The Role of Testing in Affirmative Action.

ERIC Educational Resources Information Center

Manning, Winton H.

Graphs and charts pertaining to testing in affirmative action are presented. Data concern the following: the predictive validity of College Board admissions tests using freshman grade point average as the criterion; validity coefficients of undergraduate grade point average (UGPA) alone, Law School Admission Test (LSAT) scores, and undergraduate…

Comparison of prediction methods for octanol-air partition coefficients of diverse organic compounds.

PubMed

Fu, Zhiqiang; Chen, Jingwen; Li, Xuehua; Wang, Ya'nan; Yu, Haiying

2016-04-01

The octanol-air partition coefficient (KOA) is needed for assessing multimedia transport and bioaccumulability of organic chemicals in the environment. As experimental determination of KOA for various chemicals is costly and laborious, development of KOA estimation methods is necessary. We investigated three methods for KOA prediction, conventional quantitative structure-activity relationship (QSAR) models based on molecular structural descriptors, group contribution models based on atom-centered fragments, and a novel model that predicts KOA via solvation free energy from air to octanol phase (ΔGO(0)), with a collection of 939 experimental KOA values for 379 compounds at different temperatures (263.15-323.15 K) as validation or training sets. The developed models were evaluated with the OECD guidelines on QSAR models validation and applicability domain (AD) description. Results showed that although the ΔGO(0) model is theoretically sound and has a broad AD, the prediction accuracy of the model is the poorest. The QSAR models perform better than the group contribution models, and have similar predictability and accuracy with the conventional method that estimates KOA from the octanol-water partition coefficient and Henry's law constant. One QSAR model, which can predict KOA at different temperatures, was recommended for application as to assess the long-range transport potential of chemicals. Copyright © 2016 Elsevier Ltd. All rights reserved.

Validated Questionnaire of Maternal Attitude and Knowledge for Predicting Caries Risk in Children: Epidemiological Study in North Jakarta, Indonesia.

PubMed

Laksmiastuti, Sri Ratna; Budiardjo, Sarworini Bagio; Sutadi, Heriandi

2017-06-01

Predicting caries risk in children can be done by identifying caries risk factors. It is an important measure which contributes to best understanding of the cariogenic profile of the patient. Identification could be done by clinical examination and answering the questionnaire. We arrange the study to verify the questionnaire validation for predicting caries risk in children. The study was conducted on 62 pairs of mothers and their children, aged between 3 and 5 years. The questionnaire consists of 10 questions concerning mothers' attitude and knowledge about oral health. The reliability and validity test is based on Cronbach's alpha and correlation coefficient value. All question are reliable (Cronbach's alpha = 0.873) and valid (Corrected item-total item correlation >0.4). Five questionnaires of mother's attitude about oral health and five questionnaires of mother's knowledge about oral health are reliable and valid for predicting caries risk in children.

Determination and importance of temperature dependence of retention coefficient (RPHPLC) in QSAR model of nitrazepams' partition coefficient in bile acid micelles.

PubMed

Posa, Mihalj; Pilipović, Ana; Lalić, Mladena; Popović, Jovan

2011-02-15

Linear dependence between temperature (t) and retention coefficient (k, reversed phase HPLC) of bile acids is obtained. Parameters (a, intercept and b, slope) of the linear function k=f(t) highly correlate with bile acids' structures. Investigated bile acids form linear congeneric groups on a principal component (calculated from k=f(t)) score plot that are in accordance with conformations of the hydroxyl and oxo groups in a bile acid steroid skeleton. Partition coefficient (K(p)) of nitrazepam in bile acids' micelles is investigated. Nitrazepam molecules incorporated in micelles show modified bioavailability (depo effect, higher permeability, etc.). Using multiple linear regression method QSAR models of nitrazepams' partition coefficient, K(p) are derived on the temperatures of 25°C and 37°C. For deriving linear regression models on both temperatures experimentally obtained lipophilicity parameters are included (PC1 from data k=f(t)) and in silico descriptors of the shape of a molecule while on the higher temperature molecular polarisation is introduced. This indicates the fact that the incorporation mechanism of nitrazepam in BA micelles changes on the higher temperatures. QSAR models are derived using partial least squares method as well. Experimental parameters k=f(t) are shown to be significant predictive variables. Both QSAR models are validated using cross validation and internal validation method. PLS models have slightly higher predictive capability than MLR models. Copyright © 2010 Elsevier B.V. All rights reserved.

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

PubMed Central

Zhao, Manman; Zheng, Linfeng; Qiu, Chun

2017-01-01

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q2 = 0.565 (cross-validated correlation coefficient) and r2 = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR. PMID:28630865

A view on thermodynamics of concentrated electrolytes: Modification necessity for electrostatic contribution of osmotic coefficient

NASA Astrophysics Data System (ADS)

Sahu, Jyoti; Juvekar, Vinay A.

2018-05-01

Prediction of the osmotic coefficient of concentrated electrolytes is needed in a wide variety of industrial applications. There is a need to correctly segregate the electrostatic contribution to osmotic coefficient from nonelectrostatic contribution. This is achieved in a rational way in this work. Using the Robinson-Stokes-Glueckauf hydrated ion model to predict non-electrostatic contribution to the osmotic coefficient, it is shown that hydration number should be independent of concentration so that the observed linear dependence of osmotic coefficient on electrolyte concentration in high concentration range could be predicted. The hydration number of several electrolytes (LiCl, NaCl, KCl, MgCl2, and MgSO4) has been estimated by this method. The hydration number predicted by this model shows correct dependence on temperature. It is also shown that the electrostatic contribution to osmotic coefficient is underpredicted by the Debye-Hückel theory at concentration beyond 0.1 m. The Debye-Hückel theory is modified by introducing a concentration dependent hydrated ionic size. Using the present analysis, it is possible to correctly estimate the electrostatic contribution to the osmotic coefficient, beyond the range of validation of the D-H theory. This would allow development of a more fundamental model for electrostatic interaction at high electrolyte concentrations.

Independent external validation of predictive models for urinary dysfunction following external beam radiotherapy of the prostate: Issues in model development and reporting.

PubMed

Yahya, Noorazrul; Ebert, Martin A; Bulsara, Max; Kennedy, Angel; Joseph, David J; Denham, James W

2016-08-01

Most predictive models are not sufficiently validated for prospective use. We performed independent external validation of published predictive models for urinary dysfunctions following radiotherapy of the prostate. Multivariable models developed to predict atomised and generalised urinary symptoms, both acute and late, were considered for validation using a dataset representing 754 participants from the TROG 03.04-RADAR trial. Endpoints and features were harmonised to match the predictive models. The overall performance, calibration and discrimination were assessed. 14 models from four publications were validated. The discrimination of the predictive models in an independent external validation cohort, measured using the area under the receiver operating characteristic (ROC) curve, ranged from 0.473 to 0.695, generally lower than in internal validation. 4 models had ROC >0.6. Shrinkage was required for all predictive models' coefficients ranging from -0.309 (prediction probability was inverse to observed proportion) to 0.823. Predictive models which include baseline symptoms as a feature produced the highest discrimination. Two models produced a predicted probability of 0 and 1 for all patients. Predictive models vary in performance and transferability illustrating the need for improvements in model development and reporting. Several models showed reasonable potential but efforts should be increased to improve performance. Baseline symptoms should always be considered as potential features for predictive models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Modelling of individual subject ozone exposure response kinetics.

PubMed

Schelegle, Edward S; Adams, William C; Walby, William F; Marion, M Susan

2012-06-01

A better understanding of individual subject ozone (O(3)) exposure response kinetics will provide insight into how to improve models used in the risk assessment of ambient ozone exposure. To develop a simple two compartment exposure-response model that describes individual subject decrements in forced expiratory volume in one second (FEV(1)) induced by the acute inhalation of O(3) lasting up to 8 h. FEV(1) measurements of 220 subjects who participated in 14 previously completed studies were fit to the model using both particle swarm and nonlinear least squares optimization techniques to identify three subject-specific coefficients producing minimum "global" and local errors, respectively. Observed and predicted decrements in FEV(1) of the 220 subjects were used for validation of the model. Further validation was provided by comparing the observed O(3)-induced FEV(1) decrements in an additional eight studies with predicted values obtained using model coefficients estimated from the 220 subjects used in cross validation. Overall the individual subject measured and modeled FEV(1) decrements were highly correlated (mean R(2) of 0.69 ± 0.24). In addition, it was shown that a matrix of individual subject model coefficients can be used to predict the mean and variance of group decrements in FEV(1). This modeling approach provides insight into individual subject O(3) exposure response kinetics and provides a potential starting point for improving the risk assessment of environmental O(3) exposure.

Profiling the interaction mechanism of quinoline/quinazoline derivatives as MCHR1 antagonists: an in silico method.

PubMed

Wu, Mingwei; Li, Yan; Fu, Xinmei; Wang, Jinghui; Zhang, Shuwei; Yang, Ling

2014-09-01

Melanin concentrating hormone receptor 1 (MCHR1), a crucial regulator of energy homeostasis involved in the control of feeding and energy metabolism, is a promising target for treatment of obesity. In the present work, the up-to-date largest set of 181 quinoline/quinazoline derivatives as MCHR1 antagonists was subjected to both ligand- and receptor-based three-dimensional quantitative structure-activity (3D-QSAR) analysis applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The optimal predictable CoMSIA model exhibited significant validity with the cross-validated correlation coefficient (Q²) = 0.509, non-cross-validated correlation coefficient (R²(ncv)) = 0.841 and the predicted correlation coefficient (R²(pred)) = 0.745. In addition, docking studies and molecular dynamics (MD) simulations were carried out for further elucidation of the binding modes of MCHR1 antagonists. MD simulations in both water and lipid bilayer systems were performed. We hope that the obtained models and information may help to provide an insight into the interaction mechanism of MCHR1 antagonists and facilitate the design and optimization of novel antagonists as anti-obesity agents.

Subscores and Validity. Research Report. ETS RR-08-64

ERIC Educational Resources Information Center

Haberman, Shelby J.

2008-01-01

In educational testing, subscores may be provided based on a portion of the items from a larger test. One consideration in evaluation of such subscores is their ability to predict a criterion score. Two limitations on prediction exist. The first, which is well known, is that the coefficient of determination for linear prediction of the criterion…

Field determination and QSPR prediction of equilibrium-status soil/vegetation partition coefficient of PCDD/Fs.

PubMed

Li, Li; Wang, Qiang; Qiu, Xinghua; Dong, Yian; Jia, Shenglan; Hu, Jianxin

2014-07-15

Characterizing pseudo equilibrium-status soil/vegetation partition coefficient KSV, the quotient of respective concentrations in soil and vegetation of a certain substance at remote background areas, is essential in ecological risk assessment, however few previous attempts have been made for field determination and developing validated and reproducible structure-based estimates. In this study, KSV was calculated based on measurements of seventeen 2,3,7,8-substituted PCDD/F congeners in soil and moss (Dicranum angustum), and rouzi grass (Thylacospermum caespitosum) of two background sites, Ny-Ålesund of the Arctic and Zhangmu-Nyalam region of the Tibet Plateau, respectively. By both fugacity modeling and stepwise regression of field data, the air-water partition coefficient (KAW) and aqueous solubility (SW) were identified as the influential physicochemical properties. Furthermore, validated quantitative structure-property relationship (QSPR) model was developed to extrapolate the KSV prediction to all 210 PCDD/F congeners. Molecular polarizability, molecular size and molecular energy demonstrated leading effects on KSV. Copyright © 2014 Elsevier B.V. All rights reserved.

[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.

The validity of ACT-PEP test scores for predicting academic performance of registered nurses in BSN programs.

PubMed

Yang, J C; Noble, J

1990-01-01

This study investigated the validity of three American College Testing-Proficiency Examination Program (ACT-PEP) tests (Maternal and Child Nursing, Psychiatric/Mental Health Nursing, Adult Nursing) for predicting the academic performance of registered nurses (RNs) enrolled in bachelor's degree BSN programs nationwide. This study also examined RN students' performance on the ACT-PEP tests by their demographic characteristics: student's age, sex, race, student status (full- or part-time), and employment status (full- or part-time). The total sample for the three tests comprised 2,600 students from eight institutions nationwide. The median correlation coefficients between the three ACT-PEP tests and the semester grade point averages ranged from .36 to .56. Median correlation coefficients increased over time, supporting the stability of ACT-PEP test scores for predicting academic performance over time. The relative importance of selected independent variables for predicting academic performance was also examined; the most important variable for predicting academic performance was typically the ACT-PEP test score. Across the institutions, student demographic characteristics did not contribute significantly to explaining academic performance, over and above ACT-PEP scores.

Quantitative prediction of ionization effect on human skin permeability.

PubMed

Baba, Hiromi; Ueno, Yusuke; Hashida, Mitsuru; Yamashita, Fumiyoshi

2017-04-30

Although skin permeability of an active ingredient can be severely affected by its ionization in a dose solution, most of the existing prediction models cannot predict such impacts. To provide reliable predictors, we curated a novel large dataset of in vitro human skin permeability coefficients for 322 entries comprising chemically diverse permeants whose ionization fractions can be calculated. Subsequently, we generated thousands of computational descriptors, including LogD (octanol-water distribution coefficient at a specific pH), and analyzed the dataset using nonlinear support vector regression (SVR) and Gaussian process regression (GPR) combined with greedy descriptor selection. The SVR model was slightly superior to the GPR model, with externally validated squared correlation coefficient, root mean square error, and mean absolute error values of 0.94, 0.29, and 0.21, respectively. These models indicate that Log D is effective for a comprehensive prediction of ionization effects on skin permeability. In addition, the proposed models satisfied the statistical criteria endorsed in recent model validation studies. These models can evaluate virtually generated compounds at any pH; therefore, they can be used for high-throughput evaluations of numerous active ingredients and optimization of their skin permeability with respect to permeant ionization. Copyright © 2017 Elsevier B.V. All rights reserved.

A prediction model of compressor with variable-geometry diffuser based on elliptic equation and partial least squares

PubMed Central

Yang, Chuanlei; Wang, Yinyan; Wang, Hechun

2018-01-01

To achieve a much more extensive intake air flow range of the diesel engine, a variable-geometry compressor (VGC) is introduced into a turbocharged diesel engine. However, due to the variable diffuser vane angle (DVA), the prediction for the performance of the VGC becomes more difficult than for a normal compressor. In the present study, a prediction model comprising an elliptical equation and a PLS (partial least-squares) model was proposed to predict the performance of the VGC. The speed lines of the pressure ratio map and the efficiency map were fitted with the elliptical equation, and the coefficients of the elliptical equation were introduced into the PLS model to build the polynomial relationship between the coefficients and the relative speed, the DVA. Further, the maximal order of the polynomial was investigated in detail to reduce the number of sub-coefficients and achieve acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority of compressor performance prediction, the prediction results of this model were compared with those of the look-up table and back-propagation neural networks (BPNNs). The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than the look-up table and the BPNN methods under the same condition in VGC performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for the VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future. PMID:29410849

A prediction model of compressor with variable-geometry diffuser based on elliptic equation and partial least squares.

PubMed

Li, Xu; Yang, Chuanlei; Wang, Yinyan; Wang, Hechun

2018-01-01

To achieve a much more extensive intake air flow range of the diesel engine, a variable-geometry compressor (VGC) is introduced into a turbocharged diesel engine. However, due to the variable diffuser vane angle (DVA), the prediction for the performance of the VGC becomes more difficult than for a normal compressor. In the present study, a prediction model comprising an elliptical equation and a PLS (partial least-squares) model was proposed to predict the performance of the VGC. The speed lines of the pressure ratio map and the efficiency map were fitted with the elliptical equation, and the coefficients of the elliptical equation were introduced into the PLS model to build the polynomial relationship between the coefficients and the relative speed, the DVA. Further, the maximal order of the polynomial was investigated in detail to reduce the number of sub-coefficients and achieve acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority of compressor performance prediction, the prediction results of this model were compared with those of the look-up table and back-propagation neural networks (BPNNs). The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than the look-up table and the BPNN methods under the same condition in VGC performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for the VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future.

Measurement of fatigue: Comparison of the reliability and validity of single-item and short measures to a comprehensive measure.

PubMed

Kim, Hee-Ju; Abraham, Ivo

2017-01-01

Evidence is needed on the clinicometric properties of single-item or short measures as alternatives to comprehensive measures. We examined whether two single-item fatigue measures (i.e., Likert scale, numeric rating scale) or a short fatigue measure were comparable to a comprehensive measure in reliability (i.e., internal consistency and test-retest reliability) and validity (i.e., convergent, concurrent, and predictive validity) in Korean young adults. For this quantitative study, we selected the Functional Assessment of Chronic Illness Therapy-Fatigue for the comprehensive measure and the Profile of Mood States-Brief, Fatigue subscale for the short measure; and constructed two single-item measures. A total of 368 students from four nursing colleges in South Korea participated. We used Cronbach's alpha and item-total correlation for internal consistency reliability and intraclass correlation coefficient for test-retest reliability. We assessed Pearson's correlation with a comprehensive measure for convergent validity, with perceived stress level and sleep quality for concurrent validity and the receiver operating characteristic curve for predictive validity. The short measure was comparable to the comprehensive measure in internal consistency reliability (Cronbach's alpha=0.81 vs. 0.88); test-retest reliability (intraclass correlation coefficient=0.66 vs. 0.61); convergent validity (r with comprehensive measure=0.79); concurrent validity (r with perceived stress=0.55, r with sleep quality=0.39) and predictive validity (area under curve=0.88). Single-item measures were not comparable to the comprehensive measure. A short fatigue measure exhibited similar levels of reliability and validity to the comprehensive measure in Korean young adults. Copyright © 2016 Elsevier Ltd. All rights reserved.

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

The Effectiveness of Academic Interest Scales in Predicting College Achievement.

ERIC Educational Resources Information Center

Johnson, Richard W.

The predictive validities of various SVIB academic interest scales were assessed with first semester freshman males at the University of Massachusetts. Both the Rust and Ryan and the Campbell and Johansson scales contributed significantly, albeit modestly, to a multiple correlation coefficient consisting of high school rank and scholastic aptitude…

CoMFA and CoMSIA studies on C-aryl glucoside SGLT2 inhibitors as potential anti-diabetic agents.

PubMed

Vyas, V K; Bhatt, H G; Patel, P K; Jalu, J; Chintha, C; Gupta, N; Ghate, M

2013-01-01

SGLT2 has become a target of therapeutic interest in diabetes research. CoMFA and CoMSIA studies were performed on C-aryl glucoside SGLT2 inhibitors (180 analogues) as potential anti-diabetic agents. Three different alignment strategies were used for the compounds. The best CoMFA and CoMSIA models were obtained by means of Distill rigid body alignment of training and test sets, and found statistically significant with cross-validated coefficients (q²) of 0.602 and 0.618, respectively, and conventional coefficients (r²) of 0.905 and 0.902, respectively. Both models were validated by a test set of 36 compounds giving satisfactory predicted correlation coefficients (r² pred) of 0.622 and 0.584 for CoMFA and CoMSIA models, respectively. A comparison was made with earlier 3D QSAR study on SGLT2 inhibitors, which shows that our 3D QSAR models are better than earlier models to predict good inhibitory activity. CoMFA and CoMSIA models generated in this work can provide useful information to design new compounds and helped in prediction of activity prior to synthesis.

A Note on the Incremental Validity of Aggregate Predictors.

ERIC Educational Resources Information Center

Day, H. D.; Marshall, David

Three computer simulations were conducted to show that very high aggregate predictive validity coefficients can occur when the across-case variability in absolute score stability occurring in both the predictor and criterion matrices is quite small. In light of the increase in internal consistency reliability achieved by the method of aggregation…

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.

Systematic bias of correlation coefficient may explain negative accuracy of genomic prediction.

PubMed

Zhou, Yao; Vales, M Isabel; Wang, Aoxue; Zhang, Zhiwu

2017-09-01

Accuracy of genomic prediction is commonly calculated as the Pearson correlation coefficient between the predicted and observed phenotypes in the inference population by using cross-validation analysis. More frequently than expected, significant negative accuracies of genomic prediction have been reported in genomic selection studies. These negative values are surprising, given that the minimum value for prediction accuracy should hover around zero when randomly permuted data sets are analyzed. We reviewed the two common approaches for calculating the Pearson correlation and hypothesized that these negative accuracy values reflect potential bias owing to artifacts caused by the mathematical formulas used to calculate prediction accuracy. The first approach, Instant accuracy, calculates correlations for each fold and reports prediction accuracy as the mean of correlations across fold. The other approach, Hold accuracy, predicts all phenotypes in all fold and calculates correlation between the observed and predicted phenotypes at the end of the cross-validation process. Using simulated and real data, we demonstrated that our hypothesis is true. Both approaches are biased downward under certain conditions. The biases become larger when more fold are employed and when the expected accuracy is low. The bias of Instant accuracy can be corrected using a modified formula. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Pilot Comparative Study of Quantitative Ultrasound, Conventional Ultrasound, and MRI for Predicting Histology-Determined Steatosis Grade in Adult Nonalcoholic Fatty Liver Disease

PubMed Central

Paige, Jeremy S.; Bernstein, Gregory S.; Heba, Elhamy; Costa, Eduardo A. C.; Fereirra, Marilia; Wolfson, Tanya; Gamst, Anthony C.; Valasek, Mark A.; Lin, Grace Y.; Han, Aiguo; Erdman, John W.; O’Brien, William D.; Andre, Michael P.; Loomba, Rohit; Sirlin, Claude B.

2017-01-01

OBJECTIVE The purpose of this study is to explore the diagnostic performance of two investigational quantitative ultrasound (QUS) parameters, attenuation coefficient and backscatter coefficient, in comparison with conventional ultrasound (CUS) and MRI-estimated proton density fat fraction (PDFF) for predicting histology-confirmed steatosis grade in adults with nonalcoholic fatty liver disease (NAFLD). SUBJECTS AND METHODS In this prospectively designed pilot study, 61 adults with histology-confirmed NAFLD were enrolled from September 2012 to February 2014. Subjects underwent QUS, CUS, and MRI examinations within 100 days of clinical-care liver biopsy. QUS parameters (attenuation coefficient and backscatter coefficient) were estimated using a reference phantom technique by two analysts independently. Three-point ordinal CUS scores intended to predict steatosis grade (1, 2, or 3) were generated independently by two radiologists on the basis of QUS features. PDFF was estimated using an advanced chemical shift–based MRI technique. Using histologic examination as the reference standard, ROC analysis was performed. Optimal attenuation coefficient, backscatter coefficient, and PDFF cutoff thresholds were identified, and the accuracy of attenuation coefficient, backscatter coefficient, PDFF, and CUS to predict steatosis grade was determined. Interobserver agreement for attenuation coefficient, backscatter coefficient, and CUS was analyzed. RESULTS CUS had 51.7% grading accuracy. The raw and cross-validated steatosis grading accuracies were 61.7% and 55.0%, respectively, for attenuation coefficient, 68.3% and 68.3% for backscatter coefficient, and 76.7% and 71.3% for MRI-estimated PDFF. Interobserver agreements were 53.3% for CUS (κ = 0.61), 90.0% for attenuation coefficient (κ = 0.87), and 71.7% for backscatter coefficient (κ = 0.82) (p < 0.0001 for all). CONCLUSION Preliminary observations suggest that QUS parameters may be more accurate and provide higher interobserver agreement than CUS for predicting hepatic steatosis grade in patients with NAFLD. PMID:28267360

A Pilot Comparative Study of Quantitative Ultrasound, Conventional Ultrasound, and MRI for Predicting Histology-Determined Steatosis Grade in Adult Nonalcoholic Fatty Liver Disease.

PubMed

Paige, Jeremy S; Bernstein, Gregory S; Heba, Elhamy; Costa, Eduardo A C; Fereirra, Marilia; Wolfson, Tanya; Gamst, Anthony C; Valasek, Mark A; Lin, Grace Y; Han, Aiguo; Erdman, John W; O'Brien, William D; Andre, Michael P; Loomba, Rohit; Sirlin, Claude B

2017-05-01

The purpose of this study is to explore the diagnostic performance of two investigational quantitative ultrasound (QUS) parameters, attenuation coefficient and backscatter coefficient, in comparison with conventional ultrasound (CUS) and MRI-estimated proton density fat fraction (PDFF) for predicting histology-confirmed steatosis grade in adults with nonalcoholic fatty liver disease (NAFLD). In this prospectively designed pilot study, 61 adults with histology-confirmed NAFLD were enrolled from September 2012 to February 2014. Subjects underwent QUS, CUS, and MRI examinations within 100 days of clinical-care liver biopsy. QUS parameters (attenuation coefficient and backscatter coefficient) were estimated using a reference phantom technique by two analysts independently. Three-point ordinal CUS scores intended to predict steatosis grade (1, 2, or 3) were generated independently by two radiologists on the basis of QUS features. PDFF was estimated using an advanced chemical shift-based MRI technique. Using histologic examination as the reference standard, ROC analysis was performed. Optimal attenuation coefficient, backscatter coefficient, and PDFF cutoff thresholds were identified, and the accuracy of attenuation coefficient, backscatter coefficient, PDFF, and CUS to predict steatosis grade was determined. Interobserver agreement for attenuation coefficient, backscatter coefficient, and CUS was analyzed. CUS had 51.7% grading accuracy. The raw and cross-validated steatosis grading accuracies were 61.7% and 55.0%, respectively, for attenuation coefficient, 68.3% and 68.3% for backscatter coefficient, and 76.7% and 71.3% for MRI-estimated PDFF. Interobserver agreements were 53.3% for CUS (κ = 0.61), 90.0% for attenuation coefficient (κ = 0.87), and 71.7% for backscatter coefficient (κ = 0.82) (p < 0.0001 for all). Preliminary observations suggest that QUS parameters may be more accurate and provide higher interobserver agreement than CUS for predicting hepatic steatosis grade in patients with NAFLD.

Development and testing of the Test of Functional Health Literacy in Dentistry (TOFHLiD).

PubMed

Gong, Debra A; Lee, Jessica Y; Rozier, R Gary; Pahel, Bhavna T; Richman, Julia A; Vann, William F

2007-01-01

This study aims to evaluate the reliability and validity of the Test of Functional Health Literacy in Dentistry (TOFHLiD), a new instrument to measure functional oral health literacy. TOFHLiD uses text passages and prompts related to fluoride use and access to care to assess reading comprehension and numerical ability. Parents of pediatric dental patients (n = 102) were administered TOFHLiD, a medical literacy comprehension test (TOFHLA), and two word recognition tests [Rapid Estimate of Adult Literacy in Dentistry (REALD), Rapid Estimate of Adult Literacy in Medicine (REALM)]. This design provided assessments of dental and medical health literacy by all subjects, both measured with two different methods (reading/numeracy ability and word recognition). Construct validity of TOFHLiD was assessed by entering the correlation coefficients for all pairwise comparisons of literacy instruments into a multitrait-multimethod matrix. Internal reliability of TOFHLiD was assessed with Cronbach's alpha. Criterion-related predictive validity was tested by associations between the TOFHLiD scores and the three measures of oral health in multivariate regression analyses. The correlation coefficient for TOFHLiD and REALD-99 scores (monotrait-heteromethod) was high (r = 0.82, P < 0.05). Coefficients between TOFHLiD and TOFHLA (heterotrait-monomethod: r = 0.52) and REALM (heterotrait-heteromethod: r = 0.53) were smaller than coefficients for convergent validity Cronbach's alpha for TOFHLiD was 0.63. TOFHLiD was positively correlated with OHIP-14 (P < 0.05), but not with parent or child oral health. TOFHLA was not related to dental outcomes. TOFHLiD demonstrates good convergent validity but only moderate ability to discriminate between dental and medical health literacy. Its predictive validity is only partially established, and internal consistency just meets the threshold for acceptability. Results provide solid support for more research, but not widespread use in clinical or public health practice.

Differential validity of the Defense Mechanism Manual for the TAT between Asian Americans and Whites. Thematic Apperception Test.

PubMed

Hibbard, S; Tang, P C; Latko, R; Park, J H; Munn, S; Bolz, S; Somerville, A

2000-12-01

Thematic Apperception Test (Murray, 1943) responses of 69 Asian American (hereafter, Asian) and 83 White students were coded for defenses according to the Defense Mechanism Manual (Cramer, 1991b) and studied for differential validity in predicting paper-and-pencil measures of relevant constructs. Three tests for differential validity were used: (a) differences between validity coefficients, (b) interactions between predictor and ethnicity in criterion prediction, and (c) differences between groups in mean prediction errors using a common regression equation. Modest differential validity was found. It was surprising that the DMM scales were slightly stronger predictors of their criteria among Asians than among Whites and when a common predictor was used, desirable criteria were overpredicted for Asians, whereas undesirable ones were overpredicted for Whites. The results were not affected by acculturation level or English vocabulary among the Asians.

Prediction and Validation of Mars Pathfinder Hypersonic Aerodynamic Data Base

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Braun, Robert D.; Weilmuenster, K. James; Mitcheltree, Robert A.; Engelund, Walter C.; Powell, Richard W.

1998-01-01

Postflight analysis of the Mars Pathfinder hypersonic, continuum aerodynamic data base is presented. Measured data include accelerations along the body axis and axis normal directions. Comparisons of preflight simulation and measurements show good agreement. The prediction of two static instabilities associated with movement of the sonic line from the shoulder to the nose and back was confirmed by measured normal accelerations. Reconstruction of atmospheric density during entry has an uncertainty directly proportional to the uncertainty in the predicted axial coefficient. The sensitivity of the moment coefficient to freestream density, kinetic models and center-of-gravity location are examined to provide additional consistency checks of the simulation with flight data. The atmospheric density as derived from axial coefficient and measured axial accelerations falls within the range required for sonic line shift and static stability transition as independently determined from normal accelerations.

Design, synthesis, pharmacological evaluation and in silico ADMET prediction of novel substituted benzimidazole derivatives as angiotensin II-AT1 receptor antagonists based on predictive 3D QSAR models.

PubMed

Vyas, V K; Gupta, N; Ghate, M; Patel, S

2014-01-01

In this study we designed novel substituted benzimidazole derivatives and predicted their absorption, distribution, metabolism, excretion and toxicity (ADMET) properties, based on a predictive 3D QSAR study on 132 substituted benzimidazoles as AngII-AT1 receptor antagonists. The two best predicted compounds were synthesized and evaluated for AngII-AT1 receptor antagonism. Three different alignment tools for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used. The best 3D QSAR models were obtained using the rigid body (Distill) alignment method. CoMFA and CoMSIA models were found to be statistically significant with leave-one-out correlation coefficients (q(2)) of 0.630 and 0.623, respectively, cross-validated coefficients (r(2)cv) of 0.651 and 0.630, respectively, and conventional coefficients of determination (r(2)) of 0.848 and 0.843, respectively. 3D QSAR models were validated using a test set of 24 compounds, giving satisfactory predicted results (r(2)pred) of 0.727 and 0.689 for the CoMFA and CoMSIA models, respectively. We have identified some key features in substituted benzimidazole derivatives, such as lipophilicity and H-bonding at the 2- and 5-positions of the benzimidazole nucleus, respectively, for AT1 receptor antagonistic activity. We designed 20 novel substituted benzimidazole derivatives and predicted their activity. In silico ADMET properties were also predicted for these designed molecules. Finally, the compounds with best predicted activity were synthesized and evaluated for in vitro angiotensin II-AT1 receptor antagonism.

Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies.

PubMed

Nayana, M Ravi Shashi; Sekhar, Y Nataraja; Nandyala, Haritha; Muttineni, Ravikumar; Bairy, Santosh Kumar; Singh, Kriti; Mahmood, S K

2008-10-01

In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.

Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy

NASA Astrophysics Data System (ADS)

Ying, Yibin; Yu, Haiyan; Pan, Xingxiang; Lin, Tao

2006-10-01

To evaluate the applicability of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining ethanol concentration of Chinese rice wine in square brown glass bottle, transmission spectra of 100 bottled Chinese rice wine samples were collected in the spectral range of 350-1200 nm. Statistical equations were established between the reference data and VIS-NIR spectra by partial least squares (PLS) regression method. Performance of three kinds of mathematical treatment of spectra (original spectra, first derivative spectra and second derivative spectra) were also discussed. The PLS models of original spectra turned out better results, with higher correlation coefficient in calibration (R cal) of 0.89, lower root mean standard error of calibration (RMSEC) of 0.165, and lower root mean standard error of cross validation (RMSECV) of 0.179. Using original spectra, PLS models for ethanol concentration prediction were developed. The R cal and the correlation coefficient in validation (R val) were 0.928 and 0.875, respectively; and the RMSEC and the root mean standard error of validation (RMSEP) were 0.135 (%, v v -1) and 0.177 (%, v v -1), respectively. The results demonstrated that VIS-NIR spectroscopy could be used to predict ethanol concentration in bottled Chinese rice wine.

Validation of a noninvasive maturity estimate relative to skeletal age in youth football players.

PubMed

Malina, Robert M; Dompier, Thomas P; Powell, John W; Barron, Mary J; Moore, Marguerite T

2007-09-01

To validate a non-invasive measure of biological maturity (percentage of predicted mature height at a given age) with an established indicator of maturity [skeletal age (SA)] in youth American football players. Cross-sectional. Two communities in central Michigan. 143 youth football players 9.27 to 14.24 years. Height and weight were measured, and hand-wrist radiographs were taken. SA assessed with the Fels method was the criterion measure of maturity status. Chronological age (CA), height, and weight of the player and midparent height were used to predict mature height; current height of the player was expressed as a percentage of his predicted mature height as a noninvasive estimate of biological maturity status. Boys' maturation was classified as late, on time, or early maturing on the basis of the difference between SA and CA and of present height expressed as a percentage of predicted mature height. Kappa coefficients and Spearman rank-order correlations were calculated. Characteristics of players concordant and discordant for maturity classification with SA and percentage of predicted mature height were compared with MANCOVA. Concordance between methods of maturity classification was 62%. The Kappa coefficient, 0.46 (95% CI 0.19 to 0.59) and Spearman rank-order correlation, rs = 0.52 (P < 0.001) were moderate. Players discordant for maturity status varied in midparent height and percentage of predicted mature height, but not in predicted mature height. Percentage of predicted mature height is a reasonably valid estimate of biological maturity status in this sample of youth football players.

Three phase heat and mass transfer model for unsaturated soil freezing process: Part 2 - model validation

NASA Astrophysics Data System (ADS)

Zhang, Yaning; Xu, Fei; Li, Bingxi; Kim, Yong-Song; Zhao, Wenke; Xie, Gongnan; Fu, Zhongbin

2018-04-01

This study aims to validate the three-phase heat and mass transfer model developed in the first part (Three phase heat and mass transfer model for unsaturated soil freezing process: Part 1 - model development). Experimental results from studies and experiments were used for the validation. The results showed that the correlation coefficients for the simulated and experimental water contents at different soil depths were between 0.83 and 0.92. The correlation coefficients for the simulated and experimental liquid water contents at different soil temperatures were between 0.95 and 0.99. With these high accuracies, the developed model can be well used to predict the water contents at different soil depths and temperatures.

An integrated fiber-optic probe combined with support vector regression for fast estimation of optical properties of turbid media.

PubMed

Zhou, Yang; Fu, Xiaping; Ying, Yibin; Fang, Zhenhuan

2015-06-23

A fiber-optic probe system was developed to estimate the optical properties of turbid media based on spatially resolved diffuse reflectance. Because of the limitations in numerical calculation of radiative transfer equation (RTE), diffusion approximation (DA) and Monte Carlo simulations (MC), support vector regression (SVR) was introduced to model the relationship between diffuse reflectance values and optical properties. The SVR models of four collection fibers were trained by phantoms in calibration set with a wide range of optical properties which represented products of different applications, then the optical properties of phantoms in prediction set were predicted after an optimal searching on SVR models. The results indicated that the SVR model was capable of describing the relationship with little deviation in forward validation. The correlation coefficient (R) of reduced scattering coefficient μ'(s) and absorption coefficient μ(a) in the prediction set were 0.9907 and 0.9980, respectively. The root mean square errors of prediction (RMSEP) of μ'(s) and μ(a) in inverse validation were 0.411 cm(-1) and 0.338 cm(-1), respectively. The results indicated that the integrated fiber-optic probe system combined with SVR model were suitable for fast and accurate estimation of optical properties of turbid media based on spatially resolved diffuse reflectance. Copyright © 2015 Elsevier B.V. All rights reserved.

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows.

PubMed

Visentin, G; McDermott, A; McParland, S; Berry, D P; Kenny, O A; Brodkorb, A; Fenelon, M A; De Marchi, M

2015-09-01

Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n=713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000cm(-1) were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Validation of the Hindi version of National Institute of Health Stroke Scale.

PubMed

Prasad, Kameshwar; Dash, Deepa; Kumar, Amit

2012-01-01

To determine the reliability and validity of the National Institute of Health Stroke Scale (NIHSS) with the Hindi and Indian adaptation of items 9 and 10. NIHSS items 9 and 10 were modified and culturally adapted at All India Institute of Medical Sciences (AIIMS) and the resulting version was termed as Hindi version (HV-NIHSS). HV-NIHSS was applied by two independent investigators on 107 patients with stroke. Inter-observer agreement and intra-class correlation coefficients were calculated. The predictive validity of the HV-NIHSS was calculated using functional outcome after three months in the form of modified Rankin Scale (mRS) and Barthel Index (BI). The study included 107 patients of stroke recruited from a tertiary referral hospital at Delhi between November 1, 2009, and October 1, 2010; the mean age of these patients was 56.26±13.84 years and 65.4% of them had suffered ischemic stroke. Inter-rater reliability was high between the two examiners, with Pearson's r ranging from 0.72 to 0.99 for the 15 items on the Scale. Intra-class correlation coefficient for the total score was 0.995 (95% CI-0.993-0.997). Concurrent construct validity was established between HV-NIHSS and baseline Glasgow Coma Scale, with a high correlation (Spearman coefficient = -0.863, P<.001). Predictive validity was also established with BI at three months (Spearman's rho: -0.829, P<.001) and with mRS at three months (Spearman's rho: 0.851, P<0.001). This study shows that a Hindi language version of the NIHSS developed at AIIMS appears reliable and valid when applied to a Hindi-speaking population.

Comparison between genetic parameters of cheese yield and nutrient recovery or whey loss traits measured from individual model cheese-making methods or predicted from unprocessed bovine milk samples using Fourier-transform infrared spectroscopy.

PubMed

Bittante, G; Ferragina, A; Cipolat-Gotet, C; Cecchinato, A

2014-10-01

Cheese yield is an important technological trait in the dairy industry. The aim of this study was to infer the genetic parameters of some cheese yield-related traits predicted using Fourier-transform infrared (FTIR) spectral analysis and compare the results with those obtained using an individual model cheese-producing procedure. A total of 1,264 model cheeses were produced using 1,500-mL milk samples collected from individual Brown Swiss cows, and individual measurements were taken for 10 traits: 3 cheese yield traits (fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 milk nutrient recovery traits (fat, protein, total solids, and energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits per cow (fresh curd, total solids, and water weight of the curd). Each unprocessed milk sample was analyzed using a MilkoScan FT6000 (Foss, Hillerød, Denmark) over the spectral range, from 5,000 to 900 wavenumber × cm(-1). The FTIR spectrum-based prediction models for the previously mentioned traits were developed using modified partial least-square regression. Cross-validation of the whole data set yielded coefficients of determination between the predicted and measured values in cross-validation of 0.65 to 0.95 for all traits, except for the recovery of fat (0.41). A 3-fold external validation was also used, in which the available data were partitioned into 2 subsets: a training set (one-third of the herds) and a testing set (two-thirds). The training set was used to develop calibration equations, whereas the testing subsets were used for external validation of the calibration equations and to estimate the heritabilities and genetic correlations of the measured and FTIR-predicted phenotypes. The coefficients of determination between the predicted and measured values in cross-validation results obtained from the training sets were very similar to those obtained from the whole data set, but the coefficient of determination of validation values for the external validation sets were much lower for all traits (0.30 to 0.73), and particularly for fat recovery (0.05 to 0.18), for the training sets compared with the full data set. For each testing subset, the (co)variance components for the measured and FTIR-predicted phenotypes were estimated using bivariate Bayesian analyses and linear models. The intraherd heritabilities for the predicted traits obtained from our internal cross-validation using the whole data set ranged from 0.085 for daily yield of curd solids to 0.576 for protein recovery, and were similar to those obtained from the measured traits (0.079 to 0.586, respectively). The heritabilities estimated from the testing data set used for external validation were more variable but similar (on average) to the corresponding values obtained from the whole data set. Moreover, the genetic correlations between the predicted and measured traits were high in general (0.791 to 0.996), and they were always higher than the corresponding phenotypic correlations (0.383 to 0.995), especially for the external validation subset. In conclusion, we herein report that application of the cross-validation technique to the whole data set tended to overestimate the predictive ability of FTIR spectra, give more precise phenotypic predictions than the calibrations obtained using smaller data sets, and yield genetic correlations similar to those obtained from the measured traits. Collectively, our findings indicate that FTIR predictions have the potential to be used as indicator traits for the rapid and inexpensive selection of dairy populations for improvement of cheese yield, milk nutrient recovery in curd, and daily cheese production per cow. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predictive Validity of the Body Adiposity Index in Overweight and Obese Adults Using Dual-Energy X-ray Absorptiometry

PubMed Central

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge Enrique; González-Ruíz, Katherine; Vivas, Andrés; García-Hermoso, Antonio; Triana-Reina, Hector Reynaldo

2016-01-01

The body adiposity index (BAI) is a recent anthropometric measure proven to be valid in predicting body fat percentage (BF%) in some populations. However, the results have been inconsistent across populations. This study was designed to verify the validity of BAI in predicting BF% in a sample of overweight/obese adults, using dual-energy X-ray absorptiometry (DEXA) as the reference method. A cross-sectional study was conducted in 48 participants (54% women, mean age 41.0 ± 7.3 years old). DEXA was used as the “gold standard” to determine BF%. Pearson’s correlation coefficient was used to evaluate the association between BAI and BF%, as assessed by DEXA. A paired sample t-test was used to test differences in mean BF% obtained with BAI and DEXA methods. To evaluate the concordance between BF% as measured by DEXA and as estimated by BAI, we used Lin’s concordance correlation coefficient and Bland–Altman agreement analysis. The correlation between BF% obtained by DEXA and that estimated by BAI was r = 0.844, p < 0.001. Paired t-test showed a significant mean difference in BF% between methods (BAI = 33.3 ± 6.2 vs. DEXA 39.0 ± 6.1; p < 0.001). The bias of the BAI was −6.0 ± 3.0 BF% (95% CI = −12.0 to 1.0), indicating that the BAI method significantly underestimated the BF% compared to the reference method. Lin’s concordance correlation coefficient was considered stronger (ρc = 0.923, 95% CI = 0.862 to 0.957). In obese adults, BAI presented low agreement with BF% measured by DEXA; therefore, BAI is not recommended for BF% prediction in this overweight/obese sample studied. PMID:27916871

Aqueous Binary Lanthanide(III) Nitrate Ln(NO3)3 Electrolytes Revisited: Extended Pitzer and Bromley Treatments

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

Chatterjee, Sayandev; Campbell, Emily L.; Neiner, Doinita

To date, only limited thermodynamic models describing activity coefficients of the aqueous solutions of lanthanide ions are available. This work expands the existing experimental osmotic coefficient data obtained by classical isopiestic technique for the aqueous binary trivalent lanthanide nitrate Ln(NO3)3 solutions using a combination of water activity and vapor pressure osmometry measurements. The combined osmotic coefficient database for each aqueous lanthanide nitrate at 25°C, consisting of literature available data as well as data obtained in this work, was used to test the validity of Pitzer and Bromley thermodynamic models for the accurate prediction of mean molal activity coefficients of themore » Ln(NO3)3 solutions in wide concentration ranges. The new and improved Pitzer and Bromley parameters were calculated. It was established that the Ln(NO3)3 activity coefficients in the solutions with ionic strength up to 12 mol kg-1 can be estimated by both Pitzer and single-parameter Bromley models, even though the latter provides for more accurate prediction, particularly in the lower ionic strength regime (up to 6 mol kg-1). On the other hand for the concentrated solutions, the extended three-parameter Bromley model can be employed to predict the Ln(NO3)3 activity coefficients with remarkable accuracy. The accuracy of the extended Bromley model in predicting the activity coefficients was greater than ~95% and ~90% for all solutions with the ionic strength up to 12 mol kg-1 and and 20 mol kg-1, respectively. This is the first time that the activity coefficients for concentrated lanthanide solutions have been predicted with such a remarkable accuracy.« less

Application of the Monte Carlo method for building up models for octanol-water partition coefficient of platinum complexes

NASA Astrophysics Data System (ADS)

Toropov, Andrey A.; Toropova, Alla P.

2018-06-01

Predictive model of logP for Pt(II) and Pt(IV) complexes built up with the Monte Carlo method using the CORAL software has been validated with six different splits into the training and validation sets. The improving of the predictive potential of models for six different splits has been obtained using so-called index of ideality of correlation. The suggested models give possibility to extract molecular features, which cause the increase or vice versa decrease of the logP.

Rotordynamic Instability Problems in High-Performance Turbomachinery

NASA Technical Reports Server (NTRS)

1984-01-01

Rotordynamics and predictions on the stability of characteristics of high performance turbomachinery were discussed. Resolutions of problems on experimental validation of the forces that influence rotordynamics were emphasized. The programs to predict or measure forces and force coefficients in high-performance turbomachinery are illustrated. Data to design new machines with enhanced stability characteristics or upgrading existing machines are presented.

The Measurement and Prediction of Rotordynamic Forces for Labyrinth Seals

DTIC Science & Technology

1988-03-01

Leakage of Steam Through Labyrinth Seals ," Transactions ASME, vol. 57...stiffness and damping) coefficients and leakage characteristics were completed for labyrinth -rotor/hofleycombe- Istator seals . Comparisons to labyrinth -rotor...range of labyrinth - seal con- figurations, and U (c) the development and validation of "bulk-flow" models for the prediction of leakage

Distress modeling for DARWin-ME : final report.

DOT National Transportation Integrated Search

2013-12-01

Distress prediction models, or transfer functions, are key components of the Pavement M-E Design and relevant analysis. The accuracy of such models depends on a successful process of calibration and subsequent validation of model coefficients in the ...

Quantitative determination of additive Chlorantraniliprole in Abamectin preparation: Investigation of bootstrapping soft shrinkage approach by mid-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Yan, Hong; Song, Xiangzhong; Tian, Kuangda; Chen, Yilin; Xiong, Yanmei; Min, Shungeng

2018-02-01

A novel method, mid-infrared (MIR) spectroscopy, which enables the determination of Chlorantraniliprole in Abamectin within minutes, is proposed. We further evaluate the prediction ability of four wavelength selection methods, including bootstrapping soft shrinkage approach (BOSS), Monte Carlo uninformative variable elimination (MCUVE), genetic algorithm partial least squares (GA-PLS) and competitive adaptive reweighted sampling (CARS) respectively. The results showed that BOSS method obtained the lowest root mean squared error of cross validation (RMSECV) (0.0245) and root mean squared error of prediction (RMSEP) (0.0271), as well as the highest coefficient of determination of cross-validation (Qcv2) (0.9998) and the coefficient of determination of test set (Q2test) (0.9989), which demonstrated that the mid infrared spectroscopy can be used to detect Chlorantraniliprole in Abamectin conveniently. Meanwhile, a suitable wavelength selection method (BOSS) is essential to conducting a component spectral analysis.

Three-parameter modeling of the soil sorption of acetanilide and triazine herbicide derivatives.

PubMed

Freitas, Mirlaine R; Matias, Stella V B G; Macedo, Renato L G; Freitas, Matheus P; Venturin, Nelson

2014-02-01

Herbicides have widely variable toxicity and many of them are persistent soil contaminants. Acetanilide and triazine family of herbicides have widespread use, but increasing interest for the development of new herbicides has been rising to increase their effectiveness and to diminish environmental hazard. The environmental risk of new herbicides can be accessed by estimating their soil sorption (logKoc), which is usually correlated to the octanol/water partition coefficient (logKow). However, earlier findings have shown that this correlation is not valid for some acetanilide and triazine herbicides. Thus, easily accessible quantitative structure-property relationship models are required to predict logKoc of analogues of the these compounds. Octanol/water partition coefficient, molecular weight and volume were calculated and then regressed against logKoc for two series of acetanilide and triazine herbicides using multiple linear regression, resulting in predictive and validated models.

Use of the Ames Check Standard Model for the Validation of Wall Interference Corrections

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Amaya, M.; Flach, R.

2018-01-01

The new check standard model of the NASA Ames 11-ft Transonic Wind Tunnel was chosen for a future validation of the facility's wall interference correction system. The chosen validation approach takes advantage of the fact that test conditions experienced by a large model in the slotted part of the tunnel's test section will change significantly if a subset of the slots is temporarily sealed. Therefore, the model's aerodynamic coefficients have to be recorded, corrected, and compared for two different test section configurations in order to perform the validation. Test section configurations with highly accurate Mach number and dynamic pressure calibrations were selected for the validation. First, the model is tested with all test section slots in open configuration while keeping the model's center of rotation on the tunnel centerline. In the next step, slots on the test section floor are sealed and the model is moved to a new center of rotation that is 33 inches below the tunnel centerline. Then, the original angle of attack sweeps are repeated. Afterwards, wall interference corrections are applied to both test data sets and response surface models of the resulting aerodynamic coefficients in interference-free flow are generated. Finally, the response surface models are used to predict the aerodynamic coefficients for a family of angles of attack while keeping dynamic pressure, Mach number, and Reynolds number constant. The validation is considered successful if the corrected aerodynamic coefficients obtained from the related response surface model pair show good agreement. Residual differences between the corrected coefficient sets will be analyzed as well because they are an indicator of the overall accuracy of the facility's wall interference correction process.

Calibration and prediction of removal function in magnetorheological finishing.

PubMed

Dai, Yifan; Song, Ci; Peng, Xiaoqiang; Shi, Feng

2010-01-20

A calibrated and predictive model of the removal function has been established based on the analysis of a magnetorheological finishing (MRF) process. By introducing an efficiency coefficient of the removal function, the model can be used to calibrate the removal function in a MRF figuring process and to accurately predict the removal function of a workpiece to be polished whose material is different from the spot part. Its correctness and feasibility have been validated by simulations. Furthermore, applying this model to the MRF figuring experiments, the efficiency coefficient of the removal function can be identified accurately to make the MRF figuring process deterministic and controllable. Therefore, all the results indicate that the calibrated and predictive model of the removal function can improve the finishing determinacy and increase the model applicability in a MRF process.

Determination of polyparameter linear free energy relationship (pp-LFER) substance descriptors for established and alternative flame retardants.

PubMed

Stenzel, Angelika; Goss, Kai-Uwe; Endo, Satoshi

2013-02-05

Polyparameter linear free energy relationships (pp-LFERs) can predict partition coefficients for a multitude of environmental and biological phases with high accuracy. In this work, the pp-LFER substance descriptors of 40 established and alternative flame retardants (e.g., polybrominated diphenyl ethers, hexabromocyclododecane, bromobenzenes, trialkyl phosphates) were determined experimentally. In total, 251 data for gas-chromatographic (GC) retention times and liquid/liquid partition coefficients (K) were measured and used to calibrate the pp-LFER substance descriptors. Substance descriptors were validated through a comparison between predicted and experimental log K for the systems octanol/water (K(ow)), water/air (K(wa)), organic carbon/water (K(oc)) and liposome/water (K(lipw)), revealing a high reliability of pp-LFER predictions based on our descriptors. For instance, the difference between predicted and experimental log K(ow) was <0.3 log units for 17 out of 21 compounds for which experimental values were available. Moreover, we found an indication that the H-bond acceptor value (B) depends on the solvent for some compounds. Thus, for predicting environmentally relevant partition coefficients it is important to determine B values using measurements in aqueous systems. The pp-LFER descriptors calibrated in this study can be used to predict partition coefficients for which experimental data are unavailable, and the predicted values can serve as references for further experimental measurements.

Prediction and validation of diffusion coefficients in a model drug delivery system using microsecond atomistic molecular dynamics simulation and vapour sorption analysis.

PubMed

Forrey, Christopher; Saylor, David M; Silverstein, Joshua S; Douglas, Jack F; Davis, Eric M; Elabd, Yossef A

2014-10-14

Diffusion of small to medium sized molecules in polymeric medical device materials underlies a broad range of public health concerns related to unintended leaching from or uptake into implantable medical devices. However, obtaining accurate diffusion coefficients for such systems at physiological temperature represents a formidable challenge, both experimentally and computationally. While molecular dynamics simulation has been used to accurately predict the diffusion coefficients, D, of a handful of gases in various polymers, this success has not been extended to molecules larger than gases, e.g., condensable vapours, liquids, and drugs. We present atomistic molecular dynamics simulation predictions of diffusion in a model drug eluting system that represent a dramatic improvement in accuracy compared to previous simulation predictions for comparable systems. We find that, for simulations of insufficient duration, sub-diffusive dynamics can lead to dramatic over-prediction of D. We present useful metrics for monitoring the extent of sub-diffusive dynamics and explore how these metrics correlate to error in D. We also identify a relationship between diffusion and fast dynamics in our system, which may serve as a means to more rapidly predict diffusion in slowly diffusing systems. Our work provides important precedent and essential insights for utilizing atomistic molecular dynamics simulations to predict diffusion coefficients of small to medium sized molecules in condensed soft matter systems.

Development of a model for predicting reaction rate constants of organic chemicals with ozone at different temperatures.

PubMed

Li, Xuehua; Zhao, Wenxing; Li, Jing; Jiang, Jingqiu; Chen, Jianji; Chen, Jingwen

2013-08-01

To assess the persistence and fate of volatile organic compounds in the troposphere, the rate constants for the reaction with ozone (kO3) are needed. As kO3 values are only available for hundreds of compounds, and experimental determination of kO3 is costly and time-consuming, it is of importance to develop predictive models on kO3. In this study, a total of 379 logkO3 values at different temperatures were used to develop and validate a model for the prediction of kO3, based on quantum chemical descriptors, Dragon descriptors and structural fragments. Molecular descriptors were screened by stepwise multiple linear regression, and the model was constructed by partial least-squares regression. The cross validation coefficient QCUM(2) of the model is 0.836, and the external validation coefficient Qext(2) is 0.811, indicating that the model has high robustness and good predictive performance. The most significant descriptor explaining logkO3 is the BELm2 descriptor with connectivity information weighted atomic masses. kO3 increases with increasing BELm2, and decreases with increasing ionization potential. The applicability domain of the proposed model was visualized by the Williams plot. The developed model can be used to predict kO3 at different temperatures for a wide range of organic chemicals, including alkenes, cycloalkenes, haloalkenes, alkynes, oxygen-containing compounds, nitrogen-containing compounds (except primary amines) and aromatic compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Anthropometric model for the prediction of appendicular skeletal muscle mass in Chilean older adults].

PubMed

Lera, Lydia; Albala, Cecilia; Ángel, Bárbara; Sánchez, Hugo; Picrin, Yaisy; Hormazabal, María José; Quiero, Andrea

2014-03-01

To develop a predictive model of appendicular skeletal muscle mass (ASM) based on anthropometric measurements in elderly from Santiago, Chile. 616 community dwelling, non-disabled subjects ≥ 60 years (mean 69.9 ± 5.2 years) living in Santiago, 64.6% female, participating in ALEXANDROS study. Anthropometric measurements, handgrip strength, mobility tests and DEXA were performed. Step by step linear regression models were used to associate ASM from DEXA with anthropometric variables, age and sex. The sample was divided at random into two to obtain prediction equations for both subsamples, which were mutually validated by double cross-validation. The high correlation between the values of observed and predicted MMAE in both sub-samples and the low degree of shrinkage allowed developing the final prediction equation with the total sample. The cross-validity coefficient between prediction models from the subsamples (0.941 and 0.9409) and the shrinkage (0.004 and 0.006) were similar in both equations. The final prediction model obtained from the total sample was: ASM (kg) = 0.107(weight in kg) + 0.251( knee height in cm) + 0.197 (Calf Circumference in cm) +0.047 (dynamometry in kg) - 0.034 (Hip Circumference in cm) + 3.417 (Man) - 0.020 (age years) - 7.646 (R2 = 0.89). The mean ASM obtained by the prediction equation and the DEXA measurement were similar (16.8 ± 4.0 vs 16.9 ± 3.7) and highly concordant according Bland and Altman (95% CI: -2.6 -2.7) and Lin (concordance correlation coefficient = 0.94) methods. We obtained a low cost anthropometric equation to determine the appendicular skeletal muscle mass useful for the screening of sarcopenia in older adults. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies

PubMed Central

2014-01-01

Background Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures. Methods Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5. Conclusions Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies. PMID:24410940

Atom and receptor based 3D QSAR models for generating new conformations from pyrazolopyrimidine as IL-2 inducible tyrosine kinase inhibitors.

PubMed

Ul-Haq, Zaheer; Effendi, Juweria Shahrukh; Ashraf, Sajda; Bkhaitan, Majdi M

2017-06-01

In the current study, quantitative three-dimensional structure-activity-relationship (3D-QSAR) method was performed to design a model for new chemical entities by utilizing pyrazolopyrimidines. Their inhibiting activity on receptor IL-2 Itk correlates descriptors based on topology and hydrophobicity. The best model developed by ligand-based (atom-based) approach has correlation-coefficient of r 2 : 0.987 and cross-validated squared correlation-coefficient of q 2 : 0.541 with an external prediction capability of r 2 : 0.944. Whereas the best selected model developed by structured-based (receptor-based) approach has correlation-coefficient of r 2 : 0.987, cross-validated squared correlation-coefficient of q 2 : 0.637 with an external predictive ability of r 2 : 0.941. The statistical parameters prove that structure-based gave a better model to design new chemical scaffolds. The results achieved indicated that hydrophobicity at R 1 location play a vital role in the inhibitory activity and introduction of appropriately bulky and strongly hydrophobic-groups at position 3 of the terminal phenyl-group which is highly significant to enhance the activity. Six new pyrazolopyrimidine derivatives were designed. Docking simulation study was carried out and their inhibitory activity was predicted by the best structure based model with predictive activity of ranging from 8.43 to 8.85 log unit. The interacting residues PHE435, ASP500, LYS391, GLU436, MET438, CYS442, ILE369, VAL377 of PDB 4HCT were studied with respect to type of bonding with the new compounds. This study was aimed to search out more potent inhibitors of IL-2 Itk. Copyright © 2017 Elsevier Inc. All rights reserved.

Cross-validation of bioelectrical impedance analysis of body composition in children and adolescents.

PubMed

Wu, Y T; Nielsen, D H; Cassady, S L; Cook, J S; Janz, K F; Hansen, J R

1993-05-01

The reliability and validity of measurements obtained with two bioelectrical impedance analyzers (BIAs), an RJL Systems model BIA-103 and a Berkeley Medical Research BMR-2000, were investigated using the manufacturers' prediction equations for the assessment of fat-free mass (FFM) (in kilograms) in children and adolescents. Forty-seven healthy children and adolescents (23 male, 24 female), ranging in age from 8 to 20 years (mean = 12.1, SD = 2.3), participated. In the context of a repeated-measures design, the data were analyzed according to gender and maturation (Tanner staging). Hydrostatic weighing (HYDRO) and Lohman's Siri age-adjusted body density prediction equation served as the criteria for validating the BIA-obtained measurements. High intraclass correlation coefficients (ICC > or = .987) demonstrated good test-retest (between-week) measurement reliability for HYDRO and both BIA methods. Between-method (HYDRO versus BIA) correlation coefficients were high for both boys and girls (r > or = .97). The standard errors of estimate (SEEs) for FFM were slightly larger for boys than for girls and were consistently smaller for the RJL system than for the BMR system (RJL SEE = 1.8 kg for boys, 1.3 kg for girls; BMR SEE = 2.4 kg for boys, 1.9 kg for girls). The coefficients of determination were high for both BIA methods (r2 > or = .929). Total prediction errors (TEs) for FFM showed similar between-method trends (RJL TE = 2.1 kg for boys, 1.5 kg for girls; BMR TE = 4.4 kg for boys, 1.9 kg for girls). This study demonstrated that the RJL BIA with the manufacturer's prediction equations can be used to reliably and accurately assess FFM in 8- to 20-year-old children and adolescents. The prediction of FFM by the BMR system was acceptable for girls, but significant overprediction of FFM for boys was noted.

A new scale for the assessment of performance and capacity of hand function in children with hemiplegic cerebral palsy: reliability and validity studies.

PubMed

Rosa-Rizzotto, M; Visonà Dalla Pozza, L; Corlatti, A; Luparia, A; Marchi, A; Molteni, F; Facchin, P; Pagliano, E; Fedrizzi, E

2014-10-01

In hemiplegic children, the recognition of the activity limitation pattern and the possibility of grading its severity are relevant for clinicians while planning interventions, monitoring results, predicting outcomes. Aim of the study is to examine the reliability and validity of Besta Scale, an instrument used to measure in hemiplegic children from 18 months to 12 years of age both grasp on request (capacity) and spontaneous use of upper limb (performance) in bimanual play activities and in ADL. Psychometric analysis of reliability and of validity of the Besta scale was performed. Outpatient study sample Reliability study: A sample of 39 patients was enrolled. The administration of Besta scale was video-recorded in a standardized manner. All videos were scored by 20 independent raters on subsequent viewing. 3 raters randomly selected from the 20-raters group rescored the same video two years later for intra-rater reliability. Intra and inter-rater reliability were calculated using Intraclass Correlation Coefficient (ICC) and Kendall's coefficient (K), respectively. Internal consistency reliability was assessed using Alpha's Chronbach coefficient. Validity study: a sample of 105 children was assessed 5 times (at t0 and 2, 3, 6 and 12 months later) by 20 independent raters. Each patient underwent at the same time to QUEST and Besta scale administration and assessment. Criterion validity was calculated using rho-Pearson coefficient. Reliability study: The inter-rater reliability calculated with Kendall's coefficient resulted moderate K=0.47. The intra-rater (or test-retest) reliability for 3 raters was excellent (ICC=0.927). The Cronbach's alpha for internal consistency was 0.972. Validity study: Besta scale showed a good criterion validity compared to QUEST increasing by age and severity of impairment. Rho Pearson's correlation coefficient r was 0.81 (P<0.0001). Limitations. Besta scales in infants finds hard to distinguish between mild to moderately impaired hand function. Besta scale scoring system is a valid and reliable tool, utilizable in a clinical setting to monitor evolution of unimanual and bimanual manipulation and to distinguish hand's capacity from performance.

Glass Transition Temperature- and Specific Volume- Composition Models for Tellurite Glasses

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

Riley, Brian J.; Vienna, John D.

This report provides models for predicting composition-properties for tellurite glasses, namely specific gravity and glass transition temperature. Included are the partial specific coefficients for each model, the component validity ranges, and model fit parameters.

Reliability, Validity, and Clinical Utility of the Dominic Interactive for Adolescents-RevisedA DSM-5-Based Self-Report Screen for Mental Disorders, Borderline Personality Traits, and Suicidality.

PubMed

Bergeron, Lise; Smolla, Nicole; Berthiaume, Claude; Renaud, Johanne; Breton, Jean-Jacques; St-Georges, Marie; Morin, Pauline; Zavaglia, Elissa; Labelle, Réal

2017-03-01

The Dominic Interactive for Adolescents-Revised (DIA-R) is a multimedia self-report screen for 9 mental disorders, borderline personality traits, and suicidality defined by the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders ( DSM-5). This study aimed to examine the reliability and the validity of this instrument. French- and English-speaking adolescents aged 12 to 15 years ( N = 447) were recruited from schools and clinical settings in Montreal and were evaluated twice. The internal consistency was estimated by Cronbach alpha coefficients and the test-retest reliability by intraclass correlation coefficients. Cutoff points on the DIA-R scales were determined by using clinically relevant measures for defining external validation criteria: the Schedule for Affective Disorders and Schizophrenia for School-Aged Children, the Beck Hopelessness Scale, and the Abbreviated-Diagnostic Interview for Borderlines. Receiver operating characteristic (ROC) analyses provided accuracy estimates (area under the ROC curve, sensitivity, specificity, likelihood ratio) to evaluate the ability of the DIA-R scales to predict external criteria. For most of the DIA-R scales, reliability coefficients were excellent or moderate. High or moderate accuracy estimates from ROC analyses demonstrated the ability of the DIA-R thresholds to predict psychopathological conditions. These thresholds were generally capable to discriminate between clinical and school subsamples. However, the validity of the obsessions/compulsions scale was too low. Findings clearly support the reliability and the validity of the DIA-R. This instrument may be useful to assess a wide range of adolescents' mental health problems in the continuum of services. This conclusion applies to all scales, except the obsessions/compulsions one.

Aerodynamic characteristics of the upper stages of a launch vehicle in low-density regime

NASA Astrophysics Data System (ADS)

Oh, Bum Seok; Lee, Joon Ho

2016-11-01

Aerodynamic characteristics of the orbital block (remaining configuration after separation of nose fairing and 1st and 2nd stages of the launch vehicle) and the upper 2-3stage (configuration after separation of 1st stage) of the 3 stages launch vehicle (KSLV-II, Korea Space Launch Vehicle) at high altitude of low-density regime are analyzed by SMILE code which is based on DSMC (Direct Simulation Monte-Carlo) method. To validating of the SMILE code, coefficients of axial force and normal forces of Apollo capsule are also calculated and the results agree very well with the data predicted by others. For the additional validations and applications of the DSMC code, aerodynamic calculation results of simple shapes of plate and wedge in low-density regime are also introduced. Generally, aerodynamic characteristics in low-density regime differ from those of continuum regime. To understand those kinds of differences, aerodynamic coefficients of the upper stages (including upper 2-3 stage and the orbital block) of the launch vehicle in low-density regime are analyzed as a function of Mach numbers and altitudes. The predicted axial force coefficients of the upper stages of the launch vehicle are very high compared to those in continuum regime. In case of the orbital block which flies at very high altitude (higher than 250km), all aerodynamic coefficients are more dependent on velocity variations than altitude variations. In case of the upper 2-3 stage which flies at high altitude (80km-150km), while the axial force coefficients and the locations of center of pressure are less changed with the variations of Knudsen numbers (altitudes), the normal force coefficients and pitching moment coefficients are more affected by variations of Knudsen numbers (altitude).

Predictive validity of a selection centre testing non-technical skills for recruitment to training in anaesthesia.

PubMed

Gale, T C E; Roberts, M J; Sice, P J; Langton, J A; Patterson, F C; Carr, A S; Anderson, I R; Lam, W H; Davies, P R F

2010-11-01

Assessment centres are an accepted method of recruitment in industry and are gaining popularity within medicine. We describe the development and validation of a selection centre for recruitment to speciality training in anaesthesia based on an assessment centre model incorporating the rating of candidate's non-technical skills. Expert consensus identified non-technical skills suitable for assessment at the point of selection. Four stations-structured interview, portfolio review, presentation, and simulation-were developed, the latter two being realistic scenarios of work-related tasks. Evaluation of the selection centre focused on applicant and assessor feedback ratings, inter-rater agreement, and internal consistency reliability coefficients. Predictive validity was sought via correlations of selection centre scores with subsequent workplace-based ratings of appointed trainees. Two hundred and twenty-four candidates were assessed over two consecutive annual recruitment rounds; 68 were appointed and followed up during training. Candidates and assessors demonstrated strong approval of the selection centre with more than 70% of ratings 'good' or 'excellent'. Mean inter-rater agreement coefficients ranged from 0.62 to 0.77 and internal consistency reliability of the selection centre score was high (Cronbach's α=0.88-0.91). The overall selection centre score was a good predictor of workplace performance during the first year of appointment. An assessment centre model based on the rating of non-technical skills can produce a reliable and valid selection tool for recruitment to speciality training in anaesthesia. Early results on predictive validity are encouraging and justify further development and evaluation.

Assessment of Biopsychosocial Complexity and Health Care Needs: Measurement Properties of the INTERMED Self-Assessment Version.

PubMed

van Reedt Dortland, Arianne K B; Peters, Lilian L; Boenink, Annette D; Smit, Jan H; Slaets, Joris P J; Hoogendoorn, Adriaan W; Joos, Andreas; Latour, Corine H M; Stiefel, Friedrich; Burrus, Cyrille; Guitteny-Collas, Marie; Ferrari, Silvia

2017-05-01

The INTERMED Self-Assessment questionnaire (IMSA) was developed as an alternative to the observer-rated INTERMED (IM) to assess biopsychosocial complexity and health care needs. We studied feasibility, reliability, and validity of the IMSA within a large and heterogeneous international sample of adult hospital inpatients and outpatients as well as its predictive value for health care use (HCU) and quality of life (QoL). A total of 850 participants aged 17 to 90 years from five countries completed the IMSA and were evaluated with the IM. The following measurement properties were determined: feasibility by percentages of missing values; reliability by Cronbach α; interrater agreement by intraclass correlation coefficients; convergent validity of IMSA scores with mental health (Short Form 36 emotional well-being subscale and Hospital Anxiety and Depression Scale), medical health (Cumulative Illness Rating Scale) and QoL (Euroqol-5D) by Spearman rank correlations; and predictive validity of IMSA scores with HCU and QoL by (generalized) linear mixed models. Feasibility, face validity, and reliability (Cronbach α = 0.80) were satisfactory. Intraclass correlation coefficient between IMSA and IM total scores was .78 (95% CI = .75-.81). Correlations of the IMSA with the Short Form 36, Hospital Anxiety and Depression Scale, Cumulative Illness Rating Scale, and Euroqol-5D (convergent validity) were -.65, .15, .28, and -.59, respectively. The IMSA significantly predicted QoL and also HCU (emergency department visits, hospitalization, outpatient visits, and diagnostic examinations) after 3- and 6-month follow-up. Results were comparable between hospital sites, inpatients and outpatients, as well as age groups. The IMSA is a generic and time-efficient method to assess biopsychosocial complexity and to provide guidance for multidisciplinary care trajectories in adult patients, with good reliability and validity across different cultures.

Prediction of Unsteady Aerodynamic Coefficients at High Angles of Attack

NASA Technical Reports Server (NTRS)

Pamadi, Bandu N.; Murphy, Patrick C.; Klein, Vladislav; Brandon, Jay M.

2001-01-01

The nonlinear indicial response method is used to model the unsteady aerodynamic coefficients in the low speed longitudinal oscillatory wind tunnel test data of the 0.1 scale model of the F-16XL aircraft. Exponential functions are used to approximate the deficiency function in the indicial response. Using one set of oscillatory wind tunnel data and parameter identification method, the unknown parameters in the exponential functions are estimated. The genetic algorithm is used as a least square minimizing algorithm. The assumed model structures and parameter estimates are validated by comparing the predictions with other sets of available oscillatory wind tunnel test data.

Peptide retention prediction using hydrophilic interaction liquid chromatography coupled to mass spectrometry.

PubMed

Badgett, Majors J; Boyes, Barry; Orlando, Ron

2018-02-16

A model that predicts retention for peptides using a HALO ® penta-HILIC column and gradient elution was created. Coefficients for each amino acid were derived using linear regression analysis and these coefficients can be summed to predict the retention of peptides. This model has a high correlation between experimental and predicted retention times (0.946), which is on par with previous RP and HILIC models. External validation of the model was performed using a set of H. pylori samples on the same LC-MS system used to create the model, and the deviation from actual to predicted times was low. Apart from amino acid composition, length and location of amino acid residues on a peptide were examined and two site-specific corrections for hydrophobic residues at the N-terminus as well as hydrophobic residues one spot over from the N-terminus were created. Copyright © 2017 Elsevier B.V. All rights reserved.

Transcultural adaptation and validation of the patient empowerment in long-term conditions questionnaire.

PubMed

Garcimartin, Paloma; Comin-Colet, Josep; Delgado-Hito, Pilar; Badosa-Marcé, Neus; Linas-Alonso, Anna

2017-05-04

Patient empowerment is a key element to improve the results in health, increase satisfaction amongst users and obtain higher treatment compliance. The main objective of this study is to validate the Spanish version of the questionnaire "Patient empowerment in long-term conditions" which evaluates the patients' level of empowerment of chronic diseases. The secondary objective is to identify factors which predict basal empowerment and changes (improvement or deterioration) in patients with Heart Failure (HF). An observational and prospective design of psychometric type to validate a questionnaire (aim 1) and a prospective study of cohorts (aim 2). The study will include 121 patients with confirmed diagnosis of HF. Three measurements (basal, at 15 days and at 3 months) will be carried out: quality of life, self-care and empowerment. Descriptive and inferential analyses will be used. For the first aim of the study (validation), the test-retest reproducibility will be assessed through intraclass correlation coefficient; internal consistency will be assessed through Cronbach's alpha coefficient; construct validity through Pearson's correlation coefficient; and sensibility to change through effect size coefficient. Set a valid questionnaire to measure the level of empowerment of patients with chronic diseases could be an effective tool to assess the results from the provision of the health care services. It will also allow us to identify at an early stage, those groups of patients with a low level of empowerment. Hence, they could become a risk group due to poor management of the disease, with a high rate of decompensation and a higher use rate of the health system resources.

Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network.

PubMed

Liu, Ruixin; Zhang, Xiaodong; Zhang, Lu; Gao, Xiaojie; Li, Huiling; Shi, Junhan; Li, Xuelin

2014-06-01

The aim of this study was to predict the bitterness intensity of a drug using an electronic tongue (e-tongue). The model drug of berberine hydrochloride was used to establish a bitterness prediction model (BPM), based on the taste evaluation of bitterness intensity by a taste panel, the data provided by the e-tongue and a genetic algorithm-back-propagation neural network (GA-BP) modeling method. The modeling characteristics of the GA-BP were compared with those of multiple linear regression, partial least square regression and BP methods. The determination coefficient of the BPM was 0.99965±0.00004, the root mean square error of cross-validation was 0.1398±0.0488 and the correlation coefficient of the cross-validation between the true and predicted values was 0.9959±0.0027. The model is superior to the other three models based on these indicators. In conclusion, the model established in this study has a high fitting degree and may be used for the bitterness prediction modeling of berberine hydrochloride of different concentrations. The model also provides a reference for the generation of BPMs of other drugs. Additionally, the algorithm of the study is able to conduct a rapid and accurate quantitative analysis of the data provided by the e-tongue.

Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network

PubMed Central

LIU, RUIXIN; ZHANG, XIAODONG; ZHANG, LU; GAO, XIAOJIE; LI, HUILING; SHI, JUNHAN; LI, XUELIN

2014-01-01

The aim of this study was to predict the bitterness intensity of a drug using an electronic tongue (e-tongue). The model drug of berberine hydrochloride was used to establish a bitterness prediction model (BPM), based on the taste evaluation of bitterness intensity by a taste panel, the data provided by the e-tongue and a genetic algorithm-back-propagation neural network (GA-BP) modeling method. The modeling characteristics of the GA-BP were compared with those of multiple linear regression, partial least square regression and BP methods. The determination coefficient of the BPM was 0.99965±0.00004, the root mean square error of cross-validation was 0.1398±0.0488 and the correlation coefficient of the cross-validation between the true and predicted values was 0.9959±0.0027. The model is superior to the other three models based on these indicators. In conclusion, the model established in this study has a high fitting degree and may be used for the bitterness prediction modeling of berberine hydrochloride of different concentrations. The model also provides a reference for the generation of BPMs of other drugs. Additionally, the algorithm of the study is able to conduct a rapid and accurate quantitative analysis of the data provided by the e-tongue. PMID:24926369

Quasi-steady Bingham plastic analysis of an electrorheological flow mode bypass damper with piston bleed

NASA Astrophysics Data System (ADS)

Lindler, Jason; Wereley, Norman M.

