WorldWideScience

Sample records for higher predictive accuracy

  1. Global discriminative learning for higher-accuracy computational gene prediction.

    Directory of Open Access Journals (Sweden)

    Axel Bernal

    2007-03-01

    Full Text Available Most ab initio gene predictors use a probabilistic sequence model, typically a hidden Markov model, to combine separately trained models of genomic signals and content. By combining separate models of relevant genomic features, such gene predictors can exploit small training sets and incomplete annotations, and can be trained fairly efficiently. However, that type of piecewise training does not optimize prediction accuracy and has difficulty in accounting for statistical dependencies among different parts of the gene model. With genomic information being created at an ever-increasing rate, it is worth investigating alternative approaches in which many different types of genomic evidence, with complex statistical dependencies, can be integrated by discriminative learning to maximize annotation accuracy. Among discriminative learning methods, large-margin classifiers have become prominent because of the success of support vector machines (SVM in many classification tasks. We describe CRAIG, a new program for ab initio gene prediction based on a conditional random field model with semi-Markov structure that is trained with an online large-margin algorithm related to multiclass SVMs. Our experiments on benchmark vertebrate datasets and on regions from the ENCODE project show significant improvements in prediction accuracy over published gene predictors that use intrinsic features only, particularly at the gene level and on genes with long introns.

  2. Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity

    Directory of Open Access Journals (Sweden)

    Elisa Passini

    2017-09-01

    Full Text Available Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient. Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs. Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density

  3. Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity.

    Science.gov (United States)

    Passini, Elisa; Britton, Oliver J; Lu, Hua Rong; Rohrbacher, Jutta; Hermans, An N; Gallacher, David J; Greig, Robert J H; Bueno-Orovio, Alfonso; Rodriguez, Blanca

    2017-01-01

    Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC 50 /Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca 2+ -transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca 2+ /late Na + currents and Na + /Ca 2+ -exchanger, reduced Na + /K + -pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density

  4. Meditation experience predicts introspective accuracy.

    Directory of Open Access Journals (Sweden)

    Kieran C R Fox

    Full Text Available The accuracy of subjective reports, especially those involving introspection of one's own internal processes, remains unclear, and research has demonstrated large individual differences in introspective accuracy. It has been hypothesized that introspective accuracy may be heightened in persons who engage in meditation practices, due to the highly introspective nature of such practices. We undertook a preliminary exploration of this hypothesis, examining introspective accuracy in a cross-section of meditation practitioners (1-15,000 hrs experience. Introspective accuracy was assessed by comparing subjective reports of tactile sensitivity for each of 20 body regions during a 'body-scanning' meditation with averaged, objective measures of tactile sensitivity (mean size of body representation area in primary somatosensory cortex; two-point discrimination threshold as reported in prior research. Expert meditators showed significantly better introspective accuracy than novices; overall meditation experience also significantly predicted individual introspective accuracy. These results suggest that long-term meditators provide more accurate introspective reports than novices.

  5. Final Technical Report: Increasing Prediction Accuracy.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stein, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

  6. Quantum chemistry by random walk: Higher accuracy

    International Nuclear Information System (INIS)

    Anderson, J.B.

    1980-01-01

    The random walk method of solving the Schroedinger equation is extended to allow the calculation of eigenvalues of atomic and molecular systems with higher accuracy. The combination of direct calculation of the difference delta between a true wave function psi and a trial wave function psi/sub o/ with importance sampling greatly reduces systematic and statistical error. The method is illustrated with calculations for ground-state hydrogen and helium atoms using trial wave functions from variational calculations. The energies obtained are 20 to 100 times more accurate than those of the corresponding variational calculations

  7. Audiovisual biofeedback improves motion prediction accuracy.

    Science.gov (United States)

    Pollock, Sean; Lee, Danny; Keall, Paul; Kim, Taeho

    2013-04-01

    The accuracy of motion prediction, utilized to overcome the system latency of motion management radiotherapy systems, is hampered by irregularities present in the patients' respiratory pattern. Audiovisual (AV) biofeedback has been shown to reduce respiratory irregularities. The aim of this study was to test the hypothesis that AV biofeedback improves the accuracy of motion prediction. An AV biofeedback system combined with real-time respiratory data acquisition and MR images were implemented in this project. One-dimensional respiratory data from (1) the abdominal wall (30 Hz) and (2) the thoracic diaphragm (5 Hz) were obtained from 15 healthy human subjects across 30 studies. The subjects were required to breathe with and without the guidance of AV biofeedback during each study. The obtained respiratory signals were then implemented in a kernel density estimation prediction algorithm. For each of the 30 studies, five different prediction times ranging from 50 to 1400 ms were tested (150 predictions performed). Prediction error was quantified as the root mean square error (RMSE); the RMSE was calculated from the difference between the real and predicted respiratory data. The statistical significance of the prediction results was determined by the Student's t-test. Prediction accuracy was considerably improved by the implementation of AV biofeedback. Of the 150 respiratory predictions performed, prediction accuracy was improved 69% (103/150) of the time for abdominal wall data, and 78% (117/150) of the time for diaphragm data. The average reduction in RMSE due to AV biofeedback over unguided respiration was 26% (p biofeedback improves prediction accuracy. This would result in increased efficiency of motion management techniques affected by system latencies used in radiotherapy.

  8. Accuracy assessment of landslide prediction models

    International Nuclear Information System (INIS)

    Othman, A N; Mohd, W M N W; Noraini, S

    2014-01-01

    The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones

  9. Improving orbit prediction accuracy through supervised machine learning

    Science.gov (United States)

    Peng, Hao; Bai, Xiaoli

    2018-05-01

    Due to the lack of information such as the space environment condition and resident space objects' (RSOs') body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs' trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO's orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.

  10. Predictive accuracy of backpropagation neural network ...

    Indian Academy of Sciences (India)

    incorporated into the BP model for high accuracy management purpose of irrigation water, which relies on accurate values of ET ... as seen from the recent food crisis demonstra- tion in most .... layers by using Geographical Information System.

  11. Quantitative accuracy assessment of thermalhydraulic code predictions with SARBM

    International Nuclear Information System (INIS)

    Prosek, A.

    2001-01-01

    In recent years, the nuclear reactor industry has focused significant attention on nuclear reactor systems code accuracy and uncertainty issues. A few methods suitable to quantify code accuracy of thermalhydraulic code calculations were proposed and applied in the past. In this study a Stochastic Approximation Ratio Based Method (SARBM) was adapted and proposed for accuracy quantification. The objective of the study was to qualify the SARBM. The study compare the accuracy obtained by SARBM with the results obtained by widely used Fast Fourier Transform Based Method (FFTBM). The methods were applied to RELAP5/MOD3.2 code calculations of various BETHSY experiments. The obtained results showed that the SARBM was able to satisfactorily predict the accuracy of the calculated trends when visually comparing plots and comparing the results with the qualified FFTBM. The analysis also showed that the new figure-of-merit called accuracy factor (AF) is more convenient than stochastic approximation ratio for combining single variable accuracy's into total accuracy. The accuracy results obtained for the selected tests suggest that the acceptability factors for the SAR method were reasonably defined. The results also indicate that AF is a useful quantitative measure of accuracy.(author)

  12. Empirical and deterministic accuracies of across-population genomic prediction

    NARCIS (Netherlands)

    Wientjes, Y.C.J.; Veerkamp, R.F.; Bijma, P.; Bovenhuis, H.; Schrooten, C.; Calus, M.P.L.

    2015-01-01

    Background: Differences in linkage disequilibrium and in allele substitution effects of QTL (quantitative trait loci) may hinder genomic prediction across populations. Our objective was to develop a deterministic formula to estimate the accuracy of across-population genomic prediction, for which

  13. An Information Theory Account of Preference Prediction Accuracy

    NARCIS (Netherlands)

    Pollmann, Monique; Scheibehenne, Benjamin

    2015-01-01

    Knowledge about other people's preferences is essential for successful social interactions, but what exactly are the driving factors that determine how well we can predict the likes and dislikes of people around us? To investigate the accuracy of couples’ preference predictions we outline and

  14. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  15. Higher-accuracy van der Waals density functional

    DEFF Research Database (Denmark)

    Lee, Kyuho; Murray, Éamonn D.; Kong, Lingzhu

    2010-01-01

    We propose a second version of the van der Waals density functional of Dion et al. [Phys. Rev. Lett. 92, 246401 (2004)], employing a more accurate semilocal exchange functional and the use of a large-N asymptote gradient correction in determining the vdW kernel. The predicted binding energy...

  16. The accuracy of new wheelchair users' predictions about their future wheelchair use.

    Science.gov (United States)

    Hoenig, Helen; Griffiths, Patricia; Ganesh, Shanti; Caves, Kevin; Harris, Frances

    2012-06-01

    This study examined the accuracy of new wheelchair user predictions about their future wheelchair use. This was a prospective cohort study of 84 community-dwelling veterans provided a new manual wheelchair. The association between predicted and actual wheelchair use was strong at 3 mos (ϕ coefficient = 0.56), with 90% of those who anticipated using the wheelchair at 3 mos still using it (i.e., positive predictive value = 0.96) and 60% of those who anticipated not using it indeed no longer using the wheelchair (i.e., negative predictive value = 0.60, overall accuracy = 0.92). Predictive accuracy diminished over time, with overall accuracy declining from 0.92 at 3 mos to 0.66 at 6 mos. At all time points, and for all types of use, patients better predicted use as opposed to disuse, with correspondingly higher positive than negative predictive values. Accuracy of prediction of use in specific indoor and outdoor locations varied according to location. This study demonstrates the importance of better understanding the potential mismatch between the anticipated and actual patterns of wheelchair use. The findings suggest that users can be relied upon to accurately predict their basic wheelchair-related needs in the short-term. Further exploration is needed to identify characteristics that will aid users and their providers in more accurately predicting mobility needs for the long-term.

  17. Numerical methods of higher order of accuracy for incompressible flows

    Czech Academy of Sciences Publication Activity Database

    Kozel, K.; Louda, Petr; Příhoda, Jaromír

    2010-01-01

    Roč. 80, č. 8 (2010), s. 1734-1745 ISSN 0378-4754 Institutional research plan: CEZ:AV0Z20760514 Keywords : higher order methods * upwind methods * backward-facing step Subject RIV: BK - Fluid Dynamics Impact factor: 0.812, year: 2010

  18. Accuracy of predicting milk yield from alternative recording schemes

    NARCIS (Netherlands)

    Berry, D.P.; Olori, V.E.; Cromie, A.R.; Rath, M.; Veerkamp, R.F.; Dilon, P.

    2005-01-01

    The effect of reducing the frequency of official milk recording and the number of recorded samples per test-day on the accuracy of predicting daily yield and cumulative 305-day yield was investigated. A control data set consisting of 58 210 primiparous cows with milk test-day records every 4 weeks

  19. Predictive Accuracy of Exercise Stress Testing the Healthy Adult.

    Science.gov (United States)

    Lamont, Linda S.

    1981-01-01

    Exercise stress testing provides information on the aerobic capacity, heart rate, and blood pressure responses to graded exercises of a healthy adult. The reliability of exercise tests as a diagnostic procedure is discussed in relation to sensitivity and specificity and predictive accuracy. (JN)

  20. Assessing Genomic Selection Prediction Accuracy in a Dynamic Barley Breeding Population

    Directory of Open Access Journals (Sweden)

    A. H. Sallam

    2015-03-01

    Full Text Available Prediction accuracy of genomic selection (GS has been previously evaluated through simulation and cross-validation; however, validation based on progeny performance in a plant breeding program has not been investigated thoroughly. We evaluated several prediction models in a dynamic barley breeding population comprised of 647 six-row lines using four traits differing in genetic architecture and 1536 single nucleotide polymorphism (SNP markers. The breeding lines were divided into six sets designated as one parent set and five consecutive progeny sets comprised of representative samples of breeding lines over a 5-yr period. We used these data sets to investigate the effect of model and training population composition on prediction accuracy over time. We found little difference in prediction accuracy among the models confirming prior studies that found the simplest model, random regression best linear unbiased prediction (RR-BLUP, to be accurate across a range of situations. In general, we found that using the parent set was sufficient to predict progeny sets with little to no gain in accuracy from generating larger training populations by combining the parent set with subsequent progeny sets. The prediction accuracy ranged from 0.03 to 0.99 across the four traits and five progeny sets. We explored characteristics of the training and validation populations (marker allele frequency, population structure, and linkage disequilibrium, LD as well as characteristics of the trait (genetic architecture and heritability, . Fixation of markers associated with a trait over time was most clearly associated with reduced prediction accuracy for the mycotoxin trait DON. Higher trait in the training population and simpler trait architecture were associated with greater prediction accuracy.

  1. Accuracy of ultrasound for the prediction of placenta accreta.

    Science.gov (United States)

    Bowman, Zachary S; Eller, Alexandra G; Kennedy, Anne M; Richards, Douglas S; Winter, Thomas C; Woodward, Paula J; Silver, Robert M

    2014-08-01

    Ultrasound has been reported to be greater than 90% sensitive for the diagnosis of accreta. Prior studies may be subject to bias because of single expert observers, suspicion for accreta, and knowledge of risk factors. We aimed to assess the accuracy of ultrasound for the prediction of accreta. Patients with accreta at a single academic center were matched to patients with placenta previa, but no accreta, by year of delivery. Ultrasound studies with views of the placenta were collected, deidentified, blinded to clinical history, and placed in random sequence. Six investigators prospectively interpreted each study for the presence of accreta and findings reported to be associated with its diagnosis. Sensitivity, specificity, positive predictive, negative predictive value, and accuracy were calculated. Characteristics of accurate findings were compared using univariate and multivariate analyses. Six investigators examined 229 ultrasound studies from 55 patients with accreta and 56 controls for 1374 independent observations. 1205/1374 (87.7% overall, 90% controls, 84.9% cases) studies were given a diagnosis. There were 371 (27.0%) true positives; 81 (5.9%) false positives; 533 (38.8%) true negatives, 220 (16.0%) false negatives, and 169 (12.3%) with uncertain diagnosis. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 53.5%, 88.0%, 82.1%, 64.8%, and 64.8%, respectively. In multivariate analysis, true positives were more likely to have placental lacunae (odds ratio [OR], 1.5; 95% confidence interval [CI], 1.4-1.6), loss of retroplacental clear space (OR, 2.4; 95% CI, 1.1-4.9), or abnormalities on color Doppler (OR, 2.1; 95% CI, 1.8-2.4). Ultrasound for the prediction of placenta accreta may not be as sensitive as previously described. Copyright © 2014 Mosby, Inc. All rights reserved.

  2. Genomic Prediction Accuracy for Resistance Against Piscirickettsia salmonis in Farmed Rainbow Trout

    Directory of Open Access Journals (Sweden)

    Grazyella M. Yoshida

    2018-02-01

    Full Text Available Salmonid rickettsial syndrome (SRS, caused by the intracellular bacterium Piscirickettsia salmonis, is one of the main diseases affecting rainbow trout (Oncorhynchus mykiss farming. To accelerate genetic progress, genomic selection methods can be used as an effective approach to control the disease. The aims of this study were: (i to compare the accuracy of estimated breeding values using pedigree-based best linear unbiased prediction (PBLUP with genomic BLUP (GBLUP, single-step GBLUP (ssGBLUP, Bayes C, and Bayesian Lasso (LASSO; and (ii to test the accuracy of genomic prediction and PBLUP using different marker densities (0.5, 3, 10, 20, and 27 K for resistance against P. salmonis in rainbow trout. Phenotypes were recorded as number of days to death (DD and binary survival (BS from 2416 fish challenged with P. salmonis. A total of 1934 fish were genotyped using a 57 K single-nucleotide polymorphism (SNP array. All genomic prediction methods achieved higher accuracies than PBLUP. The relative increase in accuracy for different genomic models ranged from 28 to 41% for both DD and BS at 27 K SNP. Between different genomic models, the highest relative increase in accuracy was obtained with Bayes C (∼40%, where 3 K SNP was enough to achieve a similar accuracy to that of the 27 K SNP for both traits. For resistance against P. salmonis in rainbow trout, we showed that genomic predictions using GBLUP, ssGBLUP, Bayes C, and LASSO can increase accuracy compared with PBLUP. Moreover, it is possible to use relatively low-density SNP panels for genomic prediction without compromising accuracy predictions for resistance against P. salmonis in rainbow trout.

  3. Using Genetic Distance to Infer the Accuracy of Genomic Prediction.

    Directory of Open Access Journals (Sweden)

    Marco Scutari

    2016-09-01

    Full Text Available The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics.

  4. Genomic selection in mink yield higher accuracies with a Bayesian approach allowing for heterogeneous variance than a GBLUP model

    DEFF Research Database (Denmark)

    Villumsen, Trine Michelle; Su, Guosheng; Cai, Zexi

    2018-01-01

    by sequencing. Four live grading traits and four traits on dried pelts for size and quality were analysed. GWAS analysis detected significant SNPs for all the traits. The single-trait Bayesian model resulted in higher accuracies for the genomic predictions than the single-trait GBLUP model, especially......The accuracy of genomic prediction for mink was compared for single-trait and multiple-trait GBLUP models and Bayesian models that allowed for heterogeneous (co)variance structure over the genome. The mink population consisted of 2,103 brown minks genotyped with the method of genotyping...... for the traits measured on dried pelts. We expected the multiple-trait models to be superior to the single trait models since the multiple-trait model can make use of information when traits are correlated. However, we did not find a general improvement in accuracies with the multiple-trait models compared...

  5. A New Approach to Improve Accuracy of Grey Model GMC(1,n in Time Series Prediction

    Directory of Open Access Journals (Sweden)

    Sompop Moonchai

    2015-01-01

    Full Text Available This paper presents a modified grey model GMC(1,n for use in systems that involve one dependent system behavior and n-1 relative factors. The proposed model was developed from the conventional GMC(1,n model in order to improve its prediction accuracy by modifying the formula for calculating the background value, the system of parameter estimation, and the model prediction equation. The modified GMC(1,n model was verified by two cases: the study of forecasting CO2 emission in Thailand and forecasting electricity consumption in Thailand. The results demonstrated that the modified GMC(1,n model was able to achieve higher fitting and prediction accuracy compared with the conventional GMC(1,n and D-GMC(1,n models.

  6. Bias associated with delayed verification in test accuracy studies: accuracy of tests for endometrial hyperplasia may be much higher than we think!

    OpenAIRE

    Clark, T Justin; ter Riet, Gerben; Coomarasamy, Aravinthan; Khan, Khalid S

    2004-01-01

    Abstract Background To empirically evaluate bias in estimation of accuracy associated with delay in verification of diagnosis among studies evaluating tests for predicting endometrial hyperplasia. Methods Systematic reviews of all published research on accuracy of miniature endometrial biopsy and endometr ial ultrasonography for diagnosing endometrial hyperplasia identified 27 test accuracy studies (2,982 subjects). Of these, 16 had immediate histological verification of diagnosis while 11 ha...

  7. Effects of sample size on robustness and prediction accuracy of a prognostic gene signature

    Directory of Open Access Journals (Sweden)

    Kim Seon-Young

    2009-05-01

    Full Text Available Abstract Background Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature. Results A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+ patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures Conclusion Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.

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

    Science.gov (United States)

    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.

  9. Accuracy in Orbital Propagation: A Comparison of Predictive Software Models

    Science.gov (United States)

    2017-06-01

    30] M. Lane and K. Cranford, "An improved analytical drag theory for the artificial satellite problem," American Institute of Aeronautics and...which have a foundation in similar theory . Since their first operational use, both propagators have incorporated updated theory and mathematical...propagators should therefore utilize the most current TLE data available to avoid accuracy errors. 14. SUBJECT TERMS orbital mechanics , orbital

  10. Improving prediction accuracy of cooling load using EMD, PSR and RBFNN

    Science.gov (United States)

    Shen, Limin; Wen, Yuanmei; Li, Xiaohong

    2017-08-01

    To increase the accuracy for the prediction of cooling load demand, this work presents an EMD (empirical mode decomposition)-PSR (phase space reconstruction) based RBFNN (radial basis function neural networks) method. Firstly, analyzed the chaotic nature of the real cooling load demand, transformed the non-stationary cooling load historical data into several stationary intrinsic mode functions (IMFs) by using EMD. Secondly, compared the RBFNN prediction accuracies of each IMFs and proposed an IMF combining scheme that is combine the lower-frequency components (called IMF4-IMF6 combined) while keep the higher frequency component (IMF1, IMF2, IMF3) and the residual unchanged. Thirdly, reconstruct phase space for each combined components separately, process the highest frequency component (IMF1) by differential method and predict with RBFNN in the reconstructed phase spaces. Real cooling load data of a centralized ice storage cooling systems in Guangzhou are used for simulation. The results show that the proposed hybrid method outperforms the traditional methods.

  11. Accuracy of depolarization and delay spread predictions using advanced ray-based modeling in indoor scenarios

    Directory of Open Access Journals (Sweden)

    Mani Francesco

    2011-01-01

    Full Text Available Abstract This article investigates the prediction accuracy of an advanced deterministic propagation model in terms of channel depolarization and frequency selectivity for indoor wireless propagation. In addition to specular reflection and diffraction, the developed ray tracing tool considers penetration through dielectric blocks and/or diffuse scattering mechanisms. The sensitivity and prediction accuracy analysis is based on two measurement campaigns carried out in a warehouse and an office building. It is shown that the implementation of diffuse scattering into RT significantly increases the accuracy of the cross-polar discrimination prediction, whereas the delay-spread prediction is only marginally improved.

  12. A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

    Science.gov (United States)

    Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

    2017-09-01

    Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  13. Enhancing Predictive Accuracy of Cardiac Autonomic Neuropathy Using Blood Biochemistry Features and Iterative Multitier Ensembles.

    Science.gov (United States)

    Abawajy, Jemal; Kelarev, Andrei; Chowdhury, Morshed U; Jelinek, Herbert F

    2016-01-01

    Blood biochemistry attributes form an important class of tests, routinely collected several times per year for many patients with diabetes. The objective of this study is to investigate the role of blood biochemistry for improving the predictive accuracy of the diagnosis of cardiac autonomic neuropathy (CAN) progression. Blood biochemistry contributes to CAN, and so it is a causative factor that can provide additional power for the diagnosis of CAN especially in the absence of a complete set of Ewing tests. We introduce automated iterative multitier ensembles (AIME) and investigate their performance in comparison to base classifiers and standard ensemble classifiers for blood biochemistry attributes. AIME incorporate diverse ensembles into several tiers simultaneously and combine them into one automatically generated integrated system so that one ensemble acts as an integral part of another ensemble. We carried out extensive experimental analysis using large datasets from the diabetes screening research initiative (DiScRi) project. The results of our experiments show that several blood biochemistry attributes can be used to supplement the Ewing battery for the detection of CAN in situations where one or more of the Ewing tests cannot be completed because of the individual difficulties faced by each patient in performing the tests. The results show that AIME provide higher accuracy as a multitier CAN classification paradigm. The best predictive accuracy of 99.57% has been obtained by the AIME combining decorate on top tier with bagging on middle tier based on random forest. Practitioners can use these findings to increase the accuracy of CAN diagnosis.

  14. Knowing right from wrong in mental arithmetic judgments: calibration of confidence predicts the development of accuracy.

    Science.gov (United States)

    Rinne, Luke F; Mazzocco, Michèle M M

    2014-01-01

    Does knowing when mental arithmetic judgments are right--and when they are wrong--lead to more accurate judgments over time? We hypothesize that the successful detection of errors (and avoidance of false alarms) may contribute to the development of mental arithmetic performance. Insight into error detection abilities can be gained by examining the "calibration" of mental arithmetic judgments-that is, the alignment between confidence in judgments and the accuracy of those judgments. Calibration may be viewed as a measure of metacognitive monitoring ability. We conducted a developmental longitudinal investigation of the relationship between the calibration of children's mental arithmetic judgments and their performance on a mental arithmetic task. Annually between Grades 5 and 8, children completed a problem verification task in which they rapidly judged the accuracy of arithmetic expressions (e.g., 25 + 50 = 75) and rated their confidence in each judgment. Results showed that calibration was strongly related to concurrent mental arithmetic performance, that calibration continued to develop even as mental arithmetic accuracy approached ceiling, that poor calibration distinguished children with mathematics learning disability from both low and typically achieving children, and that better calibration in Grade 5 predicted larger gains in mental arithmetic accuracy between Grades 5 and 8. We propose that good calibration supports the implementation of cognitive control, leading to long-term improvement in mental arithmetic accuracy. Because mental arithmetic "fluency" is critical for higher-level mathematics competence, calibration of confidence in mental arithmetic judgments may represent a novel and important developmental predictor of future mathematics performance.

  15. Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

    Science.gov (United States)

    Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

    2018-06-01

    Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

  16. Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding.

    Science.gov (United States)

    Ould Estaghvirou, Sidi Boubacar; Ogutu, Joseph O; Schulz-Streeck, Torben; Knaak, Carsten; Ouzunova, Milena; Gordillo, Andres; Piepho, Hans-Peter

    2013-12-06

    In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least

  17. Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

    Science.gov (United States)

    Jia, Yi; Jannink, Jean-Luc

    2012-01-01

    Genetic correlations between quantitative traits measured in many breeding programs are pervasive. These correlations indicate that measurements of one trait carry information on other traits. Current single-trait (univariate) genomic selection does not take advantage of this information. Multivariate genomic selection on multiple traits could accomplish this but has been little explored and tested in practical breeding programs. In this study, three multivariate linear models (i.e., GBLUP, BayesA, and BayesCπ) were presented and compared to univariate models using simulated and real quantitative traits controlled by different genetic architectures. We also extended BayesA with fixed hyperparameters to a full hierarchical model that estimated hyperparameters and BayesCπ to impute missing phenotypes. We found that optimal marker-effect variance priors depended on the genetic architecture of the trait so that estimating them was beneficial. We showed that the prediction accuracy for a low-heritability trait could be significantly increased by multivariate genomic selection when a correlated high-heritability trait was available. Further, multiple-trait genomic selection had higher prediction accuracy than single-trait genomic selection when phenotypes are not available on all individuals and traits. Additional factors affecting the performance of multiple-trait genomic selection were explored. PMID:23086217

  18. Bias associated with delayed verification in test accuracy studies: accuracy of tests for endometrial hyperplasia may be much higher than we think!

    Directory of Open Access Journals (Sweden)

    Coomarasamy Aravinthan

    2004-05-01

    Full Text Available Abstract Background To empirically evaluate bias in estimation of accuracy associated with delay in verification of diagnosis among studies evaluating tests for predicting endometrial hyperplasia. Methods Systematic reviews of all published research on accuracy of miniature endometrial biopsy and endometr ial ultrasonography for diagnosing endometrial hyperplasia identified 27 test accuracy studies (2,982 subjects. Of these, 16 had immediate histological verification of diagnosis while 11 had verification delayed > 24 hrs after testing. The effect of delay in verification of diagnosis on estimates of accuracy was evaluated using meta-regression with diagnostic odds ratio (dOR as the accuracy measure. This analysis was adjusted for study quality and type of test (miniature endometrial biopsy or endometrial ultrasound. Results Compared to studies with immediate verification of diagnosis (dOR 67.2, 95% CI 21.7–208.8, those with delayed verification (dOR 16.2, 95% CI 8.6–30.5 underestimated the diagnostic accuracy by 74% (95% CI 7%–99%; P value = 0.048. Conclusion Among studies of miniature endometrial biopsy and endometrial ultrasound, diagnostic accuracy is considerably underestimated if there is a delay in histological verification of diagnosis.

  19. Higher accuracy analytical approximations to a nonlinear oscillator with discontinuity by He's homotopy perturbation method

    International Nuclear Information System (INIS)

    Belendez, A.; Hernandez, A.; Belendez, T.; Neipp, C.; Marquez, A.

    2008-01-01

    He's homotopy perturbation method is used to calculate higher-order approximate periodic solutions of a nonlinear oscillator with discontinuity for which the elastic force term is proportional to sgn(x). We find He's homotopy perturbation method works very well for the whole range of initial amplitudes, and the excellent agreement of the approximate frequencies and periodic solutions with the exact ones has been demonstrated and discussed. Only one iteration leads to high accuracy of the solutions with a maximal relative error for the approximate period of less than 1.56% for all values of oscillation amplitude, while this relative error is 0.30% for the second iteration and as low as 0.057% when the third-order approximation is considered. Comparison of the result obtained using this method with those obtained by different harmonic balance methods reveals that He's homotopy perturbation method is very effective and convenient

  20. Heterogeneity of long-history migration predicts emotion recognition accuracy.

    Science.gov (United States)

    Wood, Adrienne; Rychlowska, Magdalena; Niedenthal, Paula M

    2016-06-01

    Recent work (Rychlowska et al., 2015) demonstrated the power of a relatively new cultural dimension, historical heterogeneity, in predicting cultural differences in the endorsement of emotion expression norms. Historical heterogeneity describes the number of source countries that have contributed to a country's present-day population over the last 500 years. People in cultures originating from a large number of source countries may have historically benefited from greater and clearer emotional expressivity, because they lacked a common language and well-established social norms. We therefore hypothesized that in addition to endorsing more expressive display rules, individuals from heterogeneous cultures will also produce facial expressions that are easier to recognize by people from other cultures. By reanalyzing cross-cultural emotion recognition data from 92 papers and 82 cultures, we show that emotion expressions of people from heterogeneous cultures are more easily recognized by observers from other cultures than are the expressions produced in homogeneous cultures. Heterogeneity influences expression recognition rates alongside the individualism-collectivism of the perceivers' culture, as more individualistic cultures were more accurate in emotion judgments than collectivistic cultures. This work reveals the present-day behavioral consequences of long-term historical migration patterns and demonstrates the predictive power of historical heterogeneity. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  1. Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship.

    Directory of Open Access Journals (Sweden)

    S Hong Lee

    Full Text Available Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic. It is desirable to establish a theoretical framework for genomic prediction accuracy when the reference data consists of information sources with varying degrees of relationship to the target individuals. A reference set can contain both close and distant relatives as well as 'unrelated' individuals from the wider population in the genomic prediction. The various sources of information were modeled as different populations with different effective population sizes (Ne. Both the effective number of chromosome segments (Me and Ne are considered to be a function of the data used for prediction. We validate our theory with analyses of simulated as well as real data, and illustrate that the variation in genomic relationships with the target is a predictor of the information content of the reference set. With a similar amount of data available for each source, we show that close relatives can have a substantially larger effect on genomic prediction accuracy than lesser related individuals. We also illustrate that when prediction relies on closer relatives, there is less improvement in prediction accuracy with an increase in training data or marker panel density. We release software that can estimate the expected prediction accuracy and power when combining different reference sources with various degrees of relationship to the target, which is useful when planning genomic prediction (before or after collecting data in animal, plant and human genetics.

  2. Long-term prediction of reading accuracy and speed: The importance of paired-associate learning

    DEFF Research Database (Denmark)

    Poulsen, Mads; Asmussen, Vibeke; Elbro, Carsten

    Purpose: Several cross-sectional studies have found a correlation between paired-associate learning (PAL) and reading (e.g. Litt et al., 2013; Messbauer & de Jong, 2003, 2006). These findings suggest that verbal learning of phonological forms is important for reading. However, results from...... longitudinal studies have been mixed (e.g. Lervåg & Hulme, 2009; Horbach et al. 2015). The present study investigated the possibility that the mixed results may be a result of a conflation of accuracy and speed. It is possible that PAL is a stronger correlate of reading accuracy than speed (Litt et al., 2013...... of reading comprehension and isolated sight word reading accuracy and speed. Results: PAL predicted unique variance in sight word accuracy, but not speed. Furthermore, PAL was indirectly linked to reading comprehension through sight word accuracy. RAN correlated with both accuracy and speed...

  3. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction.

    Directory of Open Access Journals (Sweden)

    Yiming Hu

    2017-06-01

    Full Text Available Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.

  4. Prediction of lung tumour position based on spirometry and on abdominal displacement: Accuracy and reproducibility

    International Nuclear Information System (INIS)

    Hoisak, Jeremy D.P.; Sixel, Katharina E.; Tirona, Romeo; Cheung, Patrick C.F.; Pignol, Jean-Philippe

    2006-01-01

    Background and purpose: A simulation investigating the accuracy and reproducibility of a tumour motion prediction model over clinical time frames is presented. The model is formed from surrogate and tumour motion measurements, and used to predict the future position of the tumour from surrogate measurements alone. Patients and methods: Data were acquired from five non-small cell lung cancer patients, on 3 days. Measurements of respiratory volume by spirometry and abdominal displacement by a real-time position tracking system were acquired simultaneously with X-ray fluoroscopy measurements of superior-inferior tumour displacement. A model of tumour motion was established and used to predict future tumour position, based on surrogate input data. The calculated position was compared against true tumour motion as seen on fluoroscopy. Three different imaging strategies, pre-treatment, pre-fraction and intrafractional imaging, were employed in establishing the fitting parameters of the prediction model. The impact of each imaging strategy upon accuracy and reproducibility was quantified. Results: When establishing the predictive model using pre-treatment imaging, four of five patients exhibited poor interfractional reproducibility for either surrogate in subsequent sessions. Simulating the formulation of the predictive model prior to each fraction resulted in improved interfractional reproducibility. The accuracy of the prediction model was only improved in one of five patients when intrafractional imaging was used. Conclusions: Employing a prediction model established from measurements acquired at planning resulted in localization errors. Pre-fractional imaging improved the accuracy and reproducibility of the prediction model. Intrafractional imaging was of less value, suggesting that the accuracy limit of a surrogate-based prediction model is reached with once-daily imaging

  5. Accuracy of algorithms to predict accessory pathway location in children with Wolff-Parkinson-White syndrome.

    Science.gov (United States)

    Wren, Christopher; Vogel, Melanie; Lord, Stephen; Abrams, Dominic; Bourke, John; Rees, Philip; Rosenthal, Eric

    2012-02-01

    The aim of this study was to examine the accuracy in predicting pathway location in children with Wolff-Parkinson-White syndrome for each of seven published algorithms. ECGs from 100 consecutive children with Wolff-Parkinson-White syndrome undergoing electrophysiological study were analysed by six investigators using seven published algorithms, six of which had been developed in adult patients. Accuracy and concordance of predictions were adjusted for the number of pathway locations. Accessory pathways were left-sided in 49, septal in 20 and right-sided in 31 children. Overall accuracy of prediction was 30-49% for the exact location and 61-68% including adjacent locations. Concordance between investigators varied between 41% and 86%. No algorithm was better at predicting septal pathways (accuracy 5-35%, improving to 40-78% including adjacent locations), but one was significantly worse. Predictive accuracy was 24-53% for the exact location of right-sided pathways (50-71% including adjacent locations) and 32-55% for the exact location of left-sided pathways (58-73% including adjacent locations). All algorithms were less accurate in our hands than in other authors' own assessment. None performed well in identifying midseptal or right anteroseptal accessory pathway locations.

  6. Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

    Science.gov (United States)

    Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

    2016-11-01

    Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

  7. Increasing imputation and prediction accuracy for Chinese Holsteins using joint Chinese-Nordic reference population

    DEFF Research Database (Denmark)

    Ma, Peipei; Lund, Mogens Sandø; Ding, X

    2015-01-01

    This study investigated the effect of including Nordic Holsteins in the reference population on the imputation accuracy and prediction accuracy for Chinese Holsteins. The data used in this study include 85 Chinese Holstein bulls genotyped with both 54K chip and 777K (HD) chip, 2862 Chinese cows...... was improved slightly when using the marker data imputed based on the combined HD reference data, compared with using the marker data imputed based on the Chinese HD reference data only. On the other hand, when using the combined reference population including 4398 Nordic Holstein bulls, the accuracy...... to increase reference population rather than increasing marker density...

  8. Typing speed, spelling accuracy, and the use of word-prediction

    Directory of Open Access Journals (Sweden)

    Marina Herold

    2008-02-01

    Full Text Available Children with spelling difficulties are limited in their participation in all written school activities. We aimed to investigate the influence of word-prediction as a tool on spelling accuracy and typing speed. To this end, we selected 80 Grade 4 - 6 children with spelling difficulties in a school for special needs to participate in a research project involving a cross-over within-subject design. The research task took the form of entering 30 words through an on-screen keyboard, with and without the use of word-prediction software. The Graded Word Spelling Test served to investigate whether there was a relationship between the children's current spelling knowledge and word-prediction efficacy. The results indicated an increase in spelling accuracy with the use of word-prediction, but at the cost of time and the tendency to use word approximations, and no significant relationship between spelling knowledge and word-prediction efficacy.

  9. Improving the accuracy of protein secondary structure prediction using structural alignment

    Directory of Open Access Journals (Sweden)

    Gallin Warren J

    2006-06-01

    Full Text Available Abstract Background The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3 of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences, the probability of a newly identified sequence having a structural homologue is actually quite high. Results We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25% onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics indicate that this new method can achieve a Q3 score approaching 88%. Conclusion By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible at http://wishart.biology.ualberta.ca/proteus. For high throughput or batch sequence analyses, the PROTEUS programs

  10. Link Prediction Methods and Their Accuracy for Different Social Networks and Network Metrics

    Directory of Open Access Journals (Sweden)

    Fei Gao

    2015-01-01

    Full Text Available Currently, we are experiencing a rapid growth of the number of social-based online systems. The availability of the vast amounts of data gathered in those systems brings new challenges that we face when trying to analyse it. One of the intensively researched topics is the prediction of social connections between users. Although a lot of effort has been made to develop new prediction approaches, the existing methods are not comprehensively analysed. In this paper we investigate the correlation between network metrics and accuracy of different prediction methods. We selected six time-stamped real-world social networks and ten most widely used link prediction methods. The results of the experiments show that the performance of some methods has a strong correlation with certain network metrics. We managed to distinguish “prediction friendly” networks, for which most of the prediction methods give good performance, as well as “prediction unfriendly” networks, for which most of the methods result in high prediction error. Correlation analysis between network metrics and prediction accuracy of prediction methods may form the basis of a metalearning system where based on network characteristics it will be able to recommend the right prediction method for a given network.

  11. Accuracy of taxonomy prediction for 16S rRNA and fungal ITS sequences

    Directory of Open Access Journals (Sweden)

    Robert C. Edgar

    2018-04-01

    Full Text Available Prediction of taxonomy for marker gene sequences such as 16S ribosomal RNA (rRNA is a fundamental task in microbiology. Most experimentally observed sequences are diverged from reference sequences of authoritatively named organisms, creating a challenge for prediction methods. I assessed the accuracy of several algorithms using cross-validation by identity, a new benchmark strategy which explicitly models the variation in distances between query sequences and the closest entry in a reference database. When the accuracy of genus predictions was averaged over a representative range of identities with the reference database (100%, 99%, 97%, 95% and 90%, all tested methods had ≤50% accuracy on the currently-popular V4 region of 16S rRNA. Accuracy was found to fall rapidly with identity; for example, better methods were found to have V4 genus prediction accuracy of ∼100% at 100% identity but ∼50% at 97% identity. The relationship between identity and taxonomy was quantified as the probability that a rank is the lowest shared by a pair of sequences with a given pair-wise identity. With the V4 region, 95% identity was found to be a twilight zone where taxonomy is highly ambiguous because the probabilities that the lowest shared rank between pairs of sequences is genus, family, order or class are approximately equal.

  12. Appropriate Combination of Artificial Intelligence and Algorithms for Increasing Predictive Accuracy Management

    Directory of Open Access Journals (Sweden)

    Shahram Gilani Nia

    2010-03-01

    Full Text Available In this paper a simple and effective expert system to predict random data fluctuation in short-term period is established. Evaluation process includes introducing Fourier series, Markov chain model prediction and comparison (Gray combined with the model prediction Gray- Fourier- Markov that the mixed results, to create an expert system predicted with artificial intelligence, made this model to predict the effectiveness of random fluctuation in most data management programs to increase. The outcome of this study introduced artificial intelligence algorithms that help detect that the computer environment to create a system that experts predict the short-term and unstable situation happens correctly and accurately predict. To test the effectiveness of the algorithm presented studies (Chen Tzay len,2008, and predicted data of tourism demand for Iran model is used. Results for the two countries show output model has high accuracy.

  13. Explained variation and predictive accuracy in general parametric statistical models: the role of model misspecification

    DEFF Research Database (Denmark)

    Rosthøj, Susanne; Keiding, Niels

    2004-01-01

    When studying a regression model measures of explained variation are used to assess the degree to which the covariates determine the outcome of interest. Measures of predictive accuracy are used to assess the accuracy of the predictions based on the covariates and the regression model. We give a ...... a detailed and general introduction to the two measures and the estimation procedures. The framework we set up allows for a study of the effect of misspecification on the quantities estimated. We also introduce a generalization to survival analysis....

  14. Estimating the Accuracy of the Chedoke-McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation.

    Science.gov (United States)

    Dang, Mia; Ramsaran, Kalinda D; Street, Melissa E; Syed, S Noreen; Barclay-Goddard, Ruth; Stratford, Paul W; Miller, Patricia A

    2011-01-01

    To estimate the predictive accuracy and clinical usefulness of the Chedoke-McMaster Stroke Assessment (CMSA) predictive equations. A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from -0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted.

  15. Estimating the Accuracy of the Chedoke–McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation

    Science.gov (United States)

    Dang, Mia; Ramsaran, Kalinda D.; Street, Melissa E.; Syed, S. Noreen; Barclay-Goddard, Ruth; Miller, Patricia A.

    2011-01-01

    ABSTRACT Purpose: To estimate the predictive accuracy and clinical usefulness of the Chedoke–McMaster Stroke Assessment (CMSA) predictive equations. Method: A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Results: Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from −0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. Conclusions: This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted. PMID:22654239

  16. Age-related differences in the accuracy of web query-based predictions of influenza-like illness.

    Directory of Open Access Journals (Sweden)

    Alexander Domnich

    Full Text Available Web queries are now widely used for modeling, nowcasting and forecasting influenza-like illness (ILI. However, given that ILI attack rates vary significantly across ages, in terms of both magnitude and timing, little is known about whether the association between ILI morbidity and ILI-related queries is comparable across different age-groups. The present study aimed to investigate features of the association between ILI morbidity and ILI-related query volume from the perspective of age.Since Google Flu Trends is unavailable in Italy, Google Trends was used to identify entry terms that correlated highly with official ILI surveillance data. All-age and age-class-specific modeling was performed by means of linear models with generalized least-square estimation. Hold-out validation was used to quantify prediction accuracy. For purposes of comparison, predictions generated by exponential smoothing were computed.Five search terms showed high correlation coefficients of > .6. In comparison with exponential smoothing, the all-age query-based model correctly predicted the peak time and yielded a higher correlation coefficient with observed ILI morbidity (.978 vs. .929. However, query-based prediction of ILI morbidity was associated with a greater error. Age-class-specific query-based models varied significantly in terms of prediction accuracy. In the 0-4 and 25-44-year age-groups, these did well and outperformed exponential smoothing predictions; in the 15-24 and ≥ 65-year age-classes, however, the query-based models were inaccurate and highly overestimated peak height. In all but one age-class, peak timing predicted by the query-based models coincided with observed timing.The accuracy of web query-based models in predicting ILI morbidity rates could differ among ages. Greater age-specific detail may be useful in flu query-based studies in order to account for age-specific features of the epidemiology of ILI.

  17. Accuracy assessment of the ERP prediction method based on analysis of 100-year ERP series

    Science.gov (United States)

    Malkin, Z.; Tissen, V. M.

    2012-12-01

    A new method has been developed at the Siberian Research Institute of Metrology (SNIIM) for highly accurate prediction of UT1 and Pole motion (PM). In this study, a detailed comparison was made of real-time UT1 predictions made in 2006-2011 and PMpredictions made in 2009-2011making use of the SNIIM method with simultaneous predictions computed at the International Earth Rotation and Reference Systems Service (IERS), USNO. Obtained results have shown that proposed method provides better accuracy at different prediction lengths.

  18. PREDICTIVE ACCURACY OF TRANSCEREBELLAR DIAMETER IN COMPARISON WITH OTHER FOETAL BIOMETRIC PARAMETERS FOR GESTATIONAL AGE ESTIMATION AMONG PREGNANT NIGERIAN WOMEN.

    Science.gov (United States)

    Adeyekun, A A; Orji, M O

    2014-04-01

    To compare the predictive accuracy of foetal trans-cerebellar diameter (TCD) with those of other biometric parameters in the estimation of gestational age (GA). A cross-sectional study. The University of Benin Teaching Hospital, Nigeria. Four hundred and fifty healthy singleton pregnant women, between 14-42 weeks gestation. Trans-cerebellar diameter (TCD), biparietal diameter (BPD), femur length (FL), abdominal circumference (AC) values across the gestational age range studied. Correlation and predictive values of TCD compared to those of other biometric parameters. The range of values for TCD was 11.9 - 59.7mm (mean = 34.2 ± 14.1mm). TCD correlated more significantly with menstrual age compared with other biometric parameters (r = 0.984, p = 0.000). TCD had a higher predictive accuracy of 96.9% ± 12 days), BPD (93.8% ± 14.1 days). AC (92.7% ± 15.3 days). TCD has a stronger predictive accuracy for gestational age compared to other routinely used foetal biometric parameters among Nigerian Africans.

  19. Probability of criminal acts of violence: a test of jury predictive accuracy.

    Science.gov (United States)

    Reidy, Thomas J; Sorensen, Jon R; Cunningham, Mark D

    2013-01-01

    The ability of capital juries to accurately predict future prison violence at the sentencing phase of aggravated murder trials was examined through retrospective review of the disciplinary records of 115 male inmates sentenced to either life (n = 65) or death (n = 50) in Oregon from 1985 through 2008, with a mean post-conviction time at risk of 15.3 years. Violent prison behavior was completely unrelated to predictions made by capital jurors, with bidirectional accuracy simply reflecting the base rate of assaultive misconduct in the group. Rejection of the special issue predicting future violence enjoyed 90% accuracy. Conversely, predictions that future violence was probable had 90% error rates. More than 90% of the assaultive rule violations committed by these offenders resulted in no harm or only minor injuries. Copyright © 2013 John Wiley & Sons, Ltd.

  20. Typing speed, spelling accuracy, and the use of word-prediction ...

    African Journals Online (AJOL)

    Children with spelling difficulties are limited in their participation in all written school activities. We aimed to investigate the influence of word-prediction as a tool on spelling accuracy and typing speed. To this end, we selected 80 Grade 4 – 6 children with spelling difficulties in a school for special needs to participate

  1. Subjective evaluation of the accuracy of video imaging prediction following orthognathic surgery in Chinese patients

    NARCIS (Netherlands)

    Chew, Ming Tak; Koh, Chay Hui; Sandham, John; Wong, Hwee Bee

    Purpose: The aims of this retrospective study were to assess the subjective accuracy of predictions generated by a computer imaging software in Chinese patients who had undergone orthognathic surgery and to determine the influence of initial dysgnathia and complexity of the surgical procedure on

  2. The contribution of educational class in improving accuracy of cardiovascular risk prediction across European regions

    DEFF Research Database (Denmark)

    Ferrario, Marco M; Veronesi, Giovanni; Chambless, Lloyd E

    2014-01-01

    OBJECTIVE: To assess whether educational class, an index of socioeconomic position, improves the accuracy of the SCORE cardiovascular disease (CVD) risk prediction equation. METHODS: In a pooled analysis of 68 455 40-64-year-old men and women, free from coronary heart disease at baseline, from 47...

