathy. Surgery is a common treatment of cervical radiculopathy in people of working age. However, few studies have investigated the impact on the work ability of these patients. Patients undergoing surgery for cervical radiculopathy (n = 201) were recruited from spine centers in Sweden to complete a battery of questionnaires and physical measures the day before surgery. The associations between various individual, psychological, and work-related factors and self-reported work ability were investigated by Spearman rank correlation coefficient, multivariate linear regression, and forward stepwise regression analyses. Factors that were significant (P < 0.05) in each statistical analysis were entered into the successive analysis to reveal the factors most related to work ability. Work ability was assessed using the Work Ability Index. The mean Work Ability Index score was 28 (SD, 9.0). The forward stepwise regression analysis revealed 6 factors significantly associated with work ability, which explained 62% of the variance in the Work Ability Index. Factors highly correlated with greater work ability included greater self-efficacy in performing self-cares, lower physical load on the neck at work, greater self-reported chance of being able to work in 6 months' time, greater use of active coping strategies, lower frequency of hand weakness, and higher health-related quality of life. Psychological, work-related and individual factors were significantly associated with work ability in patients undergoing surgery for cervical radiculopathy. High self-efficacy was most associated with greater work ability. Consideration of these factors by surgeons preoperatively may provide optimal return to work outcomes after surgery. 3.

Evaluation of job satisfaction and working atmosphere of dental nurses in Germany.

PubMed

Goetz, Katja; Hasse, Philipp; Campbell, Stephen M; Berger, Sarah; Dörfer, Christof E; Hahn, Karolin; Szecsenyi, Joachim

2016-02-01

The purpose of the study was to assess the level of job satisfaction of dental nurses in ambulatory care and to explore the impact of aspects of working atmosphere on and their association with job satisfaction. This cross-sectional study was based on a job satisfaction survey. Data were collected from 612 dental nurses working in 106 dental care practices. Job satisfaction was measured with the 10-item Warr-Cook-Wall job satisfaction scale. Working atmosphere was measured with five items. Linear regression analyses were performed in which each item of the job satisfaction scale was handled as dependent variables. A stepwise linear regression analysis was performed with overall job satisfaction and the five items of working atmosphere, job satisfaction, and individual characteristics. The response rate was 88.3%. Dental nurses were satisfied with 'colleagues' and least satisfied with 'income.' Different aspects of job satisfaction were mostly associated with the following working atmosphere issues: 'responsibilities within the practice team are clear,' 'suggestions for improvement are taken seriously,' 'working atmosphere in the practice team is good,' and 'made easier to admit own mistakes.' Within the stepwise linear regression analysis, the aspect 'physical working condition' (β = 0.304) showed the highest association with overall job satisfaction. The total explained variance of the 14 associated variables was 0.722 with overall job satisfaction. Working atmosphere within this discrete sample of dental care practice seemed to be an important influence on reported working condition and job satisfaction for dental nurses. Because of the high association of job satisfaction with physical working condition, the importance of paying more attention to an ergonomic working position for dental nurses to ensure optimal quality of care is highlighted. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Factors affecting match performance in professional Australian football.

PubMed

Sullivan, Courtney; Bilsborough, Johann C; Cianciosi, Michael; Hocking, Joel; Cordy, Justin T; Coutts, Aaron J

2014-05-01

To determine the physical activity measures and skill-performance characteristics that contribute to coaches' perception of performance and player performance rank in professional Australian Football (AF). Prospective, longitudinal. Physical activity profiles were assessed via microtechnology (GPS and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill-performance measure and player-rank scores (Champion Data Rank) were provided by a commercial statistical provider. The physical-performance variables, skill involvements, and individual player performance scores were expressed relative to playing time for each quarter. A stepwise multiple regression was used to examine the contribution of physical activity and skill involvements to coaches' perception of performance and player rank in AF. Stepwise multiple-regression analysis revealed that 42.2% of the variance in coaches' perception of a player's performance could be explained by the skill-performance characteristics (player rank/min, effective kicks/min, pressure points/min, handballs/min, and running bounces/ min), with a small contribution from physical activity measures (accelerations/min) (adjusted R2 = .422, F6,282 = 36.054, P < .001). Multiple regression also revealed that 66.4% of the adjusted variance in player rank could be explained by total disposals/min, effective kicks/min, pressure points/min, kick clangers/min, marks/min, speed (m/min), and peak speed (adjusted R2 = .664, F7,281 = 82.289, P < .001). Increased physical activity throughout a match (speed [m/min] β - 0.097 and peak speed β - 0.116) negatively affects player rank in AF. Skill performance rather than increased physical activity is more important to coaches' perception of performance and player rank in professional AF.

Seminal Plasma HIV-1 RNA Concentration Is Strongly Associated with Altered Levels of Seminal Plasma Interferon-γ, Interleukin-17, and Interleukin-5

PubMed Central

Hoffman, Jennifer C.; Anton, Peter A.; Baldwin, Gayle Cocita; Elliott, Julie; Anisman-Posner, Deborah; Tanner, Karen; Grogan, Tristan; Elashoff, David; Sugar, Catherine; Yang, Otto O.

2014-01-01

Abstract Seminal plasma HIV-1 RNA level is an important determinant of the risk of HIV-1 sexual transmission. We investigated potential associations between seminal plasma cytokine levels and viral concentration in the seminal plasma of HIV-1-infected men. This was a prospective, observational study of paired blood and semen samples from 18 HIV-1 chronically infected men off antiretroviral therapy. HIV-1 RNA levels and cytokine levels in seminal plasma and blood plasma were measured and analyzed using simple linear regressions to screen for associations between cytokines and seminal plasma HIV-1 levels. Forward stepwise regression was performed to construct the final multivariate model. The median HIV-1 RNA concentrations were 4.42 log10 copies/ml (IQR 2.98, 4.70) and 2.96 log10 copies/ml (IQR 2, 4.18) in blood and seminal plasma, respectively. In stepwise multivariate linear regression analysis, blood HIV-1 RNA level (p<0.0001) was most strongly associated with seminal plasma HIV-1 RNA level. After controlling for blood HIV-1 RNA level, seminal plasma HIV-1 RNA level was positively associated with interferon (IFN)-γ (p=0.03) and interleukin (IL)-17 (p=0.03) and negatively associated with IL-5 (p=0.0007) in seminal plasma. In addition to blood HIV-1 RNA level, cytokine profiles in the male genital tract are associated with HIV-1 RNA levels in semen. The Th1 and Th17 cytokines IFN-γ and IL-17 are associated with increased seminal plasma HIV-1 RNA, while the Th2 cytokine IL-5 is associated with decreased seminal plasma HIV-1 RNA. These results support the importance of genital tract immunomodulation in HIV-1 transmission. PMID:25209674

A stepwise composite echocardiographic score predicts severe pulmonary hypertension in patients with interstitial lung disease.

PubMed

Bax, Simon; Bredy, Charlene; Kempny, Aleksander; Dimopoulos, Konstantinos; Devaraj, Anand; Walsh, Simon; Jacob, Joseph; Nair, Arjun; Kokosi, Maria; Keir, Gregory; Kouranos, Vasileios; George, Peter M; McCabe, Colm; Wilde, Michael; Wells, Athol; Li, Wei; Wort, Stephen John; Price, Laura C

2018-04-01

European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs. Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used "additional PH signs" where RVSP was unavailable, using a bootstrapping technique. Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%). This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD.

A stepwise composite echocardiographic score predicts severe pulmonary hypertension in patients with interstitial lung disease

PubMed Central

Bax, Simon; Bredy, Charlene; Kempny, Aleksander; Dimopoulos, Konstantinos; Devaraj, Anand; Walsh, Simon; Jacob, Joseph; Nair, Arjun; Kokosi, Maria; Keir, Gregory; Kouranos, Vasileios; George, Peter M.; McCabe, Colm; Wilde, Michael; Wells, Athol; Li, Wei; Wort, Stephen John; Price, Laura C.

2018-01-01

European Respiratory Society (ERS) guidelines recommend the assessment of patients with interstitial lung disease (ILD) and severe pulmonary hypertension (PH), as defined by a mean pulmonary artery pressure (mPAP) ≥35 mmHg at right heart catheterisation (RHC). We developed and validated a stepwise echocardiographic score to detect severe PH using the tricuspid regurgitant velocity and right atrial pressure (right ventricular systolic pressure (RVSP)) and additional echocardiographic signs. Consecutive ILD patients with suspected PH underwent RHC between 2005 and 2015. Receiver operating curve analysis tested the ability of components of the score to predict mPAP ≥35 mmHg, and a score devised using a stepwise approach. The score was tested in a contemporaneous validation cohort. The score used “additional PH signs” where RVSP was unavailable, using a bootstrapping technique. Within the derivation cohort (n=210), a score ≥7 predicted severe PH with 89% sensitivity, 71% specificity, positive predictive value 68% and negative predictive value 90%, with similar performance in the validation cohort (n=61) (area under the curve (AUC) 84.8% versus 83.1%, p=0.8). Although RVSP could be estimated in 92% of studies, reducing this to 60% maintained a fair accuracy (AUC 74.4%). This simple stepwise echocardiographic PH score can predict severe PH in patients with ILD. PMID:29750141

Models to predict emissions of health-damaging pollutants and global warming contributions of residential fuel/stove combinations in China.

PubMed

Edwards, Rufus D; Smith, Kirk R; Zhang, Junfeng; Ma, Yuqing

2003-01-01

Residential energy use in developing countries has traditionally been associated with combustion devices of poor energy efficiency, which have been shown to produce substantial health-damaging pollution, contributing significantly to the global burden of disease, and greenhouse gas (GHG) emissions. Precision of these estimates in China has been hampered by limited data on stove use and fuel consumption in residences. In addition limited information is available on variability of emissions of pollutants from different stove/fuel combinations in typical use, as measurement of emission factors requires measurement of multiple chemical species in complex burn cycle tests. Such measurements are too costly and time consuming for application in conjunction with national surveys. Emissions of most of the major health-damaging pollutants (HDP) and many of the gases that contribute to GHG emissions from cooking stoves are the result of the significant portion of fuel carbon that is diverted to products of incomplete combustion (PIC) as a result of poor combustion efficiencies. The approximately linear increase in emissions of PIC with decreasing combustion efficiencies allows development of linear models to predict emissions of GHG and HDP intrinsically linked to CO2 and PIC production, and ultimately allows the prediction of global warming contributions from residential stove emissions. A comprehensive emissions database of three burn cycles of 23 typical fuel/stove combinations tested in a simulated village house in China has been used to develop models to predict emissions of HDP and global warming commitment (GWC) from cooking stoves in China, that rely on simple survey information on stove and fuel use that may be incorporated into national surveys. Stepwise regression models predicted 66% of the variance in global warming commitment (CO2, CO, CH4, NOx, TNMHC) per 1 MJ delivered energy due to emissions from these stoves if survey information on fuel type was available. Subsequently if stove type is known, stepwise regression models predicted 73% of the variance. Integrated assessment of policies to change stove or fuel type requires that implications for environmental impacts, energy efficiency, global warming and human exposures to HDP emissions can be evaluated. Frequently, this involves measurement of TSP or CO as the major HDPs. Incorporation of this information into models to predict GWC predicted 79% and 78% of the variance respectively. Clearly, however, the complexity of making multiple measurements in conjunction with a national survey would be both expensive and time consuming. Thus, models to predict HDP using simple survey information, and with measurement of either CO/CO2 or TSP/CO2 to predict emission factors for the other HDP have been derived. Stepwise regression models predicted 65% of the variance in emissions of total suspended particulate as grams of carbon (TSPC) per 1 MJ delivered if survey information on fuel and stove type was available and 74% if the CO/CO2 ratio was measured. Similarly stepwise regression models predicted 76% of the variance in COC emissions per MJ delivered with survey information on stove and fuel type and 85% if the TSPC/CO2 ratio was measured. Ultimately, with international agreements on emissions trading frameworks, similar models based on extensive databases of the fate of fuel carbon during combustion from representative household stoves would provide a mechanism for computing greenhouse credits in the residential sector as part of clean development mechanism frameworks and monitoring compliance to control regimes.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

PubMed

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Assessing the origin of old apparent ages derived by Pb stepwise leaching of vein-hosted epidote from Mount Isa, northwest Queensland, Australia

NASA Astrophysics Data System (ADS)

Duncan, Robert J.; Maas, Roland

2014-12-01

Epidote metasomatism affected large areas of tholeiitic metabasalts of the ~1,780 Ma Eastern Creek Volcanics in the Western Fold Belt of the Proterozoic Mount Isa inlier. Hydrothermal epidote generally occurs in quartz veins parallel to or boudinaged within the dominant S2 fabrics which formed during the regional metamorphic peak at ~1,570 Ma associated with the Isan orogeny. Previously published stable isotopic and halogen data suggest that the fluids responsible for epidote formation are metamorphic in origin (with an evaporitic component). Application of the Pb stepwise leaching technique to the epidote does not separate radiogenic Pb4+ and common Pb2+, generating little spread in 206Pb/204Pb (between 16.0 and 30.5). The causes for this relatively low range are twofold: There is little radiogenic Pb in the epidotes (the most radiogenic steps account for <1 % of Pb released) and both Pb2+ and uranogenic Pb4+ substitute into the same site in the epidote crystal lattice. Consequently, age regressions using the Pb stepwise leaching data give ages between 150 and 1,500 myrs older than the host rocks and over 450 myrs older than the thermal metamorphic peak. These old ages are attributed to chemical inheritance from the host metabasalts, via radiogenic Pb release by breakdown of phases such as zircon, monazite, titanomagnetite, and ilmenite during metamorphism. This idea is supported by trace element data and chrondrite-normalized rare earth element patterns that are similar to both the metabasalts and epidotes (except for a variable Eu anomaly in the latter). Relatively high fO2 during vein formation (Fe3+ dominates in the epidote crystal lattice) would allow the incorporation of Th4+ and exclusion of U6+ and would explain elevated Th/U ratios (up to 12) in epidote compared with the host metabasalts. Non-incorporation of U would explain the relatively low U/Pb ratios and non-radiogenic character of the epidote. This process may provide a source of metal for the small U deposits around Mount Isa and may also suggest a relationship between U mineralization and regional Cu mobilization during the Isan orogeny. Our work suggests that non-conventional geochronometers should be used only if additional geological information and geochemical data (e.g., mineral chemistry, trace elements) are available to evaluate any resulting age calculations.

Step-by-step training in basic laparoscopic skills using two-way web conferencing software for remote coaching: A multicenter randomized controlled study.

PubMed

Mizota, Tomoko; Kurashima, Yo; Poudel, Saseem; Watanabe, Yusuke; Shichinohe, Toshiaki; Hirano, Satoshi

2018-07-01

Despite its advantages, few trainees outside of North America have access to simulation training. We hypothesized that a stepwise training method using tele-mentoring system would be an efficient technique for training in basic laparoscopic skills. Residents were randomized into two groups and trained to proficiency in intracorporeal suturing. The stepwise group (SG) practiced the task step-by-step, while the other group practiced comprehensively (CG). Each participant received weekly coaching via two-way web conferencing software. The duration of the coaching sessions and self-practice time were compared between the two groups. Twenty residents from 15 institutions participated, and all achieved proficiency. Coaching sessions using tele-mentoring system were completed without difficulties. The SG required significantly shorter coaching time per session than the CG (p = .002). There was no significant difference in self-practice time. The stepwise training method with the tele-mentoring system appears to make efficient use of surgical trainees' and trainers' time. Copyright © 2017 Elsevier Inc. All rights reserved.

Fear of falling in older adults living at home: associated factors.

PubMed

Vitorino, Luciano Magalhães; Teixeira, Carla Araujo Bastos; Boas, Eliandra Laís Vilas; Pereira, Rúbia Lopes; Santos, Naiana Oliveira Dos; Rozendo, Célia Alves

2017-04-10

To identify the factors associated with the fear of falling in the older adultliving at home. Cross-sectional study with probabilistic sampling of older adultenrolled in two Family Health Strategies (FHS). The fear of falling was measured by the Brazilian version of the Falls Efficacy Scale-International and by a household questionnairethat contained the explanatory variables. Multiple Linear Regression using the stepwise selection technique and the Generalized Linear Models were used in the statistical analyses. A total of170 older adultsparticipated in the research, 85 from each FHS. The majority (57.1%) aged between 60 and 69; 67.6% were female; 46.1% fell once in the last year. The majority of the older adults(66.5%) had highfear of falling. In the final multiple linear regression model, it was identified that a higher number of previous falls, female gender, older age, and worse health self-assessment explained 37% of the fear of falling among the older adult. The findings reinforce the need to assess the fear of falling among the older adultliving at home, in conjunction with the development and use ofstrategies based on modifiable factors by professionalsto reduce falls and improve health status, which may contribute to the reduction of the fear of falling among the older adult. Identificar os fatores associados ao medo de cair em idosos residentes no domicílio. Estudo transversal com amostragem probabilística de idosos cadastrados em duas Estratégias Saúde da Família (ESF). O medo de cair foi avaliado pela versão brasileira da escala Falls Efficacy Scale International e por um inquérito domiciliar que continha as variáveis explicativas.A Regressão Linear Múltipla por meio da técnica stepwise selectione osModelos Lineares Generalizados foram utilizados nas análises estatísticas. Participaram da pesquisa170 idosos, 85 de cada ESF. A maioria (57,1%) tinha entre 60 e 69 anos de idade; 67,6% eram do sexo feminino; 46,1% tiveram queda no último ano. A maioria dos idosos (66,5%) tinha elevado medo de cair. No modelo final de regressão multivariada, identificou-se que maior número de quedas anteriores, sexo feminino, idade mais avançada, e pior autoavaliação de saúde explicaram 37% do medo de cair entre os idosos. Os achados reforçam a necessidade da avaliação do medo de cair entre os idosos que residem no próprio domicílio, assim como o desenvolvimento e a utilização de estratégias pelos profissionais voltadas para os fatores modificáveis,de modo a reduzir as quedas e melhorar o estado de saúde, o que pode contribuir para a diminuição do medo de cair entre os idosos.

Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study.

PubMed

Asselbergs, Joost; Ruwaard, Jeroen; Ejdys, Michal; Schrader, Niels; Sijbrandij, Marit; Riper, Heleen

2016-03-29

Ecological momentary assessment (EMA) is a useful method to tap the dynamics of psychological and behavioral phenomena in real-world contexts. However, the response burden of (self-report) EMA limits its clinical utility. The aim was to explore mobile phone-based unobtrusive EMA, in which mobile phone usage logs are considered as proxy measures of clinically relevant user states and contexts. This was an uncontrolled explorative pilot study. Our study consisted of 6 weeks of EMA/unobtrusive EMA data collection in a Dutch student population (N=33), followed by a regression modeling analysis. Participants self-monitored their mood on their mobile phone (EMA) with a one-dimensional mood measure (1 to 10) and a two-dimensional circumplex measure (arousal/valence, -2 to 2). Meanwhile, with participants' consent, a mobile phone app unobtrusively collected (meta) data from six smartphone sensor logs (unobtrusive EMA: calls/short message service (SMS) text messages, screen time, application usage, accelerometer, and phone camera events). Through forward stepwise regression (FSR), we built personalized regression models from the unobtrusive EMA variables to predict day-to-day variation in EMA mood ratings. The predictive performance of these models (ie, cross-validated mean squared error and percentage of correct predictions) was compared to naive benchmark regression models (the mean model and a lag-2 history model). A total of 27 participants (81%) provided a mean 35.5 days (SD 3.8) of valid EMA/unobtrusive EMA data. The FSR models accurately predicted 55% to 76% of EMA mood scores. However, the predictive performance of these models was significantly inferior to that of naive benchmark models. Mobile phone-based unobtrusive EMA is a technically feasible and potentially powerful EMA variant. The method is young and positive findings may not replicate. At present, we do not recommend the application of FSR-based mood prediction in real-world clinical settings. Further psychometric studies and more advanced data mining techniques are needed to unlock unobtrusive EMA's true potential.

Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study

PubMed Central

2010-01-01

Background There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. Methods Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. Results Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p < 0.001). Local meteorology did not significantly affect associations with principal GIS variables, and the regression model structure was robust to various model-building approaches. Conclusion Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal. PMID:21083910

Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study.

PubMed

Adamkiewicz, Gary; Hsu, Hsiao-Hsien; Vallarino, Jose; Melly, Steven J; Spengler, John D; Levy, Jonathan I

2010-11-17

There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p < 0.001). Local meteorology did not significantly affect associations with principal GIS variables, and the regression model structure was robust to various model-building approaches. Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal.

Guided Inquiry in a Biochemistry Laboratory Course Improves Experimental Design Ability

ERIC Educational Resources Information Center

Goodey, Nina M.; Talgar, Cigdem P.

2016-01-01

Many biochemistry laboratory courses expose students to laboratory techniques through pre-determined experiments in which students follow stepwise protocols provided by the instructor. This approach fails to provide students with sufficient opportunities to practice experimental design and critical thinking. Ten inquiry modules were created for a…

Using Small-Step Refinement for Algorithm Verification in Computer Science Education

ERIC Educational Resources Information Center

Simic, Danijela

2015-01-01

Stepwise program refinement techniques can be used to simplify program verification. Programs are better understood since their main properties are clearly stated, and verification of rather complex algorithms is reduced to proving simple statements connecting successive program specifications. Additionally, it is easy to analyse similar…

Computer Mapping of Water Quality in Saginaw Bay with LANDSAT Digital Data

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Shah, N. J.; Smith, V. E.; Mckeon, J. B.

1976-01-01

The author has identified the following significant results. LANDSAT digital data and ground truth measurements for Saginaw Bay (Lake Huron), Michigan, for 31 July 1975 were correlated by stepwise linear regression and the resulting equations used to estimate invisible water quality parameters in nonsampled areas. Chloride, conductivity, total Kjeldahl nitrogen, total phosphorus, and chlorophyll a were best correlated with the ratio of LANDSAT Band 4 to Band 5. Temperature and Secchi depth correlate best with Band 5.

Analysis of flight data from a High-Incidence Research Model by system identification methods

NASA Technical Reports Server (NTRS)

Batterson, James G.; Klein, Vladislav

1989-01-01

Data partitioning and modified stepwise regression were applied to recorded flight data from a Royal Aerospace Establishment high incidence research model. An aerodynamic model structure and corresponding stability and control derivatives were determined for angles of attack between 18 and 30 deg. Several nonlinearities in angles of attack and sideslip as well as a unique roll-dominated set of lateral modes were found. All flight estimated values were compared to available wind tunnel measurements.

Beef customer satisfaction: factors affecting consumer evaluations of clod steaks.

PubMed

Goodson, K J; Morgan, W W; Reagan, J O; Gwartney, B L; Courington, S M; Wise, J W; Savell, J W

2002-02-01

An in-home beef study evaluated consumer ratings of clod steaks (n = 1,264) as influenced by USDA quality grade (Top Choice, Low Choice, High Select, and Low Select), city (Chicago and Philadelphia), consumer segment (Beef Loyals, who are heavy consumers of beef; Budget Rotators, who are cost-driven and split meat consumption between beef and chicken; and Variety Rotators, who have higher incomes and education and split their meat consumption among beef, poultry, and other foods), degree of doneness, and cooking method. Consumers evaluated each steak for Overall Like, Tenderness, Juiciness, Flavor Like, and Flavor Amount using 10-point scales. Grilling was the predominant cooking method used, and steaks were cooked to medium-well and greater degrees of doneness. Interactions existed involving the consumer-controlled factors of degree of doneness and(or) cooking method for all consumer-evaluated traits for the clod steak (P < 0.05). USDA grade did not affect any consumer evaluation traits or Warner-Bratzler shear force values (P > 0.05). One significant main effect, segment (P = 0.006), and one significant interaction, cooking method x city (P = 0.0407), existed for Overall Like ratings. Consumers in the Beef Loyals segment rated clod steaks higher in Overall Like than the other segments. Consumers in Chicago tended to give more uniform Overall Like ratings to clod steaks cooked by various methods; however, consumers in Philadelphia gave among the highest ratings to clod steaks that were fried and among the lowest to those that were grilled. Additionally, although clod steaks that were fried were given generally high ratings by consumers in Philadelphia, consumers in Chicago rated clod steaks cooked in this manner significantly lower than those in Philadelphia. Conversely, consumers in Chicago rated clod steaks that were grilled significantly higher than consumers in Philadelphia. Correlation and stepwise regression analyses indicated that Flavor Like was driving customer satisfaction of the clod steak. Flavor Like was the sensory trait most highly correlated to Overall Like, followed by Tenderness, Flavor Amount, and Juiciness. Flavor Like was the first variable to enter into the stepwise regression equation for predicting Overall Like, followed by Tenderness and Flavor Amount. For the clod steak, it is likely that preparation techniques that improve flavor without reducing tenderness positively affect customer satisfaction.

Quantitative analysis of bayberry juice acidity based on visible and near-infrared spectroscopy

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

Shao Yongni; He Yong; Mao Jingyuan

Visible and near-infrared (Vis/NIR) reflectance spectroscopy has been investigated for its ability to nondestructively detect acidity in bayberry juice. What we believe to be a new, better mathematic model is put forward, which we have named principal component analysis-stepwise regression analysis-backpropagation neural network (PCA-SRA-BPNN), to build a correlation between the spectral reflectivity data and the acidity of bayberry juice. In this model, the optimum network parameters,such as the number of input nodes, hidden nodes, learning rate, and momentum, are chosen by the value of root-mean-square (rms) error. The results show that its prediction statistical parameters are correlation coefficient (r) ofmore » 0.9451 and root-mean-square error of prediction(RMSEP) of 0.1168. Partial least-squares (PLS) regression is also established to compare with this model. Before doing this, the influences of various spectral pretreatments (standard normal variate, multiplicative scatter correction, S. Golay first derivative, and wavelet package transform) are compared. The PLS approach with wavelet package transform preprocessing spectra is found to provide the best results, and its prediction statistical parameters are correlation coefficient (r) of 0.9061 and RMSEP of 0.1564. Hence, these two models are both desirable to analyze the data from Vis/NIR spectroscopy and to solve the problem of the acidity prediction of bayberry juice. This supplies basal research to ultimately realize the online measurements of the juice's internal quality through this Vis/NIR spectroscopy technique.« less

Impact of Dental Disorders and its Influence on Self Esteem Levels among Adolescents.

PubMed

Kaur, Puneet; Singh, Simarpreet; Mathur, Anmol; Makkar, Diljot Kaur; Aggarwal, Vikram Pal; Batra, Manu; Sharma, Anshika; Goyal, Nikita

2017-04-01

Self esteem is more of a psychological concept therefore, even the common dental disorders like dental trauma, tooth loss and untreated carious lesions may affect the self esteem thus influencing the quality of life. This study aims to assess the impact of dental disorders among the adolescents on their self esteem level. The present cross-sectional study was conducted among 10 to 17 years adolescents. In order to obtain a representative sample, multistage sampling technique was used and sample was selected based on Probability Proportional to Enrolment size (PPE). Oral health assessment was carried out using WHO type III examination and self esteem was estimated using the Rosenberg Self Esteem Scale score (RSES). The descriptive and inferential analysis of the data was done by using IBM SPSS software. Logistic and linear regression analysis was executed to test the individual association of different independent clinical variables with self esteem. Total sample of 1140 adolescents with mean age of 14.95 ±2.08 and RSES of 27.09 ±3.12 were considered. Stepwise multiple linear regression analysis was applied and best predictors in relation to RSES in the descending order were Dental Health Component (DHC), Aesthetic Component (AC), dental decay {(aesthetic zone), (masticatory zone)}, tooth loss {(aesthetic zone), (masticatory zone)} and anterior fracture of tooth. It was found that various dental disorders like malocclusion, anterior traumatic tooth, tooth loss and untreated decay causes a profound impact on aesthetics and psychosocial behaviour of adolescents, thus affecting their self esteem.

Mapping land cover from satellite images: A basic, low cost approach

NASA Technical Reports Server (NTRS)

Elifrits, C. D.; Barney, T. W.; Barr, D. J.; Johannsen, C. J.

1978-01-01

Simple, inexpensive methodologies developed for mapping general land cover and land use categories from LANDSAT images are reported. One methodology, a stepwise, interpretive, direct tracing technique was developed through working with university students from different disciplines with no previous experience in satellite image interpretation. The technique results in maps that are very accurate in relation to actual land cover and relative to the small investment in skill, time, and money needed to produce the products.

Characteristics of patients making serious inhaler errors with a dry powder inhaler and association with asthma-related events in a primary care setting

PubMed Central

Westerik, Janine A. M.; Carter, Victoria; Chrystyn, Henry; Burden, Anne; Thompson, Samantha L.; Ryan, Dermot; Gruffydd-Jones, Kevin; Haughney, John; Roche, Nicolas; Lavorini, Federico; Papi, Alberto; Infantino, Antonio; Roman-Rodriguez, Miguel; Bosnic-Anticevich, Sinthia; Lisspers, Karin; Ställberg, Björn; Henrichsen, Svein Høegh; van der Molen, Thys; Hutton, Catherine; Price, David B.

2016-01-01

Abstract Objective: Correct inhaler technique is central to effective delivery of asthma therapy. The study aim was to identify factors associated with serious inhaler technique errors and their prevalence among primary care patients with asthma using the Diskus dry powder inhaler (DPI). Methods: This was a historical, multinational, cross-sectional study (2011–2013) using the iHARP database, an international initiative that includes patient- and healthcare provider-reported questionnaires from eight countries. Patients with asthma were observed for serious inhaler errors by trained healthcare providers as predefined by the iHARP steering committee. Multivariable logistic regression, stepwise reduced, was used to identify clinical characteristics and asthma-related outcomes associated with ≥1 serious errors. Results: Of 3681 patients with asthma, 623 (17%) were using a Diskus (mean [SD] age, 51 [14]; 61% women). A total of 341 (55%) patients made ≥1 serious errors. The most common errors were the failure to exhale before inhalation, insufficient breath-hold at the end of inhalation, and inhalation that was not forceful from the start. Factors significantly associated with ≥1 serious errors included asthma-related hospitalization the previous year (odds ratio [OR] 2.07; 95% confidence interval [CI], 1.26–3.40); obesity (OR 1.75; 1.17–2.63); poor asthma control the previous 4 weeks (OR 1.57; 1.04–2.36); female sex (OR 1.51; 1.08–2.10); and no inhaler technique review during the previous year (OR 1.45; 1.04–2.02). Conclusions: Patients with evidence of poor asthma control should be targeted for a review of their inhaler technique even when using a device thought to have a low error rate. PMID:26810934

Analysis of the Magnitude and Frequency of Peak Discharge and Maximum Observed Peak Discharge in New Mexico and Surrounding Areas

USGS Publications Warehouse

Waltemeyer, Scott D.

2008-01-01

Estimates of the magnitude and frequency of peak discharges are necessary for the reliable design of bridges, culverts, and open-channel hydraulic analysis, and for flood-hazard mapping in New Mexico and surrounding areas. The U.S. Geological Survey, in cooperation with the New Mexico Department of Transportation, updated estimates of peak-discharge magnitude for gaging stations in the region and updated regional equations for estimation of peak discharge and frequency at ungaged sites. Equations were developed for estimating the magnitude of peak discharges for recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years at ungaged sites by use of data collected through 2004 for 293 gaging stations on unregulated streams that have 10 or more years of record. Peak discharges for selected recurrence intervals were determined at gaging stations by fitting observed data to a log-Pearson Type III distribution with adjustments for a low-discharge threshold and a zero skew coefficient. A low-discharge threshold was applied to frequency analysis of 140 of the 293 gaging stations. This application provides an improved fit of the log-Pearson Type III frequency distribution. Use of the low-discharge threshold generally eliminated the peak discharge by having a recurrence interval of less than 1.4 years in the probability-density function. Within each of the nine regions, logarithms of the maximum peak discharges for selected recurrence intervals were related to logarithms of basin and climatic characteristics by using stepwise ordinary least-squares regression techniques for exploratory data analysis. Generalized least-squares regression techniques, an improved regression procedure that accounts for time and spatial sampling errors, then were applied to the same data used in the ordinary least-squares regression analyses. The average standard error of prediction, which includes average sampling error and average standard error of regression, ranged from 38 to 93 percent (mean value is 62, and median value is 59) for the 100-year flood. The 1996 investigation standard error of prediction for the flood regions ranged from 41 to 96 percent (mean value is 67, and median value is 68) for the 100-year flood that was analyzed by using generalized least-squares regression analysis. Overall, the equations based on generalized least-squares regression techniques are more reliable than those in the 1996 report because of the increased length of record and improved geographic information system (GIS) method to determine basin and climatic characteristics. Flood-frequency estimates can be made for ungaged sites upstream or downstream from gaging stations by using a method that transfers flood-frequency data at the gaging station to the ungaged site by using a drainage-area ratio adjustment equation. The peak discharge for a given recurrence interval at the gaging station, drainage-area ratio, and the drainage-area exponent from the regional regression equation of the respective region is used to transfer the peak discharge for the recurrence interval to the ungaged site. Maximum observed peak discharge as related to drainage area was determined for New Mexico. Extreme events are commonly used in the design and appraisal of bridge crossings and other structures. Bridge-scour evaluations are commonly made by using the 500-year peak discharge for these appraisals. Peak-discharge data collected at 293 gaging stations and 367 miscellaneous sites were used to develop a maximum peak-discharge relation as an alternative method of estimating peak discharge of an extreme event such as a maximum probable flood.

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery - part II: an illustrative example.

PubMed

Cevenini, Gabriele; Barbini, Emanuela; Scolletta, Sabino; Biagioli, Bonizella; Giomarelli, Pierpaolo; Barbini, Paolo

2007-11-22

Popular predictive models for estimating morbidity probability after heart surgery are compared critically in a unitary framework. The study is divided into two parts. In the first part modelling techniques and intrinsic strengths and weaknesses of different approaches were discussed from a theoretical point of view. In this second part the performances of the same models are evaluated in an illustrative example. Eight models were developed: Bayes linear and quadratic models, k-nearest neighbour model, logistic regression model, Higgins and direct scoring systems and two feed-forward artificial neural networks with one and two layers. Cardiovascular, respiratory, neurological, renal, infectious and hemorrhagic complications were defined as morbidity. Training and testing sets each of 545 cases were used. The optimal set of predictors was chosen among a collection of 78 preoperative, intraoperative and postoperative variables by a stepwise procedure. Discrimination and calibration were evaluated by the area under the receiver operating characteristic curve and Hosmer-Lemeshow goodness-of-fit test, respectively. Scoring systems and the logistic regression model required the largest set of predictors, while Bayesian and k-nearest neighbour models were much more parsimonious. In testing data, all models showed acceptable discrimination capacities, however the Bayes quadratic model, using only three predictors, provided the best performance. All models showed satisfactory generalization ability: again the Bayes quadratic model exhibited the best generalization, while artificial neural networks and scoring systems gave the worst results. Finally, poor calibration was obtained when using scoring systems, k-nearest neighbour model and artificial neural networks, while Bayes (after recalibration) and logistic regression models gave adequate results. Although all the predictive models showed acceptable discrimination performance in the example considered, the Bayes and logistic regression models seemed better than the others, because they also had good generalization and calibration. The Bayes quadratic model seemed to be a convincing alternative to the much more usual Bayes linear and logistic regression models. It showed its capacity to identify a minimum core of predictors generally recognized as essential to pragmatically evaluate the risk of developing morbidity after heart surgery.

Perceived Social Support, Self-Esteem, and Internet Addiction Among Students of Al-Zahra University, Tehran, Iran.