2003-06-01

We present an improved experimental validation of our nonlinear quasi-steady electrorheological (ER) and magnetorheological damper analysis, using an idealized Bingham plastic shear flow mechanism, for the flow mode of damper operation with leakage effect. To validate the model, a double-acting ER valve or bypass damper was designed and fabricated. Both the hydraulic cylinder and the bypass duct have cylindrical geometry, and damping forces are developed in the annular bypass via Poiseuille flow. The ER fluid damper contains a controlled amount of leakage around the piston head. The leakage allows ER fluid to flow from one side of the piston head to the opposite side without passing through the ER bypass. For this flow mode damper, the damping coefficient, defined as the ratio of equivalent viscous damping of the Bingham plastic material, Ceq, to the Newtonian viscous damping, C, is a function of the non-dimensional plug thickness only. The damper was tested for varying conditions of applied electric field and frequency using a mechanical damper dynamometer. In this analysis, the leakage damping coefficient with incorporated leakage effects, predict the amount of energy dissipated for a complete cycle of the piston rod. Measured force verses displacement cycles for multiple frequencies and electric fields validate the ability of the non-dimensional groups and the leakage damping coefficient to predict the damping levels for an ER bypass damper with leakage. Based on the experimental validation of the model using these data, the Bingham plastic analysis is shown to be an effective tool for the analysis-based design of double-acting ER bypass dampers.

Development of 1RM Prediction Equations for Bench Press in Moderately Trained Men.

PubMed

Macht, Jordan W; Abel, Mark G; Mullineaux, David R; Yates, James W

2016-10-01

Macht, JW, Abel, MG, Mullineaux, DR, and Yates, JW. Development of 1RM prediction equations for bench press in moderately trained men. J Strength Cond Res 30(10): 2901-2906, 2016-There are a variety of established 1 repetition maximum (1RM) prediction equations, however, very few prediction equations use anthropometric characteristics exclusively or in part, to estimate 1RM strength. Therefore, the purpose of this study was to develop an original 1RM prediction equation for bench press using anthropometric and performance characteristics in moderately trained male subjects. Sixty male subjects (21.2 ± 2.4 years) completed a 1RM bench press and were randomly assigned a load to complete as many repetitions as possible. In addition, body composition, upper-body anthropometric characteristics, and handgrip strength were assessed. Regression analysis was used to develop a performance-based 1RM prediction equation: 1RM = 1.20 repetition weight + 2.19 repetitions to fatigue - 0.56 biacromial width (cm) + 9.6 (R = 0.99, standard error of estimate [SEE] = 3.5 kg). Regression analysis to develop a nonperformance-based 1RM prediction equation yielded: 1RM (kg) = 0.997 cross-sectional area (CSA) (cm) + 0.401 chest circumference (cm) - 0.385%fat - 0.185 arm length (cm) + 36.7 (R = 0.81, SEE = 13.0 kg). The performance prediction equations developed in this study had high validity coefficients, minimal mean bias, and small limits of agreement. The anthropometric equations had moderately high validity coefficient but larger limits of agreement. The practical applications of this study indicate that the inclusion of anthropometric characteristics and performance variables produce a valid prediction equation for 1RM strength. In addition, the CSA of the arm uses a simple nonperformance method of estimating the lifter's 1RM. This information may be used to predict the starting load for a lifter performing a 1RM prediction protocol or a 1RM testing protocol.

Development of a ROT22 - DATAMAP interface

NASA Technical Reports Server (NTRS)

Shenoy, K. R.; Waak, T.; Brieger, J. T.

1986-01-01

This report (Contract NAS2-10331- Mod 10), outlines the development and validation of an interface between the three-dimensional transonic analysis program ROT22 and the Data from Aeromechanics Test and Analytics-Management and Analysis Package (DATAMAP). After development of the interface, the validation is carried out as follows. First, the DATAMAP program is used to analyze a portion of the Tip Aerodynamics and Acoustics Test (TAAT) data. Specifically, records 2872 and 2873 are analyzed at an azimuth of 90 deg, and record 2806 is analyzed at 60 deg. Trim conditions for these flight conditions are then calculated using the Bell performance prediction program ARAM45. Equivalent shaft, pitch, and twist angles are calculated from ARAM45 results and used as input to the ROT22 program. The interface uses the ROT22 results and creates DATAMAP information files from which the surface pressure contours and sectional pressure coefficients are plotted. Twist angles input to ROT22 program are then iteratively modified in the tip region until the computed pressure coefficients closely match the measurements. In all cases studied, the location of the shock is well predicted. However, the negative pressure coefficients were underpredicted. This could be accounted for by blade vortex interaction effects.

Braden scale (ALB) for assessing pressure ulcer risk in hospital patients: A validity and reliability study.

PubMed

Chen, Hong-Lin; Cao, Ying-Juan; Zhang, Wei; Wang, Jing; Huai, Bao-Sha

2017-02-01

The inter-rater reliability of Braden Scale is not so good. We modified the Braden(ALB) scale by defining nutrition subscale based on serum albumin, then assessed it's the validity and reliability in hospital patients. We designed a retrospective study for validity analysis, and a prospective study for reliability analysis. Receiver operating curve (ROC) and area under the curve (AUC) were used to evaluate the predictive validity. Intra-class correlation coefficient (ICC) was used to investigate the inter-rater reliability. Two thousand five hundred twenty-five patients were included for validity analysis, 76 patients (3.0%) developed pressure ulcer. Positive correlation was found between serum albumin and nutrition score in Braden scale (Spearman's coefficient 0.2203, P<0.0001). The AUCs for Braden scale and Braden(ALB) scale predicting pressure ulcer risk were 0.813 (95% CI 0.797-0.828; P<0.0001), and 0.859 (95% CI 0.845-0.872; P<0.0001), respectively. The Braden(ALB) scale was even more valid than the Braden scale (z=1.860, P=0.0628). In different age subgroups, the Braden(ALB) scale seems also more valid than the original Braden scale, but no statistically significant differences were found (P>0.05). The inter-rater reliability study showed the ICC-value for nutrition increased 45.9%, and increased 4.3% for total score. The Braden(ALB) scale has similar validity compared with the original Braden scale for in hospital patients. However, the inter-rater reliability was significantly increased. Copyright © 2016 Elsevier Inc. All rights reserved.

Validation of the Korean Version of the Mini-Sleep Questionnaire-Insomnia in Korean College Students.

PubMed

Kim, Hee-Ju

2017-03-01

This study aimed to evaluate the reliability and validity of the Korean version of the Mini-Sleep Questionnaire-Insomnia in Korean college students. A total of 470 students from six nursing colleges in South Korea participated in the study. The translation and linguistic validation of the Mini-Sleep Questionnaire-Insomnia was performed based on guidelines. The Pittsburgh Sleep Quality Index and the Perceived Stress Scale were used to validate the measure. Cronbach α, item-total correlation for internal consistency reliability and intraclass correlation coefficient for test-retest reliability were evaluated. Exploratory factor analysis for construct validity, Pearson's correlation with the Pittsburgh Sleep Quality Index and the Perceived Stress Scale for concurrent validity, and the receiver operating character curve for predictive validity were assessed. The 4-item Mini-Sleep Questionnaire-Insomnia had a Cronbach α of .69 and the item-total correlations were higher than .30. Cronbach α increased to .73 if the item assessing the use of sleeping pills and tranquilizers was deleted. This item had marked skewness and kurtosis issues. Factor analysis indicated unidimensionality, explaining 53.0% of the total variance. The measure showed high test-retest reliability (i.e., intraclass correlation coefficient = .84), acceptable concurrent validity (r with the Pittsburg Sleep Quality Index = .69; r with the Perceived Stress Scale = .31) and predictive validity [area under curve = .85; 95% confidence interval (0.81, 0.90)]. The Mini-Sleep Questionnaire-Insomnia showed acceptable reliability and validity. Yet, the limited distribution in sleep medications warrants further evaluations in the clinical population. Copyright © 2017. Published by Elsevier B.V.

Finite Element Vibration Modeling and Experimental Validation for an Aircraft Engine Casing

NASA Astrophysics Data System (ADS)

Rabbitt, Christopher

This thesis presents a procedure for the development and validation of a theoretical vibration model, applies this procedure to a pair of aircraft engine casings, and compares select parameters from experimental testing of those casings to those from a theoretical model using the Modal Assurance Criterion (MAC) and linear regression coefficients. A novel method of determining the optimal MAC between axisymmetric results is developed and employed. It is concluded that the dynamic finite element models developed as part of this research are fully capable of modelling the modal parameters within the frequency range of interest. Confidence intervals calculated in this research for correlation coefficients provide important information regarding the reliability of predictions, and it is recommended that these intervals be calculated for all comparable coefficients. The procedure outlined for aligning mode shapes around an axis of symmetry proved useful, and the results are promising for the development of further optimization techniques.

Quantitative Structure-Activity Relationship of Insecticidal Activity of Benzyl Ether Diamidine Derivatives

NASA Astrophysics Data System (ADS)

Zhai, Mengting; Chen, Yan; Li, Jing; Zhou, Jun

2017-12-01

The molecular electrongativity distance vector (MEDV-13) was used to describe the molecular structure of benzyl ether diamidine derivatives in this paper, Based on MEDV-13, The three-parameter (M 3, M 15, M 47) QSAR model of insecticidal activity (pIC 50) for 60 benzyl ether diamidine derivatives was constructed by leaps-and-bounds regression (LBR) . The traditional correlation coefficient (R) and the cross-validation correlation coefficient (R CV ) were 0.975 and 0.971, respectively. The robustness of the regression model was validated by Jackknife method, the correlation coefficient R were between 0.971 and 0.983. Meanwhile, the independent variables in the model were tested to be no autocorrelation. The regression results indicate that the model has good robust and predictive capabilities. The research would provide theoretical guidance for the development of new generation of anti African trypanosomiasis drugs with efficiency and low toxicity.

Modeling temperature variations in a pilot plant thermophilic anaerobic digester.

PubMed

Valle-Guadarrama, Salvador; Espinosa-Solares, Teodoro; López-Cruz, Irineo L; Domaschko, Max

2011-05-01

A model that predicts temperature changes in a pilot plant thermophilic anaerobic digester was developed based on fundamental thermodynamic laws. The methodology utilized two simulation strategies. In the first, model equations were solved through a searching routine based on a minimal square optimization criterion, from which the overall heat transfer coefficient values, for both biodigester and heat exchanger, were determined. In the second, the simulation was performed with variable values of these overall coefficients. The prediction with both strategies allowed reproducing experimental data within 5% of the temperature span permitted in the equipment by the system control, which validated the model. The temperature variation was affected by the heterogeneity of the feeding and extraction processes, by the heterogeneity of the digestate recirculation through the heating system and by the lack of a perfect mixing inside the biodigester tank. The use of variable overall heat transfer coefficients improved the temperature change prediction and reduced the effect of a non-ideal performance of the pilot plant modeled.

Partitioning of polar and non-polar neutral organic chemicals into human and cow milk.

PubMed

Geisler, Anett; Endo, Satoshi; Goss, Kai-Uwe

2011-10-01

The aim of this work was to develop a predictive model for milk/water partition coefficients of neutral organic compounds. Batch experiments were performed for 119 diverse organic chemicals in human milk and raw and processed cow milk at 37°C. No differences (<0.3 log units) in the partition coefficients of these types of milk were observed. The polyparameter linear free energy relationship model fit the calibration data well (SD=0.22 log units). An experimental validation data set including hormones and hormone active compounds was predicted satisfactorily by the model. An alternative modelling approach based on log K(ow) revealed a poorer performance. The model presented here provides a significant improvement in predicting enrichment of potentially hazardous chemicals in milk. In combination with physiologically based pharmacokinetic modelling this improvement in the estimation of milk/water partitioning coefficients may allow a better risk assessment for a wide range of neutral organic chemicals. Copyright © 2011 Elsevier Ltd. All rights reserved.

Classification of speech dysfluencies using LPC based parameterization techniques.

PubMed

Hariharan, M; Chee, Lim Sin; Ai, Ooi Chia; Yaacob, Sazali

2012-06-01

The goal of this paper is to discuss and compare three feature extraction methods: Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC) and Weighted Linear Prediction Cepstral Coefficients (WLPCC) for recognizing the stuttered events. Speech samples from the University College London Archive of Stuttered Speech (UCLASS) were used for our analysis. The stuttered events were identified through manual segmentation and were used for feature extraction. Two simple classifiers namely, k-nearest neighbour (kNN) and Linear Discriminant Analysis (LDA) were employed for speech dysfluencies classification. Conventional validation method was used for testing the reliability of the classifier results. The study on the effect of different frame length, percentage of overlapping, value of ã in a first order pre-emphasizer and different order p were discussed. The speech dysfluencies classification accuracy was found to be improved by applying statistical normalization before feature extraction. The experimental investigation elucidated LPC, LPCC and WLPCC features can be used for identifying the stuttered events and WLPCC features slightly outperforms LPCC features and LPC features.

Numerical and experimental investigations for the evaluation of the wear coefficient of reverse total shoulder prostheses.

PubMed

Mattei, Lorenza; Di Puccio, Francesca; Joyce, Thomas J; Ciulli, Enrico

2015-03-01

In the present study, numerical and experimental wear investigations on reverse total shoulder arthroplasties (RTSAs) were combined in order to estimate specific wear coefficients, currently not available in the literature. A wear model previously developed by the authors for metal-on-plastic hip implants was adapted to RTSAs and applied in a double direction: firstly, to evaluate specific wear coefficients for RTSAs from experimental results and secondly, to predict wear distribution. In both cases, the Archard wear law (AR) and the wear law of UHMWPE (PE) were considered, assuming four different k functions. The results indicated that both the wear laws predict higher wear coefficients for RTSA with respect to hip implants, particularly the AR law, with k values higher than twofold the hip ones. Such differences can significantly affect predictive wear model results for RTSA, when non-specific wear coefficients are used. Moreover, the wear maps simulated with the two laws are markedly different, although providing the same wear volume. A higher wear depth (+51%) is obtained with the AR law, located at the dome of the cup, while with the PE law the most worn region is close to the edge. Taking advantage of the linear trend of experimental volume losses, the wear coefficients obtained with the AR law should be valid despite having neglected the geometry update in the model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics.

PubMed

McDermott, A; Visentin, G; De Marchi, M; Berry, D P; Fenelon, M A; O'Connor, P M; Kenny, O A; McParland, S

2016-04-01

The aim of this study was to evaluate the effectiveness of mid-infrared spectroscopy in predicting milk protein and free amino acid (FAA) composition in bovine milk. Milk samples were collected from 7 Irish research herds and represented cows from a range of breeds, parities, and stages of lactation. Mid-infrared spectral data in the range of 900 to 5,000 cm(-1) were available for 730 milk samples; gold standard methods were used to quantify individual protein fractions and FAA of these samples with a view to predicting these gold standard protein fractions and FAA levels with available mid-infrared spectroscopy data. Separate prediction equations were developed for each trait using partial least squares regression; accuracy of prediction was assessed using both cross validation on a calibration data set (n=400 to 591 samples) and external validation on an independent data set (n=143 to 294 samples). The accuracy of prediction in external validation was the same irrespective of whether undertaken on the entire external validation data set or just within the Holstein-Friesian breed. The strongest coefficient of correlation obtained for protein fractions in external validation was 0.74, 0.69, and 0.67 for total casein, total β-lactoglobulin, and β-casein, respectively. Total proteins (i.e., total casein, total whey, and total lactoglobulin) were predicted with greater accuracy then their respective component traits; prediction accuracy using the infrared spectrum was superior to prediction using just milk protein concentration. Weak to moderate prediction accuracies were observed for FAA. The greatest coefficient of correlation in both cross validation and external validation was for Gly (0.75), indicating a moderate accuracy of prediction. Overall, the FAA prediction models overpredicted the gold standard values. Near-unity correlations existed between total casein and β-casein irrespective of whether the traits were based on the gold standard (0.92) or mid-infrared spectroscopy predictions (0.95). Weaker correlations among FAA were observed than the correlations among the protein fractions. Pearson correlations between gold standard protein fractions and the milk processing characteristics of rennet coagulation time, curd firming time, curd firmness, heat coagulating time, pH, and casein micelle size were weak to moderate and ranged from -0.48 (protein and pH) to 0.50 (total casein and a30). Pearson correlations between gold standard FAA and these milk processing characteristics were also weak to moderate and ranged from -0.60 (Val and pH) to 0.49 (Val and K20). Results from this study indicate that mid-infrared spectroscopy has the potential to predict protein fractions and some FAA in milk at a population level. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Modeling of adipose/blood partition coefficient for environmental chemicals.

PubMed

Papadaki, K C; Karakitsios, S P; Sarigiannis, D A

2017-12-01

A Quantitative Structure Activity Relationship (QSAR) model was developed in order to predict the adipose/blood partition coefficient of environmental chemical compounds. The first step of QSAR modeling was the collection of inputs. Input data included the experimental values of adipose/blood partition coefficient and two sets of molecular descriptors for 67 organic chemical compounds; a) the descriptors from Linear Free Energy Relationship (LFER) and b) the PaDEL descriptors. The datasets were split to training and prediction set and were analysed using two statistical methods; Genetic Algorithm based Multiple Linear Regression (GA-MLR) and Artificial Neural Networks (ANN). The models with LFER and PaDEL descriptors, coupled with ANN, produced satisfying performance results. The fitting performance (R 2 ) of the models, using LFER and PaDEL descriptors, was 0.94 and 0.96, respectively. The Applicability Domain (AD) of the models was assessed and then the models were applied to a large number of chemical compounds with unknown values of adipose/blood partition coefficient. In conclusion, the proposed models were checked for fitting, validity and applicability. It was demonstrated that they are stable, reliable and capable to predict the values of adipose/blood partition coefficient of "data poor" chemical compounds that fall within the applicability domain. Copyright © 2017. Published by Elsevier Ltd.

[Rapid prediction of annual ring density of Paulownia elongate standing tress using near infrared spectroscopy].

PubMed

Jiang, Ze-Hui; Wang, Yu-Rong; Fei, Ben-Hua; Fu, Feng; Hse, Chung-Yun

2007-06-01

Rapid prediction of annual ring density of Paulownia elongate standing trees using near infrared spectroscopy was studied. It was non-destructive to collect the samples for trees, that is, the wood cores 5 mm in diameter were unthreaded at the breast height of standing trees instead of fallen trees. Then the spectra data were collected by autoscan method of NIR. The annual ring density was determined by mercury immersion. And the models were made and analyzed by the partial least square (PLS) and full cross validation in the 350-2 500 nm wavelength range. The results showed that high coefficients were obtained between the annual ring and the NIR fitted data. The correlation coefficient of prediction model was 0.88 and 0.91 in the middle diameter and bigger diameter, respectively. Moreover, high coefficients of correlation were also obtained between annual ring density laboratory-determined and the NIR fitted data in the middle diameter of Paulownia elongate standing trees, the correlation coefficient of calibration model and prediction model were 0.90 and 0.83, and the standard errors of calibration (SEC) and standard errors of prediction(SEP) were 0.012 and 0.016, respectively. The method can simply, rapidly and non-destructively estimate the annual ring density of the Paulownia elongate standing trees close to the cutting age.

Characterization of nonGaussian atmospheric turbulence for prediction of aircraft response statistics

NASA Technical Reports Server (NTRS)

Mark, W. D.

1977-01-01

Mathematical expressions were derived for the exceedance rates and probability density functions of aircraft response variables using a turbulence model that consists of a low frequency component plus a variance modulated Gaussian turbulence component. The functional form of experimentally observed concave exceedance curves was predicted theoretically, the strength of the concave contribution being governed by the coefficient of variation of the time fluctuating variance of the turbulence. Differences in the functional forms of response exceedance curves and probability densities also were shown to depend primarily on this same coefficient of variation. Criteria were established for the validity of the local stationary assumption that is required in the derivations of the exceedance curves and probability density functions. These criteria are shown to depend on the relative time scale of the fluctuations in the variance, the fluctuations in the turbulence itself, and on the nominal duration of the relevant aircraft impulse response function. Metrics that can be generated from turbulence recordings for testing the validity of the local stationary assumption were developed.

Estimation of influential points in any data set from coefficient of determination and its leave-one-out cross-validated counterpart.

PubMed

Tóth, Gergely; Bodai, Zsolt; Héberger, Károly

2013-10-01

Coefficient of determination (R (2)) and its leave-one-out cross-validated analogue (denoted by Q (2) or R cv (2) ) are the most frequantly published values to characterize the predictive performance of models. In this article we use R (2) and Q (2) in a reversed aspect to determine uncommon points, i.e. influential points in any data sets. The term (1 - Q (2))/(1 - R (2)) corresponds to the ratio of predictive residual sum of squares and the residual sum of squares. The ratio correlates to the number of influential points in experimental and random data sets. We propose an (approximate) F test on (1 - Q (2))/(1 - R (2)) term to quickly pre-estimate the presence of influential points in training sets of models. The test is founded upon the routinely calculated Q (2) and R (2) values and warns the model builders to verify the training set, to perform influence analysis or even to change to robust modeling.

Combination of acoustical radiosity and the image source method.

PubMed

Koutsouris, Georgios I; Brunskog, Jonas; Jeong, Cheol-Ho; Jacobsen, Finn

2013-06-01

A combined model for room acoustic predictions is developed, aiming to treat both diffuse and specular reflections in a unified way. Two established methods are incorporated: acoustical radiosity, accounting for the diffuse part, and the image source method, accounting for the specular part. The model is based on conservation of acoustical energy. Losses are taken into account by the energy absorption coefficient, and the diffuse reflections are controlled via the scattering coefficient, which defines the portion of energy that has been diffusely reflected. The way the model is formulated allows for a dynamic control of the image source production, so that no fixed maximum reflection order is required. The model is optimized for energy impulse response predictions in arbitrary polyhedral rooms. The predictions are validated by comparison with published measured data for a real music studio hall. The proposed model turns out to be promising for acoustic predictions providing a high level of detail and accuracy.

A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics

PubMed Central

Mabey, P.; Richardson, S.; White, T. G.; Fletcher, L. B.; Glenzer, S. H.; Hartley, N. J.; Vorberger, J.; Gericke, D. O.; Gregori, G.

2017-01-01

The state and evolution of planets, brown dwarfs and neutron star crusts is determined by the properties of dense and compressed matter. Due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ion modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. Our results have profound consequences in the interpretation of transport coefficients in dense plasmas. PMID:28134338

Estimating the physicochemical properties of polyhalogenated aromatic and aliphatic compounds using UPPER: part 2. Aqueous solubility, octanol solubility and octanol-water partition coefficient.

PubMed

Admire, Brittany; Lian, Bo; Yalkowsky, Samuel H

2015-01-01

The UPPER (Unified Physicochemical Property Estimation Relationships) model uses additive and non-additive parameters to estimate 20 biologically relevant properties of organic compounds. The model has been validated by Lian and Yalkowsky (2014) on a data set of 700 hydrocarbons. Recently, Admire et al. (2014) expanded the model to predict the boiling and melting points of 1288 polyhalogenated benzenes, biphenyls, dibenzo-p-dioxins, diphenyl ethers, anisoles and alkanes. In this work, 19 new group descriptors are determined and used to predict the aqueous solubilities, octanol solubilities and the octanol-water coefficients. Copyright © 2014 Elsevier Ltd. All rights reserved.

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

A new predictive dynamic model describing the effect of the ambient temperature and the convective heat transfer coefficient on bacterial growth.

PubMed

Ben Yaghlene, H; Leguerinel, I; Hamdi, M; Mafart, P

2009-07-31

In this study, predictive microbiology and food engineering were combined in order to develop a new analytical model predicting the bacterial growth under dynamic temperature conditions. The proposed model associates a simplified primary bacterial growth model without lag, the secondary Ratkowsky "square root" model and a simplified two-parameter heat transfer model regarding an infinite slab. The model takes into consideration the product thickness, its thermal properties, the ambient air temperature, the convective heat transfer coefficient and the growth parameters of the micro organism of concern. For the validation of the overall model, five different combinations of ambient air temperature (ranging from 8 degrees C to 12 degrees C), product thickness (ranging from 1 cm to 6 cm) and convective heat transfer coefficient (ranging from 8 W/(m(2) K) to 60 W/(m(2) K)) were tested during a cooling procedure. Moreover, three different ambient air temperature scenarios assuming alternated cooling and heating stages, drawn from real refrigerated food processes, were tested. General agreement between predicted and observed bacterial growth was obtained and less than 5% of the experimental data fell outside the 95% confidence bands estimated by the bootstrap percentile method, at all the tested conditions. Accordingly, the overall model was successfully validated for isothermal and dynamic refrigeration cycles allowing for temperature dynamic changes at the centre and at the surface of the product. The major impact of the convective heat transfer coefficient and the product thickness on bacterial growth during the product cooling was demonstrated. For instance, the time needed for the same level of bacterial growth to be reached at the product's half thickness was estimated to be 5 and 16.5 h at low and high convection level, respectively. Moreover, simulation results demonstrated that the predicted bacterial growth at the air ambient temperature cannot be assumed to be equivalent to the bacterial growth occurring at the product's surface or centre when convection heat transfer is taken into account. Our results indicate that combining food engineering and predictive microbiology models is an interesting approach providing very useful tools for food safety and process optimisation.

[Research on Resistant Starch Content of Rice Grain Based on NIR Spectroscopy Model].

PubMed

Luo, Xi; Wu, Fang-xi; Xie, Hong-guang; Zhu, Yong-sheng; Zhang, Jian-fu; Xie, Hua-an

2016-03-01

A new method based on near-infrared reflectance spectroscopy (NIRS) analysis was explored to determine the content of rice-resistant starch instead of common chemical method which took long time was high-cost. First of all, we collected 62 spectral data which have big differences in terms of resistant starch content of rice, and then the spectral data and detected chemical values are imported chemometrics software. After that a near-infrared spectroscopy calibration model for rice-resistant starch content was constructed with partial least squares (PLS) method. Results are as follows: In respect of internal cross validation, the coefficient of determination (R2) of untreated, pretreatment with MSC+1thD, pretreatment with 1thD+SNV were 0.920 2, 0.967 0 and 0.976 7 respectively. Root mean square error of prediction (RMSEP) were 1.533 7, 1.011 2 and 0.837 1 respectively. In respect of external validation, the coefficient of determination (R2) of untreated, pretreatment with MSC+ 1thD, pretreatment with 1thD+SNV were 0.805, 0.976 and 0.992 respectively. The average absolute error was 1.456, 0.818, 0.515 respectively. There was no significant difference between chemical and predicted values (Turkey multiple comparison), so we think near infrared spectrum analysis is more feasible than chemical measurement. Among the different pretreatment, the first derivation and standard normal variate (1thD+SNV) have higher coefficient of determination (R2) and lower error value whether in internal validation and external validation. In other words, the calibration model has higher precision and less error by pretreatment with 1thD+SNV.

Cross-cultural Adaptation and Validation of the Medication Regimen Complexity Index Adapted to Spanish.

PubMed

Saez de la Fuente, Javier; Such Diaz, Ana; Cañamares-Orbis, Irene; Ramila, Estela; Izquierdo-Garcia, Elsa; Esteban, Concepcion; Escobar-Rodríguez, Ismael

2016-11-01

The most widely used validated instrument to assess the complexity of medication regimens is the Medication Regimen Complexity Index (MRCI). This study aimed to translate, adapt, and validate a reliable version of the MRCI adapted to Spanish (MRCI-E). The cross-cultural adaptation process consisted of an independent translation by 3 clinical pharmacists and a backtranslation by 2 native English speakers. A reliability analysis was conducted on 20 elderly randomly selected patients. Two clinical pharmacists calculated the MRCI-E from discharge treatments and 2 months later. For the validity analysis, the sample was augmented to 60 patients. Convergent validity was assessed by analyzing the correlation between the number of medications; discriminant validity was stratified by gender; and predictive validity was determined by analyzing the ability to predict readmission and mortality at 3 and 6 months. The MRCI-E retained the original structure of 3 sections. The reliability analysis demonstrated an excellent internal consistency (Cronbach's α=0.83), and the intraclass correlation coefficient exceeded 0.9 in all cases. The correlation coefficient with the number of medications was 0.883 ( P<0.001). No significant differences were found when stratified by gender (3.6; 95%CI=-2.9 to 10.2; P=0.27). Patients who were readmitted at 3 months had a higher MRCI-E score (10.7; 95%CI=4.4 to 17.2; P=0.001). The differences remained significant in patients readmitted at 6 months, but differences in mortality were not detected. The MRCI-E retains the reliability and validity of the original index and provides a suitable tool to assess the complexity of medication regimens in Spanish.

The virial coefficients of hard hypersphere binary mixtures

NASA Astrophysics Data System (ADS)

Enciso, E.; Almarza, N. G.; Gonzalez, M. A.; Bermejo, F. J.

The third, fourth and fifth virial coefficients of hard hypersphere binary mixtures with dimensionality d = 4, 5 have been calculated for size ratios R ≥0.1, R ı σ22 / σ11 , where σ ii is the diameter of component i . The composition independent partial virial coefficients have been evaluated by Monte Carlo integration of the corresponding Mayer modified star diagrams. The results are compared with the predictions of Santos, S., Yuste, S. B., and Lopez de Haro, M., 1999, Molec. Phys ., 96 , 1 of the equation of state of a multicomponent mixture of hard hyperspheres, and the good agreement gives strong support to the validity of that recipe.

Improving the prediction of arsenic contents in agricultural soils by combining the reflectance spectroscopy of soils and rice plants

NASA Astrophysics Data System (ADS)

Shi, Tiezhu; Wang, Junjie; Chen, Yiyun; Wu, Guofeng

2016-10-01

Visible and near-infrared reflectance spectroscopy provides a beneficial tool for investigating soil heavy metal contamination. This study aimed to investigate mechanisms of soil arsenic prediction using laboratory based soil and leaf spectra, compare the prediction of arsenic content using soil spectra with that using rice plant spectra, and determine whether the combination of both could improve the prediction of soil arsenic content. A total of 100 samples were collected and the reflectance spectra of soils and rice plants were measured using a FieldSpec3 portable spectroradiometer (350-2500 nm). After eliminating spectral outliers, the reflectance spectra were divided into calibration (n = 62) and validation (n = 32) data sets using the Kennard-Stone algorithm. Genetic algorithm (GA) was used to select useful spectral variables for soil arsenic prediction. Thereafter, the GA-selected spectral variables of the soil and leaf spectra were individually and jointly employed to calibrate the partial least squares regression (PLSR) models using the calibration data set. The regression models were validated and compared using independent validation data set. Furthermore, the correlation coefficients of soil arsenic against soil organic matter, leaf arsenic and leaf chlorophyll were calculated, and the important wavelengths for PLSR modeling were extracted. Results showed that arsenic prediction using the leaf spectra (coefficient of determination in validation, Rv2 = 0.54; root mean square error in validation, RMSEv = 12.99 mg kg-1; and residual prediction deviation in validation, RPDv = 1.35) was slightly better than using the soil spectra (Rv2 = 0.42, RMSEv = 13.35 mg kg-1, and RPDv = 1.31). However, results also showed that the combinational use of soil and leaf spectra resulted in higher arsenic prediction (Rv2 = 0.63, RMSEv = 11.94 mg kg-1, RPDv = 1.47) compared with either soil or leaf spectra alone. Soil spectral bands near 480, 600, 670, 810, 1980, 2050 and 2290 nm, leaf spectral bands near 700, 890 and 900 nm in PLSR models were important wavelengths for soil arsenic prediction. Moreover, soil arsenic showed significantly positive correlations with soil organic matter (r = 0.62, p < 0.01) and leaf arsenic (r = 0.77, p < 0.01), and a significantly negative correlation with leaf chlorophyll (r = -0.67, p < 0.01). The results showed that the prediction of arsenic contents using soil and leaf spectra may be based on their relationships with soil organic matter and leaf chlorophyll contents, respectively. Although RPD of 1.47 was below the recommended RPD of >2 for soil analysis, arsenic prediction in agricultural soils can be improved by combining the leaf and soil spectra.

Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water.

PubMed

Ding, H; Chen, C; Zhang, X

2016-01-01

The linear solvation energy relationship (LSER) was applied to predict the adsorption coefficient (K) of synthetic organic compounds (SOCs) on single-walled carbon nanotubes (SWCNTs). A total of 40 log K values were used to develop and validate the LSER model. The adsorption data for 34 SOCs were collected from 13 published articles and the other six were obtained in our experiment. The optimal model composed of four descriptors was developed by a stepwise multiple linear regression (MLR) method. The adjusted r(2) (r(2)adj) and root mean square error (RMSE) were 0.84 and 0.49, respectively, indicating good fitness. The leave-one-out cross-validation Q(2) ([Formula: see text]) was 0.79, suggesting the robustness of the model was satisfactory. The external Q(2) ([Formula: see text]) and RMSE (RMSEext) were 0.72 and 0.50, respectively, showing the model's strong predictive ability. Hydrogen bond donating interaction (bB) and cavity formation and dispersion interactions (vV) stood out as the two most influential factors controlling the adsorption of SOCs onto SWCNTs. The equilibrium concentration would affect the fitness and predictive ability of the model, while the coefficients varied slightly.

QSPR models of n-octanol/water partition coefficients and aqueous solubility of halogenated methyl-phenyl ethers by DFT method.

PubMed

Zeng, Xiao-Lan; Wang, Hong-Jun; Wang, Yan

2012-02-01

The possible molecular geometries of 134 halogenated methyl-phenyl ethers were optimized at B3LYP/6-31G(*) level with Gaussian 98 program. The calculated structural parameters were taken as theoretical descriptors to establish two new novel QSPR models for predicting aqueous solubility (-lgS(w,l)) and n-octanol/water partition coefficient (lgK(ow)) of halogenated methyl-phenyl ethers. The two models achieved in this work both contain three variables: energy of the lowest unoccupied molecular orbital (E(LUMO)), most positive atomic partial charge in molecule (q(+)), and quadrupole moment (Q(yy) or Q(zz)), of which R values are 0.992 and 0.970 respectively, their standard errors of estimate in modeling (SD) are 0.132 and 0.178, respectively. The results of leave-one-out (LOO) cross-validation for training set and validation with external test sets both show that the models obtained exhibited optimum stability and good predictive power. We suggests that two QSPR models derived here can be used to predict S(w,l) and K(ow) accurately for non-tested halogenated methyl-phenyl ethers congeners. Copyright © 2011 Elsevier Ltd. All rights reserved.

A piecewise mass-spring-damper model of the human breast.

PubMed

Cai, Yiqing; Chen, Lihua; Yu, Winnie; Zhou, Jie; Wan, Frances; Suh, Minyoung; Chow, Daniel Hung-Kay

2018-01-23

Previous models to predict breast movement whilst performing physical activities have, erroneously, assumed uniform elasticity within the breast. Consequently, the predicted displacements have not yet been satisfactorily validated. In this study, real time motion capture of the natural vibrations of a breast that followed, after raising and allowing it to fall freely, revealed an obvious difference in the vibration characteristics above and below the static equilibrium position. This implied that the elastic and viscous damping properties of a breast could vary under extension or compression. Therefore, a new piecewise mass-spring-damper model of a breast was developed with theoretical equations to derive values for its spring constants and damping coefficients from free-falling breast experiments. The effective breast mass was estimated from the breast volume extracted from a 3D body scanned image. The derived spring constant (k a  = 73.5 N m -1 ) above the static equilibrium position was significantly smaller than that below it (k b  = 658 N m -1 ), whereas the respective damping coefficients were similar (c a  = 1.83 N s m -1 , c b  = 2.07 N s m -1 ). These values were used to predict the nipple displacement during bare-breasted running for validation. The predicted and experimental results had a 2.6% or less root-mean-square-error of the theoretical and experimental amplitudes, so the piecewise mass-spring-damper model and equations were considered to have been successfully validated. This provides a theoretical basis for further research into the dynamic, nonlinear viscoelastic properties of different breasts and the prediction of external forces for the necessary breast support during different sports activities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Computational Fluid Dynamics Based Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

NASA Technical Reports Server (NTRS)

Yang, H. Q.; West, Jeff

2015-01-01

Current reduced-order thermal model for cryogenic propellant tanks is based on correlations built for flat plates collected in the 1950's. The use of these correlations suffers from: inaccurate geometry representation; inaccurate gravity orientation; ambiguous length scale; and lack of detailed validation. The work presented under this task uses the first-principles based Computational Fluid Dynamics (CFD) technique to compute heat transfer from tank wall to the cryogenic fluids, and extracts and correlates the equivalent heat transfer coefficient to support reduced-order thermal model. The CFD tool was first validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the present prediction and experimental data have been found for flows in laminar as well turbulent regimes. The convective heat transfer between tank wall and cryogenic propellant, and that between tank wall and ullage gas were then simulated. The results showed that commonly used heat transfer correlations for either vertical or horizontal plate over predict heat transfer rate for the cryogenic tank, in some cases by as much as one order of magnitude. A characteristic length scale has been defined that can correlate all heat transfer coefficients for different fill levels into a single curve. This curve can be used for the reduced-order heat transfer model analysis.

Quantitative models for predicting adsorption of oxytetracycline, ciprofloxacin and sulfamerazine to swine manures with contrasting properties.

PubMed

Cheng, Dengmiao; Feng, Yao; Liu, Yuanwang; Li, Jinpeng; Xue, Jianming; Li, Zhaojun

2018-09-01

Understanding antibiotic adsorption in livestock manures is crucial to assess the fate and risk of antibiotics in the environment. In this study, three quantitative models developed with swine manure-water distribution coefficients (LgK d ) for oxytetracycline (OTC), ciprofloxacin (CIP) and sulfamerazine (SM1) in swine manures. Physicochemical parameters (n=12) of the swine manure were used as independent variables using partial least-squares (PLSs) analysis. The cumulative cross-validated regression coefficients (Q 2 cum ) values, standard deviations (SDs) and external validation coefficient (Q 2 ext ) ranged from 0.761 to 0.868, 0.027 to 0.064, and 0.743 to 0.827 for the three models; as such, internal and external predictability of the models were strong. The pH, soluble organic carbon (SOC) and nitrogen (SON), and Ca were important explanatory variables for the OTC-Model, pH, SOC, and SON for the CIP-model, and pH, total organic nitrogen (TON), and SOC for the SM1-model. The high VIPs (variable importance in the projections) of pH (1.178-1.396), SOC (0.968-1.034), and SON (0.822 and 0.865) established these physicochemical parameters as likely being dominant (associatively) in affecting transport of antibiotics in swine manures. Copyright © 2018 Elsevier B.V. All rights reserved.

CFD Extraction of Heat Transfer Coefficient in Cryogenic Propellant Tanks

NASA Technical Reports Server (NTRS)

Yang, H. Q.; West, Jeff

2015-01-01

Current reduced-order thermal model for cryogenic propellant tanks is based on correlations built for flat plates collected in the 1950's. The use of these correlations suffers from inaccurate geometry representation; inaccurate gravity orientation; ambiguous length scale; and lack of detailed validation. This study uses first-principles based CFD methodology to compute heat transfer from the tank wall to the cryogenic fluids and extracts and correlates the equivalent heat transfer coefficient to support reduced-order thermal model. The CFD tool was first validated against available experimental data and commonly used correlations for natural convection along a vertically heated wall. Good agreements between the present prediction and experimental data have been found for flows in laminar as well turbulent regimes. The convective heat transfer between the tank wall and cryogenic propellant, and that between the tank wall and ullage gas were then simulated. The results showed that the commonly used heat transfer correlations for either vertical or horizontal plate over-predict heat transfer rate for the cryogenic tank, in some cases by as much as one order of magnitude. A characteristic length scale has been defined that can correlate all heat transfer coefficients for different fill levels into a single curve. This curve can be used for the reduced-order heat transfer model analysis.

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

Dynamic CFD Simulations of the Supersonic Inflatable Aerodynamic Decelerator (SIAD) Ballistic Range Tests

NASA Technical Reports Server (NTRS)

Brock, Joseph M; Stern, Eric

2016-01-01

Dynamic CFD simulations of the SIAD ballistic test model were performed using US3D flow solver. Motivation for performing these simulations is for the purpose of validation and verification of the US3D flow solver as a viable computational tool for predicting dynamic coefficients.

[Proximate analysis of straw by near infrared spectroscopy (NIRS)].

PubMed

Huang, Cai-jin; Han, Lu-jia; Liu, Xian; Yang, Zeng-ling

2009-04-01

Proximate analysis is one of the routine analysis procedures in utilization of straw for biomass energy use. The present paper studied the applicability of rapid proximate analysis of straw by near infrared spectroscopy (NIRS) technology, in which the authors constructed the first NIRS models to predict volatile matter and fixed carbon contents of straw. NIRS models were developed using Foss 6500 spectrometer with spectra in the range of 1,108-2,492 nm to predict the contents of moisture, ash, volatile matter and fixed carbon in the directly cut straw samples; to predict ash, volatile matter and fixed carbon in the dried milled straw samples. For the models based on directly cut straw samples, the determination coefficient of independent validation (R2v) and standard error of prediction (SEP) were 0.92% and 0.76% for moisture, 0.94% and 0.84% for ash, 0.88% and 0.82% for volatile matter, and 0.75% and 0.65% for fixed carbon, respectively. For the models based on dried milled straw samples, the determination coefficient of independent validation (R2v) and standard error of prediction (SEP) were 0.98% and 0.54% for ash, 0.95% and 0.57% for volatile matter, and 0.78% and 0.61% for fixed carbon, respectively. It was concluded that NIRS models can predict accurately as an alternative analysis method, therefore rapid and simultaneous analysis of multicomponents can be achieved by NIRS technology, decreasing the cost of proximate analysis for straw.

Assessment of tinnitus-related impairments and disabilities using the German THI-12: sensitivity and stability of the scale over time.

PubMed

Görtelmeyer, Roman; Schmidt, Jürgen; Suckfüll, Markus; Jastreboff, Pawel; Gebauer, Alexander; Krüger, Hagen; Wittmann, Werner

2011-08-01

To evaluate the reliability, dimensionality, predictive validity, construct validity, and sensitivity to change of the THI-12 total and sub-scales as diagnostic aids to describe and quantify tinnitus-evoked reactions and evaluate treatment efficacy. Explorative analysis of the German tinnitus handicap inventory (THI-12) to assess potential sensitivity to tinnitus therapy in placebo-controlled randomized studies. Correlation analysis, including Cronbach's coefficient α and explorative common factor analysis (EFA), was conducted within and between assessments to demonstrate the construct validity, dimensionality, and factorial structure of the THI-12. N = 618 patients suffering from subjective tinnitus who were to be screened to participate in a randomized, placebo-controlled, 16-week, longitudinal study. The THI-12 can reliably diagnose tinnitus-related impairments and disabilities and assess changes over time. The test-retest coefficient for neighboured visits was r > 0.69, the internal consistency of the THI-12 total score was α ≤ 0.79 and α ≤ 0.89 at subsequent visits. Predictability of THI-12 total score and overall variance increased with successive measurements. The three-factorial structure allowed for evaluation of factors that affect aspects of patients' health-related quality of life. The THI-12, with its three-factorial structure, is a simple, reliable, and valid instrument for the diagnosis and assessment of tinnitus and associated impairment over time.

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Validation of limited sampling strategy for the estimation of mycophenolic acid exposure in Chinese adult liver transplant recipients.

PubMed

Hao, Chen; Erzheng, Chen; Anwei, Mao; Zhicheng, Yu; Baiyong, Shen; Xiaxing, Deng; Weixia, Zhang; Chenghong, Peng; Hongwei, Li

2007-12-01

Mycophenolate mofetil (MMF) is indicated as immunosuppressive therapy in liver transplantation. The abbreviated models for the estimation of mycophenolic acid (MPA) area under the concentration-time curve (AUC) have been established by limited sampling strategies (LSSs) in adult liver transplant recipients. In the current study, the performance of the abbreviated models to predict MPA exposure was validated in an independent group of patients. A total of 30 MPA pharmacokinetic profiles from 30 liver transplant recipients receiving MMF in combination with tacrolimus were used to compare 8 models' performance with a full 10 time-point MPA-AUC. Linear regression analysis and Bland-Altman analysis were used to compare the estimated MPA-AUC0-12h from each model against the measured MPA-AUC0-12h. A wide range of agreement was shown when estimated MPA-AUC0-12h was compared with measured MPA-AUC0-12h, and the range of coefficient of determination (r2) was from 0.479 to 0.936. The model based on MPA pharmacokinetic parameters C1h, C2h, C6h, and C8h had the best ability to predict measured MPA-AUC0-12h, with the best coefficient of determination (r2=0.936), the excellent prediction bias (2.18%), the best prediction precision (5.11%), and the best prediction variation (2SD=+/-7.88 mg.h/L). However, the model based on MPA pharmacokinetic sampling time points C1h, C2h, and C4h was more suitable when concerned with clinical convenience, which had shorter sampling interval, an excellent coefficient of determination (r2=0.795), an excellent prediction bias (3.48%), an acceptable prediction precision (14.37%), and a good prediction variation (2SD=+/-13.23 mg.h/L). Measured MPA-AUC0-12h could be best predicted by using MPA pharmacokinetic parameters C1h, C2h, C6h, and C8h. The model based on MPA pharmacokinetic parameters C1h, C2h, and C4h was more feasible in clinical application. Copyright (c) 2007 AASLD.

Determination of total phenolic compounds in compost by infrared spectroscopy.

PubMed

Cascant, M M; Sisouane, M; Tahiri, S; Krati, M El; Cervera, M L; Garrigues, S; de la Guardia, M

2016-06-01

Middle and near infrared (MIR and NIR) were applied to determine the total phenolic compounds (TPC) content in compost samples based on models built by using partial least squares (PLS) regression. The multiplicative scatter correction, standard normal variate and first derivative were employed as spectra pretreatment, and the number of latent variable were optimized by leave-one-out cross-validation. The performance of PLS-ATR-MIR and PLS-DR-NIR models was evaluated according to root mean square error of cross validation and prediction (RMSECV and RMSEP), the coefficient of determination for prediction (Rpred(2)) and residual predictive deviation (RPD) being obtained for this latter values of 5.83 and 8.26 for MIR and NIR, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies

PubMed Central

Dimitrov, Borislav D; Motterlini, Nicola; Fahey, Tom

2015-01-01

Objective Estimating calibration performance of clinical prediction rules (CPRs) in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe a simplified approach for outcomes prediction and calibration assessment and evaluate its functionality and validity. Study design and methods: Methodological study of systematic reviews of validation studies of CPRs: a) ABCD2 rule for prediction of 7 day stroke; and b) CRB-65 rule for prediction of 30 day mortality. Predicted outcomes in a sample validation study were computed by CPR distribution patterns (“derivation model”). As confirmation, a logistic regression model (with derivation study coefficients) was applied to CPR-based dummy variables in the validation study. Meta-analysis of validation studies provided pooled estimates of “predicted:observed” risk ratios (RRs), 95% confidence intervals (CIs), and indexes of heterogeneity (I2) on forest plots (fixed and random effects models), with and without adjustment of intercepts. The above approach was also applied to the CRB-65 rule. Results Our simplified method, applied to ABCD2 rule in three risk strata (low, 0–3; intermediate, 4–5; high, 6–7 points), indicated that predictions are identical to those computed by univariate, CPR-based logistic regression model. Discrimination was good (c-statistics =0.61–0.82), however, calibration in some studies was low. In such cases with miscalibration, the under-prediction (RRs =0.73–0.91, 95% CIs 0.41–1.48) could be further corrected by intercept adjustment to account for incidence differences. An improvement of both heterogeneities and P-values (Hosmer-Lemeshow goodness-of-fit test) was observed. Better calibration and improved pooled RRs (0.90–1.06), with narrower 95% CIs (0.57–1.41) were achieved. Conclusion Our results have an immediate clinical implication in situations when predicted outcomes in CPR validation studies are lacking or deficient by describing how such predictions can be obtained by everyone using the derivation study alone, without any need for highly specialized knowledge or sophisticated statistics. PMID:25931829

Use of Fuzzy rainfall-runoff predictions for claypan watersheds with conservation buffers in Northeast Missouri

NASA Astrophysics Data System (ADS)

Anomaa Senaviratne, G. M. M. M.; Udawatta, Ranjith P.; Anderson, Stephen H.; Baffaut, Claire; Thompson, Allen

2014-09-01

Fuzzy rainfall-runoff models are often used to forecast flood or water supply in large catchments and applications at small/field scale agricultural watersheds are limited. The study objectives were to develop, calibrate, and validate a fuzzy rainfall-runoff model using long-term data of three adjacent field scale row crop watersheds (1.65-4.44 ha) with intermittent discharge in the claypan soils of Northeast Missouri. The watersheds were monitored for a six-year calibration period starting 1991 (pre-buffer period). Thereafter, two of them were treated with upland contour grass and agroforestry (tree + grass) buffers (4.5 m wide, 36.5 m apart) to study water quality benefits. The fuzzy system was based on Mamdani method using MATLAB 7.10.0. The model predicted event-based runoff with model performance coefficients of r2 and Nash-Sutcliffe Coefficient (NSC) values greater than 0.65 for calibration and validation. The pre-buffer fuzzy system predicted event-based runoff for 30-50 times larger corn/soybean watersheds with r2 values of 0.82 and 0.68 and NSC values of 0.77 and 0.53, respectively. The runoff predicted by the fuzzy system closely agreed with values predicted by physically-based Agricultural Policy Environmental eXtender model (APEX) for the pre-buffer watersheds. The fuzzy rainfall-runoff model has the potential for runoff predictions at field-scale watersheds with minimum input. It also could up-scale the predictions for large-scale watersheds to evaluate the benefits of conservation practices.

Evaluating the predictive accuracy and the clinical benefit of a nomogram aimed to predict survival in node-positive prostate cancer patients: External validation on a multi-institutional database.

PubMed

Bianchi, Lorenzo; Schiavina, Riccardo; Borghesi, Marco; Bianchi, Federico Mineo; Briganti, Alberto; Carini, Marco; Terrone, Carlo; Mottrie, Alex; Gacci, Mauro; Gontero, Paolo; Imbimbo, Ciro; Marchioro, Giansilvio; Milanese, Giulio; Mirone, Vincenzo; Montorsi, Francesco; Morgia, Giuseppe; Novara, Giacomo; Porreca, Angelo; Volpe, Alessandro; Brunocilla, Eugenio

2018-04-06

To assess the predictive accuracy and the clinical value of a recent nomogram predicting cancer-specific mortality-free survival after surgery in pN1 prostate cancer patients through an external validation. We evaluated 518 prostate cancer patients treated with radical prostatectomy and pelvic lymph node dissection with evidence of nodal metastases at final pathology, at 10 tertiary centers. External validation was carried out using regression coefficients of the previously published nomogram. The performance characteristics of the model were assessed by quantifying predictive accuracy, according to the area under the curve in the receiver operating characteristic curve and model calibration. Furthermore, we systematically analyzed the specificity, sensitivity, positive predictive value and negative predictive value for each nomogram-derived probability cut-off. Finally, we implemented decision curve analysis, in order to quantify the nomogram's clinical value in routine practice. External validation showed inferior predictive accuracy as referred to in the internal validation (65.8% vs 83.3%, respectively). The discrimination (area under the curve) of the multivariable model was 66.7% (95% CI 60.1-73.0%) by testing with receiver operating characteristic curve analysis. The calibration plot showed an overestimation throughout the range of predicted cancer-specific mortality-free survival rates probabilities. However, in decision curve analysis, the nomogram's use showed a net benefit when compared with the scenarios of treating all patients or none. In an external setting, the nomogram showed inferior predictive accuracy and suboptimal calibration characteristics as compared to that reported in the original population. However, decision curve analysis showed a clinical net benefit, suggesting a clinical implication to correctly manage pN1 prostate cancer patients after surgery. © 2018 The Japanese Urological Association.

Development and validation of a novel predictive scoring model for microvascular invasion in patients with hepatocellular carcinoma.

PubMed

Zhao, Hui; Hua, Ye; Dai, Tu; He, Jian; Tang, Min; Fu, Xu; Mao, Liang; Jin, Huihan; Qiu, Yudong

2017-03-01

Microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) cannot be accurately predicted preoperatively. This study aimed to establish a predictive scoring model of MVI in solitary HCC patients without macroscopic vascular invasion. A total of 309 consecutive HCC patients who underwent curative hepatectomy were divided into the derivation (n=206) and validation cohort (n=103). A predictive scoring model of MVI was established according to the valuable predictors in the derivation cohort based on multivariate logistic regression analysis. The performance of the predictive model was evaluated in the derivation and validation cohorts. Preoperative imaging features on CECT, such as intratumoral arteries, non-nodular type of HCC and absence of radiological tumor capsule were independent predictors for MVI. The predictive scoring model was established according to the β coefficients of the 3 predictors. Area under receiver operating characteristic (AUROC) of the predictive scoring model was 0.872 (95% CI, 0.817-0.928) and 0.856 (95% CI, 0.771-0.940) in the derivation and validation cohorts. The positive and negative predictive values were 76.5% and 88.0% in the derivation cohort and 74.4% and 88.3% in the validation cohort. The performance of the model was similar between the patients with tumor size ≤5cm and >5cm in AUROC (P=0.910). The predictive scoring model based on intratumoral arteries, non-nodular type of HCC, and absence of the radiological tumor capsule on preoperative CECT is of great value in the prediction of MVI regardless of tumor size. Copyright © 2017 Elsevier B.V. All rights reserved.

Fast and simultaneous prediction of animal feed nutritive values using near infrared reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Samadi; Wajizah, S.; Munawar, A. A.

2018-02-01

Feed plays an important factor in animal production. The purpose of this study is to apply NIRS method in determining feed values. NIRS spectra data were acquired for feed samples in wavelength range of 1000 - 2500 nm with 32 scans and 0.2 nm wavelength. Spectral data were corrected by de-trending (DT) and standard normal variate (SNV) methods. Prediction of in vitro dry matter digestibility (IVDMD) and in vitro organic matter digestibility (IVOMD) were established as model by using principal component regression (PCR) and validated using leave one out cross validation (LOOCV). Prediction performance was quantified using coefficient correlation (r) and residual predictive deviation (RPD) index. The results showed that IVDMD and IVOMD can be predicted by using SNV spectra data with r and RPD index: 0.93 and 2.78 for IVDMD ; 0.90 and 2.35 for IVOMD respectively. In conclusion, NIRS technique appears feasible to predict animal feed nutritive values.

Computational Predictions of the Performance Wright 'Bent End' Propellers

NASA Technical Reports Server (NTRS)

Wang, Xiang-Yu; Ash, Robert L.; Bobbitt, Percy J.; Prior, Edwin (Technical Monitor)

2002-01-01

Computational analysis of two 1911 Wright brothers 'Bent End' wooden propeller reproductions have been performed and compared with experimental test results from the Langley Full Scale Wind Tunnel. The purpose of the analysis was to check the consistency of the experimental results and to validate the reliability of the tests. This report is one part of the project on the propeller performance research of the Wright 'Bent End' propellers, intend to document the Wright brothers' pioneering propeller design contributions. Two computer codes were used in the computational predictions. The FLO-MG Navier-Stokes code is a CFD (Computational Fluid Dynamics) code based on the Navier-Stokes Equations. It is mainly used to compute the lift coefficient and the drag coefficient at specified angles of attack at different radii. Those calculated data are the intermediate results of the computation and a part of the necessary input for the Propeller Design Analysis Code (based on Adkins and Libeck method), which is a propeller design code used to compute the propeller thrust coefficient, the propeller power coefficient and the propeller propulsive efficiency.

Prediction of jump phenomena in rotationally-coupled maneuvers of aircraft, including nonlinear aerodynamic effects

NASA Technical Reports Server (NTRS)

Young, J. W.; Schy, A. A.; Johnson, K. G.

1977-01-01

An analytical method has been developed for predicting critical control inputs for which nonlinear rotational coupling may cause sudden jumps in aircraft response. The analysis includes the effect of aerodynamics which are nonlinear in angle of attack. The method involves the simultaneous solution of two polynomials in roll rate, whose coefficients are functions of angle of attack and the control inputs. Results obtained using this procedure are compared with calculated time histories to verify the validity of the method for predicting jump-like instabilities.

Linearity and sex-specificity of impact force prediction during a fall onto the outstretched hand using a single-damper-model.

PubMed

Kawalilak, C E; Lanovaz, J L; Johnston, J D; Kontulainen, S A

2014-09-01

To assess the linearity and sex-specificity of damping coefficients used in a single-damper-model (SDM) when predicting impact forces during the worst-case falling scenario from fall heights up to 25 cm. Using 3-dimensional motion tracking and an integrated force plate, impact forces and impact velocities were assessed from 10 young adults (5 males; 5 females), falling from planted knees onto outstretched arms, from a random order of drop heights: 3, 5, 7, 10, 15, 20, and 25 cm. We assessed the linearity and sex-specificity between impact forces and impact velocities across all fall heights using analysis of variance linearity test and linear regression, respectively. Significance was accepted at P<0.05. Association between impact forces and impact velocities up to 25 cm was linear (P=0.02). Damping coefficients appeared sex-specific (males: 627 Ns/m, R(2)=0.70; females: 421 Ns/m; R(2)=0.81; sex combined: 532 Ns/m, R(2)=0.61). A linear damping coefficient used in the SDM proved valid for predicting impact forces from fall heights up to 25 cm. RESULTS suggested the use of sex-specific damping coefficients when estimating impact force using the SDM and calculating the factor-of-risk for wrist fractures.

Detrended cross-correlation coefficient: Application to predict apoptosis protein subcellular localization.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2016-12-01

Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.

Adaptation of clinical prediction models for application in local settings.

PubMed

Kappen, Teus H; Vergouwe, Yvonne; van Klei, Wilton A; van Wolfswinkel, Leo; Kalkman, Cor J; Moons, Karel G M

2012-01-01

When planning to use a validated prediction model in new patients, adequate performance is not guaranteed. For example, changes in clinical practice over time or a different case mix than the original validation population may result in inaccurate risk predictions. To demonstrate how clinical information can direct updating a prediction model and development of a strategy for handling missing predictor values in clinical practice. A previously derived and validated prediction model for postoperative nausea and vomiting was updated using a data set of 1847 patients. The update consisted of 1) changing the definition of an existing predictor, 2) reestimating the regression coefficient of a predictor, and 3) adding a new predictor to the model. The updated model was then validated in a new series of 3822 patients. Furthermore, several imputation models were considered to handle real-time missing values, so that possible missing predictor values could be anticipated during actual model use. Differences in clinical practice between our local population and the original derivation population guided the update strategy of the prediction model. The predictive accuracy of the updated model was better (c statistic, 0.68; calibration slope, 1.0) than the original model (c statistic, 0.62; calibration slope, 0.57). Inclusion of logistical variables in the imputation models, besides observed patient characteristics, contributed to a strategy to deal with missing predictor values at the time of risk calculation. Extensive knowledge of local, clinical processes provides crucial information to guide the process of adapting a prediction model to new clinical practices.

Clarifying Relationships among Work and Family Social Support, Stressors, and Work-Family Conflict

ERIC Educational Resources Information Center

Michel, Jesse S.; Mitchelson, Jacqueline K.; Pichler, Shaun; Cullen, Kristin L.

2010-01-01

Although work and family social support predict role stressors and work-family conflict, there has been much ambiguity regarding the conceptual relationships among these constructs. Using path analysis on meta-analytically derived validity coefficients (528 effect sizes from 156 samples), we compare three models to address these concerns and…

DEM modeling of ball mills with experimental validation: influence of contact parameters on charge motion and power draw

NASA Astrophysics Data System (ADS)

Boemer, Dominik; Ponthot, Jean-Philippe

2017-01-01

Discrete element method simulations of a 1:5-scale laboratory ball mill are presented in this paper to study the influence of the contact parameters on the charge motion and the power draw. The position density limit is introduced as an efficient mathematical tool to describe and to compare the macroscopic charge motion in different scenarios, i.a. with different values of the contact parameters. While the charge motion and the power draw are relatively insensitive to the stiffness and the damping coefficient of the linear spring-slider-damper contact law, the coefficient of friction has a strong influence since it controls the sliding propensity of the charge. Based on the experimental calibration and validation by charge motion photographs and power draw measurements, the descriptive and predictive capabilities of the position density limit and the discrete element method are demonstrated, i.e. the real position of the charge is precisely delimited by the respective position density limit and the power draw can be predicted with an accuracy of about 5 %.

Using boosted regression trees to predict the near-saturated hydraulic conductivity of undisturbed soils

NASA Astrophysics Data System (ADS)

Koestel, John; Bechtold, Michel; Jorda, Helena; Jarvis, Nicholas

2015-04-01

The saturated and near-saturated hydraulic conductivity of soil is of key importance for modelling water and solute fluxes in the vadose zone. Hydraulic conductivity measurements are cumbersome at the Darcy scale and practically impossible at larger scales where water and solute transport models are mostly applied. Hydraulic conductivity must therefore be estimated from proxy variables. Such pedotransfer functions are known to work decently well for e.g. water retention curves but rather poorly for near-saturated and saturated hydraulic conductivities. Recently, Weynants et al. (2009, Revisiting Vereecken pedotransfer functions: Introducing a closed-form hydraulic model. Vadose Zone Journal, 8, 86-95) reported a coefficients of determination of 0.25 (validation with an independent data set) for the saturated hydraulic conductivity from lab-measurements of Belgian soil samples. In our study, we trained boosted regression trees on a global meta-database containing tension-disk infiltrometer data (see Jarvis et al. 2013. Influence of soil, land use and climatic factors on the hydraulic conductivity of soil. Hydrology & Earth System Sciences, 17, 5185-5195) to predict the saturated hydraulic conductivity (Ks) and the conductivity at a tension of 10 cm (K10). We found coefficients of determination of 0.39 and 0.62 under a simple 10-fold cross-validation for Ks and K10. When carrying out the validation folded over the data-sources, i.e. the source publications, we found that the corresponding coefficients of determination reduced to 0.15 and 0.36, respectively. We conclude that the stricter source-wise cross-validation should be applied in future pedotransfer studies to prevent overly optimistic validation results. The boosted regression trees also allowed for an investigation of relevant predictors for estimating the near-saturated hydraulic conductivity. We found that land use and bulk density were most important to predict Ks. We also observed that Ks is large in fine and coarse textured soils and smaller in medium textured soils. Completely different predictors were important for appraising K10, where the soil macropore system is air-filled and therefore inactive. Here, the average annual temperature and precipitation where most important. The reasons for this are unclear and require further research. The clay content and the organic matter content were also important predictors of K10. We suggest that a larger and more complete database may help to improve the prediction of K10, whereas it may be more fruitful to estimate Ks statistics of sampling sites instead of individual values since the Ks is highly variable over very short distances.

External validation of preexisting first trimester preeclampsia prediction models.

PubMed

Allen, Rebecca E; Zamora, Javier; Arroyo-Manzano, David; Velauthar, Luxmilar; Allotey, John; Thangaratinam, Shakila; Aquilina, Joseph

2017-10-01

To validate the increasing number of prognostic models being developed for preeclampsia using our own prospective study. A systematic review of literature that assessed biomarkers, uterine artery Doppler and maternal characteristics in the first trimester for the prediction of preeclampsia was performed and models selected based on predefined criteria. Validation was performed by applying the regression coefficients that were published in the different derivation studies to our cohort. We assessed the models discrimination ability and calibration. Twenty models were identified for validation. The discrimination ability observed in derivation studies (Area Under the Curves) ranged from 0.70 to 0.96 when these models were validated against the validation cohort, these AUC varied importantly, ranging from 0.504 to 0.833. Comparing Area Under the Curves obtained in the derivation study to those in the validation cohort we found statistically significant differences in several studies. There currently isn't a definitive prediction model with adequate ability to discriminate for preeclampsia, which performs as well when applied to a different population and can differentiate well between the highest and lowest risk groups within the tested population. The pre-existing large number of models limits the value of further model development and future research should be focussed on further attempts to validate existing models and assessing whether implementation of these improves patient care. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Near-infrared and Mid-infrared Spectroscopic Techniques for a Fast and Nondestructive Quality Control of Thymi herba.

PubMed

Pezzei, Cornelia K; Schönbichler, Stefan A; Hussain, Shah; Kirchler, Christian G; Huck-Pezzei, Verena A; Popp, Michael; Krolitzek, Justine; Bonn, Günther K; Huck, Christian W

2018-04-01

In this study, novel near-infrared and attenuated total reflectance mid-infrared spectroscopic methods coupled with multivariate data analysis were established enabling the determination of thymol, rosmarinic acid, and the antioxidant capacity of Thymi herba. A new high-performance liquid chromatography method and UV-Vis spectroscopy were applied as reference methods. Partial least squares regressions were carried out as cross and test set validations. To reduce systematic errors, different data pretreatments, such as multiplicative scatter correction, 1st derivative, or 2nd derivative, were applied on the spectra. The performances of the two infrared spectroscopic techniques were evaluated and compared. In general, attenuated total reflectance mid-infrared spectroscopy demonstrated a slightly better predictive power (thymol: coefficient of determination = 0.93, factors = 3, ratio of performance to deviation = 3.94; rosmarinic acid: coefficient of determination = 0.91, factors = 3, ratio of performance to deviation = 3.35, antioxidant capacity: coefficient of determination = 0.87, factors = 2, ratio of performance to deviation = 2.80; test set validation) than near-infrared spectroscopy (thymol: coefficient of determination = 0.90, factors = 6, ratio of performance to deviation = 3.10; rosmarinic acid: coefficient of determination = 0.92, factors = 6, ratio of performance to deviation = 3.61, antioxidant capacity: coefficient of determination = 0.91, factors = 6, ratio of performance to deviation = 3.42; test set validation). The capability of infrared vibrational spectroscopy as a quick and simple analytical tool to replace conventional time and chemical consuming analyses for the quality control of T. herba could be demonstrated. Georg Thieme Verlag KG Stuttgart · New York.

Validation of the FACT-B+4-UL questionnaire and exploration of its predictive value in women submitted to surgery for breast cancer.

PubMed

Andrade Ortega, Juan Alfonso; Millán Gómez, Ana Pilar; Ribeiro González, Marisa; Martínez Piró, Pilar; Jiménez Anula, Juan; Sánchez Andújar, María Belén

2017-06-21

The early detection of upper limb complications is important in women operated on for breast cancer. The "FACT-B+4-UL" questionnaire, a specific variant of the Functional Assessment of Cancer Therapy-Breast (FACT-B) is available among others to measure the upper limb function. The Spanish version of the upper limb subscale of the FACT-B+4 was validated in a prospective cohort of 201 women operated on for breast cancer (factor analysis, internal consistency, test-retest reliability, construct validity and sensitivity to change were determined). Its predictive capacity of subsequent lymphoedema and other complications in the upper limb was explored using logistic regression. This subscale is unifactorial and has a great internal consistency (Cronbach's alpha: 0.87), its test-retest reliability and construct validity are strong (intraclass correlation coefficient: 0.986; Pearson's R with "Quick DASH": 0.81) as is its sensitivity to change. It didn't predict the onset of lymphedema. Its predictive capacity for other upper limb complications is low. FACT-B+4-UL is useful in measuring upper limb disability in women surgically treated for breast cancer; but it does not predict the onset of lymphoedema and its predictive capacity for others complications in the upper limb is low. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

A New Lebanese Medication Adherence Scale: Validation in Lebanese Hypertensive Adults.

PubMed

Bou Serhal, R; Salameh, P; Wakim, N; Issa, C; Kassem, B; Abou Jaoude, L; Saleh, N

2018-01-01

A new Lebanese scale measuring medication adherence considered socioeconomic and cultural factors not taken into account by the eight-item Morisky Medication Adherence Scale (MMAS-8). Objectives were to validate the new adherence scale and its prediction of hypertension control, compared to MMAS-8, and to assess adherence rates and factors. A cross-sectional study, including 405 patients, was performed in outpatient cardiology clinics of three hospitals in Beirut. Blood pressure was measured, a questionnaire filled, and sodium intake estimated by a urine test. Logistic regression defined predictors of hypertension control and adherence. 54.9% had controlled hypertension. 82.4% were adherent by the new scale, which showed good internal consistency, adequate questions (KMO coefficient = 0.743), and four factors. It predicted hypertension control (OR = 1.217; p value = 0.003), unlike MMAS-8, but the scores were correlated (ICC average measure = 0.651; p value < 0.001). Stress and smoking predicted nonadherence. This study elaborated a validated, practical, and useful tool measuring adherence to medications in Lebanese hypertensive patients.

Validity of parent's self-reported responses to home safety questions.

PubMed

Osborne, Jodie M; Shibl, Rania; Cameron, Cate M; Kendrick, Denise; Lyons, Ronan A; Spinks, Anneliese B; Sipe, Neil; McClure, Roderick J

2016-09-01

The aim of the study was to describe the validity of parent's self-reported responses to questions on home safety practices for children of 2-4 years. A cross-sectional validation study compared parent's self-administered responses to items in the Home Injury Prevention Survey with home observations undertaken by trained researchers. The relationship between the questionnaire and observation results was assessed using percentage agreement, sensitivity, specificity, positive predictive value, negative predictive value and intraclass correlation coefficients. Percentage agreements ranged from 44% to 100% with 40 of the total 45 items scoring higher than 70%. Sensitivities ranged from 0% to 100%, with 27 items scoring at least 70%. Specificities also ranged from 0% to 100%, with 33 items scoring at least 70%. As such, the study identified a series of self-administered home safety questions that have sensitivities, specificities and predictive values sufficiently high to allow the information to be useful in research and injury prevention practice.

Fatty acid profile of plasma NEFA does not reflect adipose tissue fatty acid profile.

PubMed

Walker, Celia G; Browning, Lucy M; Stecher, Lynne; West, Annette L; Madden, Jackie; Jebb, Susan A; Calder, Philip C

2015-09-14

Adipose tissue (AT) fatty acid (FA) composition partly reflects habitual dietary intake. Circulating NEFA are mobilised from AT and might act as a minimally invasive surrogate marker of AT FA profile. Agreement between twenty-eight FA in AT and plasma NEFA was assessed using concordance coefficients in 204 male and female participants in a 12-month intervention using supplements to increase the intake of EPA and DHA. Concordance coefficients generally showed very poor agreement between AT FA and plasma NEFA at baseline SFA: 0·07; MUFA: 0·03; n-6 PUFA: 0·28; n-3 PUFA: 0·01). Participants were randomly divided into training (70 %) and validation (30 %) data sets, and models to predict AT and dietary FA were fitted using data from the training set, and their predictive ability was assessed using data from the validation set. AT n-6 PUFA and SFA were predicted from plasma NEFA with moderate accuracy (mean absolute percentage error n-6 PUFA: 11 % and SFA: 8 %), but predicted values were unable to distinguish between low, medium and high FA values, with only 25 % of n-6 PUFA and 33 % of SFA predicted values correctly assigned to the appropriate tertile group. Despite an association between AT and plasma NEFA EPA (P=0·001) and DHA (P=0·01) at baseline, there was no association after the intervention. To conclude, plasma NEFA are not a suitable surrogate for AT FA.

A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics

DOE PAGES

Mabey, P.; Richardson, S.; White, T. G.; ...

2017-01-30

We determined the state and evolution of planets, brown dwarfs and neutron star crusts by the properties of dense and compressed matter. Furthermore, due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ionmore » modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. These results have profound consequences in the interpretation of transport coefficients in dense plasmas.« less

Determination of heat capacity of ionic liquid based nanofluids using group method of data handling technique

NASA Astrophysics Data System (ADS)

Sadi, Maryam

2018-01-01

In this study a group method of data handling model has been successfully developed to predict heat capacity of ionic liquid based nanofluids by considering reduced temperature, acentric factor and molecular weight of ionic liquids, and nanoparticle concentration as input parameters. In order to accomplish modeling, 528 experimental data points extracted from the literature have been divided into training and testing subsets. The training set has been used to predict model coefficients and the testing set has been applied for model validation. The ability and accuracy of developed model, has been evaluated by comparison of model predictions with experimental values using different statistical parameters such as coefficient of determination, mean square error and mean absolute percentage error. The mean absolute percentage error of developed model for training and testing sets are 1.38% and 1.66%, respectively, which indicate excellent agreement between model predictions and experimental data. Also, the results estimated by the developed GMDH model exhibit a higher accuracy when compared to the available theoretical correlations.

QSAR models for predicting octanol/water and organic carbon/water partition coefficients of polychlorinated biphenyls.

PubMed

Yu, S; Gao, S; Gan, Y; Zhang, Y; Ruan, X; Wang, Y; Yang, L; Shi, J

2016-04-01

Quantitative structure-property relationship modelling can be a valuable alternative method to replace or reduce experimental testing. In particular, some endpoints such as octanol-water (KOW) and organic carbon-water (KOC) partition coefficients of polychlorinated biphenyls (PCBs) are easier to predict and various models have been already developed. In this paper, two different methods, which are multiple linear regression based on the descriptors generated using Dragon software and hologram quantitative structure-activity relationships, were employed to predict suspended particulate matter (SPM) derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of 209 PCBs. The predictive ability of the derived models was validated using a test set. The performances of all these models were compared with EPI Suite™ software. The results indicated that the proposed models were robust and satisfactory, and could provide feasible and promising tools for the rapid assessment of the SPM derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of PCBs.

Linguistic adaptation, validation and comparison of 3 routinely used neuropathic pain questionnaires.

PubMed

Li, Jun; Feng, Yi; Han, Jisheng; Fan, Bifa; Wu, Dasheng; Zhang, Daying; Du, Dongping; Li, Hui; Lim, Jian; Wang, Jiashuang; Jin, Yi; Fu, Zhijian

2012-01-01

Neuropathic pain questionnaires are efficient diagnostic tools for neuropathic pain and play an important role in neuropathic pain epidemiologic studies in China. No comparison data was available in regards to the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS), the Neuropathic Pain Questionnaire (NPQ) and ID Pain within and among the same population. To achieve a linguistic adaptation, validation, and comparison of Chinese versions of the 3 neuropathic pain questionnaires (LANSS, NPQ and ID Pain). A nonrandomized, controlled, prospective, multicenter trial. Ten pain centers in China. Two forward translations followed by comparison and reconciliation of the translations. Comparison of the 2 backward translations with the original version was made to establish consistency and accuracy of the translations. Pilot testing and pain specialists' evaluations were also required. A total of 140 patients were enrolled in 10 centers throughout China: 70 neuropathic pain patients and 70 nociceptive pain patients. Reliability (Cronbach's alpha coefficients and Guttman split-half coefficients) and validity (sensitivity, specificity, positive and negative predictive values, receiver operating characteristic [ROC] curves and the area under the ROC curves) of the 3 questionnaires were determined. ROC curves and the area under the ROC curves of the 3 questionnaires were also compared. Chinese versions of LANSS, NPQ and ID Pain had a good reliability (Cronbach's alpha coefficients and Guttman split-half coefficients were greater than 0.7). Sensitivity, specificity, positive and negative predictive values of the Chinese versions of LANSS and ID Pain were considerably high ( > 80%). The area under the ROC curves of LANSS and ID Pain was significantly higher than that of NPQ (P < 0.05). There was no statistically significant difference between the area under the ROC curves of LANSS and ID Pain (P > 0.05). The study was based on patients with a high school degree or above, which limited the application of the 3 neuropathic pain questionnaires to patients with lower educational levels. The Chinese versions of LANSS and ID Pain developed and validated by this study can be used as a diagnostic tool in differentiating neuropathic pain in patients whose native language is Chinese (Mandarin).

An appraisal of the psychometric properties of the Clinician version of the Apathy Evaluation Scale (AES-C).