  3. Phishtest: Measuring the Impact of Email Headers on the Predictive Accuracy of Machine Learning Techniques

    Science.gov (United States)

    Tout, Hicham

    2013-01-01

    The majority of documented phishing attacks have been carried by email, yet few studies have measured the impact of email headers on the predictive accuracy of machine learning techniques in detecting email phishing attacks. Research has shown that the inclusion of a limited subset of email headers as features in training machine learning…

  4. A fuzzy set approach to assess the predictive accuracy of land use simulations

    NARCIS (Netherlands)

    van Vliet, J.; Hagen-Zanker, A.; Hurkens, J.; van van Delden, H.

    2013-01-01

    The predictive accuracy of land use models is frequently assessed by comparing two data sets: the simulated land use map and the observed land use map at the end of the simulation period. A common statistic for this is Kappa, which expresses the agreement between two categorical maps, corrected for

  5. Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program

    Directory of Open Access Journals (Sweden)

    Elliot L. Heffner

    2011-03-01

    Full Text Available Genomic selection (GS uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotypes of lines from each cross before conducting GS. This will prolong the selection cycle and may result in lower gains per year than approaches that estimate marker-effects with multiple families from previous selection cycles. In this study, phenotypic selection (PS, conventional marker-assisted selection (MAS, and GS prediction accuracy were compared for 13 agronomic traits in a population of 374 winter wheat ( L. advanced-cycle breeding lines. A cross-validation approach that trained and validated prediction accuracy across years was used to evaluate effects of model selection, training population size, and marker density in the presence of genotype × environment interactions (G×E. The average prediction accuracies using GS were 28% greater than with MAS and were 95% as accurate as PS. For net merit, the average accuracy across six selection indices for GS was 14% greater than for PS. These results provide empirical evidence that multifamily GS could increase genetic gain per unit time and cost in plant breeding.

  6. Predictive Validity and Accuracy of Oral Reading Fluency for English Learners

    Science.gov (United States)

    Vanderwood, Michael L.; Tung, Catherine Y.; Checca, C. Jason

    2014-01-01

    The predictive validity and accuracy of an oral reading fluency (ORF) measure for a statewide assessment in English language arts was examined for second-grade native English speakers (NESs) and English learners (ELs) with varying levels of English proficiency. In addition to comparing ELs with native English speakers, the impact of English…

  7. The Diagnostic Accuracy of Clinical and External Pelvimetry in Prediction of Dystocia in Nulliparous Women

    Directory of Open Access Journals (Sweden)

    R Alijahan

    2011-08-01

    Full Text Available Introduction: Clinical pelvimetry is very uncomfortable for the patient and is associated with subjective error, while external pelvimetry is a simple and acceptable method for patients. The objective of this study was to compare the diagnostic accuracy of clinical and external pelvimetry in prediction of dystocia in nulliparous women. Methods: In this study between December 2008 and January 2009, 447 nulliparous women with a single pregnancy in vertex presentation and gestational age 38-42 weeks referring to the Ommolbanin hospital of Mashhad were included. External pelvic dimensions were assessed at the time of admission and clinical pelvimetry was performed by another examiner. These measurements were not available to the clinician in charge of the delivery. Dystocia was defined as caesarean section and vacuum or forceps delivery for abnormal progress of labor ( active uterine contractions, arrest of cervical dilatation or cervical dilatation less than 1 cm /h in the active phase for 2 hours, prolongation of second stage beyond 2 hours or fetal head descent less than 1cm/h. Statistical tests included Fisher exact test and Chi- square test. Results: The highest sensitivity obtained from clinical pelvimetry was 33.3% and related to diagonal conjugate less than 11.5 cm. The sensitivity of external pelvic dimensions was higher than clinical pelvimetry that was highest for the Michaelis transverse diameter(60.72%. Conclusion: External pelvimetry in comparison to clinical pelvimetry is a better method for identifying dystocia in nulliparous women and can replace clinical pelvimetry in antenatal care programs.

  8. Accuracy of genomic breeding value prediction for intramuscular fat using different genomic relationship matrices in Hanwoo (Korean cattle).

    Science.gov (United States)

    Choi, Taejeong; Lim, Dajeong; Park, Byoungho; Sharma, Aditi; Kim, Jong-Joo; Kim, Sidong; Lee, Seung Hwan

    2017-07-01

    Intramuscular fat is one of the meat quality traits that is considered in the selection strategies for Hanwoo (Korean cattle). Different methods are used to estimate the breeding value of selection candidates. In the present work we focused on accuracy of different genotype relationship matrices as described by forni and pedigree based relationship matrix. The data set included a total of 778 animals that were genotyped for BovineSNP50 BeadChip. Among these 778 animals, 72 animals were sires for 706 reference animals and were used as a validation dataset. Single trait animal model (best linear unbiased prediction and genomic best linear unbiased prediction) was used to estimate the breeding values from genomic and pedigree information. The diagonal elements for the pedigree based coefficients were slightly higher for the genomic relationship matrices (GRM) based coefficients while off diagonal elements were considerably low for GRM based coefficients. The accuracy of breeding value for the pedigree based relationship matrix (A) was 13% while for GRM (GOF, G05, and Yang) it was 0.37, 0.45, and 0.38, respectively. Accuracy of GRM was 1.5 times higher than A in this study. Therefore, genomic information will be more beneficial than pedigree information in the Hanwoo breeding program.

  9. The diagnostic accuracy of the rapid dipstick test to predict asymptomatic urinary tract infection of pregnancy.

    Science.gov (United States)

    Eigbefoh, J O; Isabu, P; Okpere, E; Abebe, J

    2008-07-01

    Untreated urinary tract infection can have devastating maternal and neonatal effects. Thus, routine screening for bacteriuria is advocated. This study was designed to evaluate the diagnostic accuracy of the rapid dipstick test to predict urinary tract infection in pregnancy with the gold standard of urine microscopy, culture and sensitivity acting as the control. The urine dipstick test uses the leucocyte esterase, nitrite and test for protein singly and in combination. The result of the dipstick was compared with the gold standard, urine microscopy, culture and sensitivity using confidence interval for proportions. The reliability and validity of the urine dipstick was also evaluated. Overall, the urine dipstick test has a poor correlation with urine culture (p = 0.125, CI 95%). The same holds true for individual components of the dipstick test. The overall sensitivity of the urine dipstick test was poor at 2.3%. Individual sensitivity of the various components varied between 9.1% for leucocyte esterase and the nitrite test to 56.8% for leucocyte esterase alone. The other components of the dipstick test, the test of nitrite, test for protein and combination of the test (leucocyte esterase, nitrite and proteinuria) appear to decrease the sensitivity of the leucocyte esterase test alone. The ability of the urine dipstick test to correctly rule out urinary tract infection (specificity) was high. The positive predictive value for the dipstick test was high, with the leucocyte esterase test having the highest positive predictive value compared with the other components of the dipstick test. The negative predictive value (NPV) was expectedly highest for the leucocyte esterase test alone with values higher than the other components of the urine dipstick test singly and in various combinations. Compared with the other parameters of the urine dipstick test, singly and in combination, leucocyte esterase appears to be the most accurate (90.25%). The dipstick test has a

  10. The Accuracy and Bias of Single-Step Genomic Prediction for Populations Under Selection

    Directory of Open Access Journals (Sweden)

    Wan-Ling Hsu

    2017-08-01

    Full Text Available In single-step analyses, missing genotypes are explicitly or implicitly imputed, and this requires centering the observed genotypes using the means of the unselected founders. If genotypes are only available for selected individuals, centering on the unselected founder mean is not straightforward. Here, computer simulation is used to study an alternative analysis that does not require centering genotypes but fits the mean μg of unselected individuals as a fixed effect. Starting with observed diplotypes from 721 cattle, a five-generation population was simulated with sire selection to produce 40,000 individuals with phenotypes, of which the 1000 sires had genotypes. The next generation of 8000 genotyped individuals was used for validation. Evaluations were undertaken with (J or without (N μg when marker covariates were not centered; and with (JC or without (C μg when all observed and imputed marker covariates were centered. Centering did not influence accuracy of genomic prediction, but fitting μg did. Accuracies were improved when the panel comprised only quantitative trait loci (QTL; models JC and J had accuracies of 99.4%, whereas models C and N had accuracies of 90.2%. When only markers were in the panel, the 4 models had accuracies of 80.4%. In panels that included QTL, fitting μg in the model improved accuracy, but had little impact when the panel contained only markers. In populations undergoing selection, fitting μg in the model is recommended to avoid bias and reduction in prediction accuracy due to selection.

  11. A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts

    Directory of Open Access Journals (Sweden)

    Hossein Hassani

    2015-08-01

    Full Text Available This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS test, referred to as the KS Predictive Accuracy (KSPA test. The KSPA test is able to serve two distinct purposes. Initially, the test seeks to determine whether there exists a statistically significant difference between the distribution of forecast errors, and secondly it exploits the principles of stochastic dominance to determine whether the forecasts with the lower error also reports a stochastically smaller error than forecasts from a competing model, and thereby enables distinguishing between the predictive accuracy of forecasts. We perform a simulation study for the size and power of the proposed test and report the results for different noise distributions, sample sizes and forecasting horizons. The simulation results indicate that the KSPA test is correctly sized, and robust in the face of varying forecasting horizons and sample sizes along with significant accuracy gains reported especially in the case of small sample sizes. Real world applications are also considered to illustrate the applicability of the proposed KSPA test in practice.

  12. Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis.

    Science.gov (United States)

    Linden, Ariel

    2006-04-01

    Diagnostic or predictive accuracy concerns are common in all phases of a disease management (DM) programme, and ultimately play an influential role in the assessment of programme effectiveness. Areas, such as the identification of diseased patients, predictive modelling of future health status and costs and risk stratification, are just a few of the domains in which assessment of accuracy is beneficial, if not critical. The most commonly used analytical model for this purpose is the standard 2 x 2 table method in which sensitivity and specificity are calculated. However, there are several limitations to this approach, including the reliance on a single defined criterion or cut-off for determining a true-positive result, use of non-standardized measurement instruments and sensitivity to outcome prevalence. This paper introduces the receiver operator characteristic (ROC) analysis as a more appropriate and useful technique for assessing diagnostic and predictive accuracy in DM. Its advantages include; testing accuracy across the entire range of scores and thereby not requiring a predetermined cut-off point, easily examined visual and statistical comparisons across tests or scores, and independence from outcome prevalence. Therefore the implementation of ROC as an evaluation tool should be strongly considered in the various phases of a DM programme.

  13. Accuracy of Genomic Prediction in Switchgrass (Panicum virgatum L. Improved by Accounting for Linkage Disequilibrium

    Directory of Open Access Journals (Sweden)

    Guillaume P. Ramstein

    2016-04-01

    Full Text Available Switchgrass is a relatively high-yielding and environmentally sustainable biomass crop, but further genetic gains in biomass yield must be achieved to make it an economically viable bioenergy feedstock. Genomic selection (GS is an attractive technology to generate rapid genetic gains in switchgrass, and meet the goals of a substantial displacement of petroleum use with biofuels in the near future. In this study, we empirically assessed prediction procedures for genomic selection in two different populations, consisting of 137 and 110 half-sib families of switchgrass, tested in two locations in the United States for three agronomic traits: dry matter yield, plant height, and heading date. Marker data were produced for the families’ parents by exome capture sequencing, generating up to 141,030 polymorphic markers with available genomic-location and annotation information. We evaluated prediction procedures that varied not only by learning schemes and prediction models, but also by the way the data were preprocessed to account for redundancy in marker information. More complex genomic prediction procedures were generally not significantly more accurate than the simplest procedure, likely due to limited population sizes. Nevertheless, a highly significant gain in prediction accuracy was achieved by transforming the marker data through a marker correlation matrix. Our results suggest that marker-data transformations and, more generally, the account of linkage disequilibrium among markers, offer valuable opportunities for improving prediction procedures in GS. Some of the achieved prediction accuracies should motivate implementation of GS in switchgrass breeding programs.

  14. Capability Database of Injection Molding Process— Requirements Study for Wider Suitability and Higher Accuracy

    DEFF Research Database (Denmark)

    Boorla, Srinivasa Murthy; Eifler, Tobias; Jepsen, Jens Dines O.

    2017-01-01

    for an improved applicability of corresponding database solutions in an industrial context. A survey of database users at all phases of product value chain in the plastic industry revealed that 59% of the participating companies use their own, internally created databases, although reported to be not fully...... adequate in most cases. Essential influences are the suitability of the provided data, defined by the content such as material, tolerance types, etc. covered, as well as its accuracy, largely influenced by the updating frequency. Forming a consortium with stakeholders, linking database update to technology...

  15. Quantifying and estimating the predictive accuracy for censored time-to-event data with competing risks.

    Science.gov (United States)

    Wu, Cai; Li, Liang

    2018-05-15

    This paper focuses on quantifying and estimating the predictive accuracy of prognostic models for time-to-event outcomes with competing events. We consider the time-dependent discrimination and calibration metrics, including the receiver operating characteristics curve and the Brier score, in the context of competing risks. To address censoring, we propose a unified nonparametric estimation framework for both discrimination and calibration measures, by weighting the censored subjects with the conditional probability of the event of interest given the observed data. The proposed method can be extended to time-dependent predictive accuracy metrics constructed from a general class of loss functions. We apply the methodology to a data set from the African American Study of Kidney Disease and Hypertension to evaluate the predictive accuracy of a prognostic risk score in predicting end-stage renal disease, accounting for the competing risk of pre-end-stage renal disease death, and evaluate its numerical performance in extensive simulation studies. Copyright © 2018 John Wiley & Sons, Ltd.

  16. The accuracy with which adults who do not stutter predict stuttering-related communication attitudes.

    Science.gov (United States)

    Logan, Kenneth J; Willis, Julie R

    2011-12-01

    The purpose of this study was to examine the extent to which adults who do not stutter can predict communication-related attitudes of adults who do stutter. 40 participants (mean age of 22.5 years) evaluated speech samples from an adult with mild stuttering and an adult with severe stuttering via audio-only (n=20) or audio-visual (n=20) modes to predict how the adults had responded on the S24 scale of communication attitudes. Participants correctly predicted which speaker had the more favorable S24 score, and the predicted scores were significantly different between the severity conditions. Across the four subgroups, predicted S24 scores differed from actual scores by 4-9 points. Predicted values were greater than the actual values for 3 of 4 subgroups, but still relatively positive in relation to the S24 norm sample. Stimulus presentation mode interacted with stuttering severity to affect prediction accuracy. The participants predicted the speakers' negative self-attributions more accurately than their positive self-attributions. Findings suggest that adults who do not stutter estimate the communication-related attitudes of specific adults who stutter in a manner that is generally accurate, though, in some conditions, somewhat less favorable than the speaker's actual ratings. At a group level, adults who do not stutter demonstrate the ability to discern minimal versus average levels of attitudinal impact for speakers who stutter. The participants' complex prediction patterns are discussed in relation to stereotype accuracy and classic views of negative stereotyping. The reader will be able to (a) summarize main findings on research related to listeners' attitudes toward people who stutter, (b) describe the extent to which people who do not stutter can predict the communication attitudes of people who do stutter; and (c) discuss how findings from the present study relate to previous findings on stereotypes about people who stutter. Copyright © 2011 Elsevier Inc

  17. Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

    Science.gov (United States)

    Ko, P.; Kurosawa, S.

    2014-03-01

    The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.

  18. Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

    Science.gov (United States)

    Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

    2017-01-01

    Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

  19. Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

    International Nuclear Information System (INIS)

    Ko, P; Kurosawa, S

    2014-01-01

    The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine

  20. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.; Motwalli, Olaa Amin; Oliva, Romina; Jankovic, Boris R.; Medvedeva, Yulia; Ashoor, Haitham; Essack, Magbubah; Gao, Xin; Bajic, Vladimir B.

    2018-01-01

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  1. Combined Scintigraphy and Tumor Marker Analysis Predicts Unfavorable Histopathology of Neuroblastic Tumors with High Accuracy.

    Directory of Open Access Journals (Sweden)

    Wolfgang Peter Fendler

    Full Text Available Our aim was to improve the prediction of unfavorable histopathology (UH in neuroblastic tumors through combined imaging and biochemical parameters.123I-MIBG SPECT and MRI was performed before surgical resection or biopsy in 47 consecutive pediatric patients with neuroblastic tumor. Semi-quantitative tumor-to-liver count-rate ratio (TLCRR, MRI tumor size and margins, urine catecholamine and NSE blood levels of neuron specific enolase (NSE were recorded. Accuracy of single and combined variables for prediction of UH was tested by ROC analysis with Bonferroni correction.34 of 47 patients had UH based on the International Neuroblastoma Pathology Classification (INPC. TLCRR and serum NSE both predicted UH with moderate accuracy. Optimal cut-off for TLCRR was 2.0, resulting in 68% sensitivity and 100% specificity (AUC-ROC 0.86, p < 0.001. Optimal cut-off for NSE was 25.8 ng/ml, resulting in 74% sensitivity and 85% specificity (AUC-ROC 0.81, p = 0.001. Combination of TLCRR/NSE criteria reduced false negative findings from 11/9 to only five, with improved sensitivity and specificity of 85% (AUC-ROC 0.85, p < 0.001.Strong 123I-MIBG uptake and high serum level of NSE were each predictive of UH. Combined analysis of both parameters improved the prediction of UH in patients with neuroblastic tumor. MRI parameters and urine catecholamine levels did not predict UH.

  2. A novel method for improved accuracy of transcription factor binding site prediction

    KAUST Repository

    Khamis, Abdullah M.

    2018-03-20

    Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

  3. Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

    Directory of Open Access Journals (Sweden)

    Leonardo de Azevedo Peixoto

    Full Text Available Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY and the weight of 100 seeds (W100S using restricted maximum likelihood (REML; to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

  4. Both Reaction Time and Accuracy Measures of Intraindividual Variability Predict Cognitive Performance in Alzheimer's Disease

    Directory of Open Access Journals (Sweden)

    Björn U. Christ

    2018-04-01

    Full Text Available Dementia researchers around the world prioritize the urgent need for sensitive measurement tools that can detect cognitive and functional change at the earliest stages of Alzheimer's disease (AD. Sensitive indicators of underlying neural pathology assist in the early detection of cognitive change and are thus important for the evaluation of early-intervention clinical trials. One method that may be particularly well-suited to help achieve this goal involves the quantification of intraindividual variability (IIV in cognitive performance. The current study aimed to directly compare two methods of estimating IIV (fluctuations in accuracy-based scores vs. those in latency-based scores to predict cognitive performance in AD. Specifically, we directly compared the relative sensitivity of reaction time (RT—and accuracy-based estimates of IIV to cognitive compromise. The novelty of the present study, however, centered on the patients we tested [a group of patients with Alzheimer's disease (AD] and the outcome measures we used (a measure of general cognitive function and a measure of episodic memory function. Hence, we compared intraindividual standard deviations (iSDs from two RT tasks and three accuracy-based memory tasks in patients with possible or probable Alzheimer's dementia (n = 23 and matched healthy controls (n = 25. The main analyses modeled the relative contributions of RT vs. accuracy-based measures of IIV toward the prediction of performance on measures of (a overall cognitive functioning, and (b episodic memory functioning. Results indicated that RT-based IIV measures are superior predictors of neurocognitive impairment (as indexed by overall cognitive and memory performance than accuracy-based IIV measures, even after adjusting for the timescale of measurement. However, one accuracy-based IIV measure (derived from a recognition memory test also differentiated patients with AD from controls, and significantly predicted episodic memory

  5. Prediction of renal function (GFR) from cystatin C and creatinine in children: Body cell mass increases accuracy of the estimate

    DEFF Research Database (Denmark)

    Andersen, Trine Borup; Jødal, Lars; Bøgsted, Martin

    ) aged 2-14 years (mean 8.8 years). GFR was 14-147 mL/min/1.73m2 (mean 97 mL/min/1.73m2). BCM was estimated using bioimpedance spectroscopy (Xitron Hydra 4200). Log-transformed data on BCM/CysC, serum creatinine (SCr), body-surface-area (BSA), height x BSA/SCr, serum CysC, weight, sex, age, height, serum....... The present equation also had the highest R2 and the narrowest 95% limits of agreement. CONCLUSION: The new equation predicts GFR with higher accuracy than other equations. Endogenous methods are, however, still not accurate enough to replace exogenous markers when GFR must be determined with high accuracy...

  6. GFR prediction from cystatin C and creatinine in children: body cell mass increases accuracy of the estimate

    DEFF Research Database (Denmark)

    Andersen, Trine Borup; Jødal, Lars; Bøgsted, Martin

    ) aged 2-14 years (mean 8.8 years). GFR was 14-147 mL/min/1.73m2 (mean 97 mL/min/1.73m2). BCM was estimated using bioimpedance spectroscopy (Xitron Hydra 4200). Log-transformed data on BCM/CysC, serum creatinine (SCr), body-surface-area (BSA), height x BSA/SCr, serum CysC, weight, sex, age, height, serum....... The present equation also had the highest R2 and the narrowest 95% limits of agreement. CONCLUSION: The new equation predicts GFR with higher accuracy than other equations. Endogenous methods are, however, still not accurate enough to replace exogenous markers when GFR must be determined with high accuracy...

  7. Improving the accuracy of the structure prediction of the third hypervariable loop of the heavy chains of antibodies.

    KAUST Repository

    Messih, Mario Abdel; Lepore, Rosalba; Marcatili, Paolo; Tramontano, Anna

    2014-01-01

    MOTIVATION: Antibodies are able to recognize a wide range of antigens through their complementary determining regions formed by six hypervariable loops. Predicting the 3D structure of these loops is essential for the analysis and reengineering of novel antibodies with enhanced affinity and specificity. The canonical structure model allows high accuracy prediction for five of the loops. The third loop of the heavy chain, H3, is the hardest to predict because of its diversity in structure, length and sequence composition. RESULTS: We describe a method, based on the Random Forest automatic learning technique, to select structural templates for H3 loops among a dataset of candidates. These can be used to predict the structure of the loop with a higher accuracy than that achieved by any of the presently available methods. The method also has the advantage of being extremely fast and returning a reliable estimate of the model quality. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at http://www.biocomputing.it/H3Loopred/ .

  8. Improving the accuracy of the structure prediction of the third hypervariable loop of the heavy chains of antibodies.

    KAUST Repository

    Messih, Mario Abdel

    2014-06-13

    MOTIVATION: Antibodies are able to recognize a wide range of antigens through their complementary determining regions formed by six hypervariable loops. Predicting the 3D structure of these loops is essential for the analysis and reengineering of novel antibodies with enhanced affinity and specificity. The canonical structure model allows high accuracy prediction for five of the loops. The third loop of the heavy chain, H3, is the hardest to predict because of its diversity in structure, length and sequence composition. RESULTS: We describe a method, based on the Random Forest automatic learning technique, to select structural templates for H3 loops among a dataset of candidates. These can be used to predict the structure of the loop with a higher accuracy than that achieved by any of the presently available methods. The method also has the advantage of being extremely fast and returning a reliable estimate of the model quality. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at http://www.biocomputing.it/H3Loopred/ .

  9. Lessons learned from accuracy assessment of IAEA-SPE-4 experiment predictions

    International Nuclear Information System (INIS)

    Prosek, A.

    2002-01-01

    The use of methods for code accuracy assessment has strongly increased in the last years. The methods suitable to provide quantitative comparison between the thermalhydraulic code predictions and experimental measurements were proposed e.g. fast Fourier transform based method (FFTBM), stochastic approximation ratio based method (SARBM) and a few methods used in the frame of the recently developed automated code assessment program (ACAP). Further, in the frame of FFTBM also a procedure to quantify the whole calculation was proposed with averaging of the results. The problem is that averaging may hide discrepancies highlighted in the qualitative analysis when only quantitative results are published. The purpose of the study was therefore to propose additional accuracy measures. New proposed measures were tested with IAEA-SPE-4 pre- and post-test predictions. The obtained results showed that the proposed measures improve the whole picture of the code accuracy. This is important when the reader is not provided with the accompanied qualitative analysis. The study shows that proposed accuracy measures efficiently increase the confidence in the quantitative results.(author)

  10. Test accuracy of metabolic indicators in predicting decreased fertility in dairy cows

    DEFF Research Database (Denmark)

    Lomander, H; Gustafsson, H; Svensson, C

    2012-01-01

    Negative energy balance is a known risk factor for decreased fertility in dairy cows. This study evaluated the accuracy of plasma concentrations of nonesterified fatty acids (NEFA), β-hydroxybutyrate (BHBA), and insulin-like growth factor 1 (IGF-1)—factors related to negative energy balance...... was low when metabolic indicators measured as single values in early lactation were used to predict fertility in dairy cows, but accuracy was influenced by cow-level factors such as parity. The prevalence of the target condition (in this case, decreased fertility) also influences test usefulness......—in predicting decreased fertility. One plasma sample per cow was collected from 480 cows in 12 herds during the period from d 4 to 21 in milk and analyzed for NEFA, BHBA, and IGF-1. For each cow, data on breed, parity, calving date, gynecological examinations, and insemination dates were obtained. Milk samples...

  11. Accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients.

    Science.gov (United States)

    Martinez, Bruno Prata; Gomes, Isabela Barboza; Oliveira, Carolina Santana de; Ramos, Isis Resende; Rocha, Mônica Diniz Marques; Forgiarini Júnior, Luiz Alberto; Camelier, Fernanda Warken Rosa; Camelier, Aquiles Assunção

    2015-05-01

    The ability of the Timed Up and Go test to predict sarcopenia has not been evaluated previously. The objective of this study was to evaluate the accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients. This cross-sectional study analyzed 68 elderly patients (≥60 years of age) in a private hospital in the city of Salvador-BA, Brazil, between the 1st and 5th day of hospitalization. The predictive variable was the Timed Up and Go test score, and the outcome of interest was the presence of sarcopenia (reduced muscle mass associated with a reduction in handgrip strength and/or weak physical performance in a 6-m gait-speed test). After the descriptive data analyses, the sensitivity, specificity and accuracy of a test using the predictive variable to predict the presence of sarcopenia were calculated. In total, 68 elderly individuals, with a mean age 70.4±7.7 years, were evaluated. The subjects had a Charlson Comorbidity Index score of 5.35±1.97. Most (64.7%) of the subjects had a clinical admission profile; the main reasons for hospitalization were cardiovascular disorders (22.1%), pneumonia (19.1%) and abdominal disorders (10.2%). The frequency of sarcopenia in the sample was 22.1%, and the mean length of time spent performing the Timed Up and Go test was 10.02±5.38 s. A time longer than or equal to a cutoff of 10.85 s on the Timed Up and Go test predicted sarcopenia with a sensitivity of 67% and a specificity of 88.7%. The accuracy of this cutoff for the Timed Up and Go test was good (0.80; IC=0.66-0.94; p=0.002). The Timed Up and Go test was shown to be a predictor of sarcopenia in elderly hospitalized patients.

  12. Measuring Personality in Context: Improving Predictive Accuracy in Selection Decision Making

    OpenAIRE

    Hoffner, Rebecca Ann

    2009-01-01

    This study examines the accuracy of a context-sensitive (i.e., goal dimensions) measure of personality compared to a traditional measure of personality (NEO-PI-R) and generalized self-efficacy (GSE) to predict variance in task performance. The goal dimensions measure takes a unique perspective in the conceptualization of personality. While traditional measures differentiate within person and collapse across context (e.g., Big Five), the goal dimensions measure employs a hierarchical structure...

  13. High accuracy prediction of beta-turns and their types using propensities and multiple alignments.

    Science.gov (United States)

    Fuchs, Patrick F J; Alix, Alain J P

    2005-06-01

    We have developed a method that predicts both the presence and the type of beta-turns, using a straightforward approach based on propensities and multiple alignments. The propensities were calculated classically, but the way to use them for prediction was completely new: starting from a tetrapeptide sequence on which one wants to evaluate the presence of a beta-turn, the propensity for a given residue is modified by taking into account all the residues present in the multiple alignment at this position. The evaluation of a score is then done by weighting these propensities by the use of Position-specific score matrices generated by PSI-BLAST. The introduction of secondary structure information predicted by PSIPRED or SSPRO2 as well as taking into account the flanking residues around the tetrapeptide improved the accuracy greatly. This latter evaluated on a database of 426 reference proteins (previously used on other studies) by a sevenfold crossvalidation gave very good results with a Matthews Correlation Coefficient (MCC) of 0.42 and an overall prediction accuracy of 74.8%; this places our method among the best ones. A jackknife test was also done, which gave results within the same range. This shows that it is possible to reach neural networks accuracy with considerably less computional cost and complexity. Furthermore, propensities remain excellent descriptors of amino acid tendencies to belong to beta-turns, which can be useful for peptide or protein engineering and design. For beta-turn type prediction, we reached the best accuracy ever published in terms of MCC (except for the irregular type IV) in the range of 0.25-0.30 for types I, II, and I' and 0.13-0.15 for types VIII, II', and IV. To our knowledge, our method is the only one available on the Web that predicts types I' and II'. The accuracy evaluated on two larger databases of 547 and 823 proteins was not improved significantly. All of this was implemented into a Web server called COUDES (French acronym

  14. Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Herng-Chia Chiu

    2013-01-01

    Full Text Available The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC patients undergoing resection between artificial neural network (ANN and logistic regression (LR models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. We constructed a prognostic model for 434 patients with 21 potential input variables by Cox regression model. Model performance was measured by numbers of significant predictors and predictive accuracy. The results indicated that ANN had double to triple numbers of significant predictors at 1-, 3-, and 5-year survival models as compared with LR models. Scores of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC of 1-, 3-, and 5-year survival estimation models using ANN were superior to those of LR in all the training sets and most of the validation sets. The study demonstrated that ANN not only had a great number of predictors of mortality variables but also provided accurate prediction, as compared with conventional methods. It is suggested that physicians consider using data mining methods as supplemental tools for clinical decision-making and prognostic evaluation.

  15. Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network

    Science.gov (United States)

    Chiu, Herng-Chia; Ho, Te-Wei; Lee, King-Teh; Chen, Hong-Yaw; Ho, Wen-Hsien

    2013-01-01

    The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC) patients undergoing resection between artificial neural network (ANN) and logistic regression (LR) models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. We constructed a prognostic model for 434 patients with 21 potential input variables by Cox regression model. Model performance was measured by numbers of significant predictors and predictive accuracy. The results indicated that ANN had double to triple numbers of significant predictors at 1-, 3-, and 5-year survival models as compared with LR models. Scores of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of 1-, 3-, and 5-year survival estimation models using ANN were superior to those of LR in all the training sets and most of the validation sets. The study demonstrated that ANN not only had a great number of predictors of mortality variables but also provided accurate prediction, as compared with conventional methods. It is suggested that physicians consider using data mining methods as supplemental tools for clinical decision-making and prognostic evaluation. PMID:23737707

  16. Persistency of Prediction Accuracy and Genetic Gain in Synthetic Populations Under Recurrent Genomic Selection.

    Science.gov (United States)

    Müller, Dominik; Schopp, Pascal; Melchinger, Albrecht E

    2017-03-10

    Recurrent selection (RS) has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents [Formula: see text] but little is known about how [Formula: see text] affects genomic selection (GS) in RS, especially the persistency of prediction accuracy ([Formula: see text]) and genetic gain. Synthetics were simulated by intermating [Formula: see text]= 2-32 parent lines from an ancestral population with short- or long-range linkage disequilibrium ([Formula: see text]) and subjected to multiple cycles of GS. We determined [Formula: see text] and genetic gain across 30 cycles for different training set ( TS ) sizes, marker densities, and generations of recombination before model training. Contributions to [Formula: see text] and genetic gain from pedigree relationships, as well as from cosegregation and [Formula: see text] between QTL and markers, were analyzed via four scenarios differing in (i) the relatedness between TS and selection candidates and (ii) whether selection was based on markers or pedigree records. Persistency of [Formula: see text] was high for small [Formula: see text] where predominantly cosegregation contributed to [Formula: see text], but also for large [Formula: see text] where [Formula: see text] replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing [Formula: see text] > 4, given long-range LD A in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to [Formula: see text] for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size ([Formula: see text]) and higher marker density improved persistency of

  17. Persistency of Prediction Accuracy and Genetic Gain in Synthetic Populations Under Recurrent Genomic Selection

    Directory of Open Access Journals (Sweden)

    Dominik Müller

    2017-03-01

    Full Text Available Recurrent selection (RS has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents ( Np , but little is known about how Np affects genomic selection (GS in RS, especially the persistency of prediction accuracy (rg , g ^ and genetic gain. Synthetics were simulated by intermating Np= 2–32 parent lines from an ancestral population with short- or long-range linkage disequilibrium (LDA and subjected to multiple cycles of GS. We determined rg , g ^ and genetic gain across 30 cycles for different training set (TS sizes, marker densities, and generations of recombination before model training. Contributions to rg , g ^ and genetic gain from pedigree relationships, as well as from cosegregation and LDA between QTL and markers, were analyzed via four scenarios differing in (i the relatedness between TS and selection candidates and (ii whether selection was based on markers or pedigree records. Persistency of rg , g ^ was high for small Np , where predominantly cosegregation contributed to rg , g ^ , but also for large Np , where LDA replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing Np > 4, given long-range LDA in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to rg , g ^ for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size (NTS and higher marker density improved persistency of rg , g ^ and hence genetic gain, but additional recombinations could not increase genetic gain.

  18. Models of alien species richness show moderate predictive accuracy and poor transferability

    Directory of Open Access Journals (Sweden)

    César Capinha

    2018-06-01

    Full Text Available Robust predictions of alien species richness are useful to assess global biodiversity change. Nevertheless, the capacity to predict spatial patterns of alien species richness remains largely unassessed. Using 22 data sets of alien species richness from diverse taxonomic groups and covering various parts of the world, we evaluated whether different statistical models were able to provide useful predictions of absolute and relative alien species richness, as a function of explanatory variables representing geographical, environmental and socio-economic factors. Five state-of-the-art count data modelling techniques were used and compared: Poisson and negative binomial generalised linear models (GLMs, multivariate adaptive regression splines (MARS, random forests (RF and boosted regression trees (BRT. We found that predictions of absolute alien species richness had a low to moderate accuracy in the region where the models were developed and a consistently poor accuracy in new regions. Predictions of relative richness performed in a superior manner in both geographical settings, but still were not good. Flexible tree ensembles-type techniques (RF and BRT were shown to be significantly better in modelling alien species richness than parametric linear models (such as GLM, despite the latter being more commonly applied for this purpose. Importantly, the poor spatial transferability of models also warrants caution in assuming the generality of the relationships they identify, e.g. by applying projections under future scenario conditions. Ultimately, our results strongly suggest that predictability of spatial variation in richness of alien species richness is limited. The somewhat more robust ability to rank regions according to the number of aliens they have (i.e. relative richness, suggests that models of aliens species richness may be useful for prioritising and comparing regions, but not for predicting exact species numbers.

  19. Comparing the accuracy of perturbative and variational calculations for predicting fundamental vibrational frequencies of dihalomethanes

    Science.gov (United States)

    Krasnoshchekov, Sergey V.; Schutski, Roman S.; Craig, Norman C.; Sibaev, Marat; Crittenden, Deborah L.

    2018-02-01

    Three dihalogenated methane derivatives (CH2F2, CH2FCl, and CH2Cl2) were used as model systems to compare and assess the accuracy of two different approaches for predicting observed fundamental frequencies: canonical operator Van Vleck vibrational perturbation theory (CVPT) and vibrational configuration interaction (VCI). For convenience and consistency, both methods employ the Watson Hamiltonian in rectilinear normal coordinates, expanding the potential energy surface (PES) as a Taylor series about equilibrium and constructing the wavefunction from a harmonic oscillator product basis. At the highest levels of theory considered here, fourth-order CVPT and VCI in a harmonic oscillator basis with up to 10 quanta of vibrational excitation in conjunction with a 4-mode representation sextic force field (SFF-4MR) computed at MP2/cc-pVTZ with replacement CCSD(T)/aug-cc-pVQZ harmonic force constants, the agreement between computed fundamentals is closer to 0.3 cm-1 on average, with a maximum difference of 1.7 cm-1. The major remaining accuracy-limiting factors are the accuracy of the underlying electronic structure model, followed by the incompleteness of the PES expansion. Nonetheless, computed and experimental fundamentals agree to within 5 cm-1, with an average difference of 2 cm-1, confirming the utility and accuracy of both theoretical models. One exception to this rule is the formally IR-inactive but weakly allowed through Coriolis-coupling H-C-H out-of-plane twisting mode of dichloromethane, whose spectrum we therefore revisit and reassign. We also investigate convergence with respect to order of CVPT, VCI excitation level, and order of PES expansion, concluding that premature truncation substantially decreases accuracy, although VCI(6)/SFF-4MR results are still of acceptable accuracy, and some error cancellation is observed with CVPT2 using a quartic force field.

  20. Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.).

    Science.gov (United States)

    Cros, David; Denis, Marie; Sánchez, Leopoldo; Cochard, Benoit; Flori, Albert; Durand-Gasselin, Tristan; Nouy, Bruno; Omoré, Alphonse; Pomiès, Virginie; Riou, Virginie; Suryana, Edyana; Bouvet, Jean-Marc

    2015-03-01

    Genomic selection empirically appeared valuable for reciprocal recurrent selection in oil palm as it could account for family effects and Mendelian sampling terms, despite small populations and low marker density. Genomic selection (GS) can increase the genetic gain in plants. In perennial crops, this is expected mainly through shortened breeding cycles and increased selection intensity, which requires sufficient GS accuracy in selection candidates, despite often small training populations. Our objective was to obtain the first empirical estimate of GS accuracy in oil palm (Elaeis guineensis), the major world oil crop. We used two parental populations involved in conventional reciprocal recurrent selection (Deli and Group B) with 131 individuals each, genotyped with 265 SSR. We estimated within-population GS accuracies when predicting breeding values of non-progeny-tested individuals for eight yield traits. We used three methods to sample training sets and five statistical methods to estimate genomic breeding values. The results showed that GS could account for family effects and Mendelian sampling terms in Group B but only for family effects in Deli. Presumably, this difference between populations originated from their contrasting breeding history. The GS accuracy ranged from -0.41 to 0.94 and was positively correlated with the relationship between training and test sets. Training sets optimized with the so-called CDmean criterion gave the highest accuracies, ranging from 0.49 (pulp to fruit ratio in Group B) to 0.94 (fruit weight in Group B). The statistical methods did not affect the accuracy. Finally, Group B could be preselected for progeny tests by applying GS to key yield traits, therefore increasing the selection intensity. Our results should be valuable for breeding programs with small populations, long breeding cycles, or reduced effective size.

  1. Pigeons exhibit higher accuracy for chosen memory tests than for forced memory tests in duration matching-to-sample.

    Science.gov (United States)

    Adams, Allison; Santi, Angelo

    2011-03-01

    Following training to match 2- and 8-sec durations of feederlight to red and green comparisons with a 0-sec baseline delay, pigeons were allowed to choose to take a memory test or to escape the memory test. The effects of sample omission, increases in retention interval, and variation in trial spacing on selection of the escape option and accuracy were studied. During initial testing, escaping the test did not increase as the task became more difficult, and there was no difference in accuracy between chosen and forced memory tests. However, with extended training, accuracy for chosen tests was significantly greater than for forced tests. In addition, two pigeons exhibited higher accuracy on chosen tests than on forced tests at the short retention interval and greater escape rates at the long retention interval. These results have not been obtained in previous studies with pigeons when the choice to take the test or to escape the test is given before test stimuli are presented. It appears that task-specific methodological factors may determine whether a particular species will exhibit the two behavioral effects that were initially proposed as potentially indicative of metacognition.

  2. Geopositioning with a quadcopter: Extracted feature locations and predicted accuracy without a priori sensor attitude information

    Science.gov (United States)

    Dolloff, John; Hottel, Bryant; Edwards, David; Theiss, Henry; Braun, Aaron

    2017-05-01

    This paper presents an overview of the Full Motion Video-Geopositioning Test Bed (FMV-GTB) developed to investigate algorithm performance and issues related to the registration of motion imagery and subsequent extraction of feature locations along with predicted accuracy. A case study is included corresponding to a video taken from a quadcopter. Registration of the corresponding video frames is performed without the benefit of a priori sensor attitude (pointing) information. In particular, tie points are automatically measured between adjacent frames using standard optical flow matching techniques from computer vision, an a priori estimate of sensor attitude is then computed based on supplied GPS sensor positions contained in the video metadata and a photogrammetric/search-based structure from motion algorithm, and then a Weighted Least Squares adjustment of all a priori metadata across the frames is performed. Extraction of absolute 3D feature locations, including their predicted accuracy based on the principles of rigorous error propagation, is then performed using a subset of the registered frames. Results are compared to known locations (check points) over a test site. Throughout this entire process, no external control information (e.g. surveyed points) is used other than for evaluation of solution errors and corresponding accuracy.

  3. Prediction of parturition in dogs and cats: accuracy at different gestational ages.

    Science.gov (United States)

    Beccaglia, M; Luvoni, G C

    2012-12-01

    In bitches and queens, the ultrasonographic measurement of extrafoetal and foetal structures allows the evaluation of gestational age and the prediction of the parturition term for an extended period of time. The aim of this study was to investigate whether the accuracy of parturition date prediction is affected by the week of pregnancy when the ultrasonographic examination is performed. The results were obtained by retrospective analysis on the gestational period basis (from week 4 to week 9 of pregnancy) in 495 ultrasonographic examinations of pregnant bitches (small and medium size) and 60 of pregnant queens. They demonstrated that a similar accuracy (p > 0.05) was obtained by the measurement of inner chorionic cavity at week 4 and 5 of pregnancy (± 1 day, 81% vs 67.7%; ± 2 days, 93.1% vs 85.9%). Accuracy (± 1 day) based on biparietal (BP) measurement was similar at week 5 and 6 of pregnancy (78.6% vs 78.9%; p > 0.05), whereas a significant decrease (p parturition term is highly consistent for 6 and 8 weeks of gestation, respectively. © 2012 Blackwell Verlag GmbH.

  4. Continuous electroencephalography predicts delayed cerebral ischemia after subarachnoid hemorrhage: A prospective study of diagnostic accuracy.

    Science.gov (United States)

    Rosenthal, Eric S; Biswal, Siddharth; Zafar, Sahar F; O'Connor, Kathryn L; Bechek, Sophia; Shenoy, Apeksha V; Boyle, Emily J; Shafi, Mouhsin M; Gilmore, Emily J; Foreman, Brandon P; Gaspard, Nicolas; Leslie-Mazwi, Thabele M; Rosand, Jonathan; Hoch, Daniel B; Ayata, Cenk; Cash, Sydney S; Cole, Andrew J; Patel, Aman B; Westover, M Brandon

    2018-04-16

    Delayed cerebral ischemia (DCI) is a common, disabling complication of subarachnoid hemorrhage (SAH). Preventing DCI is a key focus of neurocritical care, but interventions carry risk and cannot be applied indiscriminately. Although retrospective studies have identified continuous electroencephalographic (cEEG) measures associated with DCI, no study has characterized the accuracy of cEEG with sufficient rigor to justify using it to triage patients to interventions or clinical trials. We therefore prospectively assessed the accuracy of cEEG for predicting DCI, following the Standards for Reporting Diagnostic Accuracy Studies. We prospectively performed cEEG in nontraumatic, high-grade SAH patients at a single institution. The index test consisted of clinical neurophysiologists prospectively reporting prespecified EEG alarms: (1) decreasing relative alpha variability, (2) decreasing alpha-delta ratio, (3) worsening focal slowing, or (4) late appearing epileptiform abnormalities. The diagnostic reference standard was DCI determined by blinded, adjudicated review. Primary outcome measures were sensitivity and specificity of cEEG for subsequent DCI, determined by multistate survival analysis, adjusted for baseline risk. One hundred three of 227 consecutive patients were eligible and underwent cEEG monitoring (7.7-day mean duration). EEG alarms occurred in 96.2% of patients with and 19.6% without subsequent DCI (1.9-day median latency, interquartile range = 0.9-4.1). Among alarm subtypes, late onset epileptiform abnormalities had the highest predictive value. Prespecified EEG findings predicted DCI among patients with low (91% sensitivity, 83% specificity) and high (95% sensitivity, 77% specificity) baseline risk. cEEG accurately predicts DCI following SAH and may help target therapies to patients at highest risk of secondary brain injury. Ann Neurol 2018. © 2018 American Neurological Association.

  5. The paradox of verbal autopsy in cause of death assignment: symptom question unreliability but predictive accuracy.

    Science.gov (United States)

    Serina, Peter; Riley, Ian; Hernandez, Bernardo; Flaxman, Abraham D; Praveen, Devarsetty; Tallo, Veronica; Joshi, Rohina; Sanvictores, Diozele; Stewart, Andrea; Mooney, Meghan D; Murray, Christopher J L; Lopez, Alan D

    2016-01-01

    We believe that it is important that governments understand the reliability of the mortality data which they have at their disposable to guide policy debates. In many instances, verbal autopsy (VA) will be the only source of mortality data for populations, yet little is known about how the accuracy of VA diagnoses is affected by the reliability of the symptom responses. We previously described the effect of the duration of time between death and VA administration on VA validity. In this paper, using the same dataset, we assess the relationship between the reliability and completeness of symptom responses and the reliability and accuracy of cause of death (COD) prediction. The study was based on VAs in the Population Health Metrics Research Consortium (PHMRC) VA Validation Dataset from study sites in Bohol and Manila, Philippines and Andhra Pradesh, India. The initial interview was repeated within 3-52 months of death. Question responses were assessed for reliability and completeness between the two survey rounds. COD was predicted by Tariff Method. A sample of 4226 VAs was collected for 2113 decedents, including 1394 adults, 349 children, and 370 neonates. Mean question reliability was unexpectedly low ( kappa  = 0.447): 42.5 % of responses positive at the first interview were negative at the second, and 47.9 % of responses positive at the second had been negative at the first. Question reliability was greater for the short form of the PHMRC instrument ( kappa  = 0.497) and when analyzed at the level of the individual decedent ( kappa  = 0.610). Reliability at the level of the individual decedent was associated with COD predictive reliability and predictive accuracy. Families give coherent accounts of events leading to death but the details vary from interview to interview for the same case. Accounts are accurate but inconsistent; different subsets of symptoms are identified on each occasion. However, there are sufficient accurate and consistent

  6. Accuracy of some simple models for predicting particulate interception and retention in agricultural systems

    International Nuclear Information System (INIS)

    Pinder, J.E. III; McLeod, K.W.; Adriano, D.C.