PubMed

Naseri, Laila; Mohamadi, Jalal; Sayehmiri, Koroush; Azizpoor, Yosra

2015-09-01

Internet addiction is a global phenomenon that causes serious problems in mental health and social communication. Students form a vulnerable group, since they have free, easy, and daily access to the internet. The current study aimed to investigate perceived social support, self-esteem, and internet addiction among Al-Zahra University students. In the current descriptive research, the statistical sample consisted of 101 female students residing at AL-Zahra University dormitory, Tehran, Iran. Participants were randomly selected and their identities were classified. Then, they completed the Multidimensional Scale of Perceived Social Support, Rosenberg's Self-esteem Scale, and Yang Internet Addiction Test. After completion of the questionnaires, the data were analyzed using the correlation test and stepwise regression. The Pearson correlation coefficient indicated significant relationships between self-esteem and internet addiction (P < 0.05, r = -0.345), perceived social support (r = 0.224, P < 0.05), and the subscale of family (r = 0.311, P < 0.05). The findings also demonstrated a significant relationship between internet addiction and perceived social support (r = -0.332, P < 0.05), the subscale of family (P < 0.05, r = -0.402), and the other subscales (P < 0.05, r = -0.287). Results of the stepwise regression showed that the scale of internet addiction and the family subscale were predicative variables for self-esteem (r = 0.137, P < 0.01, F2, 96 = 77.7). Findings of the current study showed that persons with low self-esteem were more vulnerable to internet addiction.

Health related quality of life and influencing factors among welders.

PubMed

Qin, Jingxiang; Liu, Wuzhong; Zhu, Jun; Weng, Wei; Xu, Jiaming; Ai, Zisheng

2014-01-01

Occupational exposure to welding fumes is a serious occupational health problem all over the world. Welders are exposed to many occupational hazards; these hazards might cause some occupational diseases. The aim of the study was to assess the health related quality of life (HRQL) of electric welders in Shanghai China and explore influencing factors to HRQL of welders. 301 male welders (without pneumoconiosis) and 305 non-dust male workers in Shanghai were enrolled in this study. Short Form-36 (SF-36) health survey questionnaires were applied in this cross-sectional study. Socio-demographic, working and health factors were also collected. Multiple stepwise regress analysis was used to identify significant factors related to the eight dimension scores. Six dimensions including role-physical (RP), bodily pain (BP), general health (GH), validity (VT), social function (SF), and mental health (MH) were significantly worse in welders compared to non-dust workers. Multiple stepwise regress analysis results show that native place, monthly income, quantity of children, drinking, sleep time, welding type, use of personal protective equipment (PPE), great events in life, and some symptoms including dizziness, discomfort of cervical vertebra, low back pain, cough and insomnia may be influencing factors for HRQL of welders. Among these factors, only sleep time and the use of PPE were salutary. Some dimensions of HRQL of these welders have been affected. Enterprises which employ welders should take measures to protect the health of these people and improve their HRQL.

Correlation between increased urinary sodium excretion and decreased left ventricular diastolic function in patients with type 2 diabetes mellitus.

PubMed

Kagiyama, Shuntaro; Koga, Tokushi; Kaseda, Shigeru; Ishihara, Shiro; Kawazoe, Nobuyuki; Sadoshima, Seizo; Matsumura, Kiyoshi; Takata, Yutaka; Tsuchihashi, Takuya; Iida, Mitsuo

2009-10-01

Increased salt intake may induce hypertension, lead to cardiac hypertrophy, and exacerbate heart failure. When elderly patients develop heart failure, diastolic dysfunction is often observed, although the ejection fraction has decreased. Diabetes mellitus (DM) is an established risk factor for heart failure. However, little is known about the relationship between cardiac function and urinary sodium excretion (U-Na) in patients with DM. We measured 24-hour U-Na; cardiac function was evaluated directly during coronary catheterization in type 2 DM (n = 46) or non-DM (n = 55) patients with preserved cardiac systolic function (ejection fraction > or = 60%). Cardiac diastolic and systolic function was evaluated as - dp/dt and + dp/dt, respectively. The average of U-Na was 166.6 +/- 61.2 mEq/24 hour (mean +/- SD). In all patients, stepwise multivariate regression analysis revealed that - dp/dt had a negative correlation with serum B-type natriuretic peptide (BNP; beta = - 0.23, P = .021) and U-Na (beta = - 0.24, P = .013). On the other hand, + dp/dt negatively correlated with BNP (beta = - 0.30, P < .001), but did not relate to U-Na. In the DM-patients, stepwise multivariate regression analysis showed that - dp/dt still had a negative correlation with U-Na (beta = - 0.33, P = .025). The results indicated that increased urinary sodium excretion is associated with an impairment of cardiac diastolic function, especially in patients with DM, suggesting that a reduction of salt intake may improve cardiac diastolic function.

The rate of adherence to urate-lowering therapy and associated factors in Chinese gout patients: a cross-sectional study.

PubMed

Yin, Rulan; Cao, Haixia; Fu, Ting; Zhang, Qiuxiang; Zhang, Lijuan; Li, Liren; Gu, Zhifeng

2017-07-01

The aim of this study was to assess adherence rate and predictors of non-adherence with urate-lowering therapy (ULT) in Chinese gout patients. A cross-sectional study was administered to 125 gout patients using the Compliance Questionnaire on Rheumatology (CQR) for adherence to ULT. Patients were asked to complete the Treatment Satisfaction Questionnaire for Medication version II, Health Assessment Questionnaire, Confidence in Gout Treatment Questionnaire, Gout Knowledge Questionnaire, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and 36-Item Short Form Health Survey. Data were analyzed by independent sample t test, rank sum test, Chi-square analysis as well as binary stepwise logistic regression modeling. The data showed that the rate of adherence (CQR ≥80%) to ULT was 9.6% in our investigated gout patients. Adherence was associated with functional capacity, gout-related knowledge, satisfaction with medication, confidence in gout treatment and mental components summary. Multivariable analysis of binary stepwise logistic regression identified gout-related knowledge and satisfaction of effectiveness with medication was the independent risk factors of medication non-adherence. Patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication, were more likely not to adhere to ULT. Non-adherence to ULT among gout patients is exceedingly common, particularly in patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication. These findings could help medical personnel develop useful interventions to improve gout patients' medication adherence.

Stigma Resistance in Stable Schizophrenia: The Relative Contributions of Stereotype Endorsement, Self-Reflection, Self-Esteem, and Coping Styles

PubMed Central

Kao, Yu-Chen; Chang, Hsin-An; Tzeng, Nian-Sheng; Yeh, Chin-Bin; Loh, Ching-Hui

2017-01-01

Objective: Stigma resistance (SR) has recently emerged as a prominent aspect of research on recovery from schizophrenia, partly because studies have suggested that the development of stigma-resisting beliefs may help individuals lead a fulfilling life and recover from their mental illness. The present study assessed the relationship between personal SR ability and prediction variables such as self-stigma, self-esteem, self-reflection, coping styles, and psychotic symptomatology. Method: We performed an exploratory cross-sectional study of 170 community-dwelling patients with schizophrenia. Self-stigma, self-esteem, self-reflection, coping skills, and SR were assessed through self-report. Psychotic symptom severity was rated by the interviewers. Factors showing significant association in univariate analyses were included in a stepwise backward regression model. Results: Stepwise regressions revealed that acceptance of stereotypes of mental illness, self-esteem, self-reflection, and only 2 adaptive coping strategies (positive reinterpretation and religious coping) were significant predictors of SR. The prediction model accounted for 27.1% of the variance in the SR subscale score in our sample. Conclusions: Greater reflective capacity, greater self-esteem, greater preferences for positive reinterpretation and religious coping, and fewer endorsements of the stereotypes of mental illness may be key factors that relate to higher levels of SR. These factors are potentially modifiable in tailored interventions, and such modification may produce considerable improvements in the SR of the investigated population. This study has implications for psychosocial rehabilitation and emerging views of recovery from mental illness. PMID:28884606

Relationships between temperaments, occupational stress, and insomnia among Japanese workers.

PubMed

Deguchi, Yasuhiko; Iwasaki, Shinichi; Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Mitake, Tomoe; Nogi, Yukako; Inoue, Koki

2017-01-01

Insomnia among workers reduces the quality of life, contributes toward the economic burden of healthcare costs and losses in work performance. The relationship between occupational stress and insomnia has been reported in previous studies, but there has been little attention to temperament in occupational safety and health research. The aim of this study was to clarify the relationships between temperament, occupational stress, and insomnia. The subjects were 133 Japanese daytime local government employees. Temperament was assessed using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Insomnia was assessed using the Athens Insomnia Scale (AIS). Stepwise multiple logistic regression analyses were conducted. In a stepwise multivariate logistic regression analysis, it was found that the higher subdivided stress group by "role conflict" (OR = 5.29, 95% CI, 1.61-17.32) and anxious temperament score (OR = 1.33; 95% CI, 1.19-1.49) was associated with the presence of insomnia using an adjusted model, whereas other factors were excluded from the model. The study limitations were the sample size and the fact that only Japanese local government employees were surveyed. This study demonstrated the relationships between workers' anxious temperament, role conflict, and insomnia. Recognizing one's own anxious temperament would lead to self-insight, and the recognition of anxious temperament and reduction of role conflict by their supervisors or coworkers would reduce the prevalence of insomnia among workers in the workplace.

Job stress, achievement motivation and occupational burnout among male nurses.

PubMed

Hsu, Hsiu-Yueh; Chen, Sheng-Hwang; Yu, Hsing-Yi; Lou, Jiunn-Horng

2010-07-01

This paper is a report of an exploration of job stress, achievement motivation and occupational burnout in male nurses and to identify predictors of occupational burnout. Since the Nightingale era, the nursing profession has been recognized as 'women's work'. The data indicate that there are more female nurses than male nurses in Taiwan. However, the turnover rate for male nurses is twice that of female nurses. Understanding the factors that affect occupational burnout of male nurses may help researchers find ways to reduce the likelihood that they will quit. A survey was conducted in Taiwan in 2008 using a cross-sectional design. A total of 121 male nurses participated in the study. Mailed questionnaires were used to collect data, which were analysed using descriptive statistics and stepwise multiple regression. The job stress of male nurses was strongly correlated with occupational burnout (r = 0.64, P < 0.001). Stepwise multiple regression analyses indicated that job stress was the only factor to have a statistically significant direct influence on occupational burnout, accounting for 45.8% of the variance in this. Job stress was comprised of three dimensions, of which role conflict accounted for 40.8% of the variance in occupational burnout. The contribution of job stress to occupational burnout of male nurses was confirmed. As occupational burnout may influence the quality of care by these nurses, nurse managers should strive to decrease male nurses' job stress as this should lead to a reduction of negative outcomes of occupational burnout.

Factors Predicting Recovery of Oral Intake in Stroke Survivors with Dysphagia in a Convalescent Rehabilitation Ward.

PubMed

Ikenaga, Yasunori; Nakayama, Sayaka; Taniguchi, Hiroki; Ohori, Isao; Komatsu, Nahoko; Nishimura, Hitoshi; Katsuki, Yasuo

2017-05-01

Percutaneous endoscopic gastrostomy may be performed in dysphagic stroke patients. However, some patients regain complete oral intake without gastrostomy. This study aimed to investigate the predictive factors of intake, thereby determining gastrostomy indications. Stroke survivors admitted to our convalescent rehabilitation ward who underwent gastrostomy or nasogastric tube placement from 2009 to 2015 were divided into 2 groups based on intake status at discharge. Demographic data and Functional Independence Measure (FIM), Dysphagia Severity Scale (DSS), National Institutes of Health Stroke Scale, and Glasgow Coma Scale (GCS) scores on admission were compared between groups. We evaluated the factors predicting intake using a stepwise logistic regression analysis. Thirty-four patients recovered intake, whereas 38 achieved incomplete intake. Mean age was lower, mean body mass index (BMI) was higher, and mean time from stroke onset to admission was shorter in the complete intake group. The complete intake group had less impairment in terms of GCS, FIM, and DSS scores. In the stepwise logistic regression analysis, BMI, FIM-cognitive score, and DSS score were significant independent factors predicting intake. The formula of BMI × .26 + FIM cognitive score × .19 + DSS score × 1.60 predicted recovery of complete intake with a sensitivity of 88.2% and a specificity of 84.2%. Stroke survivors with dysphagia with a high BMI and FIM-cognitive and DSS scores tended to recover oral intake. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Stigma Resistance in Stable Schizophrenia: The Relative Contributions of Stereotype Endorsement, Self-Reflection, Self-Esteem, and Coping Styles.

PubMed

Kao, Yu-Chen; Lien, Yin-Ju; Chang, Hsin-An; Tzeng, Nian-Sheng; Yeh, Chin-Bin; Loh, Ching-Hui

2017-10-01

Stigma resistance (SR) has recently emerged as a prominent aspect of research on recovery from schizophrenia, partly because studies have suggested that the development of stigma-resisting beliefs may help individuals lead a fulfilling life and recover from their mental illness. The present study assessed the relationship between personal SR ability and prediction variables such as self-stigma, self-esteem, self-reflection, coping styles, and psychotic symptomatology. We performed an exploratory cross-sectional study of 170 community-dwelling patients with schizophrenia. Self-stigma, self-esteem, self-reflection, coping skills, and SR were assessed through self-report. Psychotic symptom severity was rated by the interviewers. Factors showing significant association in univariate analyses were included in a stepwise backward regression model. Stepwise regressions revealed that acceptance of stereotypes of mental illness, self-esteem, self-reflection, and only 2 adaptive coping strategies (positive reinterpretation and religious coping) were significant predictors of SR. The prediction model accounted for 27.1% of the variance in the SR subscale score in our sample. Greater reflective capacity, greater self-esteem, greater preferences for positive reinterpretation and religious coping, and fewer endorsements of the stereotypes of mental illness may be key factors that relate to higher levels of SR. These factors are potentially modifiable in tailored interventions, and such modification may produce considerable improvements in the SR of the investigated population. This study has implications for psychosocial rehabilitation and emerging views of recovery from mental illness.

Prediction of reported consumption of selected fat-containing foods.

PubMed

Tuorila, H; Pangborn, R M

1988-10-01

A total of 100 American females (mean age = 20.8 years) completed a questionnaire, in which their beliefs, evaluations, liking and consumption (frequency, consumption compared to others, intention to consume) of milk, cheese, ice cream, chocolate and "high-fat foods" were measured. For the design and analysis, the basic frame of reference was the Fishbein-Ajzen model of reasoned action, but the final analyses were carried out with stepwise multiple regression analysis. In addition to the components of the Fishbein-Ajzen model, beliefs and evaluations were used as independent variables. On the average, subjects reported liking all the products but not "high-fat foods", and thought that milk and cheese were "good for you" whereas the remaining items were "bad for you". Principal component analysis for beliefs revealed factors related to pleasantness/benefit aspects, to health and weight concern and to the "functionality" of the foods. In stepwise multiple regression analyses, liking was the predominant predictor of reported consumption for all the foods, but various belief factors, particularly those related to concern with weight, also significantly predicted consumption. Social factors played only a minor role. The multiple R's of the predictive functions varied from 0.49 to 0.74. The fact that all four foods studied elicited individual sets of beliefs and belief structures, and that none of them was rated similar to the generic "high-fat foods", emphasizes that consumers attach meaning to integrated food entities rather than to ingredients.

Behavioral activation: Is it the expectation or achievement, of mastery or pleasure that contributes to improvement in depression?

PubMed

Furukawa, Toshi A; Imai, Hissei; Horikoshi, Masaru; Shimodera, Shinji; Hiroe, Takahiro; Funayama, Tadashi; Akechi, Tatsuo

2018-06-06

Behavioral activation (BA) is receiving renewed interest as a stand-alone or as a component of cognitive-behavior therapy (CBT) for depression. However, few studies have examined which aspects of BA are most contributory to its efficacy. This is a secondary analysis of a 9-week randomized controlled trial of smartphone CBT for patients with major depression. Depression severity was measured at baseline and at end of treatment by the Patient Health Questionnaire-9. All aspects of behavioral activation tasks that the participants had engaged in, including their expected mastery and pleasure and obtained mastery and pleasure, were recorded in the web server. We examined their contribution to improvement in depression as simple correlations and in stepwise multivariable linear regression. Among the 78 patients who completed at least one behavioral experiment, all aspects of expected or achieved mastery or pleasure correlated with change in depression severity. Discrepancy between the expectation and achievement, representing unexpected gain in mastery or pleasure, was not correlated. In stepwise regression, expected mastery and pleasure, especially the maximum level of the latter, emerged as the strongest contributing factors. The study is observational and cannot deduce cause-effect relationships. It may be the expected and continued sense of pleasure in planning activities that are most meaningful and rewarding to individuals, and not the simple level or amount of obtained pleasure, that contributes to the efficacy of BA. Copyright © 2018. Published by Elsevier B.V.

Association between red blood cell distribution width (RDW) and carotid artery atherosclerosis (CAS) in patients with primary ischemic stroke.

PubMed

Jia, He; Li, Huimian; Zhang, Yan; Li, Che; Hu, Yingyun; Xia, Chunfang

2015-01-01

The present study aimed to explore the association between RDW and CAS in patients with ischemic stroke, expecting to find a new and significant diagnosis index for clinical practice. This cross-sectional study involves 432 consecutive patients with primary ischemic stroke (within 72 h). All subjects were confirmed by magnetic resonance imaging, and underwent physical examination, laboratory tests and carotid ultrasonography check. Finally, 392 patients were included according to the exclusion criteria. The odds ratios of independent variables were calculated using stepwise multiple logistic regression. Carotid intimal-medial thickness (IMT) and RDW are both significantly different between CAS group and control group. Univariate analyses show that high-sensitive C-reactive protein (Hs-CRP) and RDW (r=0.436) are both in significantly positive association with IMT. Stepwise multiple logistic regression shows that RDW is an independent protective factor of CAS in patients with ischemic stroke. Compared with the lowest quartile, the second to fourth quartiles are 1.13 (95% CI: 1.13-3.05), 2.02 (95% CI: 1.66-4.67), and 3.10 (95% CI: 2.46-7.65), respectively. The present study suggested that RDW level were higher than non-CAS in patients with primary ischemic stroke. Our results facilitated a bridge to connect RDW with ischemic stroke and further confirmed the role of RDW in the progression of the ischemic stroke. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Relationships between temperaments, occupational stress, and insomnia among Japanese workers

PubMed Central

Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Mitake, Tomoe; Nogi, Yukako; Inoue, Koki

2017-01-01

Insomnia among workers reduces the quality of life, contributes toward the economic burden of healthcare costs and losses in work performance. The relationship between occupational stress and insomnia has been reported in previous studies, but there has been little attention to temperament in occupational safety and health research. The aim of this study was to clarify the relationships between temperament, occupational stress, and insomnia. The subjects were 133 Japanese daytime local government employees. Temperament was assessed using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Insomnia was assessed using the Athens Insomnia Scale (AIS). Stepwise multiple logistic regression analyses were conducted. In a stepwise multivariate logistic regression analysis, it was found that the higher subdivided stress group by “role conflict” (OR = 5.29, 95% CI, 1.61–17.32) and anxious temperament score (OR = 1.33; 95% CI, 1.19–1.49) was associated with the presence of insomnia using an adjusted model, whereas other factors were excluded from the model. The study limitations were the sample size and the fact that only Japanese local government employees were surveyed. This study demonstrated the relationships between workers’ anxious temperament, role conflict, and insomnia. Recognizing one’s own anxious temperament would lead to self-insight, and the recognition of anxious temperament and reduction of role conflict by their supervisors or coworkers would reduce the prevalence of insomnia among workers in the workplace. PMID:28407025

Is patriarchy the source of men's higher mortality?

PubMed Central

Stanistreet, D; Bambra, C; Scott-Samuel, A

2005-01-01

Objective: To examine the relation between levels of patriarchy and male health by comparing female homicide rates with male mortality within countries. Hypothesis: High levels of patriarchy in a society are associated with increased mortality among men. Design: Cross sectional ecological study design. Setting: 51 countries from four continents were represented in the data—America, Europe, Australasia, and Asia. No data were available for Africa. Results: A multivariate stepwise linear regression model was used. Main outcome measure was age standardised male mortality rates for 51 countries for the year 1995. Age standardised female homicide rates and GDP per capita ranking were the explanatory variables in the model. Results were also adjusted for the effects of general rates of homicide. Age standardised female homicide rates and ranking of GDP were strongly correlated with age standardised male mortality rates (Pearson's r = 0.699 and Spearman's 0.744 respectively) and both correlations achieved significance (p<0.005). Both factors were subsequently included in the stepwise regression model. Female homicide rates explained 48.8% of the variance in male mortality, and GDP a further 13.6% showing that the higher the rate of female homicide, and hence the greater the indicator of patriarchy, the higher is the rate of mortality among men. Conclusion: These data suggest that oppression and exploitation harm the oppressors as well as those they oppress, and that men's higher mortality is a preventable social condition, which could be tackled through global social policy measures. PMID:16166362

Relationship between Spiritual Health and Quality of Life in Patients with Cancer.

PubMed

Mohebbifar, Rafat; Pakpour, Amir H; Nahvijou, Azin; Sadeghi, Atefeh

2015-01-01

As the essence of health in humans, spiritual health is a fundamental concept for discussing chronic diseases such as cancer and a major approach for improving quality of life in patients is through creating meaningfulness and purpose. The present descriptive analytical study was conducted to assess the relationship between spiritual health and quality of life in 210 patients with cancer admitted to the Cancer Institute of Iran, selected through convenience sampling in 2014. Data were collected using Spiritual Health Questionnaire and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ). Patients' performance was assessed through the Karnofsky Performance Status Indicator and their cognitive status through the Mini-Mental State Examination (MMSE). Data were analyzed in SPSS-16 using descriptive statistics and stepwise linear regression. The results obtained reported the mean and standard deviation of the patients' spiritual health scoreas 78.4±16.1and the mean and standard deviation of their quality of life score as 58.1±18.7. The stepwise linear regression analysis confirmed a positive and significant relationship between spiritual health and quality of life in patients with cancer (β=0.688 and r=0.00). The results of the study show that spiritual health should be more emphasized and reinforced as a factor involved in improving quality of life in patients with cancer. Designing care therapies and spiritual interventions is a priority in the treatment of these patients.

The investigation of the relationship between probability of suicide and reasons for living in psychiatric inpatients

PubMed Central

Eskiyurt, Reyhan; Ozkan, Birgul

2017-01-01

Aim: This study was carried out to determine the reasons of the suicide probability and reasons for living of the inpatients hospitalized at the psychiatry clinic and to analyze the relationship between them. Materials and Methods: The sample of the study consisted of 192 patients who were hospitalized in psychiatric clinics between February and May 2016 and who agreed to participate in the study. In collecting data, personal information form, suicide probability scale (SPS), reasons for living inventory (RFL), and Beck's depression inventory (BDI) were used. Stepwise regression method was used to determine the factors that predict suicide probability. Results: In the study, as a result of analyses made, the median score on the SPS was found 76.0, the median score on the RFL was found 137.0, the median score on the BDI of the patients was found 13.5, and it was found that patients with a high probability of suicide had less reasons for living and that their depression levels were very high. As a result of stepwise regression analysis, it was determined that suicidal ideation, reasons for living, maltreatment, education level, age, and income status were the predictors of suicide probability (F = 61.125; P < 0.001). Discussion: It was found that the patients who hospitalized in the psychiatric clinic have high suicide probability and the reasons of living are strong predictors of suicide probability in accordance with the literature. PMID:29497185

QSPR models for half-wave reduction potential of steroids: a comparative study between feature selection and feature extraction from subsets of or entire set of descriptors.

PubMed

Hemmateenejad, Bahram; Yazdani, Mahdieh

2009-02-16

Steroids are widely distributed in nature and are found in plants, animals, and fungi in abundance. A data set consists of a diverse set of steroids have been used to develop quantitative structure-electrochemistry relationship (QSER) models for their half-wave reduction potential. Modeling was established by means of multiple linear regression (MLR) and principle component regression (PCR) analyses. In MLR analysis, the QSPR models were constructed by first grouping descriptors and then stepwise selection of variables from each group (MLR1) and stepwise selection of predictor variables from the pool of all calculated descriptors (MLR2). Similar procedure was used in PCR analysis so that the principal components (or features) were extracted from different group of descriptors (PCR1) and from entire set of descriptors (PCR2). The resulted models were evaluated using cross-validation, chance correlation, application to prediction reduction potential of some test samples and accessing applicability domain. Both MLR approaches represented accurate results however the QSPR model found by MLR1 was statistically more significant. PCR1 approach produced a model as accurate as MLR approaches whereas less accurate results were obtained by PCR2 approach. In overall, the correlation coefficients of cross-validation and prediction of the QSPR models resulted from MLR1, MLR2 and PCR1 approaches were higher than 90%, which show the high ability of the models to predict reduction potential of the studied steroids.

Isolation and characterization of Chinese standard fulvic acid sub-fractions separated from forest soil by stepwise elution with pyrophosphate buffer.

PubMed

Bai, Yingchen; Wu, Fengchang; Xing, Baoshan; Meng, Wei; Shi, Guolan; Ma, Yan; Giesy, John P

2015-03-04

XAD-8 adsorption technique coupled with stepwise elution using pyrophosphate buffers with initial pH values of 3, 5, 7, 9, and 13 was developed to isolate Chinese standard fulvic acid (FA) and then separated the FA into five sub-fractions: FApH3, FApH5, FApH7, FApH9 and FApH13, respectively. Mass percentages of FApH3-FApH13 decreased from 42% to 2.5%, and the recovery ratios ranged from 99.0% to 99.5%. Earlier eluting sub-fractions contained greater proportions of carboxylic groups with greater polarity and molecular mass, and later eluting sub-fractions had greater phenolic and aliphatic content. Protein-like components, as well as amorphous and crystalline poly(methylene)-containing components were enriched using neutral and basic buffers. Three main mechanisms likely affect stepwise elution of humic components from XAD-8 resin with pyrophosphate buffers including: 1) the carboxylic-rich sub-fractions are deprotonated at lower pH values and eluted earlier, while phenolic-rich sub-fractions are deprotonated at greater pH values and eluted later. 2) protein or protein-like components can be desorbed and eluted by use of stepwise elution as progressively greater pH values exceed their isoelectric points. 3) size exclusion affects elution of FA sub-fractions. Successful isolation of FA sub-fractions will benefit exploration of the origin, structure, evolution and the investigation of interactions with environmental contaminants.

Isolation and Characterization of Chinese Standard Fulvic Acid Sub-fractions Separated from Forest Soil by Stepwise Elution with Pyrophosphate Buffer

PubMed Central

Bai, Yingchen; Wu, Fengchang; Xing, Baoshan; Meng, Wei; Shi, Guolan; Ma, Yan; Giesy, John P.

2015-01-01

XAD-8 adsorption technique coupled with stepwise elution using pyrophosphate buffers with initial pH values of 3, 5, 7, 9, and 13 was developed to isolate Chinese standard fulvic acid (FA) and then separated the FA into five sub-fractions: FApH3, FApH5, FApH7, FApH9 and FApH13, respectively. Mass percentages of FApH3-FApH13 decreased from 42% to 2.5%, and the recovery ratios ranged from 99.0% to 99.5%. Earlier eluting sub-fractions contained greater proportions of carboxylic groups with greater polarity and molecular mass, and later eluting sub-fractions had greater phenolic and aliphatic content. Protein-like components, as well as amorphous and crystalline poly(methylene)-containing components were enriched using neutral and basic buffers. Three main mechanisms likely affect stepwise elution of humic components from XAD-8 resin with pyrophosphate buffers including: 1) the carboxylic-rich sub-fractions are deprotonated at lower pH values and eluted earlier, while phenolic-rich sub-fractions are deprotonated at greater pH values and eluted later. 2) protein or protein-like components can be desorbed and eluted by use of stepwise elution as progressively greater pH values exceed their isoelectric points. 3) size exclusion affects elution of FA sub-fractions. Successful isolation of FA sub-fractions will benefit exploration of the origin, structure, evolution and the investigation of interactions with environmental contaminants. PMID:25735451

Isothermal Titration Calorimetry in the Student Laboratory

ERIC Educational Resources Information Center

Wadso, Lars; Li, Yujing; Li, Xi

2011-01-01

Isothermal titration calorimetry (ITC) is the measurement of the heat produced by the stepwise addition of one substance to another. It is a common experimental technique, for example, in pharmaceutical science, to measure equilibrium constants and reaction enthalpies. We describe a stirring device and an injection pump that can be used with a…

Student-Driven Design of Peptide Mimetics: Microwave-Assisted Synthesis of Peptoid Oligomers

ERIC Educational Resources Information Center

Pohl, Nicola L. B.; Kirshenbaum, Kent; Yoo, Barney; Schulz, Nathan; Zea, Corbin J.; Streff, Jennifer M.; Schwarz, Kimberly L.

2011-01-01

An experiment for the undergraduate organic laboratory is described in which peptide mimetic oligomers called "peptoids" are built stepwise on a solid-phase resin. Students employ two modern strategies to facilitate rapid multistep syntheses: solid-phase techniques to obviate the need for intermediate purifications and microwave irradiation to…

Assessment of the integrity of concrete bridge structures by acoustic emission technique

NASA Astrophysics Data System (ADS)

Yoon, Dong-Jin; Park, Philip; Jung, Juong-Chae; Lee, Seung-Seok

2002-06-01

This study was aimed at developing a new method for assessing the integrity of concrete structures. Especially acoustic emission technique was used in carrying out both laboratory experiment and field application. From the previous laboratory study, we confirmed that AE analysis provided a promising approach for estimating the level of damage and distress in concrete structures. The Felicity ratio, one of the key parameter for assessing damage, exhibits a favorable correlation with the overall damage level. The total number of AE events under stepwise cyclic loading also showed a good agreement with the damage level. In this study, a new suggested technique was applied to several concrete bridges in Korea in order to verify the applicability in field. The AE response was analyzed to obtain key parameters such as the total number and rate of AE events, AE parameter analysis for each event, and the characteristic features of the waveform as well as Felicity ratio analysis. Stepwise loading-unloading procedure for AE generation was introduced in field test by using each different weight of vehicle. According to the condition of bridge, for instance new or old bridge, AE event rate and AE generation behavior indicated many different aspects. The results showed that the suggested analyzing method would be a promising approach for assessing the integrity of concrete structures.

Applicability of linear regression equation for prediction of chlorophyll content in rice leaves

NASA Astrophysics Data System (ADS)

Li, Yunmei

2005-09-01

A modeling approach is used to assess the applicability of the derived equations which are capable to predict chlorophyll content of rice leaves at a given view direction. Two radiative transfer models, including PROSPECT model operated at leaf level and FCR model operated at canopy level, are used in the study. The study is consisted of three steps: (1) Simulation of bidirectional reflectance from canopy with different leaf chlorophyll contents, leaf-area-index (LAI) and under storey configurations; (2) Establishment of prediction relations of chlorophyll content by stepwise regression; and (3) Assessment of the applicability of these relations. The result shows that the accuracy of prediction is affected by different under storey configurations and, however, the accuracy tends to be greatly improved with increase of LAI.

Extending the 3ω method: thermal conductivity characterization of thin films.

PubMed

Bodenschatz, Nico; Liemert, André; Schnurr, Sebastian; Wiedwald, Ulf; Ziemann, Paul

2013-08-01

A lock-in technique for measurement of thermal conductivity and volumetric heat capacity of thin films is presented. The technique is based on the 3ω approach using electrical generation and detection of oscillatory heat along a thin metal strip. Thin films are deposited onto the backside of commercial silicon nitride membranes, forming a bilayer geometry with distinct thermal parameters. Stepwise comparison to an adapted heat diffusion model delivers these parameters for both layers. Highest sensitivity is found for metallic thin films.

Profiling of barrier capacitance and spreading resistance using a transient linearly increasing voltage technique.

PubMed

Gaubas, E; Ceponis, T; Kusakovskij, J

2011-08-01

A technique for the combined measurement of barrier capacitance and spreading resistance profiles using a linearly increasing voltage pulse is presented. The technique is based on the measurement and analysis of current transients, due to the barrier and diffusion capacitance, and the spreading resistance, between a needle probe and sample. To control the impact of deep traps in the barrier capacitance, a steady state bias illumination with infrared light was employed. Measurements of the spreading resistance and barrier capacitance profiles using a stepwise positioned probe on cross sectioned silicon pin diodes and pnp structures are presented.

Rydberg series in the lanthanides and actinides observed by stepwise laser excitation

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

Worden, E.F.; Solarz, R.W.; Paisner, J.A.

1977-05-18

The techniques of stepwise laser excitation were applied to obtain Ryberg series in the lanthanides and in uranium. The methods employed circumvent many of the experimental difficulties inherent in conventional absorption spectrosopy of these heavy atoms with very complex spectra. The Rydberg series observed have allowed the determination of accurate ionization limits. The values in eV are: Ce, 5.5387(4);Nd, 5.5250(6); Sm, 5.6437(10); Eu, 5.6704(3); Gd, 6.1502(6); Tb, 5.8639(6); Dy, 5.9390(6); Ho, 6.0216(6); Er 6.1077(6); U, 6.1941(5). A comparison of the f/sup n/s/sup 2/-f/sup n/s ionization limits as a function of n with theoretical calculations is made.

A unified approach for EIT imaging of regional overdistension and atelectasis in acute lung injury.

PubMed

Gómez-Laberge, Camille; Arnold, John H; Wolf, Gerhard K

2012-03-01

Patients with acute lung injury or acute respiratory distress syndrome (ALI/ARDS) are vulnerable to ventilator-induced lung injury. Although this syndrome affects the lung heterogeneously, mechanical ventilation is not guided by regional indicators of potential lung injury. We used electrical impedance tomography (EIT) to estimate the extent of regional lung overdistension and atelectasis during mechanical ventilation. Techniques for tidal breath detection, lung identification, and regional compliance estimation were combined with the Graz consensus on EIT lung imaging (GREIT) algorithm. Nine ALI/ARDS patients were monitored during stepwise increases and decreases in airway pressure. Our method detected individual breaths with 96.0% sensitivity and 97.6% specificity. The duration and volume of tidal breaths erred on average by 0.2 s and 5%, respectively. Respiratory system compliance from EIT and ventilator measurements had a correlation coefficient of 0.80. Stepwise increases in pressure could reverse atelectasis in 17% of the lung. At the highest pressures, 73% of the lung became overdistended. During stepwise decreases in pressure, previously-atelectatic regions remained open at sub-baseline pressures. We recommend that the proposed approach be used in collaborative research of EIT-guided ventilation strategies for ALI/ARDS.

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression.

PubMed

Martínez Gila, Diego Manuel; Cano Marchal, Pablo; Gómez Ortega, Juan; Gámez García, Javier

2018-03-25

Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO), the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation.

Quantifying prosthetic gait deviation using simple outcome measures

PubMed Central

Kark, Lauren; Odell, Ross; McIntosh, Andrew S; Simmons, Anne

2016-01-01

AIM: To develop a subset of simple outcome measures to quantify prosthetic gait deviation without needing three-dimensional gait analysis (3DGA). METHODS: Eight unilateral, transfemoral amputees and 12 unilateral, transtibial amputees were recruited. Twenty-eight able-bodied controls were recruited. All participants underwent 3DGA, the timed-up-and-go test and the six-minute walk test (6MWT). The lower-limb amputees also completed the Prosthesis Evaluation Questionnaire. Results from 3DGA were summarised using the gait deviation index (GDI), which was subsequently regressed, using stepwise regression, against the other measures. RESULTS: Step-length (SL), self-selected walking speed (SSWS) and the distance walked during the 6MWT (6MWD) were significantly correlated with GDI. The 6MWD was the strongest, single predictor of the GDI, followed by SL and SSWS. The predictive ability of the regression equations were improved following inclusion of self-report data related to mobility and prosthetic utility. CONCLUSION: This study offers a practicable alternative to quantifying kinematic deviation without the need to conduct complete 3DGA. PMID:27335814

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression

PubMed Central

Cano Marchal, Pablo; Gómez Ortega, Juan; Gámez García, Javier

2018-01-01

Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO), the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation. PMID:29587403

The impact of intrinsic and extrinsic factors on the job satisfaction of dentists.