PubMed

Clarke, Diana E; Van Reekum, Robert; Patel, Jigisha; Simard, Martine; Gomez, Everlyne; Streiner, David L

2007-01-01

This article examines the psychometric properties of the clinician version of the Apathy Evaluation Scale (AES-C) to determine its ability to characterize, quantify and differentiate apathy. Critical appraisals of the item-reduction processes, effectiveness of the administration, coding and scoring procedures, and the reliability and validity of the scale were carried out. For training, administration and rating of the AES-C, clearer guidelines, including a more standardized list of verbal and non-verbal apathetic cues, are needed. There is evidence of high internal consistency for the scale across studies. In addition, the original study reported good test-retest and inter-rater reliability coefficients. However, there is a lack of replication on these more stable and informative measures of reliability and as such they warrant further investigation. The research evidence confirms that the AES-C shows good discriminant, convergent and criterion validity. However, evidence of its predictive validity is limited. As this aspect of validity refers to the scale's ability to predict future outcomes, which is important for treatment and rehabilitation planning, further assessment of the predictive validity of the AES-C is needed. In conclusion, the AES-C is a reliable and valid measure for the characterization and quantification of apathy. Copyright (c) 2007 John Wiley & Sons, Ltd.

Development and validation of Arabic version of the douleur neuropathique 4 questionnaire.

PubMed

Terkawi, Abdullah Sulieman; Abolkhair, Abdullah; Didier, Bouhassira; Alzhahrani, Tariq; Alsohaibani, Mazen; Terkawi, Yazzed Sulieman; Almoqbali, Yousuf; Tolba, Yasser Younis; Pangililan, Evelyn; Foula, Farida; Tsang, Siny

2017-05-01

The douleur neuropathique 4 (DN4) questionnaire is a widely used tool for diagnosis of neuropathic pain (NP). The aim was to translate, culturally adapt, and validate the DN4 questionnaire in Arabic. A systematic translation process was used to translate the original English DN4 into Arabic. After the pilot study, the Arabic version was validated among patients with chronic pain in two tertiary care centers. The reliability of the translated version was examined using internal consistency, test-retest reliability, and intraclass correlation coefficients. We examined the validity of the Arabic DN4 via construct validity, concurrent validity (associations with the numeric rating scale, brief pain inventory, and Self-Completed Leeds Assessment of Neuropathic Symptoms and Signs [S-LANSS]), face validity, and diagnostic validity. To investigate the responsiveness, the translated DN4 was administered twice among the same group of patients. A total of 142 subjects (68 men, 74 women) were included in the study. Cronbach's α was 0.67 (95% confidence interval [CI]: 0.59-0.75), and interclass correlation coefficients was 0.81 (95% CI: 0.76-0.87). The DN4 was moderately associated with the S-LANSS questionnaire. Results showed our Arabic DN4 to have good diagnostic accuracy, with area under the curve of 0.88 (95% CI: 0.82-0.94). As with the original version, a score of ≥4 was found to be the best cut-off for the diagnosis of NP, with a sensitivity of 88.31%, specificity of 74.47%, a positive predictive value of 85%, and a negative predictive value of 80%. Most patients found the DN4 questionnaire to be clear and easy to understand, and thought the questionnaire items covered all their problem areas regarding their pain. Our Arabic version of the DN4 is a reliable and valid screening tool that can be easily administered among patients to differentiate between NP and non-NP.

Copula based prediction models: an application to an aortic regurgitation study

PubMed Central

Kumar, Pranesh; Shoukri, Mohamed M

2007-01-01

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively. Conclusion: Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples. PMID:17573974

WHipple-ABACUS, a simple, validated risk score for 30-day mortality after pancreaticoduodenectomy developed using the ACS-NSQIP database.

PubMed

Gleeson, Elizabeth M; Shaikh, Mohammad F; Shewokis, Patricia A; Clarke, John R; Meyers, William C; Pitt, Henry A; Bowne, Wilbur B

2016-11-01

Pancreaticoduodenectomy needs simple, validated risk models to better identify 30-day mortality. The goal of this study is to develop a simple risk score to predict 30-day mortality after pancreaticoduodenectomy. We reviewed cases of pancreaticoduodenectomy from 2005-2012 in the American College of Surgeons-National Surgical Quality Improvement Program databases. Logistic regression was used to identify preoperative risk factors for morbidity and mortality from a development cohort. Scores were created using weighted beta coefficients, and predictive accuracy was assessed on the validation cohort using receiver operator characteristic curves and measuring area under the curve. The 30-day mortality rate was 2.7% for patients who underwent pancreaticoduodenectomy (n = 14,993). We identified 8 independent risk factors. The score created from weighted beta coefficients had an area under the curve of 0.71 (95% confidence interval, 0.66-0.77) on the validation cohort. Using the score WHipple-ABACUS (hypertension With medication + History of cardiac surgery + Age >62 + 2 × Bleeding disorder + Albumin <3.5 g/dL + 2 × disseminated Cancer + 2 × Use of steroids + 2 × Systemic inflammatory response syndrome), mortality rates increase with increasing score (P < .001). While other risk scores exist for 30-day mortality after pancreaticoduodenectomy, we present a simple, validated score developed using exclusively preoperative predictors surgeons could use to identify patients at risk for this procedure. Copyright © 2016 Elsevier Inc. All rights reserved.

Sensitivity Analysis of the Integrated Medical Model for ISS Programs

NASA Technical Reports Server (NTRS)

Goodenow, D. A.; Myers, J. G.; Arellano, J.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Young, M.

2016-01-01

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

Development, test-retest reliability and validity of the Pharmacy Value-Added Services Questionnaire (PVASQ).

PubMed

Tan, Christine L; Hassali, Mohamed A; Saleem, Fahad; Shafie, Asrul A; Aljadhey, Hisham; Gan, Vincent B

2015-01-01

(i) To develop the Pharmacy Value-Added Services Questionnaire (PVASQ) using emerging themes generated from interviews. (ii) To establish reliability and validity of questionnaire instrument. Using an extended Theory of Planned Behavior as the theoretical model, face-to-face interviews generated salient beliefs of pharmacy value-added services. The PVASQ was constructed initially in English incorporating important themes and later translated into the Malay language with forward and backward translation. Intention (INT) to adopt pharmacy value-added services is predicted by attitudes (ATT), subjective norms (SN), perceived behavioral control (PBC), knowledge and expectations. Using a 7-point Likert-type scale and a dichotomous scale, test-retest reliability (N=25) was assessed by administrating the questionnaire instrument twice at an interval of one week apart. Internal consistency was measured by Cronbach's alpha and construct validity between two administrations was assessed using the kappa statistic and the intraclass correlation coefficient (ICC). Confirmatory Factor Analysis, CFA (N=410) was conducted to assess construct validity of the PVASQ. The kappa coefficients indicate a moderate to almost perfect strength of agreement between test and retest. The ICC for all scales tested for intra-rater (test-retest) reliability was good. The overall Cronbach' s alpha (N=25) is 0.912 and 0.908 for the two time points. The result of CFA (N=410) showed most items loaded strongly and correctly into corresponding factors. Only one item was eliminated. This study is the first to develop and establish the reliability and validity of the Pharmacy Value-Added Services Questionnaire instrument using the Theory of Planned Behavior as the theoretical model. The translated Malay language version of PVASQ is reliable and valid to predict Malaysian patients' intention to adopt pharmacy value-added services to collect partial medicine supply.

Validity and reliability of the Spanish version of the DN4 (Douleur Neuropathique 4 questions) questionnaire for differential diagnosis of pain syndromes associated to a neuropathic or somatic component

PubMed Central

Perez, Concepcion; Galvez, Rafael; Huelbes, Silvia; Insausti, Joaquin; Bouhassira, Didier; Diaz, Silvia; Rejas, Javier

2007-01-01

Background This study assesses the validity and reliability of the Spanish version of DN4 questionnaire as a tool for differential diagnosis of pain syndromes associated to a neuropathic (NP) or somatic component (non-neuropathic pain, NNP). Methods A study was conducted consisting of two phases: cultural adaptation into the Spanish language by means of conceptual equivalence, including forward and backward translations in duplicate and cognitive debriefing, and testing of psychometric properties in patients with NP (peripheral, central and mixed) and NNP. The analysis of psychometric properties included reliability (internal consistency, inter-rater agreement and test-retest reliability) and validity (ROC curve analysis, agreement with the reference diagnosis and determination of sensitivity, specificity, and positive and negative predictive values in different subsamples according to type of NP). Results A sample of 164 subjects (99 women, 60.4%; age: 60.4 ± 16.0 years), 94 (57.3%) with NP (36 with peripheral, 32 with central, and 26 with mixed pain) and 70 with NNP was enrolled. The questionnaire was reliable [Cronbach's alpha coefficient: 0.71, inter-rater agreement coefficient: 0.80 (0.71–0.89), and test-retest intra-class correlation coefficient: 0.95 (0.92–0.97)] and valid for a cut-off value ≥ 4 points, which was the best value to discriminate between NP and NNP subjects. Discussion This study, representing the first validation of the DN4 questionnaire into another language different than the original, not only supported its high discriminatory value for identification of neuropathic pain, but also provided supplemental psychometric validation (i.e. test-retest reliability, influence of educational level and pain intensity) and showed its validity in mixed pain syndromes. PMID:18053212

A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

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

Huang, Shengzhi; Ming, Bo; Huang, Qiang

It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four orecastingmore » models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.« less

Kinetic modeling of α-hydrogen abstractions from unsaturated and saturated oxygenate compounds by hydrogen atoms.

PubMed

Paraskevas, Paschalis D; Sabbe, Maarten K; Reyniers, Marie-Françoise; Papayannakos, Nikos G; Marin, Guy B

2014-10-09

Hydrogen-abstraction reactions play a significant role in thermal biomass conversion processes, as well as regular gasification, pyrolysis, or combustion. In this work, a group additivity model is constructed that allows prediction of reaction rates and Arrhenius parameters of hydrogen abstractions by hydrogen atoms from alcohols, ethers, esters, peroxides, ketones, aldehydes, acids, and diketones in a broad temperature range (300-2000 K). A training set of 60 reactions was developed with rate coefficients and Arrhenius parameters calculated by the CBS-QB3 method in the high-pressure limit with tunneling corrections using Eckart tunneling coefficients. From this set of reactions, 15 group additive values were derived for the forward and the reverse reaction, 4 referring to primary and 11 to secondary contributions. The accuracy of the model is validated upon an ab initio and an experimental validation set of 19 and 21 reaction rates, respectively, showing that reaction rates can be predicted with a mean factor of deviation of 2 for the ab initio and 3 for the experimental values. Hence, this work illustrates that the developed group additive model can be reliably applied for the accurate prediction of kinetics of α-hydrogen abstractions by hydrogen atoms from a broad range of oxygenates.

Chemical structure-based predictive model for the oxidation of trace organic contaminants by sulfate radical.

PubMed

Ye, Tiantian; Wei, Zongsu; Spinney, Richard; Tang, Chong-Jian; Luo, Shuang; Xiao, Ruiyang; Dionysiou, Dionysios D

2017-06-01

Second-order rate constants [Formula: see text] for the reaction of sulfate radical anion (SO 4 •- ) with trace organic contaminants (TrOCs) are of scientific and practical importance for assessing their environmental fate and removal efficiency in water treatment systems. Here, we developed a chemical structure-based model for predicting [Formula: see text] using 32 molecular fragment descriptors, as this type of model provides a quick estimate at low computational cost. The model was constructed using the multiple linear regression (MLR) and artificial neural network (ANN) methods. The MLR method yielded adequate fit for the training set (R training 2 =0.88,n=75) and reasonable predictability for the validation set (R validation 2 =0.62,n=38). In contrast, the ANN method produced a more statistical robustness but rather poor predictability (R training 2 =0.99andR validation 2 =0.42). The reaction mechanisms of SO 4 •- reactivity with TrOCs were elucidated. Our result shows that the coefficients of functional groups reflect their electron donating/withdrawing characters. For example, electron donating groups typically exhibit positive coefficients, indicating enhanced SO 4 •- reactivity. Electron withdrawing groups exhibit negative values, indicating reduced reactivity. With its quick and accurate features, we applied this structure-based model to 55 discrete TrOCs culled from the Contaminant Candidate List 4, and quantitatively compared their removal efficiency with SO 4 •- and OH in the presence of environmental matrices. This high-throughput model helps prioritize TrOCs that are persistent to SO 4 •- based oxidation technologies at the screening level, and provide diagnostics of SO 4 •- reaction mechanisms. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-temperature langatate elastic constants and experimental validation up to 900 degrees C.

PubMed

Davulis, Peter M; da Cunha, Mauricio Pereira

2010-01-01

This paper reports on a set of langatate (LGT) elastic constants extracted from room temperature to 1100 degrees C using resonant ultrasound spectroscopy techniques and an accompanying assessment of these constants at high temperature. The evaluation of the constants employed SAW device measurements from room temperature to 900 degrees C along 6 different LGT wafer orientations. Langatate parallelepipeds and wafers were aligned, cut, ground, and polished, and acoustic wave devices were fabricated at the University of Maine facilities along specific orientations for elastic constant extraction and validation. SAW delay lines were fabricated on LGT wafers prepared at the University of Maine using 100-nm platinumrhodium- zirconia electrodes capable of withstanding temperatures up to 1000 degrees C. The numerical predictions based on the resonant ultrasound spectroscopy high-temperature constants were compared with SAW phase velocity, fractional frequency variation, and temperature coefficients of delay extracted from SAW delay line frequency response measurements. In particular, the difference between measured and predicted fractional frequency variation is less than 2% over the 25 degrees C to 900 degrees C temperature range and within the calculated and measured discrepancies. Multiple temperature-compensated orientations at high temperature were predicted and verified in this paper: 4 of the measured orientations had turnover temperatures (temperature coefficient of delay = 0) between 200 and 420 degrees C, and 2 had turnover temperatures below 100 degrees C. In summary, this work reports on extracted high-temperature elastic constants for LGT up to 1100 degrees C, confirmed the validity of those constants by high-temperature SAW device measurements up to 900 degrees C, and predicted and identified temperature-compensated LGT orientations at high temperature.

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

[Reliability and validity of the modified Perceived Health Competence Scale (PHCS) Japanese version].

PubMed

Togari, Taisuke; Yamazaki, Yoshihiko; Koide, Syotaro; Miyata, Ayako

2006-01-01

In community and workplace health plans, the Perceived Health Competence Scale (PHCS) is employed as an index of health competency. The purpose of this research was to examine the reliability and validity of a modified Japanese PHCS. Interviews were sought with 3,000 randomly selected Japanese individuals using a two-step stratified method. Valid PHCS responses were obtained from 1,910 individuals, yielding a 63.7% response rate. Reliability was assessed using Cronbach's alpha coefficient (henceforth, alpha) to evaluate internal consistency, and by employing item-total correlation and alpha coefficient analyses to assess the effect of removal of variables from the model. To examine content validity, we assessed the correlation between the PHCS score and four respondent attribute characteristics, that is, sex, age, the presence of chronic disease, and the existence of chronic disease at age 18. The correlation between PHCS score and commonly employed healthy lifestyle indices was examined to assess construct validity. General linear model statistical analysis was employed. The modified Japanese PHCS demonstrated a satisfactory alpha coefficient of 0.869. Moreover, reliability was confirmed by item-total correlation and alpha coefficient analyses after removal of variables from the model. Differences in PHCS scores were seen between individuals 60 years and older, and younger individuals. These with current chronic disease, or who had had a chronic disease at age 18, tended to have lower PHCS scores. After controlling for the presence of current or age 18 chronic disease, age, and sex, significant correlations were seen between PHCS scores and tobacco use, dietary habits, and exercise, but not alcohol use or frequency of medical consultation. This study supports the reliability and validity, and hence supports the use, of the modified Japanese PHCS. Future longitudinal research is needed to evaluate the predictive power of modified Japanese PHCS scores, to examine factors influencing the development of perceived health competence, and to assess the effects of interventions on perceived health competence.

[Validation of the abbreviated Zarit scales for measuring burden syndrome in the primary caregiver of an elderly patient].

PubMed

Vélez Lopera, Johana María; Berbesí Fernández, Dedsy; Cardona Arango, Doris; Segura Cardona, Angela; Ordóñez Molina, Jaime

2012-07-01

To determine which abbreviated Zarit Scale (ZS) better evaluates the burden of the caregiver of an elderly patient in Medellin, Colombia. Validation study. Primary Care setting in the city of Medellin. Primary caregiver of dependent elderly patients over 65 years old. Sensitivity, specificity, positive predictive value, and negative predictive value for the different abbreviated Zarit scales, plus performing a reliability analysis using the Cronbach Alpha coefficient. The abbreviated scales obtained a sensitivity of between 36.84 and 81.58%, specificity between 95.99 and 100%, positive predictive values between 71.05 and 100%, and negative predictive values of between 91.64 and 97.42%. The scale that better determined caregiver burden in Primary Care was the Bedard Screening scale, with a sensitivity of 81.58%, a specificity of 96.35% and positive and negative predictive values of 75.61% and 97.42%, respectively. Copyright © 2010 Elsevier España, S.L. All rights reserved.

Combined 3D-QSAR and molecular docking study on 7,8-dialkyl-1,3-diaminopyrrolo-[3,2-f] Quinazoline series compounds to understand the binding mechanism of DHFR inhibitors

NASA Astrophysics Data System (ADS)

Aouidate, Adnane; Ghaleb, Adib; Ghamali, Mounir; Chtita, Samir; Choukrad, M'barek; Sbai, Abdelouahid; Bouachrine, Mohammed; Lakhlifi, Tahar

2017-07-01

A series of nineteen DHFR inhibitors was studied based on the combination of two computational techniques namely, three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking. The comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were developed using 19 molecules having pIC50 ranging from 9.244 to 5.839. The best CoMFA and CoMSIA models show conventional determination coefficients R2 of 0.96 and 0.93 as well as the Leave One Out cross-validation determination coefficients Q2 of 0.64 and 0.72, respectively. The predictive ability of those models was evaluated by the external validation using a test set of five compounds with predicted determination coefficients R2test of 0.92 and 0.94, respectively. The binding mode between this kind of compounds and the DHFR enzyme in addition to the key amino acid residues were explored by molecular docking simulation. Contour maps and molecular docking identified that the R1 and R2 natures at the pyrazole moiety are the important features for the optimization of the binding affinity to the DHFR receptor. According to the good concordance between the CoMFA/CoMSIA contour maps and docking results, the obtained information was explored to design novel molecules.

Developing a stroke severity index based on administrative data was feasible using data mining techniques.

PubMed

Sung, Sheng-Feng; Hsieh, Cheng-Yang; Kao Yang, Yea-Huei; Lin, Huey-Juan; Chen, Chih-Hung; Chen, Yu-Wei; Hu, Ya-Han

2015-11-01

Case-mix adjustment is difficult for stroke outcome studies using administrative data. However, relevant prescription, laboratory, procedure, and service claims might be surrogates for stroke severity. This study proposes a method for developing a stroke severity index (SSI) by using administrative data. We identified 3,577 patients with acute ischemic stroke from a hospital-based registry and analyzed claims data with plenty of features. Stroke severity was measured using the National Institutes of Health Stroke Scale (NIHSS). We used two data mining methods and conventional multiple linear regression (MLR) to develop prediction models, comparing the model performance according to the Pearson correlation coefficient between the SSI and the NIHSS. We validated these models in four independent cohorts by using hospital-based registry data linked to a nationwide administrative database. We identified seven predictive features and developed three models. The k-nearest neighbor model (correlation coefficient, 0.743; 95% confidence interval: 0.737, 0.749) performed slightly better than the MLR model (0.742; 0.736, 0.747), followed by the regression tree model (0.737; 0.731, 0.742). In the validation cohorts, the correlation coefficients were between 0.677 and 0.725 for all three models. The claims-based SSI enables adjusting for disease severity in stroke studies using administrative data. Copyright © 2015 Elsevier Inc. All rights reserved.

AHRQ's hospital survey on patient safety culture: psychometric analyses.

PubMed

Blegen, Mary A; Gearhart, Susan; O'Brien, Roxanne; Sehgal, Niraj L; Alldredge, Brian K

2009-09-01

This project analyzed the psychometric properties of the Agency for Healthcare Research and Quality Hospital Survey on Patient Safety Culture (HSOPSC) including factor structure, interitem reliability and intraclass correlations, usefulness for assessment, predictive validity, and sensitivity. The survey was administered to 454 health care staff in 3 hospitals before and after a series of multidisciplinary interventions designed to improve safety culture. Respondents (before, 434; after, 368) included nurses, physicians, pharmacists, and other hospital staff members. Factor analysis partially confirmed the validity of the HSOPSC subscales. Interitem consistency reliability was above 0.7 for 5 subscales; the staffing subscale had the lowest reliability coefficients. The intraclass correlation coefficients, agreement among the members of each unit, were within recommended ranges. The pattern of high and low scores across the subscales of the HSOPSC in the study hospitals were similar to the sample of Pacific region hospitals reported by the Agency for Healthcare Research and Quality and corresponded to the proportion of items in each subscale that are worded negatively (reverse scored). Most of the unit and hospital dimensions were correlated with the Safety Grade outcome measure in the tool. Overall, the tool was shown to have moderate-to-strong validity and reliability, with the exception of the staffing subscale. The usefulness in assessing areas of strength and weakness for hospitals or units among the culture subscales is questionable. The culture subscales were shown to correlate with the perceived outcomes, but further study is needed to determine true predictive validity.

A reduced-order integral formulation to account for the finite size effect of isotropic square panels using the transfer matrix method.

PubMed

Bonfiglio, Paolo; Pompoli, Francesco; Lionti, Riccardo

2016-04-01

The transfer matrix method is a well-established prediction tool for the simulation of sound transmission loss and the sound absorption coefficient of flat multilayer systems. Much research has been dedicated to enhancing the accuracy of the method by introducing a finite size effect of the structure to be simulated. The aim of this paper is to present a reduced-order integral formulation to predict radiation efficiency and radiation impedance for a panel with equal lateral dimensions. The results are presented and discussed for different materials in terms of radiation efficiency, sound transmission loss, and the sound absorption coefficient. Finally, the application of the proposed methodology for rectangular multilayer systems is also investigated and validated against experimental data.

Effect of damage on elastically tailored composite laminates

NASA Technical Reports Server (NTRS)

Armanios, Erian; Badir, Ashraf; Berdichevsky, Victor

1991-01-01

A variationally consistent theory is derived in order to predict the response of anisotropic thin-walled closed sections subjected to axial load, torsion and bending. The theory is valid for arbitrary cross-sections made of laminated composite materials with variable thickness and stiffness. Closed form expressions for the stiffness coefficients are provided as integrals in terms of lay-ups parameters and cross-sectional geometry. A comparison of stiffness coefficients and response with finite element predictions and a closed form solution is performed. The theory is applied to the investigation of the effect of damage on the extension-twist coupling in a thin-walled closed section beam. The damage is simulated as a progressive ply-by-ply failure. Results show that damage can have a significant effect on the extension-twist coupling.

Development of polyparameter linear free energy relationship models for octanol-air partition coefficients of diverse chemicals.

PubMed

Jin, Xiaochen; Fu, Zhiqiang; Li, Xuehua; Chen, Jingwen

2017-03-22

The octanol-air partition coefficient (K OA ) is a key parameter describing the partition behavior of organic chemicals between air and environmental organic phases. As the experimental determination of K OA is costly, time-consuming and sometimes limited by the availability of authentic chemical standards for the compounds to be determined, it becomes necessary to develop credible predictive models for K OA . In this study, a polyparameter linear free energy relationship (pp-LFER) model for predicting K OA at 298.15 K and a novel model incorporating pp-LFERs with temperature (pp-LFER-T model) were developed from 795 log K OA values for 367 chemicals at different temperatures (263.15-323.15 K), and were evaluated with the OECD guidelines on QSAR model validation and applicability domain description. Statistical results show that both models are well-fitted, robust and have good predictive capabilities. Particularly, the pp-LFER model shows a strong predictive ability for polyfluoroalkyl substances and organosilicon compounds, and the pp-LFER-T model maintains a high predictive accuracy within a wide temperature range (263.15-323.15 K).

Environmental fate model for ultra-low-volume insecticide applications used for adult mosquito management

USGS Publications Warehouse

Schleier, Jerome J.; Peterson, Robert K.D.; Irvine, Kathryn M.; Marshall, Lucy M.; Weaver, David K.; Preftakes, Collin J.

2012-01-01

One of the more effective ways of managing high densities of adult mosquitoes that vector human and animal pathogens is ultra-low-volume (ULV) aerosol applications of insecticides. The U.S. Environmental Protection Agency uses models that are not validated for ULV insecticide applications and exposure assumptions to perform their human and ecological risk assessments. Currently, there is no validated model that can accurately predict deposition of insecticides applied using ULV technology for adult mosquito management. In addition, little is known about the deposition and drift of small droplets like those used under conditions encountered during ULV applications. The objective of this study was to perform field studies to measure environmental concentrations of insecticides and to develop a validated model to predict the deposition of ULV insecticides. The final regression model was selected by minimizing the Bayesian Information Criterion and its prediction performance was evaluated using k-fold cross validation. Density of the formulation and the density and CMD interaction coefficients were the largest in the model. The results showed that as density of the formulation decreases, deposition increases. The interaction of density and CMD showed that higher density formulations and larger droplets resulted in greater deposition. These results are supported by the aerosol physics literature. A k-fold cross validation demonstrated that the mean square error of the selected regression model is not biased, and the mean square error and mean square prediction error indicated good predictive ability.

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

PubMed Central

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M.

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover. PMID:27438600

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks.

PubMed

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.

Direct CFD Predictions of Low Frequency Sounds Generated by a Helicopter Main Rotor

DTIC Science & Technology

2010-05-01

modeling and grid constraints. NOTATION α Shaft tilt (corrected) or tip-path-plane angle BPF Blade passing frequency CT/σ Thrust coefficient to rotor...cyclic pitch angle, deg. LFSPL Low frequency sound metric (1st-6th BPF ), dB MFSPL Mid frequency sound metric (> 6th BPF ), dB OASPL Overall sound metric...Tunnel of the National Full- Scale Aerodynamic Complex (NFAC) at NASA Ames Research Center in 2008 (Fig. 2a), as a guide for prediction validation. The

Molecular electronegativity distance vector model for the prediction of bioconcentration factors in fish.

PubMed

Liu, Shu-Shen; Qin, Li-Tang; Liu, Hai-Ling; Yin, Da-Qiang

2008-02-01

Molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was used to describe the structures of 122 nonionic organic compounds (NOCs) and a quantitative relationship between the MEDV descriptors and the bioconcentration factors (BCF) of NOCs in fish was developed using the variable selection and modeling based on prediction (VSMP). It was found that some main structural factors influencing the BCFs of NOCs are the substructures expressed by four atomic types of nos. 2, 3, 5, and 13, i.e., atom groups -CH(2)- or =CH-, -CH< or =C<, -NH(2), and -Cl or -Br where the former two groups exist in the molecular skeleton of NOC and the latter three groups are related closely to the substituting groups on a benzene ring. The best 5-variable model, with the correlation coefficient (r(2)) of 0.9500 and the leave-one-out cross-validation correlation coefficient (q(2)) of 0.9428, was built by multiple linear regressions, which shows a good estimation ability and stability. A predictive power for the external samples was tested by the model from the training set of 80 NOCs and the predictive correlation coefficient (u(2)) for the 42 external samples in the test set was 0.9028.

Concurrent Validity of K-BIT Using the WISC-III as the Criterion.

ERIC Educational Resources Information Center

Seagle, Donna L.; Rust, James O.

The Kaufman Brief Intelligence Test (K-BIT) was used as a screening instrument to predict Wechsler Intelligence Scale for Children-Third Edition (WISC-III) scores of 94 students referred for psychoeducational evaluations. Although the correlation coefficient between the K-BIT IQ Composite and the WISC-III Full Scale IQ was 0.771 for the entire…

Comparison of classification methods for voxel-based prediction of acute ischemic stroke outcome following intra-arterial intervention

NASA Astrophysics Data System (ADS)

Winder, Anthony J.; Siemonsen, Susanne; Flottmann, Fabian; Fiehler, Jens; Forkert, Nils D.

2017-03-01

Voxel-based tissue outcome prediction in acute ischemic stroke patients is highly relevant for both clinical routine and research. Previous research has shown that features extracted from baseline multi-parametric MRI datasets have a high predictive value and can be used for the training of classifiers, which can generate tissue outcome predictions for both intravenous and conservative treatments. However, with the recent advent and popularization of intra-arterial thrombectomy treatment, novel research specifically addressing the utility of predictive classi- fiers for thrombectomy intervention is necessary for a holistic understanding of current stroke treatment options. The aim of this work was to develop three clinically viable tissue outcome prediction models using approximate nearest-neighbor, generalized linear model, and random decision forest approaches and to evaluate the accuracy of predicting tissue outcome after intra-arterial treatment. Therefore, the three machine learning models were trained, evaluated, and compared using datasets of 42 acute ischemic stroke patients treated with intra-arterial thrombectomy. Classifier training utilized eight voxel-based features extracted from baseline MRI datasets and five global features. Evaluation of classifier-based predictions was performed via comparison to the known tissue outcome, which was determined in follow-up imaging, using the Dice coefficient and leave-on-patient-out cross validation. The random decision forest prediction model led to the best tissue outcome predictions with a mean Dice coefficient of 0.37. The approximate nearest-neighbor and generalized linear model performed equally suboptimally with average Dice coefficients of 0.28 and 0.27 respectively, suggesting that both non-linearity and machine learning are desirable properties of a classifier well-suited to the intra-arterial tissue outcome prediction problem.

Performance evaluation of Maxwell and Cercignani-Lampis gas-wall interaction models in the modeling of thermally driven rarefied gas transport.

PubMed

Liang, Tengfei; Li, Qi; Ye, Wenjing

2013-07-01

A systematic study on the performance of two empirical gas-wall interaction models, the Maxwell model and the Cercignani-Lampis (CL) model, in the entire Knudsen range is conducted. The models are evaluated by examining the accuracy of key macroscopic quantities such as temperature, density, and pressure, in three benchmark thermal problems, namely the Fourier thermal problem, the Knudsen force problem, and the thermal transpiration problem. The reference solutions are obtained from a validated hybrid DSMC-MD algorithm developed in-house. It has been found that while both models predict temperature and density reasonably well in the Fourier thermal problem, the pressure profile obtained from Maxwell model exhibits a trend that opposes that from the reference solution. As a consequence, the Maxwell model is unable to predict the orientation change of the Knudsen force acting on a cold cylinder embedded in a hot cylindrical enclosure at a certain Knudsen number. In the simulation of the thermal transpiration coefficient, although all three models overestimate the coefficient, the coefficient obtained from CL model is the closest to the reference solution. The Maxwell model performs the worst. The cause of the overestimated coefficient is investigated and its link to the overly constrained correlation between the tangential momentum accommodation coefficient and the tangential energy accommodation coefficient inherent in the models is pointed out. Directions for further improvement of models are suggested.

The Crucial Role of Error Correlation for Uncertainty Modeling of CFD-Based Aerodynamics Increments

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Walker, Eric L.

2011-01-01

The Ares I ascent aerodynamics database for Design Cycle 3 (DAC-3) was built from wind-tunnel test results and CFD solutions. The wind tunnel results were used to build the baseline response surfaces for wind-tunnel Reynolds numbers at power-off conditions. The CFD solutions were used to build increments to account for Reynolds number effects. We calculate the validation errors for the primary CFD code results at wind tunnel Reynolds number power-off conditions and would like to be able to use those errors to predict the validation errors for the CFD increments. However, the validation errors are large compared to the increments. We suggest a way forward that is consistent with common practice in wind tunnel testing which is to assume that systematic errors in the measurement process and/or the environment will subtract out when increments are calculated, thus making increments more reliable with smaller uncertainty than absolute values of the aerodynamic coefficients. A similar practice has arisen for the use of CFD to generate aerodynamic database increments. The basis of this practice is the assumption of strong correlation of the systematic errors inherent in each of the results used to generate an increment. The assumption of strong correlation is the inferential link between the observed validation uncertainties at wind-tunnel Reynolds numbers and the uncertainties to be predicted for flight. In this paper, we suggest a way to estimate the correlation coefficient and demonstrate the approach using code-to-code differences that were obtained for quality control purposes during the Ares I CFD campaign. Finally, since we can expect the increments to be relatively small compared to the baseline response surface and to be typically of the order of the baseline uncertainty, we find that it is necessary to be able to show that the correlation coefficients are close to unity to avoid overinflating the overall database uncertainty with the addition of the increments.

What to Do With "Moderate" Reliability and Validity Coefficients?

PubMed

Post, Marcel W

2016-07-01

Clinimetric studies may use criteria for test-retest reliability and convergent validity such that correlation coefficients as low as .40 are supportive of reliability and validity. It can be argued that moderate (.40-.60) correlations should not be interpreted in this way and that reliability coefficients <.70 should be considered as indicative of unreliability. Convergent validity coefficients in the .40 to .60 or .40 to .70 range should be considered as indications of validity problems, or as inconclusive at best. Studies on reliability and convergent should be designed in such a way that it is realistic to expect high reliability and validity coefficients. Multitrait multimethod approaches are preferred to study construct (convergent-divergent) validity. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Quantitative structure-retention relationships of polycyclic aromatic hydrocarbons gas-chromatographic retention indices.

PubMed

Drosos, Juan Carlos; Viola-Rhenals, Maricela; Vivas-Reyes, Ricardo

2010-06-25

Polycyclic aromatic compounds (PAHs) are of concern in environmental chemistry and toxicology. In the present work, a QSRR study was performed for 209 previously reported PAHs using quantum mechanics and other sources descriptors estimated by different approaches. The B3LYP/6-31G* level of theory was used for geometrical optimization and quantum mechanics related variables. A good linear relationship between gas-chromatographic retention index and electronic or topologic descriptors was found by stepwise linear regression analysis. The molecular polarizability (alpha) and the second order molecular connectivity Kier and Hall index ((2)chi) showed evidence of significant correlation with retention index by means of important squared coefficient of determination, (R(2)), values (R(2)=0.950 and 0.962, respectively). A one variable QSRR model is presented for each descriptor and both models demonstrates a significant predictive capacity established using the leave-many-out LMO (excluding 25% of rows) cross validation method's q(2) cross-validation coefficients q(2)(CV-LMO25%), (obtained q(2)(CV-LMO25%) 0.947 and 0.960, respectively). Furthermore, the physicochemical interpretation of selected descriptors allowed detailed explanation of the source of the observed statistical correlation. The model analysis suggests that only one descriptor is sufficient to establish a consistent retention index-structure relationship. Moderate or non-significant improve was observed for quantitative results or statistical validation parameters when introducing more terms in predictive equation. The one parameter QSRR proposed model offers a consistent scheme to predict chromatographic properties of PAHs compounds. Copyright 2010 Elsevier B.V. All rights reserved.

Is there more valuable information in PWI datasets for a voxel-wise acute ischemic stroke tissue outcome prediction than what is represented by typical perfusion maps?

NASA Astrophysics Data System (ADS)

Forkert, Nils Daniel; Siemonsen, Susanne; Dalski, Michael; Verleger, Tobias; Kemmling, Andre; Fiehler, Jens

2014-03-01

The acute ischemic stroke is a leading cause for death and disability in the industry nations. In case of a present acute ischemic stroke, the prediction of the future tissue outcome is of high interest for the clinicians as it can be used to support therapy decision making. Within this context, it has already been shown that the voxel-wise multi-parametric tissue outcome prediction leads to more promising results compared to single channel perfusion map thresholding. Most previously published multi-parametric predictions employ information from perfusion maps derived from perfusion-weighted MRI together with other image sequences such as diffusion-weighted MRI. However, it remains unclear if the typically calculated perfusion maps used for this purpose really include all valuable information from the PWI dataset for an optimal tissue outcome prediction. To investigate this problem in more detail, two different methods to predict tissue outcome using a k-nearest-neighbor approach were developed in this work and evaluated based on 18 datasets of acute stroke patients with known tissue outcome. The first method integrates apparent diffusion coefficient and perfusion parameter (Tmax, MTT, CBV, CBF) information for the voxel-wise prediction, while the second method employs also apparent diffusion coefficient information but the complete perfusion information in terms of the voxel-wise residue functions instead of the perfusion parameter maps for the voxel-wise prediction. Overall, the comparison of the results of the two prediction methods for the 18 patients using a leave-one-out cross validation revealed no considerable differences. Quantitatively, the parameter-based prediction of tissue outcome led to a mean Dice coefficient of 0.474, while the prediction using the residue functions led to a mean Dice coefficient of 0.461. Thus, it may be concluded from the results of this study that the perfusion parameter maps typically derived from PWI datasets include all valuable perfusion information required for a voxel-based tissue outcome prediction, while the complete analysis of the residue functions does not add further benefits for the voxel-wise tissue outcome prediction and is also computationally more expensive.

Defining physicians' readiness to screen and manage intimate partner violence in Greek primary care settings.

PubMed

Papadakaki, Maria; Prokopiadou, Dimitra; Petridou, Eleni; Kogevinas, Manolis; Lionis, Christos

2012-06-01

The current article aims to translate the PREMIS (Physician Readiness to Manage Intimate Partner Violence) survey into the Greek language and test its validity and reliability in a sample of primary care physicians. The validation study was conducted in 2010 and involved all the general practitioners serving two adjacent prefectures of Greece (n = 80). Maximum-likelihood factor analysis (MLF) was used to extract key survey factors. The instrument was further assessed for the following psychometric properties: (a) scale reliability, (b) item-specific reliability, (c) test-retest reliability, (d) scale construct validity, and (e) internal predictive validity. The MLF analysis of 23 opinion items revealed a seven-factor solution (preparation, constraint, workplace issues, screening, self-efficacy, alcohol/drugs, victim understanding), which was statistically sound (p = .293). Most of the newly derived scales displayed satisfactory internal consistency (α ≥ .60), high item-specific reliability, strong construct, and internal predictive validity (F = 2.82; p = .004), and high repeatability when retested with 20 individuals (intraclass correlation coefficient [ICC] > .70). The tool was found appropriate to facilitate the identification of competence deficits and the evaluation of training initiatives.

Predicting surgical site infection after spine surgery: a validated model using a prospective surgical registry.

PubMed

Lee, Michael J; Cizik, Amy M; Hamilton, Deven; Chapman, Jens R

2014-09-01

The impact of surgical site infection (SSI) is substantial. Although previous study has determined relative risk and odds ratio (OR) values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of SSI, rather than relative risk or OR values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. The purpose of this study was to create and validate a predictive model for the risk of SSI after spine surgery. This study performs a multivariate analysis of SSI after spine surgery using a large prospective surgical registry. Using the results of this analysis, this study will then create and validate a predictive model for SSI after spine surgery. The patient sample is from a high-quality surgical registry from our two institutions with prospectively collected, detailed demographic, comorbidity, and complication data. An SSI that required return to the operating room for surgical debridement. Using a prospectively collected surgical registry of more than 1,532 patients with extensive demographic, comorbidity, surgical, and complication details recorded for 2 years after the surgery, we identified several risk factors for SSI after multivariate analysis. Using the beta coefficients from those regression analyses, we created a model to predict the occurrence of SSI after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created a predictive model based on our beta coefficients from our multivariate analysis. The final predictive model for SSI had a receiver-operator curve characteristic of 0.72, considered to be a fair measure. The final model has been uploaded for use on SpineSage.com. We present a validated model for predicting SSI after spine surgery. The value in this model is that it gives the user an absolute percent likelihood of SSI after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Patients are far more likely to understand an absolute percentage, rather than relative risk and confidence interval values. A model such as this is of paramount importance in counseling patients and enhancing the safety of spine surgery. In addition, a tool such as this can be of great use particularly as health care trends toward pay for performance, quality metrics (such as SSI), and risk adjustment. To facilitate the use of this model, we have created a Web site (SpineSage.com) where users can enter patient data to determine likelihood for SSI. Copyright © 2014 Elsevier Inc. All rights reserved.

The reliability and validity of ultrasound to quantify muscles in older adults: a systematic review

PubMed Central

Scafoglieri, Aldo; Jager‐Wittenaar, Harriët; Hobbelen, Johannes S.M.; van der Schans, Cees P.

2017-01-01

Abstract This review evaluates the reliability and validity of ultrasound to quantify muscles in older adults. The databases PubMed, Cochrane, and Cumulative Index to Nursing and Allied Health Literature were systematically searched for studies. In 17 studies, the reliability (n = 13) and validity (n = 8) of ultrasound to quantify muscles in community‐dwelling older adults (≥60 years) or a clinical population were evaluated. Four out of 13 reliability studies investigated both intra‐rater and inter‐rater reliability. Intraclass correlation coefficient (ICC) scores for reliability ranged from −0.26 to 1.00. The highest ICC scores were found for the vastus lateralis, rectus femoris, upper arm anterior, and the trunk (ICC = 0.72 to 1.000). All included validity studies found ICC scores ranging from 0.92 to 0.999. Two studies describing the validity of ultrasound to predict lean body mass showed good validity as compared with dual‐energy X‐ray absorptiometry (r 2 = 0.92 to 0.96). This systematic review shows that ultrasound is a reliable and valid tool for the assessment of muscle size in older adults. More high‐quality research is required to confirm these findings in both clinical and healthy populations. Furthermore, ultrasound assessment of small muscles needs further evaluation. Ultrasound to predict lean body mass is feasible; however, future research is required to validate prediction equations in older adults with varying function and health. PMID:28703496

Evaluation of Short-Term Cepstral Based Features for Detection of Parkinson’s Disease Severity Levels through Speech signals

NASA Astrophysics Data System (ADS)

Oung, Qi Wei; Nisha Basah, Shafriza; Muthusamy, Hariharan; Vijean, Vikneswaran; Lee, Hoileong

2018-03-01

Parkinson’s disease (PD) is one type of progressive neurodegenerative disease known as motor system syndrome, which is due to the death of dopamine-generating cells, a region of the human midbrain. PD normally affects people over 60 years of age, which at present has influenced a huge part of worldwide population. Lately, many researches have shown interest into the connection between PD and speech disorders. Researches have revealed that speech signals may be a suitable biomarker for distinguishing between people with Parkinson’s (PWP) from healthy subjects. Therefore, early diagnosis of PD through the speech signals can be considered for this aim. In this research, the speech data are acquired based on speech behaviour as the biomarker for differentiating PD severity levels (mild and moderate) from healthy subjects. Feature extraction algorithms applied are Mel Frequency Cepstral Coefficients (MFCC), Linear Predictive Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC), and Weighted Linear Prediction Cepstral Coefficients (WLPCC). For classification, two types of classifiers are used: k-Nearest Neighbour (KNN) and Probabilistic Neural Network (PNN). The experimental results demonstrated that PNN classifier and KNN classifier achieve the best average classification performance of 92.63% and 88.56% respectively through 10-fold cross-validation measures. Favourably, the suggested techniques have the possibilities of becoming a new choice of promising tools for the PD detection with tremendous performance.

Development of the Psychiatric Nurse Job Stressor Scale (PNJSS).

PubMed

Yada, Hironori; Abe, Hiroshi; Funakoshi, Yayoi; Omori, Hisamitsu; Matsuo, Hisae; Ishida, Yasushi; Katoh, Takahiko

2011-10-01

The aim of the present study was to develop a tool, the Psychiatric Nurse Job Stressor Scale (PNJSS), for measuring the stress of psychiatric nurses, and to evaluate the reliability and validity of the PNJSS. A total of 302 psychiatric nurses completed all the questions in an early version of the PNJSS, which was composed of 63 items and is based on past literature of psychiatric nurses' stress. A total of 22 items from four factors, 'Psychiatric Nursing Ability', 'Attitude of Patients', 'Attitude Toward Nursing' and 'Communication', were extracted in exploratory factor analysis. With regard to scale reliability, the item-scale correlation coefficient was r = 0.265-0.570 (P < 0.01), the Cronbach alpha coefficient was 0.675-0.869, and the test-retest correlation coefficient was r = 0.439-0.771 (P < 0.01). With regard to scale validity, the convergent validity of the 'job stressor' scale was r = 0.172-0.420 (P < 0.01), and the predictive validity of the 'job reaction' scale was r = 0.201-0.453 (P < 0.01). The compatibility of the factor model to the data was 1.750 (χ(2) /d.f., 343.189/196, P < 0.01), the goodness of fit index was 0.910, the adjusted goodness of fit index was 0.883, the comparative fit index was 0.924, and the root mean square error of approximation was 0.050. The PNJSS has sufficient reliability and validity as a four-factor structure containing 22 items, and is valid as a tool for evaluating psychiatric nurse job stressors. © 2011 The Authors. Psychiatry and Clinical Neurosciences © 2011 Japanese Society of Psychiatry and Neurology.

Stokes-Einstein relation in liquid iron-nickel alloy up to 300 GPa

NASA Astrophysics Data System (ADS)

Cao, Q.-L.; Wang, P.-P.

2017-05-01

Molecular dynamic simulations were applied to investigate the Stokes-Einstein relation (SER) and the Rosenfeld entropy scaling law (ESL) in liquid Fe0.9Ni0.1 over a sufficiently broad range of temperatures (0.70 < T/Tm < 1.85 Tm is melting temperature) and pressures (from 50 GPa to 300 GPa). Our results suggest that the SER and ESL hold well in the normal liquid region and break down in the supercooled region under high-pressure conditions, and the deviation becomes larger with decreasing temperature. In other words, the SER can be used to calculate the viscosity of liquid Earth's outer core from the self-diffusion coefficients of iron/nickel and the ESL can be used to predict the viscosity and diffusion coefficients of liquid Earth's outer core form its structural properties. In addition, the pressure dependence of effective diameters cannot be ignored in the course of using the SER. Moreover, ESL provides a useful, structure-based probe for the validity of SER, while the ratio of the self-diffusion coefficients of the components cannot be used as a probe for the validity of SER.

Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

PubMed

Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

2007-09-01

Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

PubMed

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient. The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84). Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008). The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

Prediction Model for Predicting Powdery Mildew using ANN for Medicinal Plant— Picrorhiza kurrooa

NASA Astrophysics Data System (ADS)

Shivling, V. D.; Ghanshyam, C.; Kumar, Rakesh; Kumar, Sanjay; Sharma, Radhika; Kumar, Dinesh; Sharma, Atul; Sharma, Sudhir Kumar

2017-02-01

Plant disease fore casting system is an important system as it can be used for prediction of disease, further it can be used as an alert system to warn the farmers in advance so as to protect their crop from being getting infected. Fore casting system will predict the risk of infection for crop by using the environmental factors that favor in germination of disease. In this study an artificial neural network based system for predicting the risk of powdery mildew in Picrorhiza kurrooa was developed. For development, Levenberg-Marquardt backpropagation algorithm was used having a single hidden layer of ten nodes. Temperature and duration of wetness are the major environmental factors that favor infection. Experimental data was used as a training set and some percentage of data was used for testing and validation. The performance of the system was measured in the form of the coefficient of correlation (R), coefficient of determination (R2), mean square error and root mean square error. For simulating the network an inter face was developed. Using this interface the network was simulated by putting temperature and wetness duration so as to predict the level of risk at that particular value of the input data.

Molecular surface area based predictive models for the adsorption and diffusion of disperse dyes in polylactic acid matrix.

PubMed

Xu, Suxin; Chen, Jiangang; Wang, Bijia; Yang, Yiqi

2015-11-15

Two predictive models were presented for the adsorption affinities and diffusion coefficients of disperse dyes in polylactic acid matrix. Quantitative structure-sorption behavior relationship would not only provide insights into sorption process, but also enable rational engineering for desired properties. The thermodynamic and kinetic parameters for three disperse dyes were measured. The predictive model for adsorption affinity was based on two linear relationships derived by interpreting the experimental measurements with molecular structural parameters and compensation effect: ΔH° vs. dye size and ΔS° vs. ΔH°. Similarly, the predictive model for diffusion coefficient was based on two derived linear relationships: activation energy of diffusion vs. dye size and logarithm of pre-exponential factor vs. activation energy of diffusion. The only required parameters for both models are temperature and solvent accessible surface area of the dye molecule. These two predictive models were validated by testing the adsorption and diffusion properties of new disperse dyes. The models offer fairly good predictive ability. The linkage between structural parameter of disperse dyes and sorption behaviors might be generalized and extended to other similar polymer-penetrant systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of a Skin Burn Predictive Model adapted to Laser Irradiation

NASA Astrophysics Data System (ADS)

Sonneck-Museux, N.; Scheer, E.; Perez, L.; Agay, D.; Autrique, L.

2016-12-01

Laser technology is increasingly used, and it is crucial for both safety and medical reasons that the impact of laser irradiation on human skin can be accurately predicted. This study is mainly focused on laser-skin interactions and potential lesions (burns). A mathematical model dedicated to heat transfers in skin exposed to infrared laser radiations has been developed. The model is validated by studying heat transfers in human skin and simultaneously performing experimentations an animal model (pig). For all experimental tests, pig's skin surface temperature is recorded. Three laser wavelengths have been tested: 808 nm, 1940 nm and 10 600 nm. The first is a diode laser producing radiation absorbed deep within the skin. The second wavelength has a more superficial effect. For the third wavelength, skin is an opaque material. The validity of the developed models is verified by comparison with experimental results (in vivo tests) and the results of previous studies reported in the literature. The comparison shows that the models accurately predict the burn degree caused by laser radiation over a wide range of conditions. The results show that the important parameter for burn prediction is the extinction coefficient. For the 1940 nm wavelength especially, significant differences between modeling results and literature have been observed, mainly due to this coefficient's value. This new model can be used as a predictive tool in order to estimate the amount of injury induced by several types (couple power-time) of laser aggressions on the arm, the face and on the palm of the hand.

Design of novel quinazolinone derivatives as inhibitors for 5HT7 receptor.

PubMed

Chitta, Aparna; Jatavath, Mohan Babu; Fatima, Sabiha; Manga, Vijjulatha

2012-02-01

To study the pharmacophore properties of quinazolinone derivatives as 5HT(7) inhibitors, 3D QSAR methodologies, namely Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) were applied, partial least square (PLS) analysis was performed and QSAR models were generated. The derived model showed good statistical reliability in terms of predicting the 5HT(7) inhibitory activity of the quinazolione derivative, based on molecular property fields like steric, electrostatic, hydrophobic, hydrogen bond donor and hydrogen bond acceptor fields. This is evident from statistical parameters like q(2) (cross validated correlation coefficient) of 0.642, 0.602 and r(2) (conventional correlation coefficient) of 0.937, 0.908 for CoMFA and CoMSIA respectively. The predictive ability of the models to determine 5HT(7) antagonistic activity is validated using a test set of 26 molecules that were not included in the training set and the predictive r(2) obtained for the test set was 0.512 & 0.541. Further, the results of the derived model are illustrated by means of contour maps, which give an insight into the interaction of the drug with the receptor. The molecular fields so obtained served as the basis for the design of twenty new ligands. In addition, ADME (Adsorption, Distribution, Metabolism and Elimination) have been calculated in order to predict the relevant pharmaceutical properties, and the results are in conformity with required drug like properties.

The construct and criterion validity of the multi-source feedback process to assess physician performance: a meta-analysis

PubMed Central

Al Ansari, Ahmed; Donnon, Tyrone; Al Khalifa, Khalid; Darwish, Abdulla; Violato, Claudio

2014-01-01

Background The purpose of this study was to conduct a meta-analysis on the construct and criterion validity of multi-source feedback (MSF) to assess physicians and surgeons in practice. Methods In this study, we followed the guidelines for the reporting of observational studies included in a meta-analysis. In addition to PubMed and MEDLINE databases, the CINAHL, EMBASE, and PsycINFO databases were searched from January 1975 to November 2012. All articles listed in the references of the MSF studies were reviewed to ensure that all relevant publications were identified. All 35 articles were independently coded by two authors (AA, TD), and any discrepancies (eg, effect size calculations) were reviewed by the other authors (KA, AD, CV). Results Physician/surgeon performance measures from 35 studies were identified. A random-effects model of weighted mean effect size differences (d) resulted in: construct validity coefficients for the MSF system on physician/surgeon performance across different levels in practice ranged from d=0.14 (95% confidence interval [CI] 0.40–0.69) to d=1.78 (95% CI 1.20–2.30); construct validity coefficients for the MSF on physician/surgeon performance on two different occasions ranged from d=0.23 (95% CI 0.13–0.33) to d=0.90 (95% CI 0.74–1.10); concurrent validity coefficients for the MSF based on differences in assessor group ratings ranged from d=0.50 (95% CI 0.47–0.52) to d=0.57 (95% CI 0.55–0.60); and predictive validity coefficients for the MSF on physician/surgeon performance across different standardized measures ranged from d=1.28 (95% CI 1.16–1.41) to d=1.43 (95% CI 0.87–2.00). Conclusion The construct and criterion validity of the MSF system is supported by small to large effect size differences based on the MSF process and physician/surgeon performance across different clinical and nonclinical domain measures. PMID:24600300

Optimal descriptor as a translator of eclectic data into prediction of cytotoxicity for metal oxide nanoparticles under different conditions.

PubMed

Toropova, Alla P; Toropov, Andrey A; Rallo, Robert; Leszczynska, Danuta; Leszczynski, Jerzy

2015-02-01

The Monte Carlo technique has been used to build up quantitative structure-activity relationships (QSARs) for prediction of dark cytotoxicity and photo-induced cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (minus logarithm of lethal concentration for 50% bacteria pLC50, LC50 in mol/L). The representation of nanoparticles include (i) in the case of the dark cytotoxicity a simplified molecular input-line entry system (SMILES), and (ii) in the case of photo-induced cytotoxicity a SMILES plus symbol '^'. The predictability of the approach is checked up with six random distributions of available data into the visible training and calibration sets, and invisible validation set. The statistical characteristics of these models are correlation coefficient 0.90-0.94 (training set) and 0.73-0.98 (validation set). Copyright © 2014 Elsevier Inc. All rights reserved.

[Validity of expired carbon monoxide and urine cotinine using dipstick method to assess smoking status].

PubMed

Park, Su San; Lee, Ju Yul; Cho, Sung-Il

2007-07-01

We investigated the validity of the dipstick method (Mossman Associates Inc. USA) and the expired CO method to distinguish between smokers and nonsmokers. We also elucidated the related factors of the two methods. This study included 244 smokers and 50 ex-smokers, recruited from smoking cessation clinics at 4 local public health centers, who had quit for over 4 weeks. We calculated the sensitivity, specificity and Kappa coefficient of each method for validity. We obtained ROC curve, predictive value and agreement to determine the cutoff of expired air CO method. Finally, we elucidated the related factors and compared their effect powers using the standardized regression coefficient. The dipstick method showed a sensitivity of 92.6%, specificity of 96.0% and Kappa coefficient of 0.79. The best cutoff value to distinguish smokers was 5-6 ppm. At 5 ppm, the expired CO method showed a sensitivity of 94.3%, specificity of 82.0% and Kappa coefficient of 0.73. And at 6 ppm, sensitivity, specificity and Kappa coefficient were 88.5%, 86.0% and 0.64, respectively. Therefore, the dipstick method had higher sensitivity and specificity than the expired CO method. The dipstick and expired CO methods were significantly increased with increasing smoking amount. With longer time since the last smoking, expired CO showed a rapid decrease after 4 hours, whereas the dipstick method showed relatively stable levels for more than 4 hours. The dipstick and expired CO methods were both good indicators for assessing smoking status. However, the former showed higher sensitivity and specificity and stable levels over longer hours after smoking, compared to the expired CO method.

Validity and reliability of a self-report instrument to assess social support and physical environmental correlates of physical activity in adolescents

PubMed Central

2012-01-01

Background The purpose of this study was to examine the internal consistency, test-retest reliability, construct validity and predictive validity of a new German self-report instrument to assess the influence of social support and the physical environment on physical activity in adolescents. Methods Based on theoretical consideration, the short scales on social support and physical environment were developed and cross-validated in two independent study samples of 9 to 17 year-old girls and boys. The longitudinal sample of Study I (n = 196) was recruited from a German comprehensive school, and subjects in this study completed the questionnaire twice with a between-test interval of seven days. Cronbach’s alphas were computed to determine the internal consistency of the factors. Test-retest reliability of the latent factors was assessed using intra-class coefficients. Factorial validity of the scales was assessed using principle components analysis. Construct validity was determined using a cross-validation technique by performing confirmatory factor analysis with the independent nationwide cross-sectional sample of Study II (n = 430). Correlations between factors and three measures of physical activity (objectively measured moderate-to-vigorous physical activity (MVPA), self-reported habitual MVPA and self-reported recent MVPA) were calculated to determine the predictive validity of the instrument. Results Construct validity of the social support scale (two factors: parental support and peer support) and the physical environment scale (four factors: convenience, public recreation facilities, safety and private sport providers) was shown. Both scales had moderate test-retest reliability. The factors of the social support scale also had good internal consistency and predictive validity. Internal consistency and predictive validity of the physical environment scale were low to acceptable. Conclusions The results of this study indicate moderate to good reliability and construct validity of the social support scale and physical environment scale. Predictive validity was only confirmed for the social support scale but not for the physical environment scale. Hence, it remains unclear if a person’s physical environment has a direct or an indirect effect on physical activity behavior or a moderation function. PMID:22928865

Validity and reliability of a self-report instrument to assess social support and physical environmental correlates of physical activity in adolescents.

PubMed

Reimers, Anne K; Jekauc, Darko; Mess, Filip; Mewes, Nadine; Woll, Alexander

2012-08-29

The purpose of this study was to examine the internal consistency, test-retest reliability, construct validity and predictive validity of a new German self-report instrument to assess the influence of social support and the physical environment on physical activity in adolescents. Based on theoretical consideration, the short scales on social support and physical environment were developed and cross-validated in two independent study samples of 9 to 17 year-old girls and boys. The longitudinal sample of Study I (n = 196) was recruited from a German comprehensive school, and subjects in this study completed the questionnaire twice with a between-test interval of seven days. Cronbach's alphas were computed to determine the internal consistency of the factors. Test-retest reliability of the latent factors was assessed using intra-class coefficients. Factorial validity of the scales was assessed using principle components analysis. Construct validity was determined using a cross-validation technique by performing confirmatory factor analysis with the independent nationwide cross-sectional sample of Study II (n = 430). Correlations between factors and three measures of physical activity (objectively measured moderate-to-vigorous physical activity (MVPA), self-reported habitual MVPA and self-reported recent MVPA) were calculated to determine the predictive validity of the instrument. Construct validity of the social support scale (two factors: parental support and peer support) and the physical environment scale (four factors: convenience, public recreation facilities, safety and private sport providers) was shown. Both scales had moderate test-retest reliability. The factors of the social support scale also had good internal consistency and predictive validity. Internal consistency and predictive validity of the physical environment scale were low to acceptable. The results of this study indicate moderate to good reliability and construct validity of the social support scale and physical environment scale. Predictive validity was only confirmed for the social support scale but not for the physical environment scale. Hence, it remains unclear if a person's physical environment has a direct or an indirect effect on physical activity behavior or a moderation function.

Development of TLSER model and QSAR model for predicting partition coefficients of hydrophobic organic chemicals between low density polyethylene film and water.

PubMed

Liu, Huihui; Wei, Mengbi; Yang, Xianhai; Yin, Cen; He, Xiao

2017-01-01

Partition coefficients are vital parameters for measuring accurately the chemicals concentrations by passive sampling devices. Given the wide use of low density polyethylene (LDPE) film in passive sampling, we developed a theoretical linear solvation energy relationship (TLSER) model and a quantitative structure-activity relationship (QSAR) model for the prediction of the partition coefficient of chemicals between LDPE and water (K pew ). For chemicals with the octanol-water partition coefficient (log K ow ) <8, a TLSER model with V x (McGowan volume) and qA - (the most negative charge on O, N, S, X atoms) as descriptors was developed, but the model had relatively low determination coefficient (R 2 ) and cross-validated coefficient (Q 2 ). In order to further explore the theoretical mechanisms involved in the partition process, a QSAR model with four descriptors (MLOGP (Moriguchi octanol-water partition coeff.), P_VSA_s_3 (P_VSA-like on I-state, bin 3), Hy (hydrophilic factor) and NssO (number of atoms of type ssO)) was established, and statistical analysis indicated that the model had satisfactory goodness-of-fit, robustness and predictive ability. For chemicals with log K OW >8, a TLSER model with V x and a QSAR model with MLOGP as descriptor were developed. This is the first paper to explore the models for highly hydrophobic chemicals. The applicability domain of the models, characterized by the Euclidean distance-based method and Williams plot, covered a large number of structurally diverse chemicals, which included nearly all the common hydrophobic organic compounds. Additionally, through mechanism interpretation, we explored the structural features those governing the partition behavior of chemicals between LDPE and water. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction of octanol-air partition coefficients for polychlorinated biphenyls (PCBs) using 3D-QSAR models.

PubMed

Chen, Ying; Cai, Xiaoyu; Jiang, Long; Li, Yu

2016-02-01

Based on the experimental data of octanol-air partition coefficients (KOA) for 19 polychlorinated biphenyl (PCB) congeners, two types of QSAR methods, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), are used to establish 3D-QSAR models using the structural parameters as independent variables and using logKOA values as the dependent variable with the Sybyl software to predict the KOA values of the remaining 190 PCB congeners. The whole data set (19 compounds) was divided into a training set (15 compounds) for model generation and a test set (4 compounds) for model validation. As a result, the cross-validation correlation coefficient (q(2)) obtained by the CoMFA and CoMSIA models (shuffled 12 times) was in the range of 0.825-0.969 (>0.5), the correlation coefficient (r(2)) obtained was in the range of 0.957-1.000 (>0.9), and the SEP (standard error of prediction) of test set was within the range of 0.070-0.617, indicating that the models were robust and predictive. Randomly selected from a set of models, CoMFA analysis revealed that the corresponding percentages of the variance explained by steric and electrostatic fields were 23.9% and 76.1%, respectively, while CoMSIA analysis by steric, electrostatic and hydrophobic fields were 0.6%, 92.6%, and 6.8%, respectively. The electrostatic field was determined as a primary factor governing the logKOA. The correlation analysis of the relationship between the number of Cl atoms and the average logKOA values of PCBs indicated that logKOA values gradually increased as the number of Cl atoms increased. Simultaneously, related studies on PCB detection in the Arctic and Antarctic areas revealed that higher logKOA values indicate a stronger PCB migration ability. From CoMFA and CoMSIA contour maps, logKOA decreased when substituents possessed electropositive groups at the 2-, 3-, 3'-, 5- and 6- positions, which could reduce the PCB migration ability. These results are expected to be beneficial in predicting logKOA values of PCB homologues and derivatives and in providing a theoretical foundation for further elucidation of the global migration behaviour of PCBs. Copyright © 2015 Elsevier Inc. All rights reserved.

Casemix classification payment for sub-acute and non-acute inpatient care, Thailand.

PubMed

Khiaocharoen, Orathai; Pannarunothai, Supasit; Zungsontiporn, Chairoj; Riewpaiboon, Wachara

2010-07-01

There is a need to develop other casemix classifications, apart from DRG for sub-acute and non-acute inpatient care payment mechanism in Thailand. To develop a casemix classification for sub-acute and non-acute inpatient service. The study began with developing a classification system, analyzing cost, assigning payment weights, and ended with testing the validity of this new casemix system. Coefficient of variation, reduction in variance, linear regression, and split-half cross-validation were employed. The casemix for sub-acute and non-acute inpatient services contained 98 groups. Two percent of them had a coefficient of variation of the cost of higher than 1.5. The reduction in variance of cost after the classification was 32%. Two classification variables (physical function and the rehabilitation impairment categories) were key determinants of the cost (adjusted R2 = 0.749, p = .001). Validity results of split-half cross-validation of sub-acute and non-acute inpatient service were high. The present study indicated that the casemix for sub-acute and non-acute inpatient services closely predicted the hospital resource use and should be further developed for payment of the inpatients sub-acute and non-acute phase.

Establishment of a Physical Model for Solute Diffusion in Hydrogel: Understanding the Diffusion of Proteins in Poly(sulfobetaine methacrylate) Hydrogel.

PubMed

Zhou, Yuhang; Li, Junjie; Zhang, Ying; Dong, Dianyu; Zhang, Ershuai; Ji, Feng; Qin, Zhihui; Yang, Jun; Yao, Fanglian

2017-02-02

Prediction of the diffusion coefficient of solute, especially bioactive molecules, in hydrogel is significant in the biomedical field. Considering the randomness of solute movement in a hydrogel network, a physical diffusion RMP-1 model based on obstruction theory was established in this study. The physical properties of the solute and the polymer chain and their interactions were introduced into this model. Furthermore, models RMP-2 and RMP-3 were established to understand and predict the diffusion behaviors of proteins in hydrogel. In addition, zwitterionic poly(sulfobetaine methacrylate) (PSBMA) hydrogels with wide range and fine adjustable mesh sizes were prepared and used as efficient experimental platforms for model validation. The Flory characteristic ratios, Flory-Huggins parameter, mesh size, and polymer chain radii of PSBMA hydrogels were determined. The diffusion coefficients of the proteins (bovine serum albumin, immunoglobulin G, and lysozyme) in PSBMA hydrogels were studied by the fluorescence recovery after photobleaching technique. The measured diffusion coefficients were compared with the predictions of obstruction models, and it was found that our model presented an excellent predictive ability. Furthermore, the assessment of our model revealed that protein diffusion in PSBMA hydrogel would be affected by the physical properties of the protein and the PSBMA network. It was also confirmed that the diffusion behaviors of protein in zwitterionic hydrogels can be adjusted by changing the cross-linking density of the hydrogel and the ionic strength of the swelling medium. Our model is expected to possess accurate predictive ability for the diffusion coefficient of solute in hydrogel, which will be widely used in the biomedical field.

Predicting the Kinetics of Ice Recrystallization in Aqueous Sugar Solutions

PubMed Central

2018-01-01

The quality of stored frozen products such as foods and biomaterials generally degrades in time due to the growth of large ice crystals by recrystallization. While there is ample experimental evidence that recrystallization within such products (or model systems thereof) is often dominated by diffusion-limited Ostwald ripening, the application of Ostwald-ripening theories to predict measured recrystallization rates has only met with limited success. For a model system of polycrystalline ice within an aqueous solution of sugars, we here show recrystallization rates can be predicted on the basis of Ostwald ripening theory, provided (1) the theory accounts for the fact the solution can be nonideal, nondilute and of different density than the crystals, (2) the effect of ice-phase volume fraction on the diffusional flux of water between crystals is accurately described, and (3) all relevant material properties (involving binary Fick diffusion coefficients, the thermodynamic factor of the solution, and the surface energy of ice) are carefully estimated. To enable calculation of material properties, we derive an alternative formulation of Ostwald ripening in terms of the Maxwell–Stefan instead of the Fick approach to diffusion. First, this leads to a cancellation of the thermodynamic factor (a measure for the nonideality of a solution), which is a notoriously difficult property to obtain. Second, we show that Maxwell–Stefan diffusion coefficients can to a reasonable approximation be related to self-diffusion coefficients, which are relatively easy to measure or predict in comparison to Fick diffusion coefficients. Our approach is validated for a binary system of water and sucrose, for which we show predicted recrystallization rates of ice compare well to experimental results, with relative deviations of at most a factor of 2. PMID:29651228

Predicting the Kinetics of Ice Recrystallization in Aqueous Sugar Solutions.

PubMed

van Westen, Thijs; Groot, Robert D

2018-04-04

The quality of stored frozen products such as foods and biomaterials generally degrades in time due to the growth of large ice crystals by recrystallization. While there is ample experimental evidence that recrystallization within such products (or model systems thereof) is often dominated by diffusion-limited Ostwald ripening, the application of Ostwald-ripening theories to predict measured recrystallization rates has only met with limited success. For a model system of polycrystalline ice within an aqueous solution of sugars, we here show recrystallization rates can be predicted on the basis of Ostwald ripening theory, provided (1) the theory accounts for the fact the solution can be nonideal, nondilute and of different density than the crystals, (2) the effect of ice-phase volume fraction on the diffusional flux of water between crystals is accurately described, and (3) all relevant material properties (involving binary Fick diffusion coefficients, the thermodynamic factor of the solution, and the surface energy of ice) are carefully estimated. To enable calculation of material properties, we derive an alternative formulation of Ostwald ripening in terms of the Maxwell-Stefan instead of the Fick approach to diffusion. First, this leads to a cancellation of the thermodynamic factor (a measure for the nonideality of a solution), which is a notoriously difficult property to obtain. Second, we show that Maxwell-Stefan diffusion coefficients can to a reasonable approximation be related to self-diffusion coefficients, which are relatively easy to measure or predict in comparison to Fick diffusion coefficients. Our approach is validated for a binary system of water and sucrose, for which we show predicted recrystallization rates of ice compare well to experimental results, with relative deviations of at most a factor of 2.

Development and evaluation of predictive model for bovine serum albumin-water partition coefficients of neutral organic chemicals.

PubMed

Ma, Guangcai; Yuan, Quan; Yu, Haiying; Lin, Hongjun; Chen, Jianrong; Hong, Huachang

2017-04-01

The binding of organic chemicals to serum albumin can significantly reduce their unbound concentration in blood and affect their biological reactions. In this study, we developed a new QSAR model for bovine serum albumin (BSA) - water partition coefficients (K BSA/W ) of neutral organic chemicals with large structural variance, logK BSA/W values covering 3.5 orders of magnitude (1.19-4.76). All chemical geometries were optimized by semi-empirical PM6 algorithm. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates the regression model derived from logK ow , the most positive net atomic charges on an atom, Connolly solvent excluded volume, polarizability, and Abraham acidity could explain the partitioning mechanism of organic chemicals between BSA and water. The simulated external validation and cross validation verifies the developed model has good statistical robustness and predictive ability, thus can be used to estimate the logK BSA/W values for chemicals in application domain, accordingly to provide basic data for the toxicity assessment of the chemicals. Copyright © 2016 Elsevier Inc. All rights reserved.

Development and validation of college students' tuberculosis knowledge, attitudes and practices questionnaire (CS-TBKAPQ).

PubMed

Jiang, Hualin; Zhang, Shaoru; Ding, Yi; Li, Yuelu; Zhang, Tianhua; Liu, Weiping; Fan, Yahui; Li, Yan; Zhang, Rongqiang; Ma, Xuexue

2017-12-12

China faces many challenges in controlling tuberculosis (TB). One significant challenge is the control of college students' TB. In particular, cross-sectional studies of college students' knowledge, attitudes and practices (KAP) in regard to TB have attracted substantial attention. However, few measurement tools have been developed to aid processes related to expert consultation, pre-testing, reliability and validity testing. Our study developed the College Students' TB Knowledge Attitudes and Practices Questionnaire (CS-TBKAPQ) following the scale development steps. The construction of the CS-TBKAPQ was based on the Theory of Knowledge, Attitude, Belief, and Practice (KABP or KAP). The item pool was compiled from literature reviews and individual interviews. The reliability validation was assessed by calculating Cronbach's α coefficient, the split-half reliability coefficient, and the test-retest reliability coefficient. Construct validity was assessed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The diagnostic accuracy was evaluated using the World Health Organization Advocacy, Communication and Social Mobilization KAP Survey Questionnaire (WHO-TBKAPQ) as the reference standard. A total of 31 questionnaire items were proposed. Cronbach's α coefficient, the split-half reliability coefficient and the test-retest reliability coefficient were 0.86, 0.78 and 0.91. Four factors that explained 62.52% of the total variance were also identified in EFA and confirmed in CFA. The CFA model fit indices were x 2 /df = 1.82 (p < 0.001), GFI = 0.925, AGFI = 0.900, RMR = 0.068, and RMSEA = 0.049. The CS-TBKAPQ was significantly correlated with the WHO-TBKAPQ and the Chinese Public TB KAP Questionnaire (CDC-TBKAPQ) developed by the Chinese Center for Disease Control and Prevention (r = 0.59, 0.60, p < 0.001). The receiver operating characteristics curve (ROC) analysis suggested a cut-off point of 47.5, with which the CS-TBKAPQ showed a sensitivity of 73.63% and a specificity of 80.51% in identifying students with low-level KAP. The positive and negative predictive values were 83.23% and 69.91%. The findings of this study demonstrate that the CS-TBKAPQ is a reliable and valid tool for measuring the KAP towards TB in college students.

A New Lebanese Medication Adherence Scale: Validation in Lebanese Hypertensive Adults

PubMed Central

Wakim, N.; Issa, C.; Kassem, B.; Abou Jaoude, L.; Saleh, N.

2018-01-01

Background A new Lebanese scale measuring medication adherence considered socioeconomic and cultural factors not taken into account by the eight-item Morisky Medication Adherence Scale (MMAS-8). Objectives were to validate the new adherence scale and its prediction of hypertension control, compared to MMAS-8, and to assess adherence rates and factors. Methodology A cross-sectional study, including 405 patients, was performed in outpatient cardiology clinics of three hospitals in Beirut. Blood pressure was measured, a questionnaire filled, and sodium intake estimated by a urine test. Logistic regression defined predictors of hypertension control and adherence. Results 54.9% had controlled hypertension. 82.4% were adherent by the new scale, which showed good internal consistency, adequate questions (KMO coefficient = 0.743), and four factors. It predicted hypertension control (OR = 1.217; p value = 0.003), unlike MMAS-8, but the scores were correlated (ICC average measure = 0.651; p value < 0.001). Stress and smoking predicted nonadherence. Conclusion This study elaborated a validated, practical, and useful tool measuring adherence to medications in Lebanese hypertensive patients. PMID:29887993

Single-layer model to predict the source/sink behavior of diffusion-controlled building materials.

PubMed

Kumar, Deept; Little, John C

2003-09-01

Building materials may act as both sources of and sinks forvolatile organic compounds (VOCs) in indoor air. A strategy to characterize the rate of absorption and desorption of VOCs by diffusion-controlled building materials is validated. A previously developed model that predicts mass transfer between a flat slab of material and the well-mixed air within a chamber or room is extended. The generalized model allows a nonuniform initial material-phase concentration and a transient influent gas-phase concentration to be simultaneously considered. An analytical solution to the more general model is developed. Experimental data are obtained by placing samples of vinyl flooring inside a small stainless steel chamber and exposing them to absorption/desorption cycles of n-dodecane and phenol. Measured values for the material-air partition coefficient and the material-phase diffusion coefficient were obtained previously in a series of completely independent experiments. The a priori model predictions are in close agreement with the observed experimental data.

Optical diagnosis of malaria infection in human plasma using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bilal, Muhammad; Saleem, Muhammad; Amanat, Samina Tufail; Shakoor, Huma Abdul; Rashid, Rashad; Mahmood, Arshad; Ahmed, Mushtaq

2015-01-01

We present the prediction of malaria infection in human plasma using Raman spectroscopy. Raman spectra of malaria-infected samples are compared with those of healthy and dengue virus infected ones for disease recognition. Raman spectra were acquired using a laser at 532 nm as an excitation source and 10 distinct spectral signatures that statistically differentiated malaria from healthy and dengue-infected cases were found. A multivariate regression model has been developed that utilized Raman spectra of 20 malaria-infected, 10 non-malarial with fever, 10 healthy, and 6 dengue-infected samples to optically predict the malaria infection. The model yields the correlation coefficient r2 value of 0.981 between the predicted values and clinically known results of trainee samples, and the root mean square error in cross validation was found to be 0.09; both these parameters validated the model. The model was further blindly tested for 30 unknown suspected samples and found to be 86% accurate compared with the clinical results, with the inaccuracy due to three samples which were predicted in the gray region. Standard deviation and root mean square error in prediction for unknown samples were found to be 0.150 and 0.149, which are accepted for the clinical validation of the model.