    1989-01-01

    The accuracy of three radionuclide transfer models for predicting the interception and retention of airborne particles by agricultural crops was tested using Pu-bearing aerosols released to the atmosphere from nuclear fuel facilities on the U.S. Department of Energy's Savannah River Plant, near Aiken, SC. The models evaluated were: (1) NRC, the model defined in U.S. Nuclear Regulatory Guide 1.109; (2) FOOD, a model similar to the NRC model that also predicts concentrations in grains; and (3) AGNS, a model developed from the NRC model for the southeastern United States. Plutonium concentrations in vegetation and grain were predicted from measured deposition rates and compared to concentrations observed in the field. Crops included wheat, soybeans, corn and cabbage. Although predictions of the three models differed by less than a factor of 4, they showed different abilities to predict concentrations observed in the field. The NRC and FOOD models consistently underpredicted the observed Pu concentrations for vegetation. The AGNS model was a more accurate predictor of Pu concentrations for vegetation. Both the FOOD and AGNS models accurately predicted the Pu concentrations for grains

  7. General Theory versus ENA Theory: Comparing Their Predictive Accuracy and Scope.

    Science.gov (United States)

    Ellis, Lee; Hoskin, Anthony; Hartley, Richard; Walsh, Anthony; Widmayer, Alan; Ratnasingam, Malini

    2015-12-01

    General theory attributes criminal behavior primarily to low self-control, whereas evolutionary neuroandrogenic (ENA) theory envisions criminality as being a crude form of status-striving promoted by high brain exposure to androgens. General theory predicts that self-control will be negatively correlated with risk-taking, while ENA theory implies that these two variables should actually be positively correlated. According to ENA theory, traits such as pain tolerance and muscularity will be positively associated with risk-taking and criminality while general theory makes no predictions concerning these relationships. Data from Malaysia and the United States are used to test 10 hypotheses derived from one or both of these theories. As predicted by both theories, risk-taking was positively correlated with criminality in both countries. However, contrary to general theory and consistent with ENA theory, the correlation between self-control and risk-taking was positive in both countries. General theory's prediction of an inverse correlation between low self-control and criminality was largely supported by the U.S. data but only weakly supported by the Malaysian data. ENA theory's predictions of positive correlations between pain tolerance, muscularity, and offending were largely confirmed. For the 10 hypotheses tested, ENA theory surpassed general theory in predictive scope and accuracy. © The Author(s) 2014.

  8. Improvement of prediction accuracy of large eddy simulation on colocated grids; Colocation koshi wo mochiita LES no keisan seido kaizen ni kansuru ichikosatsu

    Energy Technology Data Exchange (ETDEWEB)

    Inagaki, M.; Abe, K. [Toyota Central Research and Development Labs., Inc., Aichi (Japan)

    1998-07-25

    With the recent advances in computers, large eddy simulation (LES) has become applicable to engineering prediction. However, most cases of the engineering applications need to use the nonorthgonal curvilimear coordinate systems. The staggered grids, usually used in LES in the orthgonal coordinates, don`t keep conservative properties in the nonorthgonal curvilinear coordinates. On the other hand, the colocated grids can be applied in the nonorthgonal curvilinear coordinates without losing its conservative properties, although its prediction accuracy isn`t so high as the staggered grid`s in the orthgonal coordinates especially with the coarse grids. In this research, the discretization method of the colocated grids is modified to improve its prediction accuracy. Plane channel flows are simulated on four grids of different resolution using the modified colocated grids and the original colocated grids. The results show that the modified colocated grids have higher accuracy than the original colocated grids. 17 refs., 13 figs., 1 tab.

  9. A Critical Analysis and Validation of the Accuracy of Wave Overtopping Prediction Formulae for OWECs

    Directory of Open Access Journals (Sweden)

    David Gallach-Sánchez

    2018-01-01

    Full Text Available The development of wave energy devices is growing in recent years. One type of device is the overtopping wave energy converter (OWEC, for which the knowledge of the wave overtopping rates is a basic and crucial aspect in their design. In particular, the most interesting range to study is for OWECs with steep slopes to vertical walls, and with very small freeboards and zero freeboards where the overtopping rate is maximized, and which can be generalized as steep low-crested structures. Recently, wave overtopping prediction formulae have been published for this type of structures, although their accuracy has not been fully assessed, as the overtopping data available in this range is scarce. We performed a critical analysis of the overtopping prediction formulae for steep low-crested structures and the validation of the accuracy of these formulae, based on new overtopping data for steep low-crested structures obtained at Ghent University. This paper summarizes the existing knowledge about average wave overtopping, describes the physical model tests performed, analyses the results and compares them to existing prediction formulae. The new dataset extends the wave overtopping data towards vertical walls and zero freeboard structures. In general, the new dataset validated the more recent overtopping formulae focused on steep slopes with small freeboards, although the formulae are underpredicting the average overtopping rates for very small and zero relative crest freeboards.

  10. Improving accuracy of protein-protein interaction prediction by considering the converse problem for sequence representation

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2011-10-01

    Full Text Available Abstract Background With the development of genome-sequencing technologies, protein sequences are readily obtained by translating the measured mRNAs. Therefore predicting protein-protein interactions from the sequences is of great demand. The reason lies in the fact that identifying protein-protein interactions is becoming a bottleneck for eventually understanding the functions of proteins, especially for those organisms barely characterized. Although a few methods have been proposed, the converse problem, if the features used extract sufficient and unbiased information from protein sequences, is almost untouched. Results In this study, we interrogate this problem theoretically by an optimization scheme. Motivated by the theoretical investigation, we find novel encoding methods for both protein sequences and protein pairs. Our new methods exploit sufficiently the information of protein sequences and reduce artificial bias and computational cost. Thus, it significantly outperforms the available methods regarding sensitivity, specificity, precision, and recall with cross-validation evaluation and reaches ~80% and ~90% accuracy in Escherichia coli and Saccharomyces cerevisiae respectively. Our findings here hold important implication for other sequence-based prediction tasks because representation of biological sequence is always the first step in computational biology. Conclusions By considering the converse problem, we propose new representation methods for both protein sequences and protein pairs. The results show that our method significantly improves the accuracy of protein-protein interaction predictions.

  11. Accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients

    Directory of Open Access Journals (Sweden)

    Bruno Prata Martinez

    2015-05-01

    Full Text Available OBJECTIVES: The ability of the Timed Up and Go test to predict sarcopenia has not been evaluated previously. The objective of this study was to evaluate the accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients. METHODS: This cross-sectional study analyzed 68 elderly patients (≥60 years of age in a private hospital in the city of Salvador-BA, Brazil, between the 1st and 5th day of hospitalization. The predictive variable was the Timed Up and Go test score, and the outcome of interest was the presence of sarcopenia (reduced muscle mass associated with a reduction in handgrip strength and/or weak physical performance in a 6-m gait-speed test. After the descriptive data analyses, the sensitivity, specificity and accuracy of a test using the predictive variable to predict the presence of sarcopenia were calculated. RESULTS: In total, 68 elderly individuals, with a mean age 70.4±7.7 years, were evaluated. The subjects had a Charlson Comorbidity Index score of 5.35±1.97. Most (64.7% of the subjects had a clinical admission profile; the main reasons for hospitalization were cardiovascular disorders (22.1%, pneumonia (19.1% and abdominal disorders (10.2%. The frequency of sarcopenia in the sample was 22.1%, and the mean length of time spent performing the Timed Up and Go test was 10.02±5.38 s. A time longer than or equal to a cutoff of 10.85 s on the Timed Up and Go test predicted sarcopenia with a sensitivity of 67% and a specificity of 88.7%. The accuracy of this cutoff for the Timed Up and Go test was good (0.80; IC=0.66-0.94; p=0.002. CONCLUSION: The Timed Up and Go test was shown to be a predictor of sarcopenia in elderly hospitalized patients.

  12. ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes.

    Science.gov (United States)

    Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

    2015-07-01

    In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. ZCURVE 3.0: identify prokaryotic genes with higher accuracy as well as automatically and accurately select essential genes

    Science.gov (United States)

    Hua, Zhi-Gang; Lin, Yan; Yuan, Ya-Zhou; Yang, De-Chang; Wei, Wen; Guo, Feng-Biao

    2015-01-01

    In 2003, we developed an ab initio program, ZCURVE 1.0, to find genes in bacterial and archaeal genomes. In this work, we present the updated version (i.e. ZCURVE 3.0). Using 422 prokaryotic genomes, the average accuracy was 93.7% with the updated version, compared with 88.7% with the original version. Such results also demonstrate that ZCURVE 3.0 is comparable with Glimmer 3.02 and may provide complementary predictions to it. In fact, the joint application of the two programs generated better results by correctly finding more annotated genes while also containing fewer false-positive predictions. As the exclusive function, ZCURVE 3.0 contains one post-processing program that can identify essential genes with high accuracy (generally >90%). We hope ZCURVE 3.0 will receive wide use with the web-based running mode. The updated ZCURVE can be freely accessed from http://cefg.uestc.edu.cn/zcurve/ or http://tubic.tju.edu.cn/zcurveb/ without any restrictions. PMID:25977299

  14. On accuracy of the wave finite element predictions of wavenumbers and power flow: A benchmark problem

    Science.gov (United States)

    Søe-Knudsen, Alf; Sorokin, Sergey

    2011-06-01

    This rapid communication is concerned with justification of the 'rule of thumb', which is well known to the community of users of the finite element (FE) method in dynamics, for the accuracy assessment of the wave finite element (WFE) method. An explicit formula linking the size of a window in the dispersion diagram, where the WFE method is trustworthy, with the coarseness of a FE mesh employed is derived. It is obtained by the comparison of the exact Pochhammer-Chree solution for an elastic rod having the circular cross-section with its WFE approximations. It is shown that the WFE power flow predictions are also valid within this window.

  15. Predicting Performance in Higher Education Using Proximal Predictors

    Science.gov (United States)

    Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

  16. Comparison of accuracy in predicting emotional instability from MMPI data: fisherian versus contingent probability statistics

    Energy Technology Data Exchange (ETDEWEB)

    Berghausen, P.E. Jr.; Mathews, T.W.

    1987-01-01

    The security plans of nuclear power plants generally require that all personnel who are to have access to protected areas or vital islands be screened for emotional stability. In virtually all instances, the screening involves the administration of one or more psychological tests, usually including the Minnesota Multiphasic Personality Inventory (MMPI). At some plants, all employees receive a structured clinical interview after they have taken the MMPI and results have been obtained. At other plants, only those employees with dirty MMPI are interviewed. This latter protocol is referred to as interviews by exception. Behaviordyne Psychological Corp. has succeeded in removing some of the uncertainty associated with interview-by-exception protocols by developing an empirically based, predictive equation. This equation permits utility companies to make informed choices regarding the risks they are assuming. A conceptual problem exists with the predictive equation, however. Like most predictive equations currently in use, it is based on Fisherian statistics, involving least-squares analyses. Consequently, Behaviordyne Psychological Corp., in conjunction with T.W. Mathews and Associates, has just developed a second predictive equation, one based on contingent probability statistics. The particular technique used in the multi-contingent analysis of probability systems (MAPS) approach. The present paper presents a comparison of predictive accuracy of the two equations: the one derived using Fisherian techniques versus the one thing contingent probability techniques.

  17. Effect of length of measurement period on accuracy of predicted annual heating energy consumption of buildings

    International Nuclear Information System (INIS)

    Cho, Sung-Hwan; Kim, Won-Tae; Tae, Choon-Soeb; Zaheeruddin, M.

    2004-01-01

    This study examined the temperature dependent regression models of energy consumption as a function of the length of the measurement period. The methodology applied was to construct linear regression models of daily energy consumption from 1 day to 3 months data sets and compare the annual heating energy consumption predicted by these models with actual annual heating energy consumption. A commercial building in Daejon was selected, and the energy consumption was measured over a heating season. The results from the investigation show that the predicted energy consumption based on 1 day of measurements to build the regression model could lead to errors of 100% or more. The prediction error decreased to 30% when 1 week of data was used to build the regression model. Likewise, the regression model based on 3 months of measured data predicted the annual energy consumption within 6% of the measured energy consumption. These analyses show that the length of the measurement period has a significant impact on the accuracy of the predicted annual energy consumption of buildings

  18. Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

    Science.gov (United States)

    Raicar, Gaurav; Saini, Harsh; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

    2016-08-07

    Predicting the three-dimensional (3-D) structure of a protein is an important task in the field of bioinformatics and biological sciences. However, directly predicting the 3-D structure from the primary structure is hard to achieve. Therefore, predicting the fold or structural class of a protein sequence is generally used as an intermediate step in determining the protein's 3-D structure. For protein fold recognition (PFR) and structural class prediction (SCP), two steps are required - feature extraction step and classification step. Feature extraction techniques generally utilize syntactical-based information, evolutionary-based information and physicochemical-based information to extract features. In this study, we explore the importance of utilizing the physicochemical properties of amino acids for improving PFR and SCP accuracies. For this, we propose a Forward Consecutive Search (FCS) scheme which aims to strategically select physicochemical attributes that will supplement the existing feature extraction techniques for PFR and SCP. An exhaustive search is conducted on all the existing 544 physicochemical attributes using the proposed FCS scheme and a subset of physicochemical attributes is identified. Features extracted from these selected attributes are then combined with existing syntactical-based and evolutionary-based features, to show an improvement in the recognition and prediction performance on benchmark datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Comparison of accuracy in predicting emotional instability from MMPI data: fisherian versus contingent probability statistics

    International Nuclear Information System (INIS)

    Berghausen, P.E. Jr.; Mathews, T.W.

    1987-01-01

    The security plans of nuclear power plants generally require that all personnel who are to have access to protected areas or vital islands be screened for emotional stability. In virtually all instances, the screening involves the administration of one or more psychological tests, usually including the Minnesota Multiphasic Personality Inventory (MMPI). At some plants, all employees receive a structured clinical interview after they have taken the MMPI and results have been obtained. At other plants, only those employees with dirty MMPI are interviewed. This latter protocol is referred to as interviews by exception. Behaviordyne Psychological Corp. has succeeded in removing some of the uncertainty associated with interview-by-exception protocols by developing an empirically based, predictive equation. This equation permits utility companies to make informed choices regarding the risks they are assuming. A conceptual problem exists with the predictive equation, however. Like most predictive equations currently in use, it is based on Fisherian statistics, involving least-squares analyses. Consequently, Behaviordyne Psychological Corp., in conjunction with T.W. Mathews and Associates, has just developed a second predictive equation, one based on contingent probability statistics. The particular technique used in the multi-contingent analysis of probability systems (MAPS) approach. The present paper presents a comparison of predictive accuracy of the two equations: the one derived using Fisherian techniques versus the one thing contingent probability techniques

  20. The accuracy of body mass prediction for elderly specimens: Implications for paleoanthropology and legal medicine.

    Science.gov (United States)

    Chevalier, Tony; Lefèvre, Philippe; Clarys, Jan Pieter; Beauthier, Jean-Pol

    2016-10-01

    Different practices in paleoanthropology and legal medicine raise questions concerning the robustness of body mass (BM) prediction. Integrating personal identification from body mass estimation with skeleton is not a classic approach in legal medicine. The originality of our study is the use of an elderly sample in order to push prediction methods to their limits and to discuss about implications in paleoanthropology and legal medicine. The aim is to observe the accuracy of BM prediction in relation to the body mass index (BMI, index of classification) using five femoral head (FH) methods and one shaft (FSH) method. The sample is composed of 41 dry femurs obtained from dissection where age (c. 82 years) and gender are known, and weight (c. 59.5 kg) and height are measured upon admission to the body leg service. We show that the estimation of the mean BM of the elderly sample is not significantly different to the real mean BM when the appropriate formula is used for the femoral head diameter. In fact, the best prediction is obtained with the McHenry formula (1992), which was based on a sample with an equivalent average mass to that of our sample. In comparison, external shaft diameters, which are known to be more influenced by mechanical stimuli than femoral head diameters, yield less satisfactory results with the McHenry formula (1992) for shaft diameters. Based on all the methods used and the distinctive selected sample, overestimation (always observed with the different femoral head methods) can be restricted to 1.1%. The observed overestimation with the shaft method can be restricted to 7%. However, the estimation of individual BM is much less reliable. The BMI has a strong impact on the accuracy of individual BM prediction, and is unquestionably more reliable for individuals with normal BMI (9.6% vs 16.7% for the best prediction error). In this case, the FH method is also the better predictive method but not if we integrate the total sample (i.e., the FSH

  1. Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

    Science.gov (United States)

    Zheng, Ce; Kurgan, Lukasz

    2008-10-10

    beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction

  2. Prediction of novel pre-microRNAs with high accuracy through boosting and SVM.

    Science.gov (United States)

    Zhang, Yuanwei; Yang, Yifan; Zhang, Huan; Jiang, Xiaohua; Xu, Bo; Xue, Yu; Cao, Yunxia; Zhai, Qian; Zhai, Yong; Xu, Mingqing; Cooke, Howard J; Shi, Qinghua

    2011-05-15

    High-throughput deep-sequencing technology has generated an unprecedented number of expressed short sequence reads, presenting not only an opportunity but also a challenge for prediction of novel microRNAs. To verify the existence of candidate microRNAs, we have to show that these short sequences can be processed from candidate pre-microRNAs. However, it is laborious and time consuming to verify these using existing experimental techniques. Therefore, here, we describe a new method, miRD, which is constructed using two feature selection strategies based on support vector machines (SVMs) and boosting method. It is a high-efficiency tool for novel pre-microRNA prediction with accuracy up to 94.0% among different species. miRD is implemented in PHP/PERL+MySQL+R and can be freely accessed at http://mcg.ustc.edu.cn/rpg/mird/mird.php.

  3. Predicting Performance in Higher Education Using Proximal Predictors

    NARCIS (Netherlands)

    Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach,

  4. Functional knowledge transfer for high-accuracy prediction of under-studied biological processes.

    Directory of Open Access Journals (Sweden)

    Christopher Y Park

    Full Text Available A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator's organism of interest. Sequence-based search methods (e.g. BLAST have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction. We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics

  5. Sensitivity, specificity, predictive value and accuracy of ultrasonography in pregnancy rate prediction in Sahelian goats after progesterone impregnated sponge synchronization

    Directory of Open Access Journals (Sweden)

    Justin Kouamo

    2014-09-01

    Full Text Available Aim: This study was aimed to evaluate the sensitivity, specificity, predictive value and accuracy of ultrasonography in pregnancy rate (PR prediction in Sahelian goats after progesterone impregnated sponge synchronization within the framework of caprine artificial insemination (AI program in Fatick (Senegal. Materials and Methods: Of 193 candidate goats in AI program, 167 were selected (day 50 in six villages. Estrus was synchronized by progesterone impregnated sponges installed for 11 days. Two days before the time of sponge removal (day 4, each goat was treated with 500 IU of equine chorionic gonadotropin and 50 μg of dcloprostenol. All goats were inseminated (day 0 with alpine goat semen from France at 45±3 h after sponge removal (day 2. Real-time B-mode ultrasonography was performed at day 50, day 13, day 0, day 40 and day 60 post-AI. Results: Selection rate, estrus response rate, AI rate, PR at days 40 and days 60 were 86.53%; 71.85%; 83.34%; 51% and 68% (p<0.05 respectively. Value of sensitivity, specificity, positive and negative predictive value, accuracy, total conformity, conformity of correct positive, conformity of correct negative and discordance of pregnancy diagnosis by trans-abdominal ultrasonography (TU were 98.03%; 63.26%; 73.52%; 3.12%; 81%; 81%; 50%; 31% and 19%, respectively. Conclusion: These results indicate that the TU can be performed in goats under traditional condition and emphasized the importance of re-examination of goats with negative or doubtful TU diagnoses performed at day 40 post-AI.

  6. Accuracy of Igenity genomically estimated breeding values for predicting Australian Angus BREEDPLAN traits.

    Science.gov (United States)

    Boerner, V; Johnston, D; Wu, X-L; Bauck, S

    2015-02-01

    Genomically estimated breeding values (GEBV) for Angus beef cattle are available from at least 2 commercial suppliers (Igenity [http://www.igenity.com] and Zoetis [http://www.zoetis.com]). The utility of these GEBV for improving genetic evaluation depends on their accuracies, which can be estimated by the genetic correlation with phenotypic target traits. Genomically estimated breeding values of 1,032 Angus bulls calculated from prediction equations (PE) derived by 2 different procedures in the U.S. Angus population were supplied by Igenity. Both procedures were based on Illuminia BovineSNP50 BeadChip genotypes. In procedure sg, GEBV were calculated from PE that used subsets of only 392 SNP, where these subsets were individually selected for each trait by BayesCπ. In procedure rg GEBV were calculated from PE derived in a ridge regression approach using all available SNP. Because the total set of 1,032 bulls with GEBV contained 732 individuals used in the Igenity training population, GEBV subsets were formed characterized by a decreasing average relationship between individuals in the subsets and individuals in the training population. Accuracies of GEBV were estimated as genetic correlations between GEBV and their phenotypic target traits modeling GEBV as trait observations in a bivariate REML approach, in which phenotypic observations were those recorded in the commercial Australian Angus seed stock sector. Using results from the GEBV subset excluding all training individuals as a reference, estimated accuracies were generally in agreement with those already published, with both types of GEBV (sg and rg) yielding similar results. Accuracies for growth traits ranged from 0.29 to 0.45, for reproductive traits from 0.11 to 0.53, and for carcass traits from 0.3 to 0.75. Accuracies generally decreased with an increasing genetic distance between the training and the validation population. However, for some carcass traits characterized by a low number of phenotypic

  7. Prediction of pre-eclampsia: a protocol for systematic reviews of test accuracy

    Directory of Open Access Journals (Sweden)

    Khan Khalid S

    2006-10-01

    Full Text Available Abstract Background Pre-eclampsia, a syndrome of hypertension and proteinuria, is a major cause of maternal and perinatal morbidity and mortality. Accurate prediction of pre-eclampsia is important, since high risk women could benefit from intensive monitoring and preventive treatment. However, decision making is currently hampered due to lack of precise and up to date comprehensive evidence summaries on estimates of risk of developing pre-eclampsia. Methods/Design A series of systematic reviews and meta-analyses will be undertaken to determine, among women in early pregnancy, the accuracy of various tests (history, examinations and investigations for predicting pre-eclampsia. We will search Medline, Embase, Cochrane Library, MEDION, citation lists of review articles and eligible primary articles and will contact experts in the field. Reviewers working independently will select studies, extract data, and assess study validity according to established criteria. Language restrictions will not be applied. Bivariate meta-analysis of sensitivity and specificity will be considered for tests whose studies allow generation of 2 × 2 tables. Discussion The results of the test accuracy reviews will be integrated with results of effectiveness reviews of preventive interventions to assess the impact of test-intervention combinations for prevention of pre-eclampsia.

  8. Prediction of miscarriage in women with viable intrauterine pregnancy-A systematic review and diagnostic accuracy meta-analysis.

    Science.gov (United States)

    Pillai, Rekha N; Konje, Justin C; Richardson, Matthew; Tincello, Douglas G; Potdar, Neelam

    2018-01-01

    Both ultrasound and biochemical markers either alone or in combination have been described in the literature for the prediction of miscarriage. We performed this systematic review and meta-analysis to determine the best combination of biochemical, ultrasound and demographic markers to predict miscarriage in women with viable intrauterine pregnancy. The electronic database search included Medline (1946-June 2017), Embase (1980-June 2017), CINAHL (1981-June 2017) and Cochrane library. Key MESH and Boolean terms were used for the search. Data extraction and collection was performed based on the eligibility criteria by two authors independently. Quality assessment of the individual studies was done using QUADAS 2 (Quality Assessment for Diagnostic Accuracy Studies-2: A Revised Tool) and statistical analysis performed using the Cochrane systematic review manager 5.3 and STATA vs.13.0. Due to the diversity of the combinations used for prediction in the included papers it was not possible to perform a meta-analysis on combination markers. Therefore, we proceeded to perform a meta-analysis on ultrasound markers alone to determine the best marker that can help to improve the diagnostic accuracy of predicting miscarriage in women with viable intrauterine pregnancy. The systematic review identified 18 eligible studies for the quantitative meta-analysis with a total of 5584 women. Among the ultrasound scan markers, fetal bradycardia (n=10 studies, n=1762 women) on hierarchical summary receiver operating characteristic showed sensitivity of 68.41%, specificity of 97.84%, positive likelihood ratio of 31.73 (indicating a large effect on increasing the probability of predicting miscarriage) and negative likelihood ratio of 0.32. In studies for women with threatened miscarriage (n=5 studies, n=771 women) fetal bradycardia showed further increase in sensitivity (84.18%) for miscarriage prediction. Although there is gestational age dependent variation in the fetal heart rate, a plot

  9. Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

    Directory of Open Access Journals (Sweden)

    Kurgan Lukasz

    2008-10-01

    Full Text Available Abstract Background β-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of β-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based β-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM values serve as an input to the support vector machine (SVM predictor. Results We show that (1 all four predicted secondary structures are useful; (2 the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3 the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential β-turns, while the remaining four amino acids are useful to predict non-β-turns. Empirical evaluation using three nonredundant datasets shows favorable Qtotal, Qpredicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Qtotal barrier and achieves Qtotal = 80.9%, MCC = 0.47, and Qpredicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC competing methods, respectively. Conclusion Experiments show that the proposed method constitutes an

  10. Genomic Prediction Within and Across Biparental Families: Means and Variances of Prediction Accuracy and Usefulness of Deterministic Equations

    Directory of Open Access Journals (Sweden)

    Pascal Schopp

    2017-11-01

    Full Text Available A major application of genomic prediction (GP in plant breeding is the identification of superior inbred lines within families derived from biparental crosses. When models for various traits were trained within related or unrelated biparental families (BPFs, experimental studies found substantial variation in prediction accuracy (PA, but little is known about the underlying factors. We used SNP marker genotypes of inbred lines from either elite germplasm or landraces of maize (Zea mays L. as parents to generate in silico 300 BPFs of doubled-haploid lines. We analyzed PA within each BPF for 50 simulated polygenic traits, using genomic best linear unbiased prediction (GBLUP models trained with individuals from either full-sib (FSF, half-sib (HSF, or unrelated families (URF for various sizes (Ntrain of the training set and different heritabilities (h2 . In addition, we modified two deterministic equations for forecasting PA to account for inbreeding and genetic variance unexplained by the training set. Averaged across traits, PA was high within FSF (0.41–0.97 with large variation only for Ntrain < 50 and h2 < 0.6. For HSF and URF, PA was on average ∼40–60% lower and varied substantially among different combinations of BPFs used for model training and prediction as well as different traits. As exemplified by HSF results, PA of across-family GP can be very low if causal variants not segregating in the training set account for a sizeable proportion of the genetic variance among predicted individuals. Deterministic equations accurately forecast the PA expected over many traits, yet cannot capture trait-specific deviations. We conclude that model training within BPFs generally yields stable PA, whereas a high level of uncertainty is encountered in across-family GP. Our study shows the extent of variation in PA that must be at least reckoned with in practice and offers a starting point for the design of training sets composed of multiple BPFs.

  11. Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics.

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    Madarang, Krish J; Kang, Joo-Hyon

    2014-06-01

    Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days (ADD), have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency's Storm Water Management Model (SWMM). The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid (TSS) discharge loads and event mean concentrations (EMC) were extracted. From these data, linear regression models were developed. R(2) and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data. Copyright © 2014 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

  12. Accuracy statistics in predicting Independent Activities of Daily Living (IADL) capacity with comprehensive and brief neuropsychological test batteries.

    Science.gov (United States)

    Karzmark, Peter; Deutsch, Gayle K

    2018-01-01

    This investigation was designed to determine the predictive accuracy of a comprehensive neuropsychological and brief neuropsychological test battery with regard to the capacity to perform instrumental activities of daily living (IADLs). Accuracy statistics that included measures of sensitivity, specificity, positive and negative predicted power and positive likelihood ratio were calculated for both types of batteries. The sample was drawn from a general neurological group of adults (n = 117) that included a number of older participants (age >55; n = 38). Standardized neuropsychological assessments were administered to all participants and were comprised of the Halstead Reitan Battery and portions of the Wechsler Adult Intelligence Scale-III. A comprehensive test battery yielded a moderate increase over base-rate in predictive accuracy that generalized to older individuals. There was only limited support for using a brief battery, for although sensitivity was high, specificity was low. We found that a comprehensive neuropsychological test battery provided good classification accuracy for predicting IADL capacity.

  13. Atomic-accuracy prediction of protein loop structures through an RNA-inspired Ansatz.

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    Rhiju Das

    Full Text Available Consistently predicting biopolymer structure at atomic resolution from sequence alone remains a difficult problem, even for small sub-segments of large proteins. Such loop prediction challenges, which arise frequently in comparative modeling and protein design, can become intractable as loop lengths exceed 10 residues and if surrounding side-chain conformations are erased. Current approaches, such as the protein local optimization protocol or kinematic inversion closure (KIC Monte Carlo, involve stages that coarse-grain proteins, simplifying modeling but precluding a systematic search of all-atom configurations. This article introduces an alternative modeling strategy based on a 'stepwise ansatz', recently developed for RNA modeling, which posits that any realistic all-atom molecular conformation can be built up by residue-by-residue stepwise enumeration. When harnessed to a dynamic-programming-like recursion in the Rosetta framework, the resulting stepwise assembly (SWA protocol enables enumerative sampling of a 12 residue loop at a significant but achievable cost of thousands of CPU-hours. In a previously established benchmark, SWA recovers crystallographic conformations with sub-Angstrom accuracy for 19 of 20 loops, compared to 14 of 20 by KIC modeling with a comparable expenditure of computational power. Furthermore, SWA gives high accuracy results on an additional set of 15 loops highlighted in the biological literature for their irregularity or unusual length. Successes include cis-Pro touch turns, loops that pass through tunnels of other side-chains, and loops of lengths up to 24 residues. Remaining problem cases are traced to inaccuracies in the Rosetta all-atom energy function. In five additional blind tests, SWA achieves sub-Angstrom accuracy models, including the first such success in a protein/RNA binding interface, the YbxF/kink-turn interaction in the fourth 'RNA-puzzle' competition. These results establish all-atom enumeration as

  14. Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns.

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    Liu, Jin; Liao, Xuhong; Xia, Mingrui; He, Yong

    2018-02-01

    The human brain is a large, interacting dynamic network, and its architecture of coupling among brain regions varies across time (termed the "chronnectome"). However, very little is known about whether and how the dynamic properties of the chronnectome can characterize individual uniqueness, such as identifying individuals as a "fingerprint" of the brain. Here, we employed multiband resting-state functional magnetic resonance imaging data from the Human Connectome Project (N = 105) and a sliding time-window dynamic network analysis approach to systematically examine individual time-varying properties of the chronnectome. We revealed stable and remarkable individual variability in three dynamic characteristics of brain connectivity (i.e., strength, stability, and variability), which was mainly distributed in three higher order cognitive systems (i.e., default mode, dorsal attention, and fronto-parietal) and in two primary systems (i.e., visual and sensorimotor). Intriguingly, the spatial patterns of these dynamic characteristics of brain connectivity could successfully identify individuals with high accuracy and could further significantly predict individual higher cognitive performance (e.g., fluid intelligence and executive function), which was primarily contributed by the higher order cognitive systems. Together, our findings highlight that the chronnectome captures inherent functional dynamics of individual brain networks and provides implications for individualized characterization of health and disease. © 2017 Wiley Periodicals, Inc.

  15. Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.

    Science.gov (United States)

    Lopez-Cruz, Marco; Crossa, Jose; Bonnett, David; Dreisigacker, Susanne; Poland, Jesse; Jannink, Jean-Luc; Singh, Ravi P; Autrique, Enrique; de los Campos, Gustavo

    2015-02-06

    Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype × environment interaction(G×E). Several authors have proposed extensions of the single-environment GS model that accommodate G×E using either covariance functions or environmental covariates. In this study, we model G×E using a marker × environment interaction (M×E) GS model; the approach is conceptually simple and can be implemented with existing GS software. We discuss how the model can be implemented by using an explicit regression of phenotypes on markers or using co-variance structures (a genomic best linear unbiased prediction-type model). We used the M×E model to analyze three CIMMYT wheat data sets (W1, W2, and W3), where more than 1000 lines were genotyped using genotyping-by-sequencing and evaluated at CIMMYT's research station in Ciudad Obregon, Mexico, under simulated environmental conditions that covered different irrigation levels, sowing dates and planting systems. We compared the M×E model with a stratified (i.e., within-environment) analysis and with a standard (across-environment) GS model that assumes that effects are constant across environments (i.e., ignoring G×E). The prediction accuracy of the M×E model was substantially greater of that of an across-environment analysis that ignores G×E. Depending on the prediction problem, the M×E model had either similar or greater levels of prediction accuracy than the stratified analyses. The M×E model decomposes marker effects and genomic values into components that are stable across environments (main effects) and others that are environment-specific (interactions). Therefore, in principle, the interaction model could shed light over which variants have effects that are stable across environments and which ones are responsible for G×E. The data set and the scripts required to reproduce the analysis are

  16. Screening Characteristics of TIMI Score in Predicting Acute Coronary Syndrome Outcome; a Diagnostic Accuracy Study

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    Mostafa Alavi-Moghaddam

    2017-01-01

    Full Text Available Introduction: In cases with potential diagnosis of ischemic chest pain, screening high risk patients for adverse outcomes would be very helpful. The present study was designed aiming to determine the diagnostic accuracy of thrombolysis in myocardial infarction (TIMI score in Patients with potential diagnosis of ischemic chest pain.Method: This diagnostic accuracy study was designed to evaluate the screening performance characteristics of TIMI score in predicting 30-day outcomes of mortality, myocardial infarction (MI, and need for revascularization in patients presenting to ED with complaint of typical chest pain and diagnosis of unstable angina or Non-ST elevation MI.Results: 901 patients with the mean age of 58.17 ± 15.00 years (19-90 were studied (52.9% male. Mean TIMI score of the studied patients was 0.97 ± 0.93 (0-5 and the highest frequency of the score belonged to 0 to 2 with 37.2%, 35.3%, and 21.4%, respectively. In total, 170 (18.8% patients experienced the outcomes evaluated in this study. Total sensitivity, specificity, positive and negative predictive value, and positive and negative likelihood ratio of TIMI score were 20 (95% CI: 17 – 24, 99 (95% CI: 97 – 100, 98 (95% CI: 93 – 100, 42 (95% CI: 39 – 46, 58 (95% CI: 14 – 229, and 1.3 (95% CI: 1.2 – 1.4, respectively. Area under the ROC curve of this system for prediction of 30-day mortality, MI, and need for revascularization were 0.51 (95% CI: 0.47 – 0.55, 0.58 (95% CI: 0.54 – 0.62 and 0.56 (95% CI: 0.52 – 0.60, respectively.Conclusion: Based on the findings of the present study, it seems that TIMI score has a high specificity in predicting 30-day adverse outcomes of mortality, MI, and need for revascularization following acute coronary syndrome. However, since its sensitivity, negative predictive value, and negative likelihood ratio are low, it cannot be used as a proper screening tool for ruling out low risk patients in ED.

  17. Predictive Accuracy of a Cardiovascular Disease Risk Prediction Model in Rural South India – A Community Based Retrospective Cohort Study

    Directory of Open Access Journals (Sweden)

    Farah N Fathima

    2015-03-01

    Full Text Available Background: Identification of individuals at risk of developing cardiovascular diseases by risk stratification is the first step in primary prevention. Aims & Objectives: To assess the five year risk of developing a cardiovascular event from retrospective data and to assess the predictive accuracy of the non laboratory based National Health and Nutrition Examination Survey (NHANES risk prediction model among individuals in a rural South Indian population. Materials & Methods: A community based retrospective cohort study was conducted in three villages where risk stratification was done for all eligible adults aged between 35-74 years at the time of initial assessment using the NHANES risk prediction charts. Household visits were made after a period of five years by trained doctors to determine cardiovascular outcomes. Results: 521 people fulfilled the eligibility criteria of whom 486 (93.3% could be traced after five years. 56.8% were in low risk, 36.6% were in moderate risk and 6.6% were in high risk categories. 29 persons (5.97% had had cardiovascular events over the last five years of which 24 events (82.7% were nonfatal and five (17.25% were fatal. The mean age of the people who developed cardiovascular events was 57.24 ± 9.09 years. The odds ratios for the three levels of risk showed a linear trend with the odds ratios for the moderate risk and high risk category being 1.35 and 1.94 respectively with the low risk category as baseline. Conclusion: The non laboratory based NHANES charts did not accurately predict the occurrence of cardiovascular events in any of the risk categories.

  18. Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients.

    Science.gov (United States)

    Kim, Yun Hak; Jeong, Dae Cheon; Pak, Kyoungjune; Goh, Tae Sik; Lee, Chi-Seung; Han, Myoung-Eun; Kim, Ji-Young; Liangwen, Liu; Kim, Chi Dae; Jang, Jeon Yeob; Cha, Wonjae; Oh, Sae-Ock

    2017-09-29

    Accurate prediction of prognosis is critical for therapeutic decisions regarding cancer patients. Many previously developed prognostic scoring systems have limitations in reflecting recent progress in the field of cancer biology such as microarray, next-generation sequencing, and signaling pathways. To develop a new prognostic scoring system for cancer patients, we used mRNA expression and clinical data in various independent breast cancer cohorts (n=1214) from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and Gene Expression Omnibus (GEO). A new prognostic score that reflects gene network inherent in genomic big data was calculated using Network-Regularized high-dimensional Cox-regression (Net-score). We compared its discriminatory power with those of two previously used statistical methods: stepwise variable selection via univariate Cox regression (Uni-score) and Cox regression via Elastic net (Enet-score). The Net scoring system showed better discriminatory power in prediction of disease-specific survival (DSS) than other statistical methods (p=0 in METABRIC training cohort, p=0.000331, 4.58e-06 in two METABRIC validation cohorts) when accuracy was examined by log-rank test. Notably, comparison of C-index and AUC values in receiver operating characteristic analysis at 5 years showed fewer differences between training and validation cohorts with the Net scoring system than other statistical methods, suggesting minimal overfitting. The Net-based scoring system also successfully predicted prognosis in various independent GEO cohorts with high discriminatory power. In conclusion, the Net-based scoring system showed better discriminative power than previous statistical methods in prognostic prediction for breast cancer patients. This new system will mark a new era in prognosis prediction for cancer patients.

  19. Concurrent and predictive evaluation of malnutrition diagnostic measures in hip fracture inpatients: a diagnostic accuracy study.

    Science.gov (United States)

    Bell, J J; Bauer, J D; Capra, S; Pulle, R C

    2014-03-01

    Differences in malnutrition diagnostic measures impact malnutrition prevalence and outcomes data in hip fracture. This study investigated the concurrent and predictive validity of commonly reported malnutrition diagnostic measures in patients admitted to a metropolitan hospital acute hip fracture unit. A prospective, consecutive level II diagnostic accuracy study (n=142; 8 exclusions) including the International Classification of Disease, 10th Revision, Australian Modification (ICD10-AM) protein-energy malnutrition criteria, a body mass index (BMI) Patients were predominantly elderly (median age 83.5, range 50-100 years), female (68%), multimorbid (median five comorbidities), with 15% 4-month mortality. Malnutrition prevalence was lowest when assessed by BMI (13%), followed by MNA-SF (27%), ICD10-AM (48%), albumin (53%) and geriatrician assessment (55%). Agreement between measures was highest between ICD10-AM and geriatrician assessment (κ=0.61) followed by ICD10-AM and MNA-SF measures (κ=0.34). ICD10-AM diagnosed malnutrition was the only measure associated with 48-h mobilisation (35.0 vs 55.3%; P=0.018). Reduced likelihood of home discharge was predicted by ICD-10-AM (20.6 vs 57.1%; P=0.001) and MNA-SF (18.8 vs 47.8%; P=0.035). Bivariate analysis demonstrated ICD10-AM (relative risk (RR)1.2; 1.05-1.42) and MNA-SF (RR1.2; 1.0-1.5) predicted 4-month mortality. When adjusted for age, usual place of residency, comorbidities and time to surgery only ICD-10AM criteria predicted mortality (odds ratio 3.59; 1.10-11.77). Albumin, BMI and geriatrician assessment demonstrated limited concurrent and predictive validity. Malnutrition prevalence in hip fracture varies substantially depending on the diagnostic measure applied. ICD-10AM criteria or the MNA-SF should be considered for the diagnosis of protein-energy malnutrition in frail, multi-morbid hip fracture inpatients.

  20. EMUDRA: Ensemble of Multiple Drug Repositioning Approaches to Improve Prediction Accuracy.

    Science.gov (United States)

    Zhou, Xianxiao; Wang, Minghui; Katsyv, Igor; Irie, Hanna; Zhang, Bin

    2018-04-24

    Availability of large-scale genomic, epigenetic and proteomic data in complex diseases makes it possible to objectively and comprehensively identify therapeutic targets that can lead to new therapies. The Connectivity Map has been widely used to explore novel indications of existing drugs. However, the prediction accuracy of the existing methods, such as Kolmogorov-Smirnov statistic remains low. Here we present a novel high-performance drug repositioning approach that improves over the state-of-the-art methods. We first designed an expression weighted cosine method (EWCos) to minimize the influence of the uninformative expression changes and then developed an ensemble approach termed EMUDRA (Ensemble of Multiple Drug Repositioning Approaches) to integrate EWCos and three existing state-of-the-art methods. EMUDRA significantly outperformed individual drug repositioning methods when applied to simulated and independent evaluation datasets. We predicted using EMUDRA and experimentally validated an antibiotic rifabutin as an inhibitor of cell growth in triple negative breast cancer. EMUDRA can identify drugs that more effectively target disease gene signatures and will thus be a useful tool for identifying novel therapies for complex diseases and predicting new indications for existing drugs. The EMUDRA R package is available at doi:10.7303/syn11510888. bin.zhang@mssm.edu or zhangb@hotmail.com. Supplementary data are available at Bioinformatics online.

  1. Predicting perceptual learning from higher-order cortical processing.

    Science.gov (United States)

    Wang, Fang; Huang, Jing; Lv, Yaping; Ma, Xiaoli; Yang, Bin; Wang, Encong; Du, Boqi; Li, Wu; Song, Yan

    2016-01-01

    Visual perceptual learning has been shown to be highly specific to the retinotopic location and attributes of the trained stimulus. Recent psychophysical studies suggest that these specificities, which have been associated with early retinotopic visual cortex, may in fact not be inherent in perceptual learning and could be related to higher-order brain functions. Here we provide direct electrophysiological evidence in support of this proposition. In a series of event-related potential (ERP) experiments, we recorded high-density electroencephalography (EEG) from human adults over the course of learning in a texture discrimination task (TDT). The results consistently showed that the earliest C1 component (68-84ms), known to reflect V1 activity driven by feedforward inputs, was not modulated by learning regardless of whether the behavioral improvement is location specific or not. In contrast, two later posterior ERP components (posterior P1 and P160-350) over the occipital cortex and one anterior ERP component (anterior P160-350) over the prefrontal cortex were progressively modified day by day. Moreover, the change of the anterior component was closely correlated with improved behavioral performance on a daily basis. Consistent with recent psychophysical and imaging observations, our results indicate that perceptual learning can mainly involve changes in higher-level visual cortex as well as in the neural networks responsible for cognitive functions such as attention and decision making. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Predicting molybdenum toxicity to higher plants: Influence of soil properties

    Energy Technology Data Exchange (ETDEWEB)

    McGrath, S.P., E-mail: steve.mcgrath@bbsrc.ac.u [Soil Science Department, Centre for Soils and Ecosystems Functions, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ (United Kingdom); Mico, C. [Soil Science Department, Centre for Soils and Ecosystems Functions, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ (United Kingdom); Curdy, R. [Laboratory for Environmental Biotechnology (LBE), Swiss Federal Institute of Technology Lausanne (EPFL) Station 6 CH, 1015 Lausanne (Switzerland); Zhao, F.J. [Soil Science Department, Centre for Soils and Ecosystems Functions, Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ (United Kingdom)

    2010-10-15

    The effect of soil properties on the toxicity of molybdenum (Mo) to four plant species was investigated. Soil organic carbon or ammonium-oxalate extractable Fe oxides were found to be the best predictors of the 50% effective dose (ED{sub 50}) of Mo in different soils, explaining > 65% of the variance in ED{sub 50} for four species except for ryegrass (26-38%). Molybdenum concentrations in soil solution and consequently plant uptake were increased when soil pH was artificially raised because sorption of Mo to amorphous oxides is greatly reduced at high pH. The addition of sulphate significantly decreased Mo uptake by oilseed rape. For risk assessment, we suggest that Mo toxicity values for plants should be normalised using soil amorphous iron oxide concentrations. - Amorphous iron oxides or organic carbon were found to be the best predictors of the toxicity threshold values of Mo to higher plants on different soils.

  3. Predicting molybdenum toxicity to higher plants: Influence of soil properties

    International Nuclear Information System (INIS)

    McGrath, S.P.; Mico, C.; Curdy, R.; Zhao, F.J.

    2010-01-01

    The effect of soil properties on the toxicity of molybdenum (Mo) to four plant species was investigated. Soil organic carbon or ammonium-oxalate extractable Fe oxides were found to be the best predictors of the 50% effective dose (ED 50 ) of Mo in different soils, explaining > 65% of the variance in ED 50 for four species except for ryegrass (26-38%). Molybdenum concentrations in soil solution and consequently plant uptake were increased when soil pH was artificially raised because sorption of Mo to amorphous oxides is greatly reduced at high pH. The addition of sulphate significantly decreased Mo uptake by oilseed rape. For risk assessment, we suggest that Mo toxicity values for plants should be normalised using soil amorphous iron oxide concentrations. - Amorphous iron oxides or organic carbon were found to be the best predictors of the toxicity threshold values of Mo to higher plants on different soils.

  4. Accuracy of Body Mass Index Versus Lean Mass Index for Prediction of Sarcopenia in Older Women.

    Science.gov (United States)

    Benton, M J; Silva-Smith, A L

    2018-01-01

    We compared accuracy of body mass index (BMI) versus lean mass index (LMI) to predict sarcopenia in 58 community-dwelling women (74.1±0.9 years). Lean mass was measured with multi-frequency bioelectrical impedance analysis, and strength was measured with Arm Curl test, Chair Stand test, and handgrip dynamometry. Sarcopenia was defined as low LMI. When categorized by BMI, normal women had less absolute lean mass (37.6±1.0 vs. 42.6±0.9 kg; Plean mass (14.1±0.2 vs. 16.1±0.2 kg/m2; Plean mass (44.0±0.7 vs. 35.7±0.7 kg; Plean mass (16.2±0.2 vs. 13.8±0.2 kg/m2; Plean mass and strength. For clinical assessment, calculation of LMI rather than BMI is appropriate.

  5. Improving the Accuracy of the Hyperspectral Model for Apple Canopy Water Content Prediction using the Equidistant Sampling Method.