PubMed

Goetz, K; Campbell, S M; Broge, B; Dörfer, C E; Brodowski, M; Szecsenyi, J

2012-10-01

The Two-Factor Theory of job satisfaction distinguishes between intrinsic-motivation (i.e. recognition, responsibility) and extrinsic-hygiene (i.e. job security, salary, working conditions) factors. The presence of intrinsic-motivation facilitates higher satisfaction and performance, whereas the absences of extrinsic factors help mitigate against dissatisfaction. The consideration of these factors and their impact on dentists' job satisfaction is essential for the recruitment and retention of dentists. The objective of the study is to assess the level of job satisfaction of German dentists and the factors that are associated with it. This cross-sectional study was based on a job satisfaction survey. Data were collected from 147 dentists working in 106 dental practices. Job satisfaction was measured with the 10-item Warr-Cook-Wall job satisfaction scale. Organizational characteristics were measured with two items. Linear regression analyses were performed in which each of the nine items of the job satisfaction scale (excluding overall satisfaction) were handled as dependent variables. A stepwise linear regression analysis was performed with overall job satisfaction as the dependent outcome variable, the nine items of job satisfaction and the two items of organizational characteristics controlled for age and gender as predictors. The response rate was 95.0%. Dentists were satisfied with 'freedom of working method' and mostly dissatisfied with their 'income'. Both variables are extrinsic factors. The regression analyses identified five items that were significantly associated with each item of the job satisfaction scale: 'age', 'mean weekly working time', 'period in the practice', 'number of dentist's assistant' and 'working atmosphere'. Within the stepwise linear regression analysis the intrinsic factor 'opportunity to use abilities' (β = 0.687) showed the highest score of explained variance (R(2) = 0.468) regarding overall job satisfaction. With respect to the Two-Factor Theory of job satisfaction both components, intrinsic and extrinsic, are essential for dentists but the presence of intrinsic motivating factors like the opportunity to use abilities has most positive impact on job satisfaction. The findings of this study will be helpful for further activities to improve the working conditions of dentists and to ensure quality of care. © 2012 John Wiley & Sons A/S.

Study on relationship of nitric oxide, oxidation, peroxidation, lipoperoxidation with chronic chole-cystitis

PubMed Central

Zhou, Jun-Fu; Cai, Dong; Zhu, You-Gen; Yang, Jin-Lu; Peng, Cheng-Hong; Yu, Yang-Hai

2000-01-01

AIM: To study relationship of injury induced by nitric oxide, oxidation, peroxidation, lipoperoxidation with chronic cholecystitis. METHODS: The values of plasma nitric oxide (P-NO), plasma vitamin C (P-VC), plasma vitamin E (P-VE), plasma β-carotene (P-β-CAR), plasma lipoperoxides (P-LPO), erythrocyte superoxide dismutase (E-SOD), erythrocyte catalase (E-CAT), erythrocyte glutathione peroxidase (E-GSH-Px) activities and erythrocyte lipoperoxides (E-LPO) level in 77 patients with chro nic cholecystitis and 80 healthy control subjects were determined, differences of the above average values between t he patient group and the control group and differences of the average values bet ween preoperative and postoperative patients were analyzed and compared, linear regression and correlation of the disease course with the above determination values as well as the stepwise regression and correlation of the course with th e values were analyzed. RESULTS: Compared with the control group, the average values of P-NO, P-LPO, E-LPO were significantly increased (P < 0.01), and of P-VC, P-VE, P-β-CAR, E-SOD, E-CAT and E-GSH-Px decreased (P < 0.01) in the patient group. The analysis of the lin ear regression and correlation s howed that with prolonging of the course, the values of P-NO, P-LPO and E-LPO in the patients were gradually ascended and the values of P-VC, P-VE, P-β-CAR, E-SOD, E-CAT and E-GSH-Px descended (P < 0.01). The analysis of the stepwise regression and correlation indicated that the correlation of the course with P-NO, P-VE and P-β-CAR values was the closest. Compared with the preoperative patients, the average values of P-NO, P-LPO and E-LPO were significantly decre ased (P < 0.01) and the average values of P-VC, E-SOD, E-CAT and E-GSH-Px in postoperative pa tients increased (P < 0.01) in postoperative patients. But there was no signif icant difference in the average values of P-VE, P-β-CAR preope rative and postoperative patients. CONCLUSION: Chronic cholecystitis could induce the increase of nitric oxide, oxidation, peroxidation and lipoperoxidation. PMID:11819637

Relationship between affective determinants and achievement in science for seventeen-year-olds

NASA Astrophysics Data System (ADS)

Napier, John D.; Riley, Joseph P.

Data collected in the 1976-1977 NAEP survey of seventeen-year-olds was used to reanalyze the hypothesis that there are affective determinates of science achievement. Factor and item analysis procedures were used to examine affective and cognitive items from Booklet 4. Eight affective scales and one cognitive achievement scale were identified. Using stepwise multiple regression procedures, the four affective scales of Motivation, Anxiety, Student Choice, and Teacher Support were found to account for the majority of the correlation between the affective determinants and achievement.

Military Return to Duty and Civilian Return to Work Factors Following Burns With Focus on the Hand and Literature Review

DTIC Science & Technology

2008-10-01

the three parameters of skin graft - ing, treatment time and presence of a face burn where all reports agree as to the influence of each one of these...cluding the presence of hand burns. Of the studies that agree on factor influence, five document that skin grafting had a significant effect on...stepwise multiple regression analysis, Helm et al determined TBSA to be the stron- gest predictor of RTW followed equally by skin graft - ing and hand burn

Effect of perceived organizational support on suicidal ideation of young employees: The mediator role of self-esteem.

PubMed

Sang, Jinyan; Ji, Yongbao; Li, Ping; Zhao, Hao

2017-09-01

This study aimed to explore the relationships among perceived organizational support, self-esteem, and suicidal ideation of young employees. A total of 447 unmarried employees completed the survey of perceived organizational support, Rosenberg self-esteem scale, and suicide ideation scale. The results revealed that perceived organizational support, self-esteem, and suicidal ideation were significantly correlated with each other. Stepwise regression analysis and path analysis both indicated that self-esteem partially mediated the effect of perceived organizational support on suicidal ideation.

Exploration of charity toward busking (street performance) as a function of religion.

PubMed

Lemay, John O; Bates, Larry W

2013-04-01

To examine conceptions of religion and charity in a new venue--busking (street performance)--103 undergraduate students at a regional university in the southeastern U.S. completed a battery of surveys regarding religion, and attitudes and behaviors toward busking. For those 85 participants who had previously encountered a busker, stepwise regression was used to predict increased frequency of giving to buskers. The best predictive model of giving to buskers consisted of three variables including less experienced irritation toward buskers, prior experience with giving to the homeless, and lower religious fundamentalism.

Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

PubMed

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

Relation between adherence and outcome in the group treatment of insomnia.

PubMed

Vincent, Norah K; Hameed, Hannah

2003-01-01

This study evaluated adherence to group cognitive behavioral treatment in 50 adults with chronic insomnia. Adherence was measured using questionnaire data, consistency of sleep scheduling, and % of sessions attended. Results showed that therapists' rated 48% of participants as "very much" to "extremely" adherent. Using stepwise regression, only therapist-rated adherence explained a significant amount of variance in post-treatment outcome. Therapist-rated adherence predicted post-treatment ratings of sleep-related impairment, dysfunctional beliefs about sleep, and overall sleep quality (but not actual sleep duration or efficiency). Using a multivariate analysis of variance (MANOVA) procedure, results revealed that a diagnosis of dysthymia, based on a structured clinical interview, was associated with reduced adherence and less improvement in sleep-onset latency and sleep efficiency, but that scores on a dimensional measure of depression were not associated with either adherence or outcome. Implications of these findings are that the practice of treatment techniques is related to an improved perception of sleep and more healthy and appropriate beliefs about the causes of poor sleep. Therapists should continue to pay close attention to the adherence behavior of those with insomnia, particularly if they are depressed.

Growth and mortality of coral transplants (Pocillopora damicornis) along a range of sediment influence in Maui, Hawai'i

USGS Publications Warehouse

Piniak, G.A.; Brown, E.K.

2008-01-01

Fragments of the lace coral Pocillopora damicornis (Linnaeus, 1758) were transplanted to four sites on the south-central coast of Maui, Hawai'i, to examine coral growth over a range of expected sediment influence. Corals remained in situ for 11 months and were recovered seasonally for growth measurements using the buoyant weight technique. Average sediment trap accumulation rates ranged from 11 to 490 mg cm-2 day-1 and were greater at the wave-exposed reef site than at the protected harbor sites. Coral growth was highest at the donor site and was higher in the summer than in the winter. A stepwise linear regression found significant effects of sediment trap accumulation and light on growth rates, but the partial correlation coefficients suggest that these factors may be only secondary controls on growth. This study did not show a clear link between coral growth and sediment load. This result may be due, in part, to covariation of sediment load with wave exposure and the inability of trap accumulation rates to integrate all sediment effects (e.g., turbidity) that can affect coral growth. ?? 2008 by University of Hawai'i Press. All rights reserved.

An accurate and rapid radiographic method of determining total lung capacity

PubMed Central

Reger, R. B.; Young, A.; Morgan, W. K. C.

1972-01-01

The accuracy and reliability of Barnhard's radiographic method of determining total lung capacity have been confirmed by several groups of investigators. Despite its simplicity and general reliability, it has several shortcomings, especially when used in large-scale epidemiological surveys. Of these, the most serious is related to film technique; thus, when the cardiac and diaphragmatic shadows are poorly defined, the appropriate measurements cannot be made accurately. A further drawback involves the time needed to measure the segments and to perform the necessary calculations. We therefore set out to develop an abbreviated and simpler radiographic method for determining total lung capacity. This uses a step-wise multiple regression model which allows total lung capacity to be derived as follows: posteroanterior and lateral films are divided into the standard sections as described in the text, the width, depth, and height of sections 1 and 4 are measured in centimetres, finally the necessary derivations and substitutions are made and applied to the formula Ŷ = −1·41148 + (0·00479 X1) + (0·00097 X4), where Ŷ is the total lung capacity. In our hands this method has provided a simple, rapid, and acceptable method of determining total lung capacity. PMID:5034594

Estimating Dungeness crab (Cancer magister) abundance: Crab pots and dive transects compared

USGS Publications Warehouse

Taggart, S. James; O'Clair, Charles E.; Shirley, Thomas C.; Mondragon, Jennifer

2004-01-01

Dungeness crabs (Cancer magister) were sampled with commercial pots and counted by scuba divers on benthic transects at eight sites near Glacier Bay, Alaska. Catch per unit of effort (CPUE) from pots was compared to the density estimates from dives to evaluate the bias and power of the two techniques. Yearly sampling was conducted in two seasons: April and September, from 1992 to 2000. Male CPUE estimates from pots were significantly lower in April than in the following September; a step-wise regression demonstrated that season accounted for more of the variation in male CPUE than did temperature. In both April and September, pot sampling was significantly biased against females. When females were categorized as ovigerous and nonovigerous, it was clear that ovigerous females accounted for the majority of the bias because pots were not biased against nonovigerous females. We compared the power of pots and dive transects in detecting trends in populations and found that pots had much higher power than dive transects. Despite their low power, the dive transects were very useful for detecting bias in our pot sampling and in identifying the optimal times of year to sample so that pot bias could be avoided.

Impact of Donor Age on Corneal Endothelium-Descemet Membrane Layer Scroll Formation

PubMed Central

Bennett, Adam; Mahmoud, Shahira; Drury, Donna; Cavanagh, H. Dwight; McCulley, James P.; Petroll, W. Matthew; Mootha, V. Vinod

2014-01-01

Objectives To correlate corneal endothelium-Descemet membrane layer (EDM) parameters of scroll tightness with donor age, endothelial cell density, and history of diabetes. Methods EDM scrolls were harvested from 26 corneoscleral buttons using the SCUBA technique by a cornea-fellowship trained ophthalmologist masked to donor age. Two independent outcome parameters were used to characterize the scrolling severity of successfully harvested tissue: scroll width and tendency for EDM scroll formation (referred to as scroll rating on a 1 to 4 scale: incomplete scroll formation to tightly-scrolled). Results Mean donor age was 59 ± 17years (15–69). Mean endothelial cell density of EDM scroll was 2451 ± 626 cells/mm2 mm (range: 1307 – 3195). Using stepwise linear regression, a significant correlation was found between scroll width and donor age (R = 0.497, P < 0.05). Additionally, a significant inverse correlation was found between scroll width and endothelial cell density (R = −0.605, P < 0.05). There was no statistically significant correlation between a donor history of diabetes and the parameters of scrolling tendency. Conclusions Our data suggests that using older donors reduces EDM scroll tightness. PMID:25603436

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

PubMed

Weijers, Gert; Starke, Alexander; Haudum, Alois; Thijssen, Johan M; Rehage, Jürgen; De Korte, Chris L

2010-07-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty liver disease, to test this hypothesis. Five transcutaneous and five intraoperative US liver images were acquired in each animal and a liverbiopsy was taken. In liver tissue samples, triacylglycerol (TAG) was measured by biochemical analysis and hepatic diseases other than hepatic lipidosis were excluded by histopathologic examination. Ultrasonic tissue characterization (UTC) parameters--Mean echo level, standard deviation (SD) of echo level, signal-to-noise ratio (SNR), residual attenuation coefficient (ResAtt) and axial and lateral speckle size--were derived using a computer-aided US (CAUS) protocol and software package. First, the liver tissue was interactively segmented by two observers. With increasing fat content, fewer hepatic vessels were visible in the ultrasound images and, therefore, a smaller proportion of the liver needed to be excluded from these images. Automatic-segmentation algorithms were implemented and it was investigated whether better results could be achieved than with the subjective and time-consuming interactive-segmentation procedure. The automatic-segmentation algorithms were based on both fixed and adaptive thresholding techniques in combination with a 'speckle'-shaped moving-window exclusion technique. All data were analyzed with and without postprocessing as contained in CAUS and with different automated-segmentation techniques. This enabled us to study the effect of the applied postprocessing steps on single and multiple linear regressions ofthe various UTC parameters with TAG. Improved correlations for all US parameters were found by using automatic-segmentation techniques. Stepwise multiple linear-regression formulas where derived and used to predict TAG level in the liver. Receiver-operating-characteristics (ROC) analysis was applied to assess the performance and area under the curve (AUC) of predicting TAG and to compare the sensitivity and specificity of the methods. Best speckle-size estimates and overall performance (R2 = 0.71, AUC = 0.94) were achieved by using an SNR-based adaptive automatic-segmentation method (used TAG threshold: 50 mg/g liver wet weight). Automatic segmentation is thus feasible and profitable.

A stepwise under-prepared osteotomy technique improves primary stability in shallow-placed implants: a preliminary study for simultaneous vertical ridge augmentation.

PubMed

Ueno, Daisuke; Nakamura, Kei; Kojima, Kousuke; Toyoshima, Takeshi; Tanaka, Hideaki; Ueda, Kazuhiko; Koyano, Kiyoshi; Kodama, Toshiro

2018-04-01

Simultaneous vertical ridge augmentation (VRA) can reduce treatment procedures and surgery time, but the concomitant reduction in primary stability (PS) of a shallow-placed implant imparts risk to its prognosis. Although several studies have reported improvements in PS, there is little information from any simultaneous VRA model. This study aimed to evaluate whether tapered implants with stepwise under-prepared osteotomy could improve the PS of shallow-placed implants in an in vitro model of simultaneous VRA. Tapered implants (Straumann ® Bone Level Tapered implant; BLT) and hybrid implants (Straumann ® Bone Level implant; BL) were investigated in this study. A total of 80 osteotomies of different depths (4, 6, 8, 10 mm) were created in rigid polyurethane foam blocks, and each BLT and BL was inserted by either standard (BLT-S, BL-S) or a stepwise under-prepared (BLT-U, BL-U) osteotomy protocol. The PS was evaluated by measuring maximum insertion torque (IT), implant stability quotient (ISQ), and removal torque (RT). The significance level was set at P < 0.05. There were no significant differences in IT, ISQ or RT when comparing BLT-S and BL-S or BLT-U and BL-U at placement depths of 6 and 8 mm. When comparison was made between osteotomy protocols, IT was significantly greater in BLT-U than in BLT-S at all placement depths. A stepwise under-prepared osteotomy protocol improves initial stability of a tapered implant even in a shallow-placed implant model. BLT-U could be a useful protocol for simultaneous VRA.

Predictors of Long-Term School-Based Behavioral Outcomes in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder

PubMed Central

Reed, Margot O.; Jakubovski, Ewgeni; Johnson, Jessica A.

2017-01-01

Abstract Objective: To explore predictors of 8-year school-based behavioral outcomes in attention-deficit/hyperactivity disorder (ADHD). Methods: We examined potential baseline predictors of school-based behavioral outcomes in children who completed the 8-year follow-up in the multimodal treatment study of children with ADHD. Stepwise logistic regression and receiver operating characteristic (ROC) analysis identified baseline predictors that were associated with a higher risk of truancy, school discipline, and in-school fights. Results: Stepwise regression analysis explained between 8.1% (in-school fights) and 12.0% (school discipline) of the total variance in school-based behavioral outcomes. Logistic regression identified several baseline characteristics that were associated with school-based behavioral difficulties 8 years later, including being male (associated with truancy and school discipline), African American (school discipline, in-school fights), increased conduct disorder (CD) symptoms (truancy), decreased affection from parents (school discipline), ADHD severity (in-school fights), and study site (truancy and school discipline). ROC analyses identified the most discriminative predictors of truancy, school discipline, and in-school fights, which were Aggression and Conduct Problem Scale Total score, family income, and race, respectively. Conclusions: A modest, but nontrivial portion of school-based behavioral outcomes, was predicted by baseline childhood characteristics. Exploratory analyses identified modifiable (lack of paternal involvement, lower parental knowledge of behavioral principles, and parental use of physical punishment), somewhat modifiable (income and having comorbid CD), and nonmodifiable (African American and male) factors that were associated with school-based behavioral difficulties. Future research should confirm that the associations between earlier specific parenting behaviors and poor subsequent school-based behavioral outcomes are, indeed, causally related and independent cooccurring childhood psychopathology. Future research might target increasing paternal involvement and parental knowledge of behavioral principles and reducing use of physical punishment to improve school-based behavioral outcomes in children with ADHD. PMID:28253029

Predictors of Long-Term School-Based Behavioral Outcomes in the Multimodal Treatment Study of Children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Reed, Margot O; Jakubovski, Ewgeni; Johnson, Jessica A; Bloch, Michael H

2017-05-01

To explore predictors of 8-year school-based behavioral outcomes in attention-deficit/hyperactivity disorder (ADHD). We examined potential baseline predictors of school-based behavioral outcomes in children who completed the 8-year follow-up in the multimodal treatment study of children with ADHD. Stepwise logistic regression and receiver operating characteristic (ROC) analysis identified baseline predictors that were associated with a higher risk of truancy, school discipline, and in-school fights. Stepwise regression analysis explained between 8.1% (in-school fights) and 12.0% (school discipline) of the total variance in school-based behavioral outcomes. Logistic regression identified several baseline characteristics that were associated with school-based behavioral difficulties 8 years later, including being male (associated with truancy and school discipline), African American (school discipline, in-school fights), increased conduct disorder (CD) symptoms (truancy), decreased affection from parents (school discipline), ADHD severity (in-school fights), and study site (truancy and school discipline). ROC analyses identified the most discriminative predictors of truancy, school discipline, and in-school fights, which were Aggression and Conduct Problem Scale Total score, family income, and race, respectively. A modest, but nontrivial portion of school-based behavioral outcomes, was predicted by baseline childhood characteristics. Exploratory analyses identified modifiable (lack of paternal involvement, lower parental knowledge of behavioral principles, and parental use of physical punishment), somewhat modifiable (income and having comorbid CD), and nonmodifiable (African American and male) factors that were associated with school-based behavioral difficulties. Future research should confirm that the associations between earlier specific parenting behaviors and poor subsequent school-based behavioral outcomes are, indeed, causally related and independent cooccurring childhood psychopathology. Future research might target increasing paternal involvement and parental knowledge of behavioral principles and reducing use of physical punishment to improve school-based behavioral outcomes in children with ADHD.

Socio-economic factors associated with infant mortality in Italy: an ecological study

PubMed Central

2012-01-01

Introduction One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Methods Associations between infant mortality rates in the 20 Italian regions (2006–2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15–64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. Results The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = −0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = −0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). Conclusions In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels. PMID:22898293

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

PubMed

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

2015-11-01

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

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

NASA Technical Reports Server (NTRS)

Banse, Karl; Yong, Marina

1990-01-01

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

Examining the long-term racial disparities in health and economic conditions among Hurricane Katrina survivors: policy implications for Gulf Coast recovery.

PubMed

Toldson, Ivory A; Ray, Kilynda; Hatcher, Schnavia Smith; Louis, Laura Straughn

2011-01-01

This study examines disparities in the long-term health, emotional well-being, and economic consequences of the 2005 Gulf Coast hurricanes. Researchers analyzed the responses of 216 Black and 508 White Hurricane Katrina survivors who participated in the ABC News Hurricane Katrina Anniversary Poll in 2006. Self-reported data of the long-term negative impact of the hurricane on personal health, emotional well-being, and finances were regressed on race, income, and measures of loss, injury, family mortality, anxiety, and confidence in the government. Descriptive analyses, stepwise logistic regression, and analyses of variance revealed that Black hurricane survivors more frequently reported hurricane-related problems with personal health, emotional well-being, and finances. In addition, Blacks were more likely than Whites to report the loss of friends, relatives, and personal property.

A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

NASA Technical Reports Server (NTRS)

Barrett, C. A.

1985-01-01

Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.

Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS

USGS Publications Warehouse

Chelgani, S.C.; Hart, B.; Grady, W.C.; Hower, J.C.

2011-01-01

The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV. Copyright ?? Taylor & Francis Group, LLC.

[Regional scale remote sensing-based yield estimation of winter wheat by using MODIS-NDVI data: a case study of Jining City in Shandong Province].

PubMed

Ren, Jianqiang; Chen, Zhongxin; Tang, Huajun

2006-12-01

Taking Jining City of Shandong Province, one of the most important winter wheat production regions in Huanghuaihai Plain as an example, the winter wheat yield was estimated by using the 250 m MODIS-NDVI data smoothed by Savitzky-Golay filter. The NDVI values between 0. 20 and 0. 80 were selected, and the sum of NDVI value for each county was calculated to build its relation with winter wheat yield. By using stepwise regression method, the linear regression model between NDVI and winter wheat yield was established, with the precision validated by the ground survey data. The results showed that the relative error of predicted yield was between -3.6% and 3.9%, suggesting that the method was relatively accurate and feasible.

Relationships among body weight, joint moments generated during functional activities, and hip bone mass in older adults

PubMed Central

Wang, Man-Ying; Flanagan, Sean P.; Song, Joo-Eun; Greendale, Gail A.; Salem, George J.

2012-01-01

Objective To investigate the relationships among hip joint moments produced during functional activities and hip bone mass in sedentary older adults. Methods Eight male and eight female older adults (70–85 yr) performed functional activities including walking, chair sit–stand–sit, and stair stepping at a self-selected pace while instrumented for biomechanical analysis. Bone mass at proximal femur, femoral neck, and greater trochanter were measured by dual-energy X-ray absorptiometry. Three-dimensional hip moments were obtained using a six-camera motion analysis system, force platforms, and inverse dynamics techniques. Pearson’s correlation coefficients were employed to assess the relationships among hip bone mass, height, weight, age, and joint moments. Stepwise regression analyses were performed to determine the factors that significantly predicted bone mass using all significant variables identified in the correlation analysis. Findings Hip bone mass was not significantly correlated with moments during activities in men. Conversely, in women bone mass at all sites were significantly correlated with weight, moments generated with stepping, and moments generated with walking (p < 0.05 to p < 0.001). Regression analysis results further indicated that the overall moments during stepping independently predicted up to 93% of the variability in bone mass at femoral neck and proximal femur; whereas weight independently predicted up to 92% of the variability in bone mass at greater trochanter. Interpretation Submaximal loading events produced during functional activities were highly correlated with hip bone mass in sedentary older women, but not men. The findings may ultimately be used to modify exercise prescription for the preservation of bone mass. PMID:16631283

Estimation of maximal oxygen uptake by bioelectrical impedance analysis.

PubMed

Stahn, Alexander; Terblanche, Elmarie; Grunert, Sven; Strobel, Günther

2006-02-01

Previous non-exercise models for the prediction of maximal oxygen uptake VO(2max) have failed to accurately discriminate cardiorespiratory fitness within large cohorts. The aim of the present study was to evaluate the feasibility of a completely indirect method for predicting VO(2max) that was based on bioelectrical impedance analysis (BIA) in 66 young, healthy fit men and women. Multiple, stepwise regression analysis was used to determine the usefulness of BIA and additional covariates to estimate VO(2max) (ml min(-1)). BIA was highly correlated to VO(2max) (r = 0.914; P < 0.001) and entered the regression equation first. The inclusion of gender and a physical activity rating further improved the model which accounted for 88% of the variance in VO(2max) and resulted in a relative standard error of the estimate (SEE) of 7.2%. Substantial agreement between the methods was confirmed by the fact that nearly all the differences were within +/-2 SD. Furthermore, in contrast to previously published non-exercise models, no trend of a reduction in prediction accuracy with increasing VO(2max) values was apparent. It was concluded that a non-exercise model based on BIA might be a rapid and useful technique to estimate VO(2max), when a direct test does not seem feasible. However, though the present results are useful to determine the viability of the method, further refinement of the BIA approach and its validation in a large, diverse population is needed before it can be applied to the clinical and epidemiological settings.

Cavitational kyphoplasty: a new technique for reducing the rates of cement extravasation through targeted low-pressure cement injection.

PubMed

Mattei, Tobias A

2017-06-01

Previous studies have demonstrated lower rates of cement extravasation when comparing balloon kyphoplasty with vertebroplasty, an effect attributed to the low-pressure injection. However, in patients with isolated endplate fractures, balloon kyphoplasty may lead to further endplate damage and increased risks of intradiscal extravasation. The author provides a stepwise description of a new technique called cavitational kyphoplasty that allows targeted low-pressure cement injection without the necessity of balloon inflation. The new technique of cavitational kyphoplasty has been shown to be specially useful in patients with isolated endplate fractures without significant loss of the vertebral body height.

A comparative study on the level of satisfaction among regular and contractual health-care workers in a Northern city of India

PubMed Central

Dixit, Jyoti; Goel, Sonu; Sharma, Vijaylakshmi

2017-01-01

Introduction: Job satisfaction greatly determines the productivity and efficiency of human resources for health. The current study aims to assess the level of satisfaction and factors influencing the job satisfaction among regular and contractual health-care workers. Materials and Methods: A cross-sectional quantitative study was conducted from January to June 2015 among health care workers (n = 354) at all levels of public health-care facilities of Chandigarh. The correlation between variables with overall level of satisfaction was computed for regular and contractual health-care workers. Stepwise multiple linear regression was done to elucidate the major factors influencing job satisfaction. Results: Majority of the regular health-care staff was highly satisfied (86.9%) as compared to contractual staff (10.5%), which however was moderately satisfied (55.9%). Stepwise regression model showed that work-related matters (β = 1.370, P < 0.01), organizational facilities (β = 1.586, P < 0.01), privileges attached to the job (β = 0.530, P < 0.01), attention to the suggestions (β = 0.515, P < 0.01), chance of promotion (β = 0.703, P < 0.01), and human resource issues (β = 1.0721, P < 0.01) are strong predictors of overall satisfaction level. Conclusion: Under the National Rural Health Mission, contract appointments have improved the overall availability of health-care staff at all levels of public health facilities. However, there are concerns regarding their level of motivation with various aspects related to the job, which need to be urgently addressed so as to improve the effectiveness and efficiency of health services. PMID:29302557

A comparative study on the level of satisfaction among regular and contractual health-care workers in a Northern city of India.

PubMed

Dixit, Jyoti; Goel, Sonu; Sharma, Vijaylakshmi

2017-01-01

Job satisfaction greatly determines the productivity and efficiency of human resources for health. The current study aims to assess the level of satisfaction and factors influencing the job satisfaction among regular and contractual health-care workers. A cross-sectional quantitative study was conducted from January to June 2015 among health care workers ( n = 354) at all levels of public health-care facilities of Chandigarh. The correlation between variables with overall level of satisfaction was computed for regular and contractual health-care workers. Stepwise multiple linear regression was done to elucidate the major factors influencing job satisfaction. Majority of the regular health-care staff was highly satisfied (86.9%) as compared to contractual staff (10.5%), which however was moderately satisfied (55.9%). Stepwise regression model showed that work-related matters (β = 1.370, P < 0.01), organizational facilities (β = 1.586, P < 0.01), privileges attached to the job (β = 0.530, P < 0.01), attention to the suggestions (β = 0.515, P < 0.01), chance of promotion (β = 0.703, P < 0.01), and human resource issues (β = 1.0721, P < 0.01) are strong predictors of overall satisfaction level. Under the National Rural Health Mission, contract appointments have improved the overall availability of health-care staff at all levels of public health facilities. However, there are concerns regarding their level of motivation with various aspects related to the job, which need to be urgently addressed so as to improve the effectiveness and efficiency of health services.

The relationship between personality traits and sexual self-esteem and its components

PubMed Central

Firoozi, Mahbobe; Azmoude, Elham; Asgharipoor, Negar

2016-01-01

Background: Women's sexual self-esteem is one of the most important factors that affect women's sexual satisfaction and their sexual anxiety. Various aspects of sexual life are blended with the entire personality. Determining the relationship between personality traits and self-concept aspects such as sexual self-esteem leads to better understanding of sexual behavior in people with different personality traits and helps in identifying the psychological variables affecting their sexual performance. The aim this study was to determine the relationship between personality traits and sexual self-esteem. Materials and Methods: This correlation study was performed on 127 married women who referred to selected health care centers of Mashhad in 2014–2015. Data collection tools included NEO personality inventory dimensions and Zeanah and Schwarz sexual self-esteem questionnaire. Data were analyzed through Pearson correlation coefficient test and stepwise regression model. Results: The results of Pearson correlation test showed a significant relationship between neuroticism personality dimension (r = −0.414), extroversion (r = 0.363), agreeableness (r = 0.420), and conscientiousness (r = 0.364) with sexual self-esteem (P < 0.05). The relationship between openness with sexual self-esteem was not significant (P > 0.05). In addition, based on the results of the stepwise regression model, three dimensions of agreeableness, neuroticism, and extraversion could predict 27% of the women's sexual self-esteem variance. Conclusions: The results showed a correlation between women's personality characteristics and their sexual self-esteem. Paying attention to personality characteristics may be important to identify at-risk group or the women having low sexual self-esteem in premarital and family counseling. PMID:27186198

Bisphosphonates and Bone Fractures in Long-term Kidney Transplant Recipients

PubMed Central

Conley, Emily; Muth, Brenda; Samaniego, Millie; Lotfi, Mary; Voss, Barbara; Armbrust, Mike; Pirsch, John; Djamali, Arjang

2013-01-01

Background There is little information on the role of bisphosphonates and bone mineral density (BMD) measurements for the follow-up and management of bone loss and fractures in long-term kidney transplant recipients. Methods To address this question, we retrospectively studied 554 patients who had two BMD measurements after the first year posttransplant and compared outcomes in patients treated, or not with bisphosphonates between the two BMD assessments. Kaplan-Meier survival and stepwise Cox regression analyses were performed to examine fracture-free survival rates and the risk-factors associated with fractures. Results The average time (±SE) between transplant and the first BMD was 1.2±0.05 years. The time interval between the two BMD measurements was 2.5±0.05 years. There were 239 and 315 patients in the no-bisphosphonate and bisphosphonate groups, respectively. Treatment was associated with significant preservation of bone loss at the femoral neck (HR 1.56, 95% CI 1.21-2.06, P=0.0007). However, there was no association between bone loss at the femoral neck and fractures regardless of bisphosphonate therapy. Stepwise Cox regression analyses showed that type-1 diabetes, baseline femoral neck T-score, interleukin-2 receptor blockade, and proteinuria (HR 2.02, 0.69, 0.4, 1.23 respectively, P<0.01), but not bisphosphonates, were associated with the risk of fracture. Conclusions Bisphosphonates may prevent bone loss in long-term kidney transplant recipients. However, these data suggest a limited role for the initiation of therapy after the first posttransplant year to prevent fractures. PMID:18645484

A randomized-controlled trial examining the effects of reflexology on anxiety of patients undergoing coronary angiography.

PubMed

Molavi Vardanjani, Mehdi; Masoudi Alavi, Negin; Razavi, Narges Sadat; Aghajani, Mohammad; Azizi-Fini, Esmail; Vaghefi, Seied Morteza

2013-09-01

The anxiety reduction before coronary angiography has clinical advantages and is one of the objectives of nursing. Reflexology is a non-invasive method that has been used in several clinical situations. Applying reflexology might have effect on the reduction of anxiety before coronary angiography. The aim of this randomized clinical trial was to investigate the effect of reflexology on anxiety among patients undergoing coronary angiography. This trial was conducted in Shahid Beheshti Hospital, in Kashan, Iran. One hundred male patients who were undergoing coronary angiography were randomly enrolled into intervention and placebo groups. The intervention protocol was included 30 minutes of general foot massage and the stimulation of three reflex points including solar plexus, pituitary gland, and heart. The placebo group only received the general foot massage. Spielbergers state trait anxiety inventory was used to assess the anxiety experienced by patients. Data was analyzed using Man-Witney, Wilcoxon and Chi-square tests. The stepwise multiple regressions used to analyze the variables that are involved in anxiety reduction. The mean range of anxiety decreased from 53.24 to 45.24 in reflexology group which represented 8 score reduction (P = 0.0001). The reduction in anxiety was 5.9 score in placebo group which was also significant (P = 0.0001). The anxiety reduction was significantly higher in reflexology group (P = 0.014). The stepwise multiple regression analysis showed that doing reflexology can explain the 7.5% of anxiety reduction which made a significant model. Reflexology can decrease the anxiety level before coronary angiography. Therefore, reflexology before coronary angiography is recommended.

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

PubMed Central

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

2016-01-01

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

Exploring the association between parental rearing styles and medical students' critical thinking disposition in China.

PubMed

Huang, Lei; Wang, Zhaoxin; Yao, Yuhong; Shan, Chang; Wang, Haojie; Zhu, Mengyi; Lu, Yuan; Sun, Pengfei; Zhao, Xudong

2015-05-14

Critical thinking is an essential ability for medical students. However, the relationship between parental rearing styles and medical students' critical thinking disposition has rarely been considered. The aim of this study was to investigate whether parental rearing styles were significant predictors of critical thinking disposition among Chinese medical students. 1,075 medical students from the first year to the fifth year attending one of three medical schools in China were recruited via multistage stratified cluster sampling. The Chinese Critical Thinking Disposition Inventory(CTDI-CV) and The Egna Minnen av Barndoms Uppfostran (EMBU) questionnaire were applied to collect data and to conduct descriptive analysis. Stepwise multiple linear regression was used to analyze the data. The critical thinking disposition average mean score was 287.44 with 632 participants (58.79%) demonstrating positive critical thinking disposition. Stepwise multiple linear regression analysis revealed that the rearing styles of fathers, including "overprotection", "emotional warmth and understanding", "rejection" and "over-interference" were significant predictors of medical students' critical thinking disposition that explained 79.0% of the variance in critical thinking ability. Rearing styles of mothers including "emotional warmth and understanding", "punishing" and "rejection" were also found to be significant predictors, and explained 77.0% of the variance. Meaningful association has been evidenced between parental rearing styles and Chinese medical students' critical thinking disposition. Parental rearing styles should be considered as one of the many potential determinant factors that contribute to the cultivation of medical students' critical thinking capability. Positive parental rearing styles should be encouraged in the cultivation of children's critical thinking skills.