Application of transit data analysis and artificial neural network in the prediction of discharge of Lor River, NW Spain.

PubMed

Astray, G; Soto, B; Lopez, D; Iglesias, M A; Mejuto, J C

2016-01-01

Transit data analysis and artificial neural networks (ANNs) have proven to be a useful tool for characterizing and modelling non-linear hydrological processes. In this paper, these methods have been used to characterize and to predict the discharge of Lor River (North Western Spain), 1, 2 and 3 days ahead. Transit data analyses show a coefficient of correlation of 0.53 for a lag between precipitation and discharge of 1 day. On the other hand, temperature and discharge has a negative coefficient of correlation (-0.43) for a delay of 19 days. The ANNs developed provide a good result for the validation period, with R(2) between 0.92 and 0.80. Furthermore, these prediction models have been tested with discharge data from a period 16 years later. Results of this testing period also show a good correlation, with R(2) between 0.91 and 0.64. Overall, results indicate that ANNs are a good tool to predict river discharge with a small number of input variables.

Derivation and validation of in-hospital mortality prediction models in ischaemic stroke patients using administrative data.

PubMed

Lee, Jason; Morishima, Toshitaka; Kunisawa, Susumu; Sasaki, Noriko; Otsubo, Tetsuya; Ikai, Hiroshi; Imanaka, Yuichi

2013-01-01

Stroke and other cerebrovascular diseases are a major cause of death and disability. Predicting in-hospital mortality in ischaemic stroke patients can help to identify high-risk patients and guide treatment approaches. Chart reviews provide important clinical information for mortality prediction, but are laborious and limiting in sample sizes. Administrative data allow for large-scale multi-institutional analyses but lack the necessary clinical information for outcome research. However, administrative claims data in Japan has seen the recent inclusion of patient consciousness and disability information, which may allow more accurate mortality prediction using administrative data alone. The aim of this study was to derive and validate models to predict in-hospital mortality in patients admitted for ischaemic stroke using administrative data. The sample consisted of 21,445 patients from 176 Japanese hospitals, who were randomly divided into derivation and validation subgroups. Multivariable logistic regression models were developed using 7- and 30-day and overall in-hospital mortality as dependent variables. Independent variables included patient age, sex, comorbidities upon admission, Japan Coma Scale (JCS) score, Barthel Index score, modified Rankin Scale (mRS) score, and admissions after hours and on weekends/public holidays. Models were developed in the derivation subgroup, and coefficients from these models were applied to the validation subgroup. Predictive ability was analysed using C-statistics; calibration was evaluated with Hosmer-Lemeshow χ(2) tests. All three models showed predictive abilities similar or surpassing that of chart review-based models. The C-statistics were highest in the 7-day in-hospital mortality prediction model, at 0.906 and 0.901 in the derivation and validation subgroups, respectively. For the 30-day in-hospital mortality prediction models, the C-statistics for the derivation and validation subgroups were 0.893 and 0.872, respectively; in overall in-hospital mortality prediction these values were 0.883 and 0.876. In this study, we have derived and validated in-hospital mortality prediction models for three different time spans using a large population of ischaemic stroke patients in a multi-institutional analysis. The recent inclusion of JCS, Barthel Index, and mRS scores in Japanese administrative data has allowed the prediction of in-hospital mortality with accuracy comparable to that of chart review analyses. The models developed using administrative data had consistently high predictive abilities for all models in both the derivation and validation subgroups. These results have implications in the role of administrative data in future mortality prediction analyses. Copyright © 2013 S. Karger AG, Basel.

Heat and mass transport during microwave heating of mashed potato in domestic oven--model development, validation, and sensitivity analysis.

PubMed

Chen, Jiajia; Pitchai, Krishnamoorthy; Birla, Sohan; Negahban, Mehrdad; Jones, David; Subbiah, Jeyamkondan

2014-10-01

A 3-dimensional finite-element model coupling electromagnetics and heat and mass transfer was developed to understand the interactions between the microwaves and fresh mashed potato in a 500 mL tray. The model was validated by performing heating of mashed potato from 25 °C on a rotating turntable in a microwave oven, rated at 1200 W, for 3 min. The simulated spatial temperature profiles on the top and bottom layer of the mashed potato showed similar hot and cold spots when compared to the thermal images acquired by an infrared camera. Transient temperature profiles at 6 locations collected by fiber-optic sensors showed good agreement with predicted results, with the root mean square error ranging from 1.6 to 11.7 °C. The predicted total moisture loss matched well with the observed result. Several input parameters, such as the evaporation rate constant, the intrinsic permeability of water and gas, and the diffusion coefficient of water and gas, are not readily available for mashed potato, and they cannot be easily measured experimentally. Reported values for raw potato were used as baseline values. A sensitivity analysis of these input parameters on the temperature profiles and the total moisture loss was evaluated by changing the baseline values to their 10% and 1000%. The sensitivity analysis showed that the gas diffusion coefficient, intrinsic water permeability, and the evaporation rate constant greatly influenced the predicted temperature and total moisture loss, while the intrinsic gas permeability and the water diffusion coefficient had little influence. This model can be used by the food product developers to understand microwave heating of food products spatially and temporally. This tool will allow food product developers to design food package systems that would heat more uniformly in various microwave ovens. The sensitivity analysis of this study will help us determine the most significant parameters that need to be measured accurately for reliable model prediction. © 2014 Institute of Food Technologists®

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations

PubMed Central

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-01-01

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q2 (cross-validated correlation coefficient) = 0.557, R2ncv (non-cross-validated correlation coefficient) = 0.740, R2pre (predicted correlation coefficient) = 0.749 and Q2 = 0.598, R2ncv = 0.767, R2pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors. PMID:26307982

Insight into the Structural Determinants of Imidazole Scaffold-Based Derivatives as TNF-α Release Inhibitors by in Silico Explorations.

PubMed

Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua

2015-08-25

Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q(2) (cross-validated correlation coefficient) = 0.557, R(2)ncv (non-cross-validated correlation coefficient) = 0.740, R(2)pre (predicted correlation coefficient) = 0.749 and Q(2) = 0.598, R(2)ncv = 0.767, R(2)pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors.

Validation of a new formula for predicting body weight in a Mexican population with overweight and obesity.

PubMed

Quiroz-Olguín, Gabriela; Serralde-Zúñiga, Aurora Elizabeth; Saldaña-Morales, Vianey; Guevara-Cruz, Martha

2013-01-01

Body weight measurement is of critical importance when evaluating the nutritional status of patients entering a hospital. In some situations, such as the case of patients who are bedridden or in wheelchairs, these measurements cannot be obtained using standardized methods. We have designed and validated a formula for predicting body weight. To design and validate a formula for predicting body weight using circumference-based equations. The following anthropometric measurements were taken for a sample of 76 patients: weight (kg), calf circumference, average arm circumference, waist circumference, hip circumference, wrist circumference and demispan. All circumferences were taken in centimetres (cm), and gender and age were taken into account. This equation was validated in 85 individuals from a different population. The correlation with the new equation was analyzed and compared to a previously validated method. The equation for weight prediction was the following: Weight = 0.524 (WC) - 0.176 (age) + 0.484 (HC) + 0.613 (DS) + 0.704 (CC) + 2.75 (WrC) - 3.330 (if female) - 140.87. The correlation coefficient was 0.96 for the total group of patients, 0.971 for men and 0.961 for women (p < 0.0001 for all measurements). The equation we developed is accurate and can be used to estimate body weight in overweight and/or obese patients with mobility problems, such as bedridden patients or patients in wheelchairs. Copyright © AULA MEDICA EDICIONES 2013. Published by AULA MEDICA. All rights reserved.

QSPR study of polychlorinated diphenyl ethers by molecular electronegativity distance vector (MEDV-4).

PubMed

Sun, Lili; Zhou, Liping; Yu, Yu; Lan, Yukun; Li, Zhiliang

2007-01-01

Polychlorinated diphenyl ethers (PCDEs) have received more and more concerns as a group of ubiquitous potential persistent organic pollutants (POPs). By using molecular electronegativity distance vector (MEDV-4), multiple linear regression (MLR) models are developed for sub-cooled liquid vapor pressures (P(L)), n-octanol/water partition coefficients (K(OW)) and sub-cooled liquid water solubilities (S(W,L)) of 209 PCDEs and diphenyl ether. The correlation coefficients (R) and the leave-one-out cross-validation (LOO) correlation coefficients (R(CV)) of all the 6-descriptor models for logP(L), logK(OW) and logS(W,L) are more than 0.98. By using stepwise multiple regression (SMR), the descriptors are selected and the resulting models are 5-descriptor model for logP(L), 4-descriptor model for logK(OW), and 6-descriptor model for logS(W,L), respectively. All these models exhibit excellent estimate capabilities for internal sample set and good predictive capabilities for external samples set. The consistency between observed and estimated/predicted values for logP(L) is the best (R=0.996, R(CV)=0.996), followed by logK(OW) (R=0.992, R(CV)=0.992) and logS(W,L) (R=0.983, R(CV)=0.980). By using MEDV-4 descriptors, the QSPR models can be used for prediction and the model predictions can hence extend the current database of experimental values.

A unified theory for ice vapor growth suitable for cloud models: Testing and implications for cold cloud evolution

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

A new microphysical model for the vapor growth and aspect ratio evolution of atmospheric ice crystals is presented. The method is based on the adaptive habit model of Chen and Lamb (1994), but is modified to include surface kinetic processes for crystal growth. Inclusion of surface kinetic effects is accomplished with a new theory that accounts for axis dependent growth. Deposition coefficients (growth efficiencies) are predicted for two axis directions based on laboratory-determined parameters for growth initiation (critical supersaturations) on each face. In essence, the new theory extends the adaptive habit approach of Chen and Lamb (1994) to ice saturation states below that of liquid saturation, where Chen and Lamb (1994) is likely most valid. The new model is used to simulate changes in crystal primary habit as a function of temperature and ice supersaturation. Predictions are compared with a detailed hexagonal growth model both in a single particle framework and in a Lagrangian parcel model to indicate the accuracy of the new method. Moreover, predictions of the ratio of the axis deposition coefficients match laboratory-generated data. A parameterization for predicting deposition coefficients is developed for the bulk microphysics frame work in Regional Atmospheric Modeling System (RAMS). Initial eddy-resolving model simulation is conducted to study the effect of surface kinetics on microphysical and dynamical processes in cold cloud development.

QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

2009-01-01

Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

Building and validation of a prognostic model for predicting extracorporeal circuit clotting in patients with continuous renal replacement therapy.

PubMed

Fu, Xia; Liang, Xinling; Song, Li; Huang, Huigen; Wang, Jing; Chen, Yuanhan; Zhang, Li; Quan, Zilin; Shi, Wei

2014-04-01

To develop a predictive model for circuit clotting in patients with continuous renal replacement therapy (CRRT). A total of 425 cases were selected. 302 cases were used to develop a predictive model of extracorporeal circuit life span during CRRT without citrate anticoagulation in 24 h, and 123 cases were used to validate the model. The prediction formula was developed using multivariate Cox proportional-hazards regression analysis, from which a risk score was assigned. The mean survival time of the circuit was 15.0 ± 1.3 h, and the rate of circuit clotting was 66.6 % during 24 h of CRRT. Five significant variables were assigned a predicting score according to the regression coefficient: insufficient blood flow, no anticoagulation, hematocrit ≥0.37, lactic acid of arterial blood gas analysis ≤3 mmol/L and APTT < 44.2 s. The Hosmer-Lemeshow test showed no significant difference between the predicted and actual circuit clotting (R (2) = 0.232; P = 0.301). A risk score that includes the five above-mentioned variables can be used to predict the likelihood of extracorporeal circuit clotting in patients undergoing CRRT.

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control Over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

Prediction of oxygen consumption in cardiac rehabilitation patients performing leg ergometry

NASA Astrophysics Data System (ADS)

Alvarez, John Gershwin

The purpose of this study was two-fold. First, to determine the validity of the ACSM leg ergometry equation in the prediction of steady-state oxygen consumption (VO2) in a heterogeneous population of cardiac patients. Second, to determine whether a more accurate prediction equation could be developed for use in the cardiac population. Thirty-one cardiac rehabilitation patients participated in the study of which 24 were men and 7 were women. Biometric variables (mean +/- sd) of the participants were as follows: age = 61.9 +/- 9.5 years; height = 172.6 +/- 1.6 cm; and body mass = 82.3 +/- 10.6 kg. Subjects exercised on a MonarchTM cycle ergometer at 0, 180, 360, 540 and 720 kgm ˙ min-1. The length of each stage was five minutes. Heart rate, ECG, and VO2 were continuously monitored. Blood pressure and heart rate were collected at the end of each stage. Steady state VO 2 was calculated for each stage using the average of the last two minutes. Correlation coefficients, standard error of estimate, coefficient of determination, total error, and mean bias were used to determine the accuracy of the ACSM equation (1995). The analysis found the ACSM equation to be a valid means of estimating VO2 in cardiac patients. Simple linear regression was used to develop a new equation. Regression analysis found workload to be a significant predictor of VO2. The following equation is the result: VO2 = (1.6 x kgm ˙ min-1) + 444 ml ˙ min-1. The r of the equation was .78 (p < .05) and the standard error of estimate was 211 ml ˙ min-1. Analysis of variance was used to determine significant differences between means for actual and predicted VO2 values for each equation. The analysis found the ACSM and new equation to significantly (p < .05) under predict VO2 during unloaded pedaling. Furthermore, the ACSM equation was found to significantly (p < .05) under predict VO 2 during the first loaded stage of exercise. When the accuracy of the ACSM and new equations were compared based on correlation coefficients, coefficients of determinations, SEEs, total error, and mean bias the new equation was found to have equal or better accuracy at all workloads. The final form of the new equation is: VO2 (ml ˙ min-1) = (kgm ˙ min-1 x 1.6 ml ˙ kgm-1) + (3.5 ml ˙ kg-1 ˙ min-1 x body mass in kg) + 156 ml ˙ min-1.

Extension of Weighted Sum of Gray Gas Data to Mathematical Simulation of Radiative Heat Transfer in a Boiler with Gas-Soot Media

PubMed Central

Nouri-Borujerdi, Ali; Kazi, Salim Newaz

2014-01-01

In this study an expression for soot absorption coefficient is introduced to extend the weighted-sum-of-gray gases data to the furnace medium containing gas-soot mixture in a utility boiler 150 MWe. Heat transfer and temperature distribution of walls and within the furnace space are predicted by zone method technique. Analyses have been done considering both cases of presence and absence of soot particles at 100% load. To validate the proposed soot absorption coefficient, the expression is coupled with the Taylor and Foster's data as well as Truelove's data for CO2-H2O mixture and the total emissivities are calculated and compared with the Truelove's parameters for 3-term and 4-term gray gases plus two soot absorption coefficients. In addition, some experiments were conducted at 100% and 75% loads to measure furnace exit gas temperature as well as the rate of steam production. The predicted results show good agreement with the measured data at the power plant site. PMID:25143981

Extension of weighted sum of gray gas data to mathematical simulation of radiative heat transfer in a boiler with gas-soot media.

PubMed

Gharehkhani, Samira; Nouri-Borujerdi, Ali; Kazi, Salim Newaz; Yarmand, Hooman

2014-01-01

In this study an expression for soot absorption coefficient is introduced to extend the weighted-sum-of-gray gases data to the furnace medium containing gas-soot mixture in a utility boiler 150 MWe. Heat transfer and temperature distribution of walls and within the furnace space are predicted by zone method technique. Analyses have been done considering both cases of presence and absence of soot particles at 100% load. To validate the proposed soot absorption coefficient, the expression is coupled with the Taylor and Foster's data as well as Truelove's data for CO2-H2O mixture and the total emissivities are calculated and compared with the Truelove's parameters for 3-term and 4-term gray gases plus two soot absorption coefficients. In addition, some experiments were conducted at 100% and 75% loads to measure furnace exit gas temperature as well as the rate of steam production. The predicted results show good agreement with the measured data at the power plant site.

Measurement of predictive validity in violence risk assessment studies: a second-order systematic review.

PubMed

Singh, Jay P; Desmarais, Sarah L; Van Dorn, Richard A

2013-01-01

The objective of the present review was to examine how predictive validity is analyzed and reported in studies of instruments used to assess violence risk. We reviewed 47 predictive validity studies published between 1990 and 2011 of 25 instruments that were included in two recent systematic reviews. Although all studies reported receiver operating characteristic curve analyses and the area under the curve (AUC) performance indicator, this methodology was defined inconsistently and findings often were misinterpreted. In addition, there was between-study variation in benchmarks used to determine whether AUCs were small, moderate, or large in magnitude. Though virtually all of the included instruments were designed to produce categorical estimates of risk - through the use of either actuarial risk bins or structured professional judgments - only a minority of studies calculated performance indicators for these categorical estimates. In addition to AUCs, other performance indicators, such as correlation coefficients, were reported in 60% of studies, but were infrequently defined or interpreted. An investigation of sources of heterogeneity did not reveal significant variation in reporting practices as a function of risk assessment approach (actuarial vs. structured professional judgment), study authorship, geographic location, type of journal (general vs. specialized audience), sample size, or year of publication. Findings suggest a need for standardization of predictive validity reporting to improve comparison across studies and instruments. Copyright © 2013 John Wiley & Sons, Ltd.

Reliability and validity of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-30) in Saudi Arabia.

PubMed

Tadakamadla, Santosh Kumar; Quadri, Mir Faeq Ali; Pakpour, Amir H; Zailai, Abdulaziz M; Sayed, Mohammed E; Mashyakhy, Mohammed; Inamdar, Aadil S; Tadakamadla, Jyothi

2014-09-29

To evaluate the reliability and validity of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-30) in Saudi Arabia. A convenience sample of 200 subjects was approached, of which 177 agreed to participate giving a response rate of 88.5%. Rapid Estimate of Adult Literacy in Dentistry (REALD-99), was translated into Arabic to prepare the longer and shorter versions of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-99 and AREALD-30). Each participant was provided with AREALD-99 which also includes words from AREALD-30. A questionnaire containing socio-behavioral information and Arabic Oral Health Impact Profile (A-OHIP-14) was also administered. Reliability of the AREALD-30 was assessed by re-administering it to 20 subjects after two weeks. Convergent and predictive validity of AREALD-30 was evaluated by its correlations with AREALD-99 and self-perceived oral health status, dental visiting habits and A-OHIP-14 respectively. Discriminant validity was assessed in relation to the educational level while construct validity was evaluated by confirmatory factor analysis (CFA). Reliability of AREALD-30 was excellent with intraclass correlation coefficient of 0.99. It exhibited good convergent and discriminant validity but poor predictive validity. CFA showed presence of two factors and infit mean-square statistics for AREALD-30 were all within the desired range of 0.50 - 2.0 in Rasch analysis. AREALD-30 showed excellent reliability, good convergent and concurrent validity, but failed to predict the differences between the subjects categorized based on their oral health outcomes.

Development and validation of the Pediatric Anesthesia Behavior score--an objective measure of behavior during induction of anesthesia.

PubMed

Beringer, Richard M; Greenwood, Rosemary; Kilpatrick, Nicky

2014-02-01

Measuring perioperative behavior changes requires validated objective rating scales. We developed a simple score for children's behavior during induction of anesthesia (Pediatric Anesthesia Behavior score) and assessed its reliability, concurrent validity, and predictive validity. Data were collected as part of a wider observational study of perioperative behavior changes in children undergoing general anesthesia for elective dental extractions. One-hundred and two healthy children aged 2-12 were recruited. Previously validated behavioral scales were used as follows: the modified Yale Preoperative Anxiety Scale (m-YPAS); the induction compliance checklist (ICC); the Pediatric Anesthesia Emergence Delirium scale (PAED); and the Post-Hospitalization Behavior Questionnaire (PHBQ). Pediatric Anesthesia Behavior (PAB) score was independently measured by two investigators, to allow assessment of interobserver reliability. Concurrent validity was assessed by examining the correlation between the PAB score, the m-YPAS, and the ICC. Predictive validity was assessed by examining the association between the PAB score, the PAED scale, and the PHBQ. The PAB score correlated strongly with both the m-YPAS (P < 0.001) and the ICC (P < 0.001). PAB score was significantly associated with the PAED score (P = 0.031) and with the PHBQ (P = 0.034). Two independent investigators recorded identical PAB scores for 94% of children and overall, there was close agreement between scores (Kappa coefficient of 0.886 [P < 0.001]). The PAB score is simple to use and may predict which children are at increased risk of developing postoperative behavioral disturbance. This study provides evidence for its reliability and validity. © 2013 John Wiley & Sons Ltd.

Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM).

PubMed

Willis, Michael; Johansen, Pierre; Nilsson, Andreas; Asseburg, Christian

2017-03-01

The Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM) was developed to address study questions pertaining to the cost-effectiveness of treatment alternatives in the care of patients with type 2 diabetes mellitus (T2DM). Naturally, the usefulness of a model is determined by the accuracy of its predictions. A previous version of ECHO-T2DM was validated against actual trial outcomes and the model predictions were generally accurate. However, there have been recent upgrades to the model, which modify model predictions and necessitate an update of the validation exercises. The objectives of this study were to extend the methods available for evaluating model validity, to conduct a formal model validation of ECHO-T2DM (version 2.3.0) in accordance with the principles espoused by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), and secondarily to evaluate the relative accuracy of four sets of macrovascular risk equations included in ECHO-T2DM. We followed the ISPOR/SMDM guidelines on model validation, evaluating face validity, verification, cross-validation, and external validation. Model verification involved 297 'stress tests', in which specific model inputs were modified systematically to ascertain correct model implementation. Cross-validation consisted of a comparison between ECHO-T2DM predictions and those of the seminal National Institutes of Health model. In external validation, study characteristics were entered into ECHO-T2DM to replicate the clinical results of 12 studies (including 17 patient populations), and model predictions were compared to observed values using established statistical techniques as well as measures of average prediction error, separately for the four sets of macrovascular risk equations supported in ECHO-T2DM. Sub-group analyses were conducted for dependent vs. independent outcomes and for microvascular vs. macrovascular vs. mortality endpoints. All stress tests were passed. ECHO-T2DM replicated the National Institutes of Health cost-effectiveness application with numerically similar results. In external validation of ECHO-T2DM, model predictions agreed well with observed clinical outcomes. For all sets of macrovascular risk equations, the results were close to the intercept and slope coefficients corresponding to a perfect match, resulting in high R 2 and failure to reject concordance using an F test. The results were similar for sub-groups of dependent and independent validation, with some degree of under-prediction of macrovascular events. ECHO-T2DM continues to match health outcomes in clinical trials in T2DM, with prediction accuracy similar to other leading models of T2DM.

3D-QSAR and molecular docking studies on designing inhibitors of the hepatitis C virus NS5B polymerase

NASA Astrophysics Data System (ADS)

Li, Wenlian; Si, Hongzong; Li, Yang; Ge, Cuizhu; Song, Fucheng; Ma, Xiuting; Duan, Yunbo; Zhai, Honglin

2016-08-01

Viral hepatitis C infection is one of the main causes of the hepatitis after blood transfusion and hepatitis C virus (HCV) infection is a global health threat. The HCV NS5B polymerase, an RNA dependent RNA polymerase (RdRp) and an essential role in the replication of the virus, has no functional equivalent in mammalian cells. So the research and development of efficient NS5B polymerase inhibitors provides a great strategy for antiviral therapy against HCV. A combined three-dimensional quantitative structure-activity relationship (QSAR) modeling was accomplished to profoundly understand the structure-activity correlation of a train of indole-based inhibitors of the HCV NS5B polymerase to against HCV. A comparative molecular similarity indices analysis (COMSIA) model as the foundation of the maximum common substructure alignment was developed. The optimum model exhibited statistically significant results: the cross-validated correlation coefficient q2 was 0.627 and non-cross-validated r2 value was 0.943. In addition, the results of internal validations of bootstrapping and Y-randomization confirmed the rationality and good predictive ability of the model, as well as external validation (the external predictive correlation coefficient rext2 = 0.629). The information obtained from the COMSIA contour maps enables the interpretation of their structure-activity relationship. Furthermore, the molecular docking study of the compounds for 3TYV as the protein target revealed important interactions between active compounds and amino acids, and several new potential inhibitors with higher activity predicted were designed basis on our analyses and supported by the simulation of molecular docking. Meanwhile, the OSIRIS Property Explorer was introduced to help select more satisfactory compounds. The satisfactory results from this study may lay a reliable theoretical base for drug development of hepatitis C virus NS5B polymerase inhibitors.

Reliability and diagnostic validity of the slump knee bend neurodynamic test for upper/mid lumbar nerve root compression: a pilot study.

PubMed

Trainor, Kate; Pinnington, Mark A

2011-03-01

It has been proposed that neurodynamic examination can assist differential diagnosis of upper/mid lumbar nerve root compression; however, the diagnostic validity of many of these tests has yet to be established. This pilot study aimed to establish the diagnostic validity of the slump knee bend neurodynamic test for upper/mid lumbar nerve root compression in subjects with suspected lumbosacral radicular pain. Two independent examiners performed the slump knee bend test on subjects with radicular leg pain. Inter-tester reliability was calculated using the kappa coefficient. Slump knee bend test results were compared with magnetic resonance imaging findings, and diagnostic accuracy measures were calculated including sensitivity, specificity, predictive values and likelihood ratios. Orthopaedic spinal clinic, secondary care. Sixteen patients with radicular leg pain. All four subjects with mid lumbar nerve root compression on magnetic resonance imaging were correctly identified with the slump knee bend test; however, it was falsely positive in two individuals without the condition. Inter-tester reliability for the slump knee bend test using the kappa coefficient was 0.71 (95% confidence interval 0.33 to 1.0). Diagnostic validity calculations for the slump knee bend test (95% confidence intervals) were: sensitivity, 100% (40 to 100%); specificity, 83% (52 to 98%); positive predictive value, 67% (22 to 96%); negative predictive value, 100% (69 to 100%); positive likelihood ratio, 6.0 (1.58 to 19.4); and negative likelihood ratio, 0 (0 to 0.6). Results indicate good inter-tester reliability and suggest that the slump knee bend test has potential to be a useful clinical test for identifying patients with mid lumbar nerve root compression. Further investigation is needed on larger numbers of patients to confirm these findings. Copyright © 2010 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

A Surrogate Approach to the Experimental Optimization of Multielement Airfoils

NASA Technical Reports Server (NTRS)

Otto, John C.; Landman, Drew; Patera, Anthony T.

1996-01-01

The incorporation of experimental test data into the optimization process is accomplished through the use of Bayesian-validated surrogates. In the surrogate approach, a surrogate for the experiment (e.g., a response surface) serves in the optimization process. The validation step of the framework provides a qualitative assessment of the surrogate quality, and bounds the surrogate-for-experiment error on designs "near" surrogate-predicted optimal designs. The utility of the framework is demonstrated through its application to the experimental selection of the trailing edge ap position to achieve a design lift coefficient for a three-element airfoil.

Application of laser to nondestructive detection of fruit quality

NASA Astrophysics Data System (ADS)

Li, Jing; Xue, Long; Liu, Muhua; Li, Zhanlong; Yang, Yong

2008-12-01

In this study, a hyperspectral imaging system using a laser source was developed and two experiments were carried out. The first experiment was detection of pesticide residue on navel orange surface. We calculated the mean intensity of regions of interest to plot the curves between 629nm to 638nm. The analysis of the mean intensity curves showed that the mean intensity can be described by a characteristic Gaussian curve equation. The coefficients a in characteristic equations of 0%, 0.1% and 0.5% fenvalerate residue images were more than 2400, 1570-2400 and less than 1570, respectively. So we suggest using equation coefficient a to detect pesticide residue on navel orange surface. The second experiment was predicting firmness, sugar content and vitamin C content of kiwi fruit. The optimal wavelength range of the kiwi fruit firmness, sugar content, vitamin C content line regressing prediction model were 680-711nm, 674-708nm, 669-701nm. The correlation coefficients (R) of prediction models for firmness, sugar content and vitamin C content were 0.898, 0.932 and 0.918. The mean errors of validation results were 0.35×105Pa, 0.32%Brix and 7mg/100g. The experimental results indicate that a hyperspectral imaging system based on a laser source can detect fruit quality effectively.

Development of the Affordances in the Home Environment for Motor Development-Infant Scale.

PubMed

Caçola, Priscila; Gabbard, Carl; Santos, Denise C C; Batistela, Ana Carolina T

2011-12-01

The present study reports the development and application of the Affordances in the Home Environment for Motor Development-Infant Scale (AHEMD-IS), a parental self-report designed to assess the quantity and quality of affordances in the home environment that are conducive to motor development for infants aged 3-18 months. Steps in its development included use of expert feedback, establishment of construct validity, interrater and intrarater reliability, and predictive validity. With all phases of the project, 113 homes were involved. Intraclass correlation coefficients for interrater and intrarater reliability for the total score were 1 and 0.94, respectively. In addition, results indicate that the test has the characteristic of differentiating a wide range of scores. Regression analysis for the AHEMD-IS and motor development using the Alberta Infant Motor Scale supports preliminary evidence for predictive validity. Our findings suggest that the AHEMD-IS has sufficient reliability and validity as an instrument for assessing affordances in the home environment, with clinical and research applications. © 2011 The Authors. Pediatrics International © 2011 Japan Pediatric Society.

A rapid method for detection of fumonisins B1 and B2 in corn meal using Fourier transform near infrared (FT-NIR) spectroscopy implemented with integrating sphere.

PubMed

Gaspardo, B; Del Zotto, S; Torelli, E; Cividino, S R; Firrao, G; Della Riccia, G; Stefanon, B

2012-12-01

Fourier transform near infrared (FT-NIR) spectroscopy is an analytical procedure generally used to detect organic compounds in food. In this work the ability to predict fumonisin B(1)+B(2) contents in corn meal using an FT-NIR spectrophotometer, equipped with an integration sphere, was assessed. A total of 143 corn meal samples were collected in Friuli Venezia Giulia Region (Italy) and used to define a 15 principal components regression model, applying partial least square regression algorithm with full cross validation as internal validation. External validation was performed to 25 unknown samples. Coefficients of correlation, root mean square error and standard error of calibration were 0.964, 0.630 and 0.632, respectively and the external validation confirmed a fair potential of the model in predicting FB(1)+FB(2) concentration. Results suggest that FT-NIR analysis is a suitable method to detect FB(1)+FB(2) in corn meal and to discriminate safe meals from those contaminated. Copyright © 2012 Elsevier Ltd. All rights reserved.

Identification of cutting force coefficients in machining process considering cutter vibration

NASA Astrophysics Data System (ADS)

Yao, Qi; Luo, Ming; Zhang, Dinghua; Wu, Baohai

2018-03-01

Among current cutting force models, cutting force coefficients still are the foundation of predicting calculation combined with consideration of geometry engagement variation, equipment characteristics, material properties and so on. Attached with unimpeachable significance, the traditional and some novel identification methods of cutting force coefficient are still faced with trouble, including repeated onerous work, over ideal measuring condition, variation of value due to material divergence, interference from measuring units. To utilize the large amount of data from real manufacturing section, enlarge data sources and enrich cutting data base for former prediction task, a novel identification method is proposed by considering stiffness properties of the cutter-holder-spindle system in this paper. According to previously proposed studies, the direct result of cutter vibration is the form of dynamic undeformed chip thickness. This fluctuation is considered in two stages of this investigation. Firstly, a cutting force model combined with cutter vibration is established in detailed way. Then, on the foundation of modeling, a novel identification method is developed, in which the dynamic undeformed chip thickness could be obtained by using collected data. In a carefully designed experiment procedure, the reliability of model is validated by comparing predicted and measured results. Under different cutting condition and cutter stiffness, data is collected for the justification of identification method. The results showed divergence in calculated coefficients is acceptable confirming the possibility of accomplishing targets by applying this new method. In discussion, the potential directions of improvement are proposed.

Resonant indirect optical absorption in germanium

NASA Astrophysics Data System (ADS)

Menéndez, José; Noël, Mario; Zwinkels, Joanne C.; Lockwood, David J.

2017-09-01

The optical absorption coefficient of pure Ge has been determined from high-accuracy, high-precision optical measurements at photon energies covering the spectral range between the indirect and direct gaps. The results are compared with a theoretical model that fully accounts for the resonant nature of the energy denominators that appear in perturbation-theory expansions of the absorption coefficient. The model generalizes the classic Elliott approach to indirect excitons, and leads to a predicted optical absorption that is in excellent agreement with the experimental values using just a single adjustable parameter: the average deformation potential DΓ L coupling electrons at the bottom of the direct and indirect valleys in the conduction band. Remarkably, the fitted value, DΓ L=4.3 ×108eV /cm , is in nearly perfect agreement with independent measurements and ab initio predictions of this parameter, confirming the validity of the proposed theory, which has general applicability.

Development, test-retest reliability and validity of the Pharmacy Value-Added Services Questionnaire (PVASQ)

PubMed Central

Tan, Christine L.; Hassali, Mohamed A.; Saleem, Fahad; Shafie, Asrul A.; Aljadhey, Hisham; Gan, Vincent B.

2015-01-01

Objective: (i) To develop the Pharmacy Value-Added Services Questionnaire (PVASQ) using emerging themes generated from interviews. (ii) To establish reliability and validity of questionnaire instrument. Methods: Using an extended Theory of Planned Behavior as the theoretical model, face-to-face interviews generated salient beliefs of pharmacy value-added services. The PVASQ was constructed initially in English incorporating important themes and later translated into the Malay language with forward and backward translation. Intention (INT) to adopt pharmacy value-added services is predicted by attitudes (ATT), subjective norms (SN), perceived behavioral control (PBC), knowledge and expectations. Using a 7-point Likert-type scale and a dichotomous scale, test-retest reliability (N=25) was assessed by administrating the questionnaire instrument twice at an interval of one week apart. Internal consistency was measured by Cronbach’s alpha and construct validity between two administrations was assessed using the kappa statistic and the intraclass correlation coefficient (ICC). Confirmatory Factor Analysis, CFA (N=410) was conducted to assess construct validity of the PVASQ. Results: The kappa coefficients indicate a moderate to almost perfect strength of agreement between test and retest. The ICC for all scales tested for intra-rater (test-retest) reliability was good. The overall Cronbach’ s alpha (N=25) is 0.912 and 0.908 for the two time points. The result of CFA (N=410) showed most items loaded strongly and correctly into corresponding factors. Only one item was eliminated. Conclusions: This study is the first to develop and establish the reliability and validity of the Pharmacy Value-Added Services Questionnaire instrument using the Theory of Planned Behavior as the theoretical model. The translated Malay language version of PVASQ is reliable and valid to predict Malaysian patients’ intention to adopt pharmacy value-added services to collect partial medicine supply. PMID:26445622

Bronchiolitis Score of Sant Joan de Déu: BROSJOD Score, validation and usefulness.

PubMed

Balaguer, Mònica; Alejandre, Carme; Vila, David; Esteban, Elisabeth; Carrasco, Josep L; Cambra, Francisco José; Jordan, Iolanda

2017-04-01

To validate the bronchiolitis score of Sant Joan de Déu (BROSJOD) and to examine the previously defined scoring cutoff. Prospective, observational study. BROSJOD scoring was done by two independent physicians (at admission, 24 and 48 hr). Internal consistency of the score was assessed using Cronbach's α. To determine inter-rater reliability, the concordance correlation coefficient estimated as an intraclass correlation coefficient (CCC) and limits of agreement estimated as the 90% total deviation index (TDI) were estimated. An expert opinion was used to classify patients according to clinical severity. A validity analysis was conducted comparing the 3-level classification score to that expert opinion. Volume under the surface (VUS), predictive values, and probability of correct classification (PCC) were measured to assess discriminant validity. About 112 patients were recruited, 62 of them (55.4%) males. Median age: 52.5 days (IQR: 32.75-115.25). The admission Cronbach's α was 0.77 (CI95%: 0.71; 0.82) and at 24 hr it was 0.65 (CI95%: 0.48; 0.7). The inter-rater reliability analysis was: CCC at admission 0.96 (95%CI 0.94-0.97), at 24 h 0.77 (95%CI 0.65-0.86), and at 48 hr 0.94 (95%CI 0.94-0.97); TDI 90%: 1.6, 2.9, and 1.57, respectively. The discriminant validity at admission: VUS of 0.8 (95%CI 0.70-0.90), at 24 h 0.92 (95%CI 0.85-0.99), and at 48 hr 0.93 (95%CI 0.87-0.99). The predictive values and PCC values were within 38-100% depending on the level of clinical severity. There is a high inter-rater reliability, showing the BROSJOD score to be reliable and valid, even when different observers apply it. Pediatr Pulmonol. 2017;52:533-539. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Development and validation of an ICD-10-based disability predictive index for patients admitted to hospitals with trauma.

PubMed

Wada, Tomoki; Yasunaga, Hideo; Yamana, Hayato; Matsui, Hiroki; Fushimi, Kiyohide; Morimura, Naoto

2018-03-01

There was no established disability predictive measurement for patients with trauma that could be used in administrative claims databases. The aim of the present study was to develop and validate a diagnosis-based disability predictive index for severe physical disability at discharge using the International Classification of Diseases, 10th revision (ICD-10) coding. This retrospective observational study used the Diagnosis Procedure Combination database in Japan. Patients who were admitted to hospitals with trauma and discharged alive from 01 April 2010 to 31 March 2015 were included. Pediatric patients under 15 years old were excluded. Data for patients admitted to hospitals from 01 April 2010 to 31 March 2013 was used for development of a disability predictive index (derivation cohort), while data for patients admitted to hospitals from 01 April 2013 to 31 March 2015 was used for the internal validation (validation cohort). The outcome of interest was severe physical disability defined as the Barthel Index score of <60 at discharge. Trauma-related ICD-10 codes were categorized into 36 injury groups with reference to the categorization used in the Global Burden of Diseases study 2013. A multivariable logistic regression analysis was performed for the outcome using the injury groups and patient baseline characteristics including patient age, sex, and Charlson Comorbidity Index (CCI) score in the derivation cohort. A score corresponding to a regression coefficient was assigned to each injury group. The disability predictive index for each patient was defined as the sum of the scores. The predictive performance of the index was validated using the receiver operating characteristic curve analysis in the validation cohort. The derivation cohort included 1,475,158 patients, while the validation cohort included 939,659 patients. Of the 939,659 patients, 235,382 (25.0%) were discharged with severe physical disability. The c-statistics of the disability predictive index was 0.795 (95% confidence interval [CI] 0.794-0.795), while that of a model using the disability predictive index and patient baseline characteristics was 0.856 (95% CI 0.855-0.857). Severe physical disability at discharge may be well predicted with patient age, sex, CCI score, and the diagnosis-based disability predictive index in patients admitted to hospitals with trauma. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validity of the Brazilian version of the Godin-Shephard Leisure-Time Physical Activity Questionnaire.

PubMed

João, Thaís Moreira São; Rodrigues, Roberta Cunha Matheus; Gallani, Maria Cecília Bueno Jayme; Miura, Cinthya Tamie Passos; Domingues, Gabriela de Barros Leite; Amireault, Steve; Godin, Gaston

2015-09-01

This study provides evidence of construct validity for the Brazilian version of the Godin-Shephard Leisure-Time Physical Activity Questionnaire (GSLTPAQ), a 1-item instrument used among 236 participants referred for cardiopulmonary exercise testing. The Baecke Habitual Physical Activity Questionnaire (Baecke-HPA) was used to evaluate convergent and divergent validity. The self-reported measure of walking (QCAF) evaluated the convergent validity. Cardiorespiratory fitness assessed convergent validity by the Veterans Specific Activity Questionnaire (VSAQ), peak measured (VO2peak) and maximum predicted (VO2pred) oxygen uptake. Partial adjusted correlation coefficients between the GSLTPAQ, Baecke-HPA, QCAF, VO2pred and VSAQ provided evidence for convergent validity; while divergent validity was supported by the absence of correlations between the GSLTPAQ and the Occupational Physical Activity domain (Baecke-HPA). The GSLTPAQ presents level 3 of evidence of construct validity and may be useful to assess leisure-time physical activity among patients with cardiovascular disease and healthy individuals.

Continuous Diffusion Model for Concentration Dependence of Nitroxide EPR Parameters in Normal and Supercooled Water.

PubMed

Merunka, Dalibor; Peric, Miroslav

2017-05-25

Electron paramagnetic resonance (EPR) spectra of radicals in solution depend on their relative motion, which modulates the Heisenberg spin exchange and dipole-dipole interactions between them. To gain information on radical diffusion from EPR spectra demands both reliable spectral fitting to find the concentration coefficients of EPR parameters and valid expressions between the concentration and diffusion coefficients. Here, we measured EPR spectra of the 14 N- and 15 N-labeled perdeuterated TEMPONE radicals in normal and supercooled water at various concentrations. By fitting the EPR spectra to the functions based on the modified Bloch equations, we obtained the concentration coefficients for the spin dephasing, coherence transfer, and hyperfine splitting parameters. Assuming the continuous diffusion model for radical motion, the diffusion coefficients of radicals were calculated from the concentration coefficients using the standard relations and the relations derived from the kinetic equations for the spin evolution of a radical pair. The latter relations give better agreement between the diffusion coefficients calculated from different concentration coefficients. The diffusion coefficients are similar for both radicals, which supports the presented method. They decrease with lowering temperature slower than is predicted by the Stokes-Einstein relation and slower than the rotational diffusion coefficients, which is similar to the diffusion of water molecules in supercooled water.

Prospective evaluation of a bivalirudin to warfarin transition nomogram.

PubMed

Hohlfelder, Benjamin; Sylvester, Katelyn W; Rimsans, Jessica; DeiCicchi, David; Connors, Jean M

2017-05-01

Bivalirudin may cause a falsely prolonged international normalized ratio (INR) that complicates the discontinuation of bivalirudin when used as a bridge to warfarin. To prospectively validate our novel bivalirudin to warfarin transition nomogram, adult patients who received bivalirudin as a bridge to warfarin between July 2015 and June 2016 were prospectively evaluated, utilizing our predictive nomogram. The major outcome of our analysis was the correlation between the predicted change in INR upon bivalirudin discontinuation based on the nomogram, and the actual change in INR upon bivalirudin discontinuation. The major outcome was analyzed using the Pearson's correlation test. A Pearson's correlation coefficient >0.6 was considered to be a strong correlation. Bivalirudin was used as a bridge to warfarin in 29 patients. The majority of patients (86%) included in the analysis had a ventricular assist device. The median initial bivalirudin rate was 0.07 mg/kg/h and the mean increase in INR when starting bivalirudin was 0.6. The mean final weight-based bivalirudin rate was 0.08 mg/kg/h and the mean change in INR after stopping bivalirudin was 0.7. The Pearson correlation coefficient between the predicted change in INR upon bivalirudin discontinuation and the actual change in INR upon bivalirudin discontinuation was 0.86 (p < 0.001). After bivalirudin discontinuation, 68% of patients had a therapeutic INR. The results of this prospective analysis successfully validated our novel bivalirudin to warfarin transition nomogram. There was a very strong correlation between the predicted change and actual change in INR upon bivalirudin discontinuation.

Validation of the DRAGON Score in a Chinese Population to Predict Functional Outcome of Intravenous Thrombolysis-Treated Stroke Patients.

PubMed

Zhang, Xinmiao; Liao, Xiaoling; Wang, Chunjuan; Liu, Liping; Wang, Chunxue; Zhao, Xingquan; Pan, Yuesong; Wang, Yilong; Wang, Yongjun

2015-08-01

The DRAGON score predicts functional outcome of ischemic stroke patients treated with intravenous thrombolysis. Our aim was to evaluate its utility in a Chinese stroke population. Patients with acute ischemic stroke treated with intravenous thrombolysis were prospectively registered in the Thrombolysis Implementation and Monitor of acute ischemic Stroke in China. We excluded patients with basilar artery occlusion and missing data, leaving 970 eligible patients. We calculated the DRAGON score, and the clinical outcome was measured by the modified Rankin Scale at 3 months. Model discrimination was quantified by calculating the C statistic. Calibration was assessed using Pearson correlation coefficient. The C statistic was .73 (.70-.76) for good outcome and .75 (.70-.79) for miserable outcome. Proportions of patients with good outcome were 94%, 83%, 70%, and 0% for 0 to 1, 2, 3, and 8 to 10 score points, respectively. Proportions of patients with miserable outcome were 0%, 3%, 9%, and 50% for 0 to 1, 2, 3, and 8 to 10 points, respectively. There was high correlation between predicted and observed probability of 3-month favorable and miserable outcome in the external validation cohort (Pearson correlation coefficient, .98 and .98, respectively, both P < .0001). The DRAGON score showed good performance to predict functional outcome after tissue-type plasminogen activator treatment in the Chinese population. This study demonstrated the accuracy and usability of the DRAGON score in the Chinese population in daily practice. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

The utility of the Edmonton Symptom Assessment System in screening for anxiety and depression.

PubMed

Bagha, S M; Macedo, A; Jacks, L M; Lo, C; Zimmermann, C; Rodin, G; Li, M

2013-01-01

The Edmonton Symptom Assessment System (ESAS) is a common screening tool in cancer, although its validity for distress screening is unproven. Here, screening performance of the ESAS anxiety (ESAS-A) and depression (ESAS-D) items were validated against the anxiety [Generalised Anxiety Disorder-7 (GAD-7)] and depression [Patient Health Questionnaire-9 (PHQ-9)] subscales of the PHQ. A total of 1215 cancer patients completed the Distress Assessment and Response Tool (DART), a computerised distress screening instrument. Spearman's rank correlation coefficients and receiver operating characteristic curve analyses were used to evaluate the ability of ESAS-A and ESAS-D to identify moderate distress (GAD-7/PHQ-9 ≥ 10). Spearman's rank correlation coefficients comparing ESAS-A and ESAS-D with GAD-7 and PHQ-9 were 0.74 and 0.72 respectively. Areas under the receiver operating characteristic curves were 0.89 and 0.88 for anxiety and depression respectively. A cut-off of ≥3 on ESAS-A demonstrated a sensitivity of 0.91, specificity of 0.68, positive predictive value of 0.34 and negative predictive value of 0.97. A cut-off of ≥2 on the ESAS-D demonstrated a sensitivity of 0.86, specificity of 0.72, positive predictive value of 0.46 and negative predictive value of 0.95. High sensitivities of ESAS-A and ESAS-D at certain cut-offs suggest they have use in ruling-out distress. However, their low specificities indicate secondary screening is needed to rule-in anxiety or depression for case-finding. © 2012 Blackwell Publishing Ltd.

External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China

PubMed Central

Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

2016-01-01

Background and Purpose A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. Methods The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson’s correlation coefficient. Results The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79–0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81–0.84). Excellent calibration was reported in the two models with Pearson’s correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008). Conclusions The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke. PMID:27846282

Validation of the Greek Version of the Fibromyalgia Rapid Screening Tool.

PubMed

Zis, Panagiotis; Brozou, Vassiliki; Stavropoulou, Evmorfia; Argyra, Erifilli; Siafaka, Ioanna; Kararizou, Evangelia; Bouhassira, Didier; Perrot, Serge; Zis, Vassileios; Vadalouca, Athina

2017-09-01

The Fibromyalgia Rapid Screening Tool (FiRST) is a brief, simple, and straightforward self-administered questionnaire that was developed by Perrot et al. for the detection of fibromyalgia syndrome in patients with diffuse chronic pain. The aim of our study was to develop and validate the Greek version of FiRST. The study was set up as a prospective observational study. The original French version of FiRST was adapted into Greek using forward and backward translation. Patients with chronic diffuse pain with a clinical diagnosis of fibromyalgia and osteoarthritis based on the criteria of the American College of Rheumatology were invited to participate to the study. Of the 101 patients who met our inclusion criteria, 42 were diagnosed with fibromyalgia and 59 with osteoarthritis. The 2 groups did not differ significantly regarding gender and pain characteristics (duration, intensity). Cronbach's alpha coefficient was 0.79. Receiver operating characteristic analysis showed an area under the curve of 89% (95% confidence interval = 83 to 95%; SE: 0.032, P < 0.001). At a cutoff score of ≥ 5, FiRST showed a sensitivity of 86%, a specificity of 83%, a positive predictive value of 78%, and a negative predictive value of 89%. The intraclass coefficient for the test-retest reliability was 0.96. The Greek version of FiRST is a valid screening tool for fibromyalgia in daily practice. © 2016 World Institute of Pain.

Validation of a 4-item Negative Symptom Assessment (NSA-4): a short, practical clinical tool for the assessment of negative symptoms in schizophrenia.

PubMed

Alphs, Larry; Morlock, Robert; Coon, Cheryl; Cazorla, Pilar; Szegedi, Armin; Panagides, John

2011-06-01

The 16-item Negative Symptom Assessment (NSA-16) scale is a validated tool for evaluating negative symptoms of schizophrenia. The psychometric properties and predictive power of a four-item version (NSA-4) were compared with the NSA-16. Baseline data from 561 patients with predominant negative symptoms of schizophrenia who participated in two identically designed clinical trials were evaluated. Ordered logistic regression analysis of ratings using NSA-4 and NSA-16 were compared with ratings using several other standard tools to determine predictive validity and construct validity. Internal consistency and test--retest reliability were also analyzed. NSA-16 and NSA-4 scores were both predictive of scores on the NSA global rating (odds ratio = 0.83-0.86) and the Clinical Global Impressions--Severity scale (odds ratio = 0.91-0.93). NSA-16 and NSA-4 showed high correlation with each other (Pearson r = 0.85), similar high correlation with other measures of negative symptoms (demonstrating convergent validity), and lesser correlations with measures of other forms of psychopathology (demonstrating divergent validity). NSA-16 and NSA-4 both showed acceptable internal consistency (Cronbach α, 0.85 and 0.64, respectively) and test--retest reliability (intraclass correlation coefficient, 0.87 and 0.82). This study demonstrates that NSA-4 offers accuracy comparable to the NSA-16 in rating negative symptoms in patients with schizophrenia. Copyright © 2011 John Wiley & Sons, Ltd.

Impact of rain gauge quality control and interpolation on streamflow simulation: an application to the Warwick catchment, Australia

NASA Astrophysics Data System (ADS)

Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.

2017-12-01

Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.

Impact of rain gauge quality control and interpolation on streamflow simulation: an application to the Warwick catchment, Australia

NASA Astrophysics Data System (ADS)

Liu, Shulun; Li, Yuan; Pauwels, Valentijn R. N.; Walker, Jeffrey P.

2018-01-01

Rain gauges are widely used to obtain temporally continuous point rainfall records, which are then interpolated into spatially continuous data to force hydrological models. However, rainfall measurements and interpolation procedure are subject to various uncertainties, which can be reduced by applying quality control and selecting appropriate spatial interpolation approaches. Consequently, the integrated impact of rainfall quality control and interpolation on streamflow simulation has attracted increased attention but not been fully addressed. This study applies a quality control procedure to the hourly rainfall measurements obtained in the Warwick catchment in eastern Australia. The grid-based daily precipitation from the Australian Water Availability Project was used as a reference. The Pearson correlation coefficient between the daily accumulation of gauged rainfall and the reference data was used to eliminate gauges with significant quality issues. The unrealistic outliers were censored based on a comparison between gauged rainfall and the reference. Four interpolation methods, including the inverse distance weighting (IDW), nearest neighbors (NN), linear spline (LN), and ordinary Kriging (OK), were implemented. The four methods were firstly assessed through a cross-validation using the quality-controlled rainfall data. The impacts of the quality control and interpolation on streamflow simulation were then evaluated through a semi-distributed hydrological model. The results showed that the Nash–Sutcliffe model efficiency coefficient (NSE) and Bias of the streamflow simulations were significantly improved after quality control. In the cross-validation, the IDW and OK methods resulted in good interpolation rainfall, while the NN led to the worst result. In term of the impact on hydrological prediction, the IDW led to the most consistent streamflow predictions with the observations, according to the validation at five streamflow-gauged locations. The OK method performed second best according to streamflow predictions at the five gauges in the calibration period (01/01/2007–31/12/2011) and four gauges during the validation period (01/01/2012–30/06/2014). However, NN produced the worst prediction at the outlet of the catchment in the validation period, indicating a low robustness. While the IDW exhibited the best performance in the study catchment in terms of accuracy, robustness and efficiency, more general recommendations on the selection of rainfall interpolation methods need to be further explored.

Pitfalls in Prediction Modeling for Normal Tissue Toxicity in Radiation Therapy: An Illustration With the Individual Radiation Sensitivity and Mammary Carcinoma Risk Factor Investigation Cohorts

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

Mbah, Chamberlain, E-mail: chamberlain.mbah@ugent.be; Department of Mathematical Modeling, Statistics, and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent; Thierens, Hubert

Purpose: To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate. Methods and Materials: Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) (n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia. The LASSO (least absolute shrinkage and selection operator) logistic regression method was used to build a predictive model for a dichotomized endpoint (Radiation Therapy Oncology Group/European Organization for the Research and Treatment of Cancer score 0, 1, or ≥2). Internal areas undermore » the receiver operating characteristic curve (inAUCs) were calculated by a naïve approach whereby the training data (ISE) were also used for calculating the AUC. Cross-validation was also applied to calculate the AUC within the same cohort, a second type of inAUC. Internal AUCs from cross-validation were calculated within ISE and MARIE separately. Models trained on one dataset (ISE) were applied to a test dataset (MARIE) and AUCs calculated (exAUCs). Results: Internal AUCs from the naïve approach were generally larger than inAUCs from cross-validation owing to overfitting the training data. Internal AUCs from cross-validation were also generally larger than the exAUCs, reflecting heterogeneity in the predictors between cohorts. The best models with largest inAUCs from cross-validation within both cohorts had a number of common predictors: hypertension, normalized total boost, and presence of estrogen receptors. Surprisingly, the effect (coefficient in the prediction model) of hypertension on telangiectasia incidence was positive in ISE and negative in MARIE. Other predictors were also not common between the 2 cohorts, illustrating that overcoming overfitting does not solve the problem of replication failure of prediction models completely. Conclusions: Overfitting and cohort heterogeneity are the 2 main causes of replication failure of prediction models across cohorts. Cross-validation and similar techniques (eg, bootstrapping) cope with overfitting, but the development of validated predictive models for radiation therapy toxicity requires strategies that deal with cohort heterogeneity.« less

Growth of finiteness in the third year of life: replication and predictive validity.

PubMed

Hadley, Pamela A; Rispoli, Matthew; Holt, Janet K; Fitzgerald, Colleen; Bahnsen, Alison

2014-06-01

The authors of this study investigated the validity of tense and agreement productivity (TAP) scoring in diverse sentence frames obtained during conversational language sampling as an alternative measure of finiteness for use with young children. Longitudinal language samples were used to model TAP growth from 21 to 30 months of age for 37 typically developing toddlers. Empirical Bayes (EB) linear and quadratic growth coefficients and child sex were then used to predict elicited grammar composite scores on the Test of Early Grammatical Impairment (TEGI; Rice & Wexler, 2001) at 36 months. A random-effects quadratic model with no intercept best characterized TAP growth, replicating the findings of Rispoli, Hadley, and Holt (2009). The combined regression model was significant, with the 3 variables accounting for 55.5% of the variance in the TEGI composite scores. These findings establish TAP growth as a valid metric of finiteness in the 3rd year of life. Developmental and theoretical implications are discussed.

Neonatal intensive care unit: predictive models for length of stay.

PubMed

Bender, G J; Koestler, D; Ombao, H; McCourt, M; Alskinis, B; Rubin, L P; Padbury, J F

2013-02-01

Hospital length of stay (LOS) is important to administrators and families of neonates admitted to the neonatal intensive care unit (NICU). A prediction model for NICU LOS was developed using predictors birth weight, gestational age and two severity of illness tools, the score for neonatal acute physiology, perinatal extension (SNAPPE) and the morbidity assessment index for newborns (MAIN). Consecutive admissions (n=293) to a New England regional level III NICU were retrospectively collected. Multiple predictive models were compared for complexity and goodness-of-fit, coefficient of determination (R (2)) and predictive error. The optimal model was validated prospectively with consecutive admissions (n=615). Observed and expected LOS was compared. The MAIN models had best Akaike's information criterion, highest R (2) (0.786) and lowest predictive error. The best SNAPPE model underestimated LOS, with substantial variability, yet was fairly well calibrated by birthweight category. LOS was longer in the prospective cohort than the retrospective cohort, without differences in birth weight, gestational age, MAIN or SNAPPE. LOS prediction is improved by accounting for severity of illness in the first week of life, beyond factors known at birth. Prospective validation of both MAIN and SNAPPE models is warranted.

Wheelchair Shuttle Test for Assessing Aerobic Fitness in Youth With Spina Bifida: Validity and Reliability

PubMed Central

de Groot, Janke F.; Backx, Frank J.G.; Benner, Joyce; Kruitwagen, Cas L.J.J.; Takken, Tim

2017-01-01

Abstract Background Testing aerobic fitness in youth is important because of expected relationships with health. Objective The purpose of the study was to estimate the validity and reliability of the Shuttle Ride Test in youth who have spina bifida and use a wheelchair for mobility and sport. Design Ths study is a validity and reliability study. Methods The Shuttle Ride Test, Graded Wheelchair Propulsion Test, and skill-related fitness tests were administered to 33 participants for the validity study (age = 14.5 ± 3.1 y) and to 28 participants for the reliability study (age = 14.7 ± 3.3 y). Results No significant differences were found between the Graded Wheelchair Propulsion Test and the Shuttle Ride Test for most cardiorespiratory responses. Correlations between the Graded Wheelchair Propulsion Test and the Shuttle Ride Test were moderate to high (r = .55–.97). The variance in peak oxygen uptake (VO2peak) could be predicted for 77% of the participants by height, number of shuttles completed, and weight, with large prediction intervals. High correlations were found between number of shuttles completed and skill-related fitness tests (CI = .73 to −.92). Intraclass correlation coefficients were high (.77–.98), with a smallest detectable change of 1.5 for number of shuttles completed and with coefficients of variation of 6.2% and 6.4% for absolute VO2peak and relative VO2peak, respectively. Conclusions When measuring VO2peak directly by using a mobile gas analysis system, the Shuttle Ride Test is highly valid for testing VO2peak in youth who have spina bifida and use a wheelchair for mobility and sport. The outcome measure of number of shuttles represents aerobic fitness and is also highly correlated with both anaerobic performance and agility. It is not possible to predict VO2peak accurately by using the number of shuttles completed. Moreover, the Shuttle Ride Test is highly reliable in youth with spina bifida, with a good smallest detectable change for the number of shuttles completed. PMID:29029556

Validation of the new code package APOLLO2.8 for accurate PWR neutronics calculations

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

Santamarina, A.; Bernard, D.; Blaise, P.

2013-07-01

This paper summarizes the Qualification work performed to demonstrate the accuracy of the new APOLLO2.S/SHEM-MOC package based on JEFF3.1.1 nuclear data file for the prediction of PWR neutronics parameters. This experimental validation is based on PWR mock-up critical experiments performed in the EOLE/MINERVE zero-power reactors and on P.I. Es on spent fuel assemblies from the French PWRs. The Calculation-Experiment comparison for the main design parameters is presented: reactivity of UOX and MOX lattices, depletion calculation and fuel inventory, reactivity loss with burnup, pin-by-pin power maps, Doppler coefficient, Moderator Temperature Coefficient, Void coefficient, UO{sub 2}-Gd{sub 2}O{sub 3} poisoning worth, Efficiency ofmore » Ag-In-Cd and B4C control rods, Reflector Saving for both standard 2-cm baffle and GEN3 advanced thick SS reflector. From this qualification process, calculation biases and associated uncertainties are derived. This code package APOLLO2.8 is already implemented in the ARCADIA new AREVA calculation chain for core physics and is currently under implementation in the future neutronics package of the French utility Electricite de France. (authors)« less

A predictive bone drilling force model for haptic rendering with experimental validation using fresh cadaveric bone.

PubMed

Lin, Yanping; Chen, Huajiang; Yu, Dedong; Zhang, Ying; Yuan, Wen

2017-01-01

Bone drilling simulators with virtual and haptic feedback provide a safe, cost-effective and repeatable alternative to traditional surgical training methods. To develop such a simulator, accurate haptic rendering based on a force model is required to feedback bone drilling forces based on user input. Current predictive bone drilling force models based on bovine bones with various drilling conditions and parameters are not representative of the bone drilling process in bone surgery. The objective of this study was to provide a bone drilling force model for haptic rendering based on calibration and validation experiments in fresh cadaveric bones with different bone densities. Using a commonly used drill bit geometry (2 mm diameter), feed rates (20-60 mm/min) and spindle speeds (4000-6000 rpm) in orthognathic surgeries, the bone drilling forces of specimens from two groups were measured and the calibration coefficients of the specific normal and frictional pressures were determined. The comparison of the predicted forces and the measured forces from validation experiments with a large range of feed rates and spindle speeds demonstrates that the proposed bone drilling forces can predict the trends and average forces well. The presented bone drilling force model can be used for haptic rendering in surgical simulators.

A Comparison of the Fagerström Test for Cigarette Dependence and Cigarette Dependence Scale in a Treatment-Seeking Sample of Pregnant Smokers

PubMed Central

Singleton, Edward G.; Heishman, Stephen J.

2016-01-01

Introduction: Valid and reliable brief measures of cigarette dependence are essential for research purposes and effective clinical care. Two widely-used brief measures of cigarette dependence are the six-item Fagerström Test for Cigarette Dependence (FTCD) and five-item Cigarette Dependence Scale (CDS-5). Their respective metric characteristics among pregnant smokers have not yet been studied. Methods: This was a secondary analysis of data of pregnant smokers (N = 476) enrolled in a smoking cessation study. We assessed internal consistency, reliability, and examined correlations between the instruments and smoking-related behaviors for construct validity. We evaluated predictive validity by testing how well the measures predict abstinence 2 weeks after quit date. Results: Cronbach’s alpha coefficient for the CDS-5 was 0.62 and for the FTCD 0.55. Measures were strongly correlated with each other, although FTCD, but not CDS-5, was associated with saliva cotinine concentration. The FTCD, CDS-5, craving to smoke, and withdrawal symptoms failed to predict smoking status 2 weeks following the quit date. Conclusions: Suboptimal reliability estimates and failure to predict short-term smoking call into question the value of including either of the brief measures in studies that aim to explain the obstacles to smoking cessation during pregnancy. PMID:25995159

Validation of Field Methods to Assess Body Fat Percentage in Elite Youth Soccer Players.

PubMed

Munguia-Izquierdo, Diego; Suarez-Arrones, Luis; Di Salvo, Valter; Paredes-Hernandez, Victor; Alcazar, Julian; Ara, Ignacio; Kreider, Richard; Mendez-Villanueva, Alberto

2018-05-01

This study determined the most effective field method for quantifying body fat percentage in male elite youth soccer players and developed prediction equations based on anthropometric variables. Forty-four male elite-standard youth soccer players aged 16.3-18.0 years underwent body fat percentage assessments, including bioelectrical impedance analysis and the calculation of various skinfold-based prediction equations. Dual X-ray absorptiometry provided a criterion measure of body fat percentage. Correlation coefficients, bias, limits of agreement, and differences were used as validity measures, and regression analyses were used to develop soccer-specific prediction equations. The equations from Sarria et al. (1998) and Durnin & Rahaman (1967) reached very large correlations and the lowest biases, and they reached neither the practically worthwhile difference nor the substantial difference between methods. The new youth soccer-specific skinfold equation included a combination of triceps and supraspinale skinfolds. None of the practical methods compared in this study are adequate for estimating body fat percentage in male elite youth soccer players, except for the equations from Sarria et al. (1998) and Durnin & Rahaman (1967). The new youth soccer-specific equation calculated in this investigation is the only field method specifically developed and validated in elite male players, and it shows potentially good predictive power. © Georg Thieme Verlag KG Stuttgart · New York.

Design and Performance Calculations of a Propeller for Very High Altitude Flight. Degree awarded by Case Western Univ.

NASA Technical Reports Server (NTRS)

Koch, L. Danielle

1998-01-01

Reported here is a design study of a propeller for a vehicle capable of subsonic flight in Earth's stratosphere. All propellers presented were required to absorb 63.4 kW (85 hp) at 25.9 km (85,000 ft) while aircraft cruise velocity was maintained at Mach 0.40. To produce the final design, classic momentum and blade-element theories were combined with two and three-dimensional results from the Advanced Ducted Propfan Analysis Code (ADPAC), a numerical Navier-Stokes analysis code. The Eppler 387 airfoil was used for each of the constant section propeller designs compared. Experimental data from the Langley Low-Turbulence Pressure Tunnel was used in the strip theory design and analysis programs written. The experimental data was also used to validate ADPAC at a Reynolds numbers of 60,000 and a Mach number of 0.20. Experimental and calculated surface pressure coefficients are compared for a range of angles of attack. Since low Reynolds number transonic experimental data was unavailable, ADPAC was used to generate two-dimensional section performance predictions for Reynolds numbers of 60,000 and 100,000 and Mach numbers ranging from 0.45 to 0.75. Surface pressure coefficients are presented for selected angles of attack. in addition to the variation of lift and drag coefficients at each flow condition. A three-dimensional model of the final design was made which ADPAC used to calculated propeller performance. ADPAC performance predictions were compared with strip-theory calculations at design point. Propeller efficiency predicted by ADPAC was within 1.5% of that calculated by strip theory methods, although ADPAC predictions of thrust, power, and torque coefficients were approximately 5% lower than the strip theory results. Simplifying assumptions made in the strip theory account for the differences seen.

Translation and validation of the Persian version of the functional assessment of chronic illness therapy-Spiritual well-being scale (FACIT-Sp) among Muslim Iranians in treatment for cancer.

PubMed

Jafari, Najmeh; Zamani, Ahmadreza; Lazenby, Mark; Farajzadegan, Ziba; Emami, Hamid; Loghmani, Amir

2013-02-01

The Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being (FACIT-Sp) scale is a valid and reliable instrument to provide an inclusive measure of spirituality in research and clinical practice. The aim of this study was to translate and investigate the reliability and validity of the Persian version of the FACIT-Sp. The 12 item spiritual well-being subscale of the FACIT-Sp Version 4 was translated into the Persian language, Farsi, using the FACIT translation methodology. The questionnaire was administered to a diverse sample of 153 patients in treatment for cancer. Internal consistency was assessed by Cronbach's α coefficient, confirmatory factor analysis (CFA) was applied to assess construct validity, and regression analysis was used to assess the predictor role of the FACIT-Sp in health-related quality of life (HRQOL). Cronbach's α reliability coefficient for the FACIT-Sp subscales ranged from 0.72 to 0.90. The CFA generally replicated the original conceptualization of the three subscales of the FACIT-Sp12 (Peace, Meaning, and Faith). All three subscales significant predicted HRQOL. The Persian version of the FACIT-Sp scale is a reliable and valid tool for the clinical assessment of, and research into, the spiritual well-being of Muslim Iranian and Farsi-speaking patients in other regions of the world who are in treatment for cancer.

The Dutch motor skills assessment as tool for talent development in table tennis: a reproducibility and validity study.

PubMed

Faber, Irene R; Nijhuis-Van Der Sanden, Maria W G; Elferink-Gemser, Marije T; Oosterveld, Frits G J

2015-01-01

A motor skills assessment could be helpful in talent development by estimating essential perceptuo-motor skills of young players, which are considered requisite to develop excellent technical and tactical qualities. The Netherlands Table Tennis Association uses a motor skills assessment in their talent development programme consisting of eight items measuring perceptuo-motor skills specific to table tennis under varying conditions. This study aimed to investigate this assessment regarding its reproducibility, internal consistency, underlying dimensions and concurrent validity in 113 young table tennis players (6-10 years). Intraclass correlation coefficients of six test items met the criteria of 0.7 with coefficients of variation between 3% and 8%. Cronbach's alpha valued 0.853 for internal consistency. The principal components analysis distinguished two conceptually meaningful factors: "ball control" and "gross motor function." Concurrent validity analyses demonstrated moderate associations between the motor skills assessment's results and national ranking; boys r = -0.53 (P < 0.001) and girls r = -0.45 (P = 0.015). In conclusion, this evaluation demonstrated six test items with acceptable reproducibility, good internal consistency and good prospects for validity. Two test items need revision to upgrade reproducibility. Since the motor skills assessment seems to be a reproducible, objective part of a talent development programme, more longitudinal studies are required to investigate its predictive validity.

Alberta infant motor scale: reliability and validity when used on preterm infants in Taiwan.

PubMed

Jeng, S F; Yau, K I; Chen, L C; Hsiao, S F

2000-02-01

The goal of this study was to examine the reliability and validity of measurements obtained with the Alberta Infant Motor Scale (AIMS) for evaluation of preterm infants in Taiwan. Two independent groups of preterm infants were used to investigate the reliability (n=45) and validity (n=41) for the AIMS. In the reliability study, the AIMS was administered to the infants by a physical therapist, and infant performance was videotaped. The performance was then rescored by the same therapist and by 2 other therapists to examine the intrarater and interrater reliability. In the validity study, the AIMS and the Bayley Motor Scale were administered to the infants at 6 and 12 months of age to examine criterion-related validity. Intraclass correlation coefficients (ICCs) for intrarater and interrater reliability of measurements obtained with the AIMS were high (ICC=.97-.99). The AIMS scores correlated with the Bayley Motor Scale scores at 6 and 12 months (r=.78 and.90), although the AIMS scores at 6 months were only moderately predictive of the motor function at 12 months (r=.56). The results suggest that measurements obtained with the AIMS have acceptable reliability and concurrent validity but limited predictive value for evaluating preterm Taiwanese infants.

ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches.

PubMed

Sharma, Ashok K; Srivastava, Gopal N; Roy, Ankita; Sharma, Vineet K

2017-01-01

The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93%) and Matthews's correlation coefficient (0.84). The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84-0.87) on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better ( R 2 = 0.84) than the multi-linear regression (MLR) and partial least square regression (PLSR) models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2) performed better ( R 2 = 0.68) in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity, solubility, and permeability of small molecules.

ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches

PubMed Central

Sharma, Ashok K.; Srivastava, Gopal N.; Roy, Ankita; Sharma, Vineet K.

2017-01-01

The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93%) and Matthews's correlation coefficient (0.84). The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84–0.87) on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better (R2 = 0.84) than the multi-linear regression (MLR) and partial least square regression (PLSR) models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2) performed better (R2 = 0.68) in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity, solubility, and permeability of small molecules. PMID:29249969

A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score

PubMed Central

Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars

2018-01-01

Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359

[VALIDATION OF PREDICTIVE EQUATIONS FOR WEIGHT AND HEIGHT USING BODY CIRCUMFERENCES IN MEXICAN ELDERLYS].

PubMed

Osuna-Padilla, Iván Armando; Borja-Magno, Angélica Irais; Leal-Escobar, Gabriela; Verdugo-Hernández, Sonia

2015-12-01

weight and height measurements are important data for the nutritional assessment of elderly people and the implementation of the nutritional care process. Malnutrition is common in this population, who has high rates of disability that difficult to measurement this variables. evaluate the validity of predictive equations for weight and height that include body circumferences created for brazilian population, in mexican elderly people. this is a comparative, observational, prospective and cross-sectional study, 61 elderly were evaluated. Body weight, height, half span, calf, arm and abdominal circumferences were determinated. Weight and height were estimated with de predictive equations published by Rabito et al. Bland-Altman analysis and Intraclass Correlation Coefficient were used to assess the levels of agreement between the estimated and the measured values. The level of statistical significance was p < 0.05. the age mean was 78.7 ± 8.7 and 55.7% were females. The weight mean was 61.9 ± 14.1 kg, height mean was 155.4 ± 9.5 cm and Body Mass Index (BMI) mean corresponded to 25.5 ± 5.1 kg/m. The Bland-Altman plots indicated that the 95% confidence interval (95% IC) limits for the difference between real and estimated weight ranged from -14.3 kg to 8.1 kg, the mean of the difference or systematic error (SE) was -3.1 kg, we observed an statistically significant coefficient of 0.12 (p < 0.03). The 95% IC limits for the difference between real and estimated height ranged from -11.1 to 15.9 cm, the diffe rence mean or SE of 2.4 cm, we observed a coefficient of -0.04 (p = 0.67) . Intraclass Correlation Coefficient of 0.72 (p < 0.00) and 0.88 (p < 0.00) were obtained for weight and height, respectively. the equations developed by Rabito showed a good agreement when compared with the actual weight and height of elderly people. We observed variations in the estimated weight in obesity elderlys. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Non-destructive and fast identification of cotton-polyester blend fabrics by the portable near-infrared spectrometer.

PubMed

Li, Wen-xia; Li, Feng; Zhao, Guo-liang; Tang, Shi-jun; Liu, Xiao-ying

2014-12-01

A series of 376 cotton-polyester (PET) blend fabrics were studied by a portable near-infrared (NIR) spectrometer. A NIR semi-quantitative-qualitative calibration model was established by Partial Least Squares (PLS) method combined with qualitative identification coefficient. In this process, PLS method in a quantitative analysis was used as a correction method, and the qualitative identification coefficient was set by the content of cotton and polyester in blend fabrics. Cotton-polyester blend fabrics were identified qualitatively by the model and their relative contents were obtained quantitatively, the model can be used for semi-quantitative identification analysis. In the course of establishing the model, the noise and baseline drift of the spectra were eliminated by Savitzky-Golay(S-G) derivative. The influence of waveband selection and different pre-processing method was also studied in the qualitative calibration model. The major absorption bands of 100% cotton samples were in the 1400~1600 nm region, and the one for 100% polyester were around 1600~1800 nm, the absorption intensity was enhancing with the content increasing of cotton or polyester. Therefore, the cotton-polyester's major absorption region was selected as the base waveband, the optimal waveband (1100~2500 nm) was found by expanding the waveband in two directions (the correlation coefficient was 0.6, and wave-point number was 934). The validation samples were predicted by the calibration model, the results showed that the model evaluation parameters was optimum in the 1100~2500 nm region, and the combination of S-G derivative, multiplicative scatter correction (MSC) and mean centering was used as the pre-processing method. RC (relational coefficient of calibration) value was 0.978, RP (relational coefficient of prediction) value was 0.940, SEC (standard error of calibration) value was 1.264, SEP (standard error of prediction) value was 1.590, and the sample's recognition accuracy was up to 93.4%. It showed that the cotton-polyester blend fabrics could be predicted by the semi-quantitative-qualitative calibration model.

The predictive validity of the MCAT for medical school performance and medical board licensing examinations: a meta-analysis of the published research.

PubMed

Donnon, Tyrone; Paolucci, Elizabeth Oddone; Violato, Claudio

2007-01-01

To conduct a meta-analysis of published studies to determine the predictive validity of the MCAT on medical school performance and medical board licensing examinations. The authors included all peer-reviewed published studies reporting empirical data on the relationship between MCAT scores and medical school performance or medical board licensing exam measures. Moderator variables, participant characteristics, and medical school performance/medical board licensing exam measures were extracted and reviewed separately by three reviewers using a standardized protocol. Medical school performance measures from 11 studies and medical board licensing examinations from 18 studies, for a total of 23 studies, were selected. A random-effects model meta-analysis of weighted effects sizes (r) resulted in (1) a predictive validity coefficient for the MCAT in the preclinical years of r = 0.39 (95% confidence interval [CI], 0.21-0.54) and on the USMLE Step 1 of r = 0.60 (95% CI, 0.50-0.67); and (2) the biological sciences subtest as the best predictor of medical school performance in the preclinical years (r = 0.32 95% CI, 0.21-0.42) and on the USMLE Step 1 (r = 0.48 95% CI, 0.41-0.54). The predictive validity of the MCAT ranges from small to medium for both medical school performance and medical board licensing exam measures. The medical profession is challenged to develop screening and selection criteria with improved validity that can supplement the MCAT as an important criterion for admission to medical schools.