    Science.gov (United States)

    Zhao, Huan-San; Zhu, Xi-Cun; Li, Cheng; Wei, Yu; Zhao, Geng-Xing; Jiang, Yuan-Mao

    2017-09-11

    The influence of the equidistant sampling method was explored in a hyperspectral model for the accurate prediction of the water content of apple tree canopy. The relationship between spectral reflectance and water content was explored using the sample partition methods of equidistant sampling and random sampling, and a stepwise regression model of the apple canopy water content was established. The results showed that the random sampling model was Y = 0.4797 - 721787.3883 × Z 3 - 766567.1103 × Z 5 - 771392.9030 × Z 6 ; the equidistant sampling model was Y = 0.4613 - 480610.4213 × Z 2 - 552189.0450 × Z 5 - 1006181.8358 × Z 6 . After verification, the equidistant sampling method was verified to offer a superior prediction ability. The calibration set coefficient of determination of 0.6599 and validation set coefficient of determination of 0.8221 were higher than that of the random sampling model by 9.20% and 10.90%, respectively. The root mean square error (RMSE) of 0.0365 and relative error (RE) of 0.0626 were lower than that of the random sampling model by 17.23% and 17.09%, respectively. Dividing the calibration set and validation set by the equidistant sampling method can improve the prediction accuracy of the hyperspectral model of apple canopy water content.

  6. The importance of the accuracy of the experimental data for the prediction of solubility

    Directory of Open Access Journals (Sweden)

    SLAVICA ERIĆ

    2010-04-01

    Full Text Available Aqueous solubility is an important factor influencing several aspects of the pharmacokinetic profile of a drug. Numerous publications present different methodologies for the development of reliable computational models for the prediction of solubility from structure. The quality of such models can be significantly affected by the accuracy of the employed experimental solubility data. In this work, the importance of the accuracy of the experimental solubility data used for model training was investigated. Three data sets were used as training sets – data set 1, containing solubility data collected from various literature sources using a few criteria (n = 319, data set 2, created by substituting 28 values from data set 1 with uniformly determined experimental data from one laboratory (n = 319, and data set 3, created by including 56 additional components, for which the solubility was also determined under uniform conditions in the same laboratory, in the data set 2 (n = 375. The selection of the most significant descriptors was performed by the heuristic method, using one-parameter and multi-parameter analysis. The correlations between the most significant descriptors and solubility were established using multi-linear regression analysis (MLR for all three investigated data sets. Notable differences were observed between the equations corresponding to different data sets, suggesting that models updated with new experimental data need to be additionally optimized. It was successfully shown that the inclusion of uniform experimental data consistently leads to an improvement in the correlation coefficients. These findings contribute to an emerging consensus that improving the reliability of solubility prediction requires the inclusion of many diverse compounds for which solubility was measured under standardized conditions in the data set.

  7. Increasing the predictive accuracy of amyloid-β blood-borne biomarkers in Alzheimer's disease.

    Science.gov (United States)

    Watt, Andrew D; Perez, Keyla A; Faux, Noel G; Pike, Kerryn E; Rowe, Christopher C; Bourgeat, Pierrick; Salvado, Olivier; Masters, Colin L; Villemagne, Victor L; Barnham, Kevin J

    2011-01-01

    Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-β (Aβ) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-Aβ marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of Aβ species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of Aβ. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of Aβ.

  8. Accuracy of formulas used to predict post-transfusion packed cell volume rise in anemic dogs.

    Science.gov (United States)

    Short, Jacqueline L; Diehl, Shenandoah; Seshadri, Ravi; Serrano, Sergi

    2012-08-01

    To assess the accuracy of published formulas used to guide packed red blood cell (pRBC) transfusions in anemic dogs and to compare the predicted rise in packed cell volume (PCV) to the actual post-transfusion rise in PCV. Prospective observational study from April 2009 through July 2009. A small animal emergency and specialty hospital. Thirty-one anemic client-owned dogs that received pRBC transfusions for treatment of anemia. None Four formulas were evaluated to determine their predictive ability with respect to rise in PCV following transfusion with pRBC. Post-transfusion rise in PCV were compared to calculated rise in PCV using 4 different formulas. Bias and limits of agreement were investigated using Bland-Altman analyses. Accuracy of existing formulas to predict rise in PCV following transfusion varied significantly. Formula 1 (volume to be transfused [VT] [mL] = 1 mL × % PCV rise × kg body weight [BW]) overestimated the expected rise in PCV (mean difference, 6.30), while formula 2 (VT [mL] = 2 mL ×% PCV rise × kg BW) underestimated the rise in PCV (mean difference, -3.01). Formula 3 (VT [mL] = 90 mL × kg BW × [(desired PCV - Patient PCV)/PCV of donor blood]) and formula 4 (VT [mL] = 1.5 mL ×% PCV rise × kg BW) performed well (mean difference 0.23 and 0.09, respectively) in predicting rise in PCV following pRBC transfusion. Agreement between 2 formulas, "VT (mL) = kg BW × blood volume (90 mL) × [(desired PCV - recipient PCV)/Donor PCV]" and "VT (mL) = 1.5 ×desired rise in PCV × kg BW," was found when they were compared to the actual rise in PCV following pRBC transfusion in anemic dogs. Further research is warranted to determine whether these formulas perform similarly well for other species. © Veterinary Emergency and Critical Care Society 2012.

  9. The Accuracy of Urinalysis in Predicting Intra-Abdominal Injury Following Blunt Traumas

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    Anita Sabzghabaei

    2016-01-01

    Full Text Available Introduction: In cases of blunt abdominal traumas, predicting the possible intra-abdominal injuries is still a challenge for the physicians involved with these patients. Therefore, this study was designed, to evaluate the accuracy of urinalysis in predicting intra-abdominal injuries. Methods: Patients aged 15 to 65 years with blunt abdominal trauma who were admitted to emergency departments were enrolled. Abdominopelvic computed tomography (CT scan with intravenous contrast and urinalysis were requested for all the included patients. Demographic data, trauma mechanism, the results of urinalysis, and the results of abdominopelvic CT scan were gathered. Finally, the correlation between the results of abdominopelvic CT scan, and urinalysis was determined. Urinalysis was considered positive in case of at least one positive value in gross appearance, blood in dipstick, or red blood cell count. Results: 325 patients with blunt abdominal trauma were admitted to the emergency departments (83% male with the mean age of 32.63±17.48 years. Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios of urinalysis, were 77.9% (95% CI: 69.6-84.4, 58.5% (95% CI: 51.2-65.5, 56% (95% CI: 48.5-63.3, 79.6% (95% CI: 71.8-85.7, 1.27% (95% CI: 1.30-1.57, and 0.25% (95% CI: 0.18-0.36, respectively. Conclusion: The diagnostic value of urinalysis in prediction of blunt traumatic intra-abdominal injuries is low and it seems that it should be considered as an adjuvant diagnostic tool, in conjunction with other sources such as clinical findings and imaging.

  10. The Accuracy of Urinalysis in Predicting Intra-Abdominal Injury Following Blunt Traumas.

    Science.gov (United States)

    Sabzghabaei, Anita; Shojaee, Majid; Safari, Saeed; Hatamabadi, Hamid Reza; Shirvani, Reza

    2016-01-01

    In cases of blunt abdominal traumas, predicting the possible intra-abdominal injuries is still a challenge for the physicians involved with these patients. Therefore, this study was designed, to evaluate the accuracy of urinalysis in predicting intra-abdominal injuries. Patients aged 15 to 65 years with blunt abdominal trauma who were admitted to emergency departments were enrolled. Abdominopelvic computed tomography (CT) scan with intravenous contrast and urinalysis were requested for all the included patients. Demographic data, trauma mechanism, the results of urinalysis, and the results of abdominopelvic CT scan were gathered. Finally, the correlation between the results of abdominopelvic CT scan, and urinalysis was determined. Urinalysis was considered positive in case of at least one positive value in gross appearance, blood in dipstick, or red blood cell count. 325 patients with blunt abdominal trauma were admitted to the emergency departments (83% male with the mean age of 32.63±17.48 years). Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios of urinalysis, were 77.9% (95% CI: 69.6-84.4), 58.5% (95% CI: 51.2-65.5), 56% (95% CI: 48.5-63.3), 79.6% (95% CI: 71.8-85.7), 1.27% (95% CI: 1.30-1.57), and 0.25% (95% CI: 0.18-0.36), respectively. The diagnostic value of urinalysis in prediction of blunt traumatic intra-abdominal injuries is low and it seems that it should be considered as an adjuvant diagnostic tool, in conjunction with other sources such as clinical findings and imaging.

  11. Prediction of renal function (GFR) from cystatin C and creatinine in children: Body cell mass increases accuracy of the estimate

    DEFF Research Database (Denmark)

    Andersen, Trine Borup; Jødal, Lars; Bøgsted, Martin

    using robust regression in a forward, stepwise procedure. GFR (mL/min) was the dependent variable. The accuracy and precision of the prediction model were compared to other prediction models from the literature, using k-fold cross-validation. Local constants and coefficients were calculated for all...

  12. Comparison of the accuracy of three algorithms in predicting accessory pathways among adult Wolff-Parkinson-White syndrome patients.

    Science.gov (United States)

    Maden, Orhan; Balci, Kevser Gülcihan; Selcuk, Mehmet Timur; Balci, Mustafa Mücahit; Açar, Burak; Unal, Sefa; Kara, Meryem; Selcuk, Hatice

    2015-12-01

    The aim of this study was to investigate the accuracy of three algorithms in predicting accessory pathway locations in adult patients with Wolff-Parkinson-White syndrome in Turkish population. A total of 207 adult patients with Wolff-Parkinson-White syndrome were retrospectively analyzed. The most preexcited 12-lead electrocardiogram in sinus rhythm was used for analysis. Two investigators blinded to the patient data used three algorithms for prediction of accessory pathway location. Among all locations, 48.5% were left-sided, 44% were right-sided, and 7.5% were located in the midseptum or anteroseptum. When only exact locations were accepted as match, predictive accuracy for Chiang was 71.5%, 72.4% for d'Avila, and 71.5% for Arruda. The percentage of predictive accuracy of all algorithms did not differ between the algorithms (p = 1.000; p = 0.875; p = 0.885, respectively). The best algorithm for prediction of right-sided, left-sided, and anteroseptal and midseptal accessory pathways was Arruda (p algorithms were similar in predicting accessory pathway location and the predicted accuracy was lower than previously reported by their authors. However, according to the accessory pathway site, the algorithm designed by Arruda et al. showed better predictions than the other algorithms and using this algorithm may provide advantages before a planned ablation.

  13. Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder

    DEFF Research Database (Denmark)

    Maier, Robert; Moser, Gerhard; Chen, Guo-Bo

    2015-01-01

    Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk...... number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low...

  14. Diagnostic accuracy of the STRATIFY clinical prediction rule for falls: A systematic review and meta-analysis

    LENUS (Irish Health Repository)

    Billington, Jennifer

    2012-08-07

    AbstractBackgroundThe STRATIFY score is a clinical prediction rule (CPR) derived to assist clinicians to identify patients at risk of falling. The purpose of this systematic review and meta-analysis is to determine the overall diagnostic accuracy of the STRATIFY rule across a variety of clinical settings.MethodsA literature search was performed to identify all studies that validated the STRATIFY rule. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. A STRATIFY score of ≥2 points was used to identify individuals at higher risk of falling. All included studies were combined using a bivariate random effects model to generate pooled sensitivity and specificity of STRATIFY at ≥2 points. Heterogeneity was assessed using the variance of logit transformed sensitivity and specificity.ResultsSeventeen studies were included in our meta-analysis, incorporating 11,378 patients. At a score ≥2 points, the STRATIFY rule is more useful at ruling out falls in those classified as low risk, with a greater pooled sensitivity estimate (0.67, 95% CI 0.52–0.80) than specificity (0.57, 95% CI 0.45 – 0.69). The sensitivity analysis which examined the performance of the rule in different settings and subgroups also showed broadly comparable results, indicating that the STRATIFY rule performs in a similar manner across a variety of different ‘at risk’ patient groups in different clinical settings.ConclusionThis systematic review shows that the diagnostic accuracy of the STRATIFY rule is limited and should not be used in isolation for identifying individuals at high risk of falls in clinical practice.

  15. Evaluation of Accuracy of Calculational Prediction of Criticality Based on ICSBEP Handbook Experiments

    International Nuclear Information System (INIS)

    Golovko, Yury; Rozhikhin, Yevgeniy; Tsibulya, Anatoly; Koscheev, Vladimir

    2008-01-01

    Experiments with plutonium, low enriched uranium and uranium-233 from the ICSBEP Handbook are being considered in this paper. Among these experiments it was selected only those, which seem to be the most relevant to the evaluation of uncertainty of critical mass of mixtures of plutonium or low enriched uranium or uranium-233 with light water. All selected experiments were examined and covariance matrices of criticality uncertainties were developed along with some uncertainties were revised. Statistical analysis of these experiments was performed and some contradictions were discovered and eliminated. Evaluation of accuracy of prediction of criticality calculations was performed using the internally consistent set of experiments with plutonium, low enriched uranium and uranium-233 remained after the statistical analyses. The application objects for the evaluation of calculational prediction of criticality were water-reflected spherical systems of homogeneous aqueous mixtures of plutonium or low enriched uranium or uranium-233 of different concentrations which are simplified models of apparatus of external fuel cycle. It is shows that the procedure allows to considerably reduce uncertainty in k eff caused by the uncertainties in neutron cross-sections. Also it is shows that the results are practically independent of initial covariance matrices of nuclear data uncertainties. (authors)

  16. The diagnostic accuracy of endovaginal and transperineal ultrasound for detecting anal sphincter defects: The PREDICT study

    Energy Technology Data Exchange (ETDEWEB)

    Roos, A.-M., E-mail: annemarie.roos@gmail.com [Department of Obstetrics and Gynaecology, Mayday University Hospital, Croydon (United Kingdom); Abdool, Z. [Department of Obstetrics and Gynaecology, University of Pretoria, Pretoria (South Africa); Sultan, A.H.; Thakar, R. [Department of Obstetrics and Gynaecology, Mayday University Hospital, Croydon (United Kingdom)

    2011-07-15

    Aim: To determine the accuracy and predictive value of transperineal (TPU) and endovaginal ultrasound (EVU) in the detection of anal sphincter defects in women with obstetric anal sphincter injuries and/or postpartum symptoms of faecal incontinence. Materials and methods: One hundred and sixty-five women were recruited, four women were excluded as they were seen years after their last delivery. TPU and EVU, followed by endonanal ultrasound (EAU), were performed using the B and K Viking 2400 scanner. Sensitivity and specificity, as well as predictive values with 95% confidence intervals, for detecting anal sphincter defects were calculated for EVU and TPU, using EAU as the reference standard. Results: On EAU a defect was found in 42 (26%) women: 39 (93%) had an external (EAS) and 23 (55%) an internal anal sphincter (IAS) defect. Analysable images of one level of the EAS combined with an analysable IAS were available in 140 (87%) women for EVU and in 131 (81%) for TPU. The sensitivity and specificity for the detection of any defect was 48% (30-67%) and 85% (77-91%) for EVU and 64% (44-81%) and 85% (77-91%) for TPU, respectively. Conclusion: Although EAU using a rotating endoprobe is the validated reference standard in the identification of anal sphincter defects, it is not universally available. However while TPU and/or EVU with conventional ultrasound probes can be useful in identifying normality, for clinical purposes they are not sensitive enough to identify an underlying sphincter defect.

  17. The diagnostic accuracy of endovaginal and transperineal ultrasound for detecting anal sphincter defects: The PREDICT study

    International Nuclear Information System (INIS)

    Roos, A.-M.; Abdool, Z.; Sultan, A.H.; Thakar, R.

    2011-01-01

    Aim: To determine the accuracy and predictive value of transperineal (TPU) and endovaginal ultrasound (EVU) in the detection of anal sphincter defects in women with obstetric anal sphincter injuries and/or postpartum symptoms of faecal incontinence. Materials and methods: One hundred and sixty-five women were recruited, four women were excluded as they were seen years after their last delivery. TPU and EVU, followed by endonanal ultrasound (EAU), were performed using the B and K Viking 2400 scanner. Sensitivity and specificity, as well as predictive values with 95% confidence intervals, for detecting anal sphincter defects were calculated for EVU and TPU, using EAU as the reference standard. Results: On EAU a defect was found in 42 (26%) women: 39 (93%) had an external (EAS) and 23 (55%) an internal anal sphincter (IAS) defect. Analysable images of one level of the EAS combined with an analysable IAS were available in 140 (87%) women for EVU and in 131 (81%) for TPU. The sensitivity and specificity for the detection of any defect was 48% (30-67%) and 85% (77-91%) for EVU and 64% (44-81%) and 85% (77-91%) for TPU, respectively. Conclusion: Although EAU using a rotating endoprobe is the validated reference standard in the identification of anal sphincter defects, it is not universally available. However while TPU and/or EVU with conventional ultrasound probes can be useful in identifying normality, for clinical purposes they are not sensitive enough to identify an underlying sphincter defect.

  18. Accuracy test for link prediction in terms of similarity index: The case of WS and BA models

    Science.gov (United States)

    Ahn, Min-Woo; Jung, Woo-Sung

    2015-07-01

    Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction with regard to network models. In this paper, we thus apply link prediction to two network models: The Watts-Strogatz (WS) model and Barabási-Albert (BA) model. We attempt to gain a better understanding of the relation between accuracy and each network parameter (mean degree, the number of nodes and the rewiring probability in the WS model) through network models. Six similarity indices are used, with precision and area under the ROC curve (AUC) value as the accuracy metrics. We observe a positive correlation between mean degree and accuracy, and size independence of the AUC value.

  19. The use of imprecise processing to improve accuracy in weather and climate prediction

    Energy Technology Data Exchange (ETDEWEB)

    Düben, Peter D., E-mail: dueben@atm.ox.ac.uk [University of Oxford, Atmospheric, Oceanic and Planetary Physics (United Kingdom); McNamara, Hugh [University of Oxford, Mathematical Institute (United Kingdom); Palmer, T.N. [University of Oxford, Atmospheric, Oceanic and Planetary Physics (United Kingdom)

    2014-08-15

    The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing bit-reproducibility and precision in exchange for improvements in performance and potentially accuracy of forecasts, due to a reduction in power consumption that could allow higher resolution. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud-resolving atmospheric modelling. The impact of both hardware induced faults and low precision arithmetic is tested using the Lorenz '96 model and the dynamical core of a global atmosphere model. In the Lorenz '96 model there is a natural scale separation; the spectral discretisation used in the dynamical core also allows large and small scale dynamics to be treated separately within the code. Such scale separation allows the impact of lower-accuracy arithmetic to be restricted to components close to the truncation scales and hence close to the necessarily inexact parametrised representations of unresolved processes. By contrast, the larger scales are calculated using high precision deterministic arithmetic. Hardware faults from stochastic processors are emulated using a bit-flip model with different fault rates. Our simulations show that both approaches to inexact calculations do not substantially affect the large scale behaviour, provided they are restricted to act only on smaller scales. By contrast, results from the Lorenz '96 simulations are superior when small scales are calculated on an emulated stochastic processor than when those small scales are parametrised. This suggests that inexact calculations at the small scale could reduce

  20. The use of imprecise processing to improve accuracy in weather and climate prediction

    International Nuclear Information System (INIS)

    Düben, Peter D.; McNamara, Hugh; Palmer, T.N.

    2014-01-01

    The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing bit-reproducibility and precision in exchange for improvements in performance and potentially accuracy of forecasts, due to a reduction in power consumption that could allow higher resolution. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud-resolving atmospheric modelling. The impact of both hardware induced faults and low precision arithmetic is tested using the Lorenz '96 model and the dynamical core of a global atmosphere model. In the Lorenz '96 model there is a natural scale separation; the spectral discretisation used in the dynamical core also allows large and small scale dynamics to be treated separately within the code. Such scale separation allows the impact of lower-accuracy arithmetic to be restricted to components close to the truncation scales and hence close to the necessarily inexact parametrised representations of unresolved processes. By contrast, the larger scales are calculated using high precision deterministic arithmetic. Hardware faults from stochastic processors are emulated using a bit-flip model with different fault rates. Our simulations show that both approaches to inexact calculations do not substantially affect the large scale behaviour, provided they are restricted to act only on smaller scales. By contrast, results from the Lorenz '96 simulations are superior when small scales are calculated on an emulated stochastic processor than when those small scales are parametrised. This suggests that inexact calculations at the small scale could reduce computation and

  1. Accuracy of High-Resolution MRI with Lumen Distention in Rectal Cancer Staging and Circumferential Margin Involvement Prediction

    International Nuclear Information System (INIS)

    Iannicelli, Elsa; Di Renzo, Sara; Ferri, Mario; Pilozzi, Emanuela; Di Girolamo, Marco; Sapori, Alessandra; Ziparo, Vincenzo; David, Vincenzo

    2014-01-01

    To evaluate the accuracy of magnetic resonance imaging (MRI) with lumen distention for rectal cancer staging and circumferential resection margin (CRM) involvement prediction. Seventy-three patients with primary rectal cancer underwent high-resolution MRI with a phased-array coil performed using 60-80 mL room air rectal distention, 1-3 weeks before surgery. MRI results were compared to postoperative histopathological findings. The overall MRI T staging accuracy was calculated. CRM involvement prediction and the N staging, the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were assessed for each T stage. The agreement between MRI and histological results was assessed using weighted-kappa statistics. The overall MRI accuracy for T staging was 93.6% (k = 0.85). The accuracy, sensitivity, specificity, PPV and NPV for each T stage were as follows: 91.8%, 86.2%, 95.5%, 92.6% and 91.3% for the group ≤ T2; 90.4%, 94.6%, 86.1%, 87.5% and 94% for T3; 98,6%, 85.7%, 100%, 100% and 98.5% for T4, respectively. The predictive CRM accuracy was 94.5% (k = 0.86); the sensitivity, specificity, PPV and NPV were 89.5%, 96.3%, 89.5%, and 96.3% respectively. The N staging accuracy was 68.49% (k = 0.4). MRI performed with rectal lumen distention has proved to be an effective technique both for rectal cancer staging and involved CRM predicting

  2. Accuracy of High-Resolution MRI with Lumen Distention in Rectal Cancer Staging and Circumferential Margin Involvement Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Iannicelli, Elsa; Di Renzo, Sara [Radiology Institute, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); Department of Surgical and Medical Sciences and Translational Medicine, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); Ferri, Mario [Department of Surgical and Medical Sciences and Translational Medicine, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); Pilozzi, Emanuela [Department of Clinical and Molecular Sciences, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); Di Girolamo, Marco; Sapori, Alessandra [Radiology Institute, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); Department of Surgical and Medical Sciences and Translational Medicine, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); Ziparo, Vincenzo [Department of Surgical and Medical Sciences and Translational Medicine, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); David, Vincenzo [Radiology Institute, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy); Department of Surgical and Medical Sciences and Translational Medicine, Faculty of Medicine and Psychology, University of Rome, Sapienza, Sant' Andrea Hospital, Rome 00189 (Italy)

    2014-07-01

    To evaluate the accuracy of magnetic resonance imaging (MRI) with lumen distention for rectal cancer staging and circumferential resection margin (CRM) involvement prediction. Seventy-three patients with primary rectal cancer underwent high-resolution MRI with a phased-array coil performed using 60-80 mL room air rectal distention, 1-3 weeks before surgery. MRI results were compared to postoperative histopathological findings. The overall MRI T staging accuracy was calculated. CRM involvement prediction and the N staging, the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were assessed for each T stage. The agreement between MRI and histological results was assessed using weighted-kappa statistics. The overall MRI accuracy for T staging was 93.6% (k = 0.85). The accuracy, sensitivity, specificity, PPV and NPV for each T stage were as follows: 91.8%, 86.2%, 95.5%, 92.6% and 91.3% for the group ≤ T2; 90.4%, 94.6%, 86.1%, 87.5% and 94% for T3; 98,6%, 85.7%, 100%, 100% and 98.5% for T4, respectively. The predictive CRM accuracy was 94.5% (k = 0.86); the sensitivity, specificity, PPV and NPV were 89.5%, 96.3%, 89.5%, and 96.3% respectively. The N staging accuracy was 68.49% (k = 0.4). MRI performed with rectal lumen distention has proved to be an effective technique both for rectal cancer staging and involved CRM predicting.

  3. Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

    Science.gov (United States)

    Lorenz, Aaron J

    2013-03-01

    Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS). It is well known that because alleles are replicated across individuals in quantitative trait loci mapping and MAS, more resources should be allocated to increasing population size compared with phenotypic selection. Genomic selection is a form of MAS using all marker information simultaneously to predict individual genetic values for complex traits and has widely been found superior to MAS. No studies have explicitly investigated how resource allocation decisions affect success of genomic selection. My objective was to study the effect of resource allocation on response to MAS and genomic selection in a single biparental population of doubled haploid lines by using computer simulation. Simulation results were compared with previously derived formulas for the calculation of prediction accuracy under different levels of heritability and population size. Response of prediction accuracy to resource allocation strategies differed between genomic selection models (ridge regression best linear unbiased prediction [RR-BLUP], BayesCπ) and multiple linear regression using ordinary least-squares estimation (OLS), leading to different optimal resource allocation choices between OLS and RR-BLUP. For OLS, it was always advantageous to maximize population size at the expense of replication, but a high degree of flexibility was observed for RR-BLUP. Prediction accuracy of doubled haploid lines included in the training set was much greater than of those excluded from the training set, so there was little benefit to phenotyping only a subset of the lines genotyped. Finally, observed prediction accuracies in the simulation compared well to calculated prediction accuracies, indicating these theoretical formulas are useful for making resource allocation

  4. Predictive Accuracy of Sweep Frequency Impedance Technology in Identifying Conductive Conditions in Newborns.

    Science.gov (United States)

    Aithal, Venkatesh; Kei, Joseph; Driscoll, Carlie; Murakoshi, Michio; Wada, Hiroshi

    2018-02-01

    Diagnosing conductive conditions in newborns is challenging for both audiologists and otolaryngologists. Although high-frequency tympanometry (HFT), acoustic stapedial reflex tests, and wideband absorbance measures are useful diagnostic tools, there is performance measure variability in their detection of middle ear conditions. Additional diagnostic sensitivity and specificity measures gained through new technology such as sweep frequency impedance (SFI) measures may assist in the diagnosis of middle ear dysfunction in newborns. The purpose of this study was to determine the test performance of SFI to predict the status of the outer and middle ear in newborns against commonly used reference standards. Automated auditory brainstem response (AABR), HFT (1000 Hz), transient evoked otoacoustic emission (TEOAE), distortion product otoacoustic emission (DPOAE), and SFI tests were administered to the study sample. A total of 188 neonates (98 males and 90 females) with a mean gestational age of 39.4 weeks were included in the sample. Mean age at the time of testing was 44.4 hr. Diagnostic accuracy of SFI was assessed in terms of its ability to identify conductive conditions in neonates when compared with nine different reference standards (including four single tests [AABR, HFT, TEOAE, and DPOAE] and five test batteries [HFT + DPOAE, HFT + TEOAE, DPOAE + TEOAE, DPOAE + AABR, and TEOAE + AABR]), using receiver operating characteristic (ROC) analysis and traditional test performance measures such as sensitivity and specificity. The test performance of SFI against the test battery reference standard of HFT + DPOAE and single reference standard of HFT was high with an area under the ROC curve (AROC) of 0.87 and 0.82, respectively. Although the HFT + DPOAE test battery reference standard performed better than the HFT reference standard in predicting middle ear conductive conditions in neonates, the difference in AROC was not significant. Further analysis revealed that the

  5. Accuracy of cone-beam computed tomography in predicting the diameter of unerupted teeth.

    Science.gov (United States)

    Nguyen, Emerald; Boychuk, Darrell; Orellana, Maria

    2011-08-01

    An accurate prediction of the mesiodistal diameter (MDD) of the erupting permanent teeth is essential in orthodontic diagnosis and treatment planning during the mixed dentition period. Our objective was to test the accuracy and reproducibility of cone-beam computed tomography (CBCT) in predicting the MDD of unerupted teeth. Our secondary objective was to determine the accuracy and reproducibility of 3 viewing methods by using 2 CBCT software programs, InVivoDental (version 4.0; Anatomage, San Jose, Calif) and CBWorks (version 3.0, CyberMed, Seoul, Korea) in measuring the MDD of teeth in models simulating unerupted teeth. CBCT data were collected on the CB MercuRay (Hitachi Medical Corporation, Tokyo, Japan). Models of unerupted teeth (n = 25), created by embedding 25 tooth samples into a polydimethylsiloxane polymer with a similar density to tissues surrounding teeth, were scanned and measured by 2 investigators. Repeated MDD measurements of each sample were made by using 3 CBCT viewing methods: InVivo Section, InVivo Volume Render (both Anatomage), and CBWorks Volume Render (version 3.0, CyberMed). These measurements were then compared with the MDD physically measured by digital calipers before the teeth were embedded and scanned. All 3 of the new methods had mean measurements that were statistically significantly less (P <0.0001) than the physical method, adjusting for investigator and tooth effects. Specifically, InVivo Section measurements were 0.3 mm (95% CI, -0.4 to -0.2) less than the measurements with calipers, InVivo Volume Render measurements were 0.5 mm less (95% CI, -0.6 to -0.4) than those with calipers, and CBWorks Volume Render measurements were 0.4 mm less (95% CI, -0.4 to -0.3) than those with calipers. Overall, there were high correlation values among the 3 viewing methods, indicating that CBCT can be used to measure the MDD of unerupted teeth. The InVivo Section method had the greatest correlation with the calipers. Copyright © 2011 American

  6. Predictive accuracy of changes in transvaginal sonographic cervical length over time for preterm birth: a systematic review and metaanalysis.

    Science.gov (United States)

    Conde-Agudelo, Agustin; Romero, Roberto

    2015-12-01

    To determine the accuracy of changes in transvaginal sonographic cervical length over time in predicting preterm birth in women with singleton and twin gestations. PubMed, Embase, Cinahl, Lilacs, and Medion (all from inception to June 30, 2015), bibliographies, Google scholar, and conference proceedings. Cohort or cross-sectional studies reporting on the predictive accuracy for preterm birth of changes in cervical length over time. Two reviewers independently selected studies, assessed the risk of bias, and extracted the data. Summary receiver-operating characteristic curves, pooled sensitivities and specificities, and summary likelihood ratios were generated. Fourteen studies met the inclusion criteria, of which 7 provided data on singleton gestations (3374 women) and 8 on twin gestations (1024 women). Among women with singleton gestations, the shortening of cervical length over time had a low predictive accuracy for preterm birth at predictive accuracy for preterm birth at predictive accuracies for preterm birth of cervical length shortening over time and the single initial and/or final cervical length measurement in 8 of 11 studies that provided data for making these comparisons. In the largest and highest-quality study, a single measurement of cervical length obtained at 24 or 28 weeks of gestation was significantly more predictive of preterm birth than any decrease in cervical length between these gestational ages. Change in transvaginal sonographic cervical length over time is not a clinically useful test to predict preterm birth in women with singleton or twin gestations. A single cervical length measurement obtained between 18 and 24 weeks of gestation appears to be a better test to predict preterm birth than changes in cervical length over time. Published by Elsevier Inc.

  7. The diagnostic accuracy of endovaginal and transperineal ultrasound for detecting anal sphincter defects: The PREDICT study.

    Science.gov (United States)

    Roos, A-M; Abdool, Z; Sultan, A H; Thakar, R

    2011-07-01

    To determine the accuracy and predictive value of transperineal (TPU) and endovaginal ultrasound (EVU) in the detection of anal sphincter defects in women with obstetric anal sphincter injuries and/or postpartum symptoms of faecal incontinence. One hundred and sixty-five women were recruited, four women were excluded as they were seen years after their last delivery. TPU and EVU, followed by endonanal ultrasound (EAU), were performed using the B&K Viking 2400 scanner. Sensitivity and specificity, as well as predictive values with 95% confidence intervals, for detecting anal sphincter defects were calculated for EVU and TPU, using EAU as the reference standard. On EAU a defect was found in 42 (26%) women: 39 (93%) had an external (EAS) and 23 (55%) an internal anal sphincter (IAS) defect. Analysable images of one level of the EAS combined with an analysable IAS were available in 140 (87%) women for EVU and in 131 (81%) for TPU. The sensitivity and specificity for the detection of any defect was 48% (30-67%) and 85% (77-91%) for EVU and 64% (44-81%) and 85% (77-91%) for TPU, respectively. Although EAU using a rotating endoprobe is the validated reference standard in the identification of anal sphincter defects, it is not universally available. However while TPU and/or EVU with conventional ultrasound probes can be useful in identifying normality, for clinical purposes they are not sensitive enough to identify an underlying sphincter defect. Copyright © 2011 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  8. Improve accuracy and sensibility in glycan structure prediction by matching glycan isotope abundance

    International Nuclear Information System (INIS)

    Xu Guang; Liu Xin; Liu Qingyan; Zhou Yanhong; Li Jianjun

    2012-01-01

    Highlights: ► A glycan isotope pattern recognition strategy for glycomics. ► A new data preprocessing procedure to detect ion peaks in a giving MS spectrum. ► A linear soft margin SVM classification for isotope pattern recognition. - Abstract: Mass Spectrometry (MS) is a powerful technique for the determination of glycan structures and is capable of providing qualitative and quantitative information. Recent development in computational method offers an opportunity to use glycan structure databases and de novo algorithms for extracting valuable information from MS or MS/MS data. However, detecting low-intensity peaks that are buried in noisy data sets is still a challenge and an algorithm for accurate prediction and annotation of glycan structures from MS data is highly desirable. The present study describes a novel algorithm for glycan structure prediction by matching glycan isotope abundance (mGIA), which takes isotope masses, abundances, and spacing into account. We constructed a comprehensive database containing 808 glycan compositions and their corresponding isotope abundance. Unlike most previously reported methods, not only did we take into count the m/z values of the peaks but also their corresponding logarithmic Euclidean distance of the calculated and detected isotope vectors. Evaluation against a linear classifier, obtained by training mGIA algorithm with datasets of three different human tissue samples from Consortium for Functional Glycomics (CFG) in association with Support Vector Machine (SVM), was proposed to improve the accuracy of automatic glycan structure annotation. In addition, an effective data preprocessing procedure, including baseline subtraction, smoothing, peak centroiding and composition matching for extracting correct isotope profiles from MS data was incorporated. The algorithm was validated by analyzing the mouse kidney MS data from CFG, resulting in the identification of 6 more glycan compositions than the previous annotation

  9. Improving accuracy of genomic prediction in Brangus cattle by adding animals with imputed low-density SNP genotypes.

    Science.gov (United States)

    Lopes, F B; Wu, X-L; Li, H; Xu, J; Perkins, T; Genho, J; Ferretti, R; Tait, R G; Bauck, S; Rosa, G J M

    2018-02-01

    Reliable genomic prediction of breeding values for quantitative traits requires the availability of sufficient number of animals with genotypes and phenotypes in the training set. As of 31 October 2016, there were 3,797 Brangus animals with genotypes and phenotypes. These Brangus animals were genotyped using different commercial SNP chips. Of them, the largest group consisted of 1,535 animals genotyped by the GGP-LDV4 SNP chip. The remaining 2,262 genotypes were imputed to the SNP content of the GGP-LDV4 chip, so that the number of animals available for training the genomic prediction models was more than doubled. The present study showed that the pooling of animals with both original or imputed 40K SNP genotypes substantially increased genomic prediction accuracies on the ten traits. By supplementing imputed genotypes, the relative gains in genomic prediction accuracies on estimated breeding values (EBV) were from 12.60% to 31.27%, and the relative gain in genomic prediction accuracies on de-regressed EBV was slightly small (i.e. 0.87%-18.75%). The present study also compared the performance of five genomic prediction models and two cross-validation methods. The five genomic models predicted EBV and de-regressed EBV of the ten traits similarly well. Of the two cross-validation methods, leave-one-out cross-validation maximized the number of animals at the stage of training for genomic prediction. Genomic prediction accuracy (GPA) on the ten quantitative traits was validated in 1,106 newly genotyped Brangus animals based on the SNP effects estimated in the previous set of 3,797 Brangus animals, and they were slightly lower than GPA in the original data. The present study was the first to leverage currently available genotype and phenotype resources in order to harness genomic prediction in Brangus beef cattle. © 2018 Blackwell Verlag GmbH.

  10. Eyeball Position in Facial Approximation: Accuracy of Methods for Predicting Globe Positioning in Lateral View.

    Science.gov (United States)

    Zednikova Mala, Pavla; Veleminska, Jana

    2018-01-01

    This study measured the accuracy of traditional and validated newly proposed methods for globe positioning in lateral view. Eighty lateral head cephalograms of adult subjects from Central Europe were taken, and the actual and predicted dimensions were compared. The anteroposterior eyeball position was estimated as the most accurate method based on the proportion of the orbital height (SEE = 1.9 mm) and was followed by the "tangent to the iris method" showing SEE = 2.4 mm. The traditional "tangent to the cornea method" underestimated the eyeball projection by SEE = 5.8 mm. Concerning the superoinferior eyeball position, the results showed a deviation from a central to a more superior position by 0.3 mm, on average, and the traditional method of central positioning of the globe could not be rejected as inaccurate (SEE = 0.3 mm). Based on regression analyzes or proportionality of the orbital height, the SEE = 2.1 mm. © 2017 American Academy of Forensic Sciences.

  11. Accuracy of Genomic Prediction in a Commercial Perennial Ryegrass Breeding Program

    Directory of Open Access Journals (Sweden)

    Dario Fè

    2016-11-01

    Full Text Available The implementation of genomic selection (GS in plant breeding, so far, has been mainly evaluated in crops farmed as homogeneous varieties, and the results have been generally positive. Fewer results are available for species, such as forage grasses, that are grown as heterogenous families (developed from multiparent crosses in which the control of the genetic variation is far more complex. Here we test the potential for implementing GS in the breeding of perennial ryegrass ( L. using empirical data from a commercial forage breeding program. Biparental F and multiparental synthetic (SYN families of diploid perennial ryegrass were genotyped using genotyping-by-sequencing, and phenotypes for five different traits were analyzed. Genotypes were expressed as family allele frequencies, and phenotypes were recorded as family means. Different models for genomic prediction were compared by using practically relevant cross-validation strategies. All traits showed a highly significant level of genetic variance, which could be traced using the genotyping assay. While there was significant genotype × environment (G × E interaction for some traits, accuracies were high among F families and between biparental F and multiparental SYN families. We have demonstrated that the implementation of GS in grass breeding is now possible and presents an opportunity to make significant gains for various traits.

  12. The Promise and Peril of Predictive Analytics in Higher Education: A Landscape Analysis

    Science.gov (United States)

    Ekowo, Manuela; Palmer, Iris

    2016-01-01

    Predictive analytics in higher education is a hot-button topic among educators and administrators as institutions strive to better serve students by becoming more data-informed. In this paper, the authors describe how predictive analytics are used in higher education to identify students who need extra support, steer students in courses they will…

  13. Climatic associations of British species distributions show good transferability in time but low predictive accuracy for range change.

    Directory of Open Access Journals (Sweden)

    Giovanni Rapacciuolo

    Full Text Available Conservation planners often wish to predict how species distributions will change in response to environmental changes. Species distribution models (SDMs are the primary tool for making such predictions. Many methods are widely used; however, they all make simplifying assumptions, and predictions can therefore be subject to high uncertainty. With global change well underway, field records of observed range shifts are increasingly being used for testing SDM transferability. We used an unprecedented distribution dataset documenting recent range changes of British vascular plants, birds, and butterflies to test whether correlative SDMs based on climate change provide useful approximations of potential distribution shifts. We modelled past species distributions from climate using nine single techniques and a consensus approach, and projected the geographical extent of these models to a more recent time period based on climate change; we then compared model predictions with recent observed distributions in order to estimate the temporal transferability and prediction accuracy of our models. We also evaluated the relative effect of methodological and taxonomic variation on the performance of SDMs. Models showed good transferability in time when assessed using widespread metrics of accuracy. However, models had low accuracy to predict where occupancy status changed between time periods, especially for declining species. Model performance varied greatly among species within major taxa, but there was also considerable variation among modelling frameworks. Past climatic associations of British species distributions retain a high explanatory power when transferred to recent time--due to their accuracy to predict large areas retained by species--but fail to capture relevant predictors of change. We strongly emphasize the need for caution when using SDMs to predict shifts in species distributions: high explanatory power on temporally-independent records

  14. Empathic Accuracy in Male Adolescents with Conduct Disorder and Higher versus Lower Levels of Callous-Unemotional Traits.

    Science.gov (United States)

    Martin-Key, N; Brown, T; Fairchild, G

    2017-10-01

    Adolescents with disruptive behavior disorders are reported to show deficits in empathy and emotion recognition. However, prior studies have mainly used questionnaires to measure empathy or experimental paradigms that are lacking in ecological validity. We used an empathic accuracy (EA) task to study EA, emotion recognition, and affective empathy in 77 male adolescents aged 13-18 years: 37 with Conduct Disorder (CD) and 40 typically-developing controls. The CD sample was divided into higher callous-emotional traits (CD/CU+) and lower callous-unemotional traits (CD/CU-) subgroups using a median split. Participants watched films of actors recalling happy, sad, surprised, angry, disgusted or fearful autobiographical experiences and provided continuous ratings of emotional intensity (assessing EA), as well as naming the emotion (recognition) and reporting the emotion they experienced themselves (affective empathy). The CD and typically-developing groups did not significantly differ in EA and there were also no differences between the CD/CU+ and CD/CU- subgroups. Participants with CD were significantly less accurate than controls in recognizing sadness, fear, and disgust, all ps sadness, fear, and disgust relative to controls, all ps < 0.010, rs ≥ 0.33, whereas the CD/CU+ and CD/CU- subgroups did not differ in affective empathy. These results extend prior research by demonstrating affective empathy and emotion recognition deficits in adolescents with CD using a more ecologically-valid task, and challenge the view that affective empathy deficits are specific to CD/CU+.

  15. Quantitative accuracy of the simplified strong ion equation to predict serum pH in dogs.

    Science.gov (United States)

    Cave, N J; Koo, S T

    2015-01-01

    Electrochemical approach to the assessment of acid-base states should provide a better mechanistic explanation of the metabolic component than methods that consider only pH and carbon dioxide. Simplified strong ion equation (SSIE), using published dog-specific values, would predict the measured serum pH of diseased dogs. Ten dogs, hospitalized for various reasons. Prospective study of a convenience sample of a consecutive series of dogs admitted to the Massey University Veterinary Teaching Hospital (MUVTH), from which serum biochemistry and blood gas analyses were performed at the same time. Serum pH was calculated (Hcal+) using the SSIE, and published values for the concentration and dissociation constant for the nonvolatile weak acids (Atot and Ka ), and subsequently Hcal+ was compared with the dog's actual pH (Hmeasured+). To determine the source of discordance between Hcal+ and Hmeasured+, the calculations were repeated using a series of substituted values for Atot and Ka . The Hcal+ did not approximate the Hmeasured+ for any dog (P = 0.499, r(2) = 0.068), and was consistently more basic. Substituted values Atot and Ka did not significantly improve the accuracy (r(2) = 0.169 to <0.001). Substituting the effective SID (Atot-[HCO3-]) produced a strong association between Hcal+ and Hmeasured+ (r(2) = 0.977). Using the simplified strong ion equation and the published values for Atot and Ka does not appear to provide a quantitative explanation for the acid-base status of dogs. Efficacy of substituting the effective SID in the simplified strong ion equation suggests the error lies in calculating the SID. Copyright © 2015 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

  16. Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

    Science.gov (United States)

    Fang, Xingang; Bagui, Sikha; Bagui, Subhash

    2017-08-01

    The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Reduced Set of Virulence Genes Allows High Accuracy Prediction of Bacterial Pathogenicity in Humans

    Science.gov (United States)

    Iraola, Gregorio; Vazquez, Gustavo; Spangenberg, Lucía; Naya, Hugo

    2012-01-01

    Although there have been great advances in understanding bacterial pathogenesis, there is still a lack of integrative information about what makes a bacterium a human pathogen. The advent of high-throughput sequencing technologies has dramatically increased the amount of completed bacterial genomes, for both known human pathogenic and non-pathogenic strains; this information is now available to investigate genetic features that determine pathogenic phenotypes in bacteria. In this work we determined presence/absence patterns of different virulence-related genes among more than finished bacterial genomes from both human pathogenic and non-pathogenic strains, belonging to different taxonomic groups (i.e: Actinobacteria, Gammaproteobacteria, Firmicutes, etc.). An accuracy of 95% using a cross-fold validation scheme with in-fold feature selection is obtained when classifying human pathogens and non-pathogens. A reduced subset of highly informative genes () is presented and applied to an external validation set. The statistical model was implemented in the BacFier v1.0 software (freely available at ), that displays not only the prediction (pathogen/non-pathogen) and an associated probability for pathogenicity, but also the presence/absence vector for the analyzed genes, so it is possible to decipher the subset of virulence genes responsible for the classification on the analyzed genome. Furthermore, we discuss the biological relevance for bacterial pathogenesis of the core set of genes, corresponding to eight functional categories, all with evident and documented association with the phenotypes of interest. Also, we analyze which functional categories of virulence genes were more distinctive for pathogenicity in each taxonomic group, which seems to be a completely new kind of information and could lead to important evolutionary conclusions. PMID:22916122

  18. Accuracy of pre-operative hysteroscopic guided biopsy for predicting final pathology in uterine malignancies.

    Science.gov (United States)

    Martinelli, Fabio; Ditto, Antonino; Bogani, Giorgio; Signorelli, Mauro; Chiappa, Valentina; Lorusso, Domenica; Haeusler, Edward; Raspagliesi, Francesco

    2017-07-01

    To evaluate concordance (C) between pre-operative hysteroscopic-directed sampling and final pathology in uterine cancers. A retrospective cross-sectional evaluation of prospectively collected data of women who underwent hysterectomy for uterine malignancies and a previous hysteroscopic-guided biopsy was performed. Diagnostic concordance between pre-operative (hysteroscopic biopsy) and postoperative (uterine specimen) histology was evaluated. In endometrioid-endometrial cancers cases Kappa (k) statistics was applied to evaluate agreement for grading (G) between the preoperative and final pathology. A total 101 hysterectomies for uterine malignancies were evaluated. There were 23 non-endometrioid cancers: 7 serous (C:5/7, 71.4%); 10 carcinosarcomas (C:7/10, 70%, remaining 3 cases only epithelial component diagnosed); 3 clear cell (C:3/3, 100%); 3 sarcomas (C:3/3, 100%). In 78 cases an endometrioid endometrial cancer was found. In 63 cases there was a histological C (63/78, 80.8%) between hysteroscopic-guided biopsy and final pathology, while in 15 cases (19.2%) only hyperplasia (with/without atypia) was found preoperatively. Overall accuracy to detect endometrial cancer was 80.2%. In 50 out of 63 endometrial cancers (79.4%) grading was concordant. The overall level of agreement between preoperative and postoperative grading was "substantial" according to Kappa (k) statistics (k 0.64; 95% CI: 0.449-0.83; p < 0.001), as well as for G1 (0.679; 95% CI: 0.432-0.926; p < 0.001) and G3 (0.774; 94% CI: 0.534-1; p < 0.001), while for G2 (0.531; 95% CI: 0.286-0.777; p < 0.001) it was moderate. In our series we found an 80% C between pre-operative hysteroscopic-guided biopsy and final pathology, in uterine malignancies. Moreover, hysteroscopic biopsy accurately predicted endometrial cancer in 80% of cases and "substantially" predicted histological grading. Hysteroscopic-guided uterine sampling could be a useful tool to tailor treatment in patients with uterine

  19. Accuracy of liver function tests for predicting adverse maternal and fetal outcomes in women with preeclampsia: a systematic review

    NARCIS (Netherlands)

    Thangaratinam, Shakila; Koopmans, Corine M.; Iyengar, Shalini; Zamora, Javier; Ismail, Khaled M. K.; Mol, Ben W. J.; Khan, Khalid S.