Relationship between masticatory performance using a gummy jelly and masticatory movement.

PubMed

Uesugi, Hanako; Shiga, Hiroshi

2017-10-01

The purpose of this study was to clarify the relationship between masticatory performance using a gummy jelly and masticatory movement. Thirty healthy males were asked to chew a gummy jelly on their habitual chewing side for 20s, and the parameters of masticatory performance and masticatory movement were calculated as follows. For evaluating the masticatory performance, the amount of glucose extraction during chewing of a gummy jelly was measured. For evaluating the masticatory movement, the movement of the mandibular incisal point was recorded using the MKG K6-I, and ten parameters of the movement path (opening distance and masticatory width), movement rhythm (opening time, closing time, occluding time, and cycle time), stability of movement (stability of path and stability of rhythm), and movement velocity (opening maximum velocity and closing maximum velocity) were calculated from 10 cycles of chewing beginning with the fifth cycle. The relationship between the amount of glucose extraction and parameters representing masticatory movement was investigated and then stepwise multiple linear regression analysis was performed. The amount of glucose extraction was associated with 7 parameters representing the masticatory movement. Stepwise multiple linear regression analysis showed that the opening distance, closing time, stability of rhythm, and closing maximum velocity were the most important factors affecting the glucose extraction. From these results it was suggested that there was a close relation between masticatory performance and masticatory movement, and that the masticatory performance could be increased by rhythmic, rapid and stable mastication with a large opening distance. Copyright © 2017 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Job satisfaction of primary care physicians in Switzerland: an observational study.

PubMed

Goetz, Katja; Jossen, Marianne; Szecsenyi, Joachim; Rosemann, Thomas; Hahn, Karolin; Hess, Sigrid

2016-10-01

Job satisfaction of physicians is an important issue for performance of a health care system. The aim of the study was to evaluate the job satisfaction of primary care physicians in Switzerland and to explore associations between overall job satisfaction, individual characteristics and satisfaction with aspects of work within the practice separated by gender. This cross-sectional study was based on a job satisfaction survey. Data were collected from 176 primary care physicians working in 91 primary care practices. Job satisfaction was measured with the 10-item Warr-Cook-Wall job satisfaction scale. Stepwise linear regression analysis was performed for physicians separated by gender. The response rate was 92.6%. Primary care physicians reported the highest level of satisfaction with 'freedom of working method' (mean = 6.45) and the lowest satisfaction for 'hours of work' (mean = 5.38) and 'income' (mean = 5.49). Moreover, some aspects of job satisfaction were rated higher by female physicians than male physicians. Within the stepwise regression analysis, the aspect 'opportunity to use abilities' (β = 0.644) showed the highest association to overall job satisfaction for male physicians while for female physicians it was income (β = 0.733). The presented results contribute to an understanding of factors that influence levels of satisfaction of female and male physicians. Therefore, research and intervention about job satisfaction should consider gender as well as the stereotypes that come along with these social roles. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The relationship between personality traits and sexual self-esteem and its components.

PubMed

Firoozi, Mahbobe; Azmoude, Elham; Asgharipoor, Negar

2016-01-01

Women's sexual self-esteem is one of the most important factors that affect women's sexual satisfaction and their sexual anxiety. Various aspects of sexual life are blended with the entire personality. Determining the relationship between personality traits and self-concept aspects such as sexual self-esteem leads to better understanding of sexual behavior in people with different personality traits and helps in identifying the psychological variables affecting their sexual performance. The aim this study was to determine the relationship between personality traits and sexual self-esteem. This correlation study was performed on 127 married women who referred to selected health care centers of Mashhad in 2014-2015. Data collection tools included NEO personality inventory dimensions and Zeanah and Schwarz sexual self-esteem questionnaire. Data were analyzed through Pearson correlation coefficient test and stepwise regression model. The results of Pearson correlation test showed a significant relationship between neuroticism personality dimension (r = -0.414), extroversion (r = 0.363), agreeableness (r = 0.420), and conscientiousness (r = 0.364) with sexual self-esteem (P < 0.05). The relationship between openness with sexual self-esteem was not significant (P > 0.05). In addition, based on the results of the stepwise regression model, three dimensions of agreeableness, neuroticism, and extraversion could predict 27% of the women's sexual self-esteem variance. The results showed a correlation between women's personality characteristics and their sexual self-esteem. Paying attention to personality characteristics may be important to identify at-risk group or the women having low sexual self-esteem in premarital and family counseling.

Lithium might be associated with better decision-making performance in euthymic bipolar patients.

PubMed

Adida, Marc; Jollant, Fabrice; Clark, Luke; Guillaume, Sebastien; Goodwin, Guy M; Azorin, Jean-Michel; Courtet, Philippe

2015-06-01

Bipolar disorder is associated with impaired decision-making. Little is known about how treatment, especially lithium, influences decision-making abilities in bipolar patients when euthymic. We aimed at testing for an association between lithium medication and decision-making performance in remitted bipolar patients. Decision-making was measured using the Iowa Gambling Task in 3 groups of subjects: 34 and 56 euthymic outpatients with bipolar disorder, treated with lithium (monotherapy and lithium combined with anticonvulsant or antipsychotic) and without lithium (anticonvulsant, antipsychotic and combination treatment), respectively, and 152 matched healthy controls. Performance was compared between the 3 groups. In the 90 euthymic patients, the relationship between different sociodemographic and clinical variables and decision-making was assessed by stepwise multivariate regression analysis. Euthymic patients with lithium (p=0.007) and healthy controls (p=0.001) selected significantly more cards from the safe decks than euthymic patients without lithium, with no significant difference between euthymic patients with lithium and healthy controls (p=0.9). In the 90 euthymic patients, the stepwise linear multivariate regression revealed that decision-making was significantly predicted (p<0.001) by lithium dose, level of education and no family history of bipolar disorder (all p≤0.01). Because medication was not randomized, it was not possible to discriminate the effect of different medications. Lithium medication might be associated with better decision-making in remitted bipolar patients. A randomized trial is required to test for the hypothesis that lithium, but not other mood stabilizers, may specifically improve decision-making abilities in bipolar disorder. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Readiness of adolescents to use genetically modified organisms according to their knowledge and emotional attitude towards GMOs.

PubMed

Lachowski, Stanisław; Jurkiewicz, Anna; Choina, Piotr; Florek-Łuszczki, Magdalena; Buczaj, Agnieszka; Goździewska, Małgorzata

2017-06-07

Agriculture based on genetically modified organisms plays an increasingly important role in feeding the world population, which is evidenced by a considerable growth in the size of land under genetically modified crops (GM). Uncertainty and controversy around GM products are mainly due to the lack of accurate and reliable information, and lack of knowledge concerning the essence of genetic modifications, and the effect of GM food on the human organism, and consequently, a negative emotional attitude towards what is unknown. The objective of the presented study was to discover to what extent knowledge and the emotional attitude of adolescents towards genetically modified organisms is related with acceptance of growing genetically modified plants or breeding GM animals on own farm or allotment garden, and the purchase and consumption of GM food, as well as the use of GMOs in medicine. The study was conducted by the method of a diagnostic survey using a questionnaire designed by the author, which covered a group of 500 adolescents completing secondary school on the level of maturity examination. The collected material was subjected to statistical analysis. Research hypotheses were verified using chi-square test (χ ² ), t-Student test, and stepwise regression analysis. Stepwise regression analysis showed that the readiness of adolescents to use genetically modified organisms as food or for the production of pharmaceuticals, the production of GM plants or animals on own farm, depends on an emotional-evaluative attitude towards GMOs, and the level of knowledge concerning the essence of genetic modifications.

Bone stress in runners with tibial stress fracture.

PubMed

Meardon, Stacey A; Willson, John D; Gries, Samantha R; Kernozek, Thomas W; Derrick, Timothy R

2015-11-01

Combinations of smaller bone geometry and greater applied loads may contribute to tibial stress fracture. We examined tibial bone stress, accounting for geometry and applied loads, in runners with stress fracture. 23 runners with a history of tibial stress fracture & 23 matched controls ran over a force platform while 3-D kinematic and kinetic data were collected. An elliptical model of the distal 1/3 tibia cross section was used to estimate stress at 4 locations (anterior, posterior, medial and lateral). Inner and outer radii for the model were obtained from 2 planar x-ray images. Bone stress differences were assessed using two-factor ANOVA (α=0.05). Key contributors to observed stress differences between groups were examined using stepwise regression. Runners with tibial stress fracture experienced greater anterior tension and posterior compression at the distal tibia. Location, but not group, differences in shear stress were observed. Stepwise regression revealed that anterior-posterior outer diameter of the tibia and the sagittal plane bending moment explained >80% of the variance in anterior and posterior bone stress. Runners with tibial stress fracture displayed greater stress anteriorly and posteriorly at the distal tibia. Elevated tibial stress was associated with smaller bone geometry and greater bending moments about the medial-lateral axis of the tibia. Future research needs to identify key running mechanics associated with the sagittal plane bending moment at the distal tibia as well as to identify ways to improve bone geometry in runners in order to better guide preventative and rehabilitative efforts. Copyright © 2015 Elsevier Ltd. All rights reserved.

The impact of recreational boat traffic on Marbled Murrelets (Brachyramphus marmoratus).

PubMed

Bellefleur, Danielle; Lee, Philip; Ronconi, Robert A

2009-01-01

This study evaluated the impact of small boat traffic on reaction distances of Marbled Murrelets (Brachyramphus marmoratus), in the marine waters of Pacific Rim National Park Reserve, British Columbia, Canada. Observers on moving boats recorded the minimum distance the boat came to murrelets on the water, and any disturbance reaction (fly, dive, no reaction). Out of the 7500 interactions 11.7% flew, 30.8% dove and 58.1% exhibited no flushing reaction. Using a product-limit analysis, we developed curves for the proportion of Marbled Murrelets flushing (dive or flight) as a function of reaction distance. Overall, the majority of Marbled Murrelets waited until boats were within 40 m before reacting, with 25% of the population reacting at 29.2m. A stepwise Cox regression indicated that age, boat speed, and boat density (loaded in that order), significantly affected flushing response. More juveniles flushed than adults (70.1 versus 51.7%), but at closer distances. Faster boats caused a greater proportion of birds to flush, and at further distances (25% of birds flushed at 40 m at speeds > 29 kph versus 28m at speeds <12kph). A stepwise logistic regression on diving and flight responses indicated that birds tended to fly completely out of feeding areas at the approach of boats travelling >28.8 kph and later in the season (July and August). Other secondary variables included; boat density and time of day. Discussion focused on possible management actions such as the application of speed limits, set back distances, and exclusion of boat traffic to protect Marbled Murrelets.

Attitudes Toward Obese Persons and Weight Locus of Control in Chinese Nurses: A Cross-sectional Survey.

PubMed

Wang, Yan; Ding, Ye; Song, Daoping; Zhu, Daqiao; Wang, Jianrong

2016-01-01

Obese individuals frequently experience weight-related bias or discrimination-even in healthcare settings. Although obesity bias has been associated with several demographic factors, little is known about the association of weight locus of control with bias against overweight persons or about weight bias among Chinese health professionals. The aim of the study was to examine attitudes toward obese patients in a sample of Chinese registered nurses (RNs) and the relationship between weight bias and nurses' weight locus of control. RNs working in nine community health service centers across Shanghai, China, answered three self-report questionnaires: The Attitudes Toward Obese Persons Scale (ATOP), the External Weight Locus of Control Subscale (eWLOC) from the Dieting Belief Scale, and a sociodemographic profile. Hierarchical, stepwise, multiple regression was used to predict ATOP scores. From among 385 invited, a total of 297 RNs took part in the study (77.1% response rate). Participants scored an average of 71.04 on the ATOP, indicating slightly positive attitudes toward obese persons, and 30.08 on the eWLOC, indicating a belief in the uncontrollability of body weight. Using hierarchical, stepwise, multiple regression, two predictors of ATOP scores were statistically significant (eWLOC scores and status as a specialist rather than generalist nurse), but explained variance was low. Chinese RNs seemed to have relatively neutral or even slightly positive attitudes toward obese persons. Those nurses who believed that obesity was beyond the individual's control or worked in specialties were more likely to have positive attitudes toward obese people. Improved understanding of the comprehensive etiology of obesity is needed.

Chronic atrophic gastritis in association with hair mercury level.

PubMed

Xue, Zeyun; Xue, Huiping; Jiang, Jianlan; Lin, Bing; Zeng, Si; Huang, Xiaoyun; An, Jianfu

2014-11-01

The objective of this study was to explore hair mercury level in association with chronic atrophic gastritis, a precancerous stage of gastric cancer (GC), and thus provide a brand new angle of view on the timely intervention of precancerous stage of GC. We recruited 149 healthy volunteers as controls and 152 patients suffering from chronic gastritis as cases. The controls denied upper gastrointestinal discomforts, and the cases were diagnosed as chronic superficial gastritis (n=68) or chronic atrophic gastritis (n=84). We utilized Mercury Automated Analyzer (NIC MA-3000) to detect hair mercury level of both healthy controls and cases of chronic gastritis. The statistic of measurement data was expressed as mean ± standard deviation, which was analyzed using Levene variance equality test and t test. Pearson correlation analysis was employed to determine associated factors affecting hair mercury levels, and multiple stepwise regression analysis was performed to deduce regression equations. Statistical significance is considered if p value is less than 0.05. The overall hair mercury level was 0.908949 ± 0.8844490 ng/g [mean ± standard deviation (SD)] in gastritis cases and 0.460198 ± 0.2712187 ng/g (mean±SD) in healthy controls; the former level was significantly higher than the latter one (p=0.000<0.01). The hair mercury level in chronic atrophic gastritis subgroup was 1.155220 ± 0.9470246 ng/g (mean ± SD) and that in chronic superficial gastritis subgroup was 0.604732 ± 0.6942509 ng/g (mean ± SD); the former level was significantly higher than the latter level (p<0.01). The hair mercury level in chronic superficial gastritis cases was significantly higher than that in healthy controls (p<0.05). The hair mercury level in chronic atrophic gastritis cases was significantly higher than that in healthy controls (p<0.01). Stratified analysis indicated that the hair mercury level in healthy controls with eating seafood was significantly higher than that in healthy controls without eating seafood (p<0.01) and that the hair mercury level in chronic atrophic gastritis cases was significantly higher than that in chronic superficial gastritis cases (p<0.01). Pearson correlation analysis indicated that eating seafood was most correlated with hair mercury level and positively correlated in the healthy controls and that the severity of gastritis was most correlated with hair mercury level and positively correlated in the gastritis cases. Multiple stepwise regression analysis indicated that the regression equation of hair mercury level in controls could be expressed as 0.262 multiplied the value of eating seafood plus 0.434, the model that was statistically significant (p<0.01). Multiple stepwise regression analysis also indicated that the regression equation of hair mercury level in gastritis cases could be expressed as 0.305 multiplied the severity of gastritis, the model that was also statistically significant (p<0.01). The graphs of regression standardized residual for both controls and cases conformed to normal distribution. The main positively correlated factor affecting the hair mercury level is eating seafood in healthy people whereas the predominant positively correlated factor affecting the hair mercury level is the severity of gastritis in chronic gastritis patients. That is to say, the severity of chronic gastritis is positively correlated with the level of hair mercury. The incessantly increased level of hair mercury possibly reflects the development of gastritis from normal stomach to superficial gastritis and to atrophic gastritis. The detection of hair mercury is potentially a means to predict the severity of chronic gastritis and possibly to insinuate the environmental mercury threat to human health in terms of gastritis or even carcinogenesis.

Efficient least angle regression for identification of linear-in-the-parameters models

PubMed Central

Beach, Thomas H.; Rezgui, Yacine

2017-01-01

Least angle regression, as a promising model selection method, differentiates itself from conventional stepwise and stagewise methods, in that it is neither too greedy nor too slow. It is closely related to L1 norm optimization, which has the advantage of low prediction variance through sacrificing part of model bias property in order to enhance model generalization capability. In this paper, we propose an efficient least angle regression algorithm for model selection for a large class of linear-in-the-parameters models with the purpose of accelerating the model selection process. The entire algorithm works completely in a recursive manner, where the correlations between model terms and residuals, the evolving directions and other pertinent variables are derived explicitly and updated successively at every subset selection step. The model coefficients are only computed when the algorithm finishes. The direct involvement of matrix inversions is thereby relieved. A detailed computational complexity analysis indicates that the proposed algorithm possesses significant computational efficiency, compared with the original approach where the well-known efficient Cholesky decomposition is involved in solving least angle regression. Three artificial and real-world examples are employed to demonstrate the effectiveness, efficiency and numerical stability of the proposed algorithm. PMID:28293140

Long-term survival and vitality outcomes of permanent teeth following deep caries treatment with step-wise and partial-caries-removal: A Systematic Review.

PubMed

Hoefler, Vaughan; Nagaoka, Hiroko; Miller, Craig S

2016-11-01

A systematic review was performed to compare the long-term survival of deep dentine caries-affected permanent teeth treated with partial-caries-removal (PCR) versus similar teeth treated with stepwise-caries-removal techniques (SWT). Clinical studies investigating long-term PCR and SWT outcomes in unrestored permanent teeth with deep dentine caries were evaluated. Failures were defined as loss of pulp vitality or restorative failures following treatment. PubMed, Web of Science, Dentistry and Oral Sciences Source, and Central databases were systematically searched. From 136 potentially relevant articles, 9 publications utilizing data from 5 studies (2 RCTs, and 3 observational case-series) reporting outcomes for 426 permanent teeth over two to ten years were analyzed. Regarding restorative failures, >88% success at two years for both techniques was reported. For loss of pulp vitality, observational studies reported >96% vitality at two years for each technique, while one RCT reported significantly higher vitality (p<0.05) at three years for PCR (96%) compared to SWT (83%). Risk of bias was high in all studies. Successful vitality and restorative outcomes for both PCR and SWT have been demonstrated at two years and beyond in permanent teeth with deep dentine caries. Partial-caries-removal may result in fewer pulpal complications over a three year period than SWT, although claims of a therapeutic advantage are based on very few, limited-quality studies. Partial-caries-removal and SWT are deep caries management techniques that reduce pulp exposure risk. Permanent teeth with deep dentine caries treated with either technique have a high likelihood for survival beyond two years. Copyright © 2016 Elsevier Ltd. All rights reserved.

Non-Destructive Evaluation of the Leaf Nitrogen Concentration by In-Field Visible/Near-Infrared Spectroscopy in Pear Orchards.

PubMed

Wang, Jie; Shen, Changwei; Liu, Na; Jin, Xin; Fan, Xueshan; Dong, Caixia; Xu, Yangchun

2017-03-08

Non-destructive and timely determination of leaf nitrogen (N) concentration is urgently needed for N management in pear orchards. A two-year field experiment was conducted in a commercial pear orchard with five N application rates: 0 (N0), 165 (N1), 330 (N2), 660 (N3), and 990 (N4) kg·N·ha -1 . The mid-portion leaves on the year's shoot were selected for the spectral measurement first and then N concentration determination in the laboratory at 50 and 80 days after full bloom (DAB). Three methods of in-field spectral measurement (25° bare fibre under solar conditions, black background attached to plant probe, and white background attached to plant probe) were compared. We also investigated the modelling performances of four chemometric techniques (principal components regression, PCR; partial least squares regression, PLSR; stepwise multiple linear regression, SMLR; and back propagation neural network, BPNN) and three vegetation indices (difference spectral index, normalized difference spectral index, and ratio spectral index). Due to the low correlation of reflectance obtained by the 25° field of view method, all of the modelling was performed on two spectral datasets-both acquired by a plant probe. Results showed that the best modelling and prediction accuracy were found in the model established by PLSR and spectra measured with a black background. The randomly-separated subsets of calibration ( n = 1000) and validation ( n = 420) of this model resulted in high R² values of 0.86 and 0.85, respectively, as well as a low mean relative error (<6%). Furthermore, a higher coefficient of determination between the leaf N concentration and fruit yield was found at 50 DAB samplings in both 2015 (R² = 0.77) and 2014 (R² = 0.59). Thus, the leaf N concentration was suggested to be determined at 50 DAB by visible/near-infrared spectroscopy and the threshold should be 24-27 g/kg.

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

PubMed

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

Remotely Sensed Rice Yield Prediction Using Multi-Temporal NDVI Data Derived from NOAA's-AVHRR

PubMed Central

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha−1. Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly. PMID:23967112

Local repair of stoma prolapse: Case report of an in vivo application of linear stapler devices.

PubMed

Monette, Margaret M; Harney, Rodney T; Morris, Melanie S; Chu, Daniel I

2016-11-01

One of the most common late complications following stoma construction is prolapse. Although the majority of prolapse can be managed conservatively, surgical revision is required with incarceration/strangulation and in certain cases laparotomy and/or stoma reversal are not appropriate. This report will inform surgeons on safe and effective approaches to revising prolapsed stomas using local techniques. A 58 year old female with an obstructing rectal cancer previously received a diverting transverse loop colostomy. On completion of neoadjuvant treatment, re-staging found new lung metastases. She was scheduled for further chemotherapy but incarcerated a prolapsed segment of her loop colostomy. As there was no plan to resect her primary rectal tumor at the time, a local revision was preferred. Linear staplers were applied to the prolapsed stoma in step-wise fashion to locally revise the incarcerated prolapse. Post-operative recovery was satisfactory with no complications or recurrence of prolapse. We detail in step-wise fashion a technique using linear stapler devices that can be used to locally revise prolapsed stoma segments and therefore avoid a laparotomy. The procedure is technically easy to perform with satisfactory post-operative outcomes. We additionally review all previous reports of local repairs and show the evolution of local prolapse repair to the currently reported technique. This report offers surgeons an alternative, efficient and effective option for addressing the complications of stoma prolapse. While future studies are needed to assess long-term outcomes, in the short-term, our report confirms the safety and effectiveness of this local technique.

Socio-economic variables influencing mean age at marriage in Karnataka and Kerala.

PubMed

Prakasam, C P; Upadhyay, R B

1985-01-01

"In this paper an attempt was made to study the influence of certain socio-economic variables on the male and the female age at marriage in Karnataka and Kerala [India] for the year 1971. Step-wise regression method has been used to select the predictor variables influencing mean age at marriage. The results reveal that percent female literate...and percent female in labour force...are found to influence female mean age at marriage in Kerala, while the variables for Karnataka were percent female literate..., percent male literate..., and percent urban male population...." excerpt

Identification method of laser gyro error model under changing physical field

NASA Astrophysics Data System (ADS)

Wang, Qingqing; Niu, Zhenzhong

2018-04-01

In this paper, the influence mechanism of temperature, temperature changing rate and temperature gradient on the inertial devices is studied. The two-order model of zero bias and the three-order model of the calibration factor of lster gyro under temperature variation are deduced. The calibration scheme of temperature error is designed, and the experiment is carried out. Two methods of stepwise regression analysis and BP neural network are used to identify the parameters of the temperature error model, and the effectiveness of the two methods is proved by the temperature error compensation.

Prediction of health levels by remote sensing

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

Measures of the environment derived from remote sensing were compared to census population/housing measures in their ability to discriminate among health status areas in two urban communities. Three hypotheses were developed to explore the relationships between environmental and health data. Univariate and multiple step-wise linear regression analyses were performed on data from two sample areas in Houston and Galveston, Texas. Environmental data gathered by remote sensing were found to equal or surpass census data in predicting rates of health outcomes. Remote sensing offers the advantages of data collection for any chosen area or time interval, flexibilities not allowed by the decennial census.

Relationships between locus of control and paranormal beliefs.

PubMed

Newby, Robert W; Davis, Jessica Boyette

2004-06-01

The present study investigated the associations between scores on paranormal beliefs, locus of control, and certain psychological processes such as affect and cognitions as measured by the Linguistic Inquiry and Word Count. Analysis yielded significant correlations between scores on Locus of Control and two subscales of Tobacyk's (1988) Revised Paranormal Beliefs Scale, New Age Philosophy and Traditional Paranormal Beliefs. A step-wise multiple regression analysis indicated that Locus of Control was significantly related to New Age Philosophy. Other correlations were found between Tobacyk's subscales, Locus of Control, and three processes measured by the Linguistic Inquiry and Word Count.

Lateral stability analysis for X-29A drop model using system identification methodology

NASA Technical Reports Server (NTRS)

Raney, David L.; Batterson, James G.

1989-01-01

A 22-percent dynamically scaled replica of the X-29A forward-swept-wing airplane has been flown in radio-controlled drop tests at the NASA Langley Research Center. A system identification study of the recorded data was undertaken to examine the stability and control derivatives that influence the lateral behavior of this vehicle with particular emphasis on an observed wing rock phenomenon. All major lateral stability derivatives and the damping-in-roll derivative were identified for angles of attack from 5 to 80 degrees by using a data-partitioning methodology and a modified stepwise regression algorithm.

Neurocognition and community outcome in schizophrenia: long-term predictive validity.

PubMed

Fujii, Daryl E; Wylie, A Michael

2003-02-01

The present study examined the predictive validity of neuropsychological measures to functional outcome in 26 schizophrenic patients 15-plus year post-testing. Outcome measures included score on the Resource Associated Functional Level Scale (RAFLS), number of state hospital admissions, and total duration of state hospital inpatient stay. Results of several stepwise multiple regressions revealed that verbal memory significantly predicted RAFLS score, accounting for nearly half of the variance. Trails B significantly predicted duration of state hospital inpatient status. Discussion focused on the utility of these measures for clinicians and system planners. Copyright 2002 Elsevier Science B.V.

Beneficiation of the gold bearing ore by gravity and flotation

NASA Astrophysics Data System (ADS)

Gül, Alim; Kangal, Olgaç; Sirkeci, Ayhan A.; Önal, Güven

2012-02-01

Gold concentration usually consists of gravity separation, flotation, cyanidation, or the combination of these processes. The choice among these processes depends on the mineralogical characterization and gold content of the ore. Recently, the recovery of gold using gravity methods has gained attention because of low cost and environmentally friendly operations. In this study, gold pre-concentrates were produced by the stepwise gravity separation and flotation techniques. The Knelson concentrator and conventional flotation were employed for the recovery of gold. Gold bearing ore samples were taken from Gümüşhane Region, northern east part of Turkey. As a result of stepwise Knelson concentration experiments, a gold concentrate assaying around 620 g/t is produced with 41.4wt% recovery. On the other hand, a gold concentrate about 82 g/t is obtained with 89.9wt% recovery from a gold ore assaying 6 g/t Au by direct flotation.

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

Penna, M.L.; Duchiade, M.P.

This study examines the relationship between air pollution, measured as concentration of suspended particulates in the atmosphere, and infant mortality due to pneumonia in the metropolitan area of Rio de Janeiro. Multiple linear regression (progressive or stepwise method) was used to analyze infant mortality due to pneumonia, diarrhea, and all causes in 1980, by geographic area, income level, and degree of contamination. While the variable proportion of families with income equivalent to more than two minimum wages was included in the regressions corresponding to the three types of infant mortality, the average contamination index had a statistically significant coefficient (bmore » = 0.2208; t = 2.670; P = 0.0137) only in the case of mortality due to pneumonia. This would suggest a biological association, but, as in any ecological study, such conclusions should be viewed with caution. The authors believe that air quality indicators are essential to consider in studies of acute respiratory infections in developing countries.« less

Chelant-aided enhancement of lead mobilization in residential soils.

PubMed

Sarkar, Dibyendu; Andra, Syam S; Saminathan, Sumathi K M; Datta, Rupali

2008-12-01

Chelation of metals is an important factor in enhancing solubility and hence, availability to plants to promote phytoremediation. We compared the effects of two chelants, namely, ethylenediaminetetraacetic acid (EDTA) and ethylenediaminedisuccinic acid (EDDS) in enhancing mobilized lead (Pb) in Pb-based paint contaminated residential soils collected from San Antonio, Texas and Baltimore, Maryland. Batch incubation studies were performed to investigate the effectiveness of the two chelants in enhancing mobilized Pb, at various concentrations and treatment durations. Over a period of 1 month, the mobilized Pb pool in the San Antonio study soils increased from 52 mg kg(-1) to 287 and 114 mg kg(-1) in the presence of 15 mM kg(-1) EDTA and EDDS, respectively. Stepwise linear regression analysis demonstrated that pH and organic matter content significantly affected the mobilized Pb fraction. The regression models explained a large percentage, from 83 to 99%, of the total variation in mobilized Pb concentrations.

MMI: Multimodel inference or models with management implications?

USGS Publications Warehouse

Fieberg, J.; Johnson, Douglas H.

2015-01-01

We consider a variety of regression modeling strategies for analyzing observational data associated with typical wildlife studies, including all subsets and stepwise regression, a single full model, and Akaike's Information Criterion (AIC)-based multimodel inference. Although there are advantages and disadvantages to each approach, we suggest that there is no unique best way to analyze data. Further, we argue that, although multimodel inference can be useful in natural resource management, the importance of considering causality and accurately estimating effect sizes is greater than simply considering a variety of models. Determining causation is far more valuable than simply indicating how the response variable and explanatory variables covaried within a data set, especially when the data set did not arise from a controlled experiment. Understanding the causal mechanism will provide much better predictions beyond the range of data observed. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Outcome modelling strategies in epidemiology: traditional methods and basic alternatives

PubMed Central

Greenland, Sander; Daniel, Rhian; Pearce, Neil

2016-01-01

Abstract Controlling for too many potential confounders can lead to or aggravate problems of data sparsity or multicollinearity, particularly when the number of covariates is large in relation to the study size. As a result, methods to reduce the number of modelled covariates are often deployed. We review several traditional modelling strategies, including stepwise regression and the ‘change-in-estimate’ (CIE) approach to deciding which potential confounders to include in an outcome-regression model for estimating effects of a targeted exposure. We discuss their shortcomings, and then provide some basic alternatives and refinements that do not require special macros or programming. Throughout, we assume the main goal is to derive the most accurate effect estimates obtainable from the data and commercial software. Allowing that most users must stay within standard software packages, this goal can be roughly approximated using basic methods to assess, and thereby minimize, mean squared error (MSE). PMID:27097747

Modeling the language learning strategies and English language proficiency of pre-university students in UMS: A case study

NASA Astrophysics Data System (ADS)

Kiram, J. J.; Sulaiman, J.; Swanto, S.; Din, W. A.

2015-10-01

This study aims to construct a mathematical model of the relationship between a student's Language Learning Strategy usage and English Language proficiency. Fifty-six pre-university students of University Malaysia Sabah participated in this study. A self-report questionnaire called the Strategy Inventory for Language Learning was administered to them to measure their language learning strategy preferences before they sat for the Malaysian University English Test (MUET), the results of which were utilised to measure their English language proficiency. We attempted the model assessment specific to Multiple Linear Regression Analysis subject to variable selection using Stepwise regression. We conducted various assessments to the model obtained, including the Global F-test, Root Mean Square Error and R-squared. The model obtained suggests that not all language learning strategies should be included in the model in an attempt to predict Language Proficiency.

Odontological approach to sexual dimorphism in southeastern France.

PubMed

Lladeres, Emilie; Saliba-Serre, Bérengère; Sastre, Julien; Foti, Bruno; Tardivo, Delphine; Adalian, Pascal

2013-01-01

The aim of this study was to establish a prediction formula to allow for the determination of sex among the southeastern French population using dental measurements. The sample consisted of 105 individuals (57 males and 48 females, aged between 18 and 25 years). Dental measurements were calculated using Euclidean distances, in three-dimensional space, from point coordinates obtained by a Microscribe. A multiple logistic regression analysis was performed to establish the prediction formula. Among 12 selected dental distances, a stepwise logistic regression analysis highlighted the two most significant discriminate predictors of sex: one located at the mandible and the other at the maxilla. A cutpoint was proposed to prediction of true sex. The prediction formula was then tested on a validation sample (20 males and 34 females, aged between 18 and 62 years and with a history of orthodontics or restorative care) to evaluate the accuracy of the method. © 2012 American Academy of Forensic Sciences.

A Step-Wise Approach to Elicit Triangular Distributions

NASA Technical Reports Server (NTRS)

Greenberg, Marc W.

2013-01-01

Adapt/combine known methods to demonstrate an expert judgment elicitation process that: 1.Models expert's inputs as a triangular distribution, 2.Incorporates techniques to account for expert bias and 3.Is structured in a way to help justify expert's inputs. This paper will show one way of "extracting" expert opinion for estimating purposes. Nevertheless, as with most subjective methods, there are many ways to do this.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea.

PubMed

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-10-01

The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD - negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. The results suggest that psychological and medical approaches should be combined in GERD assessment.

[Establishment of cervical vertebral skeletal maturation of female children in Shanghai].

PubMed

Sun, Yan; Chen, Rong-jing; Yu, Quan; Fan, Li; Chen, Wei; Shen, Gang

2009-06-01

To establish a method for quantitatively evaluating skeletal maturation of cervical vertebrae of female children in Shanghai. The samples were selected from lateral cephalometric radiographs of 240 Shanghai girls, aged 8 to 15 years. The parameters were measured to indicate the morphological changes of the third (C3) and fourth (C4) vertebrae in width, height and the depth of the inferior curvature. The independent-sample t test and stepwise multiple regression analysis were used to estimate the growth status and the ratios of C3, C4 cervical vertebrae by SPSS 15.0 software package. The physical and morphological contour of C3, C4 cervical vertebrae increased proportionately with the increment of age. The regression formula for indicating cervical vertebral skeletal age of female children in Shanghai was expressed by the equation Y= -5.696+8.010 AH3/AP3+6.654 AH3/H3+6.045AH4/PH4 (r=0.912). The regression formula resulted from morphological measurements quantitatively indicates the skeletal maturation of cervical vertebrae of female children in Shanghai.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea

PubMed Central

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-01-01

Objectives The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Methods Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. Results GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD – negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. Conclusions The results suggest that psychological and medical approaches should be combined in GERD assessment. PMID:27691373

Sparse Logistic Regression for Diagnosis of Liver Fibrosis in Rat by Using SCAD-Penalized Likelihood

PubMed Central

Yan, Fang-Rong; Lin, Jin-Guan; Liu, Yu

2011-01-01

The objective of the present study is to find out the quantitative relationship between progression of liver fibrosis and the levels of certain serum markers using mathematic model. We provide the sparse logistic regression by using smoothly clipped absolute deviation (SCAD) penalized function to diagnose the liver fibrosis in rats. Not only does it give a sparse solution with high accuracy, it also provides the users with the precise probabilities of classification with the class information. In the simulative case and the experiment case, the proposed method is comparable to the stepwise linear discriminant analysis (SLDA) and the sparse logistic regression with least absolute shrinkage and selection operator (LASSO) penalty, by using receiver operating characteristic (ROC) with bayesian bootstrap estimating area under the curve (AUC) diagnostic sensitivity for selected variable. Results show that the new approach provides a good correlation between the serum marker levels and the liver fibrosis induced by thioacetamide (TAA) in rats. Meanwhile, this approach might also be used in predicting the development of liver cirrhosis. PMID:21716672

Comparison of machine-learning methods for above-ground biomass estimation based on Landsat imagery

NASA Astrophysics Data System (ADS)

Wu, Chaofan; Shen, Huanhuan; Shen, Aihua; Deng, Jinsong; Gan, Muye; Zhu, Jinxia; Xu, Hongwei; Wang, Ke

2016-07-01

Biomass is one significant biophysical parameter of a forest ecosystem, and accurate biomass estimation on the regional scale provides important information for carbon-cycle investigation and sustainable forest management. In this study, Landsat satellite imagery data combined with field-based measurements were integrated through comparisons of five regression approaches [stepwise linear regression, K-nearest neighbor, support vector regression, random forest (RF), and stochastic gradient boosting] with two different candidate variable strategies to implement the optimal spatial above-ground biomass (AGB) estimation. The results suggested that RF algorithm exhibited the best performance by 10-fold cross-validation with respect to R2 (0.63) and root-mean-square error (26.44 ton/ha). Consequently, the map of estimated AGB was generated with a mean value of 89.34 ton/ha in northwestern Zhejiang Province, China, with a similar pattern to the distribution mode of local forest species. This research indicates that machine-learning approaches associated with Landsat imagery provide an economical way for biomass estimation. Moreover, ensemble methods using all candidate variables, especially for Landsat images, provide an alternative for regional biomass simulation.