Recognition of Atypical Symptoms of Acute Myocardial Infarction: Development and Validation of a Risk Scoring System.

PubMed

Li, Polly W C; Yu, Doris S F

Atypical symptom presentation in patients with acute myocardial infarction (AMI) is associated with longer delay in care seeking and poorer prognosis. Symptom recognition in these patients is a challenging task. Our purpose in this risk prediction model development study was to develop and validate a risk scoring system for estimating cumulative risk for atypical AMI presentation. A consecutive sample was recruited for the developmental (n = 300) and validation (n = 97) cohorts. Symptom experience was measured with the validated Chinese version of the Symptoms of Acute Coronary Syndromes Inventory. Potential predictors were identified from the literature. Multivariable logistic regression was performed to identify significant predictors. A risk scoring system was then constructed by assigning weights to each significant predictor according to their b coefficients. Five independent predictors for atypical symptom presentation were older age (≥75 years), female gender, diabetes mellitus, history of AMI, and absence of hyperlipidemia. The Hosmer and Lemeshow test (χ6 = 4.47, P = .62) indicated that this predictive model was adequate to predict the outcome. Acceptable discrimination was demonstrated, with area under the receiver operating characteristic curve as 0.74 (95% confidence interval, 0.67-0.82) (P < .001). The predictive power of this risk scoring system was confirmed in the validation cohort. Atypical AMI presentation is common. A simple risk scoring system developed on the basis of the 5 identified predictors can raise awareness of atypical AMI presentation and promote symptom recognition by estimating the cumulative risk for an individual to present with atypical AMI symptoms.

Development and Validation of a Weather-Based Model for Predicting Infection of Loquat Fruit by Fusicladium eriobotryae

PubMed Central

González-Domínguez, Elisa; Armengol, Josep; Rossi, Vittorio

2014-01-01

A mechanistic, dynamic model was developed to predict infection of loquat fruit by conidia of Fusicladium eriobotryae, the causal agent of loquat scab. The model simulates scab infection periods and their severity through the sub-processes of spore dispersal, infection, and latency (i.e., the state variables); change from one state to the following one depends on environmental conditions and on processes described by mathematical equations. Equations were developed using published data on F. eriobotryae mycelium growth, conidial germination, infection, and conidial dispersion pattern. The model was then validated by comparing model output with three independent data sets. The model accurately predicts the occurrence and severity of infection periods as well as the progress of loquat scab incidence on fruit (with concordance correlation coefficients >0.95). Model output agreed with expert assessment of the disease severity in seven loquat-growing seasons. Use of the model for scheduling fungicide applications in loquat orchards may help optimise scab management and reduce fungicide applications. PMID:25233340

Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroid receptors β

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

Li, Xiaolin; Ye, Li; Wang, Xiaoxiang

2012-12-15

Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q{sup 2}) was 0.571 andmore » non-cross-validation correlation coefficient (r{sup 2}) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results. -- Highlights: ► The thyroid hormone activities of HO-PBDEs were studied by 3D-QSAR. ► The binding modes between HO-PBDEs and TRβ were explored. ► 3D-QSAR, molecular docking, and molecular dynamics (MD) methods were performed.« less

Assessing the accuracy of predictive models for numerical data: Not r nor r2, why not? Then what?

PubMed Central

2017-01-01

Assessing the accuracy of predictive models is critical because predictive models have been increasingly used across various disciplines and predictive accuracy determines the quality of resultant predictions. Pearson product-moment correlation coefficient (r) and the coefficient of determination (r2) are among the most widely used measures for assessing predictive models for numerical data, although they are argued to be biased, insufficient and misleading. In this study, geometrical graphs were used to illustrate what were used in the calculation of r and r2 and simulations were used to demonstrate the behaviour of r and r2 and to compare three accuracy measures under various scenarios. Relevant confusions about r and r2, has been clarified. The calculation of r and r2 is not based on the differences between the predicted and observed values. The existing error measures suffer various limitations and are unable to tell the accuracy. Variance explained by predictive models based on cross-validation (VEcv) is free of these limitations and is a reliable accuracy measure. Legates and McCabe’s efficiency (E1) is also an alternative accuracy measure. The r and r2 do not measure the accuracy and are incorrect accuracy measures. The existing error measures suffer limitations. VEcv and E1 are recommended for assessing the accuracy. The applications of these accuracy measures would encourage accuracy-improved predictive models to be developed to generate predictions for evidence-informed decision-making. PMID:28837692

The establishment and external validation of NIR qualitative analysis model for waste polyester-cotton blend fabrics.

PubMed

Li, Feng; Li, Wen-Xia; Zhao, Guo-Liang; Tang, Shi-Jun; Li, Xue-Jiao; Wu, Hong-Mei

2014-10-01

A series of 354 polyester-cotton blend fabrics were studied by the near-infrared spectra (NIRS) technology, and a NIR qualitative analysis model for different spectral characteristics was established by partial least squares (PLS) method combined with qualitative identification coefficient. There were two types of spectrum for dying polyester-cotton blend fabrics: normal spectrum and slash spectrum. The slash spectrum loses its spectral characteristics, which are effected by the samples' dyes, pigments, matting agents and other chemical additives. It was in low recognition rate when the model was established by the total sample set, so the samples were divided into two types of sets: normal spectrum sample set and slash spectrum sample set, and two NIR qualitative analysis models were established respectively. After the of models were established the model's spectral region, pretreatment methods and factors were optimized based on the validation results, and the robustness and reliability of the model can be improved lately. The results showed that the model recognition rate was improved greatly when they were established respectively, the recognition rate reached up to 99% when the two models were verified by the internal validation. RC (relation coefficient of calibration) values of the normal spectrum model and slash spectrum model were 0.991 and 0.991 respectively, RP (relation coefficient of prediction) values of them were 0.983 and 0.984 respectively, SEC (standard error of calibration) values of them were 0.887 and 0.453 respectively, SEP (standard error of prediction) values of them were 1.131 and 0.573 respectively. A series of 150 bounds samples reached used to verify the normal spectrum model and slash spectrum model and the recognition rate reached up to 91.33% and 88.00% respectively. It showed that the NIR qualitative analysis model can be used for identification in the recycle site for the polyester-cotton blend fabrics.

Development and validation of two equations based on anthropometry, estimating body fat for the Greek adult population.

PubMed

Kanellakis, Spyridon; Skoufas, Efstathios; Khudokonenko, Vladlena; Apostolidou, Eftychia; Gerakiti, Loukia; Andrioti, Maria-Chrysi; Bountouvi, Evangelia; Manios, Yannis

2017-02-01

To validate anthropometric equations in the current literature predicting body fat percentage (%BF) in the Greek population, to develop and validate two anthropometric equations estimating %BF, and to compare them with the retrieved equations. Anthropometric data from 642 Greek adults were incorporated. Dual-energy X-ray absorptiometry was used as reference method. The comparison with other equations was made using Bland-Altman analysis, intraclass correlation coefficient, and Lin's concordance correlation coefficient. Nine of the thirty-one retrieved equations had no statistically significant bias. However, all of them had wide limits of agreement (±8.3 to ±16%BF). The equations accrued were: BF% = -0.615-10.948 × sex + 0.321 × waist circumference + 0.502 × hips circumference-0.39 × forearm circumference - 19.768 × height (m) and BF% = -27.787-5.515 × sex-8.419 × height + 0.145 × waist circumference + 0.270 × hips circumference + 7.509 × log of thigh skinfold + 20.090 × log of sum of skinfolds (bicep + tricep + suprailiac + subscapular)-0.445 × forearm circumference. Bland-Altman's reliability analysis showed no significant bias of -0.058 and -0.148%BF and limits of agreement ±8.100 and ±6.056%BF; the intraclass correlation coefficient was 0.955 and 0.976; and Lin's concordance correlation coefficient was 0.914 and 0.951, respectively. Literature equations performed moderately on this study's population. Therefore, two equations were designed and validated. The first one was simple and easily applicable, with measures obtained from a measuring tape, and the second one more complicated yet more accurate and reliable. Both were found to be reliable for the assessment of body composition in the Greek population. © 2017 The Obesity Society.

Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation

DOE PAGES

Liu, Jinlong; Szybist, James; Dumitrescu, Cosmin

2018-04-03

3D CFD spark-ignition IC engine simulations are extremely complex for the regular user. Truly-predictive CFD simulations for the turbulent flame combustion that solve fully coupled transport/chemistry equations may require large computational capabilities unavailable to regular CFD users. A solution is to use a simpler phenomenological model such as the G-equation that decouples transport/chemistry result. Such simulation can still provide acceptable and faster results at the expense of predictive capabilities. While the G-equation is well understood within the experienced modeling community, the goal of this paper is to document some of them for a novice or less experienced CFD user whomore » may not be aware that phenomenological models of turbulent flame combustion usually require heavy tuning and calibration from the user to mimic experimental observations. This study used ANSYS® Forte, Version 17.2, and the built-in G-equation model, to investigate two tuning constants that influence flame propagation in 3D CFD SI engine simulations: the stretch factor coefficient, Cms and the flame development coefficient, Cm2. After identifying several Cm2-Cms pairs that matched experimental data at one operating conditions, simulation results showed that engine models that used different Cm2-Cms sets predicted similar combustion performance, when the spark timing, engine load, and engine speed were changed from the operating condition used to validate the CFD simulation. A dramatic shift was observed when engine speed was doubled, which suggested that the flame stretch coefficient, Cms, had a much larger influence at higher engine speeds compared to the flame development coefficient, Cm2. Therefore, the Cm2-Cms sets that predicted a higher turbulent flame under higher in-cylinder pressure and temperature increased the peak pressure and efficiency. This suggest that the choice of the Cm2-Cms will affect the G-equation-based simulation accuracy when engine speed increases from the one used to validate the model. As a result, for the less-experienced CFD user and in the absence of enough experimental data that would help retune the tuning parameters at various operating conditions, the purpose of a good G-equation-based 3D engine simulation is to guide and/or complement experimental investigations, not the other way around. Only a truly-predictive simulation that fully couples the turbulence/chemistry equations can help reduce the amount of experimental work.« less

Choice of Tuning Parameters on 3D IC Engine Simulations Using G-Equation

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

Liu, Jinlong; Szybist, James; Dumitrescu, Cosmin

3D CFD spark-ignition IC engine simulations are extremely complex for the regular user. Truly-predictive CFD simulations for the turbulent flame combustion that solve fully coupled transport/chemistry equations may require large computational capabilities unavailable to regular CFD users. A solution is to use a simpler phenomenological model such as the G-equation that decouples transport/chemistry result. Such simulation can still provide acceptable and faster results at the expense of predictive capabilities. While the G-equation is well understood within the experienced modeling community, the goal of this paper is to document some of them for a novice or less experienced CFD user whomore » may not be aware that phenomenological models of turbulent flame combustion usually require heavy tuning and calibration from the user to mimic experimental observations. This study used ANSYS® Forte, Version 17.2, and the built-in G-equation model, to investigate two tuning constants that influence flame propagation in 3D CFD SI engine simulations: the stretch factor coefficient, Cms and the flame development coefficient, Cm2. After identifying several Cm2-Cms pairs that matched experimental data at one operating conditions, simulation results showed that engine models that used different Cm2-Cms sets predicted similar combustion performance, when the spark timing, engine load, and engine speed were changed from the operating condition used to validate the CFD simulation. A dramatic shift was observed when engine speed was doubled, which suggested that the flame stretch coefficient, Cms, had a much larger influence at higher engine speeds compared to the flame development coefficient, Cm2. Therefore, the Cm2-Cms sets that predicted a higher turbulent flame under higher in-cylinder pressure and temperature increased the peak pressure and efficiency. This suggest that the choice of the Cm2-Cms will affect the G-equation-based simulation accuracy when engine speed increases from the one used to validate the model. As a result, for the less-experienced CFD user and in the absence of enough experimental data that would help retune the tuning parameters at various operating conditions, the purpose of a good G-equation-based 3D engine simulation is to guide and/or complement experimental investigations, not the other way around. Only a truly-predictive simulation that fully couples the turbulence/chemistry equations can help reduce the amount of experimental work.« less

Phosphate-based glasses: Prediction of acoustical properties

NASA Astrophysics Data System (ADS)

El-Moneim, Amin Abd

2016-04-01

In this work, a comprehensive study has been carried out to predict the composition dependence of bulk modulus and ultrasonic attenuation coefficient in the phosphate-based glass systems PbO-P2O5, Li2O-TeO2-B2O3-P2O5, TiO2-Na2O-CaO-P2O5 and Cr2O3-doped Na2O-ZnO-P2O5 at room temperature. The prediction is based on (i) Makishima-Mackenzie theory, which correlates the bulk modulus with packing density and dissociation energy per unit volume, and (ii) Our recently presented semi-empirical formulas, which correlate the ultrasonic attenuation coefficient with the oxygen density, mean atomic ring size, first-order stretching force constant and experimental bulk modulus. Results revealed that our recently presented semi-empirical formulas can be applied successfully to predict changes of ultrasonic attenuation coefficient in binary PbO-P2O5 glasses at 10 MHz frequency and in quaternary Li2O-TeO2-B2O3-P2O5, TiO2-Na2O-CaO-P2O5 and Cr2O3-Na2O-ZnO-P2O5 glasses at 5 MHz frequency. Also, Makishima-Mackenzie theory appears to be valid for the studied glasses if the effect of the basic structural units that present in the glass network is taken into account.

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 1. Theory

USGS Publications Warehouse

Yen, Chung-Cheng; Guymon, Gary L.

1990-01-01

An efficient probabilistic model is developed and cascaded with a deterministic model for predicting water table elevations in regional aquifers. The objective is to quantify model uncertainty where precise estimates of water table elevations may be required. The probabilistic model is based on the two-point probability method which only requires prior knowledge of uncertain variables mean and coefficient of variation. The two-point estimate method is theoretically developed and compared with the Monte Carlo simulation method. The results of comparisons using hypothetical determinisitic problems indicate that the two-point estimate method is only generally valid for linear problems where the coefficients of variation of uncertain parameters (for example, storage coefficient and hydraulic conductivity) is small. The two-point estimate method may be applied to slightly nonlinear problems with good results, provided coefficients of variation are small. In such cases, the two-point estimate method is much more efficient than the Monte Carlo method provided the number of uncertain variables is less than eight.

An Efficient Deterministic-Probabilistic Approach to Modeling Regional Groundwater Flow: 1. Theory

NASA Astrophysics Data System (ADS)

Yen, Chung-Cheng; Guymon, Gary L.

1990-07-01

An efficient probabilistic model is developed and cascaded with a deterministic model for predicting water table elevations in regional aquifers. The objective is to quantify model uncertainty where precise estimates of water table elevations may be required. The probabilistic model is based on the two-point probability method which only requires prior knowledge of uncertain variables mean and coefficient of variation. The two-point estimate method is theoretically developed and compared with the Monte Carlo simulation method. The results of comparisons using hypothetical determinisitic problems indicate that the two-point estimate method is only generally valid for linear problems where the coefficients of variation of uncertain parameters (for example, storage coefficient and hydraulic conductivity) is small. The two-point estimate method may be applied to slightly nonlinear problems with good results, provided coefficients of variation are small. In such cases, the two-point estimate method is much more efficient than the Monte Carlo method provided the number of uncertain variables is less than eight.

Separation of very hydrophobic analytes by micellar electrokinetic chromatography IV. Modeling of the effective electrophoretic mobility from carbon number equivalents and octanol-water partition coefficients.

PubMed

Huhn, Carolin; Pyell, Ute

2008-07-11

It is investigated whether those relationships derived within an optimization scheme developed previously to optimize separations in micellar electrokinetic chromatography can be used to model effective electrophoretic mobilities of analytes strongly differing in their properties (polarity and type of interaction with the pseudostationary phase). The modeling is based on two parameter sets: (i) carbon number equivalents or octanol-water partition coefficients as analyte descriptors and (ii) four coefficients describing properties of the separation electrolyte (based on retention data for a homologous series of alkyl phenyl ketones used as reference analytes). The applicability of the proposed model is validated comparing experimental and calculated effective electrophoretic mobilities. The results demonstrate that the model can effectively be used to predict effective electrophoretic mobilities of neutral analytes from the determined carbon number equivalents or from octanol-water partition coefficients provided that the solvation parameters of the analytes of interest are similar to those of the reference analytes.

EMPIRICAL DETERMINATION OF EINSTEIN A-COEFFICIENT RATIOS OF BRIGHT [Fe II] LINES

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

Giannini, T.; Antoniucci, S.; Nisini, B.

The Einstein spontaneous rates (A-coefficients) of Fe{sup +} lines have been computed by several authors with results that differ from each other by up to 40%. Consequently, models for line emissivities suffer from uncertainties that in turn affect the determination of the physical conditions at the base of line excitation. We provide an empirical determination of the A-coefficient ratios of bright [Fe II] lines that would represent both a valid benchmark for theoretical computations and a reference for the physical interpretation of the observed lines. With the ESO-Very Large Telescope X-shooter instrument between 3000 Å and 24700 Å, we obtainedmore » a spectrum of the bright Herbig-Haro object HH 1. We detect around 100 [Fe II] lines, some of which with a signal-to-noise ratios ≥100. Among these latter lines, we selected those emitted by the same level, whose dereddened intensity ratios are direct functions of the Einstein A-coefficient ratios. From the same X-shooter spectrum, we got an accurate estimate of the extinction toward HH 1 through intensity ratios of atomic species, H I  recombination lines and H{sub 2} ro-vibrational transitions. We provide seven reliable A-coefficient ratios between bright [Fe II] lines, which are compared with the literature determinations. In particular, the A-coefficient ratios involving the brightest near-infrared lines (λ12570/λ16440 and λ13209/λ16440) are in better agreement with the predictions by the Quinet et al. relativistic Hartree-Fock model. However, none of the theoretical models predict A-coefficient ratios in agreement with all of our determinations. We also show that literature data of near-infrared intensity ratios better agree with our determinations than with theoretical expectations.« less

Spanish validation of the adult Attention Deficit/Hyperactivity Disorder Rating Scale (ADHD-RS): relevance of clinical subtypes.

PubMed

Richarte, Vanesa; Corrales, Montserrat; Pozuelo, Marian; Serra-Pla, Juanfran; Ibáñez, Pol; Calvo, Eva; Corominas, Margarida; Bosch, Rosa; Casas, Miquel; Ramos-Quiroga, Josep Antoni

Adult attention deficit hyperactivity disorder (ADHD) has a prevalence between 2.5% and 4% of the general adult population. Over the past few decades, self-report measures have been developed for the current evaluation of adult ADHD. The ADHD-RS is a 18-items scale self-report version for assessing symptoms for ADHD DSM-IV. A validation of Spanish version of the ADHD-RS was performed. The sample consisted of 304 adult with ADHD and 94 controls. A case control study was carried out (adult ADHD vs. non ADHD). The diagnosis of ADHD was evaluated with the Structured Clinical Interview for DSM-IV (SCID-I) and the Conners Adult ADHD Diagnostic Interview for DSM-IV (CAADID-II). To determinate the internal validity of the two dimensions structure of ADHD-RS an exploratory factor analysis was performed. The α-coefficients were taken as a measure of the internal consistency of the dimensions considered. A logistic regression study was carried out to evaluate the model in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive values (NPV). Average age was 33.29 (SD=10.50) and 66% of subjects were men (there were no significant differences between the two groups). Factor analysis was done with a principal component analysis followed by a normalized varimax rotation. The Kaiser-Meyer-Olkin measure of sampling adequacy tests was .868 (remarkable) and the Bartlett's test of sphericity was 2 (153)=1,835.76, P<.0005, indicating the appropriateness of the factor analysis. This two-factor model accounted for 37.81% of the explained variance. The α-coefficient of the two factors was .84 and .82. The original strategy proposed 24 point for cut-off: sensitivity (81.9%), specificity (74.7%), PPV (50.0%), NPV (93.0%), kappa coefficient .78 and area under the curve (AUC) .89. The new score strategy proposed by our group suggests different cut-off for different clinical presentations. The 24 point is the best cut-off for ADHD combined presentation: sensitivity (81.9%), specificity (87.3%), PPV (78.6%), NPV (89.4%), kappa coefficient .88 and AUC .94, and 21 point is the best cut-off for ADHD predominantly inattentive presentation: sensitivity (70.2%), specificity (76.1%), PPV (71.7%), NPV (74.8%), kappa coefficient .88 and AUC .94. In this study, the Spanish version of the ADHD-RS is a valid scale to discriminate between ADHD adults and controls. The new proposed score strategy suggests the relevance of clinical presentations in the different cut-offs selected. Copyright © 2017 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

Prediction of Film Cooling Effectiveness on a Gas Turbine Blade Leading Edge Using ANN and CFD

NASA Astrophysics Data System (ADS)

Dávalos, J. O.; García, J. C.; Urquiza, G.; Huicochea, A.; De Santiago, O.

2018-05-01

In this work, the area-averaged film cooling effectiveness (AAFCE) on a gas turbine blade leading edge was predicted by employing an artificial neural network (ANN) using as input variables: hole diameter, injection angle, blowing ratio, hole and columns pitch. The database used to train the network was built using computational fluid dynamics (CFD) based on a two level full factorial design of experiments. The CFD numerical model was validated with an experimental rig, where a first stage blade of a gas turbine was represented by a cylindrical specimen. The ANN architecture was composed of three layers with four neurons in hidden layer and Levenberg-Marquardt was selected as ANN optimization algorithm. The AAFCE was successfully predicted by the ANN with a regression coefficient R2<0.99 and a root mean square error RMSE=0.0038. The ANN weight coefficients were used to estimate the relative importance of the input parameters. Blowing ratio was the most influential parameter with relative importance of 40.36 % followed by hole diameter. Additionally, by using the ANN model, the relationship between input parameters was analyzed.

The influence of pressure relaxation on the structure of an axial vortex

NASA Astrophysics Data System (ADS)

Ash, Robert L.; Zardadkhan, Irfan; Zuckerwar, Allan J.

2011-07-01

Governing equations including the effects of pressure relaxation have been utilized to study an incompressible, steady-state viscous axial vortex with specified far-field circulation. When sound generation is attributed to a velocity gradient tensor-pressure gradient product, the modified conservation of momentum equations that result yield an exact solution for a steady, incompressible axial vortex. The vortex velocity profile has been shown to closely approximate experimental vortex measurements in air and water over a wide range of circulation-based Reynolds numbers. The influence of temperature and humidity on the pressure relaxation coefficient in air has been examined using theoretical and empirical approaches, and published axial vortex experiments have been employed to estimate the pressure relaxation coefficient in water. Non-equilibrium pressure gradient forces have been shown to balance the viscous stresses in the vortex core region, and the predicted pressure deficits that result from this non-equilibrium balance can be substantially larger than the pressure deficits predicted using a Bernoulli equation approach. Previously reported pressure deficit distributions for dust devils and tornados have been employed to validate the non-equilibrium pressure deficit predictions.

Prediction of chromatographic relative retention time of polychlorinated biphenyls from the molecular electronegativity distance vector.

PubMed

Liu, Shu-Shen; Liu, Yan; Yin, Da-Qian; Wang, Xiao-Dong; Wang, Lian-Sheng

2006-02-01

Using the molecular electronegativity distance vector (MEDV) descriptors derived directly from the molecular topological structures, the gas chromatographic relative retention times (RRTs) of 209 polychlorinated biphenyls (PCBs) on the SE-54 stationary phase were predicted. A five-variable regression equation with the correlation coefficient of 0.9964 and the root mean square errors of 0.0152 was developed. The descriptors included in the equation represent degree of chlorination (nCl), nonortho index (Ino), and interactions between three pairs of atom types, i.e., atom groups -C= and -C=, -C= and >C=, -C= and -Cl. It has been proved that the retention times of all 209 PCB congeners can be accurately predicted as long as there are more than 50 calibration compounds. In the same way, the MEDV descriptors are also used to develop the five- or six-variable models of RRTs of PCBs on other 18 stationary phases and the correlation coefficients in both modeling stage and LOO cross-validation step are not lower than 0.99 except two models.

QSPR models for predicting generator-column-derived octanol/water and octanol/air partition coefficients of polychlorinated biphenyls.

PubMed

Yuan, Jintao; Yu, Shuling; Zhang, Ting; Yuan, Xuejie; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

2016-06-01

Octanol/water (K(OW)) and octanol/air (K(OA)) partition coefficients are two important physicochemical properties of organic substances. In current practice, K(OW) and K(OA) values of some polychlorinated biphenyls (PCBs) are measured using generator column method. Quantitative structure-property relationship (QSPR) models can serve as a valuable alternative method of replacing or reducing experimental steps in the determination of K(OW) and K(OA). In this paper, two different methods, i.e., multiple linear regression based on dragon descriptors and hologram quantitative structure-activity relationship, were used to predict generator-column-derived log K(OW) and log K(OA) values of PCBs. The predictive ability of the developed models was validated using a test set, and the performances of all generated models were compared with those of three previously reported models. All results indicated that the proposed models were robust and satisfactory and can thus be used as alternative models for the rapid assessment of the K(OW) and K(OA) of PCBs. Copyright © 2016 Elsevier Inc. All rights reserved.

Nondestructive evaluation of soluble solid content in strawberry by near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Guo, Zhiming; Huang, Wenqian; Chen, Liping; Wang, Xiu; Peng, Yankun

This paper indicates the feasibility to use near infrared (NIR) spectroscopy combined with synergy interval partial least squares (siPLS) algorithms as a rapid nondestructive method to estimate the soluble solid content (SSC) in strawberry. Spectral preprocessing methods were optimized selected by cross-validation in the model calibration. Partial least squares (PLS) algorithm was conducted on the calibration of regression model. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R2 c) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R2 p) in prediction set. The optimal siPLS model was obtained with after first derivation spectra preprocessing. The measurement results of best model were achieved as follow: RMSEC = 0.2259, R2 c = 0.9590 in the calibration set; and RMSEP = 0.2892, R2 p = 0.9390 in the prediction set. This work demonstrated that NIR spectroscopy and siPLS with efficient spectral preprocessing is a useful tool for nondestructively evaluation SSC in strawberry.

Cross Cultural Adaptation, Validity, and Reliability of the Farsi Breastfeeding Attrition Prediction Tools in Iranian Pregnant Women

PubMed Central

Mortazavi, Forough; Mousavi, Seyed Abbas; Chaman, Reza; Khosravi, Ahmad; Janke, Jill R.

2015-01-01

Background: The rate of exclusive breastfeeding in Iran is decreasing. The breastfeeding attrition prediction tools (BAPT) have been validated and used in predicting premature weaning. Objectives: We aimed to translate the BAPT into Farsi, assess its content validity, and examine its reliability and validity to identify exclusive breastfeeding discontinuation in Iran. Materials and Methods: The BAPT was translated into Farsi and the content validity of the Farsi version of the BAPT was assessed. It was administered to 356 pregnant women in the third trimester of pregnancy, who were residents of a city in northeast of Iran. The structural integrity of the four-factor model was assessed in confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). Reliability was assessed using Cronbach’s alpha coefficient and item-subscale correlations. Validity was assessed using the known-group comparison (128 with vs. 228 without breastfeeding experience) and predictive validity (80 successes vs. 265 failures in exclusive breastfeeding). Results: The internal consistency of the whole instrument (49 items) was 0.775. CFA provided an acceptable fit to the a priori four-factor model (Chi-square/df = 1.8, Root Mean Square Error of Approximation (RMSEA) = 0.049, Standardized Root Mean Square Residual (SRMR) = 0.064, Comparative Fit Index (CFI) = 0.911). The difference in means of breastfeeding control (BFC) between the participants with and without breastfeeding experience was significant (P < 0.001). In addition, the total score of BAPT and the score of Breast Feeding Control (BFC) subscale were higher in women who were on exclusive breastfeeding than women who were not, at four months postpartum (P < 0.05). Conclusions: This study validated the Farsi version of BAPT. It is useful for researchers who want to use it in Iran to identify women at higher risks of Exclusive Breast Feeding (EBF) discontinuation. PMID:26019910

ASTRAL-R score predicts non-recanalisation after intravenous thrombolysis in acute ischaemic stroke.

PubMed

Vanacker, Peter; Heldner, Mirjam R; Seiffge, David; Mueller, Hubertus; Eskandari, Ashraf; Traenka, Christopher; Ntaios, George; Mosimann, Pascal J; Sztajzel, Roman; Mendes Pereira, Vitor; Cras, Patrick; Engelter, Stefan; Lyrer, Philippe; Fischer, Urs; Lambrou, Dimitris; Arnold, Marcel; Michel, Patrik

2015-05-01

Intravenous thrombolysis (IVT) as treatment in acute ischaemic strokes may be insufficient to achieve recanalisation in certain patients. Predicting probability of non-recanalisation after IVT may have the potential to influence patient selection to more aggressive management strategies. We aimed at deriving and internally validating a predictive score for post-thrombolytic non-recanalisation, using clinical and radiological variables. In thrombolysis registries from four Swiss academic stroke centres (Lausanne, Bern, Basel and Geneva), patients were selected with large arterial occlusion on acute imaging and with repeated arterial assessment at 24 hours. Based on a logistic regression analysis, an integer-based score for each covariate of the fitted multivariate model was generated. Performance of integer-based predictive model was assessed by bootstrapping available data and cross validation (delete-d method). In 599 thrombolysed strokes, five variables were identified as independent predictors of absence of recanalisation: Acute glucose > 7 mmol/l (A), significant extracranial vessel STenosis (ST), decreased Range of visual fields (R), large Arterial occlusion (A) and decreased Level of consciousness (L). All variables were weighted 1, except for (L) which obtained 2 points based on β-coefficients on the logistic scale. ASTRAL-R scores 0, 3 and 6 corresponded to non-recanalisation probabilities of 18, 44 and 74 % respectively. Predictive ability showed AUC of 0.66 (95 %CI, 0.61-0.70) when using bootstrap and 0.66 (0.63-0.68) when using delete-d cross validation. In conclusion, the 5-item ASTRAL-R score moderately predicts non-recanalisation at 24 hours in thrombolysed ischaemic strokes. If its performance can be confirmed by external validation and its clinical usefulness can be proven, the score may influence patient selection for more aggressive revascularisation strategies in routine clinical practice.

Prediction of fracture load and stiffness of the proximal femur by CT-based specimen specific finite element analysis: cadaveric validation study.

PubMed

Miura, Michiaki; Nakamura, Junichi; Matsuura, Yusuke; Wako, Yasushi; Suzuki, Takane; Hagiwara, Shigeo; Orita, Sumihisa; Inage, Kazuhide; Kawarai, Yuya; Sugano, Masahiko; Nawata, Kento; Ohtori, Seiji

2017-12-16

Finite element analysis (FEA) of the proximal femur has been previously validated with large mesh size, but these were insufficient to simulate the model with small implants in recent studies. This study aimed to validate the proximal femoral computed tomography (CT)-based specimen-specific FEA model with smaller mesh size using fresh frozen cadavers. Twenty proximal femora from 10 cadavers (mean age, 87.1 years) were examined. CT was performed on all specimens with a calibration phantom. Nonlinear FEA prediction with stance configuration was performed using Mechanical Finder (mesh,1.5 mm tetrahedral elements; shell thickness, 0.2 mm; Poisson's coefficient, 0.3), in comparison with mechanical testing. Force was applied at a fixed vertical displacement rate, and the magnitude of the applied load and displacement were continuously recorded. The fracture load and stiffness were calculated from force-displacement curve, and the correlation between mechanical testing and FEA prediction was examined. A pilot study with one femur revealed that the equations proposed by Keller for vertebra were the most reproducible for calculating Young's modulus and the yield stress of elements of the proximal femur. There was a good linear correlation between fracture loads of mechanical testing and FEA prediction (R 2 = 0.6187) and between the stiffness of mechanical testing and FEA prediction (R 2 = 0.5499). There was a good linear correlation between fracture load and stiffness (R 2 = 0.6345) in mechanical testing and an excellent correlation between these (R 2 = 0.9240) in FEA prediction. CT-based specimen-specific FEA model of the proximal femur with small element size was validated using fresh frozen cadavers. The equations proposed by Keller for vertebra were found to be the most reproducible for the proximal femur in elderly people.

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy

PubMed Central

Diago, Maria P.; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψs) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction (RP2) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture. PMID:29441086

Development and Validation of a New Methodology to Assess the Vineyard Water Status by On-the-Go Near Infrared Spectroscopy.

PubMed

Diago, Maria P; Fernández-Novales, Juan; Gutiérrez, Salvador; Marañón, Miguel; Tardaguila, Javier

2018-01-01

Assessing water status and optimizing irrigation is of utmost importance in most winegrowing countries, as the grapevine vegetative growth, yield, and grape quality can be impaired under certain water stress situations. Conventional plant-based methods for water status monitoring are either destructive or time and labor demanding, therefore unsuited to detect the spatial variation of moisten content within a vineyard plot. In this context, this work aims at the development and comprehensive validation of a novel, non-destructive methodology to assess the vineyard water status distribution using on-the-go, contactless, near infrared (NIR) spectroscopy. Likewise, plant water status prediction models were built and intensely validated using the stem water potential (ψ s ) as gold standard. Predictive models were developed making use of a vast number of measurements, acquired on 15 dates with diverse environmental conditions, at two different spatial scales, on both sides of vertical shoot positioned canopies, over two consecutive seasons. Different cross-validation strategies were also tested and compared. Predictive models built from east-acquired spectra yielded the best performance indicators in both seasons, with determination coefficient of prediction ([Formula: see text]) ranging from 0.68 to 0.85, and sensitivity (expressed as prediction root mean square error) between 0.131 and 0.190 MPa, regardless the spatial scale. These predictive models were implemented to map the spatial variability of the vineyard water status at two different dates, and provided useful, practical information to help delineating specific irrigation schedules. The performance and the large amount of data that this on-the-go spectral solution provides, facilitates the exploitation of this non-destructive technology to monitor and map the vineyard water status variability with high spatial and temporal resolution, in the context of precision and sustainable viticulture.

Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement.

PubMed

Shen, Qijun; Shan, Yanna; Hu, Zhengyu; Chen, Wenhui; Yang, Bing; Han, Jing; Huang, Yanfang; Xu, Wen; Feng, Zhan

2018-04-30

To objectively quantify intracranial hematoma (ICH) enlargement by analysing the image texture of head CT scans and to provide objective and quantitative imaging parameters for predicting early hematoma enlargement. We retrospectively studied 108 ICH patients with baseline non-contrast computed tomography (NCCT) and 24-h follow-up CT available. Image data were assessed by a chief radiologist and a resident radiologist. Consistency analysis between observers was tested. The patients were divided into training set (75%) and validation set (25%) by stratified sampling. Patients in the training set were dichotomized according to 24-h hematoma expansion ≥ 33%. Using the Laplacian of Gaussian bandpass filter, we chose different anatomical spatial domains ranging from fine texture to coarse texture to obtain a series of derived parameters (mean grayscale intensity, variance, uniformity) in order to quantify and evaluate all data. The parameters were externally validated on validation set. Significant differences were found between the two groups of patients within variance at V 1.0 and in uniformity at U 1.0 , U 1.8 and U 2.5 . The intraclass correlation coefficients for the texture parameters were between 0.67 and 0.99. The area under the ROC curve between the two groups of ICH cases was between 0.77 and 0.92. The accuracy of validation set by CTTA was 0.59-0.85. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • Heterogeneity is helpful in predicting ICH enlargement. • CTTA could play an important role in predicting early ICH enlargement. • After filtering, fine texture had the best diagnostic performance. • The histogram-based uniformity parameters can independently predict ICH enlargement. • CTTA is more objective, more comprehensive, more independently operable, than previous methods.

The theoretical ultimate magnetoelectric coefficients of magnetoelectric composites by optimization design

NASA Astrophysics Data System (ADS)

Wang, H.-L.; Liu, B.

2014-03-01

This paper investigates what is the largest magnetoelectric (ME) coefficient of ME composites, and how to realize it. From the standpoint of energy conservation, a theoretical analysis is carried out on an imaginary lever structure consisting of a magnetostrictive phase, a piezoelectric phase, and a rigid lever. This structure is a generalization of various composite layouts for optimization on ME effect. The predicted theoretical ultimate ME coefficient plays a similar role as the efficiency of ideal heat engine in thermodynamics, and is used to evaluate the existing typical ME layouts, such as the parallel sandwiched layout and the serial layout. These two typical layouts exhibit ME coefficient much lower than the theoretical largest values, because in the general analysis the stress amplification ratio and the volume ratio can be optimized independently and freely, but in typical layouts they are dependent or fixed. To overcome this shortcoming and achieve the theoretical largest ME coefficient, a new design is presented. In addition, it is found that the most commonly used electric field ME coefficient can be designed to be infinitely large. We doubt the validity of this coefficient as a reasonable ME effect index and consider three more ME coefficients, namely the electric charge ME coefficient, the voltage ME coefficient, and the static electric energy ME coefficient. We note that the theoretical ultimate value of the static electric energy ME coefficient is finite and might be a more proper measure of ME effect.

The theoretical ultimate magnetoelectric coefficients of magnetoelectric composites by optimization design

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

Wang, H.-L.; Liu, B., E-mail: liubin@tsinghua.edu.cn

2014-03-21

This paper investigates what is the largest magnetoelectric (ME) coefficient of ME composites, and how to realize it. From the standpoint of energy conservation, a theoretical analysis is carried out on an imaginary lever structure consisting of a magnetostrictive phase, a piezoelectric phase, and a rigid lever. This structure is a generalization of various composite layouts for optimization on ME effect. The predicted theoretical ultimate ME coefficient plays a similar role as the efficiency of ideal heat engine in thermodynamics, and is used to evaluate the existing typical ME layouts, such as the parallel sandwiched layout and the serial layout.more » These two typical layouts exhibit ME coefficient much lower than the theoretical largest values, because in the general analysis the stress amplification ratio and the volume ratio can be optimized independently and freely, but in typical layouts they are dependent or fixed. To overcome this shortcoming and achieve the theoretical largest ME coefficient, a new design is presented. In addition, it is found that the most commonly used electric field ME coefficient can be designed to be infinitely large. We doubt the validity of this coefficient as a reasonable ME effect index and consider three more ME coefficients, namely the electric charge ME coefficient, the voltage ME coefficient, and the static electric energy ME coefficient. We note that the theoretical ultimate value of the static electric energy ME coefficient is finite and might be a more proper measure of ME effect.« less

Modeling and Prediction of Solvent Effect on Human Skin Permeability using Support Vector Regression and Random Forest.

PubMed

Baba, Hiromi; Takahara, Jun-ichi; Yamashita, Fumiyoshi; Hashida, Mitsuru

2015-11-01

The solvent effect on skin permeability is important for assessing the effectiveness and toxicological risk of new dermatological formulations in pharmaceuticals and cosmetics development. The solvent effect occurs by diverse mechanisms, which could be elucidated by efficient and reliable prediction models. However, such prediction models have been hampered by the small variety of permeants and mixture components archived in databases and by low predictive performance. Here, we propose a solution to both problems. We first compiled a novel large database of 412 samples from 261 structurally diverse permeants and 31 solvents reported in the literature. The data were carefully screened to ensure their collection under consistent experimental conditions. To construct a high-performance predictive model, we then applied support vector regression (SVR) and random forest (RF) with greedy stepwise descriptor selection to our database. The models were internally and externally validated. The SVR achieved higher performance statistics than RF. The (externally validated) determination coefficient, root mean square error, and mean absolute error of SVR were 0.899, 0.351, and 0.268, respectively. Moreover, because all descriptors are fully computational, our method can predict as-yet unsynthesized compounds. Our high-performance prediction model offers an attractive alternative to permeability experiments for pharmaceutical and cosmetic candidate screening and optimizing skin-permeable topical formulations.

Development and validation of a tool to evaluate the quality of medical education websites in pathology.

PubMed

Alyusuf, Raja H; Prasad, Kameshwar; Abdel Satir, Ali M; Abalkhail, Ali A; Arora, Roopa K

2013-01-01

The exponential use of the internet as a learning resource coupled with varied quality of many websites, lead to a need to identify suitable websites for teaching purposes. The aim of this study is to develop and to validate a tool, which evaluates the quality of undergraduate medical educational websites; and apply it to the field of pathology. A tool was devised through several steps of item generation, reduction, weightage, pilot testing, post-pilot modification of the tool and validating the tool. Tool validation included measurement of inter-observer reliability; and generation of criterion related, construct related and content related validity. The validated tool was subsequently tested by applying it to a population of pathology websites. Reliability testing showed a high internal consistency reliability (Cronbach's alpha = 0.92), high inter-observer reliability (Pearson's correlation r = 0.88), intraclass correlation coefficient = 0.85 and κ =0.75. It showed high criterion related, construct related and content related validity. The tool showed moderately high concordance with the gold standard (κ =0.61); 92.2% sensitivity, 67.8% specificity, 75.6% positive predictive value and 88.9% negative predictive value. The validated tool was applied to 278 websites; 29.9% were rated as recommended, 41.0% as recommended with caution and 29.1% as not recommended. A systematic tool was devised to evaluate the quality of websites for medical educational purposes. The tool was shown to yield reliable and valid inferences through its application to pathology websites.

Indoor air quality of low and middle income urban households in Durban, South Africa.

PubMed

Jafta, Nkosana; Barregard, Lars; Jeena, Prakash M; Naidoo, Rajen N

2017-07-01

Elevated levels of indoor air pollutants may cause cardiopulmonary disease such as lower respiratory infection, chronic obstructive lung disease and lung cancer, but the association with tuberculosis (TB) is unclear. So far the risk estimates of TB infection or/and disease due to indoor air pollution (IAP) exposure are based on self-reported exposures rather than direct measurements of IAP, and these exposures have not been validated. The aim of this paper was to characterize and develop predictive models for concentrations of three air pollutants (PM 10 , NO 2 and SO 2 ) in homes of children participating in a childhood TB study. Children younger than 15 years living within the eThekwini Municipality in South Africa were recruited for a childhood TB case control study. The homes of these children (n=246) were assessed using a walkthrough checklist, and in 114 of them monitoring of three indoor pollutants was also performed (sampling period: 24h for PM 10 , and 2-3 weeks for NO 2 and SO 2 ). Linear regression models were used to predict PM 10 and NO 2 concentrations from household characteristics, and these models were validated using leave out one cross validation (LOOCV). SO 2 concentrations were not modeled as concentrations were very low. Mean indoor concentrations of PM 10 (n=105) , NO 2 (n=82) and SO 2 (n=82) were 64μg/m 3 (range 6.6-241); 19μg/m 3 (range 4.5-55) and 0.6μg/m 3 (range 0.005-3.4) respectively with the distributions for all three pollutants being skewed to the right. Spearman correlations showed weak positive correlations between the three pollutants. The largest contributors to the PM 10 predictive model were type of housing structure (formal or informal), number of smokers in the household, and type of primary fuel used in the household. The NO 2 predictive model was influenced mostly by the primary fuel type and by distance from the major roadway. The coefficients of determination (R 2 ) for the models were 0.41 for PM 10 and 0.31 for NO 2 . Spearman correlations were significant between measured vs. predicted PM 10 and NO 2 with coefficients of 0.66 and 0.55 respectively. Indoor PM 10 levels were relatively high in these households. Both PM 10 and NO 2 can be modeled with a reasonable validity and these predictive models can decrease the necessary number of direct measurements that are expensive and time consuming. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy.

PubMed

Liu, Yan-De; Ying, Yi-Bin; Fu, Xia-Ping

2005-03-01

To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way.

Prediction of valid acidity in intact apples with Fourier transform near infrared spectroscopy*

PubMed Central

Liu, Yan-de; Ying, Yi-bin; Fu, Xia-ping

2005-01-01

To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r 2) of 0.759, low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way. PMID:15682498

Predicting permeability of regular tissue engineering scaffolds: scaling analysis of pore architecture, scaffold length, and fluid flow rate effects.

PubMed

Rahbari, A; Montazerian, H; Davoodi, E; Homayoonfar, S

2017-02-01

The main aim of this research is to numerically obtain the permeability coefficient in the cylindrical scaffolds. For this purpose, a mathematical analysis was performed to derive an equation for desired porosity in terms of morphological parameters. Then, the considered cylindrical geometries were modeled and the permeability coefficient was calculated according to the velocity and pressure drop values based on the Darcy's law. In order to validate the accuracy of the present numerical solution, the obtained permeability coefficient was compared with the published experimental data. It was observed that this model can predict permeability with the utmost accuracy. Then, the effect of geometrical parameters including porosity, scaffold pore structure, unit cell size, and length of the scaffolds as well as entrance mass flow rate on the permeability of porous structures was studied. Furthermore, a parametric study with scaling laws analysis of sample length and mass flow rate effects on the permeability showed good fit to the obtained data. It can be concluded that the sensitivity of permeability is more noticeable at higher porosities. The present approach can be used to characterize and optimize the scaffold microstructure due to the necessity of cell growth and transferring considerations.

An Efficient Non-iterative Bulk Parametrization of Surface Fluxes for Stable Atmospheric Conditions Over Polar Sea-Ice

NASA Astrophysics Data System (ADS)

Gryanik, Vladimir M.; Lüpkes, Christof

2018-02-01

In climate and weather prediction models the near-surface turbulent fluxes of heat and momentum and related transfer coefficients are usually parametrized on the basis of Monin-Obukhov similarity theory (MOST). To avoid iteration, required for the numerical solution of the MOST equations, many models apply parametrizations of the transfer coefficients based on an approach relating these coefficients to the bulk Richardson number Rib. However, the parametrizations that are presently used in most climate models are valid only for weaker stability and larger surface roughnesses than those documented during the Surface Heat Budget of the Arctic Ocean campaign (SHEBA). The latter delivered a well-accepted set of turbulence data in the stable surface layer over polar sea-ice. Using stability functions based on the SHEBA data, we solve the MOST equations applying a new semi-analytic approach that results in transfer coefficients as a function of Rib and roughness lengths for momentum and heat. It is shown that the new coefficients reproduce the coefficients obtained by the numerical iterative method with a good accuracy in the most relevant range of stability and roughness lengths. For small Rib, the new bulk transfer coefficients are similar to the traditional coefficients, but for large Rib they are much smaller than currently used coefficients. Finally, a possible adjustment of the latter and the implementation of the new proposed parametrizations in models are discussed.

Validation Database Based Thermal Analysis of an Advanced RPS Concept

NASA Technical Reports Server (NTRS)

Balint, Tibor S.; Emis, Nickolas D.

2006-01-01

Advanced RPS concepts can be conceived, designed and assessed using high-end computational analysis tools. These predictions may provide an initial insight into the potential performance of these models, but verification and validation are necessary and required steps to gain confidence in the numerical analysis results. This paper discusses the findings from a numerical validation exercise for a small advanced RPS concept, based on a thermal analysis methodology developed at JPL and on a validation database obtained from experiments performed at Oregon State University. Both the numerical and experimental configurations utilized a single GPHS module enabled design, resembling a Mod-RTG concept. The analysis focused on operating and environmental conditions during the storage phase only. This validation exercise helped to refine key thermal analysis and modeling parameters, such as heat transfer coefficients, and conductivity and radiation heat transfer values. Improved understanding of the Mod-RTG concept through validation of the thermal model allows for future improvements to this power system concept.

Two-structured solid particle model for predicting and analyzing supercritical extraction performance.

PubMed

Samadi, Sara; Vaziri, Behrooz Mahmoodzadeh

2017-07-14

Solid extraction process, using the supercritical fluid, is a modern science and technology, which has come in vogue regarding its considerable advantages. In the present article, a new and comprehensive model is presented for predicting the performance and separation yield of the supercritical extraction process. The base of process modeling is partial differential mass balances. In the proposed model, the solid particles are considered twofold: (a) particles with intact structure, (b) particles with destructed structure. A distinct mass transfer coefficient has been used for extraction of each part of solid particles to express different extraction regimes and to evaluate the process accurately (internal mass transfer coefficient was used for the intact-structure particles and external mass transfer coefficient was employed for the destructed-structure particles). In order to evaluate and validate the proposed model, the obtained results from simulations were compared with two series of available experimental data for extraction of chamomile extract with supercritical carbon dioxide, which had an excellent agreement. This is indicative of high potentiality of the model in predicting the extraction process, precisely. In the following, the effect of major parameters on supercritical extraction process, like pressure, temperature, supercritical fluid flow rate, and the size of solid particles was evaluated. The model can be used as a superb starting point for scientific and experimental applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, M.; Mehltretter, S. L.; Gharabaghi, B.; Rudra, R.

2015-12-01

One of the most uncertain modeling tasks in hydrology is the prediction of ungauged stream sediment load and concentration statistics. This study presents integrated artificial neural networks (ANN) models for prediction of sediment rating curve parameters (rating curve coefficient α and rating curve exponent β) for ungauged basins. The ANN models integrate a comprehensive list of input parameters to improve the accuracy achieved; the input parameters used include: soil, land use, topographic, climatic, and hydrometric data sets. The ANN models were trained on the randomly selected 2/3 of the dataset of 94 gauged streams in Ontario, Canada and validated on the remaining 1/3. The developed models have high correlation coefficients of 0.92 and 0.86 for α and β, respectively. The ANN model for the rating coefficient α is directly proportional to rainfall erosivity factor, soil erodibility factor, and apportionment entropy disorder index, whereas it is inversely proportional to vegetation cover and mean annual snowfall. The ANN model for the rating exponent β is directly proportional to mean annual precipitation, the apportionment entropy disorder index, main channel slope, standard deviation of daily discharge, and inversely proportional to the fraction of basin area covered by wetlands and swamps. Sediment rating curves are essential tools for the calculation of sediment load, concentration-duration curve (CDC), and concentration-duration-frequency (CDF) analysis for more accurate assessment of water quality for ungauged basins.

Comparison of photon attenuation coefficients (2-150 KeV) for diagnostic imaging simulations

NASA Astrophysics Data System (ADS)

Dodge, Charles W., III; Flynn, Michael J.

2004-05-01

The Radiology Research Laboratory at the Henry Ford Hospital has been involved in modeling x-ray units in order to predict image quality. A critical part of that modeling process is the accurate choice of interaction coefficients. This paper serves as a review and comparison of existing interaction models. Our objective was to obtain accurate and easily calculated interaction coefficients, at diagnostically relevant energies. We obtained data from: McMaster, Lawrence Berkeley Lab data (LBL), XCOM and FFAST Data from NIST, and the EPDL-97 database via LLNL. Our studies involve low energy photons; therefore, comparisons were limited to Coherent (Rayleigh), Incoherent (Compton) and Photoelectric effects, which were summed to determine a total interaction cross section. Without measured data, it becomes difficult to definitively choose the most accurate method. However, known limitations in the McMaster data and smoothing of photo-edge transitions can be used as a guide to establish more valid approaches. Each method was compared to one another graphically and at individual points. We found that agreement between all methods was excellent when away from photo-edges. Near photo-edges and at low energies, most methods were less accurate. Only the Chanter (FFAST) data seems to have consistently and accurately predicted the placement of edges (through M-shell), while minimizing smoothing errors. The EPDL-97 data by LLNL was the best over method in predicting coherent and incoherent cross sections.

Using support vector machine to predict beta- and gamma-turns in proteins.

PubMed

Hu, Xiuzhen; Li, Qianzhong

2008-09-01

By using the composite vector with increment of diversity, position conservation scoring function, and predictive secondary structures to express the information of sequence, a support vector machine (SVM) algorithm for predicting beta- and gamma-turns in the proteins is proposed. The 426 and 320 nonhomologous protein chains described by Guruprasad and Rajkumar (Guruprasad and Rajkumar J. Biosci 2000, 25,143) are used for training and testing the predictive model of the beta- and gamma-turns, respectively. The overall prediction accuracy and the Matthews correlation coefficient in 7-fold cross-validation are 79.8% and 0.47, respectively, for the beta-turns. The overall prediction accuracy in 5-fold cross-validation is 61.0% for the gamma-turns. These results are significantly higher than the other algorithms in the prediction of beta- and gamma-turns using the same datasets. In addition, the 547 and 823 nonhomologous protein chains described by Fuchs and Alix (Fuchs and Alix Proteins: Struct Funct Bioinform 2005, 59, 828) are used for training and testing the predictive model of the beta- and gamma-turns, and better results are obtained. This algorithm may be helpful to improve the performance of protein turns' prediction. To ensure the ability of the SVM method to correctly classify beta-turn and non-beta-turn (gamma-turn and non-gamma-turn), the receiver operating characteristic threshold independent measure curves are provided. (c) 2008 Wiley Periodicals, Inc.

Semi-Empirical Prediction of Aircraft Low-Speed Aerodynamic Characteristics

NASA Technical Reports Server (NTRS)

Olson, Erik D.

2015-01-01

This paper lays out a comprehensive methodology for computing a low-speed, high-lift polar, without requiring additional details about the aircraft design beyond what is typically available at the conceptual design stage. Introducing low-order, physics-based aerodynamic analyses allows the methodology to be more applicable to unconventional aircraft concepts than traditional, fully-empirical methods. The methodology uses empirical relationships for flap lift effectiveness, chord extension, drag-coefficient increment and maximum lift coefficient of various types of flap systems as a function of flap deflection, and combines these increments with the characteristics of the unflapped airfoils. Once the aerodynamic characteristics of the flapped sections are known, a vortex-lattice analysis calculates the three-dimensional lift, drag and moment coefficients of the whole aircraft configuration. This paper details the results of two validation cases: a supercritical airfoil model with several types of flaps; and a 12-foot, full-span aircraft model with slats and double-slotted flaps.

Predictive validity of the UK clinical aptitude test in the final years of medical school: a prospective cohort study.

PubMed

Husbands, Adrian; Mathieson, Alistair; Dowell, Jonathan; Cleland, Jennifer; MacKenzie, Rhoda

2014-04-23

The UK Clinical Aptitude Test (UKCAT) was designed to address issues identified with traditional methods of selection. This study aims to examine the predictive validity of the UKCAT and compare this to traditional selection methods in the senior years of medical school. This was a follow-up study of two cohorts of students from two medical schools who had previously taken part in a study examining the predictive validity of the UKCAT in first year. The sample consisted of 4th and 5th Year students who commenced their studies at the University of Aberdeen or University of Dundee medical schools in 2007. Data collected were: demographics (gender and age group), UKCAT scores; Universities and Colleges Admissions Service (UCAS) form scores; admission interview scores; Year 4 and 5 degree examination scores. Pearson's correlations were used to examine the relationships between admissions variables, examination scores, gender and age group, and to select variables for multiple linear regression analysis to predict examination scores. Ninety-nine and 89 students at Aberdeen medical school from Years 4 and 5 respectively, and 51 Year 4 students in Dundee, were included in the analysis. Neither UCAS form nor interview scores were statistically significant predictors of examination performance. Conversely, the UKCAT yielded statistically significant validity coefficients between .24 and .36 in four of five assessments investigated. Multiple regression analysis showed the UKCAT made a statistically significant unique contribution to variance in examination performance in the senior years. Results suggest the UKCAT appears to predict performance better in the later years of medical school compared to earlier years and provides modest supportive evidence for the UKCAT's role in student selection within these institutions. Further research is needed to assess the predictive validity of the UKCAT against professional and behavioural outcomes as the cohort commences working life.

Predictive validity of the UK clinical aptitude test in the final years of medical school: a prospective cohort study

PubMed Central

2014-01-01

Background The UK Clinical Aptitude Test (UKCAT) was designed to address issues identified with traditional methods of selection. This study aims to examine the predictive validity of the UKCAT and compare this to traditional selection methods in the senior years of medical school. This was a follow-up study of two cohorts of students from two medical schools who had previously taken part in a study examining the predictive validity of the UKCAT in first year. Methods The sample consisted of 4th and 5th Year students who commenced their studies at the University of Aberdeen or University of Dundee medical schools in 2007. Data collected were: demographics (gender and age group), UKCAT scores; Universities and Colleges Admissions Service (UCAS) form scores; admission interview scores; Year 4 and 5 degree examination scores. Pearson’s correlations were used to examine the relationships between admissions variables, examination scores, gender and age group, and to select variables for multiple linear regression analysis to predict examination scores. Results Ninety-nine and 89 students at Aberdeen medical school from Years 4 and 5 respectively, and 51 Year 4 students in Dundee, were included in the analysis. Neither UCAS form nor interview scores were statistically significant predictors of examination performance. Conversely, the UKCAT yielded statistically significant validity coefficients between .24 and .36 in four of five assessments investigated. Multiple regression analysis showed the UKCAT made a statistically significant unique contribution to variance in examination performance in the senior years. Conclusions Results suggest the UKCAT appears to predict performance better in the later years of medical school compared to earlier years and provides modest supportive evidence for the UKCAT’s role in student selection within these institutions. Further research is needed to assess the predictive validity of the UKCAT against professional and behavioural outcomes as the cohort commences working life. PMID:24762134

Derivation and Internal Validation of a Clinical Prediction Tool for 30-Day Mortality in Lower Gastrointestinal Bleeding.

PubMed

Sengupta, Neil; Tapper, Elliot B

2017-05-01

There are limited data to predict which patients with lower gastrointestinal bleeding are at risk for adverse outcomes. We aimed to develop a clinical tool based on admission variables to predict 30-day mortality in lower gastrointestinal bleeding. We used a validated machine learning algorithm to identify adult patients hospitalized with lower gastrointestinal bleeding at an academic medical center between 2008 and 2015. The cohort was split randomly into derivation and validation cohorts. In the derivation cohort, we used multiple logistic regression on all candidate admission variables to create a prediction model for 30-day mortality, using area under the receiving operator characteristic curve and misclassification rate to estimate prediction accuracy. Regression coefficients were used to derive an integer score, and mortality risk associated with point totals was assessed. In the derivation cohort (n = 4044), 8 variables were most associated with 30-day mortality: age, dementia, metastatic cancer, chronic kidney disease, chronic pulmonary disease, anticoagulant use, admission hematocrit, and albumin. The model yielded a misclassification rate of 0.06 and area under the curve of 0.81. The integer score ranged from -10 to 26 in the derivation cohort, with a misclassification rate of 0.11 and area under the curve of 0.74. In the validation cohort (n = 2060), the score had an area under the curve of 0.72 with a misclassification rate of 0.12. After dividing the score into 4 quartiles of risk, 30-day mortality in the derivation and validation sets was 3.6% and 4.4% in quartile 1, 4.9% and 7.3% in quartile 2, 9.9% and 9.1% in quartile 3, and 24% and 26% in quartile 4, respectively. A clinical tool can be used to predict 30-day mortality in patients hospitalized with lower gastrointestinal bleeding. Copyright © 2017 Elsevier Inc. All rights reserved.

An Application of Practical Strategies in Assessing the Criterion-Related Validity of Credentialing Examinations.

ERIC Educational Resources Information Center

Fidler, James R.

1993-01-01

Criterion-related validities of 2 laboratory practitioner certification examinations for medical technologists (MTs) and medical laboratory technicians (MLTs) were assessed for 81 MT and 70 MLT examinees. Validity coefficients are presented for both measures. Overall, summative ratings yielded stronger validity coefficients than ratings based on…

[The appraisal of reliability and validity of subjective workload assessment technique and NASA-task load index].

PubMed

Xiao, Yuan-mei; Wang, Zhi-ming; Wang, Mian-zhen; Lan, Ya-jia

2005-06-01

To test the reliability and validity of two mental workload assessment scales, i.e. subjective workload assessment technique (SWAT) and NASA task load index (NASA-TLX). One thousand two hundred and sixty-eight mental workers were sampled from various kinds of occupations, such as scientific research, education, administration and medicine, etc, with randomized cluster sampling. The re-test reliability, split-half reliability, Cronbach's alpha coefficient and correlation coefficients between item score and total score were adopted to test the reliability. The test of validity included structure validity. The re-test reliability coefficients of these two scales and their items were ranged from 0.516 to 0.753 (P < 0.01), indicating the two scales had good re-test reliability; the split-half reliability of SWAT was 0.645, and its Cronbach's alpha coefficient was more than 0.80, all the correlation coefficients between its items score and total score were more than 0.70; as for NASA-TLX, both the split-half reliability and Cronbach's alpha coefficient were more than 0.80, the correlation coefficients between its items score and total score were all more than 0.60 (P < 0.01) except the item of performance. Both scales had good inner consistency. The Pearson correlation coefficient between the two scales was 0.492 (P < 0.01), implying the results of the two scales had good consistency. Factor analysis showed that the two scales had good structure validity. Both SWAT and NASA-TLX have good reliability and validity and may be used as a valid tool to assess mental workload in China after being revised properly.

A computable phenotype for asthma case identification in adult and pediatric patients: External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN).

PubMed

Afshar, Majid; Press, Valerie G; Robison, Rachel G; Kho, Abel N; Bandi, Sindhura; Biswas, Ashvini; Avila, Pedro C; Kumar, Harsha Vardhan Madan; Yu, Byung; Naureckas, Edward T; Nyenhuis, Sharmilee M; Codispoti, Christopher D

2017-10-13

Comprehensive, rapid, and accurate identification of patients with asthma for clinical care and engagement in research efforts is needed. The original development and validation of a computable phenotype for asthma case identification occurred at a single institution in Chicago and demonstrated excellent test characteristics. However, its application in a diverse payer mix, across different health systems and multiple electronic health record vendors, and in both children and adults was not examined. The objective of this study is to externally validate the computable phenotype across diverse Chicago institutions to accurately identify pediatric and adult patients with asthma. A cohort of 900 asthma and control patients was identified from the electronic health record between January 1, 2012 and November 30, 2014. Two physicians at each site independently reviewed the patient chart to annotate cases. The inter-observer reliability between the physician reviewers had a κ-coefficient of 0.95 (95% CI 0.93-0.97). The accuracy, sensitivity, specificity, negative predictive value, and positive predictive value of the computable phenotype were all above 94% in the full cohort. The excellent positive and negative predictive values in this multi-center external validation study establish a useful tool to identify asthma cases in in the electronic health record for research and care. This computable phenotype could be used in large-scale comparative-effectiveness trials.

Design of Novel Chemotherapeutic Agents Targeting Checkpoint Kinase 1 Using 3D-QSAR Modeling and Molecular Docking Methods.

PubMed

Balupuri, Anand; Balasubramanian, Pavithra K; Cho, Seung J

2016-01-01

Checkpoint kinase 1 (Chk1) has emerged as a potential therapeutic target for design and development of novel anticancer drugs. Herein, we have performed three-dimensional quantitative structure-activity relationship (3D-QSAR) and molecular docking analyses on a series of diazacarbazoles to design potent Chk1 inhibitors. 3D-QSAR models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques. Docking studies were performed using AutoDock. The best CoMFA and CoMSIA models exhibited cross-validated correlation coefficient (q2) values of 0.631 and 0.585, and non-cross-validated correlation coefficient (r2) values of 0.933 and 0.900, respectively. CoMFA and CoMSIA models showed reasonable external predictabilities (r2 pred) of 0.672 and 0.513, respectively. A satisfactory performance in the various internal and external validation techniques indicated the reliability and robustness of the best model. Docking studies were performed to explore the binding mode of inhibitors inside the active site of Chk1. Molecular docking revealed that hydrogen bond interactions with Lys38, Glu85 and Cys87 are essential for Chk1 inhibitory activity. The binding interaction patterns observed during docking studies were complementary to 3D-QSAR results. Information obtained from the contour map analysis was utilized to design novel potent Chk1 inhibitors. Their activities and binding affinities were predicted using the derived model and docking studies. Designed inhibitors were proposed as potential candidates for experimental synthesis.

KNT-artificial neural network model for flux prediction of ultrafiltration membrane producing drinking water.

PubMed

Oh, H K; Yu, M J; Gwon, E M; Koo, J Y; Kim, S G; Koizumi, A

2004-01-01

This paper describes the prediction of flux behavior in an ultrafiltration (UF) membrane system using a Kalman neuro training (KNT) network model. The experimental data was obtained from operating a pilot plant of hollow fiber UF membrane with groundwater for 7 months. The network was trained using operating conditions such as inlet pressure, filtration duration, and feed water quality parameters including turbidity, temperature and UV254. Pre-processing of raw data allowed the normalized input data to be used in sigmoid activation functions. A neural network architecture was structured by modifying the number of hidden layers, neurons and learning iterations. The structure of KNT-neural network with 3 layers and 5 neurons allowed a good prediction of permeate flux by 0.997 of correlation coefficient during the learning phase. Also the validity of the designed model was evaluated with other experimental data not used during the training phase and nonlinear flux behavior was accurately estimated with 0.999 of correlation coefficient and a lower error of prediction in the testing phase. This good flux prediction can provide preliminary criteria in membrane design and set up the proper cleaning cycle in membrane operation. The KNT-artificial neural network is also expected to predict the variation of transmembrane pressure during filtration cycles and can be applied to automation and control of full scale treatment plants.

Cross-cultural adaptation and psychometric evaluation of oral health impact profile among school teacher community

PubMed Central

Vyas, Shaleen; Nagarajappa, Sandesh; Dasar, Pralhad L.; Mishra, Prashant

2018-01-01

AIM: To translate OHIP-14 into Hindi and test its psychometric properties among school teacher community. METHODS: The OHIP-14 was translated to OHIP-14-H using WHO recommended translation protocol. During pre-testing, an expert panel assessed content validity of the questionnaire. Face validity was assessed on a sample of 10 individuals. The OHIP-14-H was administered on a random sample of 170 primary school teachers. Internal consistency and test-retest reliability were assessed using Cronbach's alpha and Intra-class correlation coefficient (ICC) respectively, with 2 weeks interval. Predictive validity was tested by comparing OHIP-14-H scores with clinical parameters. The concurrent validity was assessed using self-reported oral health and discriminant validity was ascertained through negative association with sociodemographic variables. RESULTS: The mean OHIP-14-H score was 9.57 (S.D = 4.58). ICC and Cronbach's alpha for OHIP-14-H was 0.96 and 0.92 respectively. Concurrent validity using binomial regression model indicated that good (OR = 0.56, 95% CI = 0.55 – 4.47) and moderate (OR = 0.25, 95% CI = 0.17 – 1.87) OHIP-14-H scores were negative but significant risk indicators of poor self reported oral health (P < 0.009). Significant predictive validity was observed between OHIP-14-H scores and clinical parameters (P < 0.000). CONCLUSION: Translated and culturally adapted OHIP-14-H indicates good reliability and validity among primary school teachers. PMID:29417064

Development and internal validation of a side-specific, multiparametric magnetic resonance imaging-based nomogram for the prediction of extracapsular extension of prostate cancer.

PubMed

Martini, Alberto; Gupta, Akriti; Lewis, Sara C; Cumarasamy, Shivaram; Haines, Kenneth G; Briganti, Alberto; Montorsi, Francesco; Tewari, Ashutosh K

2018-04-19

To develop a nomogram for predicting side-specific extracapsular extension (ECE) for planning nerve-sparing radical prostatectomy. We retrospectively analysed data from 561 patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015. To develop a side-specific predictive model, we considered the prostatic lobes separately. Four variables were included: prostate-specific antigen; highest ipsilateral biopsy Gleason grade; highest ipsilateral percentage core involvement; and ECE on multiparametric magnetic resonance imaging (mpMRI). A multivariable logistic regression analysis was fitted to predict side-specific ECE. A nomogram was built based on the coefficients of the logit function. Internal validation was performed using 'leave-one-out' cross-validation. Calibration was graphically investigated. The decision curve analysis was used to evaluate the net clinical benefit. The study population consisted of 829 side-specific cases, after excluding negative biopsy observations (n = 293). ECE was reported on mpMRI and final pathology in 115 (14%) and 142 (17.1%) cases, respectively. Among these, mpMRI was able to predict ECE correctly in 57 (40.1%) cases. All variables in the model except highest percentage core involvement were predictors of ECE (all P ≤ 0.006). All variables were considered for inclusion in the nomogram. After internal validation, the area under the curve was 82.11%. The model demonstrated excellent calibration and improved clinical risk prediction, especially when compared with relying on mpMRI prediction of ECE alone. When retrospectively applying the nomogram-derived probability, using a 20% threshold for performing nerve-sparing, nine out of 14 positive surgical margins (PSMs) at the site of ECE resulted above the threshold. We developed an easy-to-use model for the prediction of side-specific ECE, and hope it serves as a tool for planning nerve-sparing radical prostatectomy and in the reduction of PSM in future series. © 2018 The Authors BJU International © 2018 BJU International Published by John Wiley & Sons Ltd.

Portuguese-language version of the Chronic Respiratory Questionnaire: a validity and reproducibility study.

PubMed

Moreira, Graciane Laender; Pitta, Fábio; Ramos, Dionei; Nascimento, Cinthia Sousa Carvalho; Barzon, Danielle; Kovelis, Demétria; Colange, Ana Lúcia; Brunetto, Antonio Fernando; Ramos, Ercy Mara Cipulo

2009-08-01

To determine the validity and reproducibility of a Portuguese-language version of the Chronic Respiratory Questionnaire (CRQ) in patients with COPD. A Portuguese-language version of the CRQ (provided by McMaster University, the holder of the questionnaire copyright) was applied to 50 patients with COPD (70 +/- 8 years of age; 32 males; FEV1 = 47 +/- 18% of predicted) on two occasions, one week apart. The CRQ has four domains (dyspnea, fatigue, emotional function, and mastery) and was applied as an interviewer-administered instrument. The Saint George's Respiratory Questionnaire (SGRQ), already validated for use in Brazil, was used as the criterion for validation. Spirometry and the six-minute walk test (6MWT) were performed to analyze the correlations with the CRQ scores. There were no significant CRQ test-retest differences (p > 0.05 for all domains). The test-retest intraclass correlation coefficient was 0.98, 0.97, 0.98 and 0.95 for the dyspnea, fatigue, emotional function and mastery domains, respectively. The Cronbach's alpha coefficient was 0.91. The CRQ domains correlated significantly with the SGRQ domains (-0.30 < r < -0.67; p < 0.05). There were no significant correlations between spirometric variables and the CRQ domains or between the CRQ domains and the 6MWT, with the exception of the fatigue domain (r = 0.30; p = 0.04). The Portuguese-language version of the CRQ proved to be reproducible and valid for use in Brazilian patients with COPD.

Instrument validation process: a case study using the Paediatric Pain Knowledge and Attitudes Questionnaire.

PubMed

Peirce, Deborah; Brown, Janie; Corkish, Victoria; Lane, Marguerite; Wilson, Sally

2016-06-01

To compare two methods of calculating interrater agreement while determining content validity of the Paediatric Pain Knowledge and Attitudes Questionnaire for use with Australian nurses. Paediatric pain assessment and management documentation was found to be suboptimal revealing a need to assess paediatric nurses' knowledge and attitude to pain. The Paediatric Pain Knowledge and Attitudes Questionnaire was selected as it had been reported as valid and reliable in the United Kingdom with student nurses. The questionnaire required content validity determination prior to use in the Australian context. A two phase process of expert review. Ten paediatric nurses completed a relevancy rating of all 68 questionnaire items. In phase two, five pain experts reviewed the items of the questionnaire that scored an unacceptable item level content validity. Item and scale level content validity indices and intraclass correlation coefficients were calculated. In phase one, 31 items received an item level content validity index <0·78 and the scale level content validity index average was 0·80 which were below levels required for acceptable validity. The intraclass correlation coefficient was 0·47. In phase two, 10 items were amended and four items deleted. The revised questionnaire provided a scale level content validity index average >0·90 and an intraclass correlation coefficient of 0·94 demonstrating excellent agreement between raters therefore acceptable content validity. Equivalent outcomes were achieved using the content validity index and the intraclass correlation coefficient. To assess content validity the content validity index has the advantage of providing an item level score and is a simple calculation. The intraclass correlation coefficient requires statistical knowledge, or support, and has the advantage of accounting for the possibility of chance agreement. © 2016 John Wiley & Sons Ltd.

A prediction scheme of tropical cyclone frequency based on lasso and random forest

NASA Astrophysics Data System (ADS)

Tan, Jinkai; Liu, Hexiang; Li, Mengya; Wang, Jun

2017-07-01

This study aims to propose a novel prediction scheme of tropical cyclone frequency (TCF) over the Western North Pacific (WNP). We concerned the large-scale meteorological factors inclusive of the sea surface temperature, sea level pressure, the Niño-3.4 index, the wind shear, the vorticity, the subtropical high, and the sea ice cover, since the chronic change of these factors in the context of climate change would cause a gradual variation of the annual TCF. Specifically, we focus on the correlation between the year-to-year increment of these factors and TCF. The least absolute shrinkage and selection operator (Lasso) method was used for variable selection and dimension reduction from 11 initial predictors. Then, a prediction model based on random forest (RF) was established by using the training samples (1978-2011) for calibration and the testing samples (2012-2016) for validation. The RF model presents a major variation and trend of TCF in the period of calibration, and also fitted well with the observed TCF in the period of validation though there were some deviations. The leave-one-out cross validation of the model exhibited most of the predicted TCF are in consistence with the observed TCF with a high correlation coefficient. A comparison between results of the RF model and the multiple linear regression (MLR) model suggested the RF is more practical and capable of giving reliable results of TCF prediction over the WNP.

Generic buckling curves for specially orthotropic rectangular plates

NASA Technical Reports Server (NTRS)

Brunnelle, E. J.; Oyibo, G. A.

1983-01-01

Using a double affine transformation, the classical buckling equation for specially orthotropic plates and the corresponding virtual work theorem are presented in a particularly simple fashion. These dual representations are characterized by a single material constant, called the generalized rigidity ratio, whose range is predicted to be the closed interval from 0 to 1 (if this prediction is correct then the numerical results using a ratio greater than 1 in the specially orthotropic plate literature are incorrect); when natural boundary conditions are considered a generalized Poisson's ratio is introduced. Thus the buckling results are valid for any specially orthotropic material; hence the curves presented in the text are generic rather than specific. The solution trends are twofold; the buckling coefficients decrease with decreasing generalized rigidity ratio and, when applicable, they decrease with increasing generalized Poisson's ratio. Since the isotropic plate is one limiting case of the above analysis, it is also true that isotropic buckling coefficients decrease with increasing Poission's ratio.

Near infrared spectroscopy for prediction of antioxidant compounds in the honey.

PubMed

Escuredo, Olga; Seijo, M Carmen; Salvador, Javier; González-Martín, M Inmaculada

2013-12-15

The selection of antioxidant variables in honey is first time considered applying the near infrared (NIR) spectroscopic technique. A total of 60 honey samples were used to develop the calibration models using the modified partial least squares (MPLS) regression method and 15 samples were used for external validation. Calibration models on honey matrix for the estimation of phenols, flavonoids, vitamin C, antioxidant capacity (DPPH), oxidation index and copper using near infrared (NIR) spectroscopy has been satisfactorily obtained. These models were optimised by cross-validation, and the best model was evaluated according to multiple correlation coefficient (RSQ), standard error of cross-validation (SECV), ratio performance deviation (RPD) and root mean standard error (RMSE) in the prediction set. The result of these statistics suggested that the equations developed could be used for rapid determination of antioxidant compounds in honey. This work shows that near infrared spectroscopy can be considered as rapid tool for the nondestructive measurement of antioxidant constitutes as phenols, flavonoids, vitamin C and copper and also the antioxidant capacity in the honey. Copyright © 2013 Elsevier Ltd. All rights reserved.

Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis.