    2011-01-01

    Background. Liver function tests are routinely performed in women as part of a battery of investigations to assess severity at admission and later to guide appropriate management. Objective. To determine the accuracy with which liver function tests predict complications in women with preeclampsia by

  20. Accuracy of liver function tests for predicting adverse maternal and fetal outcomes in women with preeclampsia : a systematic review

    NARCIS (Netherlands)

    Thangaratinam, Shakila; Koopmans, Corine M.; Iyengar, Shalini; Zamora, Javier; Ismail, Khaled M. K.; Mol, Ben W. J.; Khan, Khalid S.

    Background. Liver function tests are routinely performed in women as part of a battery of investigations to assess severity at admission and later to guide appropriate management. Objective. To determine the accuracy with which liver function tests predict complications in women with preeclampsia by

  1. Higher Levels of Psychopathy Predict Poorer Motor Control: Implications for Understanding the Psychopathy Construct

    OpenAIRE

    Robinson, Michael D.; Bresin, Konrad

    2014-01-01

    A review of the literature suggests that higher levels of psychopathy may be linked to less effective behavioral control. However, several commentators have urged caution in making statements of this type in the absence of direct evidence. In two studies (total N = 142), moment-to-moment accuracy in a motor control task was examined as a function of dimensional variations in psychopathy in an undergraduate population. As hypothesized, motor control was distinctively worse at higher levels of ...

  2. The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years.

    Science.gov (United States)

    Wang, Yu; Mette, Michael Florian; Miedaner, Thomas; Gottwald, Marlen; Wilde, Peer; Reif, Jochen C; Zhao, Yusheng

    2014-07-04

    Marker-assisted selection (MAS) and genomic selection (GS) based on genome-wide marker data provide powerful tools to predict the genotypic value of selection material in plant breeding. However, case-to-case optimization of these approaches is required to achieve maximum accuracy of prediction with reasonable input. Based on extended field evaluation data for grain yield, plant height, starch content and total pentosan content of elite hybrid rye derived from testcrosses involving two bi-parental populations that were genotyped with 1048 molecular markers, we compared the accuracy of prediction of MAS and GS in a cross-validation approach. MAS delivered generally lower and in addition potentially over-estimated accuracies of prediction than GS by ridge regression best linear unbiased prediction (RR-BLUP). The grade of relatedness of the plant material included in the estimation and test sets clearly affected the accuracy of prediction of GS. Within each of the two bi-parental populations, accuracies differed depending on the relatedness of the respective parental lines. Across populations, accuracy increased when both populations contributed to estimation and test set. In contrast, accuracy of prediction based on an estimation set from one population to a test set from the other population was low despite that the two bi-parental segregating populations under scrutiny shared one parental line. Limiting the number of locations or years in field testing reduced the accuracy of prediction of GS equally, supporting the view that to establish robust GS calibration models a sufficient number of test locations is of similar importance as extended testing for more than one year. In hybrid rye, genomic selection is superior to marker-assisted selection. However, it achieves high accuracies of prediction only for selection candidates closely related to the plant material evaluated in field trials, resulting in a rather pessimistic prognosis for distantly related material

  3. Best Practices for Mudweight Window Generation and Accuracy Assessment between Seismic Based Pore Pressure Prediction Methodologies for a Near-Salt Field in Mississippi Canyon, Gulf of Mexico

    Science.gov (United States)

    Mannon, Timothy Patrick, Jr.

    Improving well design has and always will be the primary goal in drilling operations in the oil and gas industry. Oil and gas plays are continuing to move into increasingly hostile drilling environments, including near and/or sub-salt proximities. The ability to reduce the risk and uncertainly involved in drilling operations in unconventional geologic settings starts with improving the techniques for mudweight window modeling. To address this issue, an analysis of wellbore stability and well design improvement has been conducted. This study will show a systematic approach to well design by focusing on best practices for mudweight window projection for a field in Mississippi Canyon, Gulf of Mexico. The field includes depleted reservoirs and is in close proximity of salt intrusions. Analysis of offset wells has been conducted in the interest of developing an accurate picture of the subsurface environment by making connections between depth, non-productive time (NPT) events, and mudweights used. Commonly practiced petrophysical methods of pore pressure, fracture pressure, and shear failure gradient prediction have been applied to key offset wells in order to enhance the well design for two proposed wells. For the first time in the literature, the accuracy of the commonly accepted, seismic interval velocity based and the relatively new, seismic frequency based methodologies for pore pressure prediction are qualitatively and quantitatively compared for accuracy. Accuracy standards will be based on the agreement of the seismic outputs to pressure data obtained while drilling and petrophysically based pore pressure outputs for each well. The results will show significantly higher accuracy for the seismic frequency based approach in wells that were in near/sub-salt environments and higher overall accuracy for all of the wells in the study as a whole.

  4. Development and application of a statistical methodology to evaluate the predictive accuracy of building energy baseline models

    Energy Technology Data Exchange (ETDEWEB)

    Granderson, Jessica [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Energy Technologies Area Div.; Price, Phillip N. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). Energy Technologies Area Div.

    2014-03-01

    This paper documents the development and application of a general statistical methodology to assess the accuracy of baseline energy models, focusing on its application to Measurement and Verification (M&V) of whole-­building energy savings. The methodology complements the principles addressed in resources such as ASHRAE Guideline 14 and the International Performance Measurement and Verification Protocol. It requires fitting a baseline model to data from a ``training period’’ and using the model to predict total electricity consumption during a subsequent ``prediction period.’’ We illustrate the methodology by evaluating five baseline models using data from 29 buildings. The training period and prediction period were varied, and model predictions of daily, weekly, and monthly energy consumption were compared to meter data to determine model accuracy. Several metrics were used to characterize the accuracy of the predictions, and in some cases the best-­performing model as judged by one metric was not the best performer when judged by another metric.

  5. Thoracic injury rule out criteria and NEXUS chest in predicting the risk of traumatic intra-thoracic injuries: A diagnostic accuracy study.

    Science.gov (United States)

    Safari, Saeed; Radfar, Fatemeh; Baratloo, Alireza

    2018-05-01

    This study aimed to compare the diagnostic accuracy of NEXUS chest and Thoracic Injury Rule out criteria (TIRC) models in predicting the risk of intra-thoracic injuries following blunt multiple trauma. In this diagnostic accuracy study, using the 2 mentioned models, blunt multiple trauma patients over the age of 15 years presenting to emergency department were screened regarding the presence of intra-thoracic injuries that are detectable via chest x-ray and screening performance characteristics of the models were compared. In this study, 3118 patients with the mean (SD) age of 37.4 (16.9) years were studied (57.4% male). Based on TIRC and NEXUS chest, respectively, 1340 (43%) and 1417 (45.4%) patients were deemed in need of radiography performance. Sensitivity, specificity, and positive and negative predictive values of TIRC were 98.95%, 62.70%, 21.19% and 99.83%. These values were 98.61%, 59.94%, 19.97% and 99.76%, for NEXUS chest, respectively. Accuracy of TIRC and NEXUS chest models were 66.04 (95% CI: 64.34-67.70) and 63.50 (95% CI: 61.78-65.19), respectively. TIRC and NEXUS chest models have proper and similar sensitivity in prediction of blunt traumatic intra-thoracic injuries that are detectable via chest x-ray. However, TIRC had a significantly higher specificity in this regard. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

    Science.gov (United States)

    Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

    2014-10-15

    Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Accuracy of Clinicians in Predicting the Bacterial Cause of Clinical Bovine Mastitis

    OpenAIRE

    White, Maurice E.; Glickman, Lawrence T.; Barnes-Pallesen, Frances D.; Stem, Edgar S.; Dinsmore, Page; Powers, Michael S.; Powers, Pamela; Smith, Mary C.; Jasko, David

    1986-01-01

    We examined the ability of clinicians to predict the causative organism of bovine mastitis in our practice. We obtained 118 milk culture results from 112 mastitic cows and compared the culture results to the predictions of clinicians at the time of milk sample collection. Sixty of 118 culture results were accurately predicted. The positive predictive value for coliform mastitis was 42% and the negative predictive value was 79% in a study population with a 31% prevalence of coliform mastitis. ...

  8. Early Prediction of Student Dropout and Performance in MOOCSs Using Higher Granularity Temporal Information

    Science.gov (United States)

    Ye, Cheng; Biswas, Gautam

    2014-01-01

    Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…

  9. Real time shear wave elastography in chronic liver diseases: Accuracy for predicting liver fibrosis, in comparison with serum markers

    Science.gov (United States)

    Jeong, Jae Yoon; Kim, Tae Yeob; Sohn, Joo Hyun; Kim, Yongsoo; Jeong, Woo Kyoung; Oh, Young-Ha; Yoo, Kyo-Sang

    2014-01-01

    AIM: To evaluate the correlation between liver stiffness measurement (LSM) by real-time shear wave elastography (SWE) and liver fibrosis stage and the accuracy of LSM for predicting significant and advanced fibrosis, in comparison with serum markers. METHODS: We consecutively analyzed 70 patients with various chronic liver diseases. Liver fibrosis was staged from F0 to F4 according to the Batts and Ludwig scoring system. Significant and advanced fibrosis was defined as stage F ≥ 2 and F ≥ 3, respectively. The accuracy of prediction for fibrosis was analyzed using receiver operating characteristic curves. RESULTS: Seventy patients, 15 were belonged to F0-F1 stage, 20 F2, 13 F3 and 22 F4. LSM was increased with progression of fibrosis stage (F0-F1: 6.77 ± 1.72, F2: 9.98 ± 3.99, F3: 15.80 ± 7.73, and F4: 22.09 ± 10.09, P < 0.001). Diagnostic accuracies of LSM for prediction of F ≥ 2 and F ≥ 3 were 0.915 (95%CI: 0.824-0.968, P < 0.001) and 0.913 (95%CI: 0.821-0.967, P < 0.001), respectively. The cut-off values of LSM for prediction of F ≥ 2 and F ≥ 3 were 8.6 kPa with 78.2% sensitivity and 93.3% specificity and 10.46 kPa with 88.6% sensitivity and 80.0% specificity, respectively. However, there were no significant differences between LSM and serum hyaluronic acid and type IV collagen in diagnostic accuracy. CONCLUSION: SWE showed a significant correlation with the severity of liver fibrosis and was useful and accurate to predict significant and advanced fibrosis, comparable with serum markers. PMID:25320528

  10. High-accuracy CFD prediction methods for fluid and structure temperature fluctuations at T-junction for thermal fatigue evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Qian, Shaoxiang, E-mail: qian.shaoxiang@jgc.com [EN Technology Center, Process Technology Division, JGC Corporation, 2-3-1 Minato Mirai, Nishi-ku, Yokohama 220-6001 (Japan); Kanamaru, Shinichiro [EN Technology Center, Process Technology Division, JGC Corporation, 2-3-1 Minato Mirai, Nishi-ku, Yokohama 220-6001 (Japan); Kasahara, Naoto [Nuclear Engineering and Management, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2015-07-15

    Highlights: • Numerical methods for accurate prediction of thermal loading were proposed. • Predicted fluid temperature fluctuation (FTF) intensity is close to the experiment. • Predicted structure temperature fluctuation (STF) range is close to the experiment. • Predicted peak frequencies of FTF and STF also agree well with the experiment. • CFD results show the proposed numerical methods are of sufficiently high accuracy. - Abstract: Temperature fluctuations generated by the mixing of hot and cold fluids at a T-junction, which is widely used in nuclear power and process plants, can cause thermal fatigue failure. The conventional methods for evaluating thermal fatigue tend to provide insufficient accuracy, because they were developed based on limited experimental data and a simplified one-dimensional finite element analysis (FEA). CFD/FEA coupling analysis is expected as a useful tool for the more accurate evaluation of thermal fatigue. The present paper aims to verify the accuracy of proposed numerical methods of simulating fluid and structure temperature fluctuations at a T-junction for thermal fatigue evaluation. The dynamic Smagorinsky model (DSM) is used for large eddy simulation (LES) sub-grid scale (SGS) turbulence model, and a hybrid scheme (HS) is adopted for the calculation of convective terms in the governing equations. Also, heat transfer between fluid and structure is calculated directly through thermal conduction by creating a mesh with near wall resolution (NWR) by allocating grid points within the thermal boundary sub-layer. The simulation results show that the distribution of fluid temperature fluctuation intensity and the range of structure temperature fluctuation are remarkably close to the experimental results. Moreover, the peak frequencies of power spectrum density (PSD) of both fluid and structure temperature fluctuations also agree well with the experimental results. Therefore, the numerical methods used in the present paper are

  11. Theoretical study on new bias factor methods to effectively use critical experiments for improvement of prediction accuracy of neutronic characteristics

    International Nuclear Information System (INIS)

    Kugo, Teruhiko; Mori, Takamasa; Takeda, Toshikazu

    2007-01-01

    Extended bias factor methods are proposed with two new concepts, the LC method and the PE method, in order to effectively use critical experiments and to enhance the applicability of the bias factor method for the improvement of the prediction accuracy of neutronic characteristics of a target core. Both methods utilize a number of critical experimental results and produce a semifictitious experimental value with them. The LC and PE methods define the semifictitious experimental values by a linear combination of experimental values and the product of exponentiated experimental values, respectively, and the corresponding semifictitious calculation values by those of calculation values. A bias factor is defined by the ratio of the semifictitious experimental value to the semifictitious calculation value in both methods. We formulate how to determine weights for the LC method and exponents for the PE method in order to minimize the variance of the design prediction value obtained by multiplying the design calculation value by the bias factor. From a theoretical comparison of these new methods with the conventional method which utilizes a single experimental result and the generalized bias factor method which was previously proposed to utilize a number of experimental results, it is concluded that the PE method is the most useful method for improving the prediction accuracy. The main advantages of the PE method are summarized as follows. The prediction accuracy is necessarily improved compared with the design calculation value even when experimental results include large experimental errors. This is a special feature that the other methods do not have. The prediction accuracy is most effectively improved by utilizing all the experimental results. From these facts, it can be said that the PE method effectively utilizes all the experimental results and has a possibility to make a full-scale-mockup experiment unnecessary with the use of existing and future benchmark

  12. Assessing the accuracy of software predictions of mammalian and microbial metabolites

    Science.gov (United States)

    New chemical development and hazard assessments benefit from accurate predictions of mammalian and microbial metabolites. Fourteen biotransformation libraries encoded in eight software packages that predict metabolite structures were assessed for their sensitivity (proportion of ...

  13. Impact of sampling interval in training data acquisition on intrafractional predictive accuracy of indirect dynamic tumor-tracking radiotherapy.

    Science.gov (United States)

    Mukumoto, Nobutaka; Nakamura, Mitsuhiro; Akimoto, Mami; Miyabe, Yuki; Yokota, Kenji; Matsuo, Yukinori; Mizowaki, Takashi; Hiraoka, Masahiro

    2017-08-01

    To explore the effect of sampling interval of training data acquisition on the intrafractional prediction error of surrogate signal-based dynamic tumor-tracking using a gimbal-mounted linac. Twenty pairs of respiratory motions were acquired from 20 patients (ten lung, five liver, and five pancreatic cancer patients) who underwent dynamic tumor-tracking with the Vero4DRT. First, respiratory motions were acquired as training data for an initial construction of the prediction model before the irradiation. Next, additional respiratory motions were acquired for an update of the prediction model due to the change of the respiratory pattern during the irradiation. The time elapsed prior to the second acquisition of the respiratory motion was 12.6 ± 3.1 min. A four-axis moving phantom reproduced patients' three dimensional (3D) target motions and one dimensional surrogate motions. To predict the future internal target motion from the external surrogate motion, prediction models were constructed by minimizing residual prediction errors for training data acquired at 80 and 320 ms sampling intervals for 20 s, and at 500, 1,000, and 2,000 ms sampling intervals for 60 s using orthogonal kV x-ray imaging systems. The accuracies of prediction models trained with various sampling intervals were estimated based on training data with each sampling interval during the training process. The intrafractional prediction errors for various prediction models were then calculated on intrafractional monitoring images taken for 30 s at the constant sampling interval of a 500 ms fairly to evaluate the prediction accuracy for the same motion pattern. In addition, the first respiratory motion was used for the training and the second respiratory motion was used for the evaluation of the intrafractional prediction errors for the changed respiratory motion to evaluate the robustness of the prediction models. The training error of the prediction model was 1.7 ± 0.7 mm in 3D for all sampling

  14. Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits.

    Directory of Open Access Journals (Sweden)

    Ben J Hayes

    2010-09-01

    Full Text Available Prediction of genetic merit using dense SNP genotypes can be used for estimation of breeding values for selection of livestock, crops, and forage species; for prediction of disease risk; and for forensics. The accuracy of these genomic predictions depends in part on the genetic architecture of the trait, in particular number of loci affecting the trait and distribution of their effects. Here we investigate the difference among three traits in distribution of effects and the consequences for the accuracy of genomic predictions. Proportion of black coat colour in Holstein cattle was used as one model complex trait. Three loci, KIT, MITF, and a locus on chromosome 8, together explain 24% of the variation of proportion of black. However, a surprisingly large number of loci of small effect are necessary to capture the remaining variation. A second trait, fat concentration in milk, had one locus of large effect and a host of loci with very small effects. Both these distributions of effects were in contrast to that for a third trait, an index of scores for a number of aspects of cow confirmation ("overall type", which had only loci of small effect. The differences in distribution of effects among the three traits were quantified by estimating the distribution of variance explained by chromosome segments containing 50 SNPs. This approach was taken to account for the imperfect linkage disequilibrium between the SNPs and the QTL affecting the traits. We also show that the accuracy of predicting genetic values is higher for traits with a proportion of large effects (proportion black and fat percentage than for a trait with no loci of large effect (overall type, provided the method of analysis takes advantage of the distribution of loci effects.

  15. Bagging Approach for Increasing Classification Accuracy of CART on Family Participation Prediction in Implementation of Elderly Family Development Program

    Directory of Open Access Journals (Sweden)

    Wisoedhanie Widi Anugrahanti

    2017-06-01

    Full Text Available Classification and Regression Tree (CART was a method of Machine Learning where data exploration was done by decision tree technique. CART was a classification technique with binary recursive reconciliation algorithms where the sorting was performed on a group of data collected in a space called a node / node into two child nodes (Lewis, 2000. The aim of this study was to predict family participation in Elderly Family Development program based on family behavior in providing physical, mental, social care for the elderly. Family involvement accuracy using Bagging CART method was calculated based on 1-APER value, sensitivity, specificity, and G-Means. Based on CART method, classification accuracy was obtained 97,41% with Apparent Error Rate value 2,59%. The most important determinant of family behavior as a sorter was society participation (100,00000, medical examination (98,95988, providing nutritious food (68.60476, establishing communication (67,19877 and worship (57,36587. To improved the stability and accuracy of CART prediction, used CART Bootstrap Aggregating (Bagging with 100% accuracy result. Bagging CART classifies a total of 590 families (84.77% were appropriately classified into implement elderly Family Development program class.

  16. Is Perceived Expressivity of Game Players a Cue to Game Outcome Prediction Accuracy?

    NARCIS (Netherlands)

    Mui, H.C.; Goudbeek, M.B.; Swerts, M.G.J.

    Games can be won or lost, and the outcome of the game often determines our facial expression. Thus, game players’ facial expression possibly provides information about the game outcome. The connection between such nonverbal cues and accuracy at which game outcome could be deduced is investigated in

  17. Predicting the Accuracy of Facial Affect Recognition: The Interaction of Child Maltreatment and Intellectual Functioning

    Science.gov (United States)

    Shenk, Chad E.; Putnam, Frank W.; Noll, Jennie G.

    2013-01-01

    Previous research demonstrates that both child maltreatment and intellectual performance contribute uniquely to the accurate identification of facial affect by children and adolescents. The purpose of this study was to extend this research by examining whether child maltreatment affects the accuracy of facial recognition differently at varying…

  18. Accuracy of various iron parameters in the prediction of iron deficiency in an acute care hospital

    NARCIS (Netherlands)

    Ong, K. H.; Tan, H. L.; Lai, H. C.; Kuperan, P.

    2005-01-01

    INTRODUCTION: Iron parameters like serum ferritin and iron saturation are routinely used in diagnosing iron deficiency. However, these tests are influenced by many factors. We aimed to review the accuracy of iron parameters among inpatients in an acute care hospital. MATERIALS AND METHODS: From

  19. Accounting for taxonomic distance in accuracy assessment of soil class predictions

    NARCIS (Netherlands)

    Rossiter, David G.; Zeng, Rong; Zhang, Gan Lin

    2017-01-01

    Evaluating the accuracy of allocation to classes in monothetic hierarchical soil classification systems, including the World Reference Base for Soil Classification, US Soil Taxonomy, and Chinese Soil Taxonomy, is poorly-served by binomial methods (correct/incorrect allocation per evaluation

  20. Maternal Accuracy in Predicting Toddlers' Behaviors and Associations with Toddlers' Fearful Temperament

    Science.gov (United States)

    Kiel, Elizabeth J.; Buss, Kristin A.

    2006-01-01

    Past research provides associations between maternal parenting behaviors and characteristics such as depression and toddlers' fearful temperament. Less is known about how maternal cognitive characteristics and normal personality relate to fearful temperament. This study examined associations among the maternal cognitive characteristic of accuracy,…

  1. Accuracy of Endoscopy in Predicting the Depth of Mucosal Injury Following Caustic Ingestion; a Cross-Sectional Study

    Directory of Open Access Journals (Sweden)

    Athena Alipour-Faz

    2017-01-01

    Full Text Available Introduction: Esophagogastroduodenoscopy (EGD is currently considered as the primary method of determining the degree of mucosal injury following caustic ingestion. The present study aimed to evaluate the screening performance characteristics of EGD in predicting the depth of gastrointestinal mucosal injuries following caustic ingestion.Methods: Adult patients who were referred to emergency department due to ingestion of corrosive materials, over a 7-year period, were enrolled to this diagnostic accuracy study. Sensitivity, specificity, positive and negative predictive values as well as negative and positive likelihood ratios of EGD in predicting the depth of mucosal injury was calculated using pathologic findings as the gold standard.Results: 54 cases with the mean age of 35 ± 11.2 years were enrolled (59.25% male. Primary endoscopic results defined 28 (51.85% cases as second grade and 26 (48.14% as third grade of mucosal injury. On the other hand, pathologic findings reported 21 (38.88% patients as first grade, 14 (25.92% as second, and 19 patients (35.18% as third grade. Sensitivity and specificity of endoscopy for determining grade II tissue injury were 50.00 (23.04-76.96 and 47.50 (31.51-63.87, respectively. These measures were 100.00 (82.35-100 and 80.00 (63.06-91.56, respectively for grade III. Accuracy of EGD was 87.03% for grade III and 48.14% for grade II.Conclusion: Based on the findings of the present study, endoscopic grading of caustic related mucosal injury based on the Zargar’s classification has good accuracy in predicting grade III (87% and fail accuracy in grade II injuries (48%. It seems that we should be cautious in planning treatment for these patients solely based on endoscopic results. 

  2. Prediction of nodal involvement in primary rectal carcinoma without invasion to pelvic structures: accuracy of preoperative CT, MR, and DWIBS assessments relative to histopathologic findings.

    Directory of Open Access Journals (Sweden)

    Jun Zhou

    Full Text Available OBJECTIVE: To investigate the accuracy of preoperative computed tomography (CT, magnetic resonance (MR imaging and diffusion-weighted imaging with background body signal suppression (DWIBS in the prediction of nodal involvement in primary rectal carcinoma patients in the absence of tumor invasion into pelvic structures. METHODS AND MATERIALS: Fifty-two subjects with primary rectal cancer were preoperatively assessed by CT and MRI at 1.5 T with a phased-array coil. Preoperative lymph node staging with imaging modalities (CT, MRI, and DWIBS were compared with the final histological findings. RESULTS: The accuracy of CT, MRI, and DWIBS were 57.7%, 63.5%, and 40.4%. The accuracy of DWIBS with higher sensitivity and negative predictive value for evaluating primary rectal cancer patients was lower than that of CT and MRI. Nodal staging agreement between imaging and pathology was fairly strong for CT and MRI (Kappa value = 0.331 and 0.348, P<0.01 but was relatively weaker for DWIBS (Kappa value = 0.174, P<0.05. The accuracy was 57.7% and 59.6%, respectively, for CT and MRI when the lymph node border information was used as the criteria, and was 57.7% and 61.5%, respectively, for enhanced CT and MRI when the lymph node enhancement pattern was used as the criteria. CONCLUSION: MRI is more accurate than CT in predicting nodal involvement in primary rectal carcinoma patients in the absence of tumor invasion into pelvic structures. DWIBS has a great diagnostic value in differentiating small malignant from benign lymph nodes.

  3. Accuracy of preoperative CT T staging of renal cell carcinoma: which features predict advanced stage?

    International Nuclear Information System (INIS)

    Bradley, A.J.; MacDonald, L.; Whiteside, S.; Johnson, R.J.; Ramani, V.A.C.

    2015-01-01

    Aims: To characterise CT findings in renal cell carcinoma (RCC), and establish which features are associated with higher clinical T stage disease, and to evaluate patterns of discrepancy between radiological and pathological staging of RCC. Materials and methods: Preoperative CT studies of 92 patients with 94 pathologically proven RCCs were retrospectively reviewed. CT stage was compared with pathological stage using the American Joint Committee on Cancer (AJCC), 7 th edition (2010). The presence or absence of tumour necrosis, perinephric fat standing, thickening of Gerota's fascia, collateral vessels were noted, and correlated with pT stage. The sensitivity, specificity, and positive (PPV) and negative predictive values (NPV) for predicting pT stage ≥pT3a were derived separately for different predictors using cross-tabulations. Results: Twenty-four lesions were pathological stage T1a, 21 were T1b, seven were T2a, 25 were T3a, 11 were T3b, four were T3c, and two were T4. There were no stage T2b. Sixty-three (67%) patients had necrosis, 27 (29%) thickening of Gerota's fascia (1 T1a), 25 had collateral vessels (0 T1a), 28 (30%) had fat stranding of <2 mm, 20 (21%) of 2–5mm and one (1%) of >5 mm. For pT stage ≥pT3a, the presence of perinephric fat stranding had a sensitivity, specificity, PPV and NPV of 74%, 65%, 63%, and 76%, respectively. Presence of tumour necrosis had a sensitivity, specificity, PPV, and NPV of 81%, 44%, 54%, and 72%, respectively. Thickening of Gerota's fascia had a sensitivity, specificity, PPV, and NPV of 52%, 90%, 81% and 70%, respectively; and enlarged collateral vessels had a sensitivity, specificity, PPV, and NPV value of 52%, 94%, 88%, and 71% respectively. Conclusion: The presence of perinephric stranding and tumour necrosis were not reliable signs for pT stage >T3a. Thickening of Gerota's fascia and the presence of collateral vessels in the peri- or paranephric fat had 90% and 94% specificity, with 82% and 88

  4. Physiologically-based, predictive analytics using the heart-rate-to-Systolic-Ratio significantly improves the timeliness and accuracy of sepsis prediction compared to SIRS.

    Science.gov (United States)

    Danner, Omar K; Hendren, Sandra; Santiago, Ethel; Nye, Brittany; Abraham, Prasad

    2017-04-01

    Enhancing the efficiency of diagnosis and treatment of severe sepsis by using physiologically-based, predictive analytical strategies has not been fully explored. We hypothesize assessment of heart-rate-to-systolic-ratio significantly increases the timeliness and accuracy of sepsis prediction after emergency department (ED) presentation. We evaluated the records of 53,313 ED patients from a large, urban teaching hospital between January and June 2015. The HR-to-systolic ratio was compared to SIRS criteria for sepsis prediction. There were 884 patients with discharge diagnoses of sepsis, severe sepsis, and/or septic shock. Variations in three presenting variables, heart rate, systolic BP and temperature were determined to be primary early predictors of sepsis with a 74% (654/884) accuracy compared to 34% (304/884) using SIRS criteria (p < 0.0001)in confirmed septic patients. Physiologically-based predictive analytics improved the accuracy and expediency of sepsis identification via detection of variations in HR-to-systolic ratio. This approach may lead to earlier sepsis workup and life-saving interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Accuracy of Consecutive Fecal Calprotectin Measurements to Predict Relapse in Inflammatory Bowel Disease Patients Under Maintenance With Anti-TNF Therapy: A Prospective Longitudinal Cohort Study.

    Science.gov (United States)

    Ferreiro-Iglesias, Rocio; Barreiro-de Acosta, Manuel; Lorenzo-Gonzalez, Aurelio; Dominguez-Muñoz, Juan E

    2018-03-01

    Predicting relapse in inflammatory bowel disease (IBD) patients could allow early changes in therapy. We aimed at evaluating the accuracy of consecutive fecal calprotectin (FC) measurements to predict flares in IBD patients under maintenance treatment with anti-tumor necrosis factor (TNF) drugs. A prospective longitudinal cohort study with 16-month follow-up period was designed. IBD patients in clinical remission for at least 6 months under anti-TNF therapy were included. FC was quantified at 4-month intervals for 1 year, and patients were clinically evaluated for relapse at 2-month intervals. Diagnostic accuracy of FC for predicting relapse was evaluated by receiver-operating characteristic curve analysis. In total, 95 of 106 included patients finalized the study and were analyzed (median age 44 y, 50.5% female, 75% with Crohn's disease). A total of 30 patients (31.6%) had a relapse over follow-up. FC concentration was significantly higher in patients who relapsed (477 μg/g) than in patients who maintained in remission (65 μg/g) (Ppredict remission was 130 μg/g (negative predictive value of 100%), and 300 μg/g to predict relapse (positive predictive value of 78.3%). FC is a good predictor of clinical relapse and a particularly good predictor of remission over the following 4 months in patients with IBD on maintenance therapy with anti-TNF drugs. FC levels 300 μg/g allow predicting relapse with a high probability at any time over the following 4 months.

  6. A consensus approach for estimating the predictive accuracy of dynamic models in biology.

    Science.gov (United States)

    Villaverde, Alejandro F; Bongard, Sophia; Mauch, Klaus; Müller, Dirk; Balsa-Canto, Eva; Schmid, Joachim; Banga, Julio R

    2015-04-01

    Mathematical models that predict the complex dynamic behaviour of cellular networks are fundamental in systems biology, and provide an important basis for biomedical and biotechnological applications. However, obtaining reliable predictions from large-scale dynamic models is commonly a challenging task due to lack of identifiability. The present work addresses this challenge by presenting a methodology for obtaining high-confidence predictions from dynamic models using time-series data. First, to preserve the complex behaviour of the network while reducing the number of estimated parameters, model parameters are combined in sets of meta-parameters, which are obtained from correlations between biochemical reaction rates and between concentrations of the chemical species. Next, an ensemble of models with different parameterizations is constructed and calibrated. Finally, the ensemble is used for assessing the reliability of model predictions by defining a measure of convergence of model outputs (consensus) that is used as an indicator of confidence. We report results of computational tests carried out on a metabolic model of Chinese Hamster Ovary (CHO) cells, which are used for recombinant protein production. Using noisy simulated data, we find that the aggregated ensemble predictions are on average more accurate than the predictions of individual ensemble models. Furthermore, ensemble predictions with high consensus are statistically more accurate than ensemble predictions with large variance. The procedure provides quantitative estimates of the confidence in model predictions and enables the analysis of sufficiently complex networks as required for practical applications. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  7. Accuracy of serum uric acid as a predictive test for maternal complications in pre-eclampsia: Bivariate meta-analysis and decision analysis

    NARCIS (Netherlands)

    Koopmans, Corine M.; van Pampus, Maria G.; Groen, Henk; Aarnoudse, Jan G.; van den Berg, Paul P.; Mol, Ben W. J.

    2009-01-01

    The aim of this study is to determine the accuracy and clinical value of serum uric acid in predicting maternal complications in women with pre-eclampsia. An existing meta-analysis on the subject was updated. The accuracy of serum uric acid for the prediction of maternal complications was assessed

  8. Accuracy of serum uric acid as a predictive test for maternal complications in pre-eclampsia : Bivariate meta-analysis and decision analysis

    NARCIS (Netherlands)

    Koopmans, C.M.; van Pampus, Maria; Groen, H.; Aarnoudse, J.G.; van den Berg, P.P.; Mol, B.W.J.

    The aim of this study is to determine the accuracy and clinical value of serum uric acid in predicting maternal complications in women with pre-eclampsia. An existing meta-analysis on the subject was updated. The accuracy of serum uric acid for the prediction of maternal complications was assessed

  9. Effort and accuracy during language resource generation: a pronunciation prediction case study

    CSIR Research Space (South Africa)

    Davel, M

    2006-11-01

    Full Text Available pronunciation dictionary as case study. We show that the amount of effort required to validate a 20,000-word pronunciation dictionary can be reduced sub- stantially by employing appropriate computational tools, when compared to both a fully manual validation... and correcting errors found, and finally, manually verifying a further portion of the resource in order to estimate its current accuracy. We apply this general approach to the task of developing pronunciation dictionaries. We demonstrate how the validation...

  10. Accuracy assessment of pharmacogenetically predictive warfarin dosing algorithms in patients of an academic medical center anticoagulation clinic.

    Science.gov (United States)

    Shaw, Paul B; Donovan, Jennifer L; Tran, Maichi T; Lemon, Stephenie C; Burgwinkle, Pamela; Gore, Joel

    2010-08-01

    The objectives of this retrospective cohort study are to evaluate the accuracy of pharmacogenetic warfarin dosing algorithms in predicting therapeutic dose and to determine if this degree of accuracy warrants the routine use of genotyping to prospectively dose patients newly started on warfarin. Seventy-one patients of an outpatient anticoagulation clinic at an academic medical center who were age 18 years or older on a stable, therapeutic warfarin dose with international normalized ratio (INR) goal between 2.0 and 3.0, and cytochrome P450 isoenzyme 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) genotypes available between January 1, 2007 and September 30, 2008 were included. Six pharmacogenetic warfarin dosing algorithms were identified from the medical literature. Additionally, a 5 mg fixed dose approach was evaluated. Three algorithms, Zhu et al. (Clin Chem 53:1199-1205, 2007), Gage et al. (J Clin Ther 84:326-331, 2008), and International Warfarin Pharmacogenetic Consortium (IWPC) (N Engl J Med 360:753-764, 2009) were similar in the primary accuracy endpoints with mean absolute error (MAE) ranging from 1.7 to 1.8 mg/day and coefficient of determination R (2) from 0.61 to 0.66. However, the Zhu et al. algorithm severely over-predicted dose (defined as >or=2x or >or=2 mg/day more than actual dose) in twice as many (14 vs. 7%) patients as Gage et al. 2008 and IWPC 2009. In conclusion, the algorithms published by Gage et al. 2008 and the IWPC 2009 were the two most accurate pharmacogenetically based equations available in the medical literature in predicting therapeutic warfarin dose in our study population. However, the degree of accuracy demonstrated does not support the routine use of genotyping to prospectively dose all patients newly started on warfarin.

  11. Sensitivity, Specificity, Predictive Values, and Accuracy of Three Diagnostic Tests to Predict Inferior Alveolar Nerve Blockade Failure in Symptomatic Irreversible Pulpitis

    Directory of Open Access Journals (Sweden)

    Daniel Chavarría-Bolaños

    2017-01-01

    Full Text Available Introduction. The inferior alveolar nerve block (IANB is the most common anesthetic technique used on mandibular teeth during root canal treatment. Its success in the presence of preoperative inflammation is still controversial. The aim of this study was to evaluate the sensitivity, specificity, predictive values, and accuracy of three diagnostic tests used to predict IANB failure in symptomatic irreversible pulpitis (SIP. Methodology. A cross-sectional study was carried out on the mandibular molars of 53 patients with SIP. All patients received a single cartridge of mepivacaine 2% with 1 : 100000 epinephrine using the IANB technique. Three diagnostic clinical tests were performed to detect anesthetic failure. Anesthetic failure was defined as a positive painful response to any of the three tests. Sensitivity, specificity, predictive values, accuracy, and ROC curves were calculated and compared and significant differences were analyzed. Results. IANB failure was determined in 71.7% of the patients. The sensitivity scores for the three tests (lip numbness, the cold stimuli test, and responsiveness during endodontic access were 0.03, 0.35, and 0.55, respectively, and the specificity score was determined as 1 for all of the tests. Clinically, none of the evaluated tests demonstrated a high enough accuracy (0.30, 0.53, and 0.68 for lip numbness, the cold stimuli test, and responsiveness during endodontic access, resp.. A comparison of the areas under the curve in the ROC analyses showed statistically significant differences between the three tests (p<0.05. Conclusion. None of the analyzed tests demonstrated a high enough accuracy to be considered a reliable diagnostic tool for the prediction of anesthetic failure.

  12. Accuracy of Dolphin visual treatment objective (VTO prediction software on class III patients treated with maxillary advancement and mandibular setback

    Directory of Open Access Journals (Sweden)

    Robert J. Peterman

    2016-06-01

    Full Text Available Abstract Background Dolphin® visual treatment objective (VTO prediction software is routinely utilized by orthodontists during the treatment planning of orthognathic cases to help predict post-surgical soft tissue changes. Although surgical soft tissue prediction is considered to be a vital tool, its accuracy is not well understood in tow-jaw surgical procedures. The objective of this study was to quantify the accuracy of Dolphin Imaging’s VTO soft tissue prediction software on class III patients treated with maxillary advancement and mandibular setback and to validate the efficacy of the software in such complex cases. Methods This retrospective study analyzed the records of 14 patients treated with comprehensive orthodontics in conjunction with two-jaw orthognathic surgery. Pre- and post-treatment radiographs were traced and superimposed to determine the actual skeletal movements achieved in surgery. This information was then used to simulate surgery in the software and generate a final soft tissue patient profile prediction. Prediction images were then compared to the actual post-treatment profile photos to determine differences. Results Dolphin Imaging’s software was determined to be accurate within an error range of +/− 2 mm in the X-axis at most landmarks. The lower lip predictions were most inaccurate. Conclusions Clinically, the observed error suggests that the VTO may be used for demonstration and communication with a patient or consulting practitioner. However, Dolphin should not be useful for precise treatment planning of surgical movements. This program should be used with caution to prevent unrealistic patient expectations and dissatisfaction.

  13. Effect of accuracy of wind power prediction on power system operator

    Science.gov (United States)

    Schlueter, R. A.; Sigari, G.; Costi, T.

    1985-01-01

    This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

  14. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Directory of Open Access Journals (Sweden)

    Michael F Sloma

    2017-11-01

    Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  15. Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

    Science.gov (United States)

    Sloma, Michael F; Mathews, David H

    2017-11-01

    Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

  16. Accuracy evaluation of Fourier series analysis and singular spectrum analysis for predicting the volume of motorcycle sales in Indonesia

    Science.gov (United States)

    Sasmita, Yoga; Darmawan, Gumgum

    2017-08-01

    This research aims to evaluate the performance of forecasting by Fourier Series Analysis (FSA) and Singular Spectrum Analysis (SSA) which are more explorative and not requiring parametric assumption. Those methods are applied to predicting the volume of motorcycle sales in Indonesia from January 2005 to December 2016 (monthly). Both models are suitable for seasonal and trend component data. Technically, FSA defines time domain as the result of trend and seasonal component in different frequencies which is difficult to identify in the time domain analysis. With the hidden period is 2,918 ≈ 3 and significant model order is 3, FSA model is used to predict testing data. Meanwhile, SSA has two main processes, decomposition and reconstruction. SSA decomposes the time series data into different components. The reconstruction process starts with grouping the decomposition result based on similarity period of each component in trajectory matrix. With the optimum of window length (L = 53) and grouping effect (r = 4), SSA predicting testing data. Forecasting accuracy evaluation is done based on Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The result shows that in the next 12 month, SSA has MAPE = 13.54 percent, MAE = 61,168.43 and RMSE = 75,244.92 and FSA has MAPE = 28.19 percent, MAE = 119,718.43 and RMSE = 142,511.17. Therefore, to predict volume of motorcycle sales in the next period should use SSA method which has better performance based on its accuracy.

  17. Accuracy of clinical prediction rules in peptic ulcer perforation: an observational study

    DEFF Research Database (Denmark)

    Buck, David Levarett; Vester-Andersen, Morten; Møller, Morten Hylander

    2012-01-01

    Abstract Objective. The aim of the present study was to compare the ability of four clinical prediction rules to predict adverse outcome in perforated peptic ulcer (PPU): the Boey score, the American Society of Anesthesiologists (ASA) score, the Acute Physiology and Chronic Health Evaluation...... and breastfeeding women, non-surgically treated patients, patients with malignant ulcers, and patients with perforation of other organs were excluded. Primary outcome measure: 30-day mortality rate. Statistical analysis: the ability of four clinical prediction rules to distinguish survivors from non...

  18. Accuracy of Genomic Prediction in Synthetic Populations Depending on the Number of Parents, Relatedness, and Ancestral Linkage Disequilibrium.

    Science.gov (United States)

    Schopp, Pascal; Müller, Dominik; Technow, Frank; Melchinger, Albrecht E

    2017-01-01

    Synthetics play an important role in quantitative genetic research and plant breeding, but few studies have investigated the application of genomic prediction (GP) to these populations. Synthetics are generated by intermating a small number of parents ([Formula: see text] and thereby possess unique genetic properties, which make them especially suited for systematic investigations of factors contributing to the accuracy of GP. We generated synthetics in silico from [Formula: see text]2 to 32 maize (Zea mays L.) lines taken from an ancestral population with either short- or long-range linkage disequilibrium (LD). In eight scenarios differing in relatedness of the training and prediction sets and in the types of data used to calculate the relationship matrix (QTL, SNPs, tag markers, and pedigree), we investigated the prediction accuracy (PA) of Genomic best linear unbiased prediction (GBLUP) and analyzed contributions from pedigree relationships captured by SNP markers, as well as from cosegregation and ancestral LD between QTL and SNPs. The effects of training set size [Formula: see text] and marker density were also studied. Sampling few parents ([Formula: see text]) generates substantial sample LD that carries over into synthetics through cosegregation of alleles at linked loci. For fixed [Formula: see text], [Formula: see text] influences PA most strongly. If the training and prediction set are related, using [Formula: see text] parents yields high PA regardless of ancestral LD because SNPs capture pedigree relationships and Mendelian sampling through cosegregation. As [Formula: see text] increases, ancestral LD contributes more information, while other factors contribute less due to lower frequencies of closely related individuals. For unrelated prediction sets, only ancestral LD contributes information and accuracies were poor and highly variable for [Formula: see text] due to large sample LD. For large [Formula: see text], achieving moderate accuracy requires

  19. Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.

    Science.gov (United States)

    Leong, Ivone U S; Stuckey, Alexander; Lai, Daniel; Skinner, Jonathan R; Love, Donald R

    2015-05-13

    Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico

  20. Effect of Rainfall on Travel Time and Accuracy of Travel Time prediction with rainfall

    OpenAIRE

    CHUNG, E; EL-FAOUZI, NE; KUWAHARA, M

    2007-01-01

    Travel time is an important parameter to report to travelers. From the user's perspective, accurate predictions and an estimate of their precision are more beneficial than the current travel time since conditions may change significantly before a traveler completes the journey. Past researches have developed travel time prediction models without considering accidents and rain. Normally accident and Rain may cause to increase travel time. Therefore, it may be interesting to consider Rain and a...

  1. Video image analysis in the Australian meat industry - precision and accuracy of predicting lean meat yield in lamb carcasses.

    Science.gov (United States)

    Hopkins, D L; Safari, E; Thompson, J M; Smith, C R

    2004-06-01

    A wide selection of lamb types of mixed sex (ewes and wethers) were slaughtered at a commercial abattoir and during this process images of 360 carcasses were obtained online using the VIAScan® system developed by Meat and Livestock Australia. Soft tissue depth at the GR site (thickness of tissue over the 12th rib 110 mm from the midline) was measured by an abattoir employee using the AUS-MEAT sheep probe (PGR). Another measure of this thickness was taken in the chiller using a GR knife (NGR). Each carcass was subsequently broken down to a range of trimmed boneless retail cuts and the lean meat yield determined. The current industry model for predicting meat yield uses hot carcass weight (HCW) and tissue depth at the GR site. A low level of accuracy and precision was found when HCW and PGR were used to predict lean meat yield (R(2)=0.19, r.s.d.=2.80%), which could be improved markedly when PGR was replaced by NGR (R(2)=0.41, r.s.d.=2.39%). If the GR measures were replaced by 8 VIAScan® measures then greater prediction accuracy could be achieved (R(2)=0.52, r.s.d.=2.17%). A similar result was achieved when the model was based on principal components (PCs) computed from the 8 VIAScan® measures (R(2)=0.52, r.s.d.=2.17%). The use of PCs also improved the stability of the model compared to a regression model based on HCW and NGR. The transportability of the models was tested by randomly dividing the data set and comparing coefficients and the level of accuracy and precision. Those models based on PCs were superior to those based on regression. It is demonstrated that with the appropriate modeling the VIAScan® system offers a workable method for predicting lean meat yield automatically.

  2. The Predictive Accuracy of PREDICT : A Personalized Decision-Making Tool for Southeast Asian Women With Breast Cancer

    NARCIS (Netherlands)

    Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M.; Hartman, Mikael; Bhoo Pathy, N

    Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480

  3. Improving the Accuracy of a Heliocentric Potential (HCP Prediction Model for the Aviation Radiation Dose

    Directory of Open Access Journals (Sweden)

    Junga Hwang

    2016-12-01

    Full Text Available The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs, flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA. However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015. In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1 real-time daily sunspot assessments, (2 predictions of the daily HCP by our prediction algorithm, and (3 calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

  4. Interrelated Dimensional Chains in Predicting Accuracy of Turbine Wheel Assembly Parameters

    Science.gov (United States)

    Yanyukina, M. V.; Bolotov, M. A.; Ruzanov, N. V.