Modeling and forecasting US presidential election using learning algorithms

NASA Astrophysics Data System (ADS)

Zolghadr, Mohammad; Niaki, Seyed Armin Akhavan; Niaki, S. T. A.

2017-09-01

The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president's approval rate, and others are considered in a stepwise regression to identify significant variables. The president's approval rate is identified as the most significant variable, based on which eight other variables are identified and considered in the model development. Preprocessing methods are applied to prepare the data for the learning algorithms. The proposed procedure significantly increases the accuracy of the model by 50%. The learning algorithms (ANN and SVR) proved to be superior to linear regression based on each method's calculated performance measures. The SVR model is identified as the most accurate model among the other models as this model successfully predicted the outcome of the election in the last three elections (2004, 2008, and 2012). The proposed approach significantly increases the accuracy of the forecast.

Impact of “Sick” and “Recovery” Roles on Brain Injury Rehabilitation Outcomes

PubMed Central

Barclay, David A.

2012-01-01

This study utilizes a multivariate, correlational, expost facto research design to examine Parsons' “sick role” as a dynamic, time-sensitive process of “sick role” and “recovery role” and the impact of this process on goal attainment (H1) and psychosocial distress (H2) of adult survivors of acquired brain injury. Measures used include the Brief Symptom Inventory-18, a Goal Attainment Scale, and an original instrument to measure sick role process. 60 survivors of ABI enrolled in community reentry rehabilitation participated. Stepwise regression analyses did not fully support the multivariate hypotheses. Two models emerged from the stepwise analyses. Goal attainment, gender, and postrehab responsibilities accounted for 40% of the shared variance of psychosocial distress. Anxiety and depression accounted for 22% of the shared variance of goal attainment with anxiety contributing to the majority of the explained variance. Bivariate analysis found sick role variables, anxiety, somatization, depression, gender, and goal attainment as significant. The study has implications for ABI rehabilitation in placing greater emphasis on sick role processes, anxiety, gender, and goal attainment in guiding program planning and future research with survivors of ABI. PMID:23119164

Basic principles of Hasse diagram technique in chemistry.

PubMed

Brüggemann, Rainer; Voigt, Kristina

2008-11-01

Principles of partial order applied to ranking are explained. The Hasse diagram technique (HDT) is the application of partial order theory based on a data matrix. In this paper, HDT is introduced in a stepwise procedure, and some elementary theorems are exemplified. The focus is to show how the multivariate character of a data matrix is realized by HDT and in which cases one should apply other mathematical or statistical methods. Many simple examples illustrate the basic theoretical ideas. Finally, it is shown that HDT is a useful alternative for the evaluation of antifouling agents, which was originally performed by amoeba diagrams.

Estimating the concrete compressive strength using hard clustering and fuzzy clustering based regression techniques.

PubMed

Nagwani, Naresh Kumar; Deo, Shirish V

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm.

Estimating the Concrete Compressive Strength Using Hard Clustering and Fuzzy Clustering Based Regression Techniques

PubMed Central

Nagwani, Naresh Kumar; Deo, Shirish V.

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm. PMID:25374939

Robotic Single-Site Sacrocolpopexy Using Barbed Suture Anchoring and Peritoneal Tunneling Technique: Tips and Tricks.

PubMed

Guan, Xiaoming; Ma, Yingchun; Gisseman, Jordan; Kleithermes, Christopher; Liu, Juan

2017-01-01

To demonstrate the tips and tricks of a simpler technique for single-site sacrocolpopexy using barbed suture anchoring and retroperitoneal tunneling to make the procedure more efficient and reproducible. Step-by-step description of surgical tutorial using a narrated video (Canadian Task Force classification III). Academic tertiary care hospital. Patient with Stage III uterine prolapse. Sacrocolpopexy is increasing utilized since the FDA warning about complications of vaginal mesh surgery. It is the gold standard for repair of apical prolapse. However, there is great variation in the sacrocolpopexy procedure techniques and they have not been standardized. Traditional single-site laparoscopic sacrocolpopexy is very challenging as the procedure time is long and suturing is difficult. The advantages of suturing with wristed needle drivers in robotic single-site surgery simplify this complex procedure. Furthermore, using barbed suture anchoring and peritoneal tunneling technique potentially decreases the surgeon's learning curve and makes the procedure reproducible. In this video, we demonstrate a supracervial hysterectomy with a stepwise explanation of the correct technique for performing a robotic single incision sacrocolpopexy. Sacrocolpopexy is increasing used since the US Food and Drug Administration warning about complications of vaginal mesh surgery. It is the gold standard for repair of apical prolapse. However, a great variation exists in the sacrocolpopexy procedure techniques that need to be standardized. Traditional single-site laparoscopic sacrocolpopexy is very challenging because the procedure time is long and suturing is difficult. The advantages of suturing with wristed needle drivers in robotic single-site surgery simplify this complex procedure. Furthermore, using the barbed suture anchoring and peritoneal tunneling technique potentially decreases the surgeon's learning curve and makes the procedure reproducible. In this video, we demonstrate a supracervical hysterectomy with a stepwise explaation of the correct technique for performing a robotic single-incision sacrocolpopexy. The possibility of using the barbed suture and peritoneal tunneling technique with wristed needle drivers in robotic single-site sacrocolpopexy offers the possibility of an effective, safe, reproducible, and cosmetic surgical option. Copyright © 2016 AAGL. Published by Elsevier Inc. All rights reserved.

[Stress-ECG is adequate to detect myocardial ischemia: when are additional diagnostic tests needed?].

PubMed

Baer, F M

2007-09-01

The stress-ECG is the most often adopted and most cost effective initial diagnostic test for the assessment of myocardial ischemia in patients with suspected coronary artery disease (CAD). Prerequisites for the diagnostic usefullness of stress-ECG are a clearly interpretable ST-segment, ability to reach the predicted work load, an intermediate pretest probability for CAD ranging between 10% and 90% and the absence of any contraindications for dynamic exercise. Because of the limited diagnostic sensitivity of about 70%, and a high percentage of patients, who are unable to exercise, a negative stress ECG can definitely not exclude hemodynamically significant CAD. Therefore, stress imaging techniques like myocardial scintigraphy, stress-echocardiography and stress magnetic resonance imaging play a major role in the stepwise diagnostic work-up of patients with suspected CAD. These stress imaging techniques are basically interchangeable since no method is definitely superior to one of the others. However, each method has its specific pros and cons and inherent contraindications. Therefore the choice of the stress imaging method and the form of stress applied should be based on the individual patients characteristics to gain optimal image quality and diagnostic accuracy. Moreover, the decision for one method should take the local availability and institutional expertise of diagnostic centers into account. Although partly substituted by stress imaging techniques the stress-ECG still remains the workhorse for a stepwise diagnostic work-up of patients with suspected CAD.

Inclusion of Endogenous Hormone Levels in Risk Prediction Models of Postmenopausal Breast Cancer

PubMed Central

Tworoger, Shelley S.; Zhang, Xuehong; Eliassen, A. Heather; Qian, Jing; Colditz, Graham A.; Willett, Walter C.; Rosner, Bernard A.; Kraft, Peter; Hankinson, Susan E.

2014-01-01

Purpose Endogenous hormones are risk factors for postmenopausal breast cancer, and their measurement may improve our ability to identify high-risk women. Therefore, we evaluated whether inclusion of plasma estradiol, estrone, estrone sulfate, testosterone, dehydroepiandrosterone sulfate, prolactin, and sex hormone–binding globulin (SHBG) improved risk prediction for postmenopausal invasive breast cancer (n = 437 patient cases and n = 775 controls not using postmenopausal hormones) in the Nurses' Health Study. Methods We evaluated improvement in the area under the curve (AUC) for 5-year risk of invasive breast cancer by adding each hormone to the Gail and Rosner-Colditz risk scores. We used stepwise regression to identify the subset of hormones most associated with risk and assessed AUC improvement; we used 10-fold cross validation to assess model overfitting. Results Each hormone was associated with breast cancer risk (odds ratio doubling, 0.82 [SHBG] to 1.37 [estrone sulfate]). Individual hormones improved the AUC by 1.3 to 5.2 units relative to the Gail score and 0.3 to 2.9 for the Rosner-Colditz score. Estrone sulfate, testosterone, and prolactin were selected by stepwise regression and increased the AUC by 5.9 units (P = .003) for the Gail score and 3.4 (P = .04) for the Rosner-Colditz score. In cross validation, the average AUC change across the validation data sets was 6.0 (P = .002) and 3.0 units (P = .03), respectively. Similar results were observed for estrogen receptor–positive disease (selected hormones: estrone sulfate, testosterone, prolactin, and SHBG; change in AUC, 8.8 [P < .001] for Gail score and 5.8 [P = .004] for Rosner-Colditz score). Conclusion Our results support that endogenous hormones improve risk prediction for invasive breast cancer and could help identify women who may benefit from chemoprevention or more screening. PMID:25135988

Suicidal Ideation and Schizophrenia: Contribution of Appraisal, Stigmatization, and Cognition.

PubMed

Stip, Emmanuel; Caron, Jean; Tousignant, Michel; Lecomte, Yves

2017-10-01

To predict suicidal ideation in people with schizophrenia, certain studies have measured its relationship with the variables of defeat and entrapment. The relationships are positive, but their interactions remain undefined. To further their understanding, this research sought to measure the relationship between suicidal ideation with the variables of loss, entrapment, and humiliation. The convenience sample included 30 patients with schizophrenia spectrum disorders. The study was prospective (3 measurement times) during a 6-month period. Results were analyzed by stepwise multiple regression. The contribution of the 3 variables to the variance of suicidal ideation was not significant at any of the 3 times (T1: 16.2%, P = 0.056; T2: 19.9%, P = 0.117; T3: 11.2%, P = 0.109). Further analyses measured the relationship between the variables of stigmatization, perceived cognitive dysfunction, symptoms, depression, self-esteem, reason to live, spirituality, social provision, and suicidal ideation. Stepwise multiple regression demonstrated that the contribution of the variables of stigmatization and perceived cognitive dysfunction to the variance of suicidal ideation was significant at all 3 times (T1: 41.7.5%, P = 0.000; T2: 35.2%, P = 0.001; T3: 21.5%, P = 0.012). Yet, over time, the individual contribution of the variables changed: T1, stigmatization (β = 0.518; P = 0.002); T2, stigmatization (β = 0.394; P = 0.025) and perceived cognitive dysfunction (β = 0.349; P = 0.046). Then, at T3, only perceived cognitive dysfunction contributed significantly to suicidal ideation (β = 0.438; P = 0.016). The results highlight the importance of the contribution of the variables of perceived cognitive dysfunction and stigmatization in the onset of suicidal ideation in people with schizophrenia spectrum disorders.

Baastrup's Disease Is Associated with Recurrent of Sciatica after Posterior Lumbar Spinal Decompressions Utilizing Floating Spinous Process Procedures

PubMed Central

Mannoji, Chikato; Murakami, Masazumi; Kinoshita, Tomoaki; Hirayama, Jiro; Miyashita, Tomohiro; Eguchi, Yawara; Yamazaki, Masashi; Suzuki, Takane; Aramomi, Masaaki; Ota, Mitsutoshi; Maki, Satoshi; Takahashi, Kazuhisa; Furuya, Takeo

2016-01-01

Study Design Retrospective case-control study. Purpose To determine whether kissing spine is a risk factor for recurrence of sciatica after lumbar posterior decompression using a spinous process floating approach. Overview of Literature Kissing spine is defined by apposition and sclerotic change of the facing spinous processes as shown in X-ray images, and is often accompanied by marked disc degeneration and decrement of disc height. If kissing spine significantly contributes to weight bearing and the stability of the lumbar spine, trauma to the spinous process might induce a breakdown of lumbar spine stability after posterior decompression surgery in cases of kissing spine. Methods The present study included 161 patients who had undergone posterior decompression surgery for lumbar canal stenosis using a spinous process floating approaches. We defined recurrence of sciatica as that resolved after initial surgery and then recurred. Kissing spine was defined as sclerotic change and the apposition of the spinous process in a plain radiogram. Preoperative foraminal stenosis was determined by the decrease of perineural fat intensity detected by parasagittal T1-weighted magnetic resonance imaging. Preoperative percentage slip, segmental range of motion, and segmental scoliosis were analyzed in preoperative radiographs. Univariate analysis followed by stepwise logistic regression analysis determined factors independently associated with recurrence of sciatica. Results Stepwise logistic regression revealed kissing spine (p=0.024; odds ratio, 3.80) and foraminal stenosis (p<0.01; odds ratio, 17.89) as independent risk factors for the recurrence of sciatica after posterior lumbar spinal decompression with spinous process floating procedures for lumbar spinal canal stenosis. Conclusions When a patient shows kissing spine and concomitant subclinical foraminal stenosis at the affected level, we should sufficiently discuss the selection of an appropriate surgical procedure. PMID:27994785

Baastrup's Disease Is Associated with Recurrent of Sciatica after Posterior Lumbar Spinal Decompressions Utilizing Floating Spinous Process Procedures.

PubMed

Koda, Masao; Mannoji, Chikato; Murakami, Masazumi; Kinoshita, Tomoaki; Hirayama, Jiro; Miyashita, Tomohiro; Eguchi, Yawara; Yamazaki, Masashi; Suzuki, Takane; Aramomi, Masaaki; Ota, Mitsutoshi; Maki, Satoshi; Takahashi, Kazuhisa; Furuya, Takeo

2016-12-01

Retrospective case-control study. To determine whether kissing spine is a risk factor for recurrence of sciatica after lumbar posterior decompression using a spinous process floating approach. Kissing spine is defined by apposition and sclerotic change of the facing spinous processes as shown in X-ray images, and is often accompanied by marked disc degeneration and decrement of disc height. If kissing spine significantly contributes to weight bearing and the stability of the lumbar spine, trauma to the spinous process might induce a breakdown of lumbar spine stability after posterior decompression surgery in cases of kissing spine. The present study included 161 patients who had undergone posterior decompression surgery for lumbar canal stenosis using a spinous process floating approaches. We defined recurrence of sciatica as that resolved after initial surgery and then recurred. Kissing spine was defined as sclerotic change and the apposition of the spinous process in a plain radiogram. Preoperative foraminal stenosis was determined by the decrease of perineural fat intensity detected by parasagittal T1-weighted magnetic resonance imaging. Preoperative percentage slip, segmental range of motion, and segmental scoliosis were analyzed in preoperative radiographs. Univariate analysis followed by stepwise logistic regression analysis determined factors independently associated with recurrence of sciatica. Stepwise logistic regression revealed kissing spine ( p =0.024; odds ratio, 3.80) and foraminal stenosis ( p <0.01; odds ratio, 17.89) as independent risk factors for the recurrence of sciatica after posterior lumbar spinal decompression with spinous process floating procedures for lumbar spinal canal stenosis. When a patient shows kissing spine and concomitant subclinical foraminal stenosis at the affected level, we should sufficiently discuss the selection of an appropriate surgical procedure.

Depression is a predictor for balance in people with multiple sclerosis.

PubMed

Alghwiri, Alia A; Khalil, Hanan; Al-Sharman, Alham; El-Salem, Khalid

2018-05-26

Balance impairments are common and multifactorial among people with multiple sclerosis (MS). Depression is the most common psychological disorder in MS population and is strongly correlated with MS disease. Depression might be one of the factors that contribute to balance deficits in this population. However, the relationship between depression and balance impairments has not been explored in people with MS. To investigate the association between depression and balance impairments in people with MS. Cross sectional design was used in patients with MS. The Activities-specific Balance Confidence scale (ABC) and Berg Balance Scale (BBS) was used to assess balance. Beck Depression Inventory (BDI-II) was used to quantify depression and Kurtizki Expanded Disability Status Scale (EDSS) was utilized for the evaluation of MS disability severity. Pearson correlation coefficient was used to examine the association between depression and balance measurements. Multiple linear stepwise regressions were also conducted to find out if depression is a potential predictor for balance deficits. Seventy-five individuals with MS (Female = 69%) with a mean age (SD) of 38.8 (10) and a mean (SD) EDSS score of 3.0 (1.4) were recruited in this study. Depression was present in 53% of the patients. Depression was significantly correlated with balance measurements and EDSS. However, multiple linear stepwise regressions found that only depression and age significantly predict balance. Depression and balance were found frequent and associated in people with MS. Importantly depression was a significant predictor for balance impairments in individuals with MS. Balance rehabilitation may be hindered by depression. Therefore, depression should be evaluated and treated properly in individuals with MS. Copyright © 2018 Elsevier B.V. All rights reserved.

Emergency department blood transfusion: the first two units are free.

PubMed

Ley, Eric J; Liou, Douglas Z; Singer, Matthew B; Mirocha, James; Melo, Nicolas; Chung, Rex; Bukur, Marko; Salim, Ali

2013-09-01

Studies on blood product transfusions after trauma recommend targeting specific ratios to reduce mortality. Although crystalloid volumes as little as 1.5 L predict increased mortality after trauma, little data is available regarding the threshold of red blood cell (RBC) transfusion volume that predicts increased mortality. Data from a level I trauma center between January 2000 and December 2008 were reviewed. Trauma patients who received at least 100 mL RBC in the emergency department (ED) were included. Each unit of RBC was defined as 300 mL. Demographics, RBC transfusion volume, and mortality were analyzed in the nonelderly (<70 y) and elderly (≥70 y). Multivariate logistic regression was performed at various volume cutoffs to determine whether there was a threshold transfusion volume that independently predicted mortality. A total of 560 patients received ≥100 mL RBC in the ED. Overall mortality was 24.3%, with 22.5% (104 deaths) in the nonelderly and 32.7% (32 deaths) in the elderly. Multivariate logistic regression demonstrated that RBC transfusion of ≥900 mL was associated with increased mortality in both the nonelderly (adjusted odds ratio 2.06, P = 0.008) and elderly (adjusted odds ratio 5.08, P = 0.006). Although transfusion of greater than 2 units in the ED was an independent predictor of mortality, transfusion of 2 units or less was not. Interestingly, unlike crystalloid volume, stepwise increases in blood volume were not associated with stepwise increases in mortality. The underlying etiology for mortality discrepancies, such as transfusion ratios, hypothermia, or immunosuppression, needs to be better delineated. Copyright © 2013 Elsevier Inc. All rights reserved.

Determinants of brain-derived neurotrophic factor (BDNF) in umbilical cord and maternal serum.

PubMed

Flöck, A; Weber, S K; Ferrari, N; Fietz, C; Graf, C; Fimmers, R; Gembruch, U; Merz, W M

2016-01-01

Brain-derived neurotrophic factor (BDNF) plays a fundamental role in brain development; additionally, it is involved in various aspects of cerebral function, including neurodegenerative and psychiatric diseases. Involvement of BDNF in parturition has not been investigated. The aim of our study was to analyze determinants of umbilical cord BDNF (UC-BDNF) concentrations of healthy, term newborns and their respective mothers. This cross-sectional prospective study was performed at a tertiary referral center. Maternal venous blood samples were taken on admission to labor ward; newborn venous blood samples were drawn from the umbilical cord (UC), before delivery of the placenta. Analysis was performed with a commercially available immunoassay. Univariate analyses and stepwise multivariate regression models were applied. 120 patients were recruited. UC-BDNF levels were lower than maternal serum concentrations (median 641 ng/mL, IQR 506 vs. median 780 ng/mL, IQR 602). Correlation between UC- and maternal BDNF was low (R=0.251, p=0.01). In univariate analysis, mode of delivery (MoD), gestational age (GA), body mass index at delivery, and gestational diabetes were determinants of UC-BDNF (MoD and smoking for maternal BDNF, respectively). Stepwise multivariate regression analysis revealed a model with MoD and GA as determinants for UC-BDNF (MoD for maternal BDNF). MoD and GA at delivery are determinants of circulating BDNF in the mother and newborn. We hypothesize that BDNF, like other neuroendocrine factors, is involved in the neuroendocrine cascade of delivery. Timing and mode of delivery may exert BDNF-induced effects on the cerebral function of newborns and their mothers. Copyright © 2015 Elsevier Ltd. All rights reserved.

PREOPERATIVE MRI IMPROVES PREDICTION OF EXTENSIVE OCCULT AXILLARY LYMPH NODE METASTASES IN BREAST CANCER PATIENTS WITH A POSITIVE SENTINEL LYMPH NODE BIOPSY

PubMed Central

Loiselle, Christopher; Eby, Peter R.; Kim, Janice N.; Calhoun, Kristine E.; Allison, Kimberly H.; Gadi, Vijayakrishna K.; Peacock, Sue; Storer, Barry; Mankoff, David A.; Partridge, Savannah C.; Lehman, Constance D.

2014-01-01

Rationale and Objectives To test the ability of quantitative measures from preoperative Dynamic Contrast Enhanced MRI (DCE-MRI) to predict, independently and/or with the Katz pathologic nomogram, which breast cancer patients with a positive sentinel lymph node biopsy will have ≥ 4 positive axillary lymph nodes upon completion axillary dissection. Methods and Materials A retrospective review was conducted to identify clinically node-negative invasive breast cancer patients who underwent preoperative DCE-MRI, followed by sentinel node biopsy with positive findings and complete axillary dissection (6/2005 – 1/2010). Clinical/pathologic factors, primary lesion size and quantitative DCE-MRI kinetics were collected from clinical records and prospective databases. DCE-MRI parameters with univariate significance (p < 0.05) to predict ≥ 4 positive axillary nodes were modeled with stepwise regression and compared to the Katz nomogram alone and to a combined MRI-Katz nomogram model. Results Ninety-eight patients with 99 positive sentinel biopsies met study criteria. Stepwise regression identified DCE-MRI total persistent enhancement and volume adjusted peak enhancement as significant predictors of ≥4 metastatic nodes. Receiver operating characteristic (ROC) curves demonstrated an area under the curve (AUC) of 0.78 for the Katz nomogram, 0.79 for the DCE-MRI multivariate model, and 0.87 for the combined MRI-Katz model. The combined model was significantly more predictive than the Katz nomogram alone (p = 0.003). Conclusion Integration of DCE-MRI primary lesion kinetics significantly improved the Katz pathologic nomogram accuracy to predict presence of metastases in ≥ 4 nodes. DCE-MRI may help identify sentinel node positive patients requiring further localregional therapy. PMID:24331270

A Randomized-Controlled Trial Examining the Effects of Reflexology on Anxiety of Patients Undergoing Coronary Angiography

PubMed Central

Molavi Vardanjani, Mehdi; Masoudi Alavi, Negin; Razavi, Narges Sadat; Aghajani, Mohammad; Azizi-Fini, Esmail; Vaghefi, Seied Morteza

2013-01-01

Background: The anxiety reduction before coronary angiography has clinical advantages and is one of the objectives of nursing. Reflexology is a non-invasive method that has been used in several clinical situations. Applying reflexology might have effect on the reduction of anxiety before coronary angiography. Objectives: The aim of this randomized clinical trial was to investigate the effect of reflexology on anxiety among patients undergoing coronary angiography. Patients and Methods: This trial was conducted in Shahid Beheshti Hospital, in Kashan, Iran. One hundred male patients who were undergoing coronary angiography were randomly enrolled into intervention and placebo groups. The intervention protocol was included 30 minutes of general foot massage and the stimulation of three reflex points including solar plexus, pituitary gland, and heart. The placebo group only received the general foot massage. Spielbergers state trait anxiety inventory was used to assess the anxiety experienced by patients. Data was analyzed using Man-Witney, Wilcoxon and Chi-square tests. The stepwise multiple regressions used to analyze the variables that are involved in anxiety reduction. Results: The mean range of anxiety decreased from 53.24 to 45.24 in reflexology group which represented 8 score reduction (P = 0.0001). The reduction in anxiety was 5.9 score in placebo group which was also significant (P = 0.0001). The anxiety reduction was significantly higher in reflexology group (P = 0.014). The stepwise multiple regression analysis showed that doing reflexology can explain the 7.5% of anxiety reduction which made a significant model. Conclusions: Reflexology can decrease the anxiety level before coronary angiography. Therefore, reflexology before coronary angiography is recommended. PMID:25414869

A comparison of logistic regression analysis and an artificial neural network using the BI-RADS lexicon for ultrasonography in conjunction with introbserver variability.

PubMed

Kim, Sun Mi; Han, Heon; Park, Jeong Mi; Choi, Yoon Jung; Yoon, Hoi Soo; Sohn, Jung Hee; Baek, Moon Hee; Kim, Yoon Nam; Chae, Young Moon; June, Jeon Jong; Lee, Jiwon; Jeon, Yong Hwan

2012-10-01

To determine which Breast Imaging Reporting and Data System (BI-RADS) descriptors for ultrasound are predictors for breast cancer using logistic regression (LR) analysis in conjunction with interobserver variability between breast radiologists, and to compare the performance of artificial neural network (ANN) and LR models in differentiation of benign and malignant breast masses. Five breast radiologists retrospectively reviewed 140 breast masses and described each lesion using BI-RADS lexicon and categorized final assessments. Interobserver agreements between the observers were measured by kappa statistics. The radiologists' responses for BI-RADS were pooled. The data were divided randomly into train (n = 70) and test sets (n = 70). Using train set, optimal independent variables were determined by using LR analysis with forward stepwise selection. The LR and ANN models were constructed with the optimal independent variables and the biopsy results as dependent variable. Performances of the models and radiologists were evaluated on the test set using receiver-operating characteristic (ROC) analysis. Among BI-RADS descriptors, margin and boundary were determined as the predictors according to stepwise LR showing moderate interobserver agreement. Area under the ROC curves (AUC) for both of LR and ANN were 0.87 (95% CI, 0.77-0.94). AUCs for the five radiologists ranged 0.79-0.91. There was no significant difference in AUC values among the LR, ANN, and radiologists (p > 0.05). Margin and boundary were found as statistically significant predictors with good interobserver agreement. Use of the LR and ANN showed similar performance to that of the radiologists for differentiation of benign and malignant breast masses.

[HPLC specific chromatogram spectrum-effect relationship for Shuanghuanglian on MDCK cell injury induced by influenza A virus (H1N1)].

PubMed

Liu, Ting; Wang, Hai-dan; Di, Liu-qing; Kang, An; Zhao, Xiao-li; Zhu, Xuan-xuan; Li, Jun-song

2015-11-01

To establish HPLC specific chromatogram and its correlation with the protection effect of Shuanghuanglian on MDCK (Madin-Darby canine kidney) cell injury induced by influenza A virus( H1N1). Nine recipes of Shuanghuanglian based on the official prescription were prepared according to orthogonal test for HPLC analysis and MDCK cells protection experiment separately (cytopathic effect (CPE) method was used for observing the virus infectivity and MTT staining results were used as the determining indexes for drug concentration selection and analyzing cell viability). The results suggested that all the other Shuang-Huang-Lian recipes except recipe1 demonstrate protecting effect on MDCK cell injury induced by influenza A virus (P < 0.01, P < 0.001). Stepwise regression analysis was used for analyzing the relationships between HPLC fingerprint and the protecting effect of Shuanghuanglian on influenza A virus induced MDCK cell injury. Peak 2, 3, 6, 8 and 12 were found to be strongly related with anti-influenza A virus efficacy. Stepwise regression analysis of recipes data and efficacy data showed that Lonicerae Japonicae Flos and Forsythiae Fructus were positively associated with the protecting effect of cells injury. From HPLC fingerprints, we found that peak 2, 3, 12 were from Lonicerae Japonicae Flos and peak 6, 8 were from Forsythiae Fructus. Four peaks were identified through comparing the retention time between the standard and Shuanghuanglian recipes, and they were chlorogenicacid, cryptochlorogenic acid, forsythoside B and 3,4-dicaffeoylquinic acid respectively. Caffeic acid derivatives in Lonicerae Japonicae Flos and Forsythiae Fructus were found to be greatly correlated with anti-influenza A virus efficacy and maybe the substance basis of Shuanghuanglian.

Factors associated with enrollment of African Americans into a clinical trial: results from the African American study of kidney disease and hypertension.

PubMed

Gadegbeku, Crystal A; Stillman, Phyllis Kreger; Huffman, Mark D; Jackson, James S; Kusek, John W; Jamerson, Kenneth A

2008-11-01

Recruitment of diverse populations into clinical trials remains challenging but is needed to fully understand disease processes and benefit the general public. Greater knowledge of key factors among ethnic and racial minority populations associated with the decision to participate in clinical research studies may facilitate recruitment and enhance the generalizibility of study results. Therefore, during the recruitment phase of the African American Study of Kidney Disease and Hypertension (AASK) trial, we conducted a telephone survey, using validated questions, to explore potential facilitators and barriers of research participation among eligible candidates residing in seven U.S. locations. Survey responses included a range of characteristics and perceptions among participants and non-participants and were compared using bivariate and step-wise logistic regression analyses. One-hundred forty-one respondents in the one-hundred forty (70 trial participants and 71 non-participants) completed the survey. Trial participants and non-participants were similar in multiple demographic characteristics and shared similar views on discrimination, physician mistrust, and research integrity. Key group differences were related to their perceptions of the impact of their research participation. Participants associated enrollment with personal and societal health benefits, while non-participants were influenced by the health risks. In a step-wise linear regression analysis, the most powerful significant positive predictors of participation were acknowledgement of health status as important in the enrollment decision (OR=4.54, p=0.006), employment (OR=3.12, p = 0.05) and healthcare satisfaction (OR=2.12, p<0.01). Racially-based mistrust did not emerge as a negative predictor and subjects' decisions were not influenced by the race of the research staff. In conclusion, these results suggest that health-related factors, and not psychosocial perceptions, have predominant influence on research participation among African Americans.

[Recommendations for the Stepwise Occupational Reintegration: Can the Characteristic of the Patients Explain the Differences Between the Rehabilitation Centers?].

PubMed

Schmid, L; Jankowiak, S; Kaluscha, R; Krischak, G

2016-06-01

The first step to initiate a stepwise occupational reintegration (SOR) is the recommendation of the rehabilitation centers. Therefore rehabilitation centers have a significant impact on the use of SOR. There is evidence that the recommendation rate between the rehabilitation centers differs clearly. The present survey therefore analyses in detail the differences of the recommendation rate and examines which patient-related factors could explain the differences. This study is based on analysis of routine data provided by the German pension insurance in Baden-Württemberg (Rehabilitationsstatistikdatenbasis 2013; RSD). In the analyses rehabilitation measures were included if they were conducted by employed patients (18-64 years) with a muscular-skeletal system disease or a disorder of the connective tissue. Logistic regression models were performed to explain the differences in the recommendation rate of the rehabilitation centers. The data of 134 853 rehabilitation measures out of 32 rehabilitation centers were available. The recommendation rate differed between the rehabilitation centers from 1.36-18.53%. The logistic regression analysis showed that the period of working incapacity 12 month before the rehabilitation and the working capacity on the current job were the most important predictors for the recommendation of a SOR by the rehabilitation centers. Also the rehabilitation centers themselves have an important influence. The results of this survey indicate that the characteristic of the patients is an important factor for the recommendation of SOR. Additionally the rehabilitation centers themselves have an influence on the recommendation of SOR. The results point to the fact that the rehabilitation centers use different criteria by making a recommendation. © Georg Thieme Verlag KG Stuttgart · New York.

Impact of catheter ablation with remote magnetic navigation on procedural outcomes in patients with persistent and long-standing persistent atrial fibrillation.

PubMed

Jin, Qi; Pehrson, Steen; Jacobsen, Peter Karl; Chen, Xu

2015-11-01

The objectives of this study were to assess the procedural outcomes of persistent and long-standing persistent atrial fibrillation (PsAF and L-PsAF) ablation guided by remote magnetic navigation (RMN), and to detect factors predicting acute restoration of sinus rhythm (SR) by ablation with RMN. A total of 313 patients (275 male, age 59 ± 9.5 years) with PsAF (187/313) or L-PsAF (126/313) undergoing ablation using RMN were included. Patients' disease history, pulmonary venous anatomy, left atrial (LA) volume, procedure time, mapping plus ablation time, radiofrequency (RF) ablation time, fluoroscopy time, radiation dose, and complications were assessed. Stepwise regression was used to predict which variable could best predict acute restoration from AF to SR by ablation. Compared to PsAF, procedure time and RF ablation time were significantly increased in patients with L-PsAF (P = 0.01 and P < 0.001, respectively). No major complications occurred during the procedures in either PsAF or L-PsAF patients. Fifty five of 313 patients converted directly to SR by ablation. Compared to L-PsAF, the rate of SR restoration was significantly higher in PsAF (21 vs 12%, P = 0.03). Stepwise regression analysis showed LA volume was the primary parameter affecting SR restoration (P = 0.01). The LA volume of patients without direct SR restoration by ablation was 24% greater than that of patients with SR restoration (P < 0.001). Catheter ablation using RMN is a safe and effective method for PsAF and L-PsAF. LA volume could be a predictor of direct restoration of SR from sustaining AF by ablation using RMN.

Nutritional and biochemical parameters associated with 6-year change in bone mineral density in community-dwelling Japanese women aged 69 years and older: The Muramatsu Study.

PubMed

Nakamura, Kazutoshi; Oyama, Mari; Saito, Toshiko; Oshiki, Rieko; Kobayashi, Ryosaku; Nishiwaki, Tomoko; Nashimoto, Mitsue; Tsuchiya, Yasuo

2012-04-01

Predictors of bone loss in elderly Asian women have been unclear. This cohort study aimed to assess lifestyle, nutritional, and biochemical predictors of bone loss in elderly Japanese women. Subjects included 389 community-dwelling women aged 69 y and older from the Muramatsu cohort initiated in 2003; follow-up ended in 2009. We obtained data on physical characteristics, osteoporosis treatment (with bisphosphonates or selective estrogen receptor modulators), physical activity, calcium intake, serum 25-hydroxyvitamin D, undercarboxylated osteocalcin, serum albumin, and bone turnover markers as predictors. The outcome was a 6-y change in forearm BMD (ΔBMD). Osteoporosis treatment was coded as 0 for none, 1 for sometimes, and 2 for always during the follow-up period. Stepwise multiple linear regression analysis was used to identify independent predictors of ΔBMD. Mean age of the subjects was 73.3 y. Mean values of ΔBMD and Δweight were -0.019 g/cm(2) (-5.8%) and -2.2 kg, respectively. Stepwise multiple linear regression analysis revealed baseline BMD (β = -0.137, P < 0.0001), osteoporosis treatment (β = 0.0068, P = 0.0105), serum albumin levels (β = 0.0122, P = 0.0319), and Δweight (β = 0.0015, P = 0.0009) as significant independent predictors of ΔBMD. However, none of the other nutritional or biochemical indices were found to be significant predictors of ΔBMD. Our findings indicate that adequate general nutrition and appropriate osteoporosis medication, rather than specific nutritional regimens, may be effective in preventing bone loss in elderly women. Copyright © 2012 Elsevier Inc. All rights reserved.