PubMed

Kamruzzaman, Mohammed; Sun, Da-Wen; ElMasry, Gamal; Allen, Paul

2013-01-15

Many studies have been carried out in developing non-destructive technologies for predicting meat adulteration, but there is still no endeavor for non-destructive detection and quantification of adulteration in minced lamb meat. The main goal of this study was to develop and optimize a rapid analytical technique based on near-infrared (NIR) hyperspectral imaging to detect the level of adulteration in minced lamb. Initial investigation was carried out using principal component analysis (PCA) to identify the most potential adulterate in minced lamb. Minced lamb meat samples were then adulterated with minced pork in the range 2-40% (w/w) at approximately 2% increments. Spectral data were used to develop a partial least squares regression (PLSR) model to predict the level of adulteration in minced lamb. Good prediction model was obtained using the whole spectral range (910-1700 nm) with a coefficient of determination (R(2)(cv)) of 0.99 and root-mean-square errors estimated by cross validation (RMSECV) of 1.37%. Four important wavelengths (940, 1067, 1144 and 1217 nm) were selected using weighted regression coefficients (Bw) and a multiple linear regression (MLR) model was then established using these important wavelengths to predict adulteration. The MLR model resulted in a coefficient of determination (R(2)(cv)) of 0.98 and RMSECV of 1.45%. The developed MLR model was then applied to each pixel in the image to obtain prediction maps to visualize the distribution of adulteration of the tested samples. The results demonstrated that the laborious and time-consuming tradition analytical techniques could be replaced by spectral data in order to provide rapid, low cost and non-destructive testing technique for adulterate detection in minced lamb meat. Copyright © 2012 Elsevier B.V. All rights reserved.

Modelling the light absorption coefficients of oceanic waters: Implications for underwater optical applications

NASA Astrophysics Data System (ADS)

Prabhakaran, Sai Shri; Sahu, Sanjay Kumar; Dev, Pravin Jeba; Shanmugam, Palanisamy

2018-05-01

Spectral absorption coefficients of particulate (algal and non-algal components) and dissolved substances are modelled and combined with the pure seawater component to determine the total light absorption coefficients of seawater in the Bay of Bengal. Two parameters namely chlorophyll-a (Chl) concentration and turbidity were measured using commercially available instruments with high sampling rates. For modelling the light absorption coefficients of oceanic waters, the measured data are classified into two broad groups - algal dominant and non-algal particle (NAP) dominant. With these criteria the individual absorption coefficients of phytoplankton and NAP were established based on their concentrations using an iterative method. To account for the spectral dependence of absorption by phytoplankton, the wavelength-dependent coefficients were introduced into the model. The CDOM absorption was determined by subtracting the individual absorption coefficients of phytoplankton and NAP from the measured total absorption data and then related to the Chl concentration. Validity of the model is assessed based on independent in-situ data from certain discrete locations in the Bay of Bengal. The total absorption coefficients estimated using the new model by considering the contributions of algal, non-algal and CDOM have good agreement with the measured total absorption data with the error range of 6.9 to 28.3%. Results obtained by the present model are important for predicting the propagation of the radiant energy within the ocean and interpreting remote sensing observation data.

Validation of clinic weights from electronic health records against standardized weight measurements in weight loss trials.

PubMed

Xiao, Lan; Lv, Nan; Rosas, Lisa G; Au, David; Ma, Jun

2017-02-01

To validate clinic weights in electronic health records against researcher-measured weights for outcome assessment in weight loss trials. Clinic and researcher-measured weights from a published trial (BE WELL) were compared using Lin's concordance correlation coefficient, Bland and Altman's limits of agreement, and polynomial regression model. Changes in clinic and researcher-measured weights in BE WELL and another trial, E-LITE, were analyzed using growth curve modeling. Among BE WELL (n = 330) and E-LITE (n = 241) participants, 96% and 90% had clinic weights (mean [SD] of 5.8 [6.1] and 3.7 [3.9] records) over 12 and 15 months of follow-up, respectively. The concordance correlation coefficient was 0.99, and limits of agreement plots showed no pattern between or within treatment groups, suggesting overall good agreement between researcher-measured and nearest-in-time clinic weights up to 3 months. The 95% confidence intervals for predicted percent differences fell within ±3% for clinic weights within 3 months of the researcher-measured weights. Furthermore, the growth curve slopes for clinic and researcher-measured weights by treatment group did not differ significantly, suggesting similar inferences about treatment effects over time, in both trials. Compared with researcher-measured weights, close-in-time clinic weights showed high agreement and inference validity. Clinic weights could be a valid pragmatic outcome measure in weight loss studies. © 2017 The Obesity Society.

Prediction Models for 30-Day Mortality and Complications After Total Knee and Hip Arthroplasties for Veteran Health Administration Patients With Osteoarthritis.

PubMed

Harris, Alex Hs; Kuo, Alfred C; Bowe, Thomas; Gupta, Shalini; Nordin, David; Giori, Nicholas J

2018-05-01

Statistical models to preoperatively predict patients' risk of death and major complications after total joint arthroplasty (TJA) could improve the quality of preoperative management and informed consent. Although risk models for TJA exist, they have limitations including poor transparency and/or unknown or poor performance. Thus, it is currently impossible to know how well currently available models predict short-term complications after TJA, or if newly developed models are more accurate. We sought to develop and conduct cross-validation of predictive risk models, and report details and performance metrics as benchmarks. Over 90 preoperative variables were used as candidate predictors of death and major complications within 30 days for Veterans Health Administration patients with osteoarthritis who underwent TJA. Data were split into 3 samples-for selection of model tuning parameters, model development, and cross-validation. C-indexes (discrimination) and calibration plots were produced. A total of 70,569 patients diagnosed with osteoarthritis who received primary TJA were included. C-statistics and bootstrapped confidence intervals for the cross-validation of the boosted regression models were highest for cardiac complications (0.75; 0.71-0.79) and 30-day mortality (0.73; 0.66-0.79) and lowest for deep vein thrombosis (0.59; 0.55-0.64) and return to the operating room (0.60; 0.57-0.63). Moderately accurate predictive models of 30-day mortality and cardiac complications after TJA in Veterans Health Administration patients were developed and internally cross-validated. By reporting model coefficients and performance metrics, other model developers can test these models on new samples and have a procedure and indication-specific benchmark to surpass. Published by Elsevier Inc.

Development and initial validation of primary care provider mental illness management and team-based care self-efficacy scales.

PubMed

Loeb, Danielle F; Crane, Lori A; Leister, Erin; Bayliss, Elizabeth A; Ludman, Evette; Binswanger, Ingrid A; Kline, Danielle M; Smith, Meredith; deGruy, Frank V; Nease, Donald E; Dickinson, L Miriam

Develop and validate self-efficacy scales for primary care provider (PCP) mental illness management and team-based care participation. We developed three self-efficacy scales: team-based care (TBC), mental illness management (MIM), and chronic medical illness (CMI). We developed the scales using Bandura's Social Cognitive Theory as a guide. The survey instrument included items from previously validated scales on team-based care and mental illness management. We administered a mail survey to 900 randomly selected Colorado physicians. We conducted exploratory principal factor analysis with oblique rotation. We constructed self-efficacy scales and calculated standardized Cronbach's alpha coefficients to test internal consistency. We calculated correlation coefficients between the MIM and TBC scales and previously validated measures related to each scale to evaluate convergent validity. We tested correlations between the TBC and the measures expected to correlate with the MIM scale and vice versa to evaluate discriminant validity. PCPs (n=402, response rate=49%) from diverse practice settings completed surveys. Items grouped into factors as expected. Cronbach's alphas were 0.94, 0.88, and 0.83 for TBC, MIM, and CMI scales respectively. In convergent validity testing, the TBC scale was correlated as predicted with scales assessing communications strategies, attitudes toward teams, and other teamwork indicators (r=0.25 to 0.40, all statistically significant). Likewise, the MIM scale was significantly correlated with several items about knowledge and experience managing mental illness (r=0.24 to 41, all statistically significant). As expected in discriminant validity testing, the TBC scale had only very weak correlations with the mental illness knowledge and experience managing mental illness items (r=0.03 to 0.12). Likewise, the MIM scale was only weakly correlated with measures of team-based care (r=0.09 to.17). This validation study of MIM and TBC self-efficacy scales showed high internal validity and good construct validity. Copyright © 2016 Elsevier Inc. All rights reserved.

The VCOP Scale: a measure of overprotection in parents of physically vulnerable children.

PubMed

Wright, L; Mullen, T; West, K; Wyatt, P

1993-11-01

A scale is developed for measuring the overprotecting vs. optimal developmental stimulation tendencies for parents of physically "vulnerable" children. A series of items were administered to parents whose parenting techniques had been rated as either highly overprotective or as optimal by a group of MDs and other professionals. Correlations were estimated between each of the items and parental tendencies as rated by professionals. Twenty-eight items were selected that provided maximum prediction of over-protection. The resulting R2 was extraordinarily high (.94). Coefficient alpha and test-retest coefficients were acceptable. It is hoped that release of the new instrument (VCOPS) at this time will allow others to join in determining the clinical and experimental validity of this scale.

Predictive validity of disability rating scale in determining functional outcome in patients with severe traumatic brain injury.

PubMed

Deepika, Akhil; Devi, B Indira; Shukla, Dhaval

2017-01-01

Most patients with severe traumatic brain injury (TBI) are discharged when they have still not recovered completely. Many such patients are not available for follow up. We conducted this study to determine whether the condition at discharge from acute care setting, as assessed with disability rating scale (DRS), correlates with functional outcome at follow up. This study was conducted at a Neurosurgical intensive care unit (ICU) of a tertiary care referral center. This was a prospective observational study. Patients admitted to ICU with a diagnosis of severe TBI were enrolled for the study. On the day of discharge, all patients underwent DRS assessment. A final assessment was performed using Glasgow outcome scale extended (GOSE) at 6 months after discharge from the hospital. The correlation between the DRS scores at the time of discharge with DRS scores and GOSE categories at 6 months after discharge was determined using Spearman's rho correlation coefficient. A total of 88 patients were recruited for the study. The correlation coefficient of DRS at discharge for DRS at 6 months was 0.536 and for GOSE was -0.553. The area under the curve of DRS score at discharge for predicting unfavorable outcome and mortality at 6 months was 0.770 and 0.820, respectively. The predictive validity of DRS is fair to good in determining GOSE at follow-up. Pending availability of a more accurate outcome assessment tool, DRS at discharge can be used as a surrogate outcome for GOSE at follow up.

Short communication: Variations in major mineral contents of Mediterranean buffalo milk and application of Fourier-transform infrared spectroscopy for their prediction.

PubMed

Stocco, G; Cipolat-Gotet, C; Bonfatti, V; Schiavon, S; Bittante, G; Cecchinato, A

2016-11-01

The aims of this study were (1) to assess variability in the major mineral components of buffalo milk, (2) to estimate the effect of certain environmental sources of variation on the major minerals during lactation, and (3) to investigate the possibility of using Fourier-transform infrared (FTIR) spectroscopy as an indirect, noninvasive tool for routine prediction of the mineral content of buffalo milk. A total of 173 buffaloes reared in 5 herds were sampled once during the morning milking. Milk samples were analyzed for Ca, P, K, and Mg contents within 3h of sample collection using inductively coupled plasma optical emission spectrometry. A Milkoscan FT2 (Foss, Hillerød, Denmark) was used to acquire milk spectra over the spectral range from 5,000 to 900 wavenumber/cm. Prediction models were built using a partial least square approach, and cross-validation was used to assess the prediction accuracy of FTIR. Prediction models were validated using a 4-fold random cross-validation, thus dividing the calibration-test set in 4 folds, using one of them to check the results (prediction models) and the remaining 3 to develop the calibration models. Buffalo milk minerals averaged 162, 117, 86, and 14.4mg/dL of milk for Ca, P, K, and Mg, respectively. Herd and days in milk were the most important sources of variation in the traits investigated. Parity slightly affected only Ca content. Coefficients of determination of cross-validation between the FTIR-predicted and the measured values were 0.71, 0.70, and 0.72 for Ca, Mg, and P, respectively, whereas prediction accuracy was lower for K (0.55). Our findings reveal FTIR to be an unsuitable tool when milk mineral content needs to be predicted with high accuracy. Predictions may play a role as indicator traits in selective breeding (if the additive genetic correlation between FTIR predictions and measures of milk minerals is high enough) or in monitoring the milk of buffalo populations for dairy industry purposes. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms.

PubMed

El Hajji, Feras W D; Scullin, Claire; Scott, Michael G; McElnay, James C

2015-04-01

This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized. © 2014 John Wiley & Sons, Ltd.

Psychometric properties of the modified RESIDE physical activity questionnaire among low-income overweight women.

PubMed

Jones, Sydney A; Evenson, Kelly R; Johnston, Larry F; Trost, Stewart G; Samuel-Hodge, Carmen; Jewell, David A; Kraschnewski, Jennifer L; Keyserling, Thomas C

2015-01-01

This study explored the criterion-related validity and test-retest reliability of the modified RESIDential Environment physical activity questionnaire and whether the instrument's validity varied by body mass index, education, race/ethnicity, or employment status. Validation study using baseline data collected for randomized trial of a weight loss intervention. Participants recruited from health departments wore an ActiGraph accelerometer and self-reported non-occupational walking, moderate and vigorous physical activity on the modified RESIDential Environment questionnaire. We assessed validity (n=152) using Spearman correlation coefficients, and reliability (n=57) using intraclass correlation coefficients. When compared to steps, moderate physical activity, and bouts of moderate/vigorous physical activity measured by accelerometer, these questionnaire measures showed fair evidence for validity: recreational walking (Spearman correlation coefficients 0.23-0.36), total walking (Spearman correlation coefficients 0.24-0.37), and total moderate physical activity (Spearman correlation coefficients 0.18-0.36). Correlations for self-reported walking and moderate physical activity were higher among unemployed participants and women with lower body mass indices. Generally no other variability in the validity of the instrument was found. Evidence for reliability of RESIDential Environment measures of recreational walking, total walking, and total moderate physical activity was substantial (intraclass correlation coefficients 0.56-0.68). Evidence for questionnaire validity and reliability varied by activity domain and was strongest for walking measures. The questionnaire may capture physical activity less accurately among women with higher body mass indices and employed participants. Capturing occupational activity, specifically walking at work, may improve questionnaire validity. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Application of Visible/Near-Infrared Spectroscopy in the Prediction of Azodicarbonamide in Wheat Flour.

PubMed

Che, Wenkai; Sun, Laijun; Zhang, Qian; Zhang, Dan; Ye, Dandan; Tan, Wenyi; Wang, Lekai; Dai, Changjun

2017-10-01

Azodicarbonamide is wildly used in flour industry as a flour gluten fortifier in many countries, but it was proved by some researches to be dangerous or unhealthy for people and not suitable to be added in flour. Applying a rapid, convenient, and noninvasive technique in food analytical procedure for the safety inspection has become an urgent need. This paper used Vis/NIR reflectance spectroscopy analysis technology, which is based on the physical property analysis to predict the concentration of azodicarbonamide in flour. Spectral data in range from 400 to 2498 nm were obtained by scanning 101 samples which were prepared using the stepwise dilution method. Furthermore, the combination of leave-one-out cross-validation and Mahalanobis distance method was used to eliminate abnormal spectral data, and correlation coefficient method was used to choose characteristic wavebands. Partial least squares, back propagation neural network, and radial basis function were used to establish prediction model separately. By comparing the prediction results between 3 models, the radial basis function model has the best prediction results whose correlation coefficients (R), root mean square error of prediction (RMSEP), and ratio of performance to deviation (RPD) reached 0.99996, 0.5467, and 116.5858, respectively. Azodicarbonamide has been banned or limited in many countries. This paper proposes a method to predict azodicarbonamide concentrate in wheat flour, which will be used for a rapid, convenient, and noninvasive detection device. © 2017 Institute of Food Technologists®.

Using random forests to explore the effects of site attributes and soil properties on near-saturated and saturated hydraulic conductivity

NASA Astrophysics Data System (ADS)

Jorda, Helena; Koestel, John; Jarvis, Nicholas

2014-05-01

Knowledge of the near-saturated and saturated hydraulic conductivity of soil is fundamental for understanding important processes like groundwater contamination risks or runoff and soil erosion. Hydraulic conductivities are however difficult and time-consuming to determine by direct measurements, especially at the field scale or larger. So far, pedotransfer functions do not offer an especially reliable alternative since published approaches exhibit poor prediction performances. In our study we aimed at building pedotransfer functions by growing random forests (a statistical learning approach) on 486 datasets from the meta-database on tension-disk infiltrometer measurements collected from peer-reviewed literature and recently presented by Jarvis et al. (2013, Influence of soil, land use and climatic factors on the hydraulic conductivity of soil. Hydrol. Earth Syst. Sci. 17(12), 5185-5195). When some data from a specific source publication were allowed to enter the training set whereas others were used for validation, the results of a 10-fold cross-validation showed reasonable coefficients of determination of 0.53 for hydraulic conductivity at 10 cm tension, K10, and 0.41 for saturated conductivity, Ks. The estimated average annual temperature and precipitation at the site were the most important predictors for K10, while bulk density and estimated average annual temperature were most important for Ks prediction. The soil organic carbon content and the diameter of the disk infiltrometer were also important for the prediction of both K10 and Ks. However, coefficients of determination were around zero when all datasets of a specific source publication were excluded from the training set and exclusively used for validation. This may indicate experimenter bias, or that better predictors have to be found or that a larger dataset has to be used to infer meaningful pedotransfer functions for saturated and near-saturated hydraulic conductivities. More research is in progress to further elucidate this question.

Curvelet-domain multiple matching method combined with cubic B-spline function

NASA Astrophysics Data System (ADS)

Wang, Tong; Wang, Deli; Tian, Mi; Hu, Bin; Liu, Chengming

2018-05-01

Since the large amount of surface-related multiple existed in the marine data would influence the results of data processing and interpretation seriously, many researchers had attempted to develop effective methods to remove them. The most successful surface-related multiple elimination method was proposed based on data-driven theory. However, the elimination effect was unsatisfactory due to the existence of amplitude and phase errors. Although the subsequent curvelet-domain multiple-primary separation method achieved better results, poor computational efficiency prevented its application. In this paper, we adopt the cubic B-spline function to improve the traditional curvelet multiple matching method. First, select a little number of unknowns as the basis points of the matching coefficient; second, apply the cubic B-spline function on these basis points to reconstruct the matching array; third, build constraint solving equation based on the relationships of predicted multiple, matching coefficients, and actual data; finally, use the BFGS algorithm to iterate and realize the fast-solving sparse constraint of multiple matching algorithm. Moreover, the soft-threshold method is used to make the method perform better. With the cubic B-spline function, the differences between predicted multiple and original data diminish, which results in less processing time to obtain optimal solutions and fewer iterative loops in the solving procedure based on the L1 norm constraint. The applications to synthetic and field-derived data both validate the practicability and validity of the method.

The validity of the potential model in predicting the structural, dynamical, thermodynamic properties of the unary and binary mixture of water-alcohol: Methanol-water case

NASA Astrophysics Data System (ADS)

Obeidat, Abdalla; Abu-Ghazleh, Hind

2018-06-01

Two intermolecular potential models of methanol (TraPPE-UA and OPLS-AA) have been used in order to examine their validity in reproducing the selected structural, dynamical, and thermodynamic properties in the unary and binary systems. These two models are combined with two water models (SPC/E and TIP4P). The temperature dependence of density, surface tension, diffusion and structural properties for the unary system has been computed over specific range of temperatures (200-300K). The very good performance of the TraPPE-UA potential model in predicting surface tension, diffusion, structure, and density of the unary system led us to examine its accuracy and performance in its aqueous solution. In the binary system the same properties were examined, using different mole fractions of methanol. The TraPPE-UA model combined with TIP4P-water shows a very good agreement with the experimental results for density and surface tension properties; whereas the OPLS-AA combined with SPCE-water shows a very agreement with experimental results regarding the diffusion coefficients. Two different approaches have been used in calculating the diffusion coefficient in the mixture, namely the Einstein equation (EE) and Green-Kubo (GK) method. Our results show the advantageous of applying GK over EE in reproducing the experimental results and in saving computer time.

Simultaneous Determination of Metamizole, Thiamin and Pyridoxin Using UV-Spectroscopy in Combination with Multivariate Calibration

PubMed Central

Chotimah, Chusnul; Sudjadi; Riyanto, Sugeng; Rohman, Abdul

2015-01-01

Purpose: Analysis of drugs in multicomponent system officially is carried out using chromatographic technique, however, this technique is too laborious and involving sophisticated instrument. Therefore, UV-VIS spectrophotometry coupled with multivariate calibration of partial least square (PLS) for quantitative analysis of metamizole, thiamin and pyridoxin is developed in the presence of cyanocobalamine without any separation step. Methods: The calibration and validation samples are prepared. The calibration model is prepared by developing a series of sample mixture consisting these drugs in certain proportion. Cross validation of calibration sample using leave one out technique is used to identify the smaller set of components that provide the greatest predictive ability. The evaluation of calibration model was based on the coefficient of determination (R2) and root mean square error of calibration (RMSEC). Results: The results showed that the coefficient of determination (R2) for the relationship between actual values and predicted values for all studied drugs was higher than 0.99 indicating good accuracy. The RMSEC values obtained were relatively low, indicating good precision. The accuracy and presision results of developed method showed no significant difference compared to those obtained by official method of HPLC. Conclusion: The developed method (UV-VIS spectrophotometry in combination with PLS) was succesfully used for analysis of metamizole, thiamin and pyridoxin in tablet dosage form. PMID:26819934

Supervised artificial neural network-based method for conversion of solar radiation data (case study: Algeria)

NASA Astrophysics Data System (ADS)

Laidi, Maamar; Hanini, Salah; Rezrazi, Ahmed; Yaiche, Mohamed Redha; El Hadj, Abdallah Abdallah; Chellali, Farouk

2017-04-01

In this study, a backpropagation artificial neural network (BP-ANN) model is used as an alternative approach to predict solar radiation on tilted surfaces (SRT) using a number of variables involved in physical process. These variables are namely the latitude of the site, mean temperature and relative humidity, Linke turbidity factor and Angstrom coefficient, extraterrestrial solar radiation, solar radiation data measured on horizontal surfaces (SRH), and solar zenith angle. Experimental solar radiation data from 13 stations spread all over Algeria around the year (2004) were used for training/validation and testing the artificial neural networks (ANNs), and one station was used to make the interpolation of the designed ANN. The ANN model was trained, validated, and tested using 60, 20, and 20 % of all data, respectively. The configuration 8-35-1 (8 inputs, 35 hidden, and 1 output neurons) presented an excellent agreement between the prediction and the experimental data during the test stage with determination coefficient of 0.99 and root meat squared error of 5.75 Wh/m2, considering a three-layer feedforward backpropagation neural network with Levenberg-Marquardt training algorithm, a hyperbolic tangent sigmoid and linear transfer function at the hidden and the output layer, respectively. This novel model could be used by researchers or scientists to design high-efficiency solar devices that are usually tilted at an optimum angle to increase the solar incident on the surface.

Development and validation of a tool to evaluate the quality of medical education websites in pathology

PubMed Central

Alyusuf, Raja H.; Prasad, Kameshwar; Abdel Satir, Ali M.; Abalkhail, Ali A.; Arora, Roopa K.

2013-01-01

Background: The exponential use of the internet as a learning resource coupled with varied quality of many websites, lead to a need to identify suitable websites for teaching purposes. Aim: The aim of this study is to develop and to validate a tool, which evaluates the quality of undergraduate medical educational websites; and apply it to the field of pathology. Methods: A tool was devised through several steps of item generation, reduction, weightage, pilot testing, post-pilot modification of the tool and validating the tool. Tool validation included measurement of inter-observer reliability; and generation of criterion related, construct related and content related validity. The validated tool was subsequently tested by applying it to a population of pathology websites. Results and Discussion: Reliability testing showed a high internal consistency reliability (Cronbach's alpha = 0.92), high inter-observer reliability (Pearson's correlation r = 0.88), intraclass correlation coefficient = 0.85 and κ =0.75. It showed high criterion related, construct related and content related validity. The tool showed moderately high concordance with the gold standard (κ =0.61); 92.2% sensitivity, 67.8% specificity, 75.6% positive predictive value and 88.9% negative predictive value. The validated tool was applied to 278 websites; 29.9% were rated as recommended, 41.0% as recommended with caution and 29.1% as not recommended. Conclusion: A systematic tool was devised to evaluate the quality of websites for medical educational purposes. The tool was shown to yield reliable and valid inferences through its application to pathology websites. PMID:24392243

Validating computational predictions of night-time ventilation in Stanford's Y2E2 building

NASA Astrophysics Data System (ADS)

Chen, Chen; Lamberti, Giacomo; Gorle, Catherine

2017-11-01

Natural ventilation can significantly reduce building energy consumption, but robust design is a challenging task. We previously presented predictions of natural ventilation performance in Stanford's Y2E2 building using two models with different levels of fidelity, embedded in an uncertainty quantification framework to identify the dominant uncertain parameters and predict quantified confidence intervals. The results showed a slightly high cooling rate for the volume-averaged temperature, and the initial thermal mass temperature and window discharge coefficients were found to have an important influence on the results. To further investigate the potential role of these parameters on the observed discrepancies, the current study is performing additional measurements in the Y2E2 building. Wall temperatures are recorded throughout the nightflush using thermocouples; flow rates through windows are measured using hotwires; and spatial variability in the air temperature is explored. The measured wall temperatures are found the be within the range of our model assumptions, and the measured velocities agree reasonably well with our CFD predications. Considerable local variations in the indoor air temperature have been recorded, largely explaining the discrepancies in our earlier validation study. Future work will therefore focus on a local validation of the CFD results with the measurements. Center for Integrated Facility Engineering (CIFE).

Accuracy of near infrared spectroscopy for prediction of chemical composition, salt content and free amino acids in dry-cured ham.

PubMed

Prevolnik, Maja; Škrlep, Martin; Janeš, Lucija; Velikonja-Bolta, Spela; Škorjanc, Dejan; Čandek-Potokar, Marjeta

2011-06-01

The capability of near infrared (NIR) spectroscopy was examined for the purposes of quality control of the traditional Slovenian dry-cured ham "Kraški pršut." Predictive models were developed for moisture, salt, protein, non-protein nitrogen, intramuscular fat and free amino acids in biceps femoris muscle (n = 135). The models' quality was assessed using statistical parameters: coefficient of determination (R(2)) and standard error (se) of cross-validation (CV) and external validation (EV). Residual predictive deviation (RPD) was also assessed. Best results were obtained for salt content and salt percentage in moisture/dry matter (R(CV)(2)>0.90, RPD>3.0), it was satisfactory for moisture, non-protein nitrogen, intramuscular fat and total free amino acids (R(CV)(2) = 0.75-0.90, RPD = 2.0-3.0), while not so for protein content and proteolysis index (R(CV)(2) = 0.65-0.75, RPD<2.0). Calibrations for individual free amino acids yielded R(CV)(2) from 0.40 to 0.90 and RPD from 1.3 to 2.9. Additional external validation of models on independent samples yielded comparable results. Based on the results, NIR spectroscopy can replace chemical methods in quality control of dry-cured ham. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reliability and validity of the revised Gibson Test of Cognitive Skills, a computer-based test battery for assessing cognition across the lifespan.

PubMed

Moore, Amy Lawson; Miller, Terissa M

2018-01-01

The purpose of the current study is to evaluate the validity and reliability of the revised Gibson Test of Cognitive Skills, a computer-based battery of tests measuring short-term memory, long-term memory, processing speed, logic and reasoning, visual processing, as well as auditory processing and word attack skills. This study included 2,737 participants aged 5-85 years. A series of studies was conducted to examine the validity and reliability using the test performance of the entire norming group and several subgroups. The evaluation of the technical properties of the test battery included content validation by subject matter experts, item analysis and coefficient alpha, test-retest reliability, split-half reliability, and analysis of concurrent validity with the Woodcock Johnson III Tests of Cognitive Abilities and Tests of Achievement. Results indicated strong sources of evidence of validity and reliability for the test, including internal consistency reliability coefficients ranging from 0.87 to 0.98, test-retest reliability coefficients ranging from 0.69 to 0.91, split-half reliability coefficients ranging from 0.87 to 0.91, and concurrent validity coefficients ranging from 0.53 to 0.93. The Gibson Test of Cognitive Skills-2 is a reliable and valid tool for assessing cognition in the general population across the lifespan.

Validation of a New Metric for Assessing the Integration of Health Protection and Health Promotion in a Sample of Small- and Medium-Sized Employer Groups.

PubMed

Williams, Jessica A R; Nelson, Candace C; Cabán-Martinez, Alberto J; Katz, Jeffrey N; Wagner, Gregory R; Pronk, Nicolaas P; Sorensen, Glorian; McLellan, Deborah L

2015-09-01

To conduct validation analyses for a new measure of the integration of worksite health protection and health promotion approaches developed in earlier research. A survey of small- to medium-sized employers located in the United States was conducted between October 2013 and March 2014 (n = 111). Cronbach α coefficient was used to assess reliability, and Pearson correlation coefficients were used to assess convergent validity. The integration score was positively associated with the measures of occupational safety and health and health promotion activities/policies-supporting its convergent validity (Pearson correlation coefficients of 0.32 to 0.47). Cronbach α coefficient was 0.94, indicating excellent reliability. The integration score seems to be a promising tool for assessing integration of health promotion and health protection. Further work is needed to test its dimensionality and validate its use in other samples.

The Detection and Quantification of Adulteration in Ground Roasted Asian Palm Civet Coffee Using Near-Infrared Spectroscopy in Tandem with Chemometrics

NASA Astrophysics Data System (ADS)

Suhandy, D.; Yulia, M.; Ogawa, Y.; Kondo, N.

2018-05-01

In the present research, an evaluation of using near infrared (NIR) spectroscopy in tandem with full spectrum partial least squares (FS-PLS) regression for quantification of degree of adulteration in civet coffee was conducted. A number of 126 ground roasted coffee samples with degree of adulteration 0-51% were prepared. Spectral data were acquired using a NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement in the range of 1300-2500 nm. The samples were divided into two groups calibration sample set (84 samples) and prediction sample set (42 samples). The calibration model was developed on original spectra using FS-PLS regression with full-cross validation method. The calibration model exhibited the determination coefficient R2=0.96 for calibration and R2=0.92 for validation. The prediction resulted in low root mean square error of prediction (RMSEP) (4.67%) and high ratio prediction to deviation (RPD) (3.75). In conclusion, the degree of adulteration in civet coffee have been quantified successfully by using NIR spectroscopy and FS-PLS regression in a non-destructive, economical, precise, and highly sensitive method, which uses very simple sample preparation.

QSAR studies on triazole derivatives as sglt inhibitors via CoMFA and CoMSIA

NASA Astrophysics Data System (ADS)

Zhi, Hui; Zheng, Junxia; Chang, Yiqun; Li, Qingguo; Liao, Guochao; Wang, Qi; Sun, Pinghua

2015-10-01

Forty-six sodium-dependent glucose cotransporters-2 (SGLT-2) inhibitors with hypoglycemic activity were selected to develop three-dimensional quantitative structure-activity relationship (3D-QSAR) using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. A training set of 39 compounds were used to build up the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 7 compounds was used for the external validation. The CoMFA model predicted a q2 value of 0.792 and an r2 value of 0.985. The best CoMSIA model predicted a q2 value of 0.633 and an r2 value of 0.895 based on a combination of steric, electrostatic, hydrophobic and hydrogen-bond acceptor effects. The predictive correlation coefficients (rpred2) of CoMFA and CoMSIA models were 0.872 and 0.839, respectively. The analysis of the contour maps from each model provided insight into the structural requirements for the development of more active sglt inhibitors, and on the basis of the models 8 new sglt inhibitors were designed and predicted.

Volatile profile analysis and quality prediction of Longjing tea (Camellia sinensis) by HS-SPME/GC-MS

PubMed Central

Lin, Jie; Dai, Yi; Guo, Ya-nan; Xu, Hai-rong; Wang, Xiao-chang

2012-01-01

This study aimed to analyze the volatile chemical profile of Longjing tea, and further develop a prediction model for aroma quality of Longjing tea based on potent odorants. A total of 21 Longjing samples were analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Pearson’s linear correlation analysis and partial least square (PLS) regression were applied to investigate the relationship between sensory aroma scores and the volatile compounds. Results showed that 60 volatile compounds could be commonly detected in this famous green tea. Terpenes and esters were two major groups characterized, representing 33.89% and 15.53% of the total peak area respectively. Ten compounds were determined to contribute significantly to the perceived aroma quality of Longjing tea, especially linalool (0.701), nonanal (0.738), (Z)-3-hexenyl hexanoate (−0.785), and β-ionone (−0.763). On the basis of these 10 compounds, a model (correlation coefficient of 89.4% and cross-validated correlation coefficient of 80.4%) was constructed to predict the aroma quality of Longjing tea. Summarily, this study has provided a novel option for quality prediction of green tea based on HS-SPME/GC-MS technique. PMID:23225852

Integration of experimental and computational methods for identifying geometric, thermal and diffusive properties of biomaterials

NASA Astrophysics Data System (ADS)

Weres, Jerzy; Kujawa, Sebastian; Olek, Wiesław; Czajkowski, Łukasz

2016-04-01

Knowledge of physical properties of biomaterials is important in understanding and designing agri-food and wood processing industries. In the study presented in this paper computational methods were developed and combined with experiments to enhance identification of agri-food and forest product properties, and to predict heat and water transport in such products. They were based on the finite element model of heat and water transport and supplemented with experimental data. Algorithms were proposed for image processing, geometry meshing, and inverse/direct finite element modelling. The resulting software system was composed of integrated subsystems for 3D geometry data acquisition and mesh generation, for 3D geometry modelling and visualization, and for inverse/direct problem computations for the heat and water transport processes. Auxiliary packages were developed to assess performance, accuracy and unification of data access. The software was validated by identifying selected properties and using the estimated values to predict the examined processes, and then comparing predictions to experimental data. The geometry, thermal conductivity, specific heat, coefficient of water diffusion, equilibrium water content and convective heat and water transfer coefficients in the boundary layer were analysed. The estimated values, used as an input for simulation of the examined processes, enabled reduction in the uncertainty associated with predictions.

Determination and prediction of octanol-air partition coefficients for organophosphate flame retardants.

PubMed

Wang, Qingzhi; Zhao, Hongxia; Wang, Yan; Xie, Qing; Chen, Jingwen; Quan, Xie

2017-11-01

Organophosphate flame retardants (OPFRs) have attracted wide concerns due to their toxicities and ubiquitous occurrence in the environment. In this work, Octanol-air partition coefficient (K OA ) for 14 OPFRs including 4 halogenated alkyl-, 5 aryl- and 5 alkyl-OPFRs, were estimated as a function of temperature using a gas chromatographic retention time (GC-RT) method. Their log K OA-GC values and internal energies of phase transfer (Δ OA U/kJmol -1 ) ranged from 8.03 to 13.0 and from 69.7 to 149, respectively. Substitution pattern and molar volume (V M ) were found to be capable of influencing log K OA-GC values of OPFRs. The halogenated alkyl-OPFRs had higher log K OA-GC values than aryl- or alkyl-OPFRs. The bigger the molar volume was, the greater the log K OA-GC values increased. In addition, a predicted model of log K OA-GC versus different relative retention times (RRTs) was developed with a high cross-validated value (Q 2 (cum) ) of 0.951, indicating a good predictive ability and stability. Therefore, the log K OA-GC values of the remaining OPFRs can be predicted by using their RRTs on different GC columns. Copyright © 2017 Elsevier Inc. All rights reserved.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

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.

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

Youkhana, Adel H.; Ogoshi, Richard M.; Kiniry, James R.

Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C 4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewablemore » energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R 2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C4 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.« less

Viscoelastic finite element analysis of residual stresses in porcelain-veneered zirconia dental crowns.

PubMed

Kim, Jeongho; Dhital, Sukirti; Zhivago, Paul; Kaizer, Marina R; Zhang, Yu

2018-06-01

The main problem of porcelain-veneered zirconia (PVZ) dental restorations is chipping and delamination of veneering porcelain owing to the development of deleterious residual stresses during the cooling phase of veneer firing. The aim of this study is to elucidate the effects of cooling rate, thermal contraction coefficient and elastic modulus on residual stresses developed in PVZ dental crowns using viscoelastic finite element methods (VFEM). A three-dimensional VFEM model has been developed to predict residual stresses in PVZ structures using ABAQUS finite element software and user subroutines. First, the newly established model was validated with experimentally measured residual stress profiles using Vickers indentation on flat PVZ specimens. An excellent agreement between the model prediction and experimental data was found. Then, the model was used to predict residual stresses in more complex anatomically-correct crown systems. Two PVZ crown systems with different thermal contraction coefficients and porcelain moduli were studied: VM9/Y-TZP and LAVA/Y-TZP. A sequential dual-step finite element analysis was performed: heat transfer analysis and viscoelastic stress analysis. Controlled and bench convection cooling rates were simulated by applying different convective heat transfer coefficients 1.7E-5 W/mm 2 °C (controlled cooling) and 0.6E-4 W/mm 2 °C (bench cooling) on the crown surfaces exposed to the air. Rigorous viscoelastic finite element analysis revealed that controlled cooling results in lower maximum stresses in both veneer and core layers for the two PVZ systems relative to bench cooling. Better compatibility of thermal contraction coefficients between porcelain and zirconia and a lower porcelain modulus reduce residual stresses in both layers. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validity of Rorschach Inkblot scores for discriminating psychopaths from non-psychopaths in forensic populations: a meta-analysis.

PubMed

Wood, James M; Lilienfeld, Scott O; Nezworski, M Teresa; Garb, Howard N; Allen, Keli Holloway; Wildermuth, Jessica L

2010-06-01

Gacono and Meloy (2009) have concluded that the Rorschach Inkblot Test is a sensitive instrument with which to discriminate psychopaths from nonpsychopaths. We examined the association of psychopathy with 37 Rorschach variables in a meta-analytic review of 173 validity coefficients derived from 22 studies comprising 780 forensic participants. All studies included the Hare Psychopathy Checklist or one of its versions (Hare, 1980, 1991, 2003) and Exner's (2003) Comprehensive System for the Rorschach. Mean validity coefficients of Rorschach variables in the meta-analysis ranged from -.113 to .239, with a median validity of .070 and a mean validity of .062. Psychopathy displayed a significant and medium-sized association with the number of Aggressive Potential responses (weighted mean validity coefficient = .232) and small but significant associations with the Sum of Texture responses, Cooperative Movement = 0, the number of Personal responses, and the Egocentricity Index (weighted mean validity coefficients = .097 to .159). The remaining 32 Rorschach variables were not significantly related to psychopathy. The present findings contradict the view that the Rorschach is a clinically sensitive instrument for discriminating psychopaths from nonpsychopaths.

The validation of a human force model to predict dynamic forces resulting from multi-joint motions

NASA Technical Reports Server (NTRS)

Pandya, Abhilash K.; Maida, James C.; Aldridge, Ann M.; Hasson, Scott M.; Woolford, Barbara J.

1992-01-01

The development and validation is examined of a dynamic strength model for humans. This model is based on empirical data. The shoulder, elbow, and wrist joints were characterized in terms of maximum isolated torque, or position and velocity, in all rotational planes. This data was reduced by a least squares regression technique into a table of single variable second degree polynomial equations determining torque as a function of position and velocity. The isolated joint torque equations were then used to compute forces resulting from a composite motion, in this case, a ratchet wrench push and pull operation. A comparison of the predicted results of the model with the actual measured values for the composite motion indicates that forces derived from a composite motion of joints (ratcheting) can be predicted from isolated joint measures. Calculated T values comparing model versus measured values for 14 subjects were well within the statistically acceptable limits and regression analysis revealed coefficient of variation between actual and measured to be within 0.72 and 0.80.

Spatial and temporal predictions of agricultural land prices using DSM techniques.

NASA Astrophysics Data System (ADS)

Carré, F.; Grandgirard, D.; Diafas, I.; Reuter, H. I.; Julien, V.; Lemercier, B.

2009-04-01

Agricultural land prices highly impacts land accessibility to farmers and by consequence the evolution of agricultural landscapes (crop changes, land conversion to urban infrastructures…) which can turn to irreversible soil degradation. The economic value of agricultural land has been studied spatially, in every one of the 374 French Agricultural Counties, and temporally- from 1995 to 2007, by using data of the SAFER Institute. To this aim, agricultural land price was considered as a digital soil property. The spatial and temporal predictions were done using Digital Soil Mapping techniques combined with tools mainly used for studying temporal financial behaviors. For making both predictions, a first classification of the Agricultural Counties was done for the 1995-2006 periods (2007 was excluded and served as the date of prediction) using a fuzzy k-means clustering. The Agricultural Counties were then aggregated according to land price at the different times. The clustering allows for characterizing the counties by their memberships to each class centroid. The memberships were used for the spatial prediction, whereas the centroids were used for the temporal prediction. For the spatial prediction, from the 374 Agricultural counties, three fourths were used for modeling and one fourth for validating. Random sampling was done by class to ensure that all classes are represented by at least one county in the modeling and validation datasets. The prediction was done for each class by testing the relationships between the memberships and the following factors: (i) soil variable (organic matter from the French BDAT database), (ii) soil covariates (land use classes from CORINE LANDCOVER, bioclimatic zones from the WorldClim Database, landform attributes and landform classes from the SRTM, major roads and hydrographic densities from EUROSTAT, average field sizes estimated by automatic classification of remote sensed images) and (iii) socio-economic factors (population density, gross domestic product and its combination with the population density obtained from EUROSTAT). Linear (Generalized Linear Models) and non-linear models (neural network) were used for building the relationships. For the validation, the relationships were applied to the validation datasets. The RMSE and the coefficient of determination (from a linear regression) between predicted and actual memberships, and the contingency table between the predicted and actual allocation classes were used as validation criteria. The temporal prediction was done on the year 2007 from the centroid land prices characterizing the 1995-2006 period. For each class, the land prices of the time-series 1995-2006 were modeled using an Auto-Regressive Moving Average approach. For the validation, the models were applied to the year 2007. The RMSE between predicted and actual prices is used as the validation criteria. We then discussed the methods and the results of the spatial and temporal validation. Based on this methodology, an extrapolation will be tested on another European country with land price market similar to France (to be determined).

Updated Prognostic Model for Predicting Overall Survival in First-Line Chemotherapy for Patients With Metastatic Castration-Resistant Prostate Cancer

PubMed Central

Halabi, Susan; Lin, Chen-Yen; Kelly, W. Kevin; Fizazi, Karim S.; Moul, Judd W.; Kaplan, Ellen B.; Morris, Michael J.; Small, Eric J.

2014-01-01

Purpose Prognostic models for overall survival (OS) for patients with metastatic castration-resistant prostate cancer (mCRPC) are dated and do not reflect significant advances in treatment options available for these patients. This work developed and validated an updated prognostic model to predict OS in patients receiving first-line chemotherapy. Methods Data from a phase III trial of 1,050 patients with mCRPC were used (Cancer and Leukemia Group B CALGB-90401 [Alliance]). The data were randomly split into training and testing sets. A separate phase III trial served as an independent validation set. Adaptive least absolute shrinkage and selection operator selected eight factors prognostic for OS. A predictive score was computed from the regression coefficients and used to classify patients into low- and high-risk groups. The model was assessed for its predictive accuracy using the time-dependent area under the curve (tAUC). Results The model included Eastern Cooperative Oncology Group performance status, disease site, lactate dehydrogenase, opioid analgesic use, albumin, hemoglobin, prostate-specific antigen, and alkaline phosphatase. Median OS values in the high- and low-risk groups, respectively, in the testing set were 17 and 30 months (hazard ratio [HR], 2.2; P < .001); in the validation set they were 14 and 26 months (HR, 2.9; P < .001). The tAUCs were 0.73 (95% CI, 0.70 to 0.73) and 0.76 (95% CI, 0.72 to 0.76) in the testing and validation sets, respectively. Conclusion An updated prognostic model for OS in patients with mCRPC receiving first-line chemotherapy was developed and validated on an external set. This model can be used to predict OS, as well as to better select patients to participate in trials on the basis of their prognosis. PMID:24449231

Self-esteem recognition based on gait pattern using Kinect.

PubMed

Sun, Bingli; Zhang, Zhan; Liu, Xingyun; Hu, Bin; Zhu, Tingshao

2017-10-01

Self-esteem is an important aspect of individual's mental health. When subjects are not able to complete self-report questionnaire, behavioral assessment will be a good supplement. In this paper, we propose to use gait data collected by Kinect as an indicator to recognize self-esteem. 178 graduate students without disabilities participate in our study. Firstly, all participants complete the 10-item Rosenberg Self-Esteem Scale (RSS) to acquire self-esteem score. After completing the RRS, each participant walks for two minutes naturally on a rectangular red carpet, and the gait data are recorded using Kinect sensor. After data preprocessing, we extract a few behavioral features to train predicting model by machine learning. Based on these features, we build predicting models to recognize self-esteem. For self-esteem prediction, the best correlation coefficient between predicted score and self-report score is 0.45 (p<0.001). We divide the participants according to gender, and for males, the correlation coefficient is 0.43 (p<0.001), for females, it is 0.59 (p<0.001). Using gait data captured by Kinect sensor, we find that the gait pattern could be used to recognize self-esteem with a fairly good criterion validity. The gait predicting model can be taken as a good supplementary method to measure self-esteem. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of medial and lateral contact force of the knee joint during normal and turning gait after total knee replacement.

PubMed

Purevsuren, Tserenchimed; Dorj, Ariunzaya; Kim, Kyungsoo; Kim, Yoon Hyuk

2016-04-01

The computational modeling approach has commonly been used to predict knee joint contact forces, muscle forces, and ligament loads during activities of daily living. Knowledge of these forces has several potential applications, for example, within design of equipment to protect the knee joint from injury and to plan adequate rehabilitation protocols, although clinical applications of computational models are still evolving and one of the limiting factors is model validation. The objective of this study was to extend previous modeling technique and to improve the validity of the model prediction using publicly available data set of the fifth "Grand Challenge Competition to Predict In Vivo Knee Loads." A two-stage modeling approach, which combines conventional inverse dynamic analysis (the first stage) with a multi-body subject-specific lower limb model (the second stage), was used to calculate medial and lateral compartment contact forces. The validation was performed by direct comparison of model predictions and experimental measurement of medial and lateral compartment contact forces during normal and turning gait. The model predictions of both medial and lateral contact forces showed strong correlations with experimental measurements in normal gait (r = 0.75 and 0.71) and in turning gait trials (r = 0.86 and 0.72), even though the current technique over-estimated medial compartment contact forces in swing phase. The correlation coefficient, Sprague and Geers metrics, and root mean squared error indicated that the lateral contact forces were predicted better than medial contact forces in comparison with the experimental measurements during both normal and turning gait trials. © IMechE 2016.

Systematic review and retrospective validation of prediction models for weight loss after bariatric surgery.

PubMed

Sharples, Alistair J; Mahawar, Kamal; Cheruvu, Chandra V N

2017-11-01

Patients often have less than realistic expectations of the weight loss they are likely to achieve after bariatric surgery. It would be useful to have a well-validated prediction tool that could give patients a realistic estimate of their expected weight loss. To perform a systematic review of the literature to identify existing prediction models and attempt to validate these models. University hospital, United Kingdom. A systematic review was performed. All English language studies were included if they used data to create a prediction model for postoperative weight loss after bariatric surgery. These models were then tested on patients undergoing bariatric surgery between January 1, 2013 and December 31, 2014 within our unit. An initial literature search produced 446 results, of which only 4 were included in the final review. Our study population included 317 patients. Mean preoperative body mass index was 46.1 ± 7.1. For 257 (81.1%) patients, 12-month follow-up was available, and mean body mass index and percentage excess weight loss at 12 months was 33.0 ± 6.7 and 66.1% ± 23.7%, respectively. All 4 of the prediction models significantly overestimated the amount of weight loss achieved by patients. The best performing prediction model in our series produced a correlation coefficient (R 2 ) of .61 and an area under the curve of .71 on receiver operating curve analysis. All prediction models overestimated weight loss after bariatric surgery in our cohort. There is a need to develop better procedures and patient-specific models for better patient counselling. Copyright © 2017 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Acoustic properties of reticulated plastic foams

NASA Astrophysics Data System (ADS)

Cummings, A.; Beadle, S. P.

1994-08-01

Some general aspects of sound propagation in rigid porous media are discussed, particularly with reference to the use of a single - dimensionless - frequency parameter and the role of this, in the light of the possibility of varying gas properties, is examined. Steady flow resistance coefficients of porous media are also considered, and simple scaling relationships between these coefficients and `system parameters' are derived. The results of a series of measurements of the bulk acoustic properties of 12 geometrically similar, fully reticulated, polyurethane foams are presented, and empirical curve-fitting coefficients are found; the curve-fitting formulae are valid within the experimental range of values of the frequency parameter. Comparison is made between the measured data and an alternative, fairly recently published, semi-empirical set of formulae. Measurements of the steady flow-resistive coefficients are also given and both the acoustical and flow-resistive data are shown to be consistent with theoretical ideas. The acoustical and flow-resistive data should be of use in predicting the acoustic bulk properties of open-celled foams of types similar to those used in the experimental tests.

Relationship between time-resolved and non-time-resolved Beer-Lambert law in turbid media.

PubMed

Nomura, Y; Hazeki, O; Tamura, M

1997-06-01

The time-resolved Beer-Lambert law proposed for oxygen monitoring using pulsed light was extended to the non-time-resolved case in a scattered medium such as living tissues with continuous illumination. The time-resolved Beer-Lambert law was valid for the phantom model and living tissues in the visible and near-infrared regions. The absolute concentration and oxygen saturation of haemoglobin in rat brain and thigh muscle could be determined. The temporal profile of rat brain was reproduced by Monte Carlo simulation. When the temporal profiles of rat brain under different oxygenation states were integrated with time, the absorbance difference was linearly related to changes in the absorption coefficient. When the simulated profiles were integrated, there was a linear relationship within the absorption coefficient which was predicted for fractional inspiratory oxygen concentration from 10 to 100% and, in the case beyond the range of the absorption coefficient, the deviation from linearity was slight. We concluded that an optical pathlength which is independent of changes in the absorption coefficient is a good approximation for near-infrared oxygen monitoring.

Estimating consumer familiarity with health terminology: a context-based approach.

PubMed

Zeng-Treitler, Qing; Goryachev, Sergey; Tse, Tony; Keselman, Alla; Boxwala, Aziz

2008-01-01

Effective health communication is often hindered by a "vocabulary gap" between language familiar to consumers and jargon used in medical practice and research. To present health information to consumers in a comprehensible fashion, we need to develop a mechanism to quantify health terms as being more likely or less likely to be understood by typical members of the lay public. Prior research has used approaches including syllable count, easy word list, and frequency count, all of which have significant limitations. In this article, we present a new method that predicts consumer familiarity using contextual information. The method was applied to a large query log data set and validated using results from two previously conducted consumer surveys. We measured the correlation between the survey result and the context-based prediction, syllable count, frequency count, and log normalized frequency count. The correlation coefficient between the context-based prediction and the survey result was 0.773 (p < 0.001), which was higher than the correlation coefficients between the survey result and the syllable count, frequency count, and log normalized frequency count (p < or = 0.012). The context-based approach provides a good alternative to the existing term familiarity assessment methods.

Rapid assessment of nonlinear optical propagation effects in dielectrics

PubMed Central

Hoyo, J. del; de la Cruz, A. Ruiz; Grace, E.; Ferrer, A.; Siegel, J.; Pasquazi, A.; Assanto, G.; Solis, J.

2015-01-01

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process. PMID:25564243

A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals

NASA Technical Reports Server (NTRS)

Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.

1994-01-01

Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.

Membrane-assisted extraction of monoterpenes: from in silico solvent screening towards biotechnological process application

PubMed Central

2018-01-01

This work focuses on the process development of membrane-assisted solvent extraction of hydrophobic compounds such as monoterpenes. Beginning with the choice of suitable solvents, quantum chemical calculations with the simulation tool COSMO-RS were carried out to predict the partition coefficient (logP) of (S)-(+)-carvone and terpinen-4-ol in various solvent–water systems and validated afterwards with experimental data. COSMO-RS results show good prediction accuracy for non-polar solvents such as n-hexane, ethyl acetate and n-heptane even in the presence of salts and glycerol in an aqueous medium. Based on the high logP value, n-heptane was chosen for the extraction of (S)-(+)-carvone in a lab-scale hollow-fibre membrane contactor. Two operation modes are investigated where experimental and theoretical mass transfer values, based on their related partition coefficients, were compared. In addition, the process is evaluated in terms of extraction efficiency and overall product recovery, and its biotechnological application potential is discussed. Our work demonstrates that the combination of in silico prediction by COSMO-RS with membrane-assisted extraction is a promising approach for the recovery of hydrophobic compounds from aqueous solutions. PMID:29765654

Rapid assessment of nonlinear optical propagation effects in dielectrics.

PubMed

del Hoyo, J; de la Cruz, A Ruiz; Grace, E; Ferrer, A; Siegel, J; Pasquazi, A; Assanto, G; Solis, J

2015-01-07

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process.

Rapid assessment of nonlinear optical propagation effects in dielectrics

NASA Astrophysics Data System (ADS)

Hoyo, J. Del; de La Cruz, A. Ruiz; Grace, E.; Ferrer, A.; Siegel, J.; Pasquazi, A.; Assanto, G.; Solis, J.

2015-01-01

Ultrafast laser processing applications need fast approaches to assess the nonlinear propagation of the laser beam in order to predict the optimal range of processing parameters in a wide variety of cases. We develop here a method based on the simple monitoring of the nonlinear beam shaping against numerical prediction. The numerical code solves the nonlinear Schrödinger equation with nonlinear absorption under simplified conditions by employing a state-of-the art computationally efficient approach. By comparing with experimental results we can rapidly estimate the nonlinear refractive index and nonlinear absorption coefficients of the material. The validity of this approach has been tested in a variety of experiments where nonlinearities play a key role, like spatial soliton shaping or fs-laser waveguide writing. The approach provides excellent results for propagated power densities for which free carrier generation effects can be neglected. Above such a threshold, the peculiarities of the nonlinear propagation of elliptical beams enable acquiring an instantaneous picture of the deposition of energy inside the material realistic enough to estimate the effective nonlinear refractive index and nonlinear absorption coefficients that can be used for predicting the spatial distribution of energy deposition inside the material and controlling the beam in the writing process.

Model averaging and muddled multimodel inferences.

PubMed

Cade, Brian S

2015-09-01

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the t statistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse (Centrocercus urophasianus) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

Model averaging and muddled multimodel inferences

USGS Publications Warehouse

Cade, Brian S.

2015-01-01

Three flawed practices associated with model averaging coefficients for predictor variables in regression models commonly occur when making multimodel inferences in analyses of ecological data. Model-averaged regression coefficients based on Akaike information criterion (AIC) weights have been recommended for addressing model uncertainty but they are not valid, interpretable estimates of partial effects for individual predictors when there is multicollinearity among the predictor variables. Multicollinearity implies that the scaling of units in the denominators of the regression coefficients may change across models such that neither the parameters nor their estimates have common scales, therefore averaging them makes no sense. The associated sums of AIC model weights recommended to assess relative importance of individual predictors are really a measure of relative importance of models, with little information about contributions by individual predictors compared to other measures of relative importance based on effects size or variance reduction. Sometimes the model-averaged regression coefficients for predictor variables are incorrectly used to make model-averaged predictions of the response variable when the models are not linear in the parameters. I demonstrate the issues with the first two practices using the college grade point average example extensively analyzed by Burnham and Anderson. I show how partial standard deviations of the predictor variables can be used to detect changing scales of their estimates with multicollinearity. Standardizing estimates based on partial standard deviations for their variables can be used to make the scaling of the estimates commensurate across models, a necessary but not sufficient condition for model averaging of the estimates to be sensible. A unimodal distribution of estimates and valid interpretation of individual parameters are additional requisite conditions. The standardized estimates or equivalently the tstatistics on unstandardized estimates also can be used to provide more informative measures of relative importance than sums of AIC weights. Finally, I illustrate how seriously compromised statistical interpretations and predictions can be for all three of these flawed practices by critiquing their use in a recent species distribution modeling technique developed for predicting Greater Sage-Grouse (Centrocercus urophasianus) distribution in Colorado, USA. These model averaging issues are common in other ecological literature and ought to be discontinued if we are to make effective scientific contributions to ecological knowledge and conservation of natural resources.

Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data

DOE PAGES

Hsu, David

2015-09-27

Clustering methods are often used to model energy consumption for two reasons. First, clustering is often used to process data and to improve the predictive accuracy of subsequent energy models. Second, stable clusters that are reproducible with respect to non-essential changes can be used to group, target, and interpret observed subjects. However, it is well known that clustering methods are highly sensitive to the choice of algorithms and variables. This can lead to misleading assessments of predictive accuracy and mis-interpretation of clusters in policymaking. This paper therefore introduces two methods to the modeling of energy consumption in buildings: clusterwise regression,more » also known as latent class regression, which integrates clustering and regression simultaneously; and cluster validation methods to measure stability. Using a large dataset of multifamily buildings in New York City, clusterwise regression is compared to common two-stage algorithms that use K-means and model-based clustering with linear regression. Predictive accuracy is evaluated using 20-fold cross validation, and the stability of the perturbed clusters is measured using the Jaccard coefficient. These results show that there seems to be an inherent tradeoff between prediction accuracy and cluster stability. This paper concludes by discussing which clustering methods may be appropriate for different analytical purposes.« less

Prediction of Protein Aggregation in High Concentration Protein Solutions Utilizing Protein-Protein Interactions Determined by Low Volume Static Light Scattering.

PubMed

Hofmann, Melanie; Winzer, Matthias; Weber, Christian; Gieseler, Henning

2016-06-01

The development of highly concentrated protein formulations is more demanding than for conventional concentrations due to an elevated protein aggregation tendency. Predictive protein-protein interaction parameters, such as the second virial coefficient B22 or the interaction parameter kD, have already been used to predict aggregation tendency and optimize protein formulations. However, these parameters can only be determined in diluted solutions, up to 20 mg/mL. And their validity at high concentrations is currently controversially discussed. This work presents a μ-scale screening approach which has been adapted to early industrial project needs. The procedure is based on static light scattering to directly determine protein-protein interactions at concentrations up to 100 mg/mL. Three different therapeutic molecules were formulated, varying in pH, salt content, and addition of excipients (e.g., sugars, amino acids, polysorbates, or other macromolecules). Validity of the predicted aggregation tendency was confirmed by stability data of selected formulations. Based on the results obtained, the new prediction method is a promising screening tool for fast and easy formulation development of highly concentrated protein solutions, consuming only microliter of sample volumes. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

A turbulence model for iced airfoils and its validation

NASA Technical Reports Server (NTRS)

Shin, Jaiwon; Chen, Hsun H.; Cebeci, Tuncer

1992-01-01

A turbulence model based on the extension of the algebraic eddy viscosity formulation of Cebeci and Smith developed for two dimensional flows over smooth and rough surfaces is described for iced airfoils and validated for computed ice shapes obtained for a range of total temperatures varying from 28 to -15 F. The validation is made with an interactive boundary layer method which uses a panel method to compute the inviscid flow and an inverse finite difference boundary layer method to compute the viscous flow. The interaction between inviscid and viscous flows is established by the use of the Hilbert integral. The calculated drag coefficients compare well with recent experimental data taken at the NASA-Lewis Icing Research Tunnel (IRT) and show that, in general, the drag increase due to ice accretion can be predicted well and efficiently.

Measuring attitudes, self-efficacy, and social and environmental influences on fruit and vegetable consumption of 11- and 12-year-old children: reliability and validity.

PubMed

Vereecken, Carine Anna; Van Damme, Wendy; Maes, Lea

2005-02-01

This article examines the reliability and construct validity of questions assessing mediating factors of fruit and vegetable consumption among 11- and 12-year-old children (N=207). Internal consistencies were good for most scales, ranging from 0.56 to 0.94. Intraclass correlation coefficients between test and retest were acceptable, ranging from 0.39 to 0.90. Concerning predictive validity, preferences and perceived parental and peer behavior were significantly associated with fruit and vegetable consumption. Self-efficacy in difficult situations and a variety of available fruit were significantly correlated with fruit consumption, while permissive eating practices and obligation rules were significantly correlated with vegetable consumption. General attitudes, outcome expectations, selection efficacy, and encouraging practices were not associated with fruit or vegetable consumption.

Uncertainty Quantification Techniques of SCALE/TSUNAMI

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

Rearden, Bradley T; Mueller, Don

2011-01-01

The Standardized Computer Analysis for Licensing Evaluation (SCALE) code system developed at Oak Ridge National Laboratory (ORNL) includes Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI). The TSUNAMI code suite can quantify the predicted change in system responses, such as k{sub eff}, reactivity differences, or ratios of fluxes or reaction rates, due to changes in the energy-dependent, nuclide-reaction-specific cross-section data. Where uncertainties in the neutron cross-section data are available, the sensitivity of the system to the cross-section data can be applied to propagate the uncertainties in the cross-section data to an uncertainty in the system response. Uncertainty quantification ismore » useful for identifying potential sources of computational biases and highlighting parameters important to code validation. Traditional validation techniques often examine one or more average physical parameters to characterize a system and identify applicable benchmark experiments. However, with TSUNAMI correlation coefficients are developed by propagating the uncertainties in neutron cross-section data to uncertainties in the computed responses for experiments and safety applications through sensitivity coefficients. The bias in the experiments, as a function of their correlation coefficient with the intended application, is extrapolated to predict the bias and bias uncertainty in the application through trending analysis or generalized linear least squares techniques, often referred to as 'data adjustment.' Even with advanced tools to identify benchmark experiments, analysts occasionally find that the application models include some feature or material for which adequately similar benchmark experiments do not exist to support validation. For example, a criticality safety analyst may want to take credit for the presence of fission products in spent nuclear fuel. In such cases, analysts sometimes rely on 'expert judgment' to select an additional administrative margin to account for gap in the validation data or to conclude that the impact on the calculated bias and bias uncertainty is negligible. As a result of advances in computer programs and the evolution of cross-section covariance data, analysts can use the sensitivity and uncertainty analysis tools in the TSUNAMI codes to estimate the potential impact on the application-specific bias and bias uncertainty resulting from nuclides not represented in available benchmark experiments. This paper presents the application of methods described in a companion paper.« less

Predicting the Activity Coefficients of Free-Solvent for Concentrated Globular Protein Solutions Using Independently Determined Physical Parameters

PubMed Central

McBride, Devin W.; Rodgers, Victor G. J.

2013-01-01

The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations. PMID:24324733

Cross-cultural Adaptation and Linguistic Validation of the Korean Version of the Leeds Assessment of Neuropathic Symptoms and Signs Pain Scale.

PubMed

Park, Cholhee; Lee, Youn-Woo; Yoon, Duck Mi; Kim, Do Wan; Nam, Da Jeong; Kim, Do-Hyeong

2015-09-01

Distinction between neuropathic pain and nociceptive pain helps facilitate appropriate management of pain; however, diagnosis of neuropathic pain remains a challenge. The aim of this study was to develop a Korean version of the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain scale and assess its reliability and validity. The translation and cross-cultural adaptation of the original LANSS pain scale into Korean was established according to the published guidelines. The Korean version of the LANSS pain scale was applied to a total of 213 patients who were expertly diagnosed with neuropathic (n = 113) or nociceptive pain (n = 100). The Korean version of the scale had good reliability (Cronbach's α coefficient = 0.815, Guttman split-half coefficient = 0.800). The area under the receiver operating characteristic curve was 0.928 with a 95% confidence interval of 0.885-0.959 (P < 0.001), suggesting good discriminate value. With a cut-off score ≥ 12, sensitivity was 72.6%, specificity was 98.0%, and the positive and negative predictive values were 98% and 76%, respectively. The Korean version of the LANSS pain scale is a useful, reliable, and valid instrument for screening neuropathic pain from nociceptive pain.

Cross-cultural Adaptation and Linguistic Validation of the Korean Version of the Leeds Assessment of Neuropathic Symptoms and Signs Pain Scale

PubMed Central

Park, Cholhee; Lee, Youn-Woo; Yoon, Duck Mi; Kim, Do Wan; Nam, Da Jeong

2015-01-01

Distinction between neuropathic pain and nociceptive pain helps facilitate appropriate management of pain; however, diagnosis of neuropathic pain remains a challenge. The aim of this study was to develop a Korean version of the Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) pain scale and assess its reliability and validity. The translation and cross-cultural adaptation of the original LANSS pain scale into Korean was established according to the published guidelines. The Korean version of the LANSS pain scale was applied to a total of 213 patients who were expertly diagnosed with neuropathic (n = 113) or nociceptive pain (n = 100). The Korean version of the scale had good reliability (Cronbach's α coefficient = 0.815, Guttman split-half coefficient = 0.800). The area under the receiver operating characteristic curve was 0.928 with a 95% confidence interval of 0.885-0.959 (P < 0.001), suggesting good discriminate value. With a cut-off score ≥ 12, sensitivity was 72.6%, specificity was 98.0%, and the positive and negative predictive values were 98% and 76%, respectively. The Korean version of the LANSS pain scale is a useful, reliable, and valid instrument for screening neuropathic pain from nociceptive pain. PMID:26339176

Drive for muscularity and social physique anxiety mediate the perceived ideal physique muscle dysmorphia relationship.

PubMed

Thomas, Adam; Tod, David A; Edwards, Christian J; McGuigan, Michael R

2014-12-01

This study examined the mediating role of drive for muscularity and social physique anxiety (SPA) in the perceived muscular male ideal physique and muscle dysmorphia relationship in weight training men. Men (N = 146, mean ± SD; age, 22.8 ± 5.0 years; weight, 82.0 ± 11.1 kg; height, 1.80 ± 0.07 m; body mass index, 25.1 ± 3.0) who participated in weight training completed validated questionnaires measuring drive for muscularity, SPA, perceived muscular male ideal physique, global muscle dysmorphia, and several characteristics of muscle dysmorphia (exercise dependence, diet manipulation, concerns about size/symmetry, physique protection behavior, and supplementation). Perceived ideal physique was an independent predictor of muscle dysmorphia measures except physique protection (coefficients = 0.113-0.149, p ≤ 0.05). Perceived ideal physique also predicted muscle dysmorphia characteristics (except physique protection and diet) through the indirect drive for muscularity pathway (coefficients = 0.055-0.116, p ≤ 0.05). Perceived ideal physique also predicted size/symmetry concerns and physique protection through the indirect drive for muscularity and SPA pathway (coefficients = 0.080-0.025, p ≤ 0.05). These results extend current research by providing insights into the way correlates of muscle dysmorphia interact to predict the condition. The results also highlight signs (e.g., anxiety about muscularity) that strength and conditioning coaches can use to identify at-risk people who may benefit from being referred for psychological assistance.

Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Schwartz, C. S.

2017-12-01

Bayesian linear regression (BLR) is a post-processing technique in which regression coefficients are derived and used to correct raw forecasts based on pairs of observation-model values. This study presents the development and application of a gridded Bayesian linear regression (GBLR) as a new post-processing technique to improve numerical weather prediction (NWP) of rain and wind storm forecasts over northeast United States. Ten controlled variables produced from ten ensemble members of the National Center for Atmospheric Research (NCAR) real-time prediction system are used for a GBLR model. In the GBLR framework, leave-one-storm-out cross-validation is utilized to study the performances of the post-processing technique in a database composed of 92 storms. To estimate the regression coefficients of the GBLR, optimization procedures that minimize the systematic and random error of predicted atmospheric variables (wind speed, precipitation, etc.) are implemented for the modeled-observed pairs of training storms. The regression coefficients calculated for meteorological stations of the National Weather Service are interpolated back to the model domain. An analysis of forecast improvements based on error reductions during the storms will demonstrate the value of GBLR approach. This presentation will also illustrate how the variances are optimized for the training partition in GBLR and discuss the verification strategy for grid points where no observations are available. The new post-processing technique is successful in improving wind speed and precipitation storm forecasts using past event-based data and has the potential to be implemented in real-time.

Diffusion coefficients in organic-water solutions and comparison with Stokes-Einstein predictions

NASA Astrophysics Data System (ADS)

Evoy, E.; Kamal, S.; Bertram, A. K.

2017-12-01

Diffusion coefficients of organic species in particles containing secondary organic material (SOM) are necessary for predicting the growth and reactivity of these particles in the atmosphere. Previously, the Stokes-Einstein equation combined with viscosity measurements have been used to predict these diffusion coefficients. However, the accuracy of the Stokes-Einstein equation for predicting diffusion coefficients in SOM-water particles has not been quantified. To test the Stokes-Einstein equation, diffusion coefficients of fluorescent organic probe molecules were measured in citric acid-water and sorbitol-water solutions. These solutions were used as proxies for SOM-water particles found in the atmosphere. Measurements were performed as a function of water activity, ranging from 0.26-0.86, and as a function of viscosity ranging from 10-3 to 103 Pa s. Diffusion coefficients were measured using fluorescence recovery after photobleaching. The measured diffusion coefficients were compared with predictions made using the Stokes-Einstein equation combined with literature viscosity data. Within the uncertainties of the measurements, the measured diffusion coefficients agreed with the predicted diffusion coefficients, in all cases.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

PubMed Central

Agnihotri, Samira; Sundeep, P. V. D. S.; Seelamantula, Chandra Sekhar; Balakrishnan, Rohini

2014-01-01

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential. PMID:24603717

Corticospinal signals recorded with MEAs can predict the volitional forearm forces in rats.

PubMed

Guo, Yi; Mesut, Sahin; Foulds, Richard A; Adamovich, Sergei V

2013-01-01

We set out to investigate if volitional components in the descending tracts of the spinal cord white matter can be accessed with multi-electrode array (MEA) recording technique. Rats were trained to press a lever connected to a haptic device with force feedback to receive sugar pellets. A flexible-substrate multi-electrode array was chronically implanted into the dorsal column of the cervical spinal cord. Field potentials and multi-unit activities were recorded from the descending axons of the corticospinal tract while the rat performed a lever pressing task. Forelimb forces, recorded with the sensor attached to the lever, were reconstructed using the hand position data and the neural signals through multiple trials over three weeks. The regression coefficients found from the trial set were cross-validated on the other trials recorded on same day. Approximately 30 trials of at least 2 seconds were required for accurate model estimation. The maximum correlation coefficient between the actual and predicted force was 0.7 in the test set. Positional information and its interaction with neural signals improved the correlation coefficient by 0.1 to 0.15. These results suggest that the volitional information contained in the corticospinal tract can be extracted with multi-channel neural recordings made with parenchymal electrodes.

An adaptive multi-moment FVM approach for incompressible flows

NASA Astrophysics Data System (ADS)

Liu, Cheng; Hu, Changhong

2018-04-01

In this study, a multi-moment finite volume method (FVM) based on block-structured adaptive Cartesian mesh is proposed for simulating incompressible flows. A conservative interpolation scheme following the idea of the constrained interpolation profile (CIP) method is proposed for the prolongation operation of the newly created mesh. A sharp immersed boundary (IB) method is used to model the immersed rigid body. A moving least squares (MLS) interpolation approach is applied for reconstruction of the velocity field around the solid surface. An efficient method for discretization of Laplacian operators on adaptive meshes is proposed. Numerical simulations on several test cases are carried out for validation of the proposed method. For the case of viscous flow past an impulsively started cylinder (Re = 3000 , 9500), the computed surface vorticity coincides with the result of the body-fitted method. For the case of a fast pitching NACA 0015 airfoil at moderate Reynolds numbers (Re = 10000 , 45000), the predicted drag coefficient (CD) and lift coefficient (CL) agree well with other numerical or experimental results. For 2D and 3D simulations of viscous flow past a pitching plate with prescribed motions (Re = 5000 , 40000), the predicted CD, CL and CM (moment coefficient) are in good agreement with those obtained by other numerical methods.

Predictive validity and reliability of the Braden scale for risk assessment of pressure ulcers in an intensive care unit.

PubMed

Lima-Serrano, M; González-Méndez, M I; Martín-Castaño, C; Alonso-Araujo, I; Lima-Rodríguez, J S

2018-03-01

Contribution to validation of the Braden scale in patients admitted to the ICU, based on an analysis of its reliability and predictive validity. An analytical, observational, longitudinal prospective study was carried out. Intensive Care Unit, Hospital Virgen del Rocío, Seville (Spain). Patients aged 18years or older and admitted for over 24hours to the ICU were included. Patients with pressure ulcers upon admission were excluded. A total of 335 patients were enrolled in two study periods of one month each. None. The presence of gradei-iv pressure ulcers was regarded as the main or dependent variable. Three categories were considered (demographic, clinical and prognostic) for the remaining variables. The incidence of patients who developed pressure ulcers was 8.1%. The proportion of gradei andii pressure ulcer was 40.6% and 59.4% respectively, highlighting the sacrum as the most frequently affected location. Cronbach's alpha coefficient in the assessments considered indicated good to moderate reliability. In the three evaluations made, a cutoff point of 12 was presented as optimal in the assessment of the first and second days of admission. In relation to the assessment of the day with minimum score, the optimal cutoff point was 10. The Braden scale shows insufficient predictive validity and poor precision for cutoff points of both 18 and 16, which are those accepted in the different clinical scenarios. Copyright © 2017 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Using Precept-Assist® to predict performance on the American Board of Family Medicine In-Training Examination.

PubMed

Post, Robert E; Jamena, Gemma P; Gamble, James D

2014-09-01

Precept-Assist® (PA) is a computer-based program developed by the Virtua Family Medicine Residency where residents receive a score on a Likert-type scale from an attending for each precept based on their knowledge base. The purpose of this study was to attempt to validate this program for precepting family medicine residents. This was a validation study. PA and American Board of Family Medicine (ABFM) In-Training Exam (ITE) scores for all residents from a community-based family medicine residency between the years 2002 and 2011 were included (n=216). Pearson correlation coefficients were calculated between PA scores for the second quarter of the academic year (October 1 to December 31) and scores on the ITE. An ROC curve was also created to determine sensitivity and specificity for various PA scores in predicting residents scoring 500 or above on the ITE. The PA mean (SD) score was 5.18 (0.84) and the ITE mean (SD) score was 425.1 (87.6). The Pearson correlation coefficient between PA and ITE scores was 0.55, which is a moderately positive correlation. The AUC of the ROC curve was 0.783 (95% CI 0.704-0.859). A PA score of 5.5 (between the level of a PGY-2 and PGY-3) was 72% sensitive and 77% specific for scoring 500 or above on the ITE with a positive LR of 3.12. There is a significant correlation between PA scores and ABFM In-Training Exam scores. PA is a valid screening tool that can be used as a predictor for future performance in Family Medicine In-Training exams.

Derivation and Validation of a Clostridium difficile Infection Recurrence Prediction Rule in a National Cohort of Veterans.

PubMed

Reveles, Kelly R; Mortensen, Eric M; Koeller, Jim M; Lawson, Kenneth A; Pugh, Mary Jo V; Rumbellow, Sarah A; Argamany, Jacqueline R; Frei, Christopher R

2018-03-01

Prior studies have identified risk factors for recurrent Clostridium difficile infection (CDI), but few studies have integrated these factors into a clinical prediction rule that can aid clinical decision-making. The objectives of this study were to derive and validate a CDI recurrence prediction rule to identify patients at risk for first recurrence in a national cohort of veterans. Retrospective cohort study. Veterans Affairs Informatics and Computing Infrastructure. A total of 22,615 adult Veterans Health Administration beneficiaries with first-episode CDI between October 1, 2002, and September 30, 2014; of these patients, 7538 were assigned to the derivation cohort and 15,077 to the validation cohort. A 60-day CDI recurrence prediction rule was created in a derivation cohort using backward logistic regression. Those variables significant at p<0.01 were assigned an integer score proportional to the regression coefficient. The model was then validated in the derivation cohort and a separate validation cohort. Patients were then split into three risk categories, and rates of recurrence were described for each category. The CDI recurrence prediction rule included the following predictor variables with their respective point values: prior third- and fourth-generation cephalosporins (1 point), prior proton pump inhibitors (1 point), prior antidiarrheals (1 point), nonsevere CDI (2 points), and community-onset CDI (3 points). In the derivation cohort, the 60-day CDI recurrence risk for each score ranged from 7.5% (0 points) to 57.9% (8 points). The risk score was strongly correlated with recurrence (R 2  = 0.94). Patients were split into low-risk (0-2 points), medium-risk (3-5 points), and high-risk (6-8 points) classes and had the following recurrence rates: 8.9%, 20.2%, and 35.0%, respectively. Findings were similar in the validation cohort. Several CDI and patient-specific factors were independently associated with 60-day CDI recurrence risk. When integrated into a clinical prediction rule, higher risk scores and risk classes were strongly correlated with CDI recurrence. This clinical prediction rule can be used by providers to identify patients at high risk for CDI recurrence and help guide preventive strategy decisions, while accounting for clinical judgment. © 2018 Pharmacotherapy Publications, Inc.