    2018-03-01

    The working capacity of any device primarily depends on the assembly accuracy which, in its turn, is determined by the quality of each part manufactured, i.e., the degree of conformity between final geometrical parameters and the set ones. However, the assembly accuracy depends not only on a qualitative manufacturing process but also on the assembly process correctness. In this connection, there were preliminary calculations of assembly stages in terms of conformity to real geometrical parameters with their permissible values. This task is performed by means of the calculation of dimensional chains. The calculation of interrelated dimensional chains in the aircraft industry requires particular attention. The article considers the issues of dimensional chain calculation modelling by the example of the turbine wheel assembly process. The authors described the solution algorithm in terms of mathematical statistics implemented in Matlab. The paper demonstrated the results of a dimensional chain calculation for a turbine wheel in relation to the draw of turbine blades to the shroud ring diameter. Besides, the article provides the information on the influence of a geometrical parameter tolerance for the dimensional chain link elements on a closing one.

  5. Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions

    Directory of Open Access Journals (Sweden)

    Quentin Noirhomme

    2014-01-01

    Full Text Available Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a permutation test. Here, we simulated classification results of generated random data to assess the influence of the cross-validation scheme on the significance of results. Distributions built from classification of random data with cross-validation did not follow the binomial distribution. The binomial test is therefore not adapted. On the contrary, the permutation test was unaffected by the cross-validation scheme. The influence of the cross-validation was further illustrated on real-data from a brain–computer interface experiment in patients with disorders of consciousness and from an fMRI study on patients with Parkinson disease. Three out of 16 patients with disorders of consciousness had significant accuracy on binomial testing, but only one showed significant accuracy using permutation testing. In the fMRI experiment, the mental imagery of gait could discriminate significantly between idiopathic Parkinson's disease patients and healthy subjects according to the permutation test but not according to the binomial test. Hence, binomial testing could lead to biased estimation of significance and false positive or negative results. In our view, permutation testing is thus recommended for clinical application of classification with cross-validation.

  6. Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions.

    Science.gov (United States)

    Noirhomme, Quentin; Lesenfants, Damien; Gomez, Francisco; Soddu, Andrea; Schrouff, Jessica; Garraux, Gaëtan; Luxen, André; Phillips, Christophe; Laureys, Steven

    2014-01-01

    Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a permutation test. Here, we simulated classification results of generated random data to assess the influence of the cross-validation scheme on the significance of results. Distributions built from classification of random data with cross-validation did not follow the binomial distribution. The binomial test is therefore not adapted. On the contrary, the permutation test was unaffected by the cross-validation scheme. The influence of the cross-validation was further illustrated on real-data from a brain-computer interface experiment in patients with disorders of consciousness and from an fMRI study on patients with Parkinson disease. Three out of 16 patients with disorders of consciousness had significant accuracy on binomial testing, but only one showed significant accuracy using permutation testing. In the fMRI experiment, the mental imagery of gait could discriminate significantly between idiopathic Parkinson's disease patients and healthy subjects according to the permutation test but not according to the binomial test. Hence, binomial testing could lead to biased estimation of significance and false positive or negative results. In our view, permutation testing is thus recommended for clinical application of classification with cross-validation.

  7. On the accuracy and reliability of predictions by control-system theory.

    Science.gov (United States)

    Bourbon, W T; Copeland, K E; Dyer, V R; Harman, W K; Mosley, B L

    1990-12-01

    In three experiments we used control-system theory (CST) to predict the results of tracking tasks on which people held a handle to keep a cursor even with a target on a computer screen. 10 people completed a total of 104 replications of the task. In each experiment, there were two conditions: in one, only the handle affected the position of the cursor; in the other, a random disturbance also affected the cursor. From a person's performance during Condition 1, we derived constants used in the CST model to predict the results of Condition 2. In two experiments, predictions occurred a few minutes before Condition 2; in one experiment, the delay was 1 yr. During a 1-min. experimental run, the positions of handle and cursor, produced by the person, were each sampled 1800 times, once every 1/30 sec. During a modeling run, the model predicted the positions of the handle and target for each of the 1800 intervals sampled in the experimental run. In 104 replications, the mean correlation between predicted and actual positions of the handle was .996; SD = .002.

  8. RAPID COMMUNICATION: Improving prediction accuracy of GPS satellite clocks with periodic variation behaviour

    Science.gov (United States)

    Heo, Youn Jeong; Cho, Jeongho; Heo, Moon Beom

    2010-07-01

    The broadcast ephemeris and IGS ultra-rapid predicted (IGU-P) products are primarily available for use in real-time GPS applications. The IGU orbit precision has been remarkably improved since late 2007, but its clock products have not shown acceptably high-quality prediction performance. One reason for this fact is that satellite atomic clocks in space can be easily influenced by various factors such as temperature and environment and this leads to complicated aspects like periodic variations, which are not sufficiently described by conventional models. A more reliable prediction model is thus proposed in this paper in order to be utilized particularly in describing the periodic variation behaviour satisfactorily. The proposed prediction model for satellite clocks adds cyclic terms to overcome the periodic effects and adopts delay coordinate embedding, which offers the possibility of accessing linear or nonlinear coupling characteristics like satellite behaviour. The simulation results have shown that the proposed prediction model outperforms the IGU-P solutions at least on a daily basis.

  9. Accuracy of patient's turnover time prediction using RFID technology in an academic ambulatory surgery center.

    Science.gov (United States)

    Marchand-Maillet, Florence; Debes, Claire; Garnier, Fanny; Dufeu, Nicolas; Sciard, Didier; Beaussier, Marc

    2015-02-01

    Patients flow in outpatient surgical unit is a major issue with regards to resource utilization, overall case load and patient satisfaction. An electronic Radio Frequency Identification Device (RFID) was used to document the overall time spent by the patients between their admission and discharge from the unit. The objective of this study was to evaluate how a RFID-based data collection system could provide an accurate prediction of the actual time for the patient to be discharged from the ambulatory surgical unit after surgery. This is an observational prospective evaluation carried out in an academic ambulatory surgery center (ASC). Data on length of stay at each step of the patient care, from admission to discharge, were recorded by a RFID device and analyzed according to the type of surgical procedure, the surgeon and the anesthetic technique. Based on these initial data (n = 1520), patients were scheduled in a sequential manner according to the expected duration of the previous case. The primary endpoint was the difference between actual and predicted time of discharge from the unit. A total of 414 consecutive patients were prospectively evaluated. One hundred seventy four patients (42%) were discharged at the predicted time ± 30 min. Only 24% were discharged behind predicted schedule. Using an automatic record of patient's length of stay would allow an accurate prediction of the discharge time according to the type of surgery, the surgeon and the anesthetic procedure.

  10. The predictive accuracy of PREDICT: a personalized decision-making tool for Southeast Asian women with breast cancer.

    Science.gov (United States)

    Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M; Hartman, Mikael; Bhoo-Pathy, Nirmala

    2015-02-01

    Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients' actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3 cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: -1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74-0.81) and 0.73 (95% CI: 0.68-0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings.

  11. Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

    Science.gov (United States)

    Downs, Meghan E.; Lee, Stuart M. C.; Ploutz-Snyder, Lori; Feiveson, Alan

    2016-01-01

    Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

  12. Accuracy and Uncertainty Analysis of Intelligent Techniques for Predicting the Longitudinal Dispersion Coefficient in Rivers

    Directory of Open Access Journals (Sweden)

    Abbas Akbarzadeh

    2010-09-01

    Full Text Available Accurate prediction of longitudinal dispersion coefficient (LDC can be useful for the determination of pollutants concentration distribution in natural rivers. However, the uncertainty associated with the results obtained from forecasting models has a negative effect on pollutant management in water resources. In this research, appropriate models are first developed using ANN and ANFIS techniques to predict the LDC in natural streams. Then, an uncertainty analysis is performed for ANN and ANFIS models based on Monte-Carlo simulation. The input parameters of the models are related to hydraulic variables and stream geometry. Results indicate that ANN is a suitable model for predicting the LDC, but it is also associated with a high level of uncertainty. However, results of uncertainty analysis show that ANFIS model has less uncertainty; i.e. it is the best model for forecasting satisfactorily the LDC in natural streams.

  13. Accuracy of circulating histones in predicting persistent organ failure and mortality in patients with acute pancreatitis.

    Science.gov (United States)

    Liu, T; Huang, W; Szatmary, P; Abrams, S T; Alhamdi, Y; Lin, Z; Greenhalf, W; Wang, G; Sutton, R; Toh, C H

    2017-08-01

    Early prediction of acute pancreatitis severity remains a challenge. Circulating levels of histones are raised early in mouse models and correlate with disease severity. It was hypothesized that circulating histones predict persistent organ failure in patients with acute pancreatitis. Consecutive patients with acute pancreatitis fulfilling inclusion criteria admitted to Royal Liverpool University Hospital were enrolled prospectively between June 2010 and March 2014. Blood samples were obtained within 48 h of abdominal pain onset and relevant clinical data during the hospital stay were collected. Healthy volunteers were enrolled as controls. The primary endpoint was occurrence of persistent organ failure. The predictive values of circulating histones, clinical scores and other biomarkers were determined. Among 236 patients with acute pancreatitis, there were 156 (66·1 per cent), 57 (24·2 per cent) and 23 (9·7 per cent) with mild, moderate and severe disease respectively, according to the revised Atlanta classification. Forty-seven healthy volunteers were included. The area under the receiver operating characteristic (ROC) curve (AUC) for circulating histones in predicting persistent organ failure and mortality was 0·92 (95 per cent c.i. 0·85 to 0·99) and 0·96 (0·92 to 1·00) respectively; histones were at least as accurate as clinical scores or biochemical markers. For infected pancreatic necrosis and/or sepsis, the AUC was 0·78 (0·62 to 0·94). Histones did not predict or correlate with local pancreatic complications, but correlated negatively with leucocyte cell viability (r = -0·511, P = 0·001). Quantitative assessment of circulating histones in plasma within 48 h of abdominal pain onset can predict persistent organ failure and mortality in patients with acute pancreatitis. Early death of immune cells may contribute to raised circulating histone levels in acute pancreatitis. © 2017 The Authors. BJS published by John Wiley & Sons Ltd on behalf of BJS

  14. The accuracy of dysphoric and nondepressed groups' predictions of life events.

    Science.gov (United States)

    Kapçi, E G; Cramer, D

    1998-11-01

    The phenomenon of depressive realism was examined in relation to the future prediction of positive and negative life events. A group of dysphoric (n = 20) and nondepressed (n = 38) British undergraduates participated in a prospective study lasting 3 months. Partly consistent with the depressive realism hypotheses, dysphoric participants were more realistic concerning the negative life events they would experience, but they were less realistic concerning the negative life events they would not experience. Although no difference was found for predicting the occurrence of positive life events, dysphoric participants were found to be more realistic concerning positive life events that they would not experience.

  15. Predicting academic success in higher education: what’s more important than being smart?

    NARCIS (Netherlands)

    Kappe, F.R.; van der Flier, H.

    2012-01-01

    This study investigated the combined predictive validity of intelligence and personality factors on multiple measures of academic achievement. Students in a college of higher education in the Netherlands (N0137) completed a survey that measured intelligence, the Big Five personality traits,

  16. Predicting Academic Success in Higher Education: What's More Important than Being Smart?

    Science.gov (United States)

    Kappe, Rutger; van der Flier, Henk

    2012-01-01

    This study investigated the combined predictive validity of intelligence and personality factors on multiple measures of academic achievement. Students in a college of higher education in the Netherlands (N = 137) completed a survey that measured intelligence, the Big Five personality traits, motivation, and four specific personality traits.…

  17. Higher-order predictions for splitting functions and coefficient functions from physical evolution kernels

    International Nuclear Information System (INIS)

    Vogt, A; Soar, G.; Vermaseren, J.A.M.

    2010-01-01

    We have studied the physical evolution kernels for nine non-singlet observables in deep-inelastic scattering (DIS), semi-inclusive e + e - annihilation and the Drell-Yan (DY) process, and for the flavour-singlet case of the photon- and heavy-top Higgs-exchange structure functions (F 2 , F φ ) in DIS. All known contributions to these kernels show an only single-logarithmic large-x enhancement at all powers of (1-x). Conjecturing that this behaviour persists to (all) higher orders, we have predicted the highest three (DY: two) double logarithms of the higher-order non-singlet coefficient functions and of the four-loop singlet splitting functions. The coefficient-function predictions can be written as exponentiations of 1/N-suppressed contributions in Mellin-N space which, however, are less predictive than the well-known exponentiation of the ln k N terms. (orig.)

  18. To compare the accuracy of Prayer's sign and Mallampatti test in predicting difficult intubation in Diabetic patients

    International Nuclear Information System (INIS)

    Baig, M. M. A.; Khan, F. H.

    2014-01-01

    Objective: To determine the accuracy of Prayer's sign and Mallampatti test in predicting difficult endotracheal intubation in diabetic patients. Methods: The cross-sectional study was performed at Aga Khan University Hospital, Karachi, over a period from January 2009 to April 2010, and comprised 357 patients who required endotracheal intubation for elective surgical procedures. Prayer's sign and Mallampatti tests were performed for the assessment of airway by trained observers. Ease or difficulty of laryngoscopy after the patient was fully anaesthetised with standard technique were observed and laryngoscopic view of first attempt was rated according to Cormack-Lehan grade of intubation. SPSS 15 was used for statistical analysis. Results: Of the 357 patients, 125(35%) were classified as difficult to intubate. Prayer's sign showed significantly lower accuracy, positive and negative predictive values than Mallampatti test. The sensitivity of Prayer's sign was lower 29.6 (95% Confidence Interval, 21.9-38.5) than Mallampatti test 79.3 (95% confidence interval, 70.8-85.7) while specificity of both the tests was not found to be significantly different. Conclusion: Prayer's sign is not acceptable as a single best bedside test for prediction of difficult intubation. (author)

  19. Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X-ray Crystal Structures

    Science.gov (United States)

    2014-01-01

    We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5–22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10–25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function. PMID:24392845

  20. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators.

    Science.gov (United States)

    Backović, Mihailo; Krämer, Michael; Maltoni, Fabio; Martini, Antony; Mawatari, Kentarou; Pellen, Mathieu

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s -channel mediators. We implement such models in the FeynRules/MadGraph5_aMC@NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s -channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties.

  1. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators

    Energy Technology Data Exchange (ETDEWEB)

    Backović, Mihailo [Centre for Cosmology, Particle Physics and Phenomenology (CP3), Université catholique de Louvain, 1348, Louvain-la-Neuve (Belgium); Krämer, Michael [Institute for Theoretical Particle Physics and Cosmology, RWTH Aachen University, 52056, Aachen (Germany); Maltoni, Fabio; Martini, Antony [Centre for Cosmology, Particle Physics and Phenomenology (CP3), Université catholique de Louvain, 1348, Louvain-la-Neuve (Belgium); Mawatari, Kentarou, E-mail: kentarou.mawatari@vub.ac.be [Theoretische Natuurkunde and IIHE/ELEM, Vrije Universiteit Brussel, and International Solvay Institutes, Pleinlaan 2, 1050, Brussels (Belgium); Pellen, Mathieu [Institute for Theoretical Particle Physics and Cosmology, RWTH Aachen University, 52056, Aachen (Germany)

    2015-10-07

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s-channel mediators. We implement such models in the FeynRules/MadGraph5{sub a}MC@NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s-channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties.

  2. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators

    Energy Technology Data Exchange (ETDEWEB)

    Backovic, Mihailo; Maltoni, Fabio; Martini, Antony [Universite catholique de Louvain, Centre for Cosmology, Particle Physics and Phenomenology (CP3), Louvain-la-Neuve (Belgium); Kraemer, Michael; Pellen, Mathieu [RWTH Aachen University, Institute for Theoretical Particle Physics and Cosmology, Aachen (Germany); Mawatari, Kentarou [Theoretische Natuurkunde and IIHE/ELEM, Vrije Universiteit Brussel, and International Solvay Institutes, Brussels (Belgium)

    2015-10-15

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s-channel mediators. We implement such models in the FeynRules/MadGraph5{sub a}MC rate at NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s-channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties. (orig.)

  3. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators

    International Nuclear Information System (INIS)

    Backovic, Mihailo; Maltoni, Fabio; Martini, Antony; Kraemer, Michael; Pellen, Mathieu; Mawatari, Kentarou

    2015-01-01

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s-channel mediators. We implement such models in the FeynRules/MadGraph5 a MC rate at NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s-channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties. (orig.)

  4. CRISPR-Cas9-mediated saturated mutagenesis screen predicts clinical drug resistance with improved accuracy.

    Science.gov (United States)

    Ma, Leyuan; Boucher, Jeffrey I; Paulsen, Janet; Matuszewski, Sebastian; Eide, Christopher A; Ou, Jianhong; Eickelberg, Garrett; Press, Richard D; Zhu, Lihua Julie; Druker, Brian J; Branford, Susan; Wolfe, Scot A; Jensen, Jeffrey D; Schiffer, Celia A; Green, Michael R; Bolon, Daniel N

    2017-10-31

    Developing tools to accurately predict the clinical prevalence of drug-resistant mutations is a key step toward generating more effective therapeutics. Here we describe a high-throughput CRISPR-Cas9-based saturated mutagenesis approach to generate comprehensive libraries of point mutations at a defined genomic location and systematically study their effect on cell growth. As proof of concept, we mutagenized a selected region within the leukemic oncogene BCR-ABL1 Using bulk competitions with a deep-sequencing readout, we analyzed hundreds of mutations under multiple drug conditions and found that the effects of mutations on growth in the presence or absence of drug were critical for predicting clinically relevant resistant mutations, many of which were cancer adaptive in the absence of drug pressure. Using this approach, we identified all clinically isolated BCR-ABL1 mutations and achieved a prediction score that correlated highly with their clinical prevalence. The strategy described here can be broadly applied to a variety of oncogenes to predict patient mutations and evaluate resistance susceptibility in the development of new therapeutics. Published under the PNAS license.

  5. An Other Perspective on Personality: Meta-Analytic Integration of Observers' Accuracy and Predictive Validity

    Science.gov (United States)

    Connelly, Brian S.; Ones, Deniz S.

    2010-01-01

    The bulk of personality research has been built from self-report measures of personality. However, collecting personality ratings from other-raters, such as family, friends, and even strangers, is a dramatically underutilized method that allows better explanation and prediction of personality's role in many domains of psychology. Drawing…

  6. Accuracy of spatio-temporal RARX model predictions of water table depths

    NARCIS (Netherlands)

    Knotters, M.; Bierkens, M.F.P.

    2002-01-01

    Time series of water table depths (Ht) are predicted in space using a regionalised autoregressive exogenous variable (RARX) model with precipitation surplus (Pt) as input variable. Because of their physical basis, RARX model parameters can be guessed from auxiliary information such as a digital

  7. Genomic selection accuracy using multi-family prediction models in a wheat breeding program

    Science.gov (United States)

    Genomic selection (GS) uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotyp...

  8. Accuracy of eosinophils and eosinophil cationic protein to predict steroid improvement in asthma

    NARCIS (Netherlands)

    Meijer, RJ; Postma, DS; Kauffman, HF; Arends, LR; Koeter, GH; Kerstjens, HAM

    Background There is a large variability in clinical response to corticosteroid treatment in patients with asthma. Several markers of inflammation like eosinophils and eosinophil cationic protein (ECP), as well as exhaled nitric oxide (NO), are good candidates to predict clinical response. Aim We

  9. Cognitive Models of Risky Choice: Parameter Stability and Predictive Accuracy of Prospect Theory

    Science.gov (United States)

    Glockner, Andreas; Pachur, Thorsten

    2012-01-01

    In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are…

  10. Examination of the consistency and accuracy of computerized brachytherapy dose predictions

    International Nuclear Information System (INIS)

    Tolbert, D.D.; Reed, S.A.

    1981-01-01

    Four brachytherapy test cases were sent to representatives of commercial and non-commercial, computerized radiation oncology treatment planning systems. Four commercial systems are represented herein. The non-commercial, state-of-the-art systems represented are (in alphabetical order) BRACHY, ISODOS and RADCOMP. Mutual comparisons were made to examine consistency and a comparison with experimental measurements around a single source was made to examine accuracy. The systems represented are most consistent within 5 cm from the center of a single source, and within rays from the center making angles of greater than or equal to 20 0 relative to the source axis. Taking into account tissue absorption and scatter, the spatial uncertainty in the location of a particular isodose rate value is less than or equal to 0.7 mm for commercial systems and less than or equal to 0.5 mm for non-commercial systems

  11. Study of the stiffness for predicting the accuracy of machine tools

    International Nuclear Information System (INIS)

    Ortega, N.; Campa, F.J.; Fernandez Valdivielso, A.; Alonso, U.; Olvera, D.; Compean, F.I.

    2010-01-01

    Machining processes are frequently faced with the challenge of achieving more and more precision and surface qualities. These requirements are usually attained taking into account some process variables, including the cutting parameters and the use or not of refrigerant, leaving aside the mechanical aspects associated with the influence of machine tool itself. There are many sources of error linked with machine-workpiece interaction, but, in general, we can summarize them into two types of error: quasi-static and dynamic. This paper shows the influence of quasi-static error caused by low machine rigidity on the accuracy applied on two very different processes: turning and grinding. For the study of the static stiffness of these two machines, two different methods are proposed, both of them equally valid. The first one is based on separated parameters and the second one on finite elements. (Author).

  12. Enhancing Accuracy of Sediment Total Load Prediction Using Evolutionary Algorithms (Case Study: Gotoorchay River

    Directory of Open Access Journals (Sweden)

    K. Roshangar

    2016-09-01

    Full Text Available Introduction: Exact prediction of transported sediment rate by rivers in water resources projects is of utmost importance. Basically erosion and sediment transport process is one of the most complexes hydrodynamic. Although different studies have been developed on the application of intelligent models based on neural, they are not widely used because of lacking explicitness and complexity governing on choosing and architecting of proper network. In this study, a Genetic expression programming model (as an important branches of evolutionary algorithems for predicting of sediment load is selected and investigated as an intelligent approach along with other known classical and imperical methods such as Larsen´s equation, Engelund-Hansen´s equation and Bagnold´s equation. Materials and Methods: In this study, in order to improve explicit prediction of sediment load of Gotoorchay, located in Aras catchment, Northwestern Iran latitude: 38°24´33.3˝ and longitude: 44°46´13.2˝, genetic programming (GP and Genetic Algorithm (GA were applied. Moreover, the semi-empirical models for predicting of total sediment load and rating curve have been used. Finally all the methods were compared and the best ones were introduced. Two statistical measures were used to compare the performance of the different models, namely root mean square error (RMSE and determination coefficient (DC. RMSE and DC indicate the discrepancy between the observed and computed values. Results and Discussions: The statistical characteristics results obtained from the analysis of genetic programming method for both selected model groups indicated that the model 4 including the only discharge of the river, relative to other studied models had the highest DC and the least RMSE in the testing stage (DC= 0.907, RMSE= 0.067. Although there were several parameters applied in other models, these models were complicated and had weak results of prediction. Our results showed that the model 9

  13. Accuracy of shock index versus ABC score to predict need for massive transfusion in trauma patients.

    Science.gov (United States)

    Schroll, Rebecca; Swift, David; Tatum, Danielle; Couch, Stuart; Heaney, Jiselle B; Llado-Farrulla, Monica; Zucker, Shana; Gill, Frances; Brown, Griffin; Buffin, Nicholas; Duchesne, Juan

    2018-01-01

    Various scoring systems have been developed to predict need for massive transfusion in traumatically injured patients. Assessments of Blood Consumption (ABC) score and Shock Index (SI) have been shown to be reliable predictors for Massive Transfusion Protocol (MTP) activation. However, no study has directly compared these two scoring systems to determine which is a better predictor for MTP activation. The primary objective was to determine whether ABC or SI better predicted the need for MTP in adult trauma patients with severe hemorrhage. This was a retrospective cohort study which included all injured patients who were trauma activations between January 1, 2009 and December 31, 2013 at an urban Level I trauma center. Patients ABC and SI were calculated for each patient. MTP was defined as need for >10 units PRBC transfusion within 24h of emergency department arrival. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were used to evaluate scoring systems' ability to predict effective MTP utilization. A total of 645 patients had complete data for analysis. Shock Index ≥1 had sensitivity of 67.7% (95% CI 49.5%-82.6%) and specificity of 81.3% (95% CI 78.0%-84.3%) for predicting MTP, and ABC score ≥2 had sensitivity of 47.0% (95% CI 29.8%-64.9%) and specificity of 89.8% (95% CI 87.2%-92.1%). AUROC analyses showed SI to be the strongest predictor followed by ABC score with AUROC values of 0.83 and 0.74, respectively. SI had a significantly greater sensitivity (P=0.035), but a significantly weaker specificity (PABC score. ABC score and Shock Index can both be used to predict need for massive transfusion in trauma patients, however SI is more sensitive and requires less technical skill than ABC score. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. A function accounting for training set size and marker density to model the average accuracy of genomic prediction.

    Science.gov (United States)

    Erbe, Malena; Gredler, Birgit; Seefried, Franz Reinhold; Bapst, Beat; Simianer, Henner

    2013-01-01

    Prediction of genomic breeding values is of major practical relevance in dairy cattle breeding. Deterministic equations have been suggested to predict the accuracy of genomic breeding values in a given design which are based on training set size, reliability of phenotypes, and the number of independent chromosome segments ([Formula: see text]). The aim of our study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically. Two data sets of 5'698 Holstein Friesian bulls genotyped with 50 K SNPs and 1'332 Brown Swiss bulls genotyped with 50 K SNPs and imputed to ∼600 K SNPs were available. Different k-fold (k = 2-10, 15, 20) cross-validation scenarios (50 replicates, random assignment) were performed using a genomic BLUP approach. A maximum likelihood approach was used to estimate the parameters of different prediction equations. The highest likelihood was obtained when using a modified form of the deterministic equation of Daetwyler et al. (2010), augmented by a weighting factor (w) based on the assumption that the maximum achievable accuracy is [Formula: see text]. The proportion of genetic variance captured by the complete SNP sets ([Formula: see text]) was 0.76 to 0.82 for Holstein Friesian and 0.72 to 0.75 for Brown Swiss. When modifying the number of SNPs, w was found to be proportional to the log of the marker density up to a limit which is population and trait specific and was found to be reached with ∼20'000 SNPs in the Brown Swiss population studied.

  15. A function accounting for training set size and marker density to model the average accuracy of genomic prediction.

    Directory of Open Access Journals (Sweden)

    Malena Erbe

    Full Text Available Prediction of genomic breeding values is of major practical relevance in dairy cattle breeding. Deterministic equations have been suggested to predict the accuracy of genomic breeding values in a given design which are based on training set size, reliability of phenotypes, and the number of independent chromosome segments ([Formula: see text]. The aim of our study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically. Two data sets of 5'698 Holstein Friesian bulls genotyped with 50 K SNPs and 1'332 Brown Swiss bulls genotyped with 50 K SNPs and imputed to ∼600 K SNPs were available. Different k-fold (k = 2-10, 15, 20 cross-validation scenarios (50 replicates, random assignment were performed using a genomic BLUP approach. A maximum likelihood approach was used to estimate the parameters of different prediction equations. The highest likelihood was obtained when using a modified form of the deterministic equation of Daetwyler et al. (2010, augmented by a weighting factor (w based on the assumption that the maximum achievable accuracy is [Formula: see text]. The proportion of genetic variance captured by the complete SNP sets ([Formula: see text] was 0.76 to 0.82 for Holstein Friesian and 0.72 to 0.75 for Brown Swiss. When modifying the number of SNPs, w was found to be proportional to the log of the marker density up to a limit which is population and trait specific and was found to be reached with ∼20'000 SNPs in the Brown Swiss population studied.

  16. The influence of the new ECMWF Ensemble Prediction System resolution on wind power forecast accuracy and uncertainty estimation

    DEFF Research Database (Denmark)

    Alessandrini, S.; Pinson, Pierre; Sperati, S.

    2011-01-01

    The importance of wind power forecasting (WPF) is nowadays commonly recognized because it represents a useful tool to reduce problems of grid integration and to facilitate energy trading. If on one side the prediction accuracy is fundamental to these scopes, on the other it has become also clear...... by a recalibration procedure that allowed obtaining a more uniform distribution among the 51 intervals, making the ensemble spread large enough to include the observations. After that it was observed that the EPS power spread seemed to have enough correlation with the error calculated on the deterministic forecast...

  17. Accuracy and Predictability of PANC-3 Scoring System over APACHE II in Acute Pancreatitis: A Prospective Study.

    Science.gov (United States)

    Rathnakar, Surag Kajoor; Vishnu, Vikram Hubbanageri; Muniyappa, Shridhar; Prasath, Arun

    2017-02-01

    Acute Pancreatitis (AP) is one of the common conditions encountered in the emergency room. The course of the disease ranges from mild form to severe acute form. Most of these episodes are mild and spontaneously subsiding within 3 to 5 days. In contrast, Severe Acute Pancreatitis (SAP) occurring in around 15-20% of all cases, mortality can range between 10 to 85% across various centres and countries. In such a situation we need an indicator which can predict the outcome of an attack, as severe or mild, as early as possible and such an indicator should be sensitive and specific enough to trust upon. PANC-3 scoring is such a scoring system in predicting the outcome of an attack of AP. To assess the accuracy and predictability of PANC-3 scoring system over APACHE II in predicting severity in an attack of AP. This prospective study was conducted on 82 patients admitted with the diagnosis of pancreatitis. Investigations to evaluate PANC-3 and APACHE II were done on all the patients and the PANC-3 and APACHE II score was calculated. PANC-3 score has a sensitivity of 82.6% and specificity of 77.9%, the test had a Positive Predictive Value (PPV) of 0.59 and Negative Predictive Value (NPV) of 0.92. Sensitivity of APACHE II in predicting SAP was 91.3% and specificity was 96.6% with PPV of 0.91, NPV was 0.96. Our study shows that PANC-3 can be used to predict the severity of pancreatitis as efficiently as APACHE II. The interpretation of PANC-3 does not need expertise and can be applied at the time of admission which is an advantage when compared to classical scoring systems.

  18. Efficient first-principles prediction of solid stability: Towards chemical accuracy

    Science.gov (United States)

    Zhang, Yubo; Kitchaev, Daniil A.; Yang, Julia; Chen, Tina; Dacek, Stephen T.; Sarmiento-Pérez, Rafael A.; Marques, Maguel A. L.; Peng, Haowei; Ceder, Gerbrand; Perdew, John P.; Sun, Jianwei

    2018-03-01

    The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. Here, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for main group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.

  19. Calibration and evaluation of predictive accuracy of a (micro)pollutant influent generator

    DEFF Research Database (Denmark)

    Snip, L. J. P.; Flores-Alsina, X.; Aymerich, I.

    Summary of key findings: The Benchmark Simulation Model No. 2 influent generator upgraded with pharmaceutical occurrences is capable of reproducing both the long- and short-term dynamics of traditional variables as well as micropollutants. Several quantitative evaluation criteria are presented an...... and used to assess the model’s predictive capabilities and all show satisfactory results except for COD particulates. Ongoing research aims at improving this remaining issue....

  20. ROBUSTNESS AND PREDICTION ACCURACY OF MACHINE LEARNING FOR OBJECTIVE VISUAL QUALITY ASSESSMENT

    OpenAIRE

    Hines, Andrew; Kendrick, Paul; Barri, Adriaan; Narwaria, Manish; Redi, Judith A.

    2014-01-01

    Machine Learning (ML) is a powerful tool to support the development of objective visual quality assessment metrics, serving as a substitute model for the perceptual mechanisms acting in visual quality appreciation. Nevertheless, the reliability of ML-based techniques within objective quality assessment metrics is often questioned. In this study, the robustness of ML in supporting objective quality assessment is investigated, specifically when the feature set adopted for prediction is suboptim...

  1. Predicting early academic achievement: The role of higher-versus lower-order personality traits

    Directory of Open Access Journals (Sweden)

    Zupančič Maja

    2011-01-01

    Full Text Available The study explored the role of children’s (N = 193 individual differences and parental characteristics at the beginning of the first year of schooling in predicting students’ attainment of academic standards at the end of the year. Special attention was paid to children’s personality as perceived by the teachers’ assistants. Along with parents’ education, parenting practices and first-graders’ cognitive ability, the incremental predictive power of children’s higher-order (robust personality traits was compared to the contribution of lower-order (specific traits in explaining academic achievement. The specific traits provided a somewhat more accurate prediction than the robust traits. Unique contributions of maternal authoritative parenting, children’s cognitive ability, and personality to academic achievement were established. The ratings of first-graders’ conscientiousness (a higher-order trait improved the prediction of academic achievement based on parenting and cognitive ability by 12%, whereas assistant teacher’s perceived children’s intelligence and low antagonism (lower-order traits improved the prediction by 17%.

  2. The accuracy of Internet search engines to predict diagnoses from symptoms can be assessed with a validated scoring system.

    Science.gov (United States)

    Shenker, Bennett S

    2014-02-01

    To validate a scoring system that evaluates the ability of Internet search engines to correctly predict diagnoses when symptoms are used as search terms. We developed a five point scoring system to evaluate the diagnostic accuracy of Internet search engines. We identified twenty diagnoses common to a primary care setting to validate the scoring system. One investigator entered the symptoms for each diagnosis into three Internet search engines (Google, Bing, and Ask) and saved the first five webpages from each search. Other investigators reviewed the webpages and assigned a diagnostic accuracy score. They rescored a random sample of webpages two weeks later. To validate the five point scoring system, we calculated convergent validity and test-retest reliability using Kendall's W and Spearman's rho, respectively. We used the Kruskal-Wallis test to look for differences in accuracy scores for the three Internet search engines. A total of 600 webpages were reviewed. Kendall's W for the raters was 0.71 (psearch engines is a valid and reliable instrument. The scoring system may be used in future Internet research. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  3. Application of Semiempirical Methods to Transition Metal Complexes: Fast Results but Hard-to-Predict Accuracy.

    KAUST Repository

    Minenkov, Yury

    2018-05-22

    A series of semiempirical PM6* and PM7 methods has been tested in reproducing of relative conformational energies of 27 realistic-size complexes of 16 different transition metals (TMs). An analysis of relative energies derived from single-point energy evaluations on density functional theory (DFT) optimized conformers revealed pronounced deviations between semiempirical and DFT methods indicating fundamental difference in potential energy surfaces (PES). To identify the origin of the deviation, we compared fully optimized PM7 and respective DFT conformers. For many complexes, differences in PM7 and DFT conformational energies have been confirmed often manifesting themselves in false coordination of some atoms (H, O) to TMs and chemical transformations/distortion of coordination center geometry in PM7 structures. Despite geometry optimization with fixed coordination center geometry leads to some improvements in conformational energies, the resulting accuracy is still too low to recommend explored semiempirical methods for out-of-the-box conformational search/sampling: careful testing is always needed.

  4. The psychology of intelligence analysis: drivers of prediction accuracy in world politics.

    Science.gov (United States)

    Mellers, Barbara; Stone, Eric; Atanasov, Pavel; Rohrbaugh, Nick; Metz, S Emlen; Ungar, Lyle; Bishop, Michael M; Horowitz, Michael; Merkle, Ed; Tetlock, Philip

    2015-03-01

    This article extends psychological methods and concepts into a domain that is as profoundly consequential as it is poorly understood: intelligence analysis. We report findings from a geopolitical forecasting tournament that assessed the accuracy of more than 150,000 forecasts of 743 participants on 199 events occurring over 2 years. Participants were above average in intelligence and political knowledge relative to the general population. Individual differences in performance emerged, and forecasting skills were surprisingly consistent over time. Key predictors were (a) dispositional variables of cognitive ability, political knowledge, and open-mindedness; (b) situational variables of training in probabilistic reasoning and participation in collaborative teams that shared information and discussed rationales (Mellers, Ungar, et al., 2014); and (c) behavioral variables of deliberation time and frequency of belief updating. We developed a profile of the best forecasters; they were better at inductive reasoning, pattern detection, cognitive flexibility, and open-mindedness. They had greater understanding of geopolitics, training in probabilistic reasoning, and opportunities to succeed in cognitively enriched team environments. Last but not least, they viewed forecasting as a skill that required deliberate practice, sustained effort, and constant monitoring of current affairs. PsycINFO Database Record (c) 2015 APA, all rights reserved.

  5. THE ROLE OF DIFFERENT RHEOLOGICAL MODELS IN ACCURACY OF PRESSURE LOSS PREDICTION

    Directory of Open Access Journals (Sweden)

    Katarina Simon

    2004-12-01

    Full Text Available Hydraulics play an important function in many oil field operations including drilling, completion, fracturing, acidizing, workover and production. The standard API methods for drilling fluid hydraulics assume either power law or Bingham plastic rheological model. These models and corresponding hydraulic calculations do provide a simple way for fair estimates of hydraulics for conventional vertical wells using simple drilling fluids, such as bentonite fluids. However, nowdays with many wells drilled deep, slim or horizontal using complex muds with unusual behaviour (such as tested MMH mud, it is necessary to use appropriate rheological model for mathematical modelling of fluid behaviour. Oil and gas reservoirs in Croatia have been under production for quite a while and the probability to discover new deposits of hydrocarbons is rather small. Therefore attempts have been made to maintain the gas and oil exploitation at the present level. One of possible ways to meet this target is re-entry wells drilling. The diameter of such wells in reservoir is smaller than 0,1524 m (6 in. Accurate modelling of annular pressure losses becomes therefore an important issue, particularly in cases where a small safety margin exists between optimal drilling parameters and wellbore stability, what is the case in re-entry wells. The objective of the paper is to show the influence of well geometry and accuracy of fluid rheological properties modelling to the distribution of pressure losses in a slimhole well.

  6. A numerical evaluation of prediction accuracy of CO2 absorber model for various reaction rate coefficients

    Directory of Open Access Journals (Sweden)

    Shim S.M.

    2012-01-01

    Full Text Available The performance of the CO2 absorber column using mono-ethanolamine (MEA solution as chemical solvent are predicted by a One-Dimensional (1-D rate based model in the present study. 1-D Mass and heat balance equations of vapor and liquid phase are coupled with interfacial mass transfer model and vapor-liquid equilibrium model. The two-film theory is used to estimate the mass transfer between the vapor and liquid film. Chemical reactions in MEA-CO2-H2O system are considered to predict the equilibrium pressure of CO2 in the MEA solution. The mathematical and reaction kinetics models used in this work are calculated by using in-house code. The numerical results are validated in the comparison of simulation results with experimental and simulation data given in the literature. The performance of CO2 absorber column is evaluated by the 1-D rate based model using various reaction rate coefficients suggested by various researchers. When the rate of liquid to gas mass flow rate is about 8.3, 6.6, 4.5 and 3.1, the error of CO2 loading and the CO2 removal efficiency using the reaction rate coefficients of Aboudheir et al. is within about 4.9 % and 5.2 %, respectively. Therefore, the reaction rate coefficient suggested by Aboudheir et al. among the various reaction rate coefficients used in this study is appropriate to predict the performance of CO2 absorber column using MEA solution. [Acknowledgement. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF, funded by the Ministry of Education, Science and Technology (2011-0017220].

  7. QIKAIM, a fast seminumerical algorithm for the generation of minute-of-arc accuracy satellite predictions

    Science.gov (United States)

    Vermeer, M.

    1981-07-01

    A program was designed to replace AIMLASER for the generation of aiming predictions, to achieve a major saving in computing time, and to keep the program small enough for use even on small systems. An approach was adopted that incorporated the numerical integration of the orbit through a pass, limiting the computation of osculating elements to only one point per pass. The numerical integration method which is fourth order in delta t in the cumulative error after a given time lapse is presented. Algorithms are explained and a flowchart and listing of the program are provided.

  8. Accuracy of Inferior Vena Cava Ultrasound for Predicting Dehydration in Children with Acute Diarrhea in Resource-Limited Settings.

    Science.gov (United States)

    Modi, Payal; Glavis-Bloom, Justin; Nasrin, Sabiha; Guy, Allysia; Chowa, Erika P; Dvor, Nathan; Dworkis, Daniel A; Oh, Michael; Silvestri, David M; Strasberg, Stephen; Rege, Soham; Noble, Vicki E; Alam, Nur H; Levine, Adam C

    2016-01-01

    Although dehydration from diarrhea is a leading cause of morbidity and mortality in children under five, existing methods of assessing dehydration status in children have limited accuracy. To assess the accuracy of point-of-care ultrasound measurement of the aorta-to-IVC ratio as a predictor of dehydration in children. A prospective cohort study of children under five years with acute diarrhea was conducted in the rehydration unit of the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b). Ultrasound measurements of aorta-to-IVC ratio and dehydrated weight were obtained on patient arrival. Percent weight change was monitored during rehydration to classify children as having "some dehydration" with weight change 3-9% or "severe dehydration" with weight change > 9%. Logistic regression analysis and Receiver-Operator Characteristic (ROC) curves were used to evaluate the accuracy of aorta-to-IVC ratio as a predictor of dehydration severity. 850 children were enrolled, of which 771 were included in the final analysis. Aorta to IVC ratio was a significant predictor of the percent dehydration in children with acute diarrhea, with each 1-point increase in the aorta to IVC ratio predicting a 1.1% increase in the percent dehydration of the child. However, the area under the ROC curve (0.60), sensitivity (67%), and specificity (49%), for predicting severe dehydration were all poor. Point-of-care ultrasound of the aorta-to-IVC ratio was statistically associated with volume status, but was not accurate enough to be used as an independent screening tool for dehydration in children under five years presenting with acute diarrhea in a resource-limited setting.

  9. Accuracy of Inferior Vena Cava Ultrasound for Predicting Dehydration in Children with Acute Diarrhea in Resource-Limited Settings.

    Directory of Open Access Journals (Sweden)

    Payal Modi

    Full Text Available Although dehydration from diarrhea is a leading cause of morbidity and mortality in children under five, existing methods of assessing dehydration status in children have limited accuracy.To assess the accuracy of point-of-care ultrasound measurement of the aorta-to-IVC ratio as a predictor of dehydration in children.A prospective cohort study of children under five years with acute diarrhea was conducted in the rehydration unit of the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b. Ultrasound measurements of aorta-to-IVC ratio and dehydrated weight were obtained on patient arrival. Percent weight change was monitored during rehydration to classify children as having "some dehydration" with weight change 3-9% or "severe dehydration" with weight change > 9%. Logistic regression analysis and Receiver-Operator Characteristic (ROC curves were used to evaluate the accuracy of aorta-to-IVC ratio as a predictor of dehydration severity.850 children were enrolled, of which 771 were included in the final analysis. Aorta to IVC ratio was a significant predictor of the percent dehydration in children with acute diarrhea, with each 1-point increase in the aorta to IVC ratio predicting a 1.1% increase in the percent dehydration of the child. However, the area under the ROC curve (0.60, sensitivity (67%, and specificity (49%, for predicting severe dehydration were all poor.Point-of-care ultrasound of the aorta-to-IVC ratio was statistically associated with volume status, but was not accurate enough to be used as an independent screening tool for dehydration in children under five years presenting with acute diarrhea in a resource-limited setting.

  10. Accuracy Enhancement with Processing Error Prediction and Compensation of a CNC Flame Cutting Machine Used in Spatial Surface Operating Conditions

    Directory of Open Access Journals (Sweden)

    Shenghai Hu

    2017-04-01

    Full Text Available This study deals with the precision performance of the CNC flame-cutting machine used in spatial surface operating conditions and presents an accuracy enhancement method based on processing error modeling prediction and real-time compensation. Machining coordinate systems and transformation matrix models were established for the CNC flame processing system considering both geometric errors and thermal deformation effects. Meanwhile, prediction and compensation models were constructed related to the actual cutting situation. Focusing on the thermal deformation elements, finite element analysis was used to measure the testing data of thermal errors, the grey system theory was applied to optimize the key thermal points, and related thermal dynamics models were carried out to achieve high-precision prediction values. Comparison experiments between the proposed method and the teaching method were conducted on the processing system after performing calibration. The results showed that the proposed method is valid and the cutting quality could be improved by more than 30% relative to the teaching method. Furthermore, the proposed method can be used under any working condition by making a few adjustments to the prediction and compensation models.

  11. Accuracy of the actuator disc-RANS approach for predicting the performance and wake of tidal turbines.

    Science.gov (United States)

    Batten, W M J; Harrison, M E; Bahaj, A S

    2013-02-28

    The actuator disc-RANS model has widely been used in wind and tidal energy to predict the wake of a horizontal axis turbine. The model is appropriate where large-scale effects of the turbine on a flow are of interest, for example, when considering environmental impacts, or arrays of devices. The accuracy of the model for modelling the wake of tidal stream turbines has not been demonstrated, and flow predictions presented in the literature for similar modelled scenarios vary significantly. This paper compares the results of the actuator disc-RANS model, where the turbine forces have been derived using a blade-element approach, to experimental data measured in the wake of a scaled turbine. It also compares the results with those of a simpler uniform actuator disc model. The comparisons show that the model is accurate and can predict up to 94 per cent of the variation in the experimental velocity data measured on the centreline of the wake, therefore demonstrating that the actuator disc-RANS model is an accurate approach for modelling a turbine wake, and a conservative approach to predict performance and loads. It can therefore be applied to similar scenarios with confidence.

  12. Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

    Science.gov (United States)

    Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

    2018-03-01

    Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

  13. Accuracy of the paracetamol-aminotransferase product to predict hepatotoxicity in paracetamol overdose treated with a 2-bag acetylcysteine regimen.

    Science.gov (United States)

    Wong, Anselm; Sivilotti, Marco L A; Gunja, Naren; McNulty, Richard; Graudins, Andis

    2018-03-01

    Paracetamol concentration is a highly accurate risk predictor for hepatotoxicity following overdose with known time of ingestion. However, the paracetamol-aminotransferase multiplication product can be used as a risk predictor independent of timing or ingestion type. Validated in patients treated with the traditional, "three-bag" intravenous acetylcysteine regimen, we evaluated the accuracy of the multiplication product in paracetamol overdose treated with a two-bag acetylcysteine regimen. We examined consecutive patients treated with the two-bag regimen from five emergency departments over a two-year period. We assessed the predictive accuracy of initial multiplication product for the primary outcome of hepatotoxicity (peak alanine aminotransferase ≥1000IU/L), as well as for acute liver injury (ALI), defined peak alanine aminotransferase ≥2× baseline and above 50IU/L). Of 447 paracetamol overdoses treated with the two-bag acetylcysteine regimen, 32 (7%) developed hepatotoxicity and 73 (16%) ALI. The pre-specified cut-off points of 1500 mg/L × IU/L (sensitivity 100% [95% CI 82%, 100%], specificity 62% [56%, 67%]) and 10,000 mg/L × IU/L (sensitivity 70% [47%, 87%], specificity of 97% [95%, 99%]) were highly accurate for predicting hepatotoxicity. There were few cases of hepatotoxicity irrespective of the product when acetylcysteine was administered within eight hours of overdose, when the product was largely determined by a high paracetamol concentration but normal aminotransferase. The multiplication product accurately predicts hepatotoxicity when using a two-bag acetylcysteine regimen, especially in patients treated more than eight hours post-overdose. Further studies are needed to assess the product as a method to adjust for exposure severity when testing efficacy of modified acetylcysteine regimens.