Developing screening services for colorectal cancer on Android smartphones.

PubMed

Wu, Hui-Ching; Chang, Chiao-Jung; Lin, Chun-Che; Tsai, Ming-Chang; Chang, Che-Chia; Tseng, Ming-Hseng

2014-08-01

Colorectal cancer (CRC) is an important health problem in Western countries and also in Asia. It is the third leading cause of cancer deaths in both men and women in Taiwan. According to the well-known adenoma-to-carcinoma sequence, the majority of CRC develops from colorectal adenomatous polyps. This concept provides the rationale for screening and prevention of CRC. Removal of colorectal adenoma could reduce the mortality and incidence of CRC. Mobile phones are now playing an ever more crucial role in people's daily lives. The latest generation of smartphones is increasingly viewed as hand-held computers rather than as phones, because of their powerful on-board computing capability, capacious memories, large screens, and open operating systems that encourage development of applications (apps). If we can detect the potential CRC patients early and offer them appropriate treatments and services, this would not only promote the quality of life, but also reduce the possible serious complications and medical costs. In this study, an intelligent CRC screening app on Android™ (Google™, Mountain View, CA) smartphones has been developed based on a data mining approach using decision tree algorithms. For comparison, the stepwise backward multivariate logistic regression model and the fecal occult blood test were also used. Compared with the stepwise backward multivariate logistic regression model and the fecal occult blood test, the proposed app system not only provides an easy and efficient way to quickly detect high-risk groups of potential CRC patients, but also brings more information about CRC to customer-oriented services. We developed and implemented an app system on Android platforms for ubiquitous healthcare services for CRC screening. It can assist people in achieving early screening, diagnosis, and treatment purposes, prevent the occurrence of complications, and thus reach the goal of preventive medicine.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

[Relationship between emotional labor and job-related stress among hospital nurses].

PubMed

Katayama, Harumi

2010-09-01

To clarify the effects of factors of emotional labor, defined as the suppression of own emotions to better maintain other peoples' emotional conditions, on job-related stress responses among hospital nurses, the relationship between emotional labor and job-related stress was analyzed. A self-reported questionnaire was distributed among 147 nurses of five hospitals in Japan. Complete answers were collected from 123 nurses (83.7%, 107 females and 16 males). Emotional labor was assessed by the Emotional Labor Inventory for Nurses (ELIN) (26 items), which consisted of five subscales, i.e., "suppressed expression," "surface adjustment," "deep adjustment," "exploring and understanding" and "expression on caring." Job-related stress was evaluated using the Brief Job Stress Questionnaire (BSQ) consisting of 57 items. Stepwise multiple regression analysis was performed to examine the relationships of stress responses (BSQ) with ELIN and job stressors (BSQ). Subjects working in an inpatient department showed significantly higher total ELIN scores than those working in an outpatient department. The stepwise multiple regression analysis showed the following: Scores on "anger" and "fatigue" in BSQ positively related to "suppressed expression" scores in ELIN; those on "anxiety" positively related to "deep adjustment" scores; and those on "depression" positively related to "surface adjustment" scores. Similarly, scores on negative stress responses (BSQ) such as "anger," "fatigue," "anxiety," "depression," and "somatic stress responses" positively related to scores on job stressors (BSQ), e.g., physical work load, whereas "vigor" scores positively related to "job worthwhileness" in BSQ. The aspects of "suppressed expression," "deep adjustment," and "surface adjustment" of emotional labor seem to be the major occupational stressors for nurses, as well as job-related stressors measured by BSQ. Working in an inpatient department appears to be a potent stressor for nurses.

The influence of urban heat island phenomenon on PM concentration: an observation study during the summer half-year in metropolitan Taipei, Taiwan

NASA Astrophysics Data System (ADS)

Lai, Li-Wei

2018-01-01

Air circulation due to the urban heat island (UHI) effect can influence the dispersion of air pollutants in a metropolis. This study focusses on the influence of the UHI effect on particulate matter (PM; including PM2.5 and PM2.5-10) between May and September 2010-2012 in the Taipei basin. Meteorological and PM data were obtained from the sites, owned by the governmental authorities. The analysis was carried out using t test, relative indices (RIs), Pearson product-moment correlation and stepwise regression. The results show that the RI values for PM were the highest at moderate UHI intensity (MUI; 2 °C ≤ UHI < 4 °C) rather than at strong UHI intensity (SUI; 4 °C ≤ UHI) during the peak time for anthropogenic emissions (20:00 LST). Neither the accumulation of PM nor the surface convergence occurred in the hot centre, as shown by the case study. At MUI, more than 89 % of the synoptic weather patterns showed that the weather was clear and hot or that the atmosphere was stable. The variation in PM was associated with horizontal and vertical air dispersion. Poor horizontal air dispersion, with subsidence, caused an increase in PM at MUI. However, the updraft motion diluted the PM at SUI. The stepwise regression models show that the cloud index and surface air pressure determined the variation in PM2.5-10, while cloud index, wind speed and mixing height influenced the variation in PM2.5. In conclusion, a direct relationship between UHI effect and PM was not obvious.

Suicidal Ideation and Schizophrenia: Contribution of Appraisal, Stigmatization, and Cognition

PubMed Central

Stip, Emmanuel; Caron, Jean; Tousignant, Michel

2017-01-01

Objective: To predict suicidal ideation in people with schizophrenia, certain studies have measured its relationship with the variables of defeat and entrapment. The relationships are positive, but their interactions remain undefined. To further their understanding, this research sought to measure the relationship between suicidal ideation with the variables of loss, entrapment, and humiliation. Method: The convenience sample included 30 patients with schizophrenia spectrum disorders. The study was prospective (3 measurement times) during a 6-month period. Results were analyzed by stepwise multiple regression. Results: The contribution of the 3 variables to the variance of suicidal ideation was not significant at any of the 3 times (T1: 16.2%, P = 0.056; T2: 19.9%, P = 0.117; T3: 11.2%, P = 0.109). Further analyses measured the relationship between the variables of stigmatization, perceived cognitive dysfunction, symptoms, depression, self-esteem, reason to live, spirituality, social provision, and suicidal ideation. Stepwise multiple regression demonstrated that the contribution of the variables of stigmatization and perceived cognitive dysfunction to the variance of suicidal ideation was significant at all 3 times (T1: 41.7.5%, P = 0.000; T2: 35.2%, P = 0.001; T3: 21.5%, P = 0.012). Yet, over time, the individual contribution of the variables changed: T1, stigmatization (β = 0.518; P = 0.002); T2, stigmatization (β = 0.394; P = 0.025) and perceived cognitive dysfunction (β = 0.349; P = 0.046). Then, at T3, only perceived cognitive dysfunction contributed significantly to suicidal ideation (β = 0.438; P = 0.016). Conclusion: The results highlight the importance of the contribution of the variables of perceived cognitive dysfunction and stigmatization in the onset of suicidal ideation in people with schizophrenia spectrum disorders. PMID:28673099

Correlation of P-wave dispersion with insulin sensitivity in obese adolescents.

PubMed

Sert, Ahmet; Aslan, Eyup; Buyukınan, Muammer; Pirgon, Ozgur

2017-03-01

P-wave dispersion is a new and simple electrocardiographic marker that has been reported to be associated with inhomogeneous and discontinuous propagation of sinus impulses. In the present study, we evaluated P-wave dispersion in obese adolescents and investigated the relationship between P-wave dispersion, cardiovascular risk factors, and echocardiographic parameters. We carried out a case-control study comparing 150 obese adolescents and 50 healthy controls. Maximum and minimum P-wave durations were measured using a 12-lead surface electrocardiogram, and P-wave dispersion was calculated as the difference between these two measures. Echocardiographic examination was also performed for each subject. Multivariate linear regression analysis with stepwise variable selection was used to evaluate parameters associated with increased P-wave dispersion in obese subjects. Maximum P-wave duration and P-wave dispersion were significantly higher in obese adolescents than control subjects (143±19 ms versus 117±20 ms and 49±15 ms versus 29±9 ms, p<0.0001 for both). P-wave dispersion was positively correlated with body mass index, waist and hip circumferences, systolic and diastolic blood pressures, total cholesterol, serum levels of low-density lipoprotein cholesterol, triglycerides, glucose, and insulin, homoeostasis model assessment for insulin resistance score, left ventricular mass, and left atrial dimension. P-wave dispersion was negatively correlated with high-density lipoprotein cholesterol levels. By multiple stepwise regression analysis, left atrial dimension (β: 0.252, p=0.008) and homoeostasis model assessment for insulin resistance (β: 0.205; p=0.009) were independently associated with increased P-wave dispersion in obese adolescents. Insulin resistance is a significant, independent predictor of P-wave dispersion in obese adolescents.

Masticatory performance and oral health-related quality of life before and after complete denture treatment.

PubMed

Yamamoto, Saori; Shiga, Hiroshi

2018-03-13

To clarify the relationship between masticatory performance and oral health-related quality of life (OHRQoL) before and after complete denture treatment. Thirty patients wearing complete dentures were asked to chew a gummy jelly on their habitual chewing side, and the amount of glucose extraction during chewing was measured as the parameter of masticatory performance. Subjects were asked to answer the Oral Health Impact Profile (OHIP-J49) questionnaire, which consists of 49 questions related to oral problems. The total score of 49 question items along with individual domain scores within the seven domains (functional limitation, pain, psychological discomfort, physical disability, psychological disability, social disability and handicap) were calculated and used as the parameters of OHRQoL. These records were obtained before treatment and 3 months after treatment. Each parameter of masticatory performance and OHRQoL was compared before treatment and after treatment. The relationship between masticatory performance and OHRQoL was investigated, and a stepwise multiple linear regression analysis was performed. Both masticatory performance and OHRQoL were significantly improved after treatment. Furthermore, masticatory performance was significantly correlated with some parameters of OHRQoL. The stepwise multiple linear regression analysis showed functional limitation and pain as important factors affecting masticatory performance before treatment and functional limitation as important factors affecting masticatory performance after treatment. These results suggested that masticatory performance and OHRQoL are significantly improved after treatment and that there is a close relationship between the two. Moreover, functional limitation was found to be the most important factor affecting masticatory performance. Copyright © 2018 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Study on the social adaptation of Chinese children with down syndrome.

PubMed

Wang, Yan-Xia; Mao, Shan-Shan; Xie, Chun-Hong; Qin, Yu-Feng; Zhu, Zhi-Wei; Zhan, Jian-Ying; Shao, Jie; Li, Rong; Zhao, Zheng-Yan

2007-06-30

To evaluate social adjustment and related factors among Chinese children with Down syndrome (DS). A structured interview and Peabody Picture Vocabulary Test (PPVT) were conducted with a group of 36 DS children with a mean age of 106.28 months, a group of 30 normally-developing children matched for mental age (MA) and a group of 40 normally-developing children matched for chronological age (CA). Mean scores of social adjustment were compared between the three groups, and partial correlations and stepwise multiple regression models were used to further explore related factors. There was no difference between the DS group and the MA group in terms of communication skills. However, the DS group scored much better than the MA group in self-dependence, locomotion, work skills, socialization and self-management. Children in the CA group achieved significantly higher scores in all aspects of social adjustment than the DS children. Partial correlations indicate a relationship between social adjustment and the PPVT raw score and also between social adjustment and age (significant r ranging between 0.24 and 0.92). A stepwise linear regression analysis showed that family structure was the main predictor of social adjustment. Newborn history was also a predictor of work skills, communication, socialization and self-management. Parental education was found to account for 8% of self-dependence. Maternal education explained 6% of the variation in locomotion. Although limited by the small sample size, these results indicate that Chinese DS children have better social adjustment skills when compared to their mental-age-matched normally-developing peers, but that the Chinese DS children showed aspects of adaptive development that differed from Western DS children. Analyses of factors related to social adjustment suggest that effective early intervention may improve social adaptability.

[Prevalence of respiratory syncytial virus infection in hospitalized children at a children's hospital and effects of climate change on the prevalence in Suzhou, China].

PubMed

Geng, Jia; Guo, Wan-Liang; Zhang, Xue-Lan

2015-05-01

To investigate the prevalence of respiratory syncytial virus (RSV) infection in hospitalized children and the relationship between the prevalence and the climate change in Suzhou, China. A total of 42 664 nasopharyngeal secretions from hospitalized children with acute respiratory infection at the Suzhou Children's Hospital were screened for RSV antigens using direct immunofluorescence. Monthly meteorological data (mean monthly air temperature, monthly relative humidity, monthly rainfall, total monthly sunshine duration, and mean monthly wind velocity) in Suzhou between 2001 and 2011 were collected. The correlations between RSV detection rate and climatic factors were evaluated using correlation and stepwise regression analysis. The annual RSV infection rate in hospitalized children with respiratory infection in the Suzhou Children's Hospital varied between 11.85% and 27.30% from 2001 to 2011. In the 9 epidemic seasons, each spanning from November to April of the next year, from 2001 to 2010, the RSV detection rates were 40.75%, 22.72%, 39.93%, 27.37%, 42.71%, 21.28%, 38.57%, 19.86%, and 29.73%, respectively; there were significant differences in the detection rate between the epidemic seasons. The monthly RSV detection rate was negatively correlated with mean monthly air temperature, total monthly sunshine duration, monthly rainfall, monthly relative humidity, and mean monthly wind velocity (P<0.05). Stepwise regression analysis showed that mean monthly air temperature fitted into a linear model (R(2)=0.64, P<0.01). From 2001 to 2011, RSV infection in Suzhou was predominantly prevalent between November and April of the next year. As a whole, the infection rate of RSV reached a peak every other year. Air temperature played an important role in the epidemics of RSV infection in Suzhou.

What makes patients with fibromyalgia feel better? Correlations between Patient Global Impression of Improvement and changes in clinical symptoms and function: a pooled analysis of 4 randomized placebo-controlled trials of duloxetine.

PubMed

Hudson, James I; Arnold, Lesley M; Bradley, Laurence A; Choy, Ernest H S; Mease, Philip J; Wang, Fujun; Ahl, Jonna; Wohlreich, Madelaine M

2009-11-01

To investigate the relationship between changes in clinical rating scale items and endpoint Patient Global Impression of Improvement (PGI-I). Data were pooled from 4 randomized, double-blind, placebo-controlled studies of duloxetine in patients with fibromyalgia (FM). Variables included in the analyses were those that assessed symptoms in FM domains of pain, fatigue, sleep, cognitive difficulties, emotional well-being, physical function, and impact on daily living. The association of endpoint PGI-I with changes from baseline in individual variables was assessed using Pearson product-moment correlations (r). Stepwise linear regression was used to identify those variables for which changes from baseline were statistically significant independent predictors of the endpoint PGI-I ratings. Changes in pain variables and interference of symptoms with the ability to work were highly correlated (r >or= 0.5 or r

Complex interaction between symptoms, social factors, and gender in social functioning in a community-dwelling sample of schizophrenia.

PubMed

Vila-Rodriguez, F; Ochoa, S; Autonell, J; Usall, J; Haro, J M

2011-12-01

Social functioning (SF) is the ultimate target aimed in treatment plans in schizophrenia, thus it is critical to know what are the factors that determine SF. Gender is a well-established variable influencing SF, yet it is not known how social variables and symptoms interact in schizophrenia patients. Furthermore, it remains unclear whether the interaction between social variables and symptoms is different in men compared to women. Our aim is to test whether social variables are better predictors of SF in community-dwelled individuals with schizophrenia, and whether men and women differ in how symptoms and social variables interact to impact SF. Community-dwelling individuals with schizophrenia (N = 231) were randomly selected from a register. Participants were assessed with symptom measures (PANSS), performance-based social scale (LSP), objective social and demographic variables. Stratification by gender and stepwise multivariate regression analyses by gender were used to find the best-fitting models that predict SF in both gender. Men had poorer SF than women in spite of showing similar symptom scores. On stepwise regression analyses, gender was the main variable explaining SF, with a significant contribution by disorganized and excitatory symptoms. Age of onset made a less marked, yet significant, contribution to explain SF. When the sample was stratified by gender, disorganized symptoms and 'Income' variable entered the model and accounted for a 30.8% of the SF variance in women. On the other hand, positive and disorganized symptoms entered the model and accounted for a 36.1% of the SF variance in men. Community-dwelling men and women with schizophrenia differ in the constellation of variables associated with SF. Symptom scores still account for most of the variance in SF in both genders.

Quantifying Training Loads in Contemporary Dance.

PubMed

Jeffries, Annie C; Wallace, Lee; Coutts, Aaron J

2017-07-01

To describe the training demands of contemporary dance and determine the validity of using the session rating of perceived exertion (sRPE) to monitor exercise intensity and training load in this activity. In addition, the authors examined the contribution of training (ie, accelerometry and heart rate) and non-training-related factors (ie, sleep and wellness) to perceived exertion during dance training. Training load and ActiGraphy for 16 elite amateur contemporary dancers were collected during a 49-d period, using heart-rate monitors, accelerometry, and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and several other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during dance training. Average weekly training load was 4283 ± 2442 arbitrary units (AU), monotony 2.13 ± 0.92 AU, strain 10677 ± 9438 AU, and average weekly vector magnitude load 1809,707 ± 1015,402 AU. There were large to very large within-individual correlations between training-load sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 49.7% of the adjusted variance in training-load sRPE was explained by peak heart rate, metabolic equivalents, soreness, motivation, and sleep quality (y = -4.637 + 13.817%HR peak + 0.316 METS + 0.100 soreness + 0.116 motivation - 0.204 sleep quality). The current findings demonstrate the validity of the sRPE method for quantifying training load in dance, that dancers undertake very high training loads, and a combination of training and nontraining factors contribute to perceived exertion in dance training.

Factors affecting Korean nursing student empowerment in clinical practice.

PubMed

Ahn, Yang-Heui; Choi, Jihea

2015-12-01

Understanding the phenomenon of nursing student empowerment in clinical practice is important. Investigating the cognition of empowerment and identifying predictors are necessary to enhance nursing student empowerment in clinical practice. To identify empowerment predictors for Korean nursing students in clinical practice based on studies by Bradbury-Jones et al. and Spreitzer. A cross-sectional design was used for this study. This study was performed in three nursing colleges in Korea, all of which had similar baccalaureate nursing curricula. Three hundred seven junior or senior nursing students completed a survey designed to measure factors that were hypothesized to influence nursing student empowerment in clinical practice. Data were collected from November to December 2011. Study variables included self-esteem, clinical decision making, being valued as a learner, satisfaction regarding practice with a team member, perception on professor/instructor/clinical preceptor attitude, and total number of clinical practice fields. Data were analyzed using stepwise multiple regression analyses. All of the hypothesized study variables were significantly correlated to nursing student empowerment. Stepwise multiple regression analysis revealed that clinical decision making in nursing (t=7.59, p<0.001), being valued as a learner (t=6.24, p<0.001), self-esteem (t=3.62, p<0.001), and total number of clinical practice fields (t=2.06, p=0.040). The explanatory power of these predictors was 35% (F=40.71, p<0.001). Enhancing nursing student empowerment in clinical practice will be possible by using educational strategies to improve nursing student clinical decision making. Simultaneously, attitudes of nurse educators are also important to ensure that nursing students are treated as valued learners and to increase student self-esteem in clinical practice. Finally, diverse clinical practice field environments should be considered to enhance experience. Copyright © 2015 Elsevier Ltd. All rights reserved.

Overgeneral autobiographical memory in patients with chronic pain.

PubMed

Liu, Xianhua; Liu, Yanling; Li, Li; Hu, Yiqiu; Wu, Siwei; Yao, Shuqiao

2014-03-01

Overgenerality and delay of the retrieval of autobiographical memory (AM) are well documented in a range of clinical conditions, particularly in patients with emotional disorder. The present study extended the investigation to chronic pain, attempting to identify whether the retrieval of AM in patients with chronic pain tends to be overgeneral or delayed. With an observational cross-sectional design, we evaluated the AM both in patients with chronic pain and healthy controls by Autobiographical Memory Test. Pain conditions were assessed using the pain diagnostic protocol, the short-form McGill Pain Questionnaire (SF-MPQ), and the Pain Self-Efficacy Questionnaire (PSEQ). Emotion was assessed using the Beck Depression Inventory-II (BDI-II) and the Beck Anxiety Inventory. Subjects included 176 outpatients with chronic pain lasting for at least 6 months and 170 healthy controls. 1) Compared with the healthy group, the chronic pain group had more overgeneral memories (OGMs) (F = 29.061, P < 0.01) and longer latency (F = 13.602, P < 0.01). 2) In the chronic pain group, the stepwise multiple regression models for variables predicting OGM were significant (P < 0.01). Specifically, the variance in OGM scores could be predicted by the BDI score (9.7%), pain chronicity (4.3%), PSEQ score (7.1%), and Affective Index (of SF-MPQ) score (2.7%). 3) In the chronic pain group, the stepwise multiple regression models for variables predicting latency were significant (P < 0.05). Specifically, the variance in latency could be predicted by age (3.1%), pain chronicity (2.7%), pain duration (4.3%), and PSEQ score (2.0%). The retrieval of AM in patients with chronic pain tends to be overgeneral and delayed, and the retrieval style of AM may be contributed to negative emotions and chronic pain conditions. Wiley Periodicals, Inc.

Heart rate dynamics during cardio-pulmonary exercise testing are associated with glycemic control in individuals with type 1 diabetes.

PubMed

Moser, Othmar; Eckstein, Max L; McCarthy, Olivia; Deere, Rachel; Bain, Stephen C; Haahr, Hanne L; Zijlstra, Eric; Heise, Tim; Bracken, Richard M

2018-01-01

This study investigated the degree and direction (kHR) of the heart rate to performance curve (HRPC) during cardio-pulmonary exercise (CPX) testing and explored the relationship with diabetes markers, anthropometry and exercise physiological markers in type 1 diabetes (T1DM). Sixty-four people with T1DM (13 females; age: 34 ± 8 years; HbA1c: 7.8 ± 1% (62 ± 13 mmol.mol-1) performed a CPX test until maximum exhaustion. kHR was calculated by a second-degree polynomial representation between post-warm up and maximum power output. Adjusted stepwise linear regression analysis was performed to investigate kHR and its associations. Receiver operating characteristic (ROC) curve was performed based on kHR for groups kHR < 0.20 vs. > 0.20 in relation to HbA1c. We found significant relationships between kHR and HbA1c (β = -0.70, P < 0.0001), age (β = -0.23, P = 0.03) and duration of diabetes (β = 0.20, P = 0.04). Stepwise linear regression resulted in an overall adjusted R2 of 0.57 (R = 0.79, P < 0.0001). Our data revealed also significant associations between kHR and percentage of heart rate at heart rate turn point from maximum heart rate (β = 0.43, P < 0.0001) and maximum power output relativized to bodyweight (β = 0.44, P = 0.001) (overall adjusted R2 of 0.44 (R = 0.53, P < 0.0001)). ROC curve analysis based on kHR resulted in a HbA1c threshold of 7.9% (62 mmol.mol-1). Our data demonstrate atypical HRPC during CPX testing that were mainly related to glycemic control in people with T1DM.

The left hand second to fourth digit ratio (2D:4D) is not related to any physical fitness component in adolescent girls.

PubMed

Peeters, Maarten W; Van Aken, Katrijn; Claessens, Albrecht L

2013-01-01

The second to fourth-digit-ratio (2D:4D), a putative marker of prenatal androgen action and a sexually dimorphic trait, has been suggested to be related with fitness and sports performance, although results are not univocal. Most studies however focus on a single aspect of physical fitness or one sports discipline. In this study the 2D:4D ratio of 178 adolescent girls (age 13.5-18 y) was measured on X-rays of the left hand. The relation between 2D:4D digit ratio and multiple aspects of physical fitness (balance, speed of limb movement, flexibility, explosive strength, static strength, trunk strength, functional strength, running speed/agility, and endurance) was studied by correlation analyses and stepwise multiple regression. For comparison the relation between these physical fitness components and a selected number of objectively measured anthropometric traits (stature, mass, BMI, somatotype components and the Bayer & Bailey androgyny index) are presented alongside the results of 2D:4D digit ratio. Left hand 2D:4D digit ratio (0.925±0.019) was not significantly correlated with any of the physical fitness components nor any of the anthropometric variables included in the present study. 2D:4D did not enter the multiple stepwise regression for any of the physical fitness components in which other anthropometric traits explained between 9.2% (flexibility) and 33.9% (static strength) of variance. Unlike other anthropometric traits the 2D:4D digit ratio does not seem to be related to any physical fitness component in adolescent girls and therefore most likely should not be considered in talent detection programs for sporting ability in girls.

Ethnic differences in colon cancer care in the Netherlands: a nationwide registry-based study.

PubMed

Lamkaddem, M; Elferink, M A G; Seeleman, M C; Dekker, E; Punt, C J A; Visser, O; Essink-Bot, M L

2017-05-04

Ethnic differences in colon cancer (CC) care were shown in the United States, but results are not directly applicable to European countries due to fundamental healthcare system differences. This is the first study addressing ethnic differences in treatment and survival for CC in the Netherlands. Data of 101,882 patients diagnosed with CC in 1996-2011 were selected from the Netherlands Cancer Registry and linked to databases from Statistics Netherlands. Ethnic differences in lymph node (LN) evaluation, anastomotic leakage and adjuvant chemotherapy were analysed using stepwise logistic regression models. Stepwise Cox regression was used to examine the influence of ethnic differences in adjuvant chemotherapy on 5-year all-cause and colorectal cancer-specific survival. Adequate LN evaluation was significantly more likely for patients from 'other Western' countries than for the Dutch (OR 1.09; 95% CI 1.01-1.16). 'Other Western' patients had a significantly higher risk of anastomotic leakage after resection (OR 1.24; 95% CI 1.05-1.47). Patients of Moroccan origin were significantly less likely to receive adjuvant chemotherapy (OR 0.27; 95% CI 0.13-0.59). Ethnic differences were not fully explained by differences in socioeconomic and hospital-related characteristics. The higher 5-year all-cause mortality of Moroccan patients (HR 1.64; 95% CI 1.03-2.61) was statistically explained by differences in adjuvant chemotherapy receipt. These results suggest the presence of ethnic inequalities in CC care in the Netherlands. We recommend further analysis of the role of comorbidity, communication in patient-provider interaction and patients' health literacy when looking at ethnic differences in treatment for CC.

Quality of life in children with infantile hemangioma: a case control study.

PubMed

Wang, Chuan; Li, Yanan; Xiang, Bo; Xiong, Fei; Li, Kai; Yang, Kaiying; Chen, Siyuan; Ji, Yi

2017-11-16

Infantile hemangioma (IH) is the most common vascular tumor in children. It is controversial whether IHs has effects on the quality of life (QOL) in patients of whom IH poses no threat or potential for complication. Thus, we conducted this study to evaluate the q QOL in patients with IH and find the predictors of poor QOL. The PedsQL 4.0 Genetic Core Scales and the PedsQL family information form were administered to parents of children with IH and healthy children both younger than 2-year-old. The quality-of-life instrument for IH (IH-QOL) and the PedsQL 4.0 family impact module were administered to parents of children with IH. We compared the PedsQL 4.0 Genetic Core Scales (GCIS) scores of the two groups. Multiple step-wise regression analysis was used to determine factors that influenced QOL in children with IH and their parents. Except for physical symptom, we found no significant difference in GCIS between patient group and healthy group (P = 0.409). The internal reliability of IH-QOL was excellent with the Cronbach's alpha coefficient for summary scores being 0.76. Multiple step-wise regression analysis showed that the predictors of poor IH-QOL total scores were hemangioma size, location, and mother's education level. The predictors of poor FIM total scores were hemangioma location and father's education level. The predictors of poor GCIS total scores were children's age, hemangioma location and father's education level. The findings support the feasibility and reliability of the Chinese version of IH-QOL to evaluate the QOL in children with IH and their parents. Hemangioma size, location and education level of mother are important impact factors for QOL in children with IH and their parents.

Lifestyle and health-related quality of life: a cross-sectional study among civil servants in China.

PubMed

Xu, Jun; Qiu, Jincai; Chen, Jie; Zou, Liai; Feng, Liyi; Lu, Yan; Wei, Qian; Zhang, Jinhua

2012-05-04

Health-related quality of life (HRQoL) has been increasingly acknowledged as a valid and appropriate indicator of public health and chronic morbidity. However, limited research was conducted among Chinese civil servants owing to the different lifestyle. The aim of the study was to evaluate the HRQoL among Chinese civil servants and to identify factors might be associated with their HRQoL. A cross-sectional study was conducted to investigate HRQoL of 15,000 civil servants in China using stratified random sampling methods. Independent-Samples t-Test, one-way ANOVA, and multiple stepwise regression were used to analyse the influencing factors and the HRQoL of the civil servants. A univariate analysis showed that there were significant differences among physical component summary (PCS), mental component summary (MCS), and TS between lifestyle factors, such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness (P < 0.05). Multiple stepwise regressions showed that there were significant differences among TS between lifestyle factors, such as breakfast, sleep time, physical exercise, operating computers, sedentariness, work time, and drinking (P < 0.05). In this study, using Short Form 36 items (SF-36), we assessed the association of HRQoL with lifestyle factors, including smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness in China. The performance of the questionnaire in the large-scale survey is satisfactory and provides a large picture of the HRQoL status in Chinese civil servants. Our results indicate that lifestyle factors such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness affect the HRQoL of civil servants in China.

Lifestyle and health-related quality of life: A cross-sectional study among civil servants in China

PubMed Central

2012-01-01

Background Health-related quality of life (HRQoL) has been increasingly acknowledged as a valid and appropriate indicator of public health and chronic morbidity. However, limited research was conducted among Chinese civil servants owing to the different lifestyle. The aim of the study was to evaluate the HRQoL among Chinese civil servants and to identify factors might be associated with their HRQoL. Methods A cross-sectional study was conducted to investigate HRQoL of 15,000 civil servants in China using stratified random sampling methods. Independent-Samples t-Test, one-way ANOVA, and multiple stepwise regression were used to analyse the influencing factors and the HRQoL of the civil servants. Results A univariate analysis showed that there were significant differences among physical component summary (PCS), mental component summary (MCS), and TS between lifestyle factors, such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness (P < 0.05). Multiple stepwise regressions showed that there were significant differences among TS between lifestyle factors, such as breakfast, sleep time, physical exercise, operating computers, sedentariness, work time, and drinking (P < 0.05). Conclusion In this study, using Short Form 36 items (SF-36), we assessed the association of HRQoL with lifestyle factors, including smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness in China. The performance of the questionnaire in the large-scale survey is satisfactory and provides a large picture of the HRQoL status in Chinese civil servants. Our results indicate that lifestyle factors such as smoking, drinking alcohol, having breakfast, sleep time, physical exercise, work time, operating computers, and sedentariness affect the HRQoL of civil servants in China. PMID:22559315

Risk factors for aneurysmal subarachnoid hemorrhage in Aomori, Japan.

PubMed

Ohkuma, Hiroki; Tabata, Hidefumi; Suzuki, Shigeharu; Islam, Md Shafiqul

2003-01-01

Japan is known to have an incidence of aneurysmal subarachnoid hemorrhage (SAH) as high as that in Finland, where SAH is especially common. However, the risk factors for SAH in Japan are unknown. The purpose of this study was to identify the risk factors and then examine their possible roles in cases of SAH in Japan. Case-control data were collected in the Aomori prefecture between June 2000 and May 2001 and in the Shimokita area between 1989 and 1998. A history of hypertension, cigarette smoking, alcohol consumption, hypercholesterolemia, and diabetes mellitus were examined as possible risk factors for SAH by using stepwise logistic regression analysis. Stepwise logistic regression analysis showed that a history of hypertension and current smoking increased the risk of SAH and that a history of hypercholesterolemia decreased the risk of SAH. Alcohol consumption and a history of diabetes mellitus were excluded from the model, because their log-likelihood ratios were not significant. The adjusted odds ratios, obtained by forcing matching factors, were 2.29 for a history of hypertension (95% CI, 1.66 to 3.16), 3.12 for current smoking (95% CI, 2.05 to 4.77), and 0.41 for a history of hypercholesterolemia (95% CI, 0.24 to 0.71). The prevalence of hypertension in control subjects was 27% in men and 31% in women, whereas the prevalence of cigarette smoking in control subjects was 46% in men and 9% in women. Hypertension and cigarette smoking seem to be independent risk factors for SAH in Japan. The high prevalence of hypertension in both sexes and the high prevalence of cigarette smoking in men in the general population might contribute to the high incidence of SAH in Japan.

Preoperative determinant of early postoperative renal function following radical cystectomy and intestinal urinary diversion.

PubMed

Gondo, Tatsuo; Ohno, Yoshio; Nakashima, Jun; Hashimoto, Takeshi; Nakagami, Yoshihiro; Tachibana, Masaaki

2017-02-01

To identify preoperative factors correlated with postoperative early renal function in patients who had undergone radical cystectomy (RC) and intestinal urinary diversion. We retrospectively identified 201 consecutive bladder cancer patients without distant metastasis who had undergone RC at our institution between 2003 and 2012. The estimated glomerular filtration rate (eGFR) was calculated using the modified Chronic Kidney Disease Epidemiology equation before RC and 3 months following RC. Univariate and stepwise multiple linear regression analyses were applied to estimate postoperative renal function and to identify significant preoperative predictors of postoperative renal function. Patients who had undergone intestinal urinary diversion and were available for the collection of follow-up data (n = 164) were eligible for the present study. Median preoperative and postoperative eGFRs were 69.7 (interquartile range [IQR] 56.3-78.0) and 70.7 (IQR 57.3-78.1), respectively. In univariate analyses, age, preoperative proteinuria, thickness of abdominal subcutaneous fat tissue (TSF), preoperative serum creatinine level, preoperative eGFR, and urinary diversion type were significantly associated with postoperative eGFR. In a stepwise multiple linear regression analysis, preoperative eGFR, age, and TSF were significant factors for predicting postoperative eGFR (p < 0.001, p = 0.02, and p = 0.046, respectively). The estimated postoperative eGFRs correlated well with the actual postoperative eGFRs (r = 0.65, p < 0.001). Preoperative eGFR, age, and TSF were independent preoperative factors for determining postoperative renal function in patients who had undergone RC and intestinal urinary diversion. These results may be used for patient counseling before surgery, including the planning of perioperative chemotherapy administration.

Resilience and Associated Factors among Mainland Chinese Women Newly Diagnosed with Breast Cancer.

PubMed

Wu, Zijing; Liu, Ye; Li, Xuelian; Li, Xiaohan

2016-01-01

Resilience is the individual's ability to bounce back from trauma. It has been studied for some time in the U.S., but few studies in China have addressed this important construct. In mainland China, relatively little is known about the resilience of patients in clinical settings, especially among patients with breast cancer. In this study, we aimed to evaluate the level of resilience and identify predictors of resilience among mainland Chinese women newly diagnosed with breast cancer. A cross-sectional descriptive study was conducted with 213 mainland Chinese women newly diagnosed with breast cancer between November 2014 and June 2015. Participants were assessed with the Connor-Davidson Resilience Scale (CD-RISC), Social Support Rating Scale (SSRS), Medical Coping Modes Questionnaire (MCMQ, including 3 subscales: confrontation, avoidance, and acceptance-resignation), Herth Hope Index (HHI), and demographic and disease-related information. Descriptive statistics, bivariate analyses and multiple stepwise regression were conducted to explore predictors for resilience. The average score for CD-RISC was 60.97, ranging from 37 to 69. Resilience was positively associated with educational level, family income, time span after diagnosis, social support, confrontation, avoidance, and hope. However, resilience was negatively associated with age, body mass index (BMI), and acceptance-resignation. Multiple stepwise regression analysis indicated that hope (β = 0.343, P<0.001), educational level of junior college or above (β = 0.272, P<0.001), educational level of high school (β = 0.235, P<0.001), avoidance (β = 0.220, P<0.001), confrontation (β = 0.187, P = 0.001), and age (β = -0.108, P = 0.037) significantly affected resilience and explained 50.1% of the total variance in resilience. Women with newly diagnosed breast cancer from mainland China demonstrated particularly low resilience level, which was predicted by hope educational level, avoidance, confrontation, and age.