Application of a New Resource-Constrained Triage Method to Military-Age Victims

DTIC Science & Technology

2009-12-01

evidence based, does not consider resources, and has been shown to be scientifically and opera- tionally flawed.’ General P . K. Carlton, former USAF Surgeon...metric that can be used to predict sur- vival probability) P ^ (t) = the survival probability of victims with original SCORE s treated in time period t. n...function coefficients were derived on the design set, and validated on the test set. The logistic function has the form: P ^ - 1/(1 + e"), where P ^ is

The Reliability and Validity of the Thoracolumbar Injury Classification System in Pediatric Spine Trauma.

PubMed

Savage, Jason W; Moore, Timothy A; Arnold, Paul M; Thakur, Nikhil; Hsu, Wellington K; Patel, Alpesh A; McCarthy, Kathryn; Schroeder, Gregory D; Vaccaro, Alexander R; Dimar, John R; Anderson, Paul A

2015-09-15

The thoracolumbar injury classification system (TLICS) was evaluated in 20 consecutive pediatric spine trauma cases. The purpose of this study was to determine the reliability and validity of the TLICS in pediatric spine trauma. The TLICS was developed to improve the categorization and management of thoracolumbar trauma. TLICS has been shown to have good reliability and validity in the adult population. The clinical and radiographical findings of 20 pediatric thoracolumbar fractures were prospectively presented to 20 surgeons with disparate levels of training and experience with spinal trauma. These injuries were consecutively scored using the TLICS. Cohen unweighted κ coefficients and Spearman rank order correlation values were calculated for the key parameters (injury morphology, status of posterior ligamentous complex, neurological status, TLICS total score, and proposed management) to assess the inter-rater reliabilities. Five surgeons scored the same cases 3 months later to assess the intra-rater reliability. The actual management of each case was then compared with the treatment recommended by the TLICS algorithm to assess validity. The inter-rater κ statistics of all subgroups (injury morphology, status of the posterior ligamentous complex, neurological status, TLICS total score, and proposed treatment) were within the range of moderate to substantial reproducibility (0.524-0.958). All subgroups had excellent intra-rater reliability (0.748-1.000). The various indices for validity were calculated (80.3% correct, 0.836 sensitivity, 0.785 specificity, 0.676 positive predictive value, 0.899 negative predictive value). Overall, TLICS demonstrated good validity. The TLICS has good reliability and validity when used in the pediatric population. The inter-rater reliability of predicting management and indices for validity are lower than those in adults with thoracolumbar fractures, which is likely due to differences in the way children are treated for certain types of injuries. TLICS can be used to reliably categorize thoracolumbar injuries in the pediatric population; however, modifications may be needed to better guide treatment in this specific patient population. 4.

DRA/NASA/ONERA Collaboration on Icing Research. Part 2; Prediction of Airfoil Ice Accretion

NASA Technical Reports Server (NTRS)

Wright, William B.; Gent, R. W.; Guffond, Didier

1997-01-01

This report presents results from a joint study by DRA, NASA, and ONERA for the purpose of comparing, improving, and validating the aircraft icing computer codes developed by each agency. These codes are of three kinds: (1) water droplet trajectory prediction, (2) ice accretion modeling, and (3) transient electrothermal deicer analysis. In this joint study, the agencies compared their code predictions with each other and with experimental results. These comparison exercises were published in three technical reports, each with joint authorship. DRA published and had first authorship of Part 1 - Droplet Trajectory Calculations, NASA of Part 2 - Ice Accretion Prediction, and ONERA of Part 3 - Electrothermal Deicer Analysis. The results cover work done during the period from August 1986 to late 1991. As a result, all of the information in this report is dated. Where necessary, current information is provided to show the direction of current research. In this present report on ice accretion, each agency predicted ice shapes on two dimensional airfoils under icing conditions for which experimental ice shapes were available. In general, all three codes did a reasonable job of predicting the measured ice shapes. For any given experimental condition, one of the three codes predicted the general ice features (i.e., shape, impingement limits, mass of ice) somewhat better than did the other two. However, no single code consistently did better than the other two over the full range of conditions examined, which included rime, mixed, and glaze ice conditions. In several of the cases, DRA showed that the user's knowledge of icing can significantly improve the accuracy of the code prediction. Rime ice predictions were reasonably accurate and consistent among the codes, because droplets freeze on impact and the freezing model is simple. Glaze ice predictions were less accurate and less consistent among the codes, because the freezing model is more complex and is critically dependent upon unsubstantiated heat transfer and surface roughness models. Thus, heat transfer prediction methods used in the codes became the subject for a separate study in this report to compare predicted heat transfer coefficients with a limited experimental database of heat transfer coefficients for cylinders with simulated glaze and rime ice shapes. The codes did a good job of predicting heat transfer coefficients near the stagnation region of the ice shapes. But in the region of the ice horns, all three codes predicted heat transfer coefficients considerably higher than the measured values. An important conclusion of this study is that further research is needed to understand the finer detail of of the glaze ice accretion process and to develop improved glaze ice accretion models.

Validation of engineering methods for predicting hypersonic vehicle controls forces and moments

NASA Technical Reports Server (NTRS)

Maughmer, M.; Straussfogel, D.; Long, L.; Ozoroski, L.

1991-01-01

This work examines the ability of the aerodynamic analysis methods contained in an industry standard conceptual design code, the Aerodynamic Preliminary Analysis System (APAS II), to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds. Predicted control forces and moments generated by various control effectors are compared with previously published wind-tunnel and flight-test data for three vehicles: the North American X-15, a hypersonic research airplane concept, and the Space Shuttle Orbiter. Qualitative summaries of the results are given for each force and moment coefficient and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage.

Use of the Method of Triads in the Validation of Sodium and Potassium Intake in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

PubMed Central

Pereira, Taísa Sabrina Silva; Cade, Nágela Valadão; Mill, José Geraldo; Sichieri, Rosely; Molina, Maria del Carmen Bisi

2016-01-01

Introduction Biomarkers are a good choice to be used in the validation of food frequency questionnaire due to the independence of their random errors. Objective To assess the validity of the potassium and sodium intake estimated using the Food Frequency Questionnaire ELSA-Brasil. Subjects/Methods A subsample of participants in the ELSA-Brasil cohort was included in this study in 2009. Sodium and potassium intake were estimated using three methods: Semi-quantitative food frequency questionnaire, 12-hour nocturnal urinary excretion and three 24-hour food records. Correlation coefficients were calculated between the methods, and the validity coefficient was calculated using the method of triads. The 95% confidence intervals for the validity coefficient were estimated using bootstrap sampling. Exact and adjacent agreement and disagreement of the estimated sodium and potassium intake quintiles were compared among three methods. Results The sample consisted of 246 participants, aged 53±8 years, 52% of women. Validity coefficient for sodium were considered weak (рfood frequency questionnaire actual intake = 0.37 and рbiomarker actual intake = 0.21) and moderate (рfood records actual intake 0.56). The validity coefficient were higher for potassium (рfood frequency questionnaire actual intake = 0.60; рbiomarker actual intake = 0.42; рfood records actual intake = 0.79). Conclusions: The Food Frequency Questionnaire ELSA-Brasil showed good validity in estimating potassium intake in epidemiological studies. For sodium validity was weak, likely due to the non-quantification of the added salt to prepared food. PMID:28030625

Use of the Method of Triads in the Validation of Sodium and Potassium Intake in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

PubMed

Pereira, Taísa Sabrina Silva; Cade, Nágela Valadão; Mill, José Geraldo; Sichieri, Rosely; Molina, Maria Del Carmen Bisi

2016-01-01

Biomarkers are a good choice to be used in the validation of food frequency questionnaire due to the independence of their random errors. To assess the validity of the potassium and sodium intake estimated using the Food Frequency Questionnaire ELSA-Brasil. A subsample of participants in the ELSA-Brasil cohort was included in this study in 2009. Sodium and potassium intake were estimated using three methods: Semi-quantitative food frequency questionnaire, 12-hour nocturnal urinary excretion and three 24-hour food records. Correlation coefficients were calculated between the methods, and the validity coefficient was calculated using the method of triads. The 95% confidence intervals for the validity coefficient were estimated using bootstrap sampling. Exact and adjacent agreement and disagreement of the estimated sodium and potassium intake quintiles were compared among three methods. The sample consisted of 246 participants, aged 53±8 years, 52% of women. Validity coefficient for sodium were considered weak (рfood frequency questionnaire actual intake = 0.37 and рbiomarker actual intake = 0.21) and moderate (рfood records actual intake 0.56). The validity coefficient were higher for potassium (рfood frequency questionnaire actual intake = 0.60; рbiomarker actual intake = 0.42; рfood records actual intake = 0.79). Conclusions: The Food Frequency Questionnaire ELSA-Brasil showed good validity in estimating potassium intake in epidemiological studies. For sodium validity was weak, likely due to the non-quantification of the added salt to prepared food.

Application of effective wavelengths and BP neural network for the discrimination of varieties of instant milk tea powders using visible and near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Liu, Fei; He, Yong; Wang, Li

2007-11-01

In order to implement the fast discrimination of different milk tea powders with different internal qualities, visible and near infrared (Vis/NIR) spectroscopy combined with effective wavelengths (EWs) and BP neural network (BPNN) was investigated as a new approach. Five brands of milk teas were obtained and 225 samples were selected randomly for the calibration set, while 75 samples for the validation set. The EWs were selected according to x-loading weights and regression coefficients by PLS analysis after some preprocessing. A total of 18 EWs (400, 401, 452, 453, 502, 503, 534, 535, 594, 595, 635, 636, 688, 689, 987, 988, 995 and 996 nm) were selected as the inputs of BPNN model. The performance was validated by the calibration and validation sets. The threshold error of prediction was set as +/-0.1 and an excellent precision and recognition ratio of 100% for calibration set and 98.7% for validation set were achieved. The prediction results indicated that the EWs reflected the main characteristics of milk tea of different brands based on Vis/NIR spectroscopy and BPNN model, and the EWs would be useful for the development of portable instrument to discriminate the variety and detect the adulteration of instant milk tea powders.

[Reliability and validity of a Mexican version of the Pro Children Project questionnaire].

PubMed

Ochoa-Meza, Gerardo; Sierra, Juan Carlos; Pérez-Rodrigo, Carmen; Aranceta Bartrina, Javier; Esparza-Del Villar, Óscar A

2014-08-01

To determine the test-retest reliability, the internal consistency, and the predictive validity of the constructs of the Mexican version of the Pro Children Project questionnaire (PCHP) for assessing personal and environmental factors related to fruit and vegetable intake in 10-12 year-old schoolchildren. Test-retest design with a 14 days interval. A sample of 957 children completed the questionnaire with 82 items. The study was conducted at eight primary schools in 2012 in Ciudad Juarez, Chihuahua, Mexico. For all fruit constructs and vegetable constructs, the test-retest reliability was moderate (intraclass correlation coefficient (ICC) > 0.60). Cronbach s alpha values were from moderate to high (range of 0.54 to 0.92) similar to those in the original study. Values for predictive validity ranged from moderate to good with Spearman correlations between 0.23 and 0.60 for personal factors and between 0.14 and 0.40 for environmental factors. The results of the Mexican version of the PCHP questionnaire provide a sufficient reliability and validity for assessing personal and environmental factors of fruit and vegetable intake in 10-12 year old schoolchildren. Finally, implications to administer this instrument in scholar settings and guidelines for futures studies are discussed. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

[Establishing and applying of autoregressive integrated moving average model to predict the incidence rate of dysentery in Shanghai].

PubMed

Li, Jian; Wu, Huan-Yu; Li, Yan-Ting; Jin, Hui-Ming; Gu, Bao-Ke; Yuan, Zheng-An

2010-01-01

To explore the feasibility of establishing and applying of autoregressive integrated moving average (ARIMA) model to predict the incidence rate of dysentery in Shanghai, so as to provide the theoretical basis for prevention and control of dysentery. ARIMA model was established based on the monthly incidence rate of dysentery of Shanghai from 1990 to 2007. The parameters of model were estimated through unconditional least squares method, the structure was determined according to criteria of residual un-correlation and conclusion, and the model goodness-of-fit was determined through Akaike information criterion (AIC) and Schwarz Bayesian criterion (SBC). The constructed optimal model was applied to predict the incidence rate of dysentery of Shanghai in 2008 and evaluate the validity of model through comparing the difference of predicted incidence rate and actual one. The incidence rate of dysentery in 2010 was predicted by ARIMA model based on the incidence rate from January 1990 to June 2009. The model ARIMA (1, 1, 1) (0, 1, 2)(12) had a good fitness to the incidence rate with both autoregressive coefficient (AR1 = 0.443) during the past time series, moving average coefficient (MA1 = 0.806) and seasonal moving average coefficient (SMA1 = 0.543, SMA2 = 0.321) being statistically significant (P < 0.01). AIC and SBC were 2.878 and 16.131 respectively and predicting error was white noise. The mathematic function was (1-0.443B) (1-B) (1-B(12))Z(t) = (1-0.806B) (1-0.543B(12)) (1-0.321B(2) x 12) micro(t). The predicted incidence rate in 2008 was consistent with the actual one, with the relative error of 6.78%. The predicted incidence rate of dysentery in 2010 based on the incidence rate from January 1990 to June 2009 would be 9.390 per 100 thousand. ARIMA model can be used to fit the changes of incidence rate of dysentery and to forecast the future incidence rate in Shanghai. It is a predicted model of high precision for short-time forecast.

Validity of the Special Needs Education Assessment Tool (SNEAT), a Newly Developed Scale for Children with Disabilities.

PubMed

Kohara, Aiko; Han, ChangWan; Kwon, HaeJin; Kohzuki, Masahiro

2015-11-01

The improvement of the quality of life (QOL) of children with disabilities has been considered important. Therefore, the Special Needs Education Assessment Tool (SNEAT) was developed based on the concept of QOL to objectively evaluate the educational outcome of children with disabilities. SNEAT consists of 11 items in three domains: physical functioning, mental health, and social functioning. This study aimed to verify the reliability and construct validity of SNEAT using 93 children collected from the classes on independent activities of daily living for children with disabilities in Okinawa Prefecture between October and November 2014. Survey data were collected in a longitudinal prospective cohort study. The reliability of SNEAT was verified via the internal consistency method and the test-pretest method; both the coefficient of Cronbach's α and the intra-class correlation coefficient were over 0.7. The validity of SNEAT was also verified via one-way repeated-measures ANOVA and the latent growth curve model. The scores of all the items and domains and the total scores obtained from one-way repeated-measures ANOVA were the same as the predicted scores. SNEAT is valid based on its goodness-of-fit values obtained using the latent growth curve model, where the values of comparative fit index (0.983) and root mean square error of approximation (0.062) were within the goodness-of-fit range. These results indicate that SNEAT has high reliability and construct validity and may contribute to improve QOL of children with disabilities in the classes on independent activities of daily living for children with disabilities.

Validation of the Kp Geomagnetic Index Forecast at CCMC

NASA Astrophysics Data System (ADS)

Frechette, B. P.; Mays, M. L.

2017-12-01

The Community Coordinated Modeling Center (CCMC) Space Weather Research Center (SWRC) sub-team provides space weather services to NASA robotic mission operators and science campaigns and prototypes new models, forecasting techniques, and procedures. The Kp index is a measure of geomagnetic disturbances for space weather in the magnetosphere such as geomagnetic storms and substorms. In this study, we performed validation on the Newell et al. (2007) Kp prediction equation from December 2010 to July 2017. The purpose of this research is to understand the Kp forecast performance because it's critical for NASA missions to have confidence in the space weather forecast. This research was done by computing the Kp error for each forecast (average, minimum, maximum) and each synoptic period. Then to quantify forecast performance we computed the mean error, mean absolute error, root mean square error, multiplicative bias and correlation coefficient. A contingency table was made for each forecast and skill scores were computed. The results are compared to the perfect score and reference forecast skill score. In conclusion, the skill score and error results show that the minimum of the predicted Kp over each synoptic period from the Newell et al. (2007) Kp prediction equation performed better than the maximum or average of the prediction. However, persistence (reference forecast) outperformed all of the Kp forecasts (minimum, maximum, and average). Overall, the Newell Kp prediction still predicts within a range of 1, even though persistence beats it.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

PubMed Central

2014-01-01

Background In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). Results The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. Conclusion Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks. PMID:24955114

Nutritional evaluation of commercial dry dog foods by near infrared reflectance spectroscopy.

PubMed

Alomar, D; Hodgkinson, S; Abarzúa, D; Fuchslocher, R; Alvarado, C; Rosales, E

2006-06-01

Near infrared reflectance spectroscopy (NIRS) was used to predict the nutritional value of dog foods sold in Chile. Fifty-nine dry foods for adult and growing dogs were collected, ground and scanned across the visible/NIR range and subsequently analysed for dry matter (DM), crude protein (CP), crude fibre (CF), total fat, linoleic acid, gross energy (GE), estimated metabolizable energy (ME) and several amino acids and minerals. Calibration equations were developed by modified partial least squares regression, and tested by cross-validation. Standard error of cross validation (SE(CV)) and coefficient of determination of cross validation (SE(CV)) were used to select best equations. Equations with good predicting accuracy were obtained for DM, CF, CP, GE and fat. Corresponding values for and SE(CV) were 0.96 and 1.7 g/kg, 0.91 and 3.1 g/kg, 0.99 and 5.0 g/kg, 0.93 and 0.26 MJ/kg, 0.89 and 12.4 g/kg. Several amino acids were also well predicted, such as arginine, leucine, isoleucine, phenylalanine-tyrosine (combined), threonine and valine, with values for and SE(CV) (g/kg) of 0.89 and 0.9, 0.94 and 1.3, 0.91 and 0.5, 0.95 and 0.9, 0.91 and 0.5, 0.93 and 0.5. Intermediate values, appropriate for ranking purposes, were obtained for ME, histidine, lysine and methionine-cysteine. Tryptophan, minerals or linoleic acid were not acceptably predicted, irrespective of the mathematical treatment applied. It is concluded that NIR can be successfully used to predict important nutritional characteristics of commercial dog foods.

Mass-based design and optimization of wave rotors for gas turbine engine enhancement

NASA Astrophysics Data System (ADS)

Chan, S.; Liu, H.

2017-03-01

An analytic method aiming at mass properties was developed for the preliminary design and optimization of wave rotors. In the present method, we introduce the mass balance principle into the design and thus can predict and optimize the mass qualities as well as the performance of wave rotors. A dedicated least-square method with artificial weighting coefficients was developed to solve the over-constrained system in the mass-based design. This method and the adoption of the coefficients were validated by numerical simulation. Moreover, the problem of fresh air exhaustion (FAE) was put forward and analyzed, and exhaust gas recirculation (EGR) was investigated. Parameter analyses and optimization elucidated which designs would not only achieve the best performance, but also operate with minimum EGR and no FAE.

Forecast of future aviation fuels: The model

NASA Technical Reports Server (NTRS)

Ayati, M. B.; Liu, C. Y.; English, J. M.

1981-01-01

A conceptual models of the commercial air transportation industry is developed which can be used to predict trends in economics, demand, and consumption. The methodology is based on digraph theory, which considers the interaction of variables and propagation of changes. Air transportation economics are treated by examination of major variables, their relationships, historic trends, and calculation of regression coefficients. A description of the modeling technique and a compilation of historic airline industry statistics used to determine interaction coefficients are included. Results of model validations show negligible difference between actual and projected values over the twenty-eight year period of 1959 to 1976. A limited application of the method presents forecasts of air tranportation industry demand, growth, revenue, costs, and fuel consumption to 2020 for two scenarios of future economic growth and energy consumption.

Validity and reliability of the Diagnostic Adaptive Behaviour Scale.

PubMed

Tassé, M J; Schalock, R L; Balboni, G; Spreat, S; Navas, P

2016-01-01

The Diagnostic Adaptive Behaviour Scale (DABS) is a new standardised adaptive behaviour measure that provides information for evaluating limitations in adaptive behaviour for the purpose of determining a diagnosis of intellectual disability. This article presents validity evidence and reliability data for the DABS. Validity evidence was based on comparing DABS scores with scores obtained on the Vineland Adaptive Behaviour Scale, second edition. The stability of the test scores was measured using a test and retest, and inter-rater reliability was assessed by computing the inter-respondent concordance. The DABS convergent validity coefficients ranged from 0.70 to 0.84, while the test-retest reliability coefficients ranged from 0.78 to 0.95, and the inter-rater concordance as measured by intraclass correlation coefficients ranged from 0.61 to 0.87. All obtained validity and reliability indicators were strong and comparable with the validity and reliability coefficients of the most commonly used adaptive behaviour instruments. These results and the advantages of the DABS for clinician and researcher use are discussed. © 2015 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

A Comparison of the Fagerström Test for Cigarette Dependence and Cigarette Dependence Scale in a Treatment-Seeking Sample of Pregnant Smokers.

PubMed

Berlin, Ivan; Singleton, Edward G; Heishman, Stephen J

2016-04-01

Valid and reliable brief measures of cigarette dependence are essential for research purposes and effective clinical care. Two widely-used brief measures of cigarette dependence are the six-item Fagerström Test for Cigarette Dependence (FTCD) and five-item Cigarette Dependence Scale (CDS-5). Their respective metric characteristics among pregnant smokers have not yet been studied. This was a secondary analysis of data of pregnant smokers (N = 476) enrolled in a smoking cessation study. We assessed internal consistency, reliability, and examined correlations between the instruments and smoking-related behaviors for construct validity. We evaluated predictive validity by testing how well the measures predict abstinence 2 weeks after quit date. Cronbach's alpha coefficient for the CDS-5 was 0.62 and for the FTCD 0.55. Measures were strongly correlated with each other, although FTCD, but not CDS-5, was associated with saliva cotinine concentration. The FTCD, CDS-5, craving to smoke, and withdrawal symptoms failed to predict smoking status 2 weeks following the quit date. Suboptimal reliability estimates and failure to predict short-term smoking call into question the value of including either of the brief measures in studies that aim to explain the obstacles to smoking cessation during pregnancy. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Validity, reliability, and acceptability of the scale of knowledge, attitude, and behavior of lifestyle intervention in a diabetes high-risk population].

PubMed

Wang, W J; Dong, J; Ren, Z P; Chen, B; He, W; Li, W D; Hao, Z W

2016-07-06

To evaluate the validity, reliability, and acceptability of the scale of knowledge, attitude, and behavior of lifestyle intervention in a diabetes high-risk population (HILKAB), and provide scientific evidence for its usage. By convenient sampling, we selected 406 individuals at high risk for diabetes for survey using the HILKAB. Pearson correlation coefficient, factor analysis, independent sampling, and t-test for high- and low-score groups were used to evaluate the content validity, construct validity, and discriminant validity of the scale. Reliability of the scale was evaluated by internal consistency, which included Cronbach's α coefficient, θ coefficient, Ω coefficient, and split-half reliability. Scale acceptability was evaluated by acceptance rate and completion time of the survey. In this study, 366 questionnaires (90.1%) was qnalified and the completion time was (8.62±2.79) minutes. Scores for knowledge, attitude, and behavior were 10.60±3.73, 26.56±3.58, 17.09±9.74, respectively. The scale had good face validity and content validity. The correlation coefficient of items and the dimension to which they belong was between 0.25 and 0.97, and the correlation coefficient of three dimensions and the entire scale was between 0.64 and 0.91, all with P<0.001. Factor analysis of the scale extracted eight common factors. The cumulative variance contribution rate was 65.23%, thereby reaching the 50% approved standard. Of 30 items there were 29 items with factor loadings ≥0.40, indicating the scale had good construct validity. For the high-score group, scores for knowledge, attitude, and behavior dimensions were 13.89±2.55, 29.56± 2.46, 28.05 ± 2.93, respectively, which were higher than those for the low-score group (7.67 ± 2.78, 23.89 ± 3.35, 6.25 ± 3.13); t-values were 55.14, 119.40, 95.29, respectively, with P<0.001. The scale consisted of three dimensions: knowledge, attitude, and behavior. The Cronbach's α coefficient was between 0.84 and 0.92, the θ coefficient was between 0.85 and 0.96, the Ω coefficient was between 0.90 and 0.94, and the split-half reliability was between 0.77 and 0.95, reaching the 0.70 standard letter. The validity, reliability, and acceptability of the HILKAB scale were satisfactory for use in a population at high risk of diabetes.

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

An extended CFD model to predict the pumping curve in low pressure plasma etch chamber

NASA Astrophysics Data System (ADS)

Zhou, Ning; Wu, Yuanhao; Han, Wenbin; Pan, Shaowu

2014-12-01

Continuum based CFD model is extended with slip wall approximation and rarefaction effect on viscosity, in an attempt to predict the pumping flow characteristics in low pressure plasma etch chambers. The flow regime inside the chamber ranges from slip wall (Kn ˜ 0.01), and up to free molecular (Kn = 10). Momentum accommodation coefficient and parameters for Kn-modified viscosity are first calibrated against one set of measured pumping curve. Then the validity of this calibrated CFD models are demonstrated in comparison with additional pumping curves measured in chambers of different geometry configurations. More detailed comparison against DSMC model for flow conductance over slits with contraction and expansion sections is also discussed.

Basis Function Approximation of Transonic Aerodynamic Influence Coefficient Matrix

NASA Technical Reports Server (NTRS)

Li, Wesley W.; Pak, Chan-gi

2011-01-01

A technique for approximating the modal aerodynamic influence coefficients matrices by using basis functions has been developed and validated. An application of the resulting approximated modal aerodynamic influence coefficients matrix for a flutter analysis in transonic speed regime has been demonstrated. This methodology can be applied to the unsteady subsonic, transonic, and supersonic aerodynamics. The method requires the unsteady aerodynamics in frequency-domain. The flutter solution can be found by the classic methods, such as rational function approximation, k, p-k, p, root-locus et cetera. The unsteady aeroelastic analysis for design optimization using unsteady transonic aerodynamic approximation is being demonstrated using the ZAERO flutter solver (ZONA Technology Incorporated, Scottsdale, Arizona). The technique presented has been shown to offer consistent flutter speed prediction on an aerostructures test wing 2 configuration with negligible loss in precision in transonic speed regime. These results may have practical significance in the analysis of aircraft aeroelastic calculation and could lead to a more efficient design optimization cycle.

Molecular dynamics calculation of rotational diffusion coefficient of a carbon nanotube in fluid.

PubMed

Cao, Bing-Yang; Dong, Ruo-Yu

2014-01-21

Rotational diffusion processes are correlated with nanoparticle visualization and manipulation techniques, widely used in nanocomposites, nanofluids, bioscience, and so on. However, a systematical methodology of deriving this diffusivity is still lacking. In the current work, three molecular dynamics (MD) schemes, including equilibrium (Green-Kubo formula and Einstein relation) and nonequilibrium (Einstein-Smoluchowski relation) methods, are developed to calculate the rotational diffusion coefficient, taking a single rigid carbon nanotube in fluid argon as a case. We can conclude that the three methods produce same results on the basis of plenty of data with variation of the calculation parameters (tube length, diameter, fluid temperature, density, and viscosity), indicative of the validity and accuracy of the MD simulations. However, these results have a non-negligible deviation from the theoretical predictions of Tirado et al. [J. Chem. Phys. 81, 2047 (1984)], which may come from several unrevealed factors of the theory. The three MD methods proposed in this paper can also be applied to other situations of calculating rotational diffusion coefficient.

Risk score to predict gastrointestinal bleeding after acute ischemic stroke.

PubMed

Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Singhal, Aneesh B; Wang, Yongjun

2014-07-25

Gastrointestinal bleeding (GIB) is a common and often serious complication after stroke. Although several risk factors for post-stroke GIB have been identified, no reliable or validated scoring system is currently available to predict GIB after acute stroke in routine clinical practice or clinical trials. In the present study, we aimed to develop and validate a risk model (acute ischemic stroke associated gastrointestinal bleeding score, the AIS-GIB score) to predict in-hospital GIB after acute ischemic stroke. The AIS-GIB score was developed from data in the China National Stroke Registry (CNSR). Eligible patients in the CNSR were randomly divided into derivation (60%) and internal validation (40%) cohorts. External validation was performed using data from the prospective Chinese Intracranial Atherosclerosis Study (CICAS). Independent predictors of in-hospital GIB were obtained using multivariable logistic regression in the derivation cohort, and β-coefficients were used to generate point scoring system for the AIS-GIB. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively. A total of 8,820, 5,882, and 2,938 patients were enrolled in the derivation, internal validation and external validation cohorts. The overall in-hospital GIB after AIS was 2.6%, 2.3%, and 1.5% in the derivation, internal, and external validation cohort, respectively. An 18-point AIS-GIB score was developed from the set of independent predictors of GIB including age, gender, history of hypertension, hepatic cirrhosis, peptic ulcer or previous GIB, pre-stroke dependence, admission National Institutes of Health stroke scale score, Glasgow Coma Scale score and stroke subtype (Oxfordshire). The AIS-GIB score showed good discrimination in the derivation (0.79; 95% CI, 0.764-0.825), internal (0.78; 95% CI, 0.74-0.82) and external (0.76; 95% CI, 0.71-0.82) validation cohorts. The AIS-GIB score was well calibrated in the derivation (P = 0.42), internal (P = 0.45) and external (P = 0.86) validation cohorts. The AIS-GIB score is a valid clinical grading scale to predict in-hospital GIB after AIS. Further studies on the effect of the AIS-GIB score on reducing GIB and improving outcome after AIS are warranted.

Preoperative implant selection for unilateral breast reconstruction using 3D imaging with the Microsoft Kinect sensor.

PubMed

Pöhlmann, Stefanie T L; Harkness, Elaine; Taylor, Christopher J; Gandhi, Ashu; Astley, Susan M

2017-08-01

This study aimed to investigate whether breast volume measured preoperatively using a Kinect 3D sensor could be used to determine the most appropriate implant size for reconstruction. Ten patients underwent 3D imaging before and after unilateral implant-based reconstruction. Imaging used seven configurations, varying patient pose and Kinect location, which were compared regarding suitability for volume measurement. Four methods of defining the breast boundary for automated volume calculation were compared, and repeatability assessed over five repetitions. The most repeatable breast boundary annotation used an ellipse to track the inframammary fold and a plane describing the chest wall (coefficient of repeatability: 70 ml). The most reproducible imaging position comparing pre- and postoperative volume measurement of the healthy breast was achieved for the sitting patient with elevated arms and Kinect centrally positioned (coefficient of repeatability: 141 ml). Optimal implant volume was calculated by correcting used implant volume by the observed postoperative asymmetry. It was possible to predict implant size using a linear model derived from preoperative volume measurement of the healthy breast (coefficient of determination R 2  = 0.78, standard error of prediction 120 ml). Mastectomy specimen weight and experienced surgeons' choice showed similar predictive ability (both: R 2  = 0.74, standard error: 141/142 ml). A leave one-out validation showed that in 61% of cases, 3D imaging could predict implant volume to within 10%; however for 17% of cases it was >30%. This technology has the potential to facilitate reconstruction surgery planning and implant procurement to maximise symmetry after unilateral reconstruction. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Online physician ratings fail to predict actual performance on measures of quality, value, and peer review.

PubMed

Daskivich, Timothy J; Houman, Justin; Fuller, Garth; Black, Jeanne T; Kim, Hyung L; Spiegel, Brennan

2018-04-01

Patients use online consumer ratings to identify high-performing physicians, but it is unclear if ratings are valid measures of clinical performance. We sought to determine whether online ratings of specialist physicians from 5 platforms predict quality of care, value of care, and peer-assessed physician performance. We conducted an observational study of 78 physicians representing 8 medical and surgical specialties. We assessed the association of consumer ratings with specialty-specific performance scores (metrics including adherence to Choosing Wisely measures, 30-day readmissions, length of stay, and adjusted cost of care), primary care physician peer-review scores, and administrator peer-review scores. Across ratings platforms, multivariable models showed no significant association between mean consumer ratings and specialty-specific performance scores (β-coefficient range, -0.04, 0.04), primary care physician scores (β-coefficient range, -0.01, 0.3), and administrator scores (β-coefficient range, -0.2, 0.1). There was no association between ratings and score subdomains addressing quality or value-based care. Among physicians in the lowest quartile of specialty-specific performance scores, only 5%-32% had consumer ratings in the lowest quartile across platforms. Ratings were consistent across platforms; a physician's score on one platform significantly predicted his/her score on another in 5 of 10 comparisons. Online ratings of specialist physicians do not predict objective measures of quality of care or peer assessment of clinical performance. Scores are consistent across platforms, suggesting that they jointly measure a latent construct that is unrelated to performance. Online consumer ratings should not be used in isolation to select physicians, given their poor association with clinical performance.

Prediction of Very High Reynolds Number Compressible Skin Friction

NASA Technical Reports Server (NTRS)

Carlson, John R.

1998-01-01

Flat plate skin friction calculations over a range of Mach numbers from 0.4 to 3.5 at Reynolds numbers from 16 million to 492 million using a Navier Stokes method with advanced turbulence modeling are compared with incompressible skin friction coefficient correlations. The semi-empirical correlation theories of van Driest; Cope; Winkler and Cha; and Sommer and Short T' are used to transform the predicted skin friction coefficients of solutions using two algebraic Reynolds stress turbulence models in the Navier-Stokes method PAB3D. In general, the predicted skin friction coefficients scaled well with each reference temperature theory though, overall the theory by Sommer and Short appeared to best collapse the predicted coefficients. At the lower Reynolds number 3 to 30 million, both the Girimaji and Shih, Zhu and Lumley turbulence models predicted skin-friction coefficients within 2% of the semi-empirical correlation skin friction coefficients. At the higher Reynolds numbers of 100 to 500 million, the turbulence models by Shih, Zhu and Lumley and Girimaji predicted coefficients that were 6% less and 10% greater, respectively, than the semi-empirical coefficients.

Spanish validation of the Person-centered Care Assessment Tool (P-CAT).

PubMed

Martínez, Teresa; Suárez-Álvarez, Javier; Yanguas, Javier; Muñiz, José

2016-01-01

Person-centered Care (PCC) is an innovative approach which seeks to improve the quality of care services given to the care-dependent elderly. At present there are no Spanish language instruments for the evaluation of PCC delivered by elderly care services. The aim of this work is the adaptation and validation of the Person-centered Care Assessment Tool (P-CAT) for a Spanish population. The P-CAT was translated and adapted into Spanish, then given to a sample of 1339 front-line care professionals from 56 residential elderly care homes. The reliability and validity of the P-CAT were analyzed, within the frameworks of Classical Test Theory and Item Response Theory models. The Spanish P-CAT demonstrated good reliability, with an alpha coefficient of .88 and a test-retest reliability coefficient of .79. The P-CAT information function indicates that the test measures with good precision for the majority of levels of the measured variables (θ values between -2 and +1). The factorial structure of the test is essentially one-dimensional and the item discrimination indices are high, with values between .26 and .61. In terms of predictive validity, the correlations which stand out are between the P-CAT and organizational climate (r = .689), and the burnout factors; personal accomplishment (r = .382), and emotional exhaustion (r = - .510). The Spanish version of the P-CAT demonstrates good psychometric properties for its use in the evaluation of elderly care homes both professionally and in research.

Development and Validation of a Disease Severity Scoring Model for Pediatric Sepsis.

PubMed

Hu, Li; Zhu, Yimin; Chen, Mengshi; Li, Xun; Lu, Xiulan; Liang, Ying; Tan, Hongzhuan

2016-07-01

Multiple severity scoring systems have been devised and evaluated in adult sepsis, but a simplified scoring model for pediatric sepsis has not yet been developed. This study aimed to develop and validate a new scoring model to stratify the severity of pediatric sepsis, thus assisting the treatment of sepsis in children. Data from 634 consecutive patients who presented with sepsis at Children's hospital of Hunan province in China in 2011-2013 were analyzed, with 476 patients placed in training group and 158 patients in validation group. Stepwise discriminant analysis was used to develop the accurate discriminate model. A simplified scoring model was generated using weightings defined by the discriminate coefficients. The discriminant ability of the model was tested by receiver operating characteristic curves (ROC). The discriminant analysis showed that prothrombin time, D-dimer, total bilirubin, serum total protein, uric acid, PaO2/FiO2 ratio, myoglobin were associated with severity of sepsis. These seven variables were assigned with values of 4, 3, 3, 4, 3, 3, 3 respectively based on the standardized discriminant coefficients. Patients with higher scores had higher risk of severe sepsis. The areas under ROC (AROC) were 0.836 for accurate discriminate model, and 0.825 for simplified scoring model in validation group. The proposed disease severity scoring model for pediatric sepsis showed adequate discriminatory capacity and sufficient accuracy, which has important clinical significance in evaluating the severity of pediatric sepsis and predicting its progress.

A novel body circumferences-based estimation of percentage body fat.

PubMed

Lahav, Yair; Epstein, Yoram; Kedem, Ron; Schermann, Haggai

2018-03-01

Anthropometric measures of body composition are often used for rapid and cost-effective estimation of percentage body fat (%BF) in field research, serial measurements and screening. Our aim was to develop a validated estimate of %BF for the general population, based on simple body circumferences measures. The study cohort consisted of two consecutive samples of health club members, designated as 'development' (n 476, 61 % men, 39 % women) and 'validation' (n 224, 50 % men, 50 % women) groups. All subjects underwent anthropometric measurements as part of their registration to a health club. Dual-energy X-ray absorptiometry (DEXA) scan was used as the 'gold standard' estimate of %BF. Linear regressions where used to construct the predictive equation (%BFcal). Bland-Altman statistics, Lin concordance coefficients and percentage of subjects falling within 5 % of %BF estimate by DEXA were used to evaluate accuracy and precision of the equation. The variance inflation factor was used to check multicollinearity. Two distinct equations were developed for men and women: %BFcal (men)=10·1-0·239H+0·8A-0·5N; %BFcal (women)=19·2-0·239H+0·8A-0·5N (H, height; A, abdomen; N, neck, all in cm). Bland-Altman differences were randomly distributed and showed no fixed bias. Lin concordance coefficients of %BFcal were 0·89 in men and 0·86 in women. About 79·5 % of %BF predictions in both sexes were within ±5 % of the DEXA value. The Durnin-Womersley skinfolds equation was less accurate in our study group for prediction of %BF than %BFcal. We conclude that %BFcal offers the advantage of obtaining a reliable estimate of %BF from simple measurements that require no sophisticated tools and only a minimal prior training and experience.

Component-based model to predict aerodynamic noise from high-speed train pantographs

NASA Astrophysics Data System (ADS)

Latorre Iglesias, E.; Thompson, D. J.; Smith, M. G.

2017-04-01

At typical speeds of modern high-speed trains the aerodynamic noise produced by the airflow over the pantograph is a significant source of noise. Although numerical models can be used to predict this they are still very computationally intensive. A semi-empirical component-based prediction model is proposed to predict the aerodynamic noise from train pantographs. The pantograph is approximated as an assembly of cylinders and bars with particular cross-sections. An empirical database is used to obtain the coefficients of the model to account for various factors: incident flow speed, diameter, cross-sectional shape, yaw angle, rounded edges, length-to-width ratio, incoming turbulence and directivity. The overall noise from the pantograph is obtained as the incoherent sum of the predicted noise from the different pantograph struts. The model is validated using available wind tunnel noise measurements of two full-size pantographs. The results show the potential of the semi-empirical model to be used as a rapid tool to predict aerodynamic noise from train pantographs.

Thermal conductivity of microporous layers: Analytical modeling and experimental validation

NASA Astrophysics Data System (ADS)

Andisheh-Tadbir, Mehdi; Kjeang, Erik; Bahrami, Majid

2015-11-01

A new compact relationship is developed for the thermal conductivity of the microporous layer (MPL) used in polymer electrolyte fuel cells as a function of pore size distribution, porosity, and compression pressure. The proposed model is successfully validated against experimental data obtained from a transient plane source thermal constants analyzer. The thermal conductivities of carbon paper samples with and without MPL were measured as a function of load (1-6 bars) and the MPL thermal conductivity was found between 0.13 and 0.17 W m-1 K-1. The proposed analytical model predicts the experimental thermal conductivities within 5%. A correlation generated from the analytical model was used in a multi objective genetic algorithm to predict the pore size distribution and porosity for an MPL with optimized thermal conductivity and mass diffusivity. The results suggest that an optimized MPL, in terms of heat and mass transfer coefficients, has an average pore size of 122 nm and 63% porosity.

Validation of equations for pleural effusion volume estimation by ultrasonography.

PubMed

Hassan, Maged; Rizk, Rana; Essam, Hatem; Abouelnour, Ahmed

2017-12-01

To validate the accuracy of previously published equations that estimate pleural effusion volume using ultrasonography. Only equations using simple measurements were tested. Three measurements were taken at the posterior axillary line for each case with effusion: lateral height of effusion ( H ), distance between collapsed lung and chest wall ( C ) and distance between lung and diaphragm ( D ). Cases whose effusion was aspirated to dryness were included and drained volume was recorded. Intra-class correlation coefficient (ICC) was used to determine the predictive accuracy of five equations against the actual volume of aspirated effusion. 46 cases with effusion were included. The most accurate equation in predicting effusion volume was ( H  +  D ) × 70 (ICC 0.83). The simplest and yet accurate equation was H  × 100 (ICC 0.79). Pleural effusion height measured by ultrasonography gives a reasonable estimate of effusion volume. Incorporating distance between lung base and diaphragm into estimation improves accuracy from 79% with the first method to 83% with the latter.

Identify Secretory Protein of Malaria Parasite with Modified Quadratic Discriminant Algorithm and Amino Acid Composition.

PubMed

Feng, Yong-E

2016-06-01

Malaria parasite secretes various proteins in infected red blood cell for its growth and survival. Thus identification of these secretory proteins is important for developing vaccine or drug against malaria. In this study, the modified method of quadratic discriminant analysis is presented for predicting the secretory proteins. Firstly, 20 amino acids are divided into five types according to the physical and chemical characteristics of amino acids. Then, we used five types of amino acids compositions as inputs of the modified quadratic discriminant algorithm. Finally, the best prediction performance is obtained by using 20 amino acid compositions, the sensitivity of 96 %, the specificity of 92 % with 0.88 of Mathew's correlation coefficient in fivefold cross-validation test. The results are also compared with those of existing prediction methods. The compared results shown our method are prominent in the prediction of secretory proteins.

Sliding contact fracture of dental ceramics: Principles and validation

PubMed Central

Ren, Linlin; Zhang, Yu

2014-01-01

Ceramic prostheses are subject to sliding contact under normal and tangential loads. Accurate prediction of the onset of fracture at two contacting surfaces holds the key to greater long-term performance of these prostheses. In this study, building on stress analysis of Hertzian contact and considering fracture criteria for linear elastic materials, a constitutive fracture mechanics relation was developed to incorporate the critical fracture load with the contact geometry, coefficient of friction and material fracture toughness. Critical loads necessary to cause fracture under a sliding indenter were calculated from the constitutive equation, and compared with the loads predicted from elastic stress analysis in conjunction with measured critical load for frictionless normal contact—a semi-empirical approach. The major predictions of the models were calibrated with experimentally determined critical loads of current and future dental ceramics after contact with a rigid spherical slider. Experimental results conform with the trends predicted by the models. PMID:24632538

Effects of the approximations of light propagation on quantitative photoacoustic tomography using two-dimensional photon diffusion equation and linearization

NASA Astrophysics Data System (ADS)

Okawa, Shinpei; Hirasawa, Takeshi; Kushibiki, Toshihiro; Ishihara, Miya

2017-12-01

Quantitative photoacoustic tomography (QPAT) employing a light propagation model will play an important role in medical diagnoses by quantifying the concentration of hemoglobin or a contrast agent. However, QPAT by the light propagation model with the three-dimensional (3D) radiative transfer equation (RTE) requires a huge computational load in the iterative forward calculations involved in the updating process to reconstruct the absorption coefficient. The approximations of the light propagation improve the efficiency of the image reconstruction for the QPAT. In this study, we compared the 3D/two-dimensional (2D) photon diffusion equation (PDE) approximating 3D RTE with the Monte Carlo simulation based on 3D RTE. Then, the errors in a 2D PDE-based linearized image reconstruction caused by the approximations were quantitatively demonstrated and discussed in the numerical simulations. It was clearly observed that the approximations affected the reconstructed absorption coefficient. The 2D PDE-based linearized algorithm succeeded in the image reconstruction of the region with a large absorption coefficient in the 3D phantom. The value reconstructed in the phantom experiment agreed with that in the numerical simulation, so that it was validated that the numerical simulation of the image reconstruction predicted the relationship between the true absorption coefficient of the target in the 3D medium and the reconstructed value with the 2D PDE-based linearized algorithm. Moreover, the the true absorption coefficient in 3D medium was estimated from the 2D reconstructed image on the basis of the prediction by the numerical simulation. The estimation was successful in the phantom experiment, although some limitations were revealed.

Quantitative structure-activity relationship for the partition coefficient of hydrophobic compounds between silicone oil and air.

PubMed

Qu, Yanfei; Ma, Yongwen; Wan, Jinquan; Wang, Yan

2018-06-01

The silicon oil-air partition coefficients (K SiO/A ) of hydrophobic compounds are vital parameters for applying silicone oil as non-aqueous-phase liquid in partitioning bioreactors. Due to the limited number of K SiO/A values determined by experiment for hydrophobic compounds, there is an urgent need to model the K SiO/A values for unknown chemicals. In the present study, we developed a universal quantitative structure-activity relationship (QSAR) model using a sequential approach with macro-constitutional and micromolecular descriptors for silicone oil-air partition coefficients (K SiO/A ) of hydrophobic compounds with large structural variance. The geometry optimization and vibrational frequencies of each chemical were calculated using the hybrid density functional theory at the B3LYP/6-311G** level. Several quantum chemical parameters that reflect various intermolecular interactions as well as hydrophobicity were selected to develop QSAR model. The result indicates that a regression model derived from logK SiO/A , the number of non-hydrogen atoms (#nonHatoms) and energy gap of E LUMO and E HOMO (E LUMO -E HOMO ) could explain the partitioning mechanism of hydrophobic compounds between silicone oil and air. The correlation coefficient R 2 of the model is 0.922, and the internal and external validation coefficient, Q 2 LOO and Q 2 ext , are 0.91 and 0.89 respectively, implying that the model has satisfactory goodness-of-fit, robustness, and predictive ability and thus provides a robust predictive tool to estimate the logK SiO/A values for chemicals in application domain. The applicability domain of the model was visualized by the Williams plot.

Correlations between symptoms, nasal endoscopy, and in-office computed tomography in post-surgical chronic rhinosinusitis patients.

PubMed

Ryan, William R; Ramachandra, Tara; Hwang, Peter H

2011-03-01

To determine correlations between symptoms, nasal endoscopy findings, and computed tomography (CT) scan findings in post-surgical chronic rhinosinusitis (CRS) patients. Cross-sectional. A total of 51 CRS patients who had undergone endoscopic sinus surgery (ESS) completed symptom questionnaires, underwent endoscopy, and received an in-office sinus CT scan during one clinic visit. For metrics, we used the Sinonasal Outcomes Test-20 (SNOT-20) questionnaire, visual analog symptom scale (VAS), Lund-Kennedy endoscopy scoring scale, and Lund-MacKay (LM) CT scoring scale. We determined Pearson correlation coefficients, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) between scores for symptoms, endoscopy, and CT. The SNOT-20 score and most VAS symptoms had poor correlation coefficients with both endoscopy and CT scores (0.03-0.24). Nasal drainage of pus, nasal congestion, and impaired sense of smell had moderate correlation coefficients with endoscopy and CT (0.24-0.42). Endoscopy had a strong correlation coefficient with CT (0.76). Drainage, edema, and polyps had strong correlation coefficients with CT (0.80, 0.69, and 0.49, respectively). Endoscopy had a PPV of 92.5% and NPV of 45.5% for detecting an abnormal sinus CT (LM score ≥1). In post-ESS CRS patients, most symptoms do not correlate well with either endoscopy or CT findings. Endoscopy and CT scores correlate well. Abnormal endoscopy findings have the ability to confidently rule in the presence of CT opacification, thus validating the importance of endoscopy in clinical decision making. However, a normal endoscopy cannot assure a normal CT. Thus, symptoms, endoscopy, and CT are complementary in the evaluation of the post-ESS CRS patient. Copyright © 2011 The American Laryngological, Rhinological, and Otological Society, Inc., Rhinological, and Otological Society, Inc.

External Heat Transfer Coefficient Measurements on a Surrogate Indirect Inertial Confinement Fusion Target

DOE PAGES

Miles, Robin; Havstad, Mark; LeBlanc, Mary; ...

2015-09-15

External heat transfer coefficients were measured around a surrogate Indirect inertial confinement fusion (ICF) based on the Laser Inertial Fusion Energy (LIFE) design target to validate thermal models of the LIFE target during flight through a fusion chamber. Results indicate that heat transfer coefficients for this target 25-50 W/m 2∙K are consistent with theoretically derived heat transfer coefficients and valid for use in calculation of target heating during flight through a fusion chamber.

At-line determination of pharmaceuticals small molecule's blending end point using chemometric modeling combined with Fourier transform near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tewari, Jagdish; Strong, Richard; Boulas, Pierre

2017-02-01

This article summarizes the development and validation of a Fourier transform near infrared spectroscopy (FT-NIR) method for the rapid at-line prediction of active pharmaceutical ingredient (API) in a powder blend to optimize small molecule formulations. The method was used to determine the blend uniformity end-point for a pharmaceutical solid dosage formulation containing a range of API concentrations. A set of calibration spectra from samples with concentrations ranging from 1% to 15% of API (w/w) were collected at-line from 4000 to 12,500 cm- 1. The ability of the FT-NIR method to predict API concentration in the blend samples was validated against a reference high performance liquid chromatography (HPLC) method. The prediction efficiency of four different types of multivariate data modeling methods such as partial least-squares 1 (PLS1), partial least-squares 2 (PLS2), principal component regression (PCR) and artificial neural network (ANN), were compared using relevant multivariate figures of merit. The prediction ability of the regression models were cross validated against results generated with the reference HPLC method. PLS1 and ANN showed excellent and superior prediction abilities when compared to PLS2 and PCR. Based upon these results and because of its decreased complexity compared to ANN, PLS1 was selected as the best chemometric method to predict blend uniformity at-line. The FT-NIR measurement and the associated chemometric analysis were implemented in the production environment for rapid at-line determination of the end-point of the small molecule blending operation. FIGURE 1: Correlation coefficient vs Rank plot FIGURE 2: FT-NIR spectra of different steps of Blend and final blend FIGURE 3: Predictions ability of PCR FIGURE 4: Blend uniformity predication ability of PLS2 FIGURE 5: Prediction efficiency of blend uniformity using ANN FIGURE 6: Comparison of prediction efficiency of chemometric models TABLE 1: Order of Addition for Blending Steps

Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C 4 Grasses in Hawaii

DOE PAGES

Youkhana, Adel H.; Ogoshi, Richard M.; Kiniry, James R.; ...

2017-05-02

Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C 4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewablemore » energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R 2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C4 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.« less

Reliability, validity, sensitivity and specificity of Guajarati version of the Roland-Morris Disability Questionnaire.

PubMed

Nambi, S Gopal

2013-01-01

The most common instruments developed to assess the functional status of patients with Non specific low back pain is the Roland-Morris Disability Questionnaire (RMDQ). Clinical and epidemiological research related to low back pain in the Gujarati population would be facilitated by the availability of well-established outcome measures. To find the reliability, validity, sensitivity and specificity of the Gujarati version of the RMDQ for use in Non Specific Chronic low back pain. A reliability, validity, sensitivity and specificity study of Gujarati version of the Roland-Morris Disability Questionnaire (RMDQ). Thirty out patients with Non Specific Chronic low back pain were assessed by the RMDQ. Reliability is assessed by using internal consistency and the intra-class correlation coefficient (ICC). Internal construct validity is assessed by RASCH Analysis and external construct validity is assessed by association with pain and spinal movement. Clinical calculator was used to determine the sensitivity and specificity. Internal consistency of the RMDQ is found to be adequate (> 0.65) at both times, with high ICC's also at both time points. Internal construct validity of the scale is good, indicating a single underlying construct. Expected associations with pain and spinal movement confirm external construct validity. The Sensitivity and Specificity at cut off point of 0.5 was 80% and 84% with respectively positive predictive value (PPV) of 83.33% and negative predictive value (NPV) of 80.76%. The Questionnaire is at the ordinal level. The RMDQ is a one-dimensional, ordinal measure, which works well in the Gujarati population.

3D-QSAR studies on the inhibitory activity of trimethoprim analogues against Escherichia coli dihydrofolate reductase.

PubMed

Vijayaraj, Ramadoss; Devi, Mekapothula Lakshmi Vasavi; Subramanian, Venkatesan; Chattaraj, Pratim Kumar

2012-06-01

Three-dimensional quantitative structure activity relationship (3D-QSAR) study has been carried out on the Escherichia coli DHFR inhibitors 2,4-diamino-5-(substituted-benzyl)pyrimidine derivatives to understand the structural features responsible for the improved potency. To construct highly predictive 3D-QSAR models, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were used. The predicted models show statistically significant cross-validated and non-cross-validated correlation coefficient of r2 CV and r2 nCV, respectively. The final 3D-QSAR models were validated using structurally diverse test set compounds. Analysis of the contour maps generated from CoMFA and CoMSIA methods reveals that the substitution of electronegative groups at the first and second position along with electropositive group at the third position of R2 substitution significantly increases the potency of the derivatives. The results obtained from the CoMFA and CoMSIA study delineate the substituents on the trimethoprim analogues responsible for the enhanced potency and also provide valuable directions for the design of new trimethoprim analogues with improved affinity. © 2012 John Wiley & Sons A/S.

Development and validation of a risk-prediction nomogram for in-hospital mortality in adults poisoned with drugs and nonpharmaceutical agents

PubMed Central

Lionte, Catalina; Sorodoc, Victorita; Jaba, Elisabeta; Botezat, Alina

2017-01-01

Abstract Acute poisoning with drugs and nonpharmaceutical agents represents an important challenge in the emergency department (ED). The objective is to create and validate a risk-prediction nomogram for use in the ED to predict the risk of in-hospital mortality in adults from acute poisoning with drugs and nonpharmaceutical agents. This was a prospective cohort study involving adults with acute poisoning from drugs and nonpharmaceutical agents admitted to a tertiary referral center for toxicology between January and December 2015 (derivation cohort) and between January and June 2016 (validation cohort). We used a program to generate nomograms based on binary logistic regression predictive models. We included variables that had significant associations with death. Using regression coefficients, we calculated scores for each variable, and estimated the event probability. Model validation was performed using bootstrap to quantify our modeling strategy and using receiver operator characteristic (ROC) analysis. The nomogram was tested on a separate validation cohort using ROC analysis and goodness-of-fit tests. Data from 315 patients aged 18 to 91 years were analyzed (n = 180 in the derivation cohort; n = 135 in the validation cohort). In the final model, the following variables were significantly associated with mortality: age, laboratory test results (lactate, potassium, MB isoenzyme of creatine kinase), electrocardiogram parameters (QTc interval), and echocardiography findings (E wave velocity deceleration time). Sex was also included to use the same model for men and women. The resulting nomogram showed excellent survival/mortality discrimination (area under the curve [AUC] 0.976, 95% confidence interval [CI] 0.954–0.998, P < 0.0001 for the derivation cohort; AUC 0.957, 95% CI 0.892–1, P < 0.0001 for the validation cohort). This nomogram provides more precise, rapid, and simple risk-analysis information for individual patients acutely exposed to drugs and nonpharmaceutical agents, and accurately estimates the probability of in-hospital death, exclusively using the results of objective tests available in the ED. PMID:28328838

Pooled Results From 5 Validation Studies of Dietary Self-Report Instruments Using Recovery Biomarkers for Energy and Protein Intake

PubMed Central

Freedman, Laurence S.; Commins, John M.; Moler, James E.; Arab, Lenore; Baer, David J.; Kipnis, Victor; Midthune, Douglas; Moshfegh, Alanna J.; Neuhouser, Marian L.; Prentice, Ross L.; Schatzkin, Arthur; Spiegelman, Donna; Subar, Amy F.; Tinker, Lesley F.; Willett, Walter

2014-01-01

We pooled data from 5 large validation studies of dietary self-report instruments that used recovery biomarkers as references to clarify the measurement properties of food frequency questionnaires (FFQs) and 24-hour recalls. The studies were conducted in widely differing US adult populations from 1999 to 2009. We report on total energy, protein, and protein density intakes. Results were similar across sexes, but there was heterogeneity across studies. Using a FFQ, the average correlation coefficients for reported versus true intakes for energy, protein, and protein density were 0.21, 0.29, and 0.41, respectively. Using a single 24-hour recall, the coefficients were 0.26, 0.40, and 0.36, respectively, for the same nutrients and rose to 0.31, 0.49, and 0.46 when three 24-hour recalls were averaged. The average rate of under-reporting of energy intake was 28% with a FFQ and 15% with a single 24-hour recall, but the percentages were lower for protein. Personal characteristics related to under-reporting were body mass index, educational level, and age. Calibration equations for true intake that included personal characteristics provided improved prediction. This project establishes that FFQs have stronger correlations with truth for protein density than for absolute protein intake, that the use of multiple 24-hour recalls substantially increases the correlations when compared with a single 24-hour recall, and that body mass index strongly predicts under-reporting of energy and protein intakes. PMID:24918187

Comparative molecular field analysis and molecular docking studies on novel aryl chalcone derivatives against an important drug target cysteine protease in Plasmodium falciparum.

PubMed

Thillainayagam, Mahalakshmi; Anbarasu, Anand; Ramaiah, Sudha

2016-08-21

The computational studies namely molecular docking simulations and Comparative Molecular Field Analysis (CoMFA) are executed on series of 52 novel aryl chalcones derivatives using Plasmodium falciparum cysteine proteases (falcipain - 2) as vital target. In the present study, the correlation between different molecular field effects namely steric and electrostatic interactions and chemical structures to the inhibitory activities of novel aryl chalcone derivatives is inferred to perceive the major structural prerequisites for the rational design and development of potent and novel lead anti-malarial compound. The apparent binding conformations of all the compounds at the active site of falcipain - 2 and the hydrogen-bond interactions which could be used to modify the inhibitory activities are identified by using Surflex-dock study. Statistically significant CoMFA model has been developed with the cross-validated correlation coefficient (q(2)) of 0.912 and the non-cross-validated correlation coefficient (r(2)) of 0.901. Standard error of estimation (SEE) of 0.210, with the optimum number of components is ten. The predictability of the derived model is examined with a test set consists of sixteen compounds and the predicted r(2) value is found to be 0.924. The docking and QSAR study results confer crucial suggestions for the optimization of novel 1,3-diphenyl-2-propen-1-one derivatives and synthesis of effective anti- malarial compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

Expression profiles of loneliness-associated genes for survival prediction in cancer patients.

PubMed

You, Liang-Fu; Yeh, Jia-Rong; Su, Mu-Chun

2014-01-01

Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high- lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness- associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

[Study on freshness evaluation of ice-stored large yellow croaker (Pseudosciaena crocea) using near infrared spectroscopy].

PubMed

Liu, Yuan; Chen, Wei-Hua; Hou, Qiao-Juan; Wang, Xi-Chang; Dong, Ruo-Yan; Wu, Hao

2014-04-01

Near infrared spectroscopy (NIR) was used in this experiment to evaluate the freshness of ice-stored large yellow croaker (Pseudosciaena crocea) during different storage periods. And the TVB-N was used as an index to evaluate the freshness. Through comparing the correlation coefficent and standard deviations of calibration set and validation set of models established by singly and combined using of different pretreatment methods, different modeling methods and different wavelength region, the best TVB-N models of ice-stored large yellow croaker sold in the market were established to predict the freshness quickly. According to the research, the model shows that the best performance could be established by using the normalization by closure (Ncl) with 1st derivative (Dbl) and normalization to unit length (Nle) with 1st derivative as the pretreated method and partial least square (PLS) as the modeling method combined with choosing the wavelength region of 5 000-7 144, and 7 404-10 000 cm(-1). The calibration model gave the correlation coefficient of 0.992, with a standard error of calibration of 1.045 and the validation model gave the correlation coefficient of 0.999, with a standard error of prediction of 0.990. This experiment attempted to combine several pretreatment methods and choose the best wavelength region, which has got a good result. It could have a good prospective application of freshness detection and quality evaluation of large yellow croaker in the market.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

USGS Publications Warehouse

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

Raman spectroscopy-based screening of hepatitis C and associated molecular changes

NASA Astrophysics Data System (ADS)

Bilal, Maria; Bilal, M.; Saleem, M.; Khan, Saranjam; Ullah, Rahat; Fatima, Kiran; Ahmed, M.; Hayat, Abbas; Shahzada, Shaista; Ullah Khan, Ehsan

2017-09-01

This study presents the optical screening of hepatitis C and its associated molecular changes in human blood sera using a partial least-squares regression model based on their Raman spectra. In total, 152 samples were tested through enzyme-linked immunosorbent assay for confirmation. This model utilizes minor spectral variations in the Raman spectra of the positive and control groups. Regression coefficients of this model were analyzed with reference to the variations in concentration of associated molecules in these two groups. It was found that trehalose, chitin, ammonia, and cytokines are positively correlated while lipids, beta structures of proteins, and carbohydrate-binding proteins are negatively correlated with hepatitis C. The regression vector yielded by this model is utilized to predict hepatitis C in unknown samples. This model has been evaluated by a cross-validation method, which yielded a correlation coefficient of 0.91. Moreover, 30 unknown samples were screened for hepatitis C infection using this model to test its performance. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve from these predictions were found to be 93.3%, 100%, 96.7%, and 1, respectively.

An effective approach to quantitative analysis of ternary amino acids in foxtail millet substrate based on terahertz spectroscopy.

PubMed

Lu, Shao Hua; Li, Bao Qiong; Zhai, Hong Lin; Zhang, Xin; Zhang, Zhuo Yong

2018-04-25

Terahertz time-domain spectroscopy has been applied to many fields, however, it still encounters drawbacks in multicomponent mixtures analysis due to serious spectral overlapping. Here, an effective approach to quantitative analysis was proposed, and applied on the determination of the ternary amino acids in foxtail millet substrate. Utilizing three parameters derived from the THz-TDS, the images were constructed and the Tchebichef image moments were used to extract the information of target components. Then the quantitative models were obtained by stepwise regression. The correlation coefficients of leave-one-out cross-validation (R loo-cv 2 ) were more than 0.9595. As for external test set, the predictive correlation coefficients (R p 2 ) were more than 0.8026 and the root mean square error of prediction (RMSE p ) were less than 1.2601. Compared with the traditional methods (PLS and N-PLS methods), our approach is more accurate, robust and reliable, and can be a potential excellent approach to quantify multicomponent with THz-TDS spectroscopy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reference-free determination of tissue absorption coefficient by modulation transfer function characterization in spatial frequency domain.

PubMed

Chen, Weiting; Zhao, Huijuan; Li, Tongxin; Yan, Panpan; Zhao, Kuanxin; Qi, Caixia; Gao, Feng

2017-08-08

Spatial frequency domain (SFD) measurement allows rapid and non-contact wide-field imaging of the tissue optical properties, thus has become a potential tool for assessing physiological parameters and therapeutic responses during photodynamic therapy of skin diseases. The conventional SFD measurement requires a reference measurement within the same experimental scenario as that for a test one to calibrate mismatch between the real measurements and the model predictions. Due to the individual physical and geometrical differences among different tissues, organs and patients, an ideal reference measurement might be unavailable in clinical trials. To address this problem, we present a reference-free SFD determination of absorption coefficient that is based on the modulation transfer function (MTF) characterization. Instead of the absolute amplitude that is used in the conventional SFD approaches, we herein employ the MTF to characterize the propagation of the modulated lights in tissues. With such a dimensionless relative quantity, the measurements can be naturally corresponded to the model predictions without calibrating the illumination intensity. By constructing a three-dimensional database that portrays the MTF as a function of the optical properties (both the absorption coefficient μ a and the reduced scattering coefficient [Formula: see text]) and the spatial frequency, a look-up table approach or a least-square curve-fitting method is readily applied to recover the absorption coefficient from a single frequency or multiple frequencies, respectively. Simulation studies have verified the feasibility of the proposed reference-free method and evaluated its accuracy in the absorption recovery. Experimental validations have been performed on homogeneous tissue-mimicking phantoms with μ a ranging from 0.01 to 0.07 mm -1 and [Formula: see text] = 1.0 or 2.0 mm -1 . The results have shown maximum errors of 4.86 and 7% for [Formula: see text] = 1.0 mm -1 and [Formula: see text] = 2.0 mm -1 , respectively. We have also presented quantitative ex vivo imaging of human lung cancer in a subcutaneous xenograft mouse model for further validation, and observed high absorption contrast in the tumor region. The proposed method can be applied to the rapid and accurate determination of the absorption coefficient, and better yet, in a reference-free way. We believe this reference-free strategy will facilitate the clinical translation of the SFD measurement to achieve enhanced intraoperative hemodynamic monitoring and personalized treatment planning in photodynamic therapy.

A novel household water insecurity scale: Procedures and psychometric analysis among postpartum women in western Kenya.

PubMed

Boateng, Godfred O; Collins, Shalean M; Mbullo, Patrick; Wekesa, Pauline; Onono, Maricianah; Neilands, Torsten B; Young, Sera L

2018-01-01

Our ability to measure household-level food insecurity has revealed its critical role in a range of physical, psychosocial, and health outcomes. Currently, there is no analogous, standardized instrument for quantifying household-level water insecurity, which prevents us from understanding both its prevalence and consequences. Therefore, our objectives were to develop and validate a household water insecurity scale appropriate for use in our cohort in western Kenya. We used a range of qualitative techniques to develop a preliminary set of 29 household water insecurity questions and administered those questions at 15 and 18 months postpartum, concurrent with a suite of other survey modules. These data were complemented by data on quantity of water used and stored, and microbiological quality. Inter-item and item-total correlations were performed to reduce scale items to 20. Exploratory factor and parallel analyses were used to determine the latent factor structure; a unidimensional scale was hypothesized and tested using confirmatory factor and bifactor analyses, along with multiple statistical fit indices. Reliability was assessed using Cronbach's alpha and the coefficient of stability, which produced a coefficient alpha of 0.97 at 15 and 18 months postpartum and a coefficient of stability of 0.62. Predictive, convergent and discriminant validity of the final household water insecurity scale were supported based on relationships with food insecurity, perceived stress, per capita household water use, and time and money spent acquiring water. The resultant scale is a valid and reliable instrument. It can be used in this setting to test a range of hypotheses about the role of household water insecurity in numerous physical and psychosocial health outcomes, to identify the households most vulnerable to water insecurity, and to evaluate the effects of water-related interventions. To extend its applicability, we encourage efforts to develop a cross-culturally valid scale using robust qualitative and quantitative techniques.

Optimization and experimental validation of a thermal cycle that maximizes entropy coefficient fisher identifiability for lithium iron phosphate cells

NASA Astrophysics Data System (ADS)

Mendoza, Sergio; Rothenberger, Michael; Hake, Alison; Fathy, Hosam

2016-03-01

This article presents a framework for optimizing the thermal cycle to estimate a battery cell's entropy coefficient at 20% state of charge (SOC). Our goal is to maximize Fisher identifiability: a measure of the accuracy with which a parameter can be estimated. Existing protocols in the literature for estimating entropy coefficients demand excessive laboratory time. Identifiability optimization makes it possible to achieve comparable accuracy levels in a fraction of the time. This article demonstrates this result for a set of lithium iron phosphate (LFP) cells. We conduct a 24-h experiment to obtain benchmark measurements of their entropy coefficients. We optimize a thermal cycle to maximize parameter identifiability for these cells. This optimization proceeds with respect to the coefficients of a Fourier discretization of this thermal cycle. Finally, we compare the estimated parameters using (i) the benchmark test, (ii) the optimized protocol, and (iii) a 15-h test from the literature (by Forgez et al.). The results are encouraging for two reasons. First, they confirm the simulation-based prediction that the optimized experiment can produce accurate parameter estimates in 2 h, compared to 15-24. Second, the optimized experiment also estimates a thermal time constant representing the effects of thermal capacitance and convection heat transfer.

A test of source-surface model predictions of heliospheric current sheet inclination

NASA Technical Reports Server (NTRS)

Burton, M. E.; Crooker, N. U.; Siscoe, G. L.; Smith, E. J.

1994-01-01

The orientation of the heliospheric current sheet predicted from a source surface model is compared with the orientation determined from minimum-variance analysis of International Sun-Earth Explorer (ISEE) 3 magnetic field data at 1 AU near solar maximum. Of the 37 cases analyzed, 28 have minimum variance normals that lie orthogonal to the predicted Parker spiral direction. For these cases, the correlation coefficient between the predicted and measured inclinations is 0.6. However, for the subset of 14 cases for which transient signatures (either interplanetary shocks or bidirectional electrons) are absent, the agreement in inclinations improves dramatically, with a correlation coefficient of 0.96. These results validate not only the use of the source surface model as a predictor but also the previously questioned usefulness of minimum variance analysis across complex sector boundaries. In addition, the results imply that interplanetary dynamics have little effect on current sheet inclination at 1 AU. The dependence of the correlation on transient occurrence suggests that the leading edge of a coronal mass ejection (CME), where transient signatures are detected, disrupts the heliospheric current sheet but that the sheet re-forms between the trailing legs of the CME. In this way the global structure of the heliosphere, reflected both in the source surface maps and in the interplanetary sector structure, can be maintained even when the CME occurrence rate is high.

Numerical prediction of fiber orientation in injection-molded short-fiber/thermoplastic composite parts with experimental validation

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

Thi, Thanh Binh Nguyen; Morioka, Mizuki; Yokoyama, Atsushi

Numerical prediction of the fiber orientation in the short-glass fiber (GF) reinforced polyamide 6 (PA6) composites with the fiber weight concentration of 30%, 50%, and 70% manufactured by the injection molding process is presented. And the fiber orientation was also directly observed and measured through X-ray computed tomography. During the injection molding process of the short-fiber/thermoplastic composite, the fiber orientation is produced by the flow states and the fiber-fiber interaction. Folgar and Tucker equation is the well known for modeling the fiber orientation in a concentrated suspension. They included into Jeffrey’s equation a diffusive type of term by introducing amore » phenomenological coefficient to account for the fiber-fiber interaction. Our developed model for the fiber-fiber interaction was proposed by modifying the rotary diffusion term of the Folgar-Tucker equation. This model was presented in a conference paper of the 29{sup th} International Conference of the Polymer Processing Society published by AIP conference proceeding. For modeling fiber interaction, the fiber dynamic simulation was introduced in order to obtain a global fiber interaction coefficient, which is sum function of the fiber concentration, aspect ratio, and angular velocity. The fiber orientation is predicted by using the proposed fiber interaction model incorporated into a computer aided engineering simulation package C-Mold. An experimental program has been carried out in which the fiber orientation distribution has been measured in 100 x 100 x 2 mm injection-molded plate and 100 x 80 x 2 mm injection-molded weld by analyzed with a high resolution 3D X-ray computed tomography system XVA-160α, and calculated by X-ray computed tomography imaging. The numerical prediction shows a good agreement with experimental validation. And the complex fiber orientation in the injection-molded weld was investigated.« less

Numerical prediction of fiber orientation in injection-molded short-fiber/thermoplastic composite parts with experimental validation

NASA Astrophysics Data System (ADS)

Thi, Thanh Binh Nguyen; Morioka, Mizuki; Yokoyama, Atsushi; Hamanaka, Senji; Yamashita, Katsuhisa; Nonomura, Chisato

2015-05-01

Numerical prediction of the fiber orientation in the short-glass fiber (GF) reinforced polyamide 6 (PA6) composites with the fiber weight concentration of 30%, 50%, and 70% manufactured by the injection molding process is presented. And the fiber orientation was also directly observed and measured through X-ray computed tomography. During the injection molding process of the short-fiber/thermoplastic composite, the fiber orientation is produced by the flow states and the fiber-fiber interaction. Folgar and Tucker equation is the well known for modeling the fiber orientation in a concentrated suspension. They included into Jeffrey's equation a diffusive type of term by introducing a phenomenological coefficient to account for the fiber-fiber interaction. Our developed model for the fiber-fiber interaction was proposed by modifying the rotary diffusion term of the Folgar-Tucker equation. This model was presented in a conference paper of the 29th International Conference of the Polymer Processing Society published by AIP conference proceeding. For modeling fiber interaction, the fiber dynamic simulation was introduced in order to obtain a global fiber interaction coefficient, which is sum function of the fiber concentration, aspect ratio, and angular velocity. The fiber orientation is predicted by using the proposed fiber interaction model incorporated into a computer aided engineering simulation package C-Mold. An experimental program has been carried out in which the fiber orientation distribution has been measured in 100 x 100 x 2 mm injection-molded plate and 100 x 80 x 2 mm injection-molded weld by analyzed with a high resolution 3D X-ray computed tomography system XVA-160α, and calculated by X-ray computed tomography imaging. The numerical prediction shows a good agreement with experimental validation. And the complex fiber orientation in the injection-molded weld was investigated.

Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

NASA Astrophysics Data System (ADS)

Wang, Dong; Zhao, Yang; Yang, Fangfang; Tsui, Kwok-Leung

2017-09-01

Brownian motion with adaptive drift has attracted much attention in prognostics because its first hitting time is highly relevant to remaining useful life prediction and it follows the inverse Gaussian distribution. Besides linear degradation modeling, nonlinear-drifted Brownian motion has been developed to model nonlinear degradation. Moreover, the first hitting time distribution of the nonlinear-drifted Brownian motion has been approximated by time-space transformation. In the previous studies, the drift coefficient is the only hidden state used in state space modeling of the nonlinear-drifted Brownian motion. Besides the drift coefficient, parameters of a nonlinear function used in the nonlinear-drifted Brownian motion should be treated as additional hidden states of state space modeling to make the nonlinear-drifted Brownian motion more flexible. In this paper, a prognostic method based on nonlinear-drifted Brownian motion with multiple hidden states is proposed and then it is applied to predict remaining useful life of rechargeable batteries. 26 sets of rechargeable battery degradation samples are analyzed to validate the effectiveness of the proposed prognostic method. Moreover, some comparisons with a standard particle filter based prognostic method, a spherical cubature particle filter based prognostic method and two classic Bayesian prognostic methods are conducted to highlight the superiority of the proposed prognostic method. Results show that the proposed prognostic method has lower average prediction errors than the particle filter based prognostic methods and the classic Bayesian prognostic methods for battery remaining useful life prediction.

QSAR, docking and ADMET studies of artemisinin derivatives for antimalarial activity targeting plasmepsin II, a hemoglobin-degrading enzyme from P. falciparum.