  14. Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties

    Science.gov (United States)

    Sankey, Joel B.; McVay, Jason C.; Kreitler, Jason R.; Hawbaker, Todd J.; Vaillant, Nicole; Lowe, Scott

    2015-01-01

    Increased sedimentation following wildland fire can negatively impact water supply and water quality. Understanding how changing fire frequency, extent, and location will affect watersheds and the ecosystem services they supply to communities is of great societal importance in the western USA and throughout the world. In this work we assess the utility of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Sediment Retention Model to accurately characterize erosion and sedimentation of burned watersheds. InVEST was developed by the Natural Capital Project at Stanford University (Tallis et al., 2014) and is a suite of GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., USLE – Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. In this study, we evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured postfire sediment yields available for many watersheds throughout the western USA from an existing, published large database. We show that the model can be parameterized in a relatively simple fashion to predict post-fire sediment yield with accuracy. Our ultimate goal is to use the model to accurately predict variability in post-fire sediment yield at a watershed scale as a function of future wildfire conditions.

  15. Quantifying the predictive accuracy of time-to-event models in the presence of competing risks.

    Science.gov (United States)

    Schoop, Rotraut; Beyersmann, Jan; Schumacher, Martin; Binder, Harald

    2011-02-01

    Prognostic models for time-to-event data play a prominent role in therapy assignment, risk stratification and inter-hospital quality assurance. The assessment of their prognostic value is vital not only for responsible resource allocation, but also for their widespread acceptance. The additional presence of competing risks to the event of interest requires proper handling not only on the model building side, but also during assessment. Research into methods for the evaluation of the prognostic potential of models accounting for competing risks is still needed, as most proposed methods measure either their discrimination or calibration, but do not examine both simultaneously. We adapt the prediction error proposal of Graf et al. (Statistics in Medicine 1999, 18, 2529–2545) and Gerds and Schumacher (Biometrical Journal 2006, 48, 1029–1040) to handle models with competing risks, i.e. more than one possible event type, and introduce a consistent estimator. A simulation study investigating the behaviour of the estimator in small sample size situations and for different levels of censoring together with a real data application follows.

  16. Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

    Science.gov (United States)

    Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

    2012-01-01

    Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

  17. Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

    Science.gov (United States)

    Santanello, J. A.; Kumar, S.; Peters-Lidard, C. D.; Harrison, K. W.; Zhou, S.

    2012-12-01

    Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

  18. The Multi-center Evaluation of the Accuracy of the Contrast MEdium INduced Pd/Pa RaTiO in Predicting FFR (MEMENTO-FFR) Study.

    Science.gov (United States)

    Leone, Antonio Maria; Martin-Reyes, Roberto; Baptista, Sergio B; Amabile, Nicolas; Raposo, Luis; Franco Pelaez, Juan Antonio; Trani, Carlo; Cialdella, Pio; Basile, Eloisa; Zimbardo, Giuseppe; Burzotta, Francesco; Porto, Italo; Aurigemma, Cristina; Rebuzzi, Antonio G; Faustino, Mariana; Niccoli, Giampaolo; Abreu, Pedro F; Slama, Michel S; Spagnoli, Vincent; Telleria Arrieta, Miren; Amat Santos, Ignacio J; de la Torre Hernandez, Jose M; Lopez Palop, Ramon; Crea, Filippo

    2016-08-20

    Adenosine administration is needed for the achievement of maximal hyperaemia fractional flow reserve (FFR) assessment. The objective was to test the accuracy of Pd/Pa ratio registered during submaximal hyperaemia induced by non-ionic contrast medium (contrast FFR [cFFR]) in predicting FFR and comparing it to the performance of resting Pd/Pa in a collaborative registry of 926 patients enrolled in 10 hospitals from four European countries (Italy, Spain, France and Portugal). Resting Pd/Pa, cFFR and FFR were measured in 1,026 coronary stenoses functionally evaluated using commercially available pressure wires. cFFR was obtained after intracoronary injection of contrast medium, while FFR was measured after administration of adenosine. Resting Pd/Pa and cFFR were significantly higher than FFR (0.93±0.05 vs. 0.87±0.08 vs. 0.84±0.08, ptime and costs.

  19. Accuracy and Reliability in the Prediction of End-of-Life Performance of Solar Generators

    Science.gov (United States)

    Rapp, Etienne

    2008-09-01

    The end-of-life power analysis of solar arrays is calculated using a combination of arithmetic and root square sums of loss factors. These loss factors are sometimes linked to degradations, sometimes linked to uncertainties. The uncertainties of the degradations are taken into account considering contractual "worst cases". This paper will put the first stones for a move "metrological" evaluation of the probable performance associated with a standard uncertainty. The turn from silicon to triple junction solar cells induces some changes in the degradation parameters of solar arrays: * The triple junction cells are more sensitive to UV darkening than silicon ones. * The cell voltage is higher and the current is lower. Then the cell strings are shorter, and there are more strings in parallel. This induces some changes in the reliability analyses and risk management. * The failure modes and failure rates of these cells have to be compared and discussed. We try to define improved rules to design solar arrays for end of life performance, for a better knowledge of the margins and a better reliability.

  20. Accuracy of clinical signs, SEP, and EEG in predicting outcome of hypoxic coma: a meta-analysis.

    Science.gov (United States)

    Lee, Y C; Phan, T G; Jolley, D J; Castley, H C; Ingram, D A; Reutens, D C

    2010-02-16

    Accurate prediction of neurologic outcome after hypoxic coma is important. Previous systematic reviews have not used summary statistics to summarize and formally compare the accuracy of different prognostic tests. We therefore used summary receiver operating characteristic curve (SROC) and cluster regression methods to compare motor and pupillary responses with sensory evoked potential (SEP) and EEG in predicting outcome after hypoxic coma. We searched PubMed, MEDLINE, and Embase (1966-2007) for reports in English, German, and French and identified 25 suitable studies. An SROC was constructed for each marker (SEP, EEG, M1 and M SEP was larger than those for M1, M SEP (AUC 0.891) and that for M1 (AUC 0.786) was small (0.105, 95% confidence interval 0.023-0.187), only reaching significance on day 1 after coma onset. The use of M SEP) is marginally better than M1 at predicting outcome after hypoxic coma. However, the superiority of SEP diminishes after day 1 and when M SEP is a better marker than clinical signs.

  1. Does diagnosis affect the predictive accuracy of risk assessment tools for juvenile offenders: Conduct Disorder and Attention Deficit Hyperactivity Disorder.

    Science.gov (United States)

    Khanna, Dinesh; Shaw, Jenny; Dolan, Mairead; Lennox, Charlotte

    2014-10-01

    Studies have suggested an increased risk of criminality in juveniles if they suffer from co-morbid Attention Deficit Hyperactivity Disorder (ADHD) along with Conduct Disorder. The Structured Assessment of Violence Risk in Youth (SAVRY), the Psychopathy Checklist Youth Version (PCL:YV), and Youth Level of Service/Case Management Inventory (YLS/CMI) have been shown to be good predictors of violent and non-violent re-offending. The aim was to compare the accuracy of these tools to predict violent and non-violent re-offending in young people with co-morbid ADHD and Conduct Disorder and Conduct Disorder only. The sample included 109 White-British adolescent males in secure settings. Results revealed no significant differences between the groups for re-offending. SAVRY factors had better predictive values than PCL:YV or YLS/CMI. Tools generally had better predictive values for the Conduct Disorder only group than the co-morbid group. Possible reasons for these findings have been discussed along with limitations of the study. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

  2. FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort.

    Science.gov (United States)

    Caminiti, Silvia Paola; Ballarini, Tommaso; Sala, Arianna; Cerami, Chiara; Presotto, Luca; Santangelo, Roberto; Fallanca, Federico; Vanoli, Emilia Giovanna; Gianolli, Luigi; Iannaccone, Sandro; Magnani, Giuseppe; Perani, Daniela

    2018-01-01

    In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias. We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated. The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p CSF biomarkers.

  3. Accuracy of the paracetamol-aminotransferase multiplication product to predict hepatotoxicity in modified-release paracetamol overdose.

    Science.gov (United States)

    Wong, Anselm; Sivilotti, Marco L A; Graudins, Andis

    2017-06-01

    The paracetamol-aminotransferase multiplication product (APAP × ALT) is a risk predictor of hepatotoxicity that is somewhat independent of time and type of ingestion. However, its accuracy following ingestion of modified-release formulations is not known, as the product has been derived and validated after immediate-release paracetamol overdoses. The aim of this retrospective cohort study was to evaluate the accuracy of the multiplication product to predict hepatotoxicity in a cohort of patients with modified-release paracetamol overdose. We assessed all patients with modified-release paracetamol overdose presenting to our hospital network from October 2009 to July 2016. Ingestion of a modified-release formulation was identified by patient self-report or retrieval of the original container. Hepatotoxicity was defined as peak alanine aminotransferase ≥1000 IU/L, and acute liver injury (ALI) as a doubling of baseline ALT to more than 50 IU/L. Of 1989 paracetamol overdose presentations, we identified 73 modified-release paracetamol exposures treated with acetylcysteine. Five patients developed hepatotoxicity, including one who received acetylcysteine within eight hours of an acute ingestion. No patient with an initial multiplication product paracetamol overdose treated with acetylcysteine, the paracetamol-aminotransferase multiplication product demonstrated similar accuracy and temporal profile to previous reports involving mostly immediate-release formulations. Above a cut-point of 10,000 mg/L × IU/L, it was very strongly associated with the development of acute liver injury and hepatotoxicity, especially when calculated more than eight hours post-ingestion. When below 1500 mg/L × IU/L the likelihood of developing hepatotoxicity was very low. Persistently high serial multiplication product calculations were associated with the greatest risk of hepatotoxicity.

  4. A Modified LS+AR Model to Improve the Accuracy of the Short-term Polar Motion Prediction

    Science.gov (United States)

    Wang, Z. W.; Wang, Q. X.; Ding, Y. Q.; Zhang, J. J.; Liu, S. S.

    2017-03-01

    There are two problems of the LS (Least Squares)+AR (AutoRegressive) model in polar motion forecast: the inner residual value of LS fitting is reasonable, but the residual value of LS extrapolation is poor; and the LS fitting residual sequence is non-linear. It is unsuitable to establish an AR model for the residual sequence to be forecasted, based on the residual sequence before forecast epoch. In this paper, we make solution to those two problems with two steps. First, restrictions are added to the two endpoints of LS fitting data to fix them on the LS fitting curve. Therefore, the fitting values next to the two endpoints are very close to the observation values. Secondly, we select the interpolation residual sequence of an inward LS fitting curve, which has a similar variation trend as the LS extrapolation residual sequence, as the modeling object of AR for the residual forecast. Calculation examples show that this solution can effectively improve the short-term polar motion prediction accuracy by the LS+AR model. In addition, the comparison results of the forecast models of RLS (Robustified Least Squares)+AR, RLS+ARIMA (AutoRegressive Integrated Moving Average), and LS+ANN (Artificial Neural Network) confirm the feasibility and effectiveness of the solution for the polar motion forecast. The results, especially for the polar motion forecast in the 1-10 days, show that the forecast accuracy of the proposed model can reach the world level.

  5. Accuracy of Single Frequency GPS Observations Processing In Near Real-time With Use of Code Predicted Products

    Science.gov (United States)

    Wielgosz, P. A.

    In this year, the system of active geodetic GPS permanent stations is going to be estab- lished in Poland. This system should provide GPS observations for a wide spectrum of users, especially it will be a great opportunity for surveyors. Many of surveyors still use cheaper, single frequency receivers. This paper focuses on processing of single frequency GPS observations only. During processing of such observations the iono- sphere plays an important role, so we concentrated on the influence of the ionosphere on the positional coordinates. Twenty consecutive days of GPS data from 2001 year were processed to analyze the accuracy of a derived three-dimensional relative vec- tor position between GPS stations. Observations from two Polish EPN/IGS stations: BOGO and JOZE were used. In addition to, a new test station - IGIK was created. In this paper, the results of single frequency GPS observations processing in near real- time are presented. Baselines of 15, 27 and 42 kilometers and sessions of 1, 2, 3, 4, and 6 hours long were processed. While processing we used CODE (Centre for Orbit De- termination in Europe, Bern, Switzerland) predicted products: orbits and ionosphere info. These products are available in real-time and enable near real-time processing. Software Bernese v. 4.2 for Linux and BPE (Bernese Processing Engine) mode were used. These results are shown with a reference to dual frequency weekly solution (the best solution). Obtained GPS positional time and GPS baseline length dependency accuracy is presented for single frequency GPS observations.

  6. Astudy on accuracy of predicted breeding value for body weight at eighth week of age in Khorasan native chickens

    Directory of Open Access Journals (Sweden)

    faeze ghorbani

    2015-12-01

    Full Text Available Introduction: Genetic resources in any country are valuable materials which needed to be conserved for a sustainable agriculture. An animal phenotype is generally affected by genetic and environmental factors. To increase mean performance in a population under consideration not only environmental conditions, but also genetic potential of the animals should be improved. Although, environmental improvement could increase the level of animals’ production in a more rapid way, it is not a permanent and non-cumulative progress. In any breeding schemes prediction breeding value of the candidate animals is needed to be obtained with a high precision and accuracy for making a remarkable genetic gain for the traits over the time. The main objective of the present research was to study accuracy of predicted breeding value for body weight at eighth week of age in indigenous chickens of Khorasan Razavi province. Materials and methods: A set of 47,000 body weight (at the age of eight weeks records belonging to 47,000 head of male and female chicks (progeny of 753 sires and 5,154 dams collected during seven generations (2006-2012 was used. The data were obtained in Khorasan Razavi native chicken breeding center. An animal model was applied for analyzing the records. In the model, contemporary group of generation*hatch*sex (GHS as a fixed effect, weight at birth as a covariable, as well as direct and maternal additive genetic random effects were taken into account. In an initial analysis using SAS software, all fixed and covariate factors included in the model were detected to be significant for the trait. All additive genetic relationships among the animals in the pedigree file (47,880 animals were accounted for. Variance and covariance components of direct and maternal additive genetic effects were estimated through restricted maximum likelihood (REML method. Breeding value of the animals was obtained by best linear unbiased prediction (BLUP. Selection

  7. Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.

    Science.gov (United States)

    Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

    2015-03-01

    Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.

  8. Mortality Risk After Transcatheter Aortic Valve Implantation: Analysis of the Predictive Accuracy of the Transcatheter Valve Therapy Registry Risk Assessment Model.

    Science.gov (United States)

    Codner, Pablo; Malick, Waqas; Kouz, Remi; Patel, Amisha; Chen, Cheng-Han; Terre, Juan; Landes, Uri; Vahl, Torsten Peter; George, Isaac; Nazif, Tamim; Kirtane, Ajay J; Khalique, Omar K; Hahn, Rebecca T; Leon, Martin B; Kodali, Susheel

    2018-05-08

    Risk assessment tools currently used to predict mortality in transcatheter aortic valve implantation (TAVI) were designed for patients undergoing cardiac surgery. We aim to assess the accuracy of the TAVI dedicated American College of Cardiology / Transcatheter Valve Therapies (ACC/TVT) risk score in predicting mortality outcomes. Consecutive patients (n=1038) undergoing TAVI at a single institution from 2014 to 2016 were included. The ACC/TVT registry mortality risk score, the Society of Thoracic Surgeons - Patient Reported Outcomes (STS-PROM) score and the EuroSCORE II were calculated for all patients. In hospital and 30-day all-cause mortality rates were 1.3% and 2.9%, respectively. The ACC/TVT risk stratification tool scored higher for patients who died in-hospital than in those who survived the index hospitalization (6.4 ± 4.6 vs. 3.5 ± 1.6, p = 0.03; respectively). The ACC/TVT score showed a high level of discrimination, C-index for in-hospital mortality 0.74, 95% CI [0.59 - 0.88]. There were no significant differences between the performance of the ACC/TVT registry risk score, the EuroSCORE II and the STS-PROM for in hospital and 30-day mortality rates. The ACC/TVT registry risk model is a dedicated tool to aid in the prediction of in-hospital mortality risk after TAVI.

  9. Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

    Science.gov (United States)

    Basyuni, M.; Wati, R.

    2018-03-01

    The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

  10. Diagnostic accuracy of calculated serum osmolarity to predict dehydration in older people: adding value to pathology laboratory reports.

    Science.gov (United States)

    Hooper, Lee; Abdelhamid, Asmaa; Ali, Adam; Bunn, Diane K; Jennings, Amy; John, W Garry; Kerry, Susan; Lindner, Gregor; Pfortmueller, Carmen A; Sjöstrand, Fredrik; Walsh, Neil P; Fairweather-Tait, Susan J; Potter, John F; Hunter, Paul R; Shepstone, Lee

    2015-10-21

    To assess which osmolarity equation best predicts directly measured serum/plasma osmolality and whether its use could add value to routine blood test results through screening for dehydration in older people. Diagnostic accuracy study. Older people (≥65 years) in 5 cohorts: Dietary Strategies for Healthy Ageing in Europe (NU-AGE, living in the community), Dehydration Recognition In our Elders (DRIE, living in residential care), Fortes (admitted to acute medical care), Sjöstrand (emergency room) or Pfortmueller cohorts (hospitalised with liver cirrhosis). Directly measured serum/plasma osmolality: current dehydration (serum osmolality>300 mOsm/kg), impending/current dehydration (≥295 mOsm/kg). 39 osmolarity equations calculated using serum indices from the same blood draw as directly measured osmolality. Across 5 cohorts 595 older people were included, of whom 19% were dehydrated (directly measured osmolality>300 mOsm/kg). Of 39 osmolarity equations, 5 showed reasonable agreement with directly measured osmolality and 3 had good predictive accuracy in subgroups with diabetes and poor renal function. Two equations were characterised by narrower limits of agreement, low levels of differential bias and good diagnostic accuracy in receiver operating characteristic plots (areas under the curve>0.8). The best equation was osmolarity=1.86×(Na++K+)+1.15×glucose+urea+14 (all measured in mmol/L). It appeared useful in people aged ≥65 years with and without diabetes, poor renal function, dehydration, in men and women, with a range of ages, health, cognitive and functional status. Some commonly used osmolarity equations work poorly, and should not be used. Given costs and prevalence of dehydration in older people we suggest use of the best formula by pathology laboratories using a cutpoint of 295 mOsm/L (sensitivity 85%, specificity 59%), to report dehydration risk opportunistically when serum glucose, urea and electrolytes are measured for other reasons in

  11. Slat Noise Predictions Using Higher-Order Finite-Difference Methods on Overset Grids

    Science.gov (United States)

    Housman, Jeffrey A.; Kiris, Cetin

    2016-01-01

    Computational aeroacoustic simulations using the structured overset grid approach and higher-order finite difference methods within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for slat noise predictions. The simulations are part of a collaborative study comparing noise generation mechanisms between a conventional slat and a Krueger leading edge flap. Simulation results are compared with experimental data acquired during an aeroacoustic test in the NASA Langley Quiet Flow Facility. Details of the structured overset grid, numerical discretization, and turbulence model are provided.

  12. SU-E-T-802: Verification of Implanted Cardiac Pacemaker Doses in Intensity-Modulated Radiation Therapy: Dose Prediction Accuracy and Reduction Effect of a Lead Sheet

    Energy Technology Data Exchange (ETDEWEB)

    Lee, J [Dept. of Radiation Oncology, Konkuk University Medical Center, Seoul (Korea, Republic of); Chung, J [Dept. of Radiation Oncology, Seoul National University Bundang Hospital, Seongnam (Korea, Republic of)

    2015-06-15

    Purpose: To verify delivered doses on the implanted cardiac pacemaker, predicted doses with and without dose reduction method were verified using the MOSFET detectors in terms of beam delivery and dose calculation techniques in intensity-modulated radiation therapy (IMRT). Methods: The pacemaker doses for a patient with a tongue cancer were predicted according to the beam delivery methods [step-and-shoot (SS) and sliding window (SW)], intensity levels for dose optimization, and dose calculation algorithms. Dosimetric effects on the pacemaker were calculated three dose engines: pencil-beam convolution (PBC), analytical anisotropic algorithm (AAA), and Acuros-XB. A lead shield of 2 mm thickness was designed for minimizing irradiated doses to the pacemaker. Dose variations affected by the heterogeneous material properties of the pacemaker and effectiveness of the lead shield were predicted by the Acuros-XB. Dose prediction accuracy and the feasibility of the dose reduction strategy were verified based on the measured skin doses right above the pacemaker using mosfet detectors during the radiation treatment. Results: The Acuros-XB showed underestimated skin doses and overestimated doses by the lead-shield effect, even though the lower dose disagreement was observed. It led to improved dose prediction with higher intensity level of dose optimization in IMRT. The dedicated tertiary lead sheet effectively achieved reduction of pacemaker dose up to 60%. Conclusion: The current SS technique could deliver lower scattered doses than recommendation criteria, however, use of the lead sheet contributed to reduce scattered doses.Thin lead plate can be a useful tertiary shielder and it could not acuse malfunction or electrical damage of the implanted pacemaker in IMRT. It is required to estimate more accurate scattered doses of the patient with medical device to design proper dose reduction strategy.

  13. SU-E-T-802: Verification of Implanted Cardiac Pacemaker Doses in Intensity-Modulated Radiation Therapy: Dose Prediction Accuracy and Reduction Effect of a Lead Sheet

    International Nuclear Information System (INIS)

    Lee, J; Chung, J

    2015-01-01

    Purpose: To verify delivered doses on the implanted cardiac pacemaker, predicted doses with and without dose reduction method were verified using the MOSFET detectors in terms of beam delivery and dose calculation techniques in intensity-modulated radiation therapy (IMRT). Methods: The pacemaker doses for a patient with a tongue cancer were predicted according to the beam delivery methods [step-and-shoot (SS) and sliding window (SW)], intensity levels for dose optimization, and dose calculation algorithms. Dosimetric effects on the pacemaker were calculated three dose engines: pencil-beam convolution (PBC), analytical anisotropic algorithm (AAA), and Acuros-XB. A lead shield of 2 mm thickness was designed for minimizing irradiated doses to the pacemaker. Dose variations affected by the heterogeneous material properties of the pacemaker and effectiveness of the lead shield were predicted by the Acuros-XB. Dose prediction accuracy and the feasibility of the dose reduction strategy were verified based on the measured skin doses right above the pacemaker using mosfet detectors during the radiation treatment. Results: The Acuros-XB showed underestimated skin doses and overestimated doses by the lead-shield effect, even though the lower dose disagreement was observed. It led to improved dose prediction with higher intensity level of dose optimization in IMRT. The dedicated tertiary lead sheet effectively achieved reduction of pacemaker dose up to 60%. Conclusion: The current SS technique could deliver lower scattered doses than recommendation criteria, however, use of the lead sheet contributed to reduce scattered doses.Thin lead plate can be a useful tertiary shielder and it could not acuse malfunction or electrical damage of the implanted pacemaker in IMRT. It is required to estimate more accurate scattered doses of the patient with medical device to design proper dose reduction strategy

  14. Predictive accuracy of Edinburgh Postnatal Depression Scale assessment during pregnancy for the risk of developing postpartum depressive symptoms : a prospective cohort study

    NARCIS (Netherlands)

    Meijer, J. L.; Beijers, C.; van Pampus, M. G.; Verbeek, T.; Stolk, R. P.; Milgrom, J.; Bockting, C. L. H.; Burger, H.

    2014-01-01

    ObjectiveTo investigate whether the 10-item Edinburgh Postnatal Depression Scale (EPDS) administered antenatally is accurate in predicting postpartum depressive symptoms, and whether a two-item EPDS has similar predictive accuracy. DesignProspective cohort study. SettingObstetric care in the

  15. Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks

    DEFF Research Database (Denmark)

    Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie

    2015-01-01

    to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands...

  16. Diagnostic Accuracy of Perioperative Measurement of Basal Anterior Pituitary and Target Gland Hormones in Predicting Adrenal Insufficiency After Pituitary Surgery.

    Science.gov (United States)

    Cerina, Vatroslav; Kruljac, Ivan; Radosevic, Jelena Marinkovic; Kirigin, Lora Stanka; Stipic, Darko; Pecina, Hrvoje Ivan; Vrkljan, Milan

    2016-03-01

    The insulin tolerance test (ITT) is the gold standard for diagnosing adrenal insufficiency (AI) after pituitary surgery. The ITT is unpleasant for patients, requires close medical supervision and is contraindicated in several comorbidities. The aim of this study was to analyze whether tumor size, remission rate, preoperative, and early postoperative baseline hormone concentrations could serve as predictors of AI in order to increase the diagnostic accuracy of morning serum cortisol. This prospective study enrolled 70 consecutive patients with newly diagnosed pituitary adenomas. Thirty-seven patients had nonfunctioning pituitary adenomas (NPA), 28 had prolactinomas and 5 had somatotropinomas. Thyroxin (T4), thyrotropin (TSH), prolactin, follicle-stimulating hormone (FSH), luteinizing hormone (LH), testosterone, and insulin-like growth factor 1 (IGF-I) were measured preoperatively and on the sixth postoperative day. Serum morning cortisol was measured on the third postoperative day (CORT3) as well as the sixth postoperative day (CORT6). Tumor mass was measured preoperatively and remission was assessed 3 months after surgery. An ITT was performed 3 to 6 months postoperatively. Remission was achieved in 48% of patients and AI occurred in 51%. Remission rates and tumor type were not associated with AI. CORT3 had the best predictive value for AI (area under the curve (AUC) 0.868, sensitivity 82.4%, specificity 83.3%). Tumor size, preoperative T4, postoperative T4, and TSH were also associated with AI in a multivariate regression model. A combination of all preoperative and postoperative variables (excluding serum cortisol) had a sensitivity of 75.0% and specificity of 77.8%. The predictive power of CORT3 substantially improved by adding those variables into the model (AUC 0.921, sensitivity 94.1%, specificity 78.3%, PPV 81.9%, NPV of 92.7%). In a subgroup analysis that included only female patients with NPA, LH had exactly the same predictive value as CORT3. The addition

  17. Culture shapes whether the pursuit of happiness predicts higher or lower well-being.

    Science.gov (United States)

    Ford, Brett Q; Dmitrieva, Julia O; Heller, Daniel; Chentsova-Dutton, Yulia; Grossmann, Igor; Tamir, Maya; Uchida, Yukiko; Koopmann-Holm, Birgit; Floerke, Victoria A; Uhrig, Meike; Bokhan, Tatiana; Mauss, Iris B

    2015-12-01

    Pursuing happiness can paradoxically impair well-being. Here, the authors propose the potential downsides to pursuing happiness may be specific to individualistic cultures. In collectivistic (vs. individualistic) cultures, pursuing happiness may be more successful because happiness is viewed--and thus pursued--in relatively socially engaged ways. In 4 geographical regions that vary in level of collectivism (United States, Germany, Russia, East Asia), we assessed participants' well-being, motivation to pursue happiness, and to what extent they pursued happiness in socially engaged ways. Motivation to pursue happiness predicted lower well-being in the United States, did not predict well-being in Germany, and predicted higher well-being in Russia and in East Asia. These cultural differences in the link between motivation to pursue happiness and well-being were explained by cultural differences in the socially engaged pursuit of happiness. These findings suggest that culture shapes whether the pursuit of happiness is linked with better or worse well-being, perhaps via how people pursue happiness. (c) 2015 APA, all rights reserved).

  18. Culture shapes whether the pursuit of happiness predicts higher or lower well-being

    Science.gov (United States)

    Ford, Brett Q.; Dmitrieva, Julia O.; Heller, Daniel; Chentsova-Dutton, Yulia; Grossmann, Igor; Tamir, Maya; Uchida, Yukiko; Koopmann-Holm, Birgit; Floerke, Victoria A.; Uhrig, Meike; Bokhan, Tatiana; Mauss, Iris B.

    2015-01-01

    Pursuing happiness can paradoxically impair well-being. Here, we propose the potential downsides to pursuing happiness may be specific to individualistic cultures. In collectivistic (vs. individualistic) cultures, pursuing happiness may be more successful because happiness is viewed – and thus pursued – in relatively socially-engaged ways. In four geographical regions that vary in level of collectivism (U.S., Germany, Russia, East Asia), we assessed participants’ well-being, motivation to pursue happiness, and to what extent they pursued happiness in socially-engaged ways. Motivation to pursue happiness predicted lower well-being in the U.S., did not predict well-being in Germany, and predicted higher well-being in Russia and in East Asia. These cultural differences in the link between motivation to pursue happiness and well-being were explained by cultural differences in the socially-engaged pursuit of happiness. These findings suggest that culture shapes whether the pursuit of happiness is linked with better or worse well-being, perhaps via how people pursue happiness. PMID:26347945

  19. Accuracy of gastrocnemius muscles forces in walking and running goats predicted by one-element and two-element Hill-type models.

    Science.gov (United States)

    Lee, Sabrina S M; Arnold, Allison S; Miara, Maria de Boef; Biewener, Andrew A; Wakeling, James M

    2013-09-03

    Hill-type models are commonly used to estimate muscle forces during human and animal movement-yet the accuracy of the forces estimated during walking, running, and other tasks remains largely unknown. Further, most Hill-type models assume a single contractile element, despite evidence that faster and slower motor units, which have different activation-deactivation dynamics, may be independently or collectively excited. This study evaluated a novel, two-element Hill-type model with "differential" activation of fast and slow contractile elements. Model performance was assessed using a comprehensive data set (including measures of EMG intensity, fascicle length, and tendon force) collected from the gastrocnemius muscles of goats during locomotor experiments. Muscle forces predicted by the new two-element model were compared to the forces estimated using traditional one-element models and to the forces measured in vivo using tendon buckle transducers. Overall, the two-element model resulted in the best predictions of in vivo gastrocnemius force. The coefficient of determination, r(2), was up to 26.9% higher and the root mean square error, RMSE, was up to 37.4% lower for the two-element model than for the one-element models tested. All models captured salient features of the measured muscle force during walking, trotting, and galloping (r(2)=0.26-0.51), and all exhibited some errors (RMSE=9.63-32.2% of the maximum in vivo force). These comparisons provide important insight into the accuracy of Hill-type models. The results also show that incorporation of fast and slow contractile elements within muscle models can improve estimates of time-varying, whole muscle force during locomotor tasks. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Validation and diagnostic accuracy of predictive curves for age-associated longitudinal cognitive decline in older adults

    Science.gov (United States)

    Bernier, Patrick J.; Gourdeau, Christian; Carmichael, Pierre-Hugues; Beauchemin, Jean-Pierre; Verreault, René; Bouchard, Rémi W.; Kröger, Edeltraut; Laforce, Robert

    2017-01-01

    BACKGROUND: The Mini-Mental State Examination continues to be used frequently to screen for cognitive impairment in older adults, but it remains unclear how to interpret changes in its score over time to distinguish age-associated cognitive decline from an early degenerative process. We aimed to generate cognitive charts for use in clinical practice for longitudinal evaluation of age-associated cognitive decline. METHODS: We used data from the Canadian Study of Health and Aging from 7569 participants aged 65 years or older who completed a Mini-Mental State Examination at baseline, and at 5 and 10 years later to develop a linear regression model for the Mini-Mental State Examination score as a function of age and education. Based on this model, we generated cognitive charts designed to optimize accuracy for distinguishing participants with dementia from healthy controls. We validated our model using a separate data set of 6501 participants from the National Alzheimer’s Coordinating Center’s Uniform Data Set. RESULTS: For baseline measurement, the cognitive charts had a sensitivity of 80% (95% confidence interval [CI] 75% to 84%) and a specificity of 89% (95% CI 88% to 90%) for distinguishing healthy controls from participants with dementia. Similar sensitivities and specificities were observed for a decline over time greater than 1 percentile zone from the first measurement. Results in the validation sample were comparable, albeit with lower sensitivities. Negative predictive value was 99%. INTERPRETATION: Our innovative model, which factors in age and education, showed validity and diagnostic accuracy for determining whether older patients show abnormal performance on serial Mini-Mental State Examination measurements. Similar to growth curves used in pediatrics, cognitive charts allow longitudinal cognitive evaluation and enable prompt initiation of investigation and treatment when appropriate. PMID:29203616

  1. Early static {sup 18}F-FET-PET scans have a higher accuracy for glioma grading than the standard 20-40 min scans

    Energy Technology Data Exchange (ETDEWEB)

    Albert, Nathalie L.; Winkelmann, Isabel; Wenter, Vera; Mille, Erik; Todica, Andrei; Brendel, Matthias; Bartenstein, Peter [Ludwig-Maximilians-University Munich, Department of Nuclear Medicine, Munich (Germany); Suchorska, Bogdana; Tonn, Joerg-Christian [Ludwig-Maximilians-University Munich, Department of Neurosurgery, Munich (Germany); Schmid-Tannwald, Christine [Ludwig-Maximilians-University Munich, Institute for Clinical Radiology, Munich (Germany); La Fougere, Christian [University of Tuebingen, Division of Nuclear Medicine and Clinical Molecular Imaging, Department of Radiology, Tuebingen (Germany)

    2016-06-15

    Current guidelines for glioma imaging by positron emission tomography (PET) using the amino acid analogue O-(2-[{sup 18}F]fluoroethyl)-L-tyrosine ({sup 18}F-FET) recommend image acquisition from 20-40 min post injection (p.i.). The maximal tumour-to-background evaluation (TBR{sub max}) obtained in these summation images does not enable reliable differentiation between low and high grade glioma (LGG and HGG), which, however, can be achieved by dynamic {sup 18}F-FET-PET. We investigated the accuracy of tumour grading using TBR{sub max} values at different earlier time points after tracer injection. Three hundred and fourteen patients with histologically proven primary diagnosis of glioma (131 LGG, 183 HGG) who had undergone 40-min dynamic {sup 18}F-FET-PET scans were retrospectively evaluated. TBR{sub max} was assessed in the standard 20-40 min summation images, as well as in summation images from 0-10 min, 5-15 min, 5-20 min, and 15-30 min p.i., and kinetic analysis was performed. TBR{sub max} values and kinetic analysis were correlated with histological classification. ROC analyses were performed for each time frame and sensitivity, specificity, and accuracy were assessed. TBR{sub max} values in the earlier summation images were significantly better for tumour grading (P < 0.001) when compared to standard 20-40 min scans, with best results for the early 5-15 min scan. This was due to higher TBR{sub max} in the HGG (3.9 vs. 3.3; p < 0.001), while TBR{sub max} remained nearly stable in the LGG (2.2 vs. 2.1). Overall, accuracy increased from 70 % in the 20-40 min analysis to 77 % in the 5-15 min images, but did not reach the accuracy of dynamic analysis (80 %). Early TBR{sub max} assessment (5-15 min p.i.) is more accurate for the differentiation between LGG and HGG than the standard static scan (20-40 min p.i.) mainly caused by the characteristic high {sup 18}F-FET uptake of HGG in the initial phase. Therefore, when dynamic {sup 18}F-FET-PET cannot be performed

  2. Higher Self-Control Capacity Predicts Lower Anxiety-Impaired Cognition during Math Examinations.

    Science.gov (United States)

    Bertrams, Alex; Baumeister, Roy F; Englert, Chris

    2016-01-01

    We assumed that self-control capacity, self-efficacy, and self-esteem would enable students to keep attentional control during tests. Therefore, we hypothesized that the three personality traits would be negatively related to anxiety-impaired cognition during math examinations. Secondary school students (N = 158) completed measures of self-control capacity, self-efficacy, and self-esteem at the beginning of the school year. Five months later, anxiety-impaired cognition during math examinations was assessed. Higher self-control capacity, but neither self-efficacy nor self-esteem, predicted lower anxiety-impaired cognition 5 months later, over and above baseline anxiety-impaired cognition. Moreover, self-control capacity was indirectly related to math grades via anxiety-impaired cognition. The findings suggest that improving self-control capacity may enable students to deal with anxiety-related problems during school tests.

  3. Higher Self-Control Capacity Predicts Lower Anxiety-Impaired Cognition During Math Examinations

    Directory of Open Access Journals (Sweden)

    Alex eBertrams

    2016-03-01

    Full Text Available We assumed that self-control capacity, self-efficacy, and self-esteem would enable students to keep attentional control during tests. Therefore, we hypothesized that the three personality traits would be negatively related to anxiety-impaired cognition during math examinations. Secondary school students (N = 158 completed measures of self-control capacity, self-efficacy, and self-esteem at the beginning of the school year. Five months later, anxiety-impaired cognition during math examinations was assessed. Higher self-control capacity, but neither self-efficacy nor self-esteem, predicted lower anxiety-impaired cognition five months later, over and above baseline anxiety-impaired cognition. Moreover, self-control capacity was indirectly related to math grades via anxiety-impaired cognition. The findings suggest that improving self-control capacity may enable students to deal with anxiety-related problems during school tests.

  4. Higher schizotypy predicts better metabolic profile in unaffected siblings of patients with schizophrenia.

    Science.gov (United States)

    Atbasoglu, E Cem; Gumus-Akay, Guvem; Guloksuz, Sinan; Saka, Meram Can; Ucok, Alp; Alptekin, Koksal; Gullu, Sevim; van Os, Jim

    2018-04-01

    Type 2 diabetes (T2D) is more frequent in schizophrenia (Sz) than in the general population. This association is partly accounted for by shared susceptibility genetic variants. We tested the hypotheses that a genetic predisposition to Sz would be associated with higher likelihood of insulin resistance (IR), and that IR would be predicted by subthreshold psychosis phenotypes. Unaffected siblings of Sz patients (n = 101) were compared with a nonclinical sample (n = 305) in terms of IR, schizotypy (SzTy), and a behavioural experiment of "jumping to conclusions". The measures, respectively, were the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), Structured Interview for Schizotypy-Revised (SIS-R), and the Beads Task (BT). The likelihood of IR was examined in multiple regression models that included sociodemographic, metabolic, and cognitive parameters alongside group status, SIS-R scores, and BT performance. Insulin resistance was less frequent in siblings (31.7%) compared to controls (43.3%) (p model that examined all relevant parameters included the tSzTy tertiles, TG and HDL-C levels, and BMI, as significant predictors of IR. Lack of IR was predicted by the highest as compared to the lowest SzTy tertile [OR (95%CI): 0.43 (0.21-0.85), p = 0.015]. Higher dopaminergic activity may contribute to both schizotypal features and a favourable metabolic profile in the same individual. This is compatible with dopamine's regulatory role in glucose metabolism via indirect central actions and a direct action on pancreatic insulin secretion. The relationship between dopaminergic activity and metabolic profile in Sz must be examined in longitudinal studies with younger unaffected siblings.

  5. Greenhouse crop residues: Energy potential and models for the prediction of their higher heating value

    Energy Technology Data Exchange (ETDEWEB)

    Callejon-Ferre, A.J.; Lopez-Martinez, J.A.; Manzano-Agugliaro, F. [Departamento de Ingenieria Rural, Universidad de Almeria, Ctra. Sacramento s/n, La Canada de San Urbano, 04120 Almeria (Spain); Velazquez-Marti, B. [Departamento de Ingenieria Rural y Agroalimentaria, Universidad Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain)

    2011-02-15

    Almeria, in southeastern Spain, generates some 1,086,261 t year{sup -1} (fresh weight) of greenhouse crop (Cucurbita pepo L., Cucumis sativus L., Solanum melongena L., Solanum lycopersicum L., Phaseoulus vulgaris L., Capsicum annuum L., Citrillus vulgaris Schrad. and Cucumis melo L.) residues. The energy potential of this biomass is unclear. The aim of the present work was to accurately quantify this variable, differentiating between crop species while taking into consideration the area they each occupy. This, however, required the direct analysis of the higher heating value (HHV) of these residues, involving very expensive and therefore not commonly available equipment. Thus, a further aim was to develop models for predicting the HHV of these residues, taking into account variables measured by elemental and/or proximate analysis, thus providing an economically attractive alternative to direct analysis. All the analyses in this work involved the use of worldwide-recognised standards and methods. The total energy potential for these plant residues, as determined by direct analysis, was 1,003,497.49 MW h year{sup -1}. Twenty univariate and multivariate equations were developed to predict the HHV. The R{sup 2} and adjusted R{sup 2} values obtained for the univariate and multivariate models were 0.909 and 0.946 or above respectively. In all cases, the mean absolute percentage error varied between 0.344 and 2.533. These results show that any of these 20 equations could be used to accurately predict the HHV of crop residues. The residues produced by the Almeria greenhouse industry would appear to be an interesting source of renewable energy. (author)

  6. Overgeneral autobiographical memory predicts higher prospective levels of depressive symptoms and intrusions in borderline patients.

    Science.gov (United States)

    Van den Broeck, Kris; Pieters, Guido; Claes, Laurence; Berens, Ann; Raes, Filip

    2016-11-01

    Overgeneral memory (OGM), the tendency to retrieve categories of events from autobiographical memory instead of single events, is found to be a reliable predictor for future mood disturbances and post-traumatic symptom severity. Patients with borderline personality disorder (BPD) often report co-morbid episodes of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). Therefore, we investigated whether OGM would predict depression severity and (post-traumatic) stress symptoms in BPD patients. At admission (N = 54) and at six-month follow-up (N ≥ 31), BPD patients completed the Structured Clinical Interview for DSM-IV Disorders, the Assessment of DSM-IV Personality Disorders, the Autobiographical Memory Test, the Beck Depression Inventory-2nd edition (BDI-II), and the Impact of Event Scale. OGM at baseline predicted (a) higher levels of depressive symptoms at follow-up and (b) more intrusions related to a stressful event over and above baseline levels of borderline symptoms, depressive symptoms, and intrusions, respectively. No association was found between memory specificity and event-related avoidance at follow-up. Despite previous findings suggesting that OGM in BPD is less robust than in MDD and PTSD, our results suggest that memory specificity in BPD patients may have some relevance for the course of depressive and stress symptomatology in BPD.

  7. Lower- and higher-order aberrations predicted by an optomechanical model of arcuate keratotomy for astigmatism.

    Science.gov (United States)

    Navarro, Rafael; Palos, Fernando; Lanchares, Elena; Calvo, Begoña; Cristóbal, José A

    2009-01-01

    To develop a realistic model of the optomechanical behavior of the cornea after curved relaxing incisions to simulate the induced astigmatic change and predict the optical aberrations produced by the incisions. ICMA Consejo Superior de Investigaciones Científicas and Universidad de Zaragoza, Zaragoza, Spain. A 3-dimensional finite element model of the anterior hemisphere of the ocular surface was used. The corneal tissue was modeled as a quasi-incompressible, anisotropic hyperelastic constitutive behavior strongly dependent on the physiological collagen fibril distribution. Similar behaviors were assigned to the limbus and sclera. With this model, some corneal incisions were computer simulated after the Lindstrom nomogram. The resulting geometry of the biomechanical simulation was analyzed in the optical zone, and finite ray tracing was performed to compute refractive power and higher-order aberrations (HOAs). The finite-element simulation provided new geometry of the corneal surfaces, from which elevation topographies were obtained. The surgically induced astigmatism (SIA) of the simulated incisions according to the Lindstrom nomogram was computed by finite ray tracing. However, paraxial computations would yield slightly different results (undercorrection of astigmatism). In addition, arcuate incisions would induce significant amounts of HOAs. Finite-element models, together with finite ray-tracing computations, yielded realistic simulations of the biomechanical and optical changes induced by relaxing incisions. The model reproduced the SIA indicated by the Lindstrom nomogram for the simulated incisions and predicted a significant increase in optical aberrations induced by arcuate keratotomy.

  8. Surgical planning of total hip arthroplasty: accuracy of computer-assisted EndoMap software in predicting component size

    International Nuclear Information System (INIS)

    Davila, Jesse A.; Kransdorf, Mark J.; Duffy, Gavan P.

    2006-01-01

    The purpose of our study was to assess the accuracy of a computer-assisted templating in the surgical planning of patients undergoing total hip arthroplasty utilizing EndoMap software (Siemans AG, Medical Solutions, Erlangen, Germany). Endomap Software is an electronic program that uses DICOM images to analyze standard anteroposterior radiographs for determination of optimal prosthesis component size. We retrospectively reviewed the preoperative radiographs of 36 patients undergoing uncomplicated primary total hip arthroplasty, utilizing EndoMap software, Version VA20. DICOM anteroposterior radiographs were analyzed using standard manufacturer supplied electronic templates to determine acetabular and femoral component sizes. No additional clinical information was reviewed. Acetabular and femoral component sizes were assessed by an orthopedic surgeon and two radiologists. Mean and estimated component size was compared with component size as documented in operative reports. The mean estimated acetabular component size was 53 mm (range 48-60 mm), 1 mm larger than the mean implanted size of 52 mm (range 48-62 mm). Thirty-one of 36 acetabular component sizes (86%) were accurate within one size. The mean calculated femoral component size was 4 (range 2-7), 1 size smaller than the actual mean component size of 5 (range 2-9). Twenty-six of 36 femoral component sizes (72%) were accurate within one size, and accurate within two sizes in all but four cases (94%). EndoMap Software predicted femoral component size well, with 72% within one component size of that used, and 94% within two sizes. Acetabular component size was predicted slightly better with 86% within one component size and 94% within two component sizes. (orig.)

  9. Higher resting heart rate variability predicts skill in expressing some emotions.

    Science.gov (United States)

    Tuck, Natalie L; Grant, Rosemary C I; Sollers, John J; Booth, Roger J; Consedine, Nathan S

    2016-12-01

    Vagally mediated heart rate variability (vmHRV) is a measure of cardiac vagal tone, and is widely viewed as a physiological index of the capacity to regulate emotions. However, studies have not directly tested whether vmHRV is associated with the ability to facially express emotions. In extending prior work, the current report tested links between resting vmHRV and the objectively assessed ability to facially express emotions, hypothesizing that higher vmHRV would predict greater expressive skill. Eighty healthy women completed self-reported measures, before attending a laboratory session in which vmHRV and the ability to express six emotions in the face were assessed. A repeated measures analysis of variance revealed a marginal main effect for vmHRV on skill overall; individuals with higher resting vmHRV were only better able to deliberately facially express anger and interest. Findings suggest that differences in resting vmHRV are associated with the objectively assessed ability to facially express some, but not all, emotions, with potential implications for health and well-being. © 2016 Society for Psychophysiological Research.

  10. Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial

    DEFF Research Database (Denmark)

    Winkler Wille, Mathilde M.; van Riel, Sarah J.; Saghir, Zaigham

    2015-01-01

    Objectives: Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. Methods: From...... the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were...... used to evaluate risk discrimination. Results: AUCs of 0.826–0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer...