The self-perception of dyspnoea threshold during the 6-min walk test: a good alternative to estimate the ventilatory threshold in chronic obstructive pulmonary disease.

PubMed

Couillard, Annabelle; Tremey, Emilie; Prefaut, Christian; Varray, Alain; Heraud, Nelly

2016-12-01

To determine and/or adjust exercise training intensity for patients when the cardiopulmonary exercise test is not accessible, the determination of dyspnoea threshold (defined as the onset of self-perceived breathing discomfort) during the 6-min walk test (6MWT) could be a good alternative. The aim of this study was to evaluate the feasibility and reproducibility of self-perceived dyspnoea threshold and to determine whether a useful equation to estimate ventilatory threshold from self-perceived dyspnoea threshold could be derived. A total of 82 patients were included and performed two 6MWTs, during which they raised a hand to signal self-perceived dyspnoea threshold. The reproducibility in terms of heart rate (HR) was analysed. On a subsample of patients (n=27), a stepwise regression analysis was carried out to obtain a predictive equation of HR at ventilatory threshold measured during a cardiopulmonary exercise test estimated from HR at self-perceived dyspnoea threshold, age and forced expiratory volume in 1 s. Overall, 80% of patients could identify self-perceived dyspnoea threshold during the 6MWT. Self-perceived dyspnoea threshold was reproducibly expressed in HR (coefficient of variation=2.8%). A stepwise regression analysis enabled estimation of HR at ventilatory threshold from HR at self-perceived dyspnoea threshold, age and forced expiratory volume in 1 s (adjusted r=0.79, r=0.63, and relative standard deviation=9.8 bpm). This study shows that a majority of patients with chronic obstructive pulmonary disease can identify a self-perceived dyspnoea threshold during the 6MWT. This HR at the dyspnoea threshold is highly reproducible and enable estimation of the HR at the ventilatory threshold.

The association between insured male expatriates' knowledge of health insurance benefits and lack of access to health care in Saudi Arabia.

PubMed

Alkhamis, Abdulwahab A

2018-03-15

Insufficient knowledge of health insurance benefits could be associated with lack of access to health care, particularly for minority populations. This study aims to assess the association between expatriates' knowledge of health insurance benefits and lack of access to health care. A cross-sectional study design was conducted from March 2015 to February 2016 among 3398 insured male expatriates in Riyadh, Saudi Arabia. The dependent variable was binary and expresses access or lack of access to health care. Independent variables included perceived and validated knowledge of health insurance benefits and other variables. Data were summarized by computing frequencies and percentage of all quantities of variables. To evaluate variations in knowledge, personal and job characteristics with lack of access to health care, the Chi square test was used. Odds ratio (OR) and 95% confidence interval (CI) were recorded for each independent variable. Multiple logistic regression and stepwise logistic regression were performed and adjusted ORs were extracted. Descriptive analysis showed that 15% of participants lacked access to health care. The majority of these were unskilled laborers, usually with no education (17.5%), who had been working for less than 3 years (28.1%) in Saudi Arabia. A total of 23.3% worked for companies with less than 50 employees and 16.5% earned less than 4500 Saudi Riyals monthly ($1200). Many (20.3%) were young (< 30 years old) or older (17.9% ≥ 56 years old) and had no formal education (24.7%). Nearly half had fair or poor health status (49.5%), were uncomfortable conversing in Arabic (29.7%) or English (16.7%) and lacked previous knowledge of health insurance (18%). For perceived knowledge of health insurance, 55.2% scored 1 or 0 from total of 3. For validated knowledge, 16.9% scored 1 or 0 from total score of 4. Multiple logistic regression analysis showed that only perceived knowledge of health insurance had significant associations with lack of access to health care ((OR) = 0.393, (CI) = 0.335-0.461), but the result was insignificant for validated knowledge. Stepwise logistic regression gave similar findings. Our results confirmed that low perceived knowledge of health insurance in expatriates was associated with less access to health care.

Stepwise pumping approach to improve free phase light hydrocarbon recovery from unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

1995-04-01

A stepwise, time-varying pumping approach is developed to improve free phase oil recovery of light non-aqueous phase liquids (LNAPL) from a homogeneous, unconfined aquifer. Stepwise pumping is used to contain the floating oil plume and obtain efficient free oil recovery. The graphical plots. The approach uses ARMOS ©, an areal two-dimensional multiphase flow, finite-element simulation model. Systematic simulations of free oil area changes to pumping rates are analyzed. Pumping rates are determined that achieve LNAPL plume containment at different times (i.e. 90, 180 and 360 days) for a planning period of 360 days. These pumping rates are used in reverse order as a stepwise (monotonically increasing) pumping strategy. This stepwise pumping strategy is analyzed further by performing additional simulations at different pumping rates for the last pumping period. The final stepwise pumping strategy is varied by factors of -25% and +30% to evaluate sensitivity in the free oil recovery process. Stepwise pumping is compared to steady pumping rates to determine the best free oil recovery strategy. Stepwise pumping is shown to improve oil recovery by increasing recoveredoil volume (11%) and decreasing residual oil (15%) when compared with traditional steady pumping strategies. The best stepwise pumping strategy recovers more free oil by reducing the amount of residual oil left in the system due to pumping drawdown. This stepwise pumping pproach can be used to enhance free oil recovery and provide for cost-effective design and management of LNAPL cleanup.

Efficacy and Safety of a Novel Three-Step Medial Release Technique in Varus Total Knee Arthroplasty.

PubMed

Kim, Min Woo; Koh, In Jun; Kim, Ju Hwan; Jung, Jae Jong; In, Yong

2015-09-01

We investigated the efficacy and safety of our novel three-step medial release technique in varus total knee arthroplasty (TKA) over time. Two hundred sixty seven consecutive varus TKAs were performed by applying the algorithmic release technique which consisted of sequential release of the deep medial collateral ligament (step 1), the semimembranosus (step 2), and multiple needle puncturing of the superficial medial collateral ligament (step 3). One hundred seventeen, 114, and 36 knees were balanced after step 1, 2, and 3 releases, respectively. There were no significant differences in changes of medial and lateral laxities between groups in over a year. Our novel stepwise medial release technique was efficacious and safe in balancing varus knees during TKA. Copyright © 2015 Elsevier Inc. All rights reserved.

A technique for open trocar placement in laparoscopic surgery using the umbilical cicatrix tube.

PubMed

Lal, Pawanindra; Sharma, R; Chander, R; Ramteke, V K

2002-09-01

Increasingly the open method for placement of the initial or first trocar is replacing the conventional technique with the Veress needle. Indeed, it is preferred because it affords peritoneal access under direct vision. A number of methods have been described in the literature using a variety of approaches and different instruments. We describe a method of open trocar placement in the supra- or subumbilical region that follows a stepwise procedure and employs specific instruments sequentially, while utilizing the umbilical cicatrix pillar or tube. This technique has been done in 525 cases with no complications or port site hernias. This is a simple technique that is safe and easy to learn. It can be performed rapidly and is a reliable method for the insertion of the first port under vision.

An Investigation into the Roles of Theory of Mind, Emotion Regulation, and Attachment Styles in Predicting the Traits of Borderline Personality Disorder

PubMed Central

Ghiasi, Hamed; Mohammadi, Abolalfazl; Zarrinfar, Pouria

2016-01-01

Objective: Borderline personality disorder is one of the most complex and prevalent personality disorders. Many variables have so far been studied in relation to this disorder. This study aimed to investigate the role of emotion regulation, attachment styles, and theory of mind in predicting the traits of borderline personality disorder. Method: In this study, 85 patients with borderline personality disorder were selected using convenience sampling method. To measure the desired variables, the questionnaires of Gross emotion regulation, Collins and Read attachment styles, and Baron Cohen's Reading Mind from Eyes Test were applied. The data were analyzed using multivariate stepwise regression technique. Results: Emotion regulation, attachment styles, and theory of mind predicted 41.2% of the variance criterion altogether; among which, the shares of emotion regulation, attachment styles and theory of mind to the distribution of the traits of borderline personality disorder were 27.5%, 9.8%, and 3.9%, respectively.‎‎ Conclusion: The results of the study revealed that emotion regulation, attachment styles, and theory of mind are important variables in predicting the traits of borderline personality disorder and that these variables can be well applied for both the treatment and identification of this disorder. PMID:28050180

Analysis of swimming performance from physical, physiological, and biomechanical parameters in young swimmers.

PubMed

Jürimäe, Jaak; Haljaste, Kaja; Cicchella, Antonio; Lätt, Evelin; Purge, Priit; Leppik, Aire; Jürimäe, Toivo

2007-02-01

The purpose of this study was to examine the influence of the energy cost of swimming, body composition, and technical parameters on swimming performance in young swimmers. Twenty-nine swimmers, 15 prepubertal (11.9 +/- 0.3 years; Tanner Stages 1-2) and 14 pubertal (14.3 +/- 1.4 years; Tanner Stages 3-4) boys participated in the study. The energy cost of swimming (Cs) and stroking parameters were assessed over maximal 400-m front-crawl swimming in a 25-m swimming pool. The backward extrapolation technique was used to evaluate peak oxygen consumption (VO2peak). A stroke index (SI; m2 . s(-1) . cycles(-1)) was calculated by multiplying the swimming speed by the stroke length. VO2peak results were compared with VO2peak test in the laboratory (bicycle, 2.86 +/- 0.74 L/min, vs. in water, 2.53 +/- 0.50 L/min; R2 = .713; p = .0001). Stepwise-regression analyses revealed that SI (R2 = .898), in-water VO2peak (R2 = .358), and arm span (R2 = .454) were the best predictors of swimming performance. The backward-extrapolation method could be used to assess VO2peak in young swimmers. SI, arm span, and VO2peak appear to be the major determinants of front-crawl swimming performance in young swimmers.

New approaches for sampling and modeling native and exotic plant species richness

USGS Publications Warehouse

Chong, G.W.; Reich, R.M.; Kalkhan, M.A.; Stohlgren, T.J.

2001-01-01

We demonstrate new multi-phase, multi-scale approaches for sampling and modeling native and exotic plant species to predict the spread of invasive species and aid in control efforts. Our test site is a 54,000-ha portion of Rocky Mountain National Park, Colorado, USA. This work is based on previous research wherein we developed vegetation sampling techniques to identify hot spots of diversity, important rare habitats, and locations of invasive plant species. Here we demonstrate statistical modeling tools to rapidly assess current patterns of native and exotic plant species to determine which habitats are most vulnerable to invasion by exotic species. We use stepwise multiple regression and modified residual kriging to estimate numbers of native species and exotic species, as well as probability of observing an exotic species in 30 × 30-m cells. Final models accounted for 62% of the variability observed in number of native species, 51% of the variability observed in number of exotic species, and 47% of the variability associated with observing an exotic species. Important independent variables used in developing the models include geographical location, elevation, slope, aspect, and Landsat TM bands 1-7. These models can direct resource managers to areas in need of further inventory, monitoring, and exotic species control efforts.

An Investigation into the Roles of Theory of Mind, Emotion Regulation, and Attachment Styles in Predicting the Traits of Borderline Personality Disorder.

PubMed

Ghiasi, Hamed; Mohammadi, Abolalfazl; Zarrinfar, Pouria

2016-10-01

Objective: Borderline personality disorder is one of the most complex and prevalent personality disorders. Many variables have so far been studied in relation to this disorder. This study aimed to investigate the role of emotion regulation, attachment styles, and theory of mind in predicting the traits of borderline personality disorder. Method: In this study, 85 patients with borderline personality disorder were selected using convenience sampling method. To measure the desired variables, the questionnaires of Gross emotion regulation, Collins and Read attachment styles, and Baron Cohen's Reading Mind from Eyes Test were applied. The data were analyzed using multivariate stepwise regression technique. Results: Emotion regulation, attachment styles, and theory of mind predicted 41.2% of the variance criterion altogether; among which, the shares of emotion regulation, attachment styles and theory of mind to the distribution of the traits of borderline personality disorder were 27.5%, 9.8%, and 3.9%, respectively.‎‎ Conclusion : The results of the study revealed that emotion regulation, attachment styles, and theory of mind are important variables in predicting the traits of borderline personality disorder and that these variables can be well applied for both the treatment and identification of this disorder.

Characterizing Walk Trips in communities by Using Data from 2009 National Household Travel Survey, American Community Survey, and Other Sources

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

Hwang, Ho-Ling; Reuscher, Tim; Wilson, Daniel W

Non-motorized travel (i.e. walking and bicycling) are of increasing interest to the transportation profession, especially in context with energy consumption, reducing vehicular congestion, urban development patterns, and promotion of healthier life styles. This research project aimed to identify factors impacting the amount of travel for both walk and bike trips at the Census block group or tract level, using several public and private data sources. The key survey of travel behavior is the 2009 National Household Travel Survey (NHTS) which had over 87,000 walk trips for persons 16 and over, and over 6000 bike trips for persons 16 and over.more » The NHTS, in conjunction with the Census Bureau s American Community Survey, street density measures using Census Bureau TIGER, WalkScore , Nielsen Claritas employment estimates, and several other sources were used for this study. Stepwise Logistic Regression modeling techniques as well as Discriminant Analysis were applied using the integrated data set. While the models performed reasonably well for walk trips, travel by bike was abandoned due to sparseness of data. This paper discusses data sources utilized and modeling processes conducted under this study. It also presents a summary of findings and addresses data challenges and lesson-learned from this research effort.« less

Predictors of the Perception of Smoking Health Risks in Smokers With or Without Schizophrenia.

PubMed

Kowalczyk, William J; Wehring, Heidi J; Burton, George; Raley, Heather; Feldman, Stephanie; Heishman, Stephen J; Kelly, Deanna L

2017-01-01

This study sought to examine the predictors of health risk perception in smokers with or without schizophrenia. The health risk subscale from the Smoking Consequences Questionnaire was dichotomized and used to measure health risk perception in smokers with (n = 67) and without schizophrenia (n = 100). A backward stepwise logistic regression was conducted using variables associated at the bivariate level to determine multivariate predictors. Overall, 62.5% of smokers without schizophrenia and 40.3% of smokers with schizophrenia completely recognize the health risks of smoking (p ≤ .01). Multivariate predictors for smokers without schizophrenia included: sex (Exp (B) = .3; p < .05), Smoking Consequences Questionnaire state enhancement (Exp (B) = .69; p < .01), and craving relief (Exp (B) = 1.8; p < .01). Among smokers with schizophrenia, predictors were education (Exp (B) = .7; p < .05), nicotine dependence (Exp (B) = .5; p < .01), motivation to quit (Exp (B) = 1.8; p < .01), and Smoking Consequences Questionnaire craving relief (Exp (B) = 1.8; p < .01). There was overlap and differences between predictors in smokers with and without schizophrenia. Commonly used techniques for education on the health consequences of cigarettes may work in smokers with schizophrenia, but intervention efforts specifically tailored to smokers with schizophrenia might be more efficacious.

Predictors of the Perception of Smoking Health Risks in Smokers With or Without Schizophrenia

PubMed Central

Kowalczyk, William J.; Wehring, Heidi J.; Burton, George; Raley, Heather; Feldman, Stephanie; Heishman, Stephen J.; Kelly, Deanna L.

2017-01-01

Objective This study sought to examine the predictors of health risk perception in smokers with or without schizophrenia. Methods The health risk subscale from the Smoking Consequences Questionnaire was dichotomized and used to measure health risk perception in smokers with (n = 67) and without schizophrenia (n = 100). A backward stepwise logistic regression was conducted using variables associated at the bivariate level to determine multivariate predictors. Results Overall, 62.5% of smokers without schizophrenia and 40.3% of smokers with schizophrenia completely recognize the health risks of smoking (p ≤ .01). Multivariate predictors for smokers without schizophrenia included: sex (Exp (B) = .3; p < .05), Smoking Consequences Questionnaire state enhancement (Exp (B) = .69; p < .01), and craving relief (Exp (B) = 1.8; p < .01). Among smokers with schizophrenia, predictors were education (Exp (B) = .7; p < .05), nicotine dependence (Exp (B) = .5; p < .01), motivation to quit (Exp (B) = 1.8; p < .01), and Smoking Consequences Questionnaire craving relief (Exp (B) = 1.8; p < .01). Conclusions There was overlap and differences between predictors in smokers with and without schizophrenia. Commonly used techniques for education on the health consequences of cigarettes may work in smokers with schizophrenia, but intervention efforts specifically tailored to smokers with schizophrenia might be more efficacious. PMID:27858591

Nitrate-nitrogen contamination in groundwater: Spatiotemporal variation and driving factors under cropland in Shandong Province, China

NASA Astrophysics Data System (ADS)

Liu, J.; Jiang, L. H.; Zhang, C. J.; Li, P.; Zhao, T. K.

2017-08-01

High groundwater nitrate-N is a serious problem especially in highly active agricultural areas. In study, the concentration and spatialtemporal distribution of groundwater nitrate-N under cropland in Shandong province were assessed by statistical and geostatistical techniques. Nitrate-N concentration reached a maximum of 184.60 mg L-1 and 29.5% of samples had levels in excess of safety threshold concentration (20 mg L-1). The median nitrate-N contents after rainy season were significantly higher than those before rainy season, and decreased with increasing groundwater depth. Nitrate-N under vegetable and orchard area are significantly higher than ones under grain. The kriging map shows that groundwater nitrate-N has a strong spatial variability. Many districts, such as Weifang, Linyi in Shandong province are heavily contaminated with nitrate-N. However, there are no significant trends of NO3 --N for most cities. Stepwise regression analysis showed influencing factors are different for the groundwater in different depth. But overall, vegetable yield per unit area, percentages of orchard area, per capita agricultural production, unit-area nitrogen fertilizer, livestock per unit area, percentages of irrigation areas, population per unit area and annual mean temperature are significant variables for groundwater nitrate-N variation.

A statistical framework for applying RNA profiling to chemical hazard detection.

PubMed

Kostich, Mitchell S

2017-12-01

Use of 'omics technologies in environmental science is expanding. However, application is mostly restricted to characterizing molecular steps leading from toxicant interaction with molecular receptors to apical endpoints in laboratory species. Use in environmental decision-making is limited, due to difficulty in elucidating mechanisms in sufficient detail to make quantitative outcome predictions in any single species or in extending predictions to aquatic communities. Here we introduce a mechanism-agnostic statistical approach, supplementing mechanistic investigation by allowing probabilistic outcome prediction even when understanding of molecular pathways is limited, and facilitating extrapolation from results in laboratory test species to predictions about aquatic communities. We use concepts familiar to environmental managers, supplemented with techniques employed for clinical interpretation of 'omics-based biomedical tests. We describe the framework in step-wise fashion, beginning with single test replicates of a single RNA variant, then extending to multi-gene RNA profiling, collections of test replicates, and integration of complementary data. In order to simplify the presentation, we focus on using RNA profiling for distinguishing presence versus absence of chemical hazards, but the principles discussed can be extended to other types of 'omics measurements, multi-class problems, and regression. We include a supplemental file demonstrating many of the concepts using the open source R statistical package. Published by Elsevier Ltd.

Multiple regression analysis of anthropometric measurements influencing the cephalic index of male Japanese university students.

PubMed

Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku

2013-09-01

Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p < 0.01), bizygomatic breadth (p < 0.01) and head height (p < 0.05), and a negative relationship between CI and morphological facial height (p < 0.01) and head circumference (p < 0.01). Moreover, the coefficient and odds ratio of logistic regression analysis showed a greater likelihood for minimum frontal breadth (p < 0.01) and bizygomatic breadth (p < 0.01) to predict round-headedness, and morphological facial height (p < 0.05) and head circumference (p < 0.01) to predict long-headedness. Stepwise regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Evaluation of pre-implantation kidney biopsies: comparison of Banff criteria to a morphometric approach.

PubMed

Lopes, José António; Moreso, Francesc; Riera, Luis; Carrera, Marta; Ibernon, Meritxell; Fulladosa, Xavier; Grinyó, Josep Maria; Serón, Daniel

2005-04-01

Donor glomerulosclerosis, interstitial fibrosis, and fibrous intimal thickening correlate with graft outcome. We evaluate chronic lesions in donor biopsies according to Banff criteria and with a morphometric technique to ascertain their predictive value on graft outcome. We evaluated 77 cadaveric donor biopsies according to Banff criteria. Glomerulosclerosis was expressed as the percentage of global sclerotic glomeruli. The following morphometric parameters were obtained: cortical interstitial volume fraction (Vvint/c), cortical glomerular volume fraction (Vvglom/c), mean glomerular volume (Vg), mean and maximal intimal arterial volume fraction (Vvintima/art), and Vvintima/art of the largest artery. We evaluated the correlation of histologic lesions with delayed graft function, 3 months' glomerular filtration rate (GFR), and death-censored graft survival. Multivariate logistic regression showed that delayed graft function was associated with cv score [relative risk (RR) 4.2 and 95% CI 1.1 to 16.0) and glomerulosclerosis (RR 1.06 and 95% CI 1.01 to 1.13). Stepwise regression showed that Vvint/c and glomerulosclerosis were independent predictors of 3 months' GFR (R= 0.62, P= 0.0001). Repeated analysis not considering morphometric parameters showed that glomerulosclerosis, cv score and ci score were independent predictors of 3 months' GFR (R= 0.64, P= 0.0001). A donor chronic damage score was generated considering glomerulosclerosis, cv score and ci score. This score after adjusting for clinical variables was associated with 3 months' GFR (R= 0.71, P < 0.0001) and death-censored graft survival (RR 2.2 and 95% CI 1.3 to 3.7). Combined evaluation of donor glomerulosclerosis, chronic vascular and interstitial damage according to Banff criteria allows a precise prediction of graft outcome. Morphometric evaluation of donor biopsies does not improve the predictive value of semiquantitative grading.

Transhilar passage in right graft live donor liver transplantation: intrahilar anatomy and its impact on operative strategy.

PubMed

Radtke, A; Sotiropoulos, G C; Molmenti, E P; Sgourakis, G; Schroeder, T; Beckebaum, S; Peitgen, H-O; Cicinnati, V R; Broelsch, C E; Broering, D C; Malagó, M

2012-03-01

The passage through the hilar plate during right graft live donor liver transplantation (LDLT) can have dangerous consequences for both donors and recipients. The purpose of our study was to delineate hilar transection and biliary reconstruction strategies in right graft LDLT, with special consideration of central and peripheral hilar anatomical variants. A total of 71 consecutive donors underwent preoperative three-dimensional (3D) CT reconstructions and virtual 3D hepatectomies. A three-modal hilar passage strategy was applied, and its impact on operative strategy analyzed. In 68.4% of cases, type I and II anatomical configurations allowed for an en block hilar transection with simple anastomotic reconstructions. In 23.6% of cases, donors had "difficult" type II and types III/IV hilar bile duct anatomy that required stepwise hilar transections and complex graft biliary reconstructions. Morbidity rates for our early (A) and recent (B) experience periods were 67% and 39%, respectively. (1) Our two-level classification and 3D imaging technique allowed for donor-individualized transhilar passage. (2) A stepwise transhilar passage was favored in types III and IV inside the right-sided hilar corridor. (3) Reconstruction techniques showed no ameliorating effect on early/late biliary morbidity rates. © copyright 2012 The American Society of Transplantation and the American Society of Transplant Surgeons.

Wheat flour dough Alveograph characteristics predicted by Mixolab regression models.

PubMed

Codină, Georgiana Gabriela; Mironeasa, Silvia; Mironeasa, Costel; Popa, Ciprian N; Tamba-Berehoiu, Radiana

2012-02-01

In Romania, the Alveograph is the most used device to evaluate the rheological properties of wheat flour dough, but lately the Mixolab device has begun to play an important role in the breadmaking industry. These two instruments are based on different principles but there are some correlations that can be found between the parameters determined by the Mixolab and the rheological properties of wheat dough measured with the Alveograph. Statistical analysis on 80 wheat flour samples using the backward stepwise multiple regression method showed that Mixolab values using the ‘Chopin S’ protocol (40 samples) and ‘Chopin + ’ protocol (40 samples) can be used to elaborate predictive models for estimating the value of the rheological properties of wheat dough: baking strength (W), dough tenacity (P) and extensibility (L). The correlation analysis confirmed significant findings (P < 0.05 and P < 0.01) between the parameters of wheat dough studied by the Mixolab and its rheological properties measured with the Alveograph. A number of six predictive linear equations were obtained. Linear regression models gave multiple regression coefficients with R²(adjusted) > 0.70 for P, R²(adjusted) > 0.70 for W and R²(adjusted) > 0.38 for L, at a 95% confidence interval. Copyright © 2011 Society of Chemical Industry.

Associations with substance abuse treatment completion in drug court

PubMed Central

Brown, Randall T

2009-01-01

Subjects in the study included all participants (N = 573) in drug treatment court in a mid-sized U.S. city from 1996 through 2004. Administrative data from the drug court included measures of demographics and socioeconomics, substance use, and criminal justice history. Stepwise multivariate logistic regression yielded a final model of failure to complete drug treatment. Unemployment, lower educational attainment, and cocaine use disorders were associated with failure to complete treatment. The limitations of administrative data should be considered in the interpretation of results. Funding was provided by the National Institutes of Health, National Institute on Drug Abuse (1 K23 DA017283-01). PMID:20380560

BrightStat.com: free statistics online.

PubMed

Stricker, Daniel

2008-10-01

Powerful software for statistical analysis is expensive. Here I present BrightStat, a statistical software running on the Internet which is free of charge. BrightStat's goals, its main capabilities and functionalities are outlined. Three different sample runs, a Friedman test, a chi-square test, and a step-wise multiple regression are presented. The results obtained by BrightStat are compared with results computed by SPSS, one of the global leader in providing statistical software, and VassarStats, a collection of scripts for data analysis running on the Internet. Elementary statistics is an inherent part of academic education and BrightStat is an alternative to commercial products.

Population dynamics of pond zooplankton, I. Diaptomus pallidus Herrick

USGS Publications Warehouse

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

1973-01-01

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

Hydraulic geometry and streamflow of channels in the Piceance Basin, Rio Blanco and Garfield counties, Colorado

USGS Publications Warehouse

Elliott, J.G.; Cartier, K.D.

1986-01-01

The influence of streamflow and basin characteristics on channel geometry was investigated at 18 perennial and ephemeral stream reaches in the Piceance basin of northwestern Colorado. Results of stepwise multiple regression analyses indicated that the variabilities of mean bankfull depth (D) and bankfull cross-sectional flow area (Af) were predominantly a function of bankfull discharge (QB), and that most of the variability in channel slopes (S) could be explained by drainage area (DA). None of the independent variables selected for the study could account for a large part of the variability in bankfull channel width (W). (USGS)

Indicators of commitment to the church: a longitudinal study of church-affiliated youth.

PubMed

Dudley, R L

1993-01-01

In an attempt to discover the factors that determine which late adolescents drop out of the church and which remain committed to it, a broad sample of Seventh-day Adventist youth was surveyed. These youth were part of a ten-year study which originally involved over 1,500 subjects distributed throughout the United States and Canada. Commitment was found to be related to cognitive, experiential, and activity dimensions of religion. Ethical considerations, a perception of one's importance to the local congregation, and peer influence also played a part in the stepwise regression package, which accounted for half of the variance in commitment scores.

Family environment and its relation to adolescent personality factors.

PubMed

Forman, S G; Forman, B D

1981-04-01

Investigated the relationship between family social climate characteristics and adolescent personality functioning. The High School Personality Questionnaire (HSPQ) was administered to 80 high school students. These students and their parents also completed the Family Environment Scale (FES). Results of a stepwise multiple regression analysis indicated that one or more HSPQ scales had significant associations with each FES scale. Significant variance in child behavior was attributed to family social system functioning; however, no single family variable accounted for a major portion of the variance to the exclusion of other factors. It was concluded that child behavior varies with total system functioning, more than with separate system factors.

Creep-Rupture Data Analysis - Engineering Application of Regression Techniques. Ph.D. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Rummler, D. R.

1976-01-01

The results are presented of investigations to apply regression techniques to the development of methodology for creep-rupture data analysis. Regression analysis techniques are applied to the explicit description of the creep behavior of materials for space shuttle thermal protection systems. A regression analysis technique is compared with five parametric methods for analyzing three simulated and twenty real data sets, and a computer program for the evaluation of creep-rupture data is presented.

Role of 2 common variants of 5HT2A gene in medication overuse headache.

PubMed

Terrazzino, Salvatore; Sances, Grazia; Balsamo, Francesca; Viana, Michele; Monaco, Francesco; Bellomo, Giorgio; Martignoni, Emilia; Tassorelli, Cristina; Nappi, Giuseppe; Canonico, Pier Luigi; Genazzani, Armando A

2010-11-01

The aim of the present study was to evaluate a possible involvement of 2 polymorphisms of the serotonin 5HT2A receptor gene (A-1438G and C516T) as risk factors for medication overuse headache (MOH) and whether the presence of these polymorphic variants might determine differences within MOH patients in monthly drug consumption. Despite a growing scientific interest in the mechanisms underlying the pathophysiology of MOH, few studies have focused on the role of genetics in the development of the disease, as well as on the genetic determinants of the inter-individual variability in the number of drug doses taken per month. Our study was performed by polymerase chain reaction (PCR) and PCR-restriction fragment length polymorphism on genomic DNA extracted from peripheral blood of 227 MOH patients and 312 control subjects. Genotype-specific risks were estimated as odds ratios with associated 95% confidence intervals by unconditional logistic regression and adjusted for age and gender. A stepwise multiple linear regression analysis was employed to identify significant predictors of the number of drug doses taken per month. No significant association was found between 5HT2A A and 1438G and C516T gene polymorphisms and MOH risk. In contrast, a higher consumption of monthly drug doses was observed among 516T 5HT2A carriers (median 50, range 13-120) compared to 516CC patients (median 30, range 12-128) (Mann-Whitney U-test, P = .018). In the stepwise multiple regression analysis, C516T 5HT2A polymorphism (P = .018) and class of overused drug (P = .047) emerged as significant, independent predictors of the monthly drug consumption in MOH patients. Although our results do not support a major role of the A-1438G and C516T polymorphic variants of the 5HT2A gene in the susceptibility of MOH, our findings support an influence of the C516T polymorphism on the number of symptomatic drug doses taken and, possibly, on the drug-seeking behavior in these patients. © 2010 American Headache Society.

Stone volume is best predictor of operative time required in retrograde intrarenal surgery for renal calculi: implications for surgical planning and quality improvement.

PubMed

Sorokin, Igor; Cardona-Grau, Diana K; Rehfuss, Alexandra; Birney, Alan; Stavrakis, Costas; Leinwand, Gabriel; Herr, Allen; Feustel, Paul J; White, Mark D

2016-11-01

Retrograde intrarenal surgery (RIRS) is highly successful at eliminating renal stones of various sizes and compositions. As urologists are taking on more complex procedures using RIRS, this has led to an increase in operative (OR) times. Our objective was to determine the best predictor of OR time in patients undergoing RIRS. We retrospectively reviewed the records of patients undergoing unilateral RIRS for solitary stones over a 10 year time span. Stones were fragmented and actively extracted using a basket. Variables potentially affecting OR time such as patient age, sex, BMI, lower pole stone location, volume, Hounsfield units (HU), composition, ureteral access sheath (UAS) use, and pre-operative stenting were collected. Multivariable linear and stepwise regression was used to evaluate the predictors of OR time. There were 118 patients that met inclusion criteria. The median stone volume was 282.6 mm 3 (IQR 150.7-644.7) and the mean OR time was 50 min (±25.9 SD). On univariate linear regression, stone volume had a moderate correlation with OR time (y = 0.022x + 38.2, r 2  = 0.363, p < 0.01). On multivariable stepwise regression, stone volume had the strongest impact on OR time, increasing time by 2.0 min for each 100 mm 3 increase in stone volume (p < 0.001). UAS added 13.5 (SE 3.9, p = 0.001) minutes and renal lower pole location added 9 min (SE 4.3, p = 0.03) in each case they were used. Pre-operative stenting, HU, calcium oxalate stone composition, sex, and age had no significant effect on OR time. Amongst the main stone factors in RIRS, stone volume has the strongest impact on operative time. This can be used to predict the length of the procedure by roughly adding 2 min per 100 mm 3 increase in stone volume.

Power Relative to Body Mass Best Predicts Change in Core Temperature During Exercise-Heat Stress.

PubMed

Gibson, Oliver R; Willmott, Ashley G B; James, Carl A; Hayes, Mark; Maxwell, Neil S

2017-02-01

Gibson, OR, Willmott, AGB, James, CA, Hayes, M, and Maxwell, NS. Power relative to body mass best predicts change in core temperature during exercise-heat stress. J Strength Cond Res 31(2): 403-414, 2017-Controlling internal temperature is crucial when prescribing exercise-heat stress, particularly during interventions designed to induce thermoregulatory adaptations. This study aimed to determine the relationship between the rate of rectal temperature (Trec) increase, and various methods for prescribing exercise-heat stress, to identify the most efficient method of prescribing isothermic heat acclimation (HA) training. Thirty-five men cycled in hot conditions (40° C, 39% R.H.) for 29 ± 2 minutes. Subjects exercised at 60 ± 9% V[Combining Dot Above]O2peak, with methods for prescribing exercise retrospectively observed for each participant. Pearson product moment correlations were calculated for each prescriptive variable against the rate of change in Trec (° C·h), with stepwise multiple regressions performed on statistically significant variables (p ≤ 0.05). Linear regression identified the predicted intensity required to increase Trec by 1.0-2.0° C between 20- and 45-minute periods and the duration taken to increase Trec by 1.5° C in response to incremental intensities to guide prescription. Significant (p ≤ 0.05) relationships with the rate of change in Trec were observed for prescriptions based on relative power (W·kg; r = 0.764), power (%Powermax; r = 0.679), rating of perceived exertion (RPE) (r = 0.577), V[Combining Dot Above]O2 (%V[Combining Dot Above]O2peak; r = 0.562), heart rate (HR) (%HRmax; r = 0.534), and thermal sensation (r = 0.311). Stepwise multiple regressions observed relative power and RPE as variables to improve the model (r = 0.791), with no improvement after inclusion of any anthropometric variable. Prescription of exercise under heat stress using power (W·kg or %Powermax) has the strongest relationship with the rate of change in Trec with no additional requirement to correct for body composition within a normal range. Practitioners should therefore prescribe exercise intensity using relative power during isothermic HA training to increase Trec efficiently and maximize adaptation.

The Outlier Detection for Ordinal Data Using Scalling Technique of Regression Coefficients

NASA Astrophysics Data System (ADS)

Adnan, Arisman; Sugiarto, Sigit

2017-06-01

The aims of this study is to detect the outliers by using coefficients of Ordinal Logistic Regression (OLR) for the case of k category responses where the score from 1 (the best) to 8 (the worst). We detect them by using the sum of moduli of the ordinal regression coefficients calculated by jackknife technique. This technique is improved by scalling the regression coefficients to their means. R language has been used on a set of ordinal data from reference distribution. Furthermore, we compare this approach by using studentised residual plots of jackknife technique for ANOVA (Analysis of Variance) and OLR. This study shows that the jackknifing technique along with the proper scaling may lead us to reveal outliers in ordinal regression reasonably well.