PubMed

Qidwai, Tabish; Yadav, Dharmendra K; Khan, Feroz; Dhawan, Sangeeta; Bhakuni, R S

2012-01-01

This work presents the development of quantitative structure activity relationship (QSAR) model to predict the antimalarial activity of artemisinin derivatives. The structures of the molecules are represented by chemical descriptors that encode topological, geometric, and electronic structure features. Screening through QSAR model suggested that compounds A24, A24a, A53, A54, A62 and A64 possess significant antimalarial activity. Linear model is developed by the multiple linear regression method to link structures to their reported antimalarial activity. The correlation in terms of regression coefficient (r(2)) was 0.90 and prediction accuracy of model in terms of cross validation regression coefficient (rCV(2)) was 0.82. This study indicates that chemical properties viz., atom count (all atoms), connectivity index (order 1, standard), ring count (all rings), shape index (basic kappa, order 2), and solvent accessibility surface area are well correlated with antimalarial activity. The docking study showed high binding affinity of predicted active compounds against antimalarial target Plasmepsins (Plm-II). Further studies for oral bioavailability, ADMET and toxicity risk assessment suggest that compound A24, A24a, A53, A54, A62 and A64 exhibits marked antimalarial activity comparable to standard antimalarial drugs. Later one of the predicted active compound A64 was chemically synthesized, structure elucidated by NMR and in vivo tested in multidrug resistant strain of Plasmodium yoelii nigeriensis infected mice. The experimental results obtained agreed well with the predicted values.

The reliability and validity of multiple mini interviews (MMIs) in values based recruitment to nursing, midwifery and paramedic practice programmes: Findings from an evaluation study.

PubMed

Callwood, Alison; Cooke, Debbie; Bolger, Sarah; Lemanska, Agnieszka; Allan, Helen

2018-01-01

Universities in the United Kingdom (UK) are required to incorporate values based recruitment (VBR) into their healthcare student selection processes. This reflects an international drive to strengthen the quality of healthcare service provision. This paper presents novel findings in relation to the reliability and predictive validity of multiple mini interviews (MMIs); one approach to VBR widely being employed by universities. To examine the reliability (internal consistency) and predictive validity of MMIs using end of Year One practice outcomes of under-graduate pre-registration adult, child, mental health nursing, midwifery and paramedic practice students. Cross-discipline evaluation study. One university in the United Kingdom. Data were collected in two streams: applicants to A) The September 2014 and 2015 Midwifery Studies programmes; B) September 2015 adult; Child and Mental Health Nursing and Paramedic Practice programmes. Fifty-seven midwifery students commenced their programme in 2014 and 69 in 2015; 47 and 54 agreed to participate and completed Year One respectively. 333 healthcare students commenced their programmes in September 2015. Of these, 281 agreed to participate and completed their first year (180 adult, 33 child and 34 mental health nursing and 34 paramedic practice students). Stream A featured a seven station four-minute model with one interviewer at each station and in Stream B a six station model was employed. Cronbach's alpha was used to assess MMI station internal consistency and Pearson's moment correlation co-efficient to explore associations between participants' admission MMI score and end of Year one clinical practice outcomes (OSCE and mentor grading). Stream A: Significant correlations are reported between midwifery applicant's MMI scores and end of Year One practice outcomes. A multivariate linear regression model demonstrated that MMI score significantly predicted end of Year One practice outcomes controlling for age and academic entry level: coefficients 0.195 (p=0.002) and 0.116 (p=0.002) for OSCE and mentor grading respectively. In Stream B no significant correlations were found between MMI score and practice outcomes measured by mentor grading. Internal consistency for each MMI station was 'excellent' with values ranging from 0.966-0.974 across Streams A and B. This novel, cross-discipline study shows that MMIs are reliable VBR tools which have predictive validity when a seven station model is used. These data are important given the current international use of different MMI models in healthcare student selection processes. Copyright © 2017. Published by Elsevier Ltd.

Development and Validation of a Novel Scoring System for Predicting Technical Success of Chronic Total Occlusion Percutaneous Coronary Interventions: The PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) Score.

PubMed

Christopoulos, Georgios; Kandzari, David E; Yeh, Robert W; Jaffer, Farouc A; Karmpaliotis, Dimitri; Wyman, Michael R; Alaswad, Khaldoon; Lombardi, William; Grantham, J Aaron; Moses, Jeffrey; Christakopoulos, Georgios; Tarar, Muhammad Nauman J; Rangan, Bavana V; Lembo, Nicholas; Garcia, Santiago; Cipher, Daisha; Thompson, Craig A; Banerjee, Subhash; Brilakis, Emmanouil S

2016-01-11

This study sought to develop a novel parsimonious score for predicting technical success of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) performed using the hybrid approach. Predicting technical success of CTO PCI can facilitate clinical decision making and procedural planning. We analyzed clinical and angiographic parameters from 781 CTO PCIs included in PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) using a derivation and validation cohort (2:1 sampling ratio). Variables with strong association with technical success in multivariable analysis were assigned 1 point, and a 4-point score was developed from summing all points. The PROGRESS CTO score was subsequently compared with the J-CTO (Multicenter Chronic Total Occlusion Registry in Japan) score in the validation cohort. Technical success was 92.9%. On multivariable analysis, factors associated with technical success included proximal cap ambiguity (beta coefficient [b] = 0.88), moderate/severe tortuosity (b = 1.18), circumflex artery CTO (b = 0.99), and absence of "interventional" collaterals (b = 0.88). The resulting score demonstrated good calibration and discriminatory capacity in the derivation (Hosmer-Lemeshow chi-square = 2.633; p = 0.268, and receiver-operator characteristic [ROC] area = 0.778) and validation (Hosmer-Lemeshow chi-square = 5.333; p = 0.070, and ROC area = 0.720) subset. In the validation cohort, the PROGRESS CTO and J-CTO scores performed similarly in predicting technical success (ROC area 0.720 vs. 0.746, area under the curve difference = 0.026, 95% confidence interval = -0.093 to 0.144). The PROGRESS CTO score is a novel useful tool for estimating technical success in CTO PCI performed using the hybrid approach. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

Reliability and validity of the Tilburg Frailty Indicator (TFI) among Chinese community-dwelling older people.

PubMed

Dong, Lijuan; Liu, Na; Tian, Xiaoyu; Qiao, Xiaoxia; Gobbens, Robbert J J; Kane, Robert L; Wang, Cuili

2017-11-01

To translate the Tilburg Frailty Indicator (TFI) into Chinese and assess its reliability and validity. A sample of 917 community-dwelling older people, aged ≥60 years, in a Chinese city was included between August 2015 and March 2016. Construct validity was assessed using alternative measures corresponding to the TFI items, including self-rated health status (SRH), unintentional weight loss, walking speed, timed-up-and-go tests (TUGT), making telephone calls, grip strength, exhaustion, Short Portable Mental Status Questionnaire (SPMSQ), Geriatric Depression scale (GDS-15), emotional role, Adaptability Partnership Growth Affection and Resolve scale (APGAR) and Social Support Rating Scale (SSRS). Fried's phenotype and frailty index were measured to evaluate criterion validity. Adverse health outcomes (ADL and IADL disability, healthcare utilization, GDS-15, SSRS) were used to assess predictive (concurrent) validity. The internal consistency reliability was good (Cronbach's α=0.71). The test-retest reliability was strong (r=0.88). Kappa coefficients showed agreements between the TFI items and corresponding alternative measures. Alternative measures correlated as expected with the three domains of TFI, with an exclusion that alternative psychological measures had similar correlations with psychological and physical domains of the TFI. The Chinese TFI had excellent criterion validity with the AUCs regarding physical phenotype and frailty index of 0.87 and 0.86, respectively. The predictive (concurrent) validities of the adverse health outcomes and healthcare utilization were acceptable (AUCs: 0.65-0.83). The Chinese TFI has good validity and reliability as an integral instrument to measure frailty of older people living in the community in China. Copyright © 2017 Elsevier B.V. All rights reserved.

Validity and Reliability of the Turkish Version of the DSM-5 Posttraumatic Stress Symptom Severity Scale-Child Form.

PubMed

Yalin Sapmaz, Şermin; Ergin, Dilek; Özek Erkuran, Handan; Şen Celasin, Nesrin; Öztürk, Masum; Karaarslan, Duygu; Köroğlu, Ertuğrul; Aydemir, Ömer

2017-09-01

This study assessed the validity and reliability of the Turkish version of the DSM-5 Posttraumatic Stress Symptom Severity Scale-Child Form for use among the Turkish population. The study group consisted of 30 patients that had been treated in a child psychiatry unit and diagnosed with posttraumatic stress disorder and 83 healthy volunteers that were attending middle or high school during the study period. For reliability analyses, the internal consistency coefficient and the test-retest correlation coefficient were measured. For validity analyses, the exploratory factor analysis and correlation analysis with the Child Posttraumatic Stress Reaction Index for concurrent validity were measured. The Cronbach's alpha (the internal consistency coefficient) of the scale was 0.909, and the test-retest correlation coefficient was 0.663. One factor that could explain 58.5% of the variance was obtained and was congruent with the original construct of the scale. As for concurrent validity, the scale showed high correlation with the Child Posttraumatic Stress Reaction Index. It was concluded that the Turkish version of the DSM-5 Posttraumatic Stress Symptom Severity Scale-Child Form can be used as a valid and reliable tool.

Evaluating the validity and reliability of the V-scale instrument (Turkish version) used to determine nurses' attitudes towards vital sign monitoring.

PubMed

Ertuğ, Nurcan

2018-06-01

The aim of this study was to determine the validity and reliability of the Turkish version of the V-scale, which measures nurses' attitudes towards vital signs monitoring in the detection of clinical deterioration. This validity and reliability study was conducted at a tertiary hospital in Ankara, Turkey, in 2016. A total of 169 ward nurses participated in the study. Exploratory factor analysis, Cronbach's alpha coefficient, and the intraclass correlation coefficient were used to determine the validity and reliability of the scale. A 5-factor, 16-item scale explained 60.823% of the total variance according to the validity analysis. Our version matched the original scale in terms of the number of items and factor structure. Cronbach's alpha coefficient of the Turkish version of the V-scale was 0.764. The test-retest reliability results were 0.855 for the overall intraclass correlation coefficient, and the t-test result was P > 0.05. The V-scale is a reliable and valid instrument to measure Turkish nurses' attitudes towards vital signs monitoring in the detection of clinical deterioration. © 2018 John Wiley & Sons Australia, Ltd.

[Validation of the Polish version of The Authentic Leadership Questionnaire for the of evaluation purpose of nursing management staff in national hospital wards].

PubMed

Sierpińska, Lidia

2013-09-01

The Authentic Leadership Questionnaire (ALQ) is a standardized research instrument for the evaluation of individual elements of leader's conduct which contribute to the authentic leadership. The application of this questionnaire in Polish conditions required to carry out the validation process. The aim of the study was to evaluate of validity and reliability of the Polish version of the American research instrument for the needs of evaluation of authenticity of leadership of the nursing management in Polish hospitals. The study covered 286 nurses (143 head nurses and 143 of their subordinates) employed in 45 hospitals in Poland. Theoretical validity of the instrument was evaluated using Fisher's transformation (r-Person correlation coefficient), while the criterion validity of the ALQ was evaluated using rho-Spearman correlation coefficient and the BOHIPSZO questionnaire. The reliability of the ALQ was assessed by means of the Cronbach-alpha coefficient. The ALQ questionnaire applied for the evaluation of authenticity of leadership of the nursing management in Polish hospital wards shows an acceptable theoretical and criterion validity and reliability (Cronbach-alpha coefficient 0.80). The Polish version of the ALQ is valid and reliable, and may be applied in studies concerning the evaluation of authenticity of leadership of the nursing management in Polish hospital wards.

[Reliability and Validity of the Scale for Homophobia in Medicine Students].

PubMed

Campo-Arias, Adalberto; Lafaurie, María Mercedes; Gaitán-Duarte, Hernando G

2012-12-01

There are several scales to quantify homophobia in different populations. However, the reliability and validity of these instruments among Colombian students are unknown. Consequently, this work is intended to assess reliability (inner consistency) as well as the validity of the Scale for Homophobia in Medicine students from a private university in Bogotá (Colombia). Methodological study with 199 Medicine students from 1st to 5th semester that filled out the Homophobia Scale form, the general welfare questionnaire, the Attitude Towards Gays and Lesbians Scale (ATGL), WHO-5 (divergent validity) and the Francis Scale of Attitude Toward Christianity (nomologic validity). Pearson's correlations were computed, the Cronbach's alfa coefficient, the omega coefficient (construct's reliability) and confirmatory factorial analysis. The Scale for Homophobia showed an alpha Cronbach coefficient of 0,785, an omega coefficient of 0,790 and a Pearson correlation with the ATGL of 0,844; with WHO-5, -0,059; and a Francis Scale of Attitude Toward Christianity, 0,187. The Scale toward Homophobia exhibited a relevant factor of 44,7% of the total variance. The Scale for Homophobia showed acceptable reliability and validity. New studies should investigate the stability of the scale and the nomologic validity regarding other constructs. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Vehicular traffic noise prediction using soft computing approach.

PubMed

Singh, Daljeet; Nigam, S P; Agrawal, V P; Kumar, Maneek

2016-12-01

A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data. Copyright © 2016 Elsevier Ltd. All rights reserved.

The big five personality traits and individual job performance growth trajectories in maintenance and transitional job stages.

PubMed

Thoresen, Carl J; Bradley, Jill C; Bliese, Paul D; Thoresen, Joseph D

2004-10-01

This study extends the literature on personality and job performance through the use of random coefficient modeling to test the validity of the Big Five personality traits in predicting overall sales performance and sales performance trajectories--or systematic patterns of performance growth--in 2 samples of pharmaceutical sales representatives at maintenance and transitional job stages (K. R. Murphy, 1989). In the maintenance sample, conscientiousness and extraversion were positively associated with between-person differences in total sales, whereas only conscientiousness predicted performance growth. In the transitional sample, agreeableness and openness to experience predicted overall performance differences and performance trends. All effects remained significant with job tenure statistically controlled. Possible explanations for these findings are offered, and theoretical and practical implications of findings are discussed. (c) 2004 APA, all rights reserved

Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model.

PubMed

Diaz-Rodriguez, Sebastian; Bozada, Samantha M; Phifer, Jeremy R; Paluch, Andrew S

2016-11-01

We present blind predictions using the solubility parameter based method MOSCED submitted for the SAMPL5 challenge on calculating cyclohexane/water distribution coefficients at 298 K. Reference data to parameterize MOSCED was generated with knowledge only of chemical structure by performing solvation free energy calculations using electronic structure calculations in the SMD continuum solvent. To maintain simplicity and use only a single method, we approximate the distribution coefficient with the partition coefficient of the neutral species. Over the final SAMPL5 set of 53 compounds, we achieved an average unsigned error of [Formula: see text] log units (ranking 15 out of 62 entries), the correlation coefficient (R) was [Formula: see text] (ranking 35), and [Formula: see text] of the predictions had the correct sign (ranking 30). While used here to predict cyclohexane/water distribution coefficients at 298 K, MOSCED is broadly applicable, allowing one to predict temperature dependent infinite dilution activity coefficients in any solvent for which parameters exist, and provides a means by which an excess Gibbs free energy model may be parameterized to predict composition dependent phase-equilibrium.

Estimation of Aerosol Optical Depth at Different Wavelengths by Multiple Regression Method

NASA Technical Reports Server (NTRS)

Tan, Fuyi; Lim, Hwee San; Abdullah, Khiruddin; Holben, Brent

2015-01-01

This study aims to investigate and establish a suitable model that can help to estimate aerosol optical depth (AOD) in order to monitor aerosol variations especially during non-retrieval time. The relationship between actual ground measurements (such as air pollution index, visibility, relative humidity, temperature, and pressure) and AOD obtained with a CIMEL sun photometer was determined through a series of statistical procedures to produce an AOD prediction model with reasonable accuracy. The AOD prediction model calibrated for each wavelength has a set of coefficients. The model was validated using a set of statistical tests. The validated model was then employed to calculate AOD at different wavelengths. The results show that the proposed model successfully predicted AOD at each studied wavelength ranging from 340 nm to 1020 nm. To illustrate the application of the model, the aerosol size determined using measure AOD data for Penang was compared with that determined using the model. This was done by examining the curvature in the ln [AOD]-ln [wavelength] plot. Consistency was obtained when it was concluded that Penang was dominated by fine mode aerosol in 2012 and 2013 using both measured and predicted AOD data. These results indicate that the proposed AOD prediction model using routine measurements as input is a promising tool for the regular monitoring of aerosol variation during non-retrieval time.

Health Service Quality Scale: Brazilian Portuguese translation, reliability and validity.

PubMed

Rocha, Luiz Roberto Martins; Veiga, Daniela Francescato; e Oliveira, Paulo Rocha; Song, Elaine Horibe; Ferreira, Lydia Masako

2013-01-17

The Health Service Quality Scale is a multidimensional hierarchical scale that is based on interdisciplinary approach. This instrument was specifically created for measuring health service quality based on marketing and health care concepts. The aim of this study was to translate and culturally adapt the Health Service Quality Scale into Brazilian Portuguese and to assess the validity and reliability of the Brazilian Portuguese version of the instrument. We conducted a cross-sectional, observational study, with public health system patients in a Brazilian university hospital. Validity was assessed using Pearson's correlation coefficient to measure the strength of the association between the Brazilian Portuguese version of the instrument and the SERVQUAL scale. Internal consistency was evaluated using Cronbach's alpha coefficient; the intraclass (ICC) and Pearson's correlation coefficients were used for test-retest reliability. One hundred and sixteen consecutive postoperative patients completed the questionnaire. Pearson's correlation coefficient for validity was 0.20. Cronbach's alpha for the first and second administrations of the final version of the instrument were 0.982 and 0.986, respectively. For test-retest reliability, Pearson's correlation coefficient was 0.89 and ICC was 0.90. The culturally adapted, Brazilian Portuguese version of the Health Service Quality Scale is a valid and reliable instrument to measure health service quality.

Development of a job stressor scale for nurses caring for patients with intractable neurological diseases.

PubMed

Ando, Yukako; Kataoka, Tsuyoshi; Okamura, Hitoshi; Tanaka, Katsutoshi; Kobayashi, Toshio

2013-12-01

The purpose of this research is to verify the reliability and validity of a job stressor scale for nurses caring for patients with intractable neurological diseases. A mail survey was conducted using a self-report questionnaire. The subjects were 263 nurses and assistant nurses working in wards specializing in intractable neurological diseases. The response rate was 71.9% (valid response rate, 66.2%). With regard to reliability, internal consistency and stability were assessed. Internal consistency was examined via Cronbach's alpha. For stability, the test-retest method was performed and stability was examined via intraclass correlation coefficients. With regard to validity, factor validity, criterion-related validity, and content validity were assessed. Exploratory factor analysis was used for factor validity. For criterion-related validity, an existing scale was used as an external criterion; concurrent validity was examined via Spearman's rank correlation coefficients. As a result of analysis, there were 26 items in the scale created with an eight factor structure. Cronbach's a for the 26 items was 0.90; with the exception of two factors, alpha for all of the individual sub-factors was high at 0.7 or higher. The intraclass correlation coefficient for the 26 items was 0.89 (p < 0.001). With regard to criterion-related validity, concurrent validity was confirmed and the correlation coefficient with an external criterion was 0.73 (p < 0.001). For content validity, subjects who responded that "The questionnaire represents a stressor well or to a degree" accounted for 81% of the total responses. Reliability and validity were confirmed, so the scale created in the current research is a usable scale.

Application of Wavelet Analysis on Variability, Teleconnectivity, and Predictability November-January Taiwan rainfall

NASA Astrophysics Data System (ADS)

T.; Gan, Y.

2009-04-01

First the wavelet analysis was used to analyze the variability of winter (November-January) rainfall (1974-2006) of Taiwan and seasonal sea surface temperature (SST) in selected domains of the Pacific Ocean. From the scale average wavelet power (SAWP) computed for the seasonal rainfall and seasonal SST, it seems that these data exhibit interannual oscillations at 2-4-year period. Correlations between rainfall and SST SAWP were further estimated. Next the SST in selected sectors of the western Pacific Ocean (around 5°N-30°N, 120°E-150°E) was used as predictors to predict the winter rainfall of Taiwan at one season lead time using an Artificial Neural Network calibrated by Genetic Algorithm (ANN-GA). The ANN-GA was first calibrated using the 1974-1998 data and independently validated using 1999-2005 data. In terms of summary statistics such as the correlation coefficient, root-mean-square errors (RMSE), and Hansen-Kuipers (HK) scores, the seasonal prediction for northern and western Taiwan are generally good for both calibration and validation stages, but not so in some stations located in southeast Taiwan and Central Mountain.

Experimental investigation of performance and dynamic loading of an axial-flow marine hydrokinetic turbine with comparison to predicted design values from BEM computations

NASA Astrophysics Data System (ADS)

van Ness, Katherine; Hill, Craig; Aliseda, Alberto; Polagye, Brian

2017-11-01

Experimental measurements of a 0.45-m diameter, variable-pitch marine hydrokinetic (MHK) turbine were collected in a tow tank at different tip speed ratios and blade pitch angles. The coefficients of power and thrust are computed from direct measurements of torque, force and angular speed at the hub level. Loads on individual blades were measured with a six-degree of freedom load cell mounted at the root of one of the turbine blades. This information is used to validate the performance predictions provided by blade element model (BEM) simulations used in the turbine design, specifically the open-source code WTPerf developed by the National Renewable Energy Lab (NREL). Predictions of blade and hub loads by NREL's AeroDyn are also validated for the first time for an axial-flow MHK turbine. The influence of design twist angle, combined with the variable pitch angle, on the flow separation and subsequent blade loading will be analyzed with the complementary information from simulations and experiments. Funding for this research was provided by the United States Naval Facilities Engineering Command.

Psychometrics of a new questionnaire to assess glaucoma adherence: the Glaucoma Treatment Compliance Assessment Tool (an American Ophthalmological Society thesis).

PubMed

Mansberger, Steven L; Sheppler, Christina R; McClure, Tina M; Vanalstine, Cory L; Swanson, Ingrid L; Stoumbos, Zoey; Lambert, William E

2013-09-01

To report the psychometrics of the Glaucoma Treatment Compliance Assessment Tool (GTCAT), a new questionnaire designed to assess adherence with glaucoma therapy. We developed the questionnaire according to the constructs of the Health Belief Model. We evaluated the questionnaire using data from a cross-sectional study with focus groups (n = 20) and a prospective observational case series (n=58). Principal components analysis provided assessment of construct validity. We repeated the questionnaire after 3 months for test-retest reliability. We evaluated predictive validity using an electronic dosing monitor as an objective measure of adherence. Focus group participants provided 931 statements related to adherence, of which 88.7% (826/931) could be categorized into the constructs of the Health Belief Model. Perceived barriers accounted for 31% (288/931) of statements, cues-to-action 14% (131/931), susceptibility 12% (116/931), benefits 12% (115/931), severity 10% (91/931), and self-efficacy 9% (85/931). The principal components analysis explained 77% of the variance with five components representing Health Belief Model constructs. Reliability analyses showed acceptable Cronbach's alphas (>.70) for four of the seven components (severity, susceptibility, barriers [eye drop administration], and barriers [discomfort]). Predictive validity was high, with several Health Belief Model questions significantly associated (P <.05) with adherence and a correlation coefficient (R (2)) of .40. Test-retest reliability was 90%. The GTCAT shows excellent repeatability, content, construct, and predictive validity for glaucoma adherence. A multisite trial is needed to determine whether the results can be generalized and whether the questionnaire accurately measures the effect of interventions to increase adherence.

Using the NANA toolkit at home to predict older adults' future depression.

PubMed

Andrews, J A; Harrison, R F; Brown, L J E; MacLean, L M; Hwang, F; Smith, T; Williams, E A; Timon, C; Adlam, T; Khadra, H; Astell, A J

2017-04-15

Depression is currently underdiagnosed among older adults. As part of the Novel Assessment of Nutrition and Aging (NANA) validation study, 40 older adults self-reported their mood using a touchscreen computer over three, one-week periods. Here, we demonstrate the potential of these data to predict future depression status. We analysed data from the NANA validation study using a machine learning approach. We applied the least absolute shrinkage and selection operator with a logistic model to averages of six measures of mood, with depression status according to the Geriatric Depression Scale 10 weeks later as the outcome variable. We tested multiple values of the selection parameter in order to produce a model with low deviance. We used a cross-validation framework to avoid overspecialisation, and receiver operating characteristic (ROC) curve analysis to determine the quality of the fitted model. The model we report contained coefficients for two variables: sadness and tiredness, as well as a constant. The cross-validated area under the ROC curve for this model was 0.88 (CI: 0.69-0.97). While results are based on a small sample, the methodology for the selection of variables appears suitable for the problem at hand, suggesting promise for a wider study and ultimate deployment with older adults at increased risk of depression. We have identified self-reported scales of sadness and tiredness as sensitive measures which have the potential to predict future depression status in older adults, partially addressing the problem of underdiagnosis. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Irradiation dose detection of irradiated milk powder using visible and near-infrared spectroscopy and chemometrics.

PubMed

Kong, W W; Zhang, C; Liu, F; Gong, A P; He, Y

2013-08-01

The objective of this study was to examine the possibility of applying visible and near-infrared spectroscopy to the quantitative detection of irradiation dose of irradiated milk powder. A total of 150 samples were used: 100 for the calibration set and 50 for the validation set. The samples were irradiated at 5 different dose levels in the dose range 0 to 6.0 kGy. Six different pretreatment methods were compared. The prediction results of full spectra given by linear and nonlinear calibration methods suggested that Savitzky-Golay smoothing and first derivative were suitable pretreatment methods in this study. Regression coefficient analysis was applied to select effective wavelengths (EW). Less than 10 EW were selected and they were useful for portable detection instrument or sensor development. Partial least squares, extreme learning machine, and least squares support vector machine were used. The best prediction performance was achieved by the EW-extreme learning machine model with first-derivative spectra, and correlation coefficients=0.97 and root mean square error of prediction=0.844. This study provided a new approach for the fast detection of irradiation dose of milk powder. The results could be helpful for quality detection and safety monitoring of milk powder. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets.

PubMed

Feng, Yao-Ze; Elmasry, Gamal; Sun, Da-Wen; Scannell, Amalia G M; Walsh, Des; Morcy, Noha

2013-06-01

Bacterial pathogens are the main culprits for outbreaks of food-borne illnesses. This study aimed to use the hyperspectral imaging technique as a non-destructive tool for quantitative and direct determination of Enterobacteriaceae loads on chicken fillets. Partial least squares regression (PLSR) models were established and the best model using full wavelengths was obtained in the spectral range 930-1450 nm with coefficients of determination R(2)≥ 0.82 and root mean squared errors (RMSEs) ≤ 0.47 log(10)CFUg(-1). In further development of simplified models, second derivative spectra and weighted PLS regression coefficients (BW) were utilised to select important wavelengths. However, the three wavelengths (930, 1121 and 1345 nm) selected from BW were competent and more preferred for predicting Enterobacteriaceae loads with R(2) of 0.89, 0.86 and 0.87 and RMSEs of 0.33, 0.40 and 0.45 log(10)CFUg(-1) for calibration, cross-validation and prediction, respectively. Besides, the constructed prediction map provided the distribution of Enterobacteriaceae bacteria on chicken fillets, which cannot be achieved by conventional methods. It was demonstrated that hyperspectral imaging is a potential tool for determining food sanitation and detecting bacterial pathogens on food matrix without using complicated laboratory regimes. Copyright © 2012 Elsevier Ltd. All rights reserved.

International journal of computational fluid dynamics real-time prediction of unsteady flow based on POD reduced-order model and particle filter

NASA Astrophysics Data System (ADS)

Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru

2016-04-01

An integrated method consisting of a proper orthogonal decomposition (POD)-based reduced-order model (ROM) and a particle filter (PF) is proposed for real-time prediction of an unsteady flow field. The proposed method is validated using identical twin experiments of an unsteady flow field around a circular cylinder for Reynolds numbers of 100 and 1000. In this study, a PF is employed (ROM-PF) to modify the temporal coefficient of the ROM based on observation data because the prediction capability of the ROM alone is limited due to the stability issue. The proposed method reproduces the unsteady flow field several orders faster than a reference numerical simulation based on Navier-Stokes equations. Furthermore, the effects of parameters, related to observation and simulation, on the prediction accuracy are studied. Most of the energy modes of the unsteady flow field are captured, and it is possible to stably predict the long-term evolution with ROM-PF.

Shear viscosity in monatomic liquids: a simple mode-coupling approach

NASA Astrophysics Data System (ADS)

Balucani, Umberto

The value of the shear-viscosity coefficient in fluids is controlled by the dynamical processes affecting the time decay of the associated Green-Kubo integrand, the stress autocorrelation function (SACF). These processes are investigated in monatomic liquids by means of a microscopic approach with a minimum use of phenomenological assumptions. In particular, mode-coupling effects (responsible for the presence in the SACF of a long-lasting 'tail') are accounted for by a simplified approach where the only requirement is knowledge of the structural properties. The theory readily yields quantitative predictions in its domain of validity, which comprises ordinary and moderately supercooled 'simple' liquids. The framework is applied to liquid Ar and Rb near their melting points, and quite satisfactory agreement with the simulation data is found for both the details of the SACF and the value of the shear-viscosity coefficient.

Effect of hydrostatic pressure on physical properties of strontium based fluoroperovskites for novel applications

NASA Astrophysics Data System (ADS)

Erum, Nazia; Azhar Iqbal, Muhammad

2018-02-01

Density functional theory (DFT) is employed to calculate the effect of pressure variation on electronic structure, elastic parameters, mechanical durability, and thermodynamic aspects of SrRbF3, in combination with Quasi-harmonic Debye model. The pressure effects are determined in the range of 0-25 GPa, in which cubic stability of SrRbF3 fluoroperovskite remains valid. Significant influence of compression on wide range of elastic parameters and related mechanical properties have been discussed, to utilize this material in low birefringence lens fabrication technology. Apart of linear dependence on elastic coefficients, transition from brittle to ductile behavior is also observed at elevated pressure ranges. Moreover, successful prediction of important thermodynamic aspects such as volume expansion coefficient (α), Debye temperature (θ D), heat capacities (Cp and Cv) are also done within wide pressure and temperature ranges.

Predicting protein-binding regions in RNA using nucleotide profiles and compositions.

PubMed

Choi, Daesik; Park, Byungkyu; Chae, Hanju; Lee, Wook; Han, Kyungsook

2017-03-14

Motivated by the increased amount of data on protein-RNA interactions and the availability of complete genome sequences of several organisms, many computational methods have been proposed to predict binding sites in protein-RNA interactions. However, most computational methods are limited to finding RNA-binding sites in proteins instead of protein-binding sites in RNAs. Predicting protein-binding sites in RNA is more challenging than predicting RNA-binding sites in proteins. Recent computational methods for finding protein-binding sites in RNAs have several drawbacks for practical use. We developed a new support vector machine (SVM) model for predicting protein-binding regions in mRNA sequences. The model uses sequence profiles constructed from log-odds scores of mono- and di-nucleotides and nucleotide compositions. The model was evaluated by standard 10-fold cross validation, leave-one-protein-out (LOPO) cross validation and independent testing. Since actual mRNA sequences have more non-binding regions than protein-binding regions, we tested the model on several datasets with different ratios of protein-binding regions to non-binding regions. The best performance of the model was obtained in a balanced dataset of positive and negative instances. 10-fold cross validation with a balanced dataset achieved a sensitivity of 91.6%, a specificity of 92.4%, an accuracy of 92.0%, a positive predictive value (PPV) of 91.7%, a negative predictive value (NPV) of 92.3% and a Matthews correlation coefficient (MCC) of 0.840. LOPO cross validation showed a lower performance than the 10-fold cross validation, but the performance remains high (87.6% accuracy and 0.752 MCC). In testing the model on independent datasets, it achieved an accuracy of 82.2% and an MCC of 0.656. Testing of our model and other state-of-the-art methods on a same dataset showed that our model is better than the others. Sequence profiles of log-odds scores of mono- and di-nucleotides were much more powerful features than nucleotide compositions in finding protein-binding regions in RNA sequences. But, a slight performance gain was obtained when using the sequence profiles along with nucleotide compositions. These are preliminary results of ongoing research, but demonstrate the potential of our approach as a powerful predictor of protein-binding regions in RNA. The program and supporting data are available at http://bclab.inha.ac.kr/RBPbinding .

C-history method: rapid measurement of the initial emittable concentration, diffusion and partition coefficients for formaldehyde and VOCs in building materials.

PubMed

Xiong, Jianyin; Yao, Yuan; Zhang, Yinping

2011-04-15

The initial emittable concentration (C(m,0)), the diffusion coefficient (D(m)), and the material/air partition coefficient (K) are the three characteristic parameters influencing emissions of formaldehyde and volatile organic compounds (VOCs) from building materials or furniture. It is necessary to determine these parameters to understand emission characteristics and how to control them. In this paper we develop a new method, the C-history method for a closed chamber, to measure these three parameters. Compared to the available methods of determining the three parameters described in the literature, our approach has the following salient features: (1) the three parameters can be simultaneously obtained; (2) it is time-saving, generally taking less than 3 days for the cases studied (the available methods tend to need 7-28 days); (3) the maximum relative standard deviations of the measured C(m,0), D(m) and K are 8.5%, 7.7%, and 9.8%, respectively, which are acceptable for engineering applications. The new method was validated by using the characteristic parameters determined in the closed chamber experiment to predict the observed emissions in a ventilated full scale chamber experiment, proving that the approach is reliable and convincing. Our new C-history method should prove useful for rapidly determining the parameters required to predict formaldehyde and VOC emissions from building materials as well as for furniture labeling.

Six-minute-walk test in idiopathic pulmonary fibrosis: test validation and minimal clinically important difference.

PubMed

du Bois, Roland M; Weycker, Derek; Albera, Carlo; Bradford, Williamson Z; Costabel, Ulrich; Kartashov, Alex; Lancaster, Lisa; Noble, Paul W; Sahn, Steven A; Szwarcberg, Javier; Thomeer, Michiel; Valeyre, Dominique; King, Talmadge E

2011-05-01

The 6-minute-walk test (6MWT) is a practical and clinically meaningful measure of exercise tolerance with favorable performance characteristics in various cardiac and pulmonary diseases. Performance characteristics in patients with idiopathic pulmonary fibrosis (IPF) have not been systematically evaluated. To assess the reliability, validity, and responsiveness of the 6MWT and estimate the minimal clinically important difference (MCID) in patients with IPF. The study population included all subjects completing a 6MWT in a clinical trial evaluating interferon gamma-1b (n = 822). Six-minute walk distance (6MWD) and other parameters were measured at baseline and at 24-week intervals using a standardized protocol. Parametric and distribution-independent correlation coefficients were used to assess the strength of the relationships between 6MWD and measures of pulmonary function, dyspnea, and health-related quality of life. Both distribution-based and anchor-based methods were used to estimate the MCID. Comparison of two proximal measures of 6MWD (mean interval, 24 d) demonstrated good reliability (coefficient = 0.83; P < 0.001). 6MWD was weakly correlated with measures of physiologic function and health-related quality of life; however, values were consistently and significantly lower for patients with the poorest functional status, suggesting good construct validity. Importantly, change in 6MWD was highly predictive of mortality; a 24-week decline of greater than 50 m was associated with a fourfold increase in risk of death at 1 year (hazard ratio, 4.27; 95% confidence interval, 2.57- 7.10; P < 0.001). The estimated MCID was 24-45 m. The 6MWT is a reliable, valid, and responsive measure of disease status and a valid endpoint for clinical trials in IPF.

Translation, Cultural Adaptation, and Validation of Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) and Self-Complete Leeds Assessment of Neuropathic Symptoms and Signs (S-LANSS) Questionnaires into the Greek Language.

PubMed

Batistaki, Chrysanthi; Lyrakos, George; Drachtidi, Kalliopi; Stamatiou, Georgia; Kitsou, Maria-Chrysanthi; Kostopanagiotou, Georgia

2016-06-01

The LANSS and S-LANSS questionnaires represent two widely accepted and validated instruments used to assist the identification of neuropathic pain worldwide. The aim of this study was to translate, culturally adapt, and validate the LANSS and S-LANSS questionnaires into the Greek language. Forward and backward translations of both questionnaires were performed from the English to Greek language. The final versions were assessed by a committee of clinical experts, and they were then pilot-tested in 20 patients with chronic pain. Both questionnaires were validated in 200 patients with chronic pain (100 patients for each questionnaire), using as the "gold standard" the diagnosis of a clinical expert in pain management. Sensitivity and specificity of questionnaires were assessed, as well as the internal consistency (using Cronbach's alpha coefficient) and correlation with the "gold standard" diagnosis (using Pearson correlation coefficient). Sensitivity and specificity of the LANSS questionnaire were calculated to be 82.76% and 95.24%, while for the S-LANSS 86.21% and 95.24%, respectively. Positive predictive value for neuropathic pain was 96% for the LANSS and 96.15% for the S-LANSS. Cronbach's alpha was revealed to be acceptable for both questionnaires (0.65 for LANSS and 0.67 for the S-LANSS), while a significant correlation was observed compared to the "gold standard" diagnosis (rLANSS   = 0.79 και tSLANSS   = 0.77, respectively, P = 0.01). The LANSS and the S-LANSS diagnostic tools have been translated and validated into the Greek language and can be adequately used to assist the identification of neuropathic pain in everyday clinical practice. © 2015 World Institute of Pain.

Equations based on anthropometry to predict body fat measured by absorptiometry in schoolchildren and adolescents.

PubMed

Ortiz-Hernández, Luis; Vega López, A Valeria; Ramos-Ibáñez, Norma; Cázares Lara, L Joana; Medina Gómez, R Joab; Pérez-Salgado, Diana

To develop and validate equations to estimate the percentage of body fat of children and adolescents from Mexico using anthropometric measurements. A cross-sectional study was carried out with 601 children and adolescents from Mexico aged 5-19 years. The participants were randomly divided into the following two groups: the development sample (n=398) and the validation sample (n=203). The validity of previously published equations (e.g., Slaughter) was also assessed. The percentage of body fat was estimated by dual-energy X-ray absorptiometry. The anthropometric measurements included height, sitting height, weight, waist and arm circumferences, skinfolds (triceps, biceps, subscapular, supra-iliac, and calf), and elbow and bitrochanteric breadth. Linear regression models were estimated with the percentage of body fat as the dependent variable and the anthropometric measurements as the independent variables. Equations were created based on combinations of six to nine anthropometric variables and had coefficients of determination (r 2 ) equal to or higher than 92.4% for boys and 85.8% for girls. In the validation sample, the developed equations had high r 2 values (≥85.6% in boys and ≥78.1% in girls) in all age groups, low standard errors (SE≤3.05% in boys and ≤3.52% in girls), and the intercepts were not different from the origin (p>0.050). Using the previously published equations, the coefficients of determination were lower, and/or the intercepts were different from the origin. The equations developed in this study can be used to assess the percentage of body fat of Mexican schoolchildren and adolescents, as they demonstrate greater validity and lower error compared with previously published equations. Copyright © 2017 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

A predictive scoring instrument for tuberculosis lost to follow-up outcome

PubMed Central

2012-01-01

Background Adherence to tuberculosis (TB) treatment is troublesome, due to long therapy duration, quick therapeutic response which allows the patient to disregard about the rest of their treatment and the lack of motivation on behalf of the patient for improved. The objective of this study was to develop and validate a scoring system to predict the probability of lost to follow-up outcome in TB patients as a way to identify patients suitable for directly observed treatments (DOT) and other interventions to improve adherence. Methods Two prospective cohorts, were used to develop and validate a logistic regression model. A scoring system was constructed, based on the coefficients of factors associated with a lost to follow-up outcome. The probability of lost to follow-up outcome associated with each score was calculated. Predictions in both cohorts were tested using receiver operating characteristic curves (ROC). Results The best model to predict lost to follow-up outcome included the following characteristics: immigration (1 point value), living alone (1 point) or in an institution (2 points), previous anti-TB treatment (2 points), poor patient understanding (2 points), intravenous drugs use (IDU) (4 points) or unknown IDU status (1 point). Scores of 0, 1, 2, 3, 4 and 5 points were associated with a lost to follow-up probability of 2,2% 5,4% 9,9%, 16,4%, 15%, and 28%, respectively. The ROC curve for the validation group demonstrated a good fit (AUC: 0,67 [95% CI; 0,65-0,70]). Conclusion This model has a good capacity to predict a lost to follow-up outcome. Its use could help TB Programs to determine which patients are good candidates for DOT and other strategies to improve TB treatment adherence. PMID:22938040

In Vivo Knee Contact Force Prediction Using Patient-Specific Musculoskeletal Geometry in a Segment-Based Computational Model.

PubMed

Ding, Ziyun; Nolte, Daniel; Kit Tsang, Chui; Cleather, Daniel J; Kedgley, Angela E; Bull, Anthony M J

2016-02-01

Segment-based musculoskeletal models allow the prediction of muscle, ligament, and joint forces without making assumptions regarding joint degrees-of-freedom (DOF). The dataset published for the "Grand Challenge Competition to Predict in vivo Knee Loads" provides directly measured tibiofemoral contact forces for activities of daily living (ADL). For the Sixth Grand Challenge Competition to Predict in vivo Knee Loads, blinded results for "smooth" and "bouncy" gait trials were predicted using a customized patient-specific musculoskeletal model. For an unblinded comparison, the following modifications were made to improve the predictions: further customizations, including modifications to the knee center of rotation; reductions to the maximum allowable muscle forces to represent known loss of strength in knee arthroplasty patients; and a kinematic constraint to the hip joint to address the sensitivity of the segment-based approach to motion tracking artifact. For validation, the improved model was applied to normal gait, squat, and sit-to-stand for three subjects. Comparisons of the predictions with measured contact forces showed that segment-based musculoskeletal models using patient-specific input data can estimate tibiofemoral contact forces with root mean square errors (RMSEs) of 0.48-0.65 times body weight (BW) for normal gait trials. Comparisons between measured and predicted tibiofemoral contact forces yielded an average coefficient of determination of 0.81 and RMSEs of 0.46-1.01 times BW for squatting and 0.70-0.99 times BW for sit-to-stand tasks. This is comparable to the best validations in the literature using alternative models.

Transonic Flow Past Cone Cylinders

NASA Technical Reports Server (NTRS)

Solomon, George E

1955-01-01

Experimental results are presented for transonic flow post cone-cylinder, axially symmetric bodies. The drag coefficient and surface Mach number are studied as the free-stream Mach number is varied and, wherever possible, the experimental results are compared with theoretical predictions. Interferometric results for several typical flow configurations are shown and an example of shock-free supersonic-to-subsonic compression is experimentally demonstrated. The theoretical problem of transonic flow past finite cones is discussed briefly and an approximate solution of the axially symmetric transonic equations, valid for a semi-infinite cone, is presented.

Urinary 1-methylhistidine is a marker of meat consumption in Black and in White California Seventh-day Adventists.

PubMed

Myint, T; Fraser, G E; Lindsted, K D; Knutsen, S F; Hubbard, R W; Bennett, H W

2000-10-15

Meat consumption predicts risk of several chronic diseases. The authors validate the accuracy of meat consumption reported by food frequency questionnaires and the mean of eight 24-hour recalls, using urinary methylhistidine excretion, in 55 Black and 71 White Adventist subjects in Los Angeles and San Diego, California, in 1994-1997. 1-Methylhistidine excretion predicts vegetarian status in Black (p = 0.02) and in White (p = 0.005) subjects. Spearman's correlation coefficients between 1-methylhistidine and estimated meat consumption were usually between 0.4 and 0.6 for both food frequency questionnaires and 24-hour recall data. This is despite the chance collection of dietary recalls and urines from omnivores on meatless days.

Characterizing (rating) the performance of large photovoltaic arrays for all operating conditions

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

King, D.L.; Eckert, P.E.

1996-06-01

A new method has been developed for characterizing the electrical performance of photovoltaic arrays. The method provides both a ``rating`` at standard reporting conditions and a rigorous yet straightforward model for predicting array performance at all operating conditions. For the first time, the performance model handles the influences of irradiance, module temperature, solar spectrum, solar angle-of-incidence, and temperature coefficients, in a practical way. Validity of the procedure was confirmed during field testing of a 25-kW array recently installed by Arizona Public Service Co. on Carol Spring Mountain (which powers microwave, ceullular phone, and TV communictions equipment). This paper describes themore » characterization procedure, measured array performance, and the predictive model.« less

Visible and Near-Infrared Spectroscopy Analysis of a Polycyclic Aromatic Hydrocarbon in Soils

PubMed Central

Okparanma, Reuben N.; Mouazen, Abdul M.

2013-01-01

Visible and near-infrared (VisNIR) spectroscopy is becoming recognised by soil scientists as a rapid and cost-effective measurement method for hydrocarbons in petroleum-contaminated soils. This study investigated the potential application of VisNIR spectroscopy (350–2500 nm) for the prediction of phenanthrene, a polycyclic aromatic hydrocarbon (PAH), in soils. A total of 150 diesel-contaminated soil samples were used in the investigation. Partial least-squares (PLS) regression analysis with full cross-validation was used to develop models to predict the PAH compound. Results showed that the PAH compound was predicted well with residual prediction deviation of 2.0–2.32, root-mean-square error of prediction of 0.21–0.25 mg kg−1, and coefficient of determination (r 2) of 0.75–0.83. The mechanism of prediction was attributed to covariation of the PAH with clay and soil organic carbon. Overall, the results demonstrated that the methodology may be used for predicting phenanthrene in soils utilizing the interrelationship between clay and soil organic carbon. PMID:24453798

Prediction of pi-turns in proteins using PSI-BLAST profiles and secondary structure information.

PubMed

Wang, Yan; Xue, Zhi-Dong; Shi, Xiao-Hong; Xu, Jin

2006-09-01

Due to the structural and functional importance of tight turns, some methods have been proposed to predict gamma-turns, beta-turns, and alpha-turns in proteins. In the past, studies of pi-turns were made, but not a single prediction approach has been developed so far. It will be useful to develop a method for identifying pi-turns in a protein sequence. In this paper, the support vector machine (SVM) method has been introduced to predict pi-turns from the amino acid sequence. The training and testing of this approach is performed with a newly collected data set of 640 non-homologous protein chains containing 1931 pi-turns. Different sequence encoding schemes have been explored in order to investigate their effects on the prediction performance. With multiple sequence alignment and predicted secondary structure, the final SVM model yields a Matthews correlation coefficient (MCC) of 0.556 by a 7-fold cross-validation. A web server implementing the prediction method is available at the following URL: http://210.42.106.80/piturn/.

Quantifying prognosis with risk predictions.

PubMed

Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R

2012-01-01

Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.

External Validation of the Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale Score for Predicting Pneumonia After Stroke Using Data From the China National Stroke Registry.

PubMed

Zhang, Runhua; Ji, Ruijun; Pan, Yuesong; Jiang, Yong; Liu, Gaifen; Wang, Yilong; Wang, Yongjun

2017-05-01

Pneumonia is an important risk factor for mortality and morbidity after stroke. The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) score was shown to be a useful tool for predicting stroke-associated pneumonia based on UK multicenter cohort study. We aimed to externally validate the score using data from the China National Stroke Registry (CNSR). Eligible patients with acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH) in the CNSR from 2007 to 2008 were included. The area under the receiver operating characteristic (AUC) curve was used to evaluate discrimination. The Hosmer-Lemeshow goodness of fit test and Pearson correlation coefficient were performed to assess calibration of the model. A total of 19,333 patients (AIS = 14400; ICH = 4933) were included and the overall pneumonia rate was 12.7%. The AUC was .76 (95% confidence interval [CI]: .75-.78) for the subgroup of AIS and .70 (95% CI: .68-.72) for the subgroup of ICH. The Hosmer-Lemeshow test showed the ISAN score with the good calibration for AIS and ICH (P = .177 and .405, respectively). The plot of observed versus predicted pneumonia rates suggested higher correlation for patients with AIS than with ICH (Pearson correlation coefficient = .99 and .83, respectively). The ISAN score was a useful tool for predicting in-hospital pneumonia after acute stroke, especially for patients with AIS. Further validations need to be done in different populations. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Quality assessment of gasoline using comprehensive two-dimensional gas chromatography combined with unfolded partial least squares: A reliable approach for the detection of gasoline adulteration.

PubMed

Parastar, Hadi; Mostafapour, Sara; Azimi, Gholamhasan

2016-01-01

Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make calibration samples. Appropriate statistical parameters of regression coefficient of 0.996-0.998, root-mean square error of prediction of 0.005-0.010 and relative error of prediction of 1.54-3.82% for the calibration set show the reliability of the developed method. In addition, the developed method is externally validated with three samples in validation set (with a relative error of prediction below 10.0%). Finally, to test the applicability of the proposed strategy for the analysis of real samples, five real gasoline samples collected from gas stations are used for this purpose and the gasoline proportions were in range of 70-85%. Also, the relative standard deviations were below 8.5% for different samples in the prediction set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

ACSNSQIP Risk Calculator in Indian Patients Undergoing Surgery for Head and Neck Cancers: Is It Valid?

PubMed

Subramaniam, Narayana; Balasubramanian, Deepak; Rka, Pradeep; Murthy, Samskruthi; Rathod, Priyank; Vidhyadharan, Sivakumar; Thankappan, Krishnakumar; Iyer, Subramania

2018-06-01

Pre-operative assessment is vital to determine patient-specific risks and minimize them in order to optimize surgical outcomes. The American College of Surgeons National Surgical Quality Improvement Program (ACSNSQIP) Surgical Risk Calculator is the most comprehensive surgical risk assessment tool available. We performed this study to determine the validity of ACSNSQIP calculator when used to predict surgical complications in a cohort of patients with head and neck cancer treated in an Indian tertiary care center. Retrospective data was collected for 150 patients with head and neck cancer who were operated in the Department of Head and Neck Oncology, Amrita Institute of Medical Sciences, Kochi, in the year 2016. The predicted outcome data was compared with actual documented outcome data for the variables mentioned. Brier's score was used to estimate the predictive value of the risk assessment generated. Pearson's r coefficient was utilized to validate the prediction of length of hospital stay. Brier's score for the entire calculator was 0.32 (not significant). Additionally, when the score was determined for individual parameters (surgical site infection, pneumonia, etc.), none were significant. Pearson's r value for length of stay was also not significant ( p  = .632). The ACSNSQIP risk assessment tool did not accurately reflect surgical outcomes in our cohort of Indian patients. Although it is the most comprehensive tool available at present, modifications that may improve accuracy are allowing for input of multiple procedure codes, risk stratifying for previous radiation or surgery, and better risk assessment for microvascular flap reconstruction.

Modelling by partial least squares the relationship between the HPLC mobile phases and analytes on phenyl column.

PubMed

Markopoulou, Catherine K; Kouskoura, Maria G; Koundourellis, John E

2011-06-01

Twenty-five descriptors and 61 structurally different analytes have been used on a partial least squares (PLS) to latent structure technique in order to study chromatographically their interaction mechanism on a phenyl column. According to the model, 240 different retention times of the analytes, expressed as Y variable (log k), at different % MeOH mobile-phase concentrations have been correlated with their theoretical most important structural or molecular descriptors. The goodness-of-fit was estimated by the coefficient of multiple determinations r(2) (0.919), and the root mean square error of estimation (RMSEE=0.1283) values with a predictive ability (Q(2)) of 0.901. The model was further validated using cross-validation (CV), validated by 20 response permutations r(2) (0.0, 0.0146), Q(2) (0.0, -0.136) and validated by external prediction. The contribution of certain mechanism interactions between the analytes, the mobile phase and the column, proportional or counterbalancing is also studied. Trying to evaluate the influence on Y of every variable in a PLS model, VIP (variables importance in the projection) plot provides evidence that lipophilicity (expressed as Log D, Log P), polarizability, refractivity and the eluting power of the mobile phase are dominant in the retention mechanism on a phenyl column. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Outpatient Experience Questionnaire of comprehensive public hospital in China: development, validity and reliability.

PubMed

Hu, Yinhuan; Zhang, Zixia; Xie, Jinzhu; Wang, Guanping

2017-02-01

The objective of this study is to describe the development of the Outpatient Experience Questionnaire (OPEQ) and to assess the validity and reliability of the scale. Literature review, patient interviews, Delphi method and Cross-sectional validation survey. Six comprehensive public hospitals in China. The survey was carried out on a sample of 600 outpatients. Acceptability of the questionnaire was assessed according to the overall response rate, item non-response rate and the average completion time. Correlation coefficients and confirmatory factor analysis were used to test construct validity. Delphi method was used to assess the content validity of the questionnaire. Cronbach's coefficient alpha and split-half reliability coefficient were used to estimate the internal reliability of the questionnaire. The overall response rate was 97.2% and the item non-response rate ranged from 0% to 0.3%. The mean completion time was 6 min. The Spearman correlations of item-total score ranged from 0.466 to 0.765. The results of confirmatory factor analysis showed that all items had factor loadings above 0.40 and the dimension intercorrelation ranged from 0.449 to 0.773, the goodness of fit of the questionnaire was reasonable. The overall authority grade of expert consultation was 0.80 and Kendall's coefficient of concordance W was 0.186. The Cronbach's coefficients alpha of six dimensions ranged from 0.708 to 0.895, the split-half reliability coefficient (Spearman-Brown coefficient) was 0.969. The OPEQ is a promising instrument covering the most important aspects which influence outpatient experiences of comprehensive public hospital in China. It has good evidence for acceptability, validity and reliability. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

The zonally averaged transport characteristics of the atmosphere as determined by a general circulation model

NASA Technical Reports Server (NTRS)

Plumb, R. A.

1985-01-01

Two dimensional modeling has become an established technique for the simulation of the global structure of trace constituents. Such models are simpler to formulate and cheaper to operate than three dimensional general circulation models, while avoiding some of the gross simplifications of one dimensional models. Nevertheless, the parameterization of eddy fluxes required in a 2-D model is not a trivial problem. This fact has apparently led some to interpret the shortcomings of existing 2-D models as indicating that the parameterization procedure is wrong in principle. There are grounds to believe that these shortcomings result primarily from incorrect implementations of the predictions of eddy transport theory and that a properly based parameterization may provide a good basis for atmospheric modeling. The existence of these GCM-derived coefficients affords an unprecedented opportunity to test the validity of the flux-gradient parameterization. To this end, a zonally averaged (2-D) model was developed, using these coefficients in the transport parameterization. Results from this model for a number of contrived tracer experiments were compared with the parent GCM. The generally good agreement substantially validates the flus-gradient parameterization, and thus the basic principle of 2-D modeling.

Assessment scale of risk for surgical positioning injuries 1

PubMed Central

Lopes, Camila Mendonça de Moraes; Haas, Vanderlei José; Dantas, Rosana Aparecida Spadoti; de Oliveira, Cheila Gonçalves; Galvão, Cristina Maria

2016-01-01

ABSTRACT Objective: to build and validate a scale to assess the risk of surgical positioning injuries in adult patients. Method: methodological research, conducted in two phases: construction and face and content validation of the scale and field research, involving 115 patients. Results: the Risk Assessment Scale for the Development of Injuries due to Surgical Positioning contains seven items, each of which presents five subitems. The scale score ranges between seven and 35 points in which, the higher the score, the higher the patient's risk. The Content Validity Index of the scale corresponded to 0.88. The application of Student's t-test for equality of means revealed the concurrent criterion validity between the scores on the Braden scale and the constructed scale. To assess the predictive criterion validity, the association was tested between the presence of pain deriving from surgical positioning and the development of pressure ulcer, using the score on the Risk Assessment Scale for the Development of Injuries due to Surgical Positioning (p<0.001). The interrater reliability was verified using the intraclass correlation coefficient, equal to 0.99 (p<0.001). Conclusion: the scale is a valid and reliable tool, but further research is needed to assess its use in clinical practice. PMID:27579925

Reliability and Construct Validity of the Portuguese Version of the Psychological Capital Questionnaire.

PubMed

Antunes, Ana Cristina; Caetano, António; Pina E Cunha, Miguel

2017-06-01

The Psychological Capital Questionnaire (PCQ) is the most commonly used measure for assessing psychological capital in work settings. Although several studies confirmed its factorial validity, most validation studies only examined the four-factor structure preconized by Luthans, Youssef, and Avolio, not attending to empirical evidence on alternative factorial structures. The present study aimed to test the psychometric properties of the Portuguese version of the PCQ, by using two independent samples (NS1 = 542; NS2 = 115) of Portuguese employees. We conducted a series of confirmatory factor analyses and found that, unlike previous findings, a five-factor solution of the PCQ best fitted the data. The evidence obtained also supported the existence of a second-order factor, psychological capital. The coefficients of internal consistency, as measured by Cronbach's alpha, were adequate and test-retest reliability suggested that the PCQ presented a lower stability than personality factors. Convergent validity, assessed with average variance extracted, revealed problems in the optimism subscale. The discriminant validity of the PCQ was confirmed by its correlations with Positive and Negative Affect and Big Five personality factors. Hierarchical regression analyses showed that this measure has incremental validity over personality and affect when predicting job performance.

[Evaluation on the validity and reliability of the Diabetes Self-management Knowledge, Attitude, and Behavior Assessment Scale (DSKAB)].

PubMed

Liu, Xiaoli; Dai, Long; Chen, Bo; Feng, Nongping; Wu, Qianhui; Lin, Yonghai; Zhang, Lan; Tan, Dong; Zhang, Jinhua; Tu, Huijuan; Li, Changfeng; Wang, Wenjuan

2016-01-01

To evaluate the validity and reliability of Diabetes Self-management Knowledge, Attitude, and Behavior Assessment Scale (DSKAB). We selected 460 patients with diabetes in the community, used the scale which was after two rounds of the Delphi method and pilot study. Investigators surveyed the patients by the way of face to face. by draw lots, we selected 25 community diabetes randomly for repeating investigations after one week. The validity analyses included face validity, content validity, construct validity and discriminant validity. The reliability analyses included Cronbach's α coefficient, θ coefficient, Ω coefficient, split-half reliability and test-retest reliability. This study distributed a total of 460 questionnaires, reclaimed 442, qualified 432. The score of the scale was 254.59 ± 28.90, the scores of the knowledge, attitude, behavior sub-scales were 82.44 ± 11.24, 63.53 ± 5.77 and 108.61 ± 17.55, respectively. It had excellent face validity and content validity. The correlation coefficient was from 0.71 to 0.91 among three sub-scales and the scale, P<0.001. The common factor cumulative variance contribution rate of the scale and three sub-scales was from 57.28% to 67.19%, which achieved more than 50% of the approved standard, there was 25 common factors, 91 items of the total 98 items held factor loading ≥0.40 in its relevant common factor, it had good construct validity. The scores of high group and low group in three sub-scales were: knowledge (91.12 ± 3.62) and (69.96 ± 11.20), attitude (68.75 ± 4.51) and (58.79 ± 4.87), behavior (129.38 ± 8.53) and (89.65 ± 11.34),mean scores of three sub-scales were apparently different, which compared between high score group and low score group, the t value were - 19.45, -16.24 and -30.29, respectively, P<0.001, and it had good discriminant validity. The Cronbach's α coefficient of the scale and three sub-scales was from 0.79 to 0.93, the θ coefficient was from 0.86 to 0.95, the Ω coefficient was from 0.90 to 0.98, split-half reliability was from 0.89 to 0.95.Test-retest reliability of the scale was 0.51;the three sub-scales was from 0.46 to 0.52, P<0.05. The validity and reliability of the Diabetes Self-management Knowledge, Attitude, and Behavior Assessment Scale are excellent, which is a suitable instrument to evaluate the self-management for patients with diabetes.

Excess entropy scaling for the segmental and global dynamics of polyethylene melts.

PubMed

Voyiatzis, Evangelos; Müller-Plathe, Florian; Böhm, Michael C

2014-11-28

The range of validity of the Rosenfeld and Dzugutov excess entropy scaling laws is analyzed for unentangled linear polyethylene chains. We consider two segmental dynamical quantities, i.e. the bond and the torsional relaxation times, and two global ones, i.e. the chain diffusion coefficient and the viscosity. The excess entropy is approximated by either a series expansion of the entropy in terms of the pair correlation function or by an equation of state for polymers developed in the context of the self associating fluid theory. For the whole range of temperatures and chain lengths considered, the two estimates of the excess entropy are linearly correlated. The scaled bond and torsional relaxation times fall into a master curve irrespective of the chain length and the employed scaling scheme. Both quantities depend non-linearly on the excess entropy. For a fixed chain length, the reduced diffusion coefficient and viscosity scale linearly with the excess entropy. An empirical reduction to a chain length-independent master curve is accessible for both dynamic quantities. The Dzugutov scheme predicts an increased value of the scaled diffusion coefficient with increasing chain length which contrasts physical expectations. The origin of this trend can be traced back to the density dependence of the scaling factors. This finding has not been observed previously for Lennard-Jones chain systems (Macromolecules, 2013, 46, 8710-8723). Thus, it limits the applicability of the Dzugutov approach to polymers. In connection with diffusion coefficients and viscosities, the Rosenfeld scaling law appears to be of higher quality than the Dzugutov approach. An empirical excess entropy scaling is also proposed which leads to a chain length-independent correlation. It is expected to be valid for polymers in the Rouse regime.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

[Cross-cultural adaptation and validation of the Health and Taste Attitude Scale (HTAS) in Portuguese].

PubMed

Koritar, Priscila; Philippi, Sonia Tucunduva; Alvarenga, Marle dos Santos; Santos, Bernardo dos

2014-08-01

The scope of this study was to show the cross-cultural adaptation and validation of the Health and Taste Attitude Scale in Portuguese. The methodology included translation of the scale; evaluation of conceptual, operational and item-based equivalence by 14 experts and 51 female undergraduates; semantic equivalence and measurement assessment by 12 bilingual women by the paired t-test, the Pearson correlation coefficient and the coefficient intraclass correlation; internal consistency and test-retest reliability by Cronbach's alpha and intraclass correlation coefficient, respectively, after application on 216 female undergraduates; assessment of discriminant and concurrent validity via the t-test and Spearman's correlation coefficient, respectively, in addition to Confirmatory Factor and Exploratory Factor Analysis. The scale was considered adequate and easily understood by the experts and university students and presented good internal consistency and reliability (µ 0.86, ICC 0.84). The results show that the scale is valid and can be used in studies with women to better understand attitudes related to taste.

Construct validity and internal consistency in the Leisure Practices Scale (EPL) for adults.

PubMed

Andrade, Rubian Diego; Schwartz, Gisele Maria; Tavares, Giselle Helena; Pelegrini, Andreia; Teixeira, Clarissa Stefani; Felden, Érico Pereira Gomes

2018-02-01

This study proposes and analyzes the construct validity and internal consistency of the Leisure Practices Scale (EPL). This survey seeks to identify the preferences and involvement in in different leisure practices in adults. The instrument was formed based on the cultural leisure content (artistic, manual, physical, sports, intellectual, social, tourist, virtual and contemplation/leisure). The validation process was conducted with: a) content analysis by leisure experts, who evaluated the instrument for clarity of language and practical relevance, which allowed the calculation of the content validity coefficient (CVC); b) reproducibility test-retest with 51 subjects to calculate the temporal variation coefficient; c) internal consistency analysis with 885 participants. The evaluation presented appropriate coefficients, both with respect to language clarity (CVCt = 0.883) and practical relevance (CVCt = 0.879). The reproducibility coefficients were moderate to excellent. The scale showed adequate internal consistency (0.72). The EPL has psychometric quality and acceptable values in its structure, and can be used to investigate adult involvement in leisure activities.

Perioperative Respiratory Adverse Events in Pediatric Ambulatory Anesthesia: Development and Validation of a Risk Prediction Tool.

PubMed

Subramanyam, Rajeev; Yeramaneni, Samrat; Hossain, Mohamed Monir; Anneken, Amy M; Varughese, Anna M

2016-05-01

Perioperative respiratory adverse events (PRAEs) are the most common cause of serious adverse events in children receiving anesthesia. Our primary aim of this study was to develop and validate a risk prediction tool for the occurrence of PRAE from the onset of anesthesia induction until discharge from the postanesthesia care unit in children younger than 18 years undergoing elective ambulatory anesthesia for surgery and radiology. The incidence of PRAE was studied. We analyzed data from 19,059 patients from our department's quality improvement database. The predictor variables were age, sex, ASA physical status, morbid obesity, preexisting pulmonary disorder, preexisting neurologic disorder, and location of ambulatory anesthesia (surgery or radiology). Composite PRAE was defined as the presence of any 1 of the following events: intraoperative bronchospasm, intraoperative laryngospasm, postoperative apnea, postoperative laryngospasm, postoperative bronchospasm, or postoperative prolonged oxygen requirement. Development and validation of the risk prediction tool for PRAE were performed using a split sampling technique to split the database into 2 independent cohorts based on the year when the patient received ambulatory anesthesia for surgery and radiology using logistic regression. A risk score was developed based on the regression coefficients from the validation tool. The performance of the risk prediction tool was assessed by using tests of discrimination and calibration. The overall incidence of composite PRAE was 2.8%. The derivation cohort included 8904 patients, and the validation cohort included 10,155 patients. The risk of PRAE was 3.9% in the development cohort and 1.8% in the validation cohort. Age ≤ 3 years (versus >3 years), ASA physical status II or III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) significantly predicted the occurrence of PRAE in a multivariable logistic regression model. A risk score in the range of 0 to 3 was assigned to each significant variable in the logistic regression model, and final score for all risk factors ranged from 0 to 11. A cutoff score of 4 was derived from a receiver operating characteristic curve to determine the high-risk category. The model C-statistic and the corresponding SE for the derivation and validation cohort was 0.64 ± 0.01 and 0.63 ± 0.02, respectively. Sensitivity and SE of the risk prediction tool to identify children at risk for PRAE was 77.6 ± 0.02 in the derivation cohort and 76.2 ± 0.03 in the validation cohort. The risk tool developed and validated from our study cohort identified 5 risk factors: age ≤ 3 years (versus >3 years), ASA physical status II and III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) for PRAE. This tool can be used to provide an individual risk score for each patient to predict the risk of PRAE in the preoperative period.

Effect of genotyped cows in the reference population on the genomic evaluation of Holstein cattle.

PubMed

Uemoto, Y; Osawa, T; Saburi, J

2017-03-01

This study evaluated the dependence of reliability and prediction bias on the prediction method, the contribution of including animals (bulls or cows), and the genetic relatedness, when including genotyped cows in the progeny-tested bull reference population. We performed genomic evaluation using a Japanese Holstein population, and assessed the accuracy of genomic enhanced breeding value (GEBV) for three production traits and 13 linear conformation traits. A total of 4564 animals for production traits and 4172 animals for conformation traits were genotyped using Illumina BovineSNP50 array. Single- and multi-step methods were compared for predicting GEBV in genotyped bull-only and genotyped bull-cow reference populations. No large differences in realized reliability and regression coefficient were found between the two reference populations; however, a slight difference was found between the two methods for production traits. The accuracy of GEBV determined by single-step method increased slightly when genotyped cows were included in the bull reference population, but decreased slightly by multi-step method. A validation study was used to evaluate the accuracy of GEBV when 800 additional genotyped bulls (POPbull) or cows (POPcow) were included in the base reference population composed of 2000 genotyped bulls. The realized reliabilities of POPbull were higher than those of POPcow for all traits. For the gain of realized reliability over the base reference population, the average ratios of POPbull gain to POPcow gain for production traits and conformation traits were 2.6 and 7.2, respectively, and the ratios depended on heritabilities of the traits. For regression coefficient, no large differences were found between the results for POPbull and POPcow. Another validation study was performed to investigate the effect of genetic relatedness between cows and bulls in the reference and test populations. The effect of genetic relationship among bulls in the reference population was also assessed. The results showed that it is important to account for relatedness among bulls in the reference population. Our studies indicate that the prediction method, the contribution ratio of including animals, and genetic relatedness could affect the prediction accuracy in genomic evaluation of Holstein cattle, when including genotyped cows in the reference population.

Adaptation and validation of the Malayalam pediatric voice handicap index.

PubMed

Devadas, Usha; Dhanya, M; Gunjawate, Dhanshree

2015-09-01

The aim of the present study was to adapt and validate the English version of pediatric voice handicap index (pVHI) into Malayalam language. The English version of pediatric voice handicap index was translated into Malayalam language using parallel back translation. The translated version was content validated by three qualified speech language pathologists. The content familiarity was carried out by 10 parents of children with voice problems. This was distributed to 136 parents (57 parents of children with dysphonia, 79 parents of children with no voice problems). The internal consistency and test--retest reliability was determined using Cronbach's alpha and intraclass correlation coefficient. Independent sample t-test was used to assess the difference in means. Kappa coefficient was used to determine the correlation between overall severity of the problem and total pVHI. Discriminant analysis was used to identify thresholds for differentiating between normal and dysphonic participants. The results obtained revealed that the Malayalam version of pVHI has an excellent internal consistency; total (α=0.974), functional (α=0.922), physical (α=0.953), and emotional (α=0.923). There was an excellent test-retest reliability; total (r=0.937), functional (r=0.954), physical (r=0.95), and emotional (r=0.929). The prediction probability of the dysphonics is 98.2% using the discriminant score function. The translated and validated pVHI tool can be effectively used in the assessment of children with voice problems. It can provide a better insight into the parents' perception of their child's voice problems. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The Swedish validation of Edinburgh Postnatal Depression Scale (EPDS) during pregnancy.

PubMed

Rubertsson, Christine; Börjesson, Karin; Berglund, Anna; Josefsson, Ann; Sydsjö, Gunilla

2011-12-01

Around 10-15% of women suffer from depressive illness during pregnancy or the first year postpartum. Depression during pregnancy constitutes a risk for prenatal stress and preterm birth. No validated screening instrument for detecting depression during pregnancy was available in Swedish. We aimed to validate the Edinburgh Postnatal Depression Scale (EPDS) against DSM-IV criteria for depression during pregnancy, establish a reliable cut-off and estimate the correlation between the EPDS and HAD-S (Hospital Anxiety and Depression Scale). In a population-based community sample of 1175 pregnant women, 918 women (78%) answered questionnaires with the EPDS and HAD-S. In all, 121 were interviewed using the PRIME-MD (Primary Care Evaluation of Mental disorders) for diagnosing depression. Women were interviewed in mean gestational week 13 (range 8-21). For the EPDS, a receiver operating characteristic (ROC) curve was calculated for prediction of depression. Pearson's correlation coefficient was used to investigate the association between EPDS and HAD-S scores. The optimal cut-off score on the EPDS scale for detecting depression was ≥13 (standard error coefficient of 1.09 and c-statistics of 0.84) giving a sensitivity of 77% and specificity of 94%. The EPDS scores correlated strongly with the HAD-S, Pearson's correlation was 0.83 (P < 0.0001). This study confirms that the EPDS is a valid screening instrument for detection of depressive symptoms during pregnancy. The EPDS shows persuasive measuring outcomes with an optimal cut-off at ≥13. Healthcare for pregnant women should consider screening procedures and follow-up routines for depressive symptoms.

Parameter Optimisation and Uncertainty Analysis in Visual MODFLOW based Flow Model for predicting the groundwater head in an Eastern Indian Aquifer

NASA Astrophysics Data System (ADS)

Mohanty, B.; Jena, S.; Panda, R. K.

2016-12-01

The overexploitation of groundwater elicited in abandoning several shallow tube wells in the study Basin in Eastern India. For the sustainability of groundwater resources, basin-scale modelling of groundwater flow is indispensable for the effective planning and management of the water resources. The basic intent of this study is to develop a 3-D groundwater flow model of the study basin using the Visual MODFLOW Flex 2014.2 package and successfully calibrate and validate the model using 17 years of observed data. The sensitivity analysis was carried out to quantify the susceptibility of aquifer system to the river bank seepage, recharge from rainfall and agriculture practices, horizontal and vertical hydraulic conductivities, and specific yield. To quantify the impact of parameter uncertainties, Sequential Uncertainty Fitting Algorithm (SUFI-2) and Markov chain Monte Carlo (McMC) techniques were implemented. Results from the two techniques were compared and the advantages and disadvantages were analysed. Nash-Sutcliffe coefficient (NSE), Coefficient of Determination (R2), Mean Absolute Error (MAE), Mean Percent Deviation (Dv) and Root Mean Squared Error (RMSE) were adopted as criteria of model evaluation during calibration and validation of the developed model. NSE, R2, MAE, Dv and RMSE values for groundwater flow model during calibration and validation were in acceptable range. Also, the McMC technique was able to provide more reasonable results than SUFI-2. The calibrated and validated model will be useful to identify the aquifer properties, analyse the groundwater flow dynamics and the change in groundwater levels in future forecasts.

Predicting cyclohexane/water distribution coefficients for the SAMPL5 challenge using MOSCED and the SMD solvation model

NASA Astrophysics Data System (ADS)

Diaz-Rodriguez, Sebastian; Bozada, Samantha M.; Phifer, Jeremy R.; Paluch, Andrew S.

2016-11-01

We present blind predictions using the solubility parameter based method MOSCED submitted for the SAMPL5 challenge on calculating cyclohexane/water distribution coefficients at 298 K. Reference data to parameterize MOSCED was generated with knowledge only of chemical structure by performing solvation free energy calculations using electronic structure calculations in the SMD continuum solvent. To maintain simplicity and use only a single method, we approximate the distribution coefficient with the partition coefficient of the neutral species. Over the final SAMPL5 set of 53 compounds, we achieved an average unsigned error of 2.2± 0.2 log units (ranking 15 out of 62 entries), the correlation coefficient ( R) was 0.6± 0.1 (ranking 35), and 72± 6 % of the predictions had the correct sign (ranking 30). While used here to predict cyclohexane/water distribution coefficients at 298 K, MOSCED is broadly applicable, allowing one to predict temperature dependent infinite dilution activity coefficients in any solvent for which parameters exist, and provides a means by which an excess Gibbs free energy model may be parameterized to predict composition dependent phase-equilibrium.

Development and validation of a risk assessment tool for gastric cancer in a general Japanese population.

PubMed

Iida, Masahiro; Ikeda, Fumie; Hata, Jun; Hirakawa, Yoichiro; Ohara, Tomoyuki; Mukai, Naoko; Yoshida, Daigo; Yonemoto, Koji; Esaki, Motohiro; Kitazono, Takanari; Kiyohara, Yutaka; Ninomiya, Toshiharu

2018-05-01

There have been very few reports of risk score models for the development of gastric cancer. The aim of this study was to develop and validate a risk assessment tool for discerning future gastric cancer risk in Japanese. A total of 2444 subjects aged 40 years or over were followed up for 14 years from 1988 (derivation cohort), and 3204 subjects of the same age group were followed up for 5 years from 2002 (validation cohort). The weighting (risk score) of each risk factor for predicting future gastric cancer in the risk assessment tool was determined based on the coefficients of a Cox proportional hazards model in the derivation cohort. The goodness of fit of the established risk assessment tool was assessed using the c-statistic and the Hosmer-Lemeshow test in the validation cohort. During the follow-up, gastric cancer developed in 90 subjects in the derivation cohort and 35 subjects in the validation cohort. In the derivation cohort, the risk prediction model for gastric cancer was established using significant risk factors: age, sex, the combination of Helicobacter pylori antibody and pepsinogen status, hemoglobin A1c level, and smoking status. The incidence of gastric cancer increased significantly as the sum of risk scores increased (P trend < 0.001). The risk assessment tool was validated internally and showed good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test P = 0.43) in the validation cohort. We developed a risk assessment tool for gastric cancer that provides a useful guide for stratifying an individual's risk of future gastric cancer.