STRCMACS: An extensive set of Macros for structured programming in OS/360 assembly language

NASA Technical Reports Server (NTRS)

Barth, C. W.

1974-01-01

Two techniques are discussed that have been most often referred to as structured programming. One is that of programming with high level control structures (such as the if and while) replacing the branch instruction (goto-less programming); the other is the process of developing a program by progressively refining descriptions of components in terms of more primitive components (called stepwise refinement or top-down programming). In addition to discussing what these techniques are, it is shown why their use is advised and how both can be implemented in OS assembly language by the use of a special macro instruction package.

Better Care Teams: A Stepwise Skill Reinforcement Model.

PubMed

Christopher, Beth-Anne; Grantner, Mary; Coke, Lola A; Wideman, Marilyn; Kwakwa, Francis

2016-06-01

The Building Healthy Urban Communities initiative presents a path for organizations partnering to improve patient outcomes with continuing education (CE) as a key component. Components of the CE initiative included traditional CE delivery formats with an essential element of adaptability and new methods, with rigorous evaluation over time that included evaluation prior to the course, immediately following the CE session, 6 to 8 weeks after the CE session, and then subsequent monthly "testlets." Outcome measures were designed to allow for ongoing adaptation of content, reinforcement of key learning objectives, and use of innovative concordant testing and retrieval practice techniques. The results after 1 year of programming suggest the stepwise skill reinforcement model is effective for learning and is an efficient use of financial and human resources. More important, its design is one that could be adopted at low cost by organizations willing to work in close partnership. J Contin Educ Nurs. 2016;47(6):283-288. Copyright 2016, SLACK Incorporated.

Preparative isolation and purification of macrolactin antibiotics from marine bacterium Bacillus amyloliquefaciens using high-speed counter-current chromatography in stepwise elution mode.

PubMed

He, Shan; Wang, Hongqiang; Yan, Xiaojun; Zhu, Peng; Chen, Juanjuan; Yang, Rui

2013-01-11

Preparative high-speed counter-current chromatography (HSCCC) was successfully applied to the isolation and purification of two macrolactin antibiotics from marine bacterium Bacillus amyloliquefaciens for the first time using stepwise elution with a pair of two-phase solvent systems composed of n-hexane-ethyl acetate-methanol-water at (1:4:1:4, v/v) and (3:4:3:4, v/v). The preparative HSCCC separation was performed on 300 mg of crude sample yielding macrolactin B (22.7 mg) and macrolactin A (40.4 mg) in a one-step separation, with purities over 95% as determined by HPLC. The structures of these compounds were identified by MS, (1)H NMR and (13)C NMR. Our results demonstrated that HSCCC was an efficient technique to separate marine antibiotics, which provide an approach to solve the problem of their sample availability for drug development. Copyright © 2012 Elsevier B.V. All rights reserved.

Stepwise molding, etching, and imprinting to form libraries of nanopatterned substrates.

PubMed

Zhao, Zhi; Cai, Yangjun; Liao, Wei-Ssu; Cremer, Paul S

2013-06-04

Herein, we describe a novel colloidal lithographic strategy for the stepwise patterning of planar substrates with numerous complex and unique designs. In conjunction with colloidal self-assembly, imprint molding, and capillary force lithography, reactive ion etching was used to create complex libraries of nanoscale features. This combinatorial strategy affords the ability to develop an exponentially increasing number of two-dimensional nanoscale patterns with each sequential step in the process. Specifically, dots, triangles, circles, and lines could be assembled on the surface separately and in combination with each other. Numerous architectures are obtained for the first time with high uniformity and reproducibility. These hexagonal arrays were made from polystyrene and gold features, whereby each surface element could be tuned from the micrometer size scale down to line widths of ~35 nm. The patterned area could be 1 cm(2) or even larger. The techniques described herein can be combined with further steps to make even larger libraries. Moreover, these polymer and metal features may prove useful in optical, sensing, and electronic applications.

Growth of Pd Nanoclusters on Single-Layer Graphene on Cu(111)

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

Soy, Esin; Guisinger, Nathan P.; Trenary, Michael

We report scanning tunneling microscopy results on the nucleation and growth of Pd nanoclusters on a single layer of graphene on the Cu(111) surface. The shape, organization, and structural evolution of the Pd nanoclusters were investigated using two different growth methods, continuous and stepwise. The size and shape of the formed nanoclusters were found to greatly depend on the growth technique used. The size and density of spherical Pd nanoclusters increased with increasing coverage during stepwise deposition as a result of coarsening of existing clusters and continued nucleation of new clusters. In contrast, continuous deposition gave rise to well-defined triangularmore » Pd clusters as a result of anisotropic growth on the graphene surface. Exposure to ethylene caused a decrease in the size of the Pd clusters. As a result, this is attributed to the exothermic formation of ethylidyne on the cluster surfaces and an accompanying weakening of the Pd–Pd bonding.« less

Growth of Pd Nanoclusters on Single-Layer Graphene on Cu(111)

DOE PAGES

Soy, Esin; Guisinger, Nathan P.; Trenary, Michael

2017-07-05

We report scanning tunneling microscopy results on the nucleation and growth of Pd nanoclusters on a single layer of graphene on the Cu(111) surface. The shape, organization, and structural evolution of the Pd nanoclusters were investigated using two different growth methods, continuous and stepwise. The size and shape of the formed nanoclusters were found to greatly depend on the growth technique used. The size and density of spherical Pd nanoclusters increased with increasing coverage during stepwise deposition as a result of coarsening of existing clusters and continued nucleation of new clusters. In contrast, continuous deposition gave rise to well-defined triangularmore » Pd clusters as a result of anisotropic growth on the graphene surface. Exposure to ethylene caused a decrease in the size of the Pd clusters. As a result, this is attributed to the exothermic formation of ethylidyne on the cluster surfaces and an accompanying weakening of the Pd–Pd bonding.« less

Diagnosis and Multimodality Management of Cushing's Disease: A Practical Review

PubMed Central

Zada, Gabriel

2013-01-01

Cushing's Disease is caused by oversecretion of ACTH from a pituitary adenoma and results in subsequent elevations of systemic cortisol, ultimately contributing to reduced patient survival. The diagnosis of Cushing's Disease frequently involves a stepwise approach including clinical, laboratory, neuroimaging, and sometimes interventional radiology techniques, often mandating multidisciplinary collaboration from numerous specialty practitioners. Pituitary microadenomas that do not appear on designated pituitary MRI or dynamic contrast protocols may pose a particularly challenging subset of this disease. The treatment of Cushing's Disease typically involves transsphenoidal surgical resection of the pituitary adenoma as a first-line option, yet may require the addition of adjunctive measures such as stereotactic radiosurgery or medical management to achieve normalization of serum cortisol levels. Vigilant long-term serial endocrine monitoring of patients is imperative in order to detect any recurrence that may occur, even years following initial remission. In this paper, a stepwise approach to the diagnosis, and various management strategies and associated outcomes in patients with Cushing's Disease are discussed. PMID:23401686

Work Done by Titin Protein Folding Assists Muscle Contraction.

PubMed

Rivas-Pardo, Jaime Andrés; Eckels, Edward C; Popa, Ionel; Kosuri, Pallav; Linke, Wolfgang A; Fernández, Julio M

2016-02-16

Current theories of muscle contraction propose that the power stroke of a myosin motor is the sole source of mechanical energy driving the sliding filaments of a contracting muscle. These models exclude titin, the largest protein in the human body, which determines the passive elasticity of muscles. Here, we show that stepwise unfolding/folding of titin immunoglobulin (Ig) domains occurs in the elastic I band region of intact myofibrils at physiological sarcomere lengths and forces of 6-8 pN. We use single-molecule techniques to demonstrate that unfolded titin Ig domains undergo a spontaneous stepwise folding contraction at forces below 10 pN, delivering up to 105 zJ of additional contractile energy, which is larger than the mechanical energy delivered by the power stroke of a myosin motor. Thus, it appears inescapable that folding of titin Ig domains is an important, but as yet unrecognized, contributor to the force generated by a contracting muscle. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Integrated, Step-Wise, Mass-Isotopomeric Flux Analysis of the TCA Cycle.

PubMed

Alves, Tiago C; Pongratz, Rebecca L; Zhao, Xiaojian; Yarborough, Orlando; Sereda, Sam; Shirihai, Orian; Cline, Gary W; Mason, Graeme; Kibbey, Richard G

2015-11-03

Mass isotopomer multi-ordinate spectral analysis (MIMOSA) is a step-wise flux analysis platform to measure discrete glycolytic and mitochondrial metabolic rates. Importantly, direct citrate synthesis rates were obtained by deconvolving the mass spectra generated from [U-(13)C6]-D-glucose labeling for position-specific enrichments of mitochondrial acetyl-CoA, oxaloacetate, and citrate. Comprehensive steady-state and dynamic analyses of key metabolic rates (pyruvate dehydrogenase, β-oxidation, pyruvate carboxylase, isocitrate dehydrogenase, and PEP/pyruvate cycling) were calculated from the position-specific transfer of (13)C from sequential precursors to their products. Important limitations of previous techniques were identified. In INS-1 cells, citrate synthase rates correlated with both insulin secretion and oxygen consumption. Pyruvate carboxylase rates were substantially lower than previously reported but showed the highest fold change in response to glucose stimulation. In conclusion, MIMOSA measures key metabolic rates from the precursor/product position-specific transfer of (13)C-label between metabolites and has broad applicability to any glucose-oxidizing cell. Copyright © 2015 Elsevier Inc. All rights reserved.

Generalized linear and generalized additive models in studies of species distributions: Setting the scene

USGS Publications Warehouse

Guisan, Antoine; Edwards, T.C.; Hastie, T.

2002-01-01

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001. We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling. ?? 2002 Elsevier Science B.V. All rights reserved.

Risk factors for highly pathogenic avian influenza in commercial layer chicken farms in bangladesh during 2011.

PubMed

Osmani, M G; Thornton, R N; Dhand, N K; Hoque, M A; Milon, Sk M A; Kalam, M A; Hossain, M; Yamage, M

2014-12-01

A case-control study conducted during 2011 involved 90 randomly selected commercial layer farms infected with highly pathogenic avian influenza type A subtype H5N1 (HPAI) and 175 control farms randomly selected from within 5 km of infected farms. A questionnaire was designed to obtain information about potential risk factors for contracting HPAI and was administered to farm owners or managers. Logistic regression analyses were conducted to identify significant risk factors. A total of 20 of 43 risk factors for contracting HPAI were identified after univariable logistic regression analysis. A multivariable logistic regression model was derived by forward stepwise selection. Both unmatched and matched analyses were performed. The key risk factors identified were numbers of staff, frequency of veterinary visits, presence of village chickens roaming on the farm and staff trading birds. Aggregating these findings with those from other studies resulted in a list of 16 key risk factors identified in Bangladesh. Most of these related to biosecurity. It is considered feasible for Bangladesh to achieve a very low incidence of HPAI. Using the cumulative list of risk factors to enhance biosecurity pertaining to commercial farms would facilitate this objective. © 2013 Blackwell Verlag GmbH.

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

PubMed

Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

2016-09-01

The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

An evaluation of supervised classifiers for indirectly detecting salt-affected areas at irrigation scheme level

NASA Astrophysics Data System (ADS)

Muller, Sybrand Jacobus; van Niekerk, Adriaan

2016-07-01

Soil salinity often leads to reduced crop yield and quality and can render soils barren. Irrigated areas are particularly at risk due to intensive cultivation and secondary salinization caused by waterlogging. Regular monitoring of salt accumulation in irrigation schemes is needed to keep its negative effects under control. The dynamic spatial and temporal characteristics of remote sensing can provide a cost-effective solution for monitoring salt accumulation at irrigation scheme level. This study evaluated a range of pan-fused SPOT-5 derived features (spectral bands, vegetation indices, image textures and image transformations) for classifying salt-affected areas in two distinctly different irrigation schemes in South Africa, namely Vaalharts and Breede River. The relationship between the input features and electro conductivity measurements were investigated using regression modelling (stepwise linear regression, partial least squares regression, curve fit regression modelling) and supervised classification (maximum likelihood, nearest neighbour, decision tree analysis, support vector machine and random forests). Classification and regression trees and random forest were used to select the most important features for differentiating salt-affected and unaffected areas. The results showed that the regression analyses produced weak models (<0.4 R squared). Better results were achieved using the supervised classifiers, but the algorithms tend to over-estimate salt-affected areas. A key finding was that none of the feature sets or classification algorithms stood out as being superior for monitoring salt accumulation at irrigation scheme level. This was attributed to the large variations in the spectral responses of different crops types at different growing stages, coupled with their individual tolerances to saline conditions.

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

PubMed

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

2014-01-01

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

Stochastic optimal operation of reservoirs based on copula functions

NASA Astrophysics Data System (ADS)

Lei, Xiao-hui; Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wen, Xin; Wang, Chao; Zhang, Jing-wen

2018-02-01

Stochastic dynamic programming (SDP) has been widely used to derive operating policies for reservoirs considering streamflow uncertainties. In SDP, there is a need to calculate the transition probability matrix more accurately and efficiently in order to improve the economic benefit of reservoir operation. In this study, we proposed a stochastic optimization model for hydropower generation reservoirs, in which 1) the transition probability matrix was calculated based on copula functions; and 2) the value function of the last period was calculated by stepwise iteration. Firstly, the marginal distribution of stochastic inflow in each period was built and the joint distributions of adjacent periods were obtained using the three members of the Archimedean copulas, based on which the conditional probability formula was derived. Then, the value in the last period was calculated by a simple recursive equation with the proposed stepwise iteration method and the value function was fitted with a linear regression model. These improvements were incorporated into the classic SDP and applied to the case study in Ertan reservoir, China. The results show that the transition probability matrix can be more easily and accurately obtained by the proposed copula function based method than conventional methods based on the observed or synthetic streamflow series, and the reservoir operation benefit can also be increased.

The effects of short- and long-term air pollutants on plant phenology and leaf characteristics.

PubMed

Jochner, Susanne; Markevych, Iana; Beck, Isabelle; Traidl-Hoffmann, Claudia; Heinrich, Joachim; Menzel, Annette

2015-11-01

Pollution adversely affects vegetation; however, its impact on phenology and leaf morphology is not satisfactorily understood yet. We analyzed associations between pollutants and phenological data of birch, hazel and horse chestnut in Munich (2010) along with the suitability of leaf morphological parameters of birch for monitoring air pollution using two datasets: cumulated atmospheric concentrations of nitrogen dioxide and ozone derived from passive sampling (short-term exposure) and pollutant information derived from Land Use Regression models (long-term exposure). Partial correlations and stepwise regressions revealed that increased ozone (birch, horse chestnut), NO2, NOx and PM levels (hazel) were significantly related to delays in phenology. Correlations were especially high when rural sites were excluded suggesting a better estimation of long-term within-city pollution. In situ measurements of foliar characteristics of birch were not suitable for bio-monitoring pollution. Inconsistencies between long- and short-term exposure effects suggest some caution when interpreting short-term data collected within field studies. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Simulation of three-dimensional green biomass of urban forests in Shenyang City and the factors affecting the biomass].

PubMed

Liu, Chang-Fu; He, Xing-Yuan; Chen, Wei; Zhao, Gui-Ling; Xue, Wen-Duo

2008-06-01

Based on the fractal theory of forest growth, stepwise regression was employed to pursue a convenient and efficient method of measuring the three-dimensional green biomass (TGB) of urban forests in small area. A total of thirteen simulation equations of TGB of urban forests in Shenyang City were derived, with the factors affecting the TGB analyzed. The results showed that the coefficients of determination (R2) of the 13 simulation equations ranged from 0.612 to 0.842. No evident pattern was shown in residual analysis, and the precisions were all higher than 87% (alpha = 0.05) and 83% (alpha = 0.01). The most convenient simulation equation was ln Y = 7.468 + 0.926 lnx1, where Y was the simulated TGB and x1 was basal area at breast height per hectare (SDB). The correlations between the standard regression coefficients of the simulation equations and 16 tree characteristics suggested that SDB was the main factor affecting the TGB of urban forests in Shenyang.

QSAR and docking based semi-synthesis and in vitro evaluation of 18 β-glycyrrhetinic acid derivatives against human lung cancer cell line A-549.

PubMed

Yadav, Dharmendra Kumar; Kalani, Komal; Khan, Feroz; Srivastava, Santosh Kumar

2013-12-01

For the prediction of anticancer activity of glycyrrhetinic acid (GA-1) analogs against the human lung cancer cell line (A-549), a QSAR model was developed by forward stepwise multiple linear regression methodology. The regression coefficient (r(2)) and prediction accuracy (rCV(2)) of the QSAR model were taken 0.94 and 0.82, respectively in terms of correlation. The QSAR study indicates that the dipole moments, size of smallest ring, amine counts, hydroxyl and nitro functional groups are correlated well with cytotoxic activity. The docking studies showed high binding affinity of the predicted active compounds against the lung cancer target EGFR. These active glycyrrhetinic acid derivatives were then semi-synthesized, characterized and in-vitro tested for anticancer activity. The experimental results were in agreement with the predicted values and the ethyl oxalyl derivative of GA-1 (GA-3) showed equal cytotoxic activity to that of standard anticancer drug paclitaxel.

Women's work stress and cortisol levels: a longitudinal study of the association between the psychosocial work environment and serum cortisol.

PubMed

Evolahti, Annika; Hultcrantz, Malou; Collins, Aila

2006-11-01

The aim of the present study was to investigate whether there is an association between serum cortisol and work-related stress, as defined by the demand-control model in a longitudinal design. One hundred ten women aged 47-53 years completed a health questionnaire, including the Swedish version of the Job Content Scale, and participated in a psychological interview at baseline and in a follow-up session 2 years later. Morning blood samples were drawn for analyses of cortisol. Multiple stepwise regression analyses and logistic regression analyses showed that work demands and lack of social support were significantly associated with cortisol. The results of this study showed that negative work characteristics in terms of high demands and low social support contributed significantly to the biological stress levels in middle-aged women. Participation in the study may have served as an intervention, increasing the women's awareness and thus improving their health profiles on follow-up.

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

Longitudinal cognitive biomarkers predicting symptom onset in presymptomatic frontotemporal dementia.

PubMed

Jiskoot, Lize C; Panman, Jessica L; van Asseldonk, Lauren; Franzen, Sanne; Meeter, Lieke H H; Donker Kaat, Laura; van der Ende, Emma L; Dopper, Elise G P; Timman, Reinier; van Minkelen, Rick; van Swieten, John C; van den Berg, Esther; Papma, Janne M

2018-06-01

We performed 4-year follow-up neuropsychological assessment to investigate cognitive decline and the prognostic abilities from presymptomatic to symptomatic familial frontotemporal dementia (FTD). Presymptomatic MAPT (n = 15) and GRN mutation carriers (n = 31), and healthy controls (n = 39) underwent neuropsychological assessment every 2 years. Eight mutation carriers (5 MAPT, 3 GRN) became symptomatic. We investigated cognitive decline with multilevel regression modeling; the prognostic performance was assessed with ROC analyses and stepwise logistic regression. MAPT converters declined on language, attention, executive function, social cognition, and memory, and GRN converters declined on attention and executive function (p < 0.05). Cognitive decline in ScreeLing phonology (p = 0.046) and letter fluency (p = 0.046) were predictive for conversion to non-fluent variant PPA, and decline on categorical fluency (p = 0.025) for an underlying MAPT mutation. Using longitudinal neuropsychological assessment, we detected a mutation-specific pattern of cognitive decline, potentially suggesting prognostic value of neuropsychological trajectories in conversion to symptomatic FTD.

Logistic LASSO regression for the diagnosis of breast cancer using clinical demographic data and the BI-RADS lexicon for ultrasonography.

PubMed

Kim, Sun Mi; Kim, Yongdai; Jeong, Kuhwan; Jeong, Heeyeong; Kim, Jiyoung

2018-01-01

The aim of this study was to compare the performance of image analysis for predicting breast cancer using two distinct regression models and to evaluate the usefulness of incorporating clinical and demographic data (CDD) into the image analysis in order to improve the diagnosis of breast cancer. This study included 139 solid masses from 139 patients who underwent a ultrasonography-guided core biopsy and had available CDD between June 2009 and April 2010. Three breast radiologists retrospectively reviewed 139 breast masses and described each lesion using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We applied and compared two regression methods-stepwise logistic (SL) regression and logistic least absolute shrinkage and selection operator (LASSO) regression-in which the BI-RADS descriptors and CDD were used as covariates. We investigated the performances of these regression methods and the agreement of radiologists in terms of test misclassification error and the area under the curve (AUC) of the tests. Logistic LASSO regression was superior (P<0.05) to SL regression, regardless of whether CDD was included in the covariates, in terms of test misclassification errors (0.234 vs. 0.253, without CDD; 0.196 vs. 0.258, with CDD) and AUC (0.785 vs. 0.759, without CDD; 0.873 vs. 0.735, with CDD). However, it was inferior (P<0.05) to the agreement of three radiologists in terms of test misclassification errors (0.234 vs. 0.168, without CDD; 0.196 vs. 0.088, with CDD) and the AUC without CDD (0.785 vs. 0.844, P<0.001), but was comparable to the AUC with CDD (0.873 vs. 0.880, P=0.141). Logistic LASSO regression based on BI-RADS descriptors and CDD showed better performance than SL in predicting the presence of breast cancer. The use of CDD as a supplement to the BI-RADS descriptors significantly improved the prediction of breast cancer using logistic LASSO regression.

Statistical summary of selected physical, chemical, and toxicity characteristics and estimates of annual constituent loads in urban stormwater, Maricopa County, Arizona

USGS Publications Warehouse

Fossum, Kenneth D.; O'Day, Christie M.; Wilson, Barbara J.; Monical, Jim E.

2001-01-01

Stormwater and streamflow in Maricopa County were monitored to (1) describe the physical, chemical, and toxicity characteristics of stormwater from areas having different land uses, (2) describe the physical, chemical, and toxicity characteristics of streamflow from areas that receive urban stormwater, and (3) estimate constituent loads in stormwater. Urban stormwater and streamflow had similar ranges in most constituent concentrations. The mean concentration of dissolved solids in urban stormwater was lower than in streamflow from the Salt River and Indian Bend Wash. Urban stormwater, however, had a greater chemical oxygen demand and higher concentrations of most nutrients. Mean seasonal loads and mean annual loads of 11 constituents and volumes of runoff were estimated for municipalities in the metropolitan Phoenix area, Arizona, by adjusting regional regression equations of loads. This adjustment procedure uses the original regional regression equation and additional explanatory variables that were not included in the original equation. The adjusted equations had standard errors that ranged from 161 to 196 percent. The large standard errors of the prediction result from the large variability of the constituent concentration data used in the regression analysis. Adjustment procedures produced unsatisfactory results for nine of the regressions?suspended solids, dissolved solids, total phosphorus, dissolved phosphorus, total recoverable cadmium, total recoverable copper, total recoverable lead, total recoverable zinc, and storm runoff. These equations had no consistent direction of bias and no other additional explanatory variables correlated with the observed loads. A stepwise-multiple regression or a three-variable regression (total storm rainfall, drainage area, and impervious area) and local data were used to develop local regression equations for these nine constituents. These equations had standard errors from 15 to 183 percent.

Identification of extremely premature infants at high risk of rehospitalization.

PubMed

Ambalavanan, Namasivayam; Carlo, Waldemar A; McDonald, Scott A; Yao, Qing; Das, Abhik; Higgins, Rosemary D

2011-11-01

Extremely low birth weight infants often require rehospitalization during infancy. Our objective was to identify at the time of discharge which extremely low birth weight infants are at higher risk for rehospitalization. Data from extremely low birth weight infants in Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network centers from 2002-2005 were analyzed. The primary outcome was rehospitalization by the 18- to 22-month follow-up, and secondary outcome was rehospitalization for respiratory causes in the first year. Using variables and odds ratios identified by stepwise logistic regression, scoring systems were developed with scores proportional to odds ratios. Classification and regression-tree analysis was performed by recursive partitioning and automatic selection of optimal cutoff points of variables. A total of 3787 infants were evaluated (mean ± SD birth weight: 787 ± 136 g; gestational age: 26 ± 2 weeks; 48% male, 42% black). Forty-five percent of the infants were rehospitalized by 18 to 22 months; 14.7% were rehospitalized for respiratory causes in the first year. Both regression models (area under the curve: 0.63) and classification and regression-tree models (mean misclassification rate: 40%-42%) were moderately accurate. Predictors for the primary outcome by regression were shunt surgery for hydrocephalus, hospital stay of >120 days for pulmonary reasons, necrotizing enterocolitis stage II or higher or spontaneous gastrointestinal perforation, higher fraction of inspired oxygen at 36 weeks, and male gender. By classification and regression-tree analysis, infants with hospital stays of >120 days for pulmonary reasons had a 66% rehospitalization rate compared with 42% without such a stay. The scoring systems and classification and regression-tree analysis models identified infants at higher risk of rehospitalization and might assist planning for care after discharge.

Identification of Extremely Premature Infants at High Risk of Rehospitalization

PubMed Central

Carlo, Waldemar A.; McDonald, Scott A.; Yao, Qing; Das, Abhik; Higgins, Rosemary D.

2011-01-01

OBJECTIVE: Extremely low birth weight infants often require rehospitalization during infancy. Our objective was to identify at the time of discharge which extremely low birth weight infants are at higher risk for rehospitalization. METHODS: Data from extremely low birth weight infants in Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network centers from 2002–2005 were analyzed. The primary outcome was rehospitalization by the 18- to 22-month follow-up, and secondary outcome was rehospitalization for respiratory causes in the first year. Using variables and odds ratios identified by stepwise logistic regression, scoring systems were developed with scores proportional to odds ratios. Classification and regression-tree analysis was performed by recursive partitioning and automatic selection of optimal cutoff points of variables. RESULTS: A total of 3787 infants were evaluated (mean ± SD birth weight: 787 ± 136 g; gestational age: 26 ± 2 weeks; 48% male, 42% black). Forty-five percent of the infants were rehospitalized by 18 to 22 months; 14.7% were rehospitalized for respiratory causes in the first year. Both regression models (area under the curve: 0.63) and classification and regression-tree models (mean misclassification rate: 40%–42%) were moderately accurate. Predictors for the primary outcome by regression were shunt surgery for hydrocephalus, hospital stay of >120 days for pulmonary reasons, necrotizing enterocolitis stage II or higher or spontaneous gastrointestinal perforation, higher fraction of inspired oxygen at 36 weeks, and male gender. By classification and regression-tree analysis, infants with hospital stays of >120 days for pulmonary reasons had a 66% rehospitalization rate compared with 42% without such a stay. CONCLUSIONS: The scoring systems and classification and regression-tree analysis models identified infants at higher risk of rehospitalization and might assist planning for care after discharge. PMID:22007016

An interative solution of an integral equation for radiative transfer by using variational technique

NASA Technical Reports Server (NTRS)

Yoshikawa, K. K.

1973-01-01

An effective iterative technique is introduced to solve a nonlinear integral equation frequently associated with radiative transfer problems. The problem is formulated in such a way that each step of an iterative sequence requires the solution of a linear integral equation. The advantage of a previously introduced variational technique which utilizes a stepwise constant trial function is exploited to cope with the nonlinear problem. The method is simple and straightforward. Rapid convergence is obtained by employing a linear interpolation of the iterative solutions. Using absorption coefficients of the Milne-Eddington type, which are applicable to some planetary atmospheric radiation problems. Solutions are found in terms of temperature and radiative flux. These solutions are presented numerically and show excellent agreement with other numerical solutions.

Step-by-step integration for fractional operators

NASA Astrophysics Data System (ADS)

Colinas-Armijo, Natalia; Di Paola, Mario

2018-06-01

In this paper, an approach based on the definition of the Riemann-Liouville fractional operators is proposed in order to provide a different discretisation technique as alternative to the Grünwald-Letnikov operators. The proposed Riemann-Liouville discretisation consists of performing step-by-step integration based upon the discretisation of the function f(t). It has been shown that, as f(t) is discretised as stepwise or piecewise function, the Riemann-Liouville fractional integral and derivative are governing by operators very similar to the Grünwald-Letnikov operators. In order to show the accuracy and capabilities of the proposed Riemann-Liouville discretisation technique and the Grünwald-Letnikov discrete operators, both techniques have been applied to: unit step functions, exponential functions and sample functions of white noise.

Patterns and Variations in Microvascular Decompression for Trigeminal Neuralgia

PubMed Central

TODA, Hiroki; GOTO, Masanori; IWASAKI, Koichi

2015-01-01

Microvascular decompression (MVD) is a highly effective surgical treatment for trigeminal neuralgia (TN). Although there is little prospective clinical evidence, accumulated observational studies have demonstrated the benefits of MVD for refractory TN. In the current surgical practice of MVD for TN, there have been recognized patterns and variations in surgical anatomy and various decompression techniques. Here we provide a stepwise description of surgical procedures and relevant anatomical characteristics, as well as procedural options. PMID:25925756

Rapid initiation of fetal therapy services with a system of learner-centred training under proctorship: the National University Hospital (Singapore) experience

PubMed Central

Gosavi, Arundhati; Vijayakumar, Pradip D; Ng, Bryan SW; Loh, May-Han; Tan, Lay Geok; Johana, Nuryanti; Tan, Yi Wan; Sandikin, Dedy; Su, Lin Lin; Wataganara, Tuangsit; Biswas, Arijit; Choolani, Mahesh A; Mattar, Citra NZ

2017-01-01

INTRODUCTION Management of complicated monochorionic twins and certain intrauterine structural anomalies is a pressing challenge in communities that still lack advanced fetal therapy. We describe our efforts to rapidly initiate selective feticide using radiofrequency ablation (RFA) and selective fetoscopic laser photocoagulation (SFLP) for twin-to-twin transfusion syndrome (TTTS), and present the latter as a potential model for aspiring fetal therapy units. METHODS Five pregnancies with fetal complications were identified for RFA. Three pregnancies with Stage II TTTS were selected for SFLP. While RFA techniques utilising ultrasonography skills were quickly mastered, SFLP required stepwise technical learning with an overseas-based proctor, who provided real-time hands-off supervision. RESULTS All co-twins were live-born following selective feticide; one singleton pregnancy was lost. Fetoscopy techniques were learned in a stepwise manner and procedures were performed by a novice team of surgeons under proctorship. Dichorionisation was completed in only one patient. Five of six twins were live-born near term. One pregnancy developed twin anaemia-polycythaemia sequence, while another was complicated by co-twin demise. DISCUSSION Proctor-supervised directed learning facilitated the rapid provision of basic fetal therapy services by our unit. While traditional apprenticeship is important for building individual expertise, this system is complementary and may benefit other small units committed to providing these services. PMID:27439783

Identification of the contribution of contact and aerial biomechanical parameters in acrobatic performance

PubMed Central

Haering, Diane; Huchez, Aurore; Barbier, Franck; Holvoët, Patrice; Begon, Mickaël

2017-01-01

Introduction Teaching acrobatic skills with a minimal amount of repetition is a major challenge for coaches. Biomechanical, statistical or computer simulation tools can help them identify the most determinant factors of performance. Release parameters, change in moment of inertia and segmental momentum transfers were identified in the prediction of acrobatics success. The purpose of the present study was to evaluate the relative contribution of these parameters in performance throughout expertise or optimisation based improvements. The counter movement forward in flight (CMFIF) was chosen for its intrinsic dichotomy between the accessibility of its attempt and complexity of its mastery. Methods Three repetitions of the CMFIF performed by eight novice and eight advanced female gymnasts were recorded using a motion capture system. Optimal aerial techniques that maximise rotation potential at regrasp were also computed. A 14-segment-multibody-model defined through the Rigid Body Dynamics Library was used to compute recorded and optimal kinematics, and biomechanical parameters. A stepwise multiple linear regression was used to determine the relative contribution of these parameters in novice recorded, novice optimised, advanced recorded and advanced optimised trials. Finally, fixed effects of expertise and optimisation were tested through a mixed-effects analysis. Results and discussion Variation in release state only contributed to performances in novice recorded trials. Moment of inertia contribution to performance increased from novice recorded, to novice optimised, advanced recorded, and advanced optimised trials. Contribution to performance of momentum transfer to the trunk during the flight prevailed in all recorded trials. Although optimisation decreased transfer contribution, momentum transfer to the arms appeared. Conclusion Findings suggest that novices should be coached on both contact and aerial technique. Inversely, mainly improved aerial technique helped advanced gymnasts increase their performance. For both, reduction of the moment of inertia should be focused on. The method proposed in this article could be generalized to any aerial skill learning investigation. PMID:28422954

Regression and multivariate models for predicting particulate matter concentration level.

PubMed

Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S

2018-01-01

The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

Analysis of a database to predict the result of allergy testing in vivo in patients with chronic nasal symptoms.

PubMed

Lacagnina, Valerio; Leto-Barone, Maria S; La Piana, Simona; Seidita, Aurelio; Pingitore, Giuseppe; Di Lorenzo, Gabriele

2014-01-01

This article uses the logistic regression model for diagnostic decision making in patients with chronic nasal symptoms. We studied the ability of the logistic regression model, obtained by the evaluation of a database, to detect patients with positive allergy skin-prick test (SPT) and patients with negative SPT. The model developed was validated using the data set obtained from another medical institution. The analysis was performed using a database obtained from a questionnaire administered to the patients with nasal symptoms containing personal data, clinical data, and results of allergy testing (SPT). All variables found to be significantly different between patients with positive and negative SPT (p < 0.05) were selected for the logistic regression models and were analyzed with backward stepwise logistic regression, evaluated with area under the curve of the receiver operating characteristic curve. A second set of patients from another institution was used to prove the model. The accuracy of the model in identifying, over the second set, both patients whose SPT will be positive and negative was high. The model detected 96% of patients with nasal symptoms and positive SPT and classified 94% of those with negative SPT. This study is preliminary to the creation of a software that could help the primary care doctors in a diagnostic decision making process (need of allergy testing) in patients complaining of chronic nasal symptoms.

"Geo-statistics methods and neural networks in geophysical applications: A case study"

NASA Astrophysics Data System (ADS)

Rodriguez Sandoval, R.; Urrutia Fucugauchi, J.; Ramirez Cruz, L. C.

2008-12-01

The study is focus in the Ebano-Panuco basin of northeastern Mexico, which is being explored for hydrocarbon reservoirs. These reservoirs are in limestones and there is interest in determining porosity and permeability in the carbonate sequences. The porosity maps presented in this study are estimated from application of multiattribute and neural networks techniques, which combine geophysics logs and 3-D seismic data by means of statistical relationships. The multiattribute analysis is a process to predict a volume of any underground petrophysical measurement from well-log and seismic data. The data consist of a series of target logs from wells which tie a 3-D seismic volume. The target logs are neutron porosity logs. From the 3-D seismic volume a series of sample attributes is calculated. The objective of this study is to derive a set of attributes and the target log values. The selected set is determined by a process of forward stepwise regression. The analysis can be linear or nonlinear. In the linear mode the method consists of a series of weights derived by least-square minimization. In the nonlinear mode, a neural network is trained using the select attributes as inputs. In this case we used a probabilistic neural network PNN. The method is applied to a real data set from PEMEX. For better reservoir characterization the porosity distribution was estimated using both techniques. The case shown a continues improvement in the prediction of the porosity from the multiattribute to the neural network analysis. The improvement is in the training and the validation, which are important indicators of the reliability of the results. The neural network showed an improvement in resolution over the multiattribute analysis. The final maps provide more realistic results of the porosity distribution.