  11. SU-F-T-119: Development of Heart Prediction Model to Increase Accuracy of Dose Reconstruction for Radiotherapy Patients

    Energy Technology Data Exchange (ETDEWEB)

    Mosher, E; Choi, M; Lee, C [Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD (United States); Jones, E [Radiology and Imaging Sciences Clinical Center, National Institutes of Health, Bethesda, MD (United States)

    2016-06-15

    Purpose: To assess individual variation in heart volume and location in order to develop a prediction model of the heart. This heart prediction model will be used to calculate individualized heart doses for radiotherapy patients in epidemiological studies. Methods: Chest CT images for 30 adult male and 30 adult female patients were obtained from NIH Clinical Center. Image-analysis computer programs were used to segment the whole heart and 8 sub-regions and to measure the volume of each sub- region and the dimension of the whole heart. An analytical dosimetry method was used for the 30 adult female patients to estimate mean heart dose during conventional left breast radiotherapy. Results: The average volumes of the whole heart were 803.37 cm{sup 3} (COV 18.8%) and 570.19 cm{sup 3} (COV 18.8%) for adult male and female patients, respectively, which are comparable with the international reference volumes of 807.69 cm{sup 3} for males and 596.15 cm{sup 3} for females. Some patient characteristics were strongly correlated (R{sup 2}>0.5) with heart volume and heart dimensions (e.g., Body Mass Index vs. heart depth in males: R{sup 2}=0.54; weight vs. heart width in the adult females: R{sup 2}=0.63). We found that the mean heart dose 3.805 Gy (assuming prescribed dose of 50 Gy) in the breast radiotherapy simulations of the 30 adult females could be an underestimate (up to 1.6-fold) or overestimate (up to 1.8-fold) of the patient-specific heart dose. Conclusion: The study showed the significant variation in patient heart volumes and dimensions, resulting in substantial dose errors when a single average heart model is used for retrospective dose reconstruction. We are completing a multivariate analysis to develop a prediction model of the heart. This model will increase accuracy in dose reconstruction for radiotherapy patients and allow us to individualize heart dose calculations for patients whose CT images are not available.

  12. SU-F-T-119: Development of Heart Prediction Model to Increase Accuracy of Dose Reconstruction for Radiotherapy Patients

    International Nuclear Information System (INIS)

    Mosher, E; Choi, M; Lee, C; Jones, E

    2016-01-01

    Purpose: To assess individual variation in heart volume and location in order to develop a prediction model of the heart. This heart prediction model will be used to calculate individualized heart doses for radiotherapy patients in epidemiological studies. Methods: Chest CT images for 30 adult male and 30 adult female patients were obtained from NIH Clinical Center. Image-analysis computer programs were used to segment the whole heart and 8 sub-regions and to measure the volume of each sub- region and the dimension of the whole heart. An analytical dosimetry method was used for the 30 adult female patients to estimate mean heart dose during conventional left breast radiotherapy. Results: The average volumes of the whole heart were 803.37 cm"3 (COV 18.8%) and 570.19 cm"3 (COV 18.8%) for adult male and female patients, respectively, which are comparable with the international reference volumes of 807.69 cm"3 for males and 596.15 cm"3 for females. Some patient characteristics were strongly correlated (R"2>0.5) with heart volume and heart dimensions (e.g., Body Mass Index vs. heart depth in males: R"2=0.54; weight vs. heart width in the adult females: R"2=0.63). We found that the mean heart dose 3.805 Gy (assuming prescribed dose of 50 Gy) in the breast radiotherapy simulations of the 30 adult females could be an underestimate (up to 1.6-fold) or overestimate (up to 1.8-fold) of the patient-specific heart dose. Conclusion: The study showed the significant variation in patient heart volumes and dimensions, resulting in substantial dose errors when a single average heart model is used for retrospective dose reconstruction. We are completing a multivariate analysis to develop a prediction model of the heart. This model will increase accuracy in dose reconstruction for radiotherapy patients and allow us to individualize heart dose calculations for patients whose CT images are not available.

  13. Diagnostic accuracy of soluble urokinase plasminogen activator receptor (suPAR) for prediction of bacteremia in patients with systemic inflammatory response syndrome.

    Science.gov (United States)

    Hoenigl, Martin; Raggam, Reinhard B; Wagner, Jasmin; Valentin, Thomas; Leitner, Eva; Seeber, Katharina; Zollner-Schwetz, Ines; Krammer, Werner; Prüller, Florian; Grisold, Andrea J; Krause, Robert

    2013-02-01

    Soluble urokinase plasminogen activator receptor (suPAR) serum concentrations have recently been described to reflect the severity status of systemic inflammation. In this study, the diagnostic accuracy of suPAR, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6) to predict bacteremia in patients with systemic inflammatory response syndrome (SIRS) was compared. A total of 132 patients with SIRS were included. In 55 patients blood cultures had resulted positive (study group 1, Gram positive bacteria: Staphylococcus aureus and Streptococcus spp., n=15; study group 2, Gram-negative bacteria, n=40) and 77 patients had negative blood culture results (control group, n=77). Simultaneously with blood cultures suPAR, CRP, PCT, IL-6 and white blood count (WBC) were determined. SuPAR values were significantly higher in study group 1 (median 8.11; IQR 5.78-15.53; p=0.006) and study group 2 (median 9.62; IQR 6.52-11.74; p<0.001) when compared with the control group (median 5.65; IQR 4.30-7.83). ROC curve analysis revealed an AUC of 0.726 for suPAR in differentiating SIRS patients with bacteremia from those without. The biomarkers PCT and IL-6 showed comparable results. Regarding combinations of biomarkers multiplying suPAR, PCT and IL-6 was most promising and resulted in an AUC value of 0.804. Initial suPAR serum concentrations were significantly higher (p=0.028) in patients who died within 28 days than in those who survived. No significant difference was seen for PCT, IL-6 and CRP. In conclusion, suPAR, IL-6 and PCT may contribute to predicting bacteremia in SIRS patients. Copyright © 2012 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  14. Prediction of higher cost of antiretroviral therapy (ART) according to clinical complexity. A validated clinical index.

    Science.gov (United States)

    Velasco, Cesar; Pérez, Inaki; Podzamczer, Daniel; Llibre, Josep Maria; Domingo, Pere; González-García, Juan; Puig, Inma; Ayala, Pilar; Martín, Mayte; Trilla, Antoni; Lázaro, Pablo; Gatell, Josep Maria

    2016-03-01

    The financing of antiretroviral therapy (ART) is generally determined by the cost incurred in the previous year, the number of patients on treatment, and the evidence-based recommendations, but not the clinical characteristics of the population. To establish a score relating the cost of ART and patient clinical complexity in order to understand the costing differences between hospitals in the region that could be explained by the clinical complexity of their population. Retrospective analysis of patients receiving ART in a tertiary hospital between 2009 and 2011. Factors potentially associated with a higher cost of ART were assessed by bivariate and multivariate analysis. Two predictive models of "high-cost" were developed. The normalized estimated (adjusted for the complexity scores) costs were calculated and compared with the normalized real costs. In the Hospital Index, 631 (16.8%) of the 3758 patients receiving ART were responsible for a "high-cost" subgroup, defined as the highest 25% of spending on ART. Baseline variables that were significant predictors of high cost in the Clinic-B model in the multivariate analysis were: route of transmission of HIV, AIDS criteria, Spanish nationality, year of initiation of ART, CD4+ lymphocyte count nadir, and number of hospital admissions. The Clinic-B score ranged from 0 to 13, and the mean value (5.97) was lower than the overall mean value of the four hospitals (6.16). The clinical complexity of the HIV patient influences the cost of ART. The Clinic-B and Clinic-BF scores predicted patients with high cost of ART and could be used to compare and allocate costs corrected for the patient clinical complexity. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

  15. Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

    NARCIS (Netherlands)

    Calus, M.P.L.; Meuwissen, T.H.E.; Windig, J.J.; Knol, E.F.; Schrooten, C.; Vereijken, A.L.J.; Veerkamp, R.F.

    2009-01-01

    The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e.

  16. Accuracy of Prediction Equations to Assess Percentage of Body Fat in Children and Adolescents with Down Syndrome Compared to Air Displacement Plethysmography

    Science.gov (United States)

    Gonzalez-Aguero, A.; Vicente-Rodriguez, G.; Ara, I.; Moreno, L. A.; Casajus, J. A.

    2011-01-01

    To determine the accuracy of the published percentage body fat (%BF) prediction equations (Durnin et al., Johnston et al., Brook and Slaughter et al.) from skinfold thickness compared to air displacement plethysmography (ADP) in children and adolescents with Down syndrome (DS). Twenty-eight children and adolescents with DS (10-20 years old; 12…

  17. Agency Beliefs Over Time and Across Cultures: Free Will Beliefs Predict Higher Job Satisfaction

    Science.gov (United States)

    Feldman, Gilad; Farh, Jiing-Lih; Wong, Kin Fai Ellick

    2017-01-01

    In three studies, we examined the relationship between free will beliefs and job satisfaction over time and across cultures. Study 1 examined 252 Taiwanese real-estate agents over a 3-months period. Study 2 examined job satisfaction for 137 American workers on an online labor market over a 6-months period. Study 3 extended to a large sample of 14,062 employees from 16 countries and examined country-level moderators. We found a consistent positive relationship between the belief in free will and job satisfaction. The relationship was above and beyond other agency constructs (Study 2), mediated by perceived autonomy (Studies 2-3), and stronger in countries with a higher national endorsement of the belief in free will (Study 3). We conclude that free-will beliefs predict outcomes over time and across cultures beyond other agency constructs. We call for more cross-cultural and longitudinal studies examining free-will beliefs as predictors of real-life outcomes. PMID:29191084

  18. Diagnostic accuracy of S100B urinary testing at birth in full-term asphyxiated newborns to predict neonatal death.

    Directory of Open Access Journals (Sweden)

    Diego Gazzolo

    Full Text Available BACKGROUND: Neonatal death in full-term infants who suffer from perinatal asphyxia (PA is a major subject of investigation, since few tools exist to predict patients at risk of ominous outcome. We studied the possibility that urine S100B measurement may identify which PA-affected infants are at risk of early postnatal death. METHODOLOGY/PRINCIPAL FINDINGS: In a cross-sectional study between January 1, 2001 and December 1, 2006 we measured S100B protein in urine collected from term infants (n = 132, 60 of whom suffered PA. According to their outcome at 7 days, infants with PA were subsequently classified either as asphyxiated infants complicated by hypoxic ischemic encephalopathy with no ominous outcome (HIE Group; n = 48, or as newborns who died within the first post-natal week (Ominous Outcome Group; n = 12. Routine laboratory variables, cerebral ultrasound, neurological patterns and urine concentrations of S100B protein were determined at first urination and after 24, 48 and 96 hours. The severity of illness in the first 24 hours after birth was measured using the Score for Neonatal Acute Physiology-Perinatal Extension (SNAP-PE. Urine S100B levels were higher from the first urination in the ominous outcome group than in healthy or HIE Groups (p1.0 microg/L S100B had a sensitivity/specificity of 100% for predicting neonatal death. CONCLUSIONS/SIGNIFICANCE: Increased S100B protein urine levels in term newborns suffering PA seem to suggest a higher risk of neonatal death for these infants.

  19. A comparison of accuracy validation methods for genomic and pedigree-based predictions of swine litter size traits using Large White and simulated data.

    Science.gov (United States)

    Putz, A M; Tiezzi, F; Maltecca, C; Gray, K A; Knauer, M T

    2018-02-01

    The objective of this study was to compare and determine the optimal validation method when comparing accuracy from single-step GBLUP (ssGBLUP) to traditional pedigree-based BLUP. Field data included six litter size traits. Simulated data included ten replicates designed to mimic the field data in order to determine the method that was closest to the true accuracy. Data were split into training and validation sets. The methods used were as follows: (i) theoretical accuracy derived from the prediction error variance (PEV) of the direct inverse (iLHS), (ii) approximated accuracies from the accf90(GS) program in the BLUPF90 family of programs (Approx), (iii) correlation between predictions and the single-step GEBVs from the full data set (GEBV Full ), (iv) correlation between predictions and the corrected phenotypes of females from the full data set (Y c ), (v) correlation from method iv divided by the square root of the heritability (Y ch ) and (vi) correlation between sire predictions and the average of their daughters' corrected phenotypes (Y cs ). Accuracies from iLHS increased from 0.27 to 0.37 (37%) in the Large White. Approximation accuracies were very consistent and close in absolute value (0.41 to 0.43). Both iLHS and Approx were much less variable than the corrected phenotype methods (ranging from 0.04 to 0.27). On average, simulated data showed an increase in accuracy from 0.34 to 0.44 (29%) using ssGBLUP. Both iLHS and Y ch approximated the increase well, 0.30 to 0.46 and 0.36 to 0.45, respectively. GEBV Full performed poorly in both data sets and is not recommended. Results suggest that for within-breed selection, theoretical accuracy using PEV was consistent and accurate. When direct inversion is infeasible to get the PEV, correlating predictions to the corrected phenotypes divided by the square root of heritability is adequate given a large enough validation data set. © 2017 Blackwell Verlag GmbH.

  20. Potential of EnMAP spaceborne imaging spectroscopy for the prediction of common surface soil properties and expected accuracy

    Science.gov (United States)

    Chabrillat, Sabine; Foerster, Saskia; Steinberg, Andreas; Stevens, Antoine; Segl, Karl

    2016-04-01

    There is a renewed awareness of the finite nature of the world's soil resources, growing concern about soil security, and significant uncertainties about the carrying capacity of the planet. As a consequence, soil scientists are being challenged to provide regular assessments of soil conditions from local through to global scales. However, only a few countries have the necessary survey and monitoring programs to meet these new needs and existing global data sets are out-of-date. A particular issue is the clear demand for a new area-wide regional to global coverage with accurate, up-to-date, and spatially referenced soil information as expressed by the modeling scientific community, farmers and land users, and policy and decision makers. Soil spectroscopy from remote sensing observations based on studies from the laboratory scale to the airborne scale has been shown to be a proven method for the quantitative prediction of key soil surface properties in local areas for exposed soils in appropriate surface conditions such as low vegetation cover and low water content. With the upcoming launch of the next generation of hyperspectral satellite sensors in the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. Nevertheless, the capabilities to extend the soil properties current spectral modeling from local to regional scales are still to be demonstrated using robust methods. In particular, three central questions are at the forefront of research nowadays: a) methodological developments toward improved algorithms and operational tools for the extraction of soil properties, b) up scaling from the laboratory into space domain, and c) demonstration of the potential of upcoming satellite systems and expected accuracy of soil maps. In this study, airborne imaging spectroscopy data from several test sites are used to simulate EnMAP satellite images at 30 m scale. Then, different soil

  1. New Parameters for Higher Accuracy in the Computation of Binding Free Energy Differences upon Alanine Scanning Mutagenesis on Protein-Protein Interfaces.

    Science.gov (United States)

    Simões, Inês C M; Costa, Inês P D; Coimbra, João T S; Ramos, Maria J; Fernandes, Pedro A

    2017-01-23

    Knowing how proteins make stable complexes enables the development of inhibitors to preclude protein-protein (P:P) binding. The identification of the specific interfacial residues that mostly contribute to protein binding, denominated as hot spots, is thus critical. Here, we refine an in silico alanine scanning mutagenesis protocol, based on a residue-dependent dielectric constant version of the Molecular Mechanics/Poisson-Boltzmann Surface Area method. We have used a large data set of structurally diverse P:P complexes to redefine the residue-dependent dielectric constants used in the determination of binding free energies. The accuracy of the method was validated through comparison with experimental data, considering the per-residue P:P binding free energy (ΔΔG binding ) differences upon alanine mutation. Different protocols were tested, i.e., a geometry optimization protocol and three molecular dynamics (MD) protocols: (1) one using explicit water molecules, (2) another with an implicit solvation model, and (3) a third where we have carried out an accelerated MD with explicit water molecules. Using a set of protein dielectric constants (within the range from 1 to 20) we showed that the dielectric constants of 7 for nonpolar and polar residues and 11 for charged residues (and histidine) provide optimal ΔΔG binding predictions. An overall mean unsigned error (MUE) of 1.4 kcal mol -1 relative to the experiment was achieved in 210 mutations only with geometry optimization, which was further reduced with MD simulations (MUE of 1.1 kcal mol -1 for the MD employing explicit solvent). This recalibrated method allows for a better computational identification of hot spots, avoiding expensive and time-consuming experiments or thermodynamic integration/ free energy perturbation/ uBAR calculations, and will hopefully help new drug discovery campaigns in their quest of searching spots of interest for binding small drug-like molecules at P:P interfaces.

  2. Racial Discrimination and Low Household Education Predict Higher Body Mass Index in African American Youth.

    Science.gov (United States)

    Nelson, Devin S; Gerras, Julia M; McGlumphy, Kellye C; Shaver, Erika R; Gill, Amaanat K; Kanneganti, Kamala; Ajibewa, Tiwaloluwa A; Hasson, Rebecca E

    The purpose of this study was to examine the relationships between environmental factors, including household education, community violence exposure, racial discrimination, and cultural identity, and BMI in African American adolescents. A community-based sample of 198 African American youth (120 girls, 78 boys; ages 11-19 years) from Washtenaw County, Michigan, were included in this analysis. Violence exposure was assessed by using the Survey of Children's Exposure to Community Violence; racial discrimination by using the Adolescent Discrimination Distress Index; cultural identity by using the Acculturation, Habits, and Interests Multicultural Scale for Adolescents; and household education by using a seven-category variable. Measured height and body weight were used to calculate BMI. Racial discrimination was positively associated with BMI, whereas household education was inversely associated with BMI in African American adolescents (discrimination: β = 0.11 ± 0.04, p = 0.01; education: β = -1.13 ± 0.47, p = 0.02). These relationships were significant when accounting for the confounding effects of stress, activity, diet, and pubertal development. Significant gender interactions were observed with racial discrimination and low household education associated with BMI in girls only (discrimination: β = 0.16 ± 0.05, p = 0.003; education: β = -1.12 ± 0.55, p = 0.045). There were no significant relationships between culture, community violence exposure, and BMI (all p's > 0.05). Environmental factors, including racial discrimination and low household education, predicted higher BMI in African American adolescents, particularly among girls. Longitudinal studies are needed to better understand the mechanisms by which these environmental factors increase obesity risk in African American youth.

  3. Predictive accuracy of the PanCan lung cancer risk prediction model - external validation based on CT from the Danish Lung Cancer Screening Trial

    International Nuclear Information System (INIS)

    Winkler Wille, Mathilde M.; Dirksen, Asger; Riel, Sarah J. van; Jacobs, Colin; Scholten, Ernst T.; Ginneken, Bram van; Saghir, Zaigham; Pedersen, Jesper Holst; Hohwue Thomsen, Laura; Skovgaard, Lene T.

    2015-01-01

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. From the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were used to evaluate risk discrimination. AUCs of 0.826-0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer; in fact opposing effects of sex were observed in the two cohorts. Thus, female sex appeared to lower the risk (p = 0.047 and p = 0.040) in the DLCST. High risk discrimination was validated in the DLCST cohort, mainly determined by nodule size. Age and family history of lung cancer were significant predictors and could be included in the parsimonious model. Sex appears to be a less useful predictor. (orig.)

  4. Predictive accuracy of the PanCan lung cancer risk prediction model - external validation based on CT from the Danish Lung Cancer Screening Trial

    Energy Technology Data Exchange (ETDEWEB)

    Winkler Wille, Mathilde M.; Dirksen, Asger [Gentofte Hospital, Department of Respiratory Medicine, Hellerup (Denmark); Riel, Sarah J. van; Jacobs, Colin; Scholten, Ernst T.; Ginneken, Bram van [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Saghir, Zaigham [Herlev Hospital, Department of Respiratory Medicine, Herlev (Denmark); Pedersen, Jesper Holst [Copenhagen University Hospital, Department of Thoracic Surgery, Rigshospitalet, Koebenhavn Oe (Denmark); Hohwue Thomsen, Laura [Hvidovre Hospital, Department of Respiratory Medicine, Hvidovre (Denmark); Skovgaard, Lene T. [University of Copenhagen, Department of Biostatistics, Koebenhavn Oe (Denmark)

    2015-10-15

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. From the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were used to evaluate risk discrimination. AUCs of 0.826-0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer; in fact opposing effects of sex were observed in the two cohorts. Thus, female sex appeared to lower the risk (p = 0.047 and p = 0.040) in the DLCST. High risk discrimination was validated in the DLCST cohort, mainly determined by nodule size. Age and family history of lung cancer were significant predictors and could be included in the parsimonious model. Sex appears to be a less useful predictor. (orig.)

  5. Predicting University Preference and Attendance: Applied Marketing in Higher Education Administration.

    Science.gov (United States)

    Cook, Robert W.; Zallocco, Ronald L.

    1983-01-01

    A multi-attribute attitude model was used to determine whether a multicriteria scale can be used to predict student preferences for and attendance at universities. Data were gathered from freshmen attending five state universities in Ohio. The results indicate a high level of predictability. (Author/MLW)

  6. Humor Ability Reveals Intelligence, Predicts Mating Success, and Is Higher in Males

    Science.gov (United States)

    Greengross, Gil; Miller, Geoffrey

    2011-01-01

    A good sense of humor is sexually attractive, perhaps because it reveals intelligence, creativity, and other "good genes" or "good parent" traits. If so, intelligence should predict humor production ability, which in turn should predict mating success. In this study, 400 university students (200 men and 200 women) completed…

  7. The power within: The experimental manipulation of power interacts with trait BDD symptoms to predict interoceptive accuracy.

    Science.gov (United States)

    Kunstman, Jonathan W; Clerkin, Elise M; Palmer, Kateyln; Peters, M Taylar; Dodd, Dorian R; Smith, April R

    2016-03-01

    This study tested whether relatively low levels of interoceptive accuracy (IAcc) are associated with body dysmorphic disorder (BDD) symptoms. Additionally, given research indicating that power attunes individuals to their internal states, we sought to determine if state interoceptive accuracy could be improved through an experimental manipulation of power.. Undergraduate women (N = 101) completed a baseline measure of interoceptive accuracy and then were randomized to a power or control condition. Participants were primed with power or a neutral control topic and then completed a post-manipulation measure of state IAcc. Trait BDD symptoms were assessed with a self-report measure. Controlling for baseline IAcc, within the control condition, there was a significant inverse relationship between trait BDD symptoms and interoceptive accuracy. Continuing to control for baseline IAcc, within the power condition, there was not a significant relationship between trait BDD symptoms and IAcc, suggesting that power may have attenuated this relationship. At high levels of BDD symptomology, there was also a significant simple effect of experimental condition, such that participants in the power (vs. control) condition had better interoceptive accuracy. These results provide initial evidence that power may positively impact interoceptive accuracy among those with high levels of BDD symptoms.. This cross-sectional study utilized a demographically homogenous sample of women that reflected a broad range of symptoms; thus, although there were a number of participants reporting elevated BDD symptoms, these findings might not generalize to other populations or clinical samples. This study provides the first direct test of the relationship between trait BDD symptoms and IAcc, and provides preliminary evidence that among those with severe BDD symptoms, power may help connect individuals with their internal states. Future research testing the mechanisms linking BDD symptoms with IAcc, as

  8. Comparison of predictive accuracy of pre surgical serum parathormone (PTH) level with that of parathyroid scan in case of primary hyperparathyroidism

    International Nuclear Information System (INIS)

    Nasreen, F.; Yasmeen, S.; Ahsan, A.S.M.; Mandal, T.; Sultana, K.S.A.; Shirin, A.

    2007-01-01

    Full text: Aims and Objective: Parathyroid scintigraphy with Tc-99m Sestamibi is a sensitive and specific test for pre operative localization of parathyroid adenoma (PA) in patients with primary hyperparathyroidism. However false ve studies are not uncommon. Our aim was to find out the predictive accuracy of pre surgical parathormone (PTH) level with that of parathyroid scan in case of primary hyperparathyroidism. Materials And Method: A total of 54 patients (29 male, 25 female) with a mean age of 41. 24+14.26 years suspected of primary hyperparathyroidism were included in this study. All patients had serum PTH and calcium level higher than the normal limit. Parathyroid scintigraphy was done by subtraction method using 185 MBq of Tc-99m PO4 which was given first and images were taken by planar gamma camera after 20 minutes followed by Tc-99m Sestamibi (740MBq) injection without moving the patient. We calculated the sensitivity and specificity at different cut off values of PTH such as >70pg/ml, >80pg/ml, >90pg/ml and >100pg/ml and observed the changes in sensitivity, specificity, PPV and NPV against scintigraphic diagnosis of PA. Result: Parathyroid scintigraphy revealed 15 positive cases (27.8%) amongst 54 patients, which were surgically proven to be so. The sensitivity of PTH in predicting positive parathyroid scan revealed to be 86.7% at serum PTH level of 70-90pg/ml. Then the sensitivity declines steadily to 73.3% at PTH level of >100pg/ml. The specificity increases gradually from 20.5% at serum PTH level >70pg/ml to 53.8% at serum PTH level >100pg/ml. However, PPV and NPV of serum PTH did not experience significant change like sensitivity and specificity with the increase of cut off values. Conclusion: We can use a cut off value of pre surgical serum PTH level at 90pg/ml before doing parathyroid scan as this has maximum sensitivity and optimum specificity. It will help to predict the outcome of scan and avoid unnecessary parathyroid scan and false ve cases

  9. Relationship between the Prediction Accuracy of Tsunami Inundation and Relative Distribution of Tsunami Source and Observation Arrays: A Case Study in Tokyo Bay

    Science.gov (United States)

    Takagawa, T.

    2017-12-01

    A rapid and precise tsunami forecast based on offshore monitoring is getting attention to reduce human losses due to devastating tsunami inundation. We developed a forecast method based on the combination of hierarchical Bayesian inversion with pre-computed database and rapid post-computing of tsunami inundation. The method was applied to Tokyo bay to evaluate the efficiency of observation arrays against three tsunamigenic earthquakes. One is a scenario earthquake at Nankai trough and the other two are historic ones of Genroku in 1703 and Enpo in 1677. In general, rich observation array near the tsunami source has an advantage in both accuracy and rapidness of tsunami forecast. To examine the effect of observation time length we used four types of data with the lengths of 5, 10, 20 and 45 minutes after the earthquake occurrences. Prediction accuracy of tsunami inundation was evaluated by the simulated tsunami inundation areas around Tokyo bay due to target earthquakes. The shortest time length of accurate prediction varied with target earthquakes. Here, accurate prediction means the simulated values fall within the 95% credible intervals of prediction. In Enpo earthquake case, 5-minutes observation is enough for accurate prediction for Tokyo bay, but 10-minutes and 45-minutes are needed in the case of Nankai trough and Genroku, respectively. The difference of the shortest time length for accurate prediction shows the strong relationship with the relative distance from the tsunami source and observation arrays. In the Enpo case, offshore tsunami observation points are densely distributed even in the source region. So, accurate prediction can be rapidly achieved within 5 minutes. This precise prediction is useful for early warnings. Even in the worst case of Genroku, where less observation points are available near the source, accurate prediction can be obtained within 45 minutes. This information can be useful to figure out the outline of the hazard in an early

  10. 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.

    Science.gov (United States)

    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.

  11. Effect of Trait Heritability, Training Population Size and Marker Density on Genomic Prediction Accuracy Estimation in 22 bi-parental Tropical Maize Populations.

    Science.gov (United States)

    Zhang, Ao; Wang, Hongwu; Beyene, Yoseph; Semagn, Kassa; Liu, Yubo; Cao, Shiliang; Cui, Zhenhai; Ruan, Yanye; Burgueño, Juan; San Vicente, Felix; Olsen, Michael; Prasanna, Boddupalli M; Crossa, José; Yu, Haiqiu; Zhang, Xuecai

    2017-01-01

    Genomic selection is being used increasingly in plant breeding to accelerate genetic gain per unit time. One of the most important applications of genomic selection in maize breeding is to predict and select the best un-phenotyped lines in bi-parental populations based on genomic estimated breeding values. In the present study, 22 bi-parental tropical maize populations genotyped with low density SNPs were used to evaluate the genomic prediction accuracy ( r MG ) of the six trait-environment combinations under various levels of training population size (TPS) and marker density (MD), and assess the effect of trait heritability ( h 2 ), TPS and MD on r MG estimation. Our results showed that: (1) moderate r MG values were obtained for different trait-environment combinations, when 50% of the total genotypes was used as training population and ~200 SNPs were used for prediction; (2) r MG increased with an increase in h 2 , TPS and MD, both correlation and variance analyses showed that h 2 is the most important factor and MD is the least important factor on r MG estimation for most of the trait-environment combinations; (3) predictions between pairwise half-sib populations showed that the r MG values for all the six trait-environment combinations were centered around zero, 49% predictions had r MG values above zero; (4) the trend observed in r MG differed with the trend observed in r MG / h , and h is the square root of heritability of the predicted trait, it indicated that both r MG and r MG / h values should be presented in GS study to show the accuracy of genomic selection and the relative accuracy of genomic selection compared with phenotypic selection, respectively. This study provides useful information to maize breeders to design genomic selection workflow in their breeding programs.

  12. Effect of Trait Heritability, Training Population Size and Marker Density on Genomic Prediction Accuracy Estimation in 22 bi-parental Tropical Maize Populations

    Directory of Open Access Journals (Sweden)

    Ao Zhang

    2017-11-01

    Full Text Available Genomic selection is being used increasingly in plant breeding to accelerate genetic gain per unit time. One of the most important applications of genomic selection in maize breeding is to predict and select the best un-phenotyped lines in bi-parental populations based on genomic estimated breeding values. In the present study, 22 bi-parental tropical maize populations genotyped with low density SNPs were used to evaluate the genomic prediction accuracy (rMG of the six trait-environment combinations under various levels of training population size (TPS and marker density (MD, and assess the effect of trait heritability (h2, TPS and MD on rMG estimation. Our results showed that: (1 moderate rMG values were obtained for different trait-environment combinations, when 50% of the total genotypes was used as training population and ~200 SNPs were used for prediction; (2 rMG increased with an increase in h2, TPS and MD, both correlation and variance analyses showed that h2 is the most important factor and MD is the least important factor on rMG estimation for most of the trait-environment combinations; (3 predictions between pairwise half-sib populations showed that the rMG values for all the six trait-environment combinations were centered around zero, 49% predictions had rMG values above zero; (4 the trend observed in rMG differed with the trend observed in rMG/h, and h is the square root of heritability of the predicted trait, it indicated that both rMG and rMG/h values should be presented in GS study to show the accuracy of genomic selection and the relative accuracy of genomic selection compared with phenotypic selection, respectively. This study provides useful information to maize breeders to design genomic selection workflow in their breeding programs.

  13. Open-Source Learning Management Systems: A Predictive Model for Higher Education

    Science.gov (United States)

    van Rooij, S. Williams

    2012-01-01

    The present study investigated the role of pedagogical, technical, and institutional profile factors in an institution of higher education's decision to select an open-source learning management system (LMS). Drawing on the results of previous research that measured patterns of deployment of open-source software (OSS) in US higher education and…

  14. Small angle X-ray scattering and cross-linking for data assisted protein structure prediction in CASP 12 with prospects for improved accuracy

    KAUST Repository

    Ogorzalek, Tadeusz L.

    2018-01-04

    Experimental data offers empowering constraints for structure prediction. These constraints can be used to filter equivalently scored models or more powerfully within optimization functions toward prediction. In CASP12, Small Angle X-ray Scattering (SAXS) and Cross-Linking Mass Spectrometry (CLMS) data, measured on an exemplary set of novel fold targets, were provided to the CASP community of protein structure predictors. As HT, solution-based techniques, SAXS and CLMS can efficiently measure states of the full-length sequence in its native solution conformation and assembly. However, this experimental data did not substantially improve prediction accuracy judged by fits to crystallographic models. One issue, beyond intrinsic limitations of the algorithms, was a disconnect between crystal structures and solution-based measurements. Our analyses show that many targets had substantial percentages of disordered regions (up to 40%) or were multimeric or both. Thus, solution measurements of flexibility and assembly support variations that may confound prediction algorithms trained on crystallographic data and expecting globular fully-folded monomeric proteins. Here, we consider the CLMS and SAXS data collected, the information in these solution measurements, and the challenges in incorporating them into computational prediction. As improvement opportunities were only partly realized in CASP12, we provide guidance on how data from the full-length biological unit and the solution state can better aid prediction of the folded monomer or subunit. We furthermore describe strategic integrations of solution measurements with computational prediction programs with the aim of substantially improving foundational knowledge and the accuracy of computational algorithms for biologically-relevant structure predictions for proteins in solution. This article is protected by copyright. All rights reserved.

  15. Small angle X-ray scattering and cross-linking for data assisted protein structure prediction in CASP 12 with prospects for improved accuracy

    KAUST Repository

    Ogorzalek, Tadeusz L.; Hura, Greg L.; Belsom, Adam; Burnett, Kathryn H.; Kryshtafovych, Andriy; Tainer, John A.; Rappsilber, Juri; Tsutakawa, Susan E.; Fidelis, Krzysztof

    2018-01-01

    Experimental data offers empowering constraints for structure prediction. These constraints can be used to filter equivalently scored models or more powerfully within optimization functions toward prediction. In CASP12, Small Angle X-ray Scattering (SAXS) and Cross-Linking Mass Spectrometry (CLMS) data, measured on an exemplary set of novel fold targets, were provided to the CASP community of protein structure predictors. As HT, solution-based techniques, SAXS and CLMS can efficiently measure states of the full-length sequence in its native solution conformation and assembly. However, this experimental data did not substantially improve prediction accuracy judged by fits to crystallographic models. One issue, beyond intrinsic limitations of the algorithms, was a disconnect between crystal structures and solution-based measurements. Our analyses show that many targets had substantial percentages of disordered regions (up to 40%) or were multimeric or both. Thus, solution measurements of flexibility and assembly support variations that may confound prediction algorithms trained on crystallographic data and expecting globular fully-folded monomeric proteins. Here, we consider the CLMS and SAXS data collected, the information in these solution measurements, and the challenges in incorporating them into computational prediction. As improvement opportunities were only partly realized in CASP12, we provide guidance on how data from the full-length biological unit and the solution state can better aid prediction of the folded monomer or subunit. We furthermore describe strategic integrations of solution measurements with computational prediction programs with the aim of substantially improving foundational knowledge and the accuracy of computational algorithms for biologically-relevant structure predictions for proteins in solution. This article is protected by copyright. All rights reserved.

  16. Improving Prediction Accuracy of a Rate-Based Model of an MEA-Based Carbon Capture Process for Large-Scale Commercial Deployment

    Directory of Open Access Journals (Sweden)

    Xiaobo Luo

    2017-04-01

    Full Text Available Carbon capture and storage (CCS technology will play a critical role in reducing anthropogenic carbon dioxide (CO2 emission from fossil-fired power plants and other energy-intensive processes. However, the increment of energy cost caused by equipping a carbon capture process is the main barrier to its commercial deployment. To reduce the capital and operating costs of carbon capture, great efforts have been made to achieve optimal design and operation through process modeling, simulation, and optimization. Accurate models form an essential foundation for this purpose. This paper presents a study on developing a more accurate rate-based model in Aspen Plus® for the monoethanolamine (MEA-based carbon capture process by multistage model validations. The modeling framework for this process was established first. The steady-state process model was then developed and validated at three stages, which included a thermodynamic model, physical properties calculations, and a process model at the pilot plant scale, covering a wide range of pressures, temperatures, and CO2 loadings. The calculation correlations of liquid density and interfacial area were updated by coding Fortran subroutines in Aspen Plus®. The validation results show that the correlation combination for the thermodynamic model used in this study has higher accuracy than those of three other key publications and the model prediction of the process model has a good agreement with the pilot plant experimental data. A case study was carried out for carbon capture from a 250 MWe combined cycle gas turbine (CCGT power plant. Shorter packing height and lower specific duty were achieved using this accurate model.

  17. Predicting higher education graduation rates from institutional characteristics and resource allocation

    OpenAIRE

    Florence A. Hamrick; John H. Schuh; Mack C. Shelley

    2004-01-01

    This study incorporated institutional characteristics (e.g., Carnegie type, selectivity) and resource allocations (e.g., instructional expenditures, student affairs expenditures) into a statistical model to predict undergraduate graduation rates. Instructional expenditures, library expenditures, and a number of institutional classification variables were significant predictors of graduation rates. Based on these results, recommendations as well as warranted cautions are included about allocat...

  18. Influence of radiation on predictive accuracy in numerical simulations of the thermal environment in industrial buildings with buoyancy-driven natural ventilation

    International Nuclear Information System (INIS)

    Meng, Xiaojing; Wang, Yi; Liu, Tiening; Xing, Xiao; Cao, Yingxue; Zhao, Jiangping

    2016-01-01

    Highlights: • The effects of radiation on predictive accuracy in numerical simulations were studied. • A scaled experimental model with a high-temperature heat source was set up. • Simulation results were discussed considering with and without radiation model. • The buoyancy force and the ventilation rate were investigated. - Abstract: This paper investigates the effects of radiation on predictive accuracy in the numerical simulations of industrial buildings. A scaled experimental model with a high-temperature heat source is set up and the buoyancy-driven natural ventilation performance is presented. Besides predicting ventilation performance in an industrial building, the scaled model in this paper is also used to generate data to validate the numerical simulations. The simulation results show good agreement with the experiment data. The effects of radiation on predictive accuracy in the numerical simulations are studied for both pure convection model and combined convection and radiation model. Detailed results are discussed regarding the temperature and velocity distribution, the buoyancy force and the ventilation rate. The temperature and velocity distributions through the middle plane are presented for the pure convection model and the combined convection and radiation model. It is observed that the overall temperature and velocity magnitude predicted by the simulations for pure convection were significantly greater than those for the combined convection and radiation model. In addition, the Grashof number and the ventilation rate are investigated. The results show that the Grashof number and the ventilation rate are greater for the pure convection model than for the combined convection and radiation model.

  19. Energy expenditure prediction via a footwear-based physical activity monitor: Accuracy and comparison to other devices

    Science.gov (United States)

    Dannecker, Kathryn

    2011-12-01

    Accurately estimating free-living energy expenditure (EE) is important for monitoring or altering energy balance and quantifying levels of physical activity. The use of accelerometers to monitor physical activity and estimate physical activity EE is common in both research and consumer settings. Recent advances in physical activity monitors include the ability to identify specific activities (e.g. stand vs. walk) which has resulted in improved EE estimation accuracy. Recently, a multi-sensor footwear-based physical activity monitor that is capable of achieving 98% activity identification accuracy has been developed. However, no study has compared the EE estimation accuracy for this monitor and compared this accuracy to other similar devices. Purpose . To determine the accuracy of physical activity EE estimation of a footwear-based physical activity monitor that uses an embedded accelerometer and insole pressure sensors and to compare this accuracy against a variety of research and consumer physical activity monitors. Methods. Nineteen adults (10 male, 9 female), mass: 75.14 (17.1) kg, BMI: 25.07(4.6) kg/m2 (mean (SD)), completed a four hour stay in a room calorimeter. Participants wore a footwear-based physical activity monitor, as well as three physical activity monitoring devices used in research: hip-mounted Actical and Actigraph accelerometers and a multi-accelerometer IDEEA device with sensors secured to the limb and chest. In addition, participants wore two consumer devices: Philips DirectLife and Fitbit. Each individual performed a series of randomly assigned and ordered postures/activities including lying, sitting (quietly and using a computer), standing, walking, stepping, cycling, sweeping, as well as a period of self-selected activities. We developed branched (i.e. activity specific) linear regression models to estimate EE from the footwear-based device, and we used the manufacturer's software to estimate EE for all other devices. Results. The shoe

  20. Engaging Students Emotionally: The Role of Emotional Intelligence in Predicting Cognitive and Affective Engagement in Higher Education

    Science.gov (United States)

    Maguire, Rebecca; Egan, Arlene; Hyland, Philip; Maguire, Phil

    2017-01-01

    Student engagement is a key predictor of academic performance, persistence and retention in higher education. While many studies have identified how aspects of the college environment influence engagement, fewer have specifically focused on emotional intelligence (EI). In this study, we sought to explore whether EI could predict cognitive and/or…

  1. Students-as-Customers' Satisfaction, Predictive Retention with Marketing Implications: The Case of Malaysian Higher Education Business Students

    Science.gov (United States)

    Carter, Stephen; Yeo, Amy Chu-May

    2016-01-01

    Purpose: The purpose of this paper is to investigate two areas of interest: first, to determine business student customer satisfiers that could be contributors to students' current and predicted retention in a higher educational institution (HEI) and second, to use these satisfiers to inform HEI marketing planning. Design/Methodology/Approach: The…

  2. Improved prediction of higher heating value of biomass using an artificial neural network model based on proximate analysis.

    Science.gov (United States)

    Uzun, Harun; Yıldız, Zeynep; Goldfarb, Jillian L; Ceylan, Selim

    2017-06-01

    As biomass becomes more integrated into our energy feedstocks, the ability to predict its combustion enthalpies from routine data such as carbon, ash, and moisture content enables rapid decisions about utilization. The present work constructs a novel artificial neural network model with a 3-3-1 tangent sigmoid architecture to predict biomasses' higher heating values from only their proximate analyses, requiring minimal specificity as compared to models based on elemental composition. The model presented has a considerably higher correlation coefficient (0.963) and lower root mean square (0.375), mean absolute (0.328), and mean bias errors (0.010) than other models presented in the literature which, at least when applied to the present data set, tend to under-predict the combustion enthalpy. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. A Comparison of Data Sets Varying in Spatial Accuracy Used to Predict the Occurrence of Wildlife-Vehicle Collisions

    Science.gov (United States)

    Gunson, Kari E.; Clevenger, Anthony P.; Ford, Adam T.; Bissonette, John A.; Hardy, Amanda

    2009-08-01

    Wildlife-vehicle collisions (WVCs) pose a significant safety and conservation concern in areas where high-traffic roads are situated adjacent to wildlife habitat. Improving transportation safety, accurately planning highway mitigation, and identifying key habitat linkage areas may all depend on the quality of WVC data collection. Two common approaches to describe the location of WVCs are spatially accurate data derived from global positioning systems (GPS) or vehicle odometer measurements and less accurate road-marker data derived from reference points (e.g., mile-markers or landmarks) along the roadside. In addition, there are two common variable types used to predict WVC locations: (1) field-derived, site-specific measurements and (2) geographic information system (GIS)-derived information. It is unclear whether these different approaches produce similar results when attempting to identify and explain the location of WVCs. Our first objective was to determine and compare the spatial error found in road-marker data (in our case the closest mile-marker) and landmark-referenced data. Our second objective was to evaluate the performance of models explaining high- and low-probability WVC locations, using congruent, spatially accurate (GIS-derived explanatory variables. Our WVC data sets were comprised of ungulate collisions and were located along five major roads in the central Canadian Rocky Mountains. We found that spatial error (mean ± SD) was higher for WVC data referenced to nearby landmarks (516 ± 808 m) than for data referenced to the closest mile-marker data (401 ± 219 m). The top-performing model using the spatially accurate WVC locations contained all explanatory variable types, whereas GIS-derived variables were only influential in the best road-marker model and the spatially accurate reduced model. Our study showed that spatial error and sample size, using road-marker data for ungulate species, are important to consider for model output interpretation

  4. Influenza detection and prediction algorithms: comparative accuracy trial in Östergötland county, Sweden, 2008-2012.

    Science.gov (United States)

    Spreco, A; Eriksson, O; Dahlström, Ö; Timpka, T

    2017-07-01

    Methods for the detection of influenza epidemics and prediction of their progress have seldom been comparatively evaluated using prospective designs. This study aimed to perform a prospective comparative trial of algorithms for the detection and prediction of increased local influenza activity. Data on clinical influenza diagnoses recorded by physicians and syndromic data from a telenursing service were used. Five detection and three prediction algorithms previously evaluated in public health settings were calibrated and then evaluated over 3 years. When applied on diagnostic data, only detection using the Serfling regression method and prediction using the non-adaptive log-linear regression method showed acceptable performances during winter influenza seasons. For the syndromic data, none of the detection algorithms displayed a satisfactory performance, while non-adaptive log-linear regression was the best performing prediction method. We conclude that evidence was found for that available algorithms for influenza detection and prediction display satisfactory performance when applied on local diagnostic data during winter influenza seasons. When applied on local syndromic data, the evaluated algorithms did not display consistent performance. Further evaluations and research on combination of methods of these types in public health information infrastructures for 'nowcasting' (integrated detection and prediction) of influenza activity are warranted.

  5. Vigorous physical activity predicts higher heart rate variability among younger adults.

    Science.gov (United States)

    May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

    2017-06-14

    Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

  6. Clinical chemistry in higher dimensions: Machine-learning and enhanced prediction from routine clinical chemistry data.

    Science.gov (United States)

    Richardson, Alice; Signor, Ben M; Lidbury, Brett A; Badrick, Tony

    2016-11-01

    Big Data is having an impact on many areas of research, not the least of which is biomedical science. In this review paper, big data and machine learning are defined in terms accessible to the clinical chemistry community. Seven myths associated with machine learning and big data are then presented, with the aim of managing expectation of machine learning amongst clinical chemists. The myths are illustrated with four examples investigating the relationship between biomarkers in liver function tests, enhanced laboratory prediction of hepatitis virus infection, the relationship between bilirubin and white cell count, and the relationship between red cell distribution width and laboratory prediction of anaemia. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  7. Consistency between analytical and finite element predictions for safety of cylindrical pressure vessels at higher temperatures

    International Nuclear Information System (INIS)

    Iancu, Otto Theodor

    2014-01-01

    The prediction of the plastic collapse load of cylindrical pressure vessels is very often made by using expensive Finite Element computations. The calculation of the collapse load requires an elastic-plastic material model and the consideration of non-linear geometry effects. The plastic collapse load causes overall structural instability and cannot be determined directly from a Finite Element analysis. In the present paper the plastic collapse load for a cylindrical pressure vessel is determined by an analytical method based on a linear elastic perfectly plastic material model. When plasticity occurs the material is considered to be incompressible and the tensor of plastic strains to be parallel to the stress deviator tensor. In this case the finite stress-strain relationships of Henkel can be used for calculating the pressure for which plastic flow occurs. The analytical results are completely confirmed by Finite Element predictions. (orig.)

  8. Predicting higher education graduation rates from institutional characteristics and resource allocation

    Directory of Open Access Journals (Sweden)

    Florence A. Hamrick

    2004-05-01

    Full Text Available This study incorporated institutional characteristics (e.g., Carnegie type, selectivity and resource allocations (e.g., instructional expenditures, student affairs expenditures into a statistical model to predict undergraduate graduation rates. Instructional expenditures, library expenditures, and a number of institutional classification variables were significant predictors of graduation rates. Based on these results, recommendations as well as warranted cautions are included about allocating academic financial resources to optimize graduation rates

  9. The predictive accuracy of the black hole sign and the spot sign for hematoma expansion in patients with spontaneous intracerebral hemorrhage.

    Science.gov (United States)

    Yu, Zhiyuan; Zheng, Jun; Ma, Lu; Guo, Rui; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

    2017-09-01

    In patients with spontaneous intracerebral hemorrhage (sICH), hematoma expansion (HE) is associated with poor outcome. Spot sign and black hole sign are neuroimaging predictors for HE. This study was aimed to compare the predictive value of two signs for HE. Within 6 h after onset of sICH, patients were screened for the computed tomography angiography spot sign and the non-contrast computed tomography black hole sign. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of two signs for HE prediction were calculated. The accuracy of two signs in predicting HE was analyzed by receiver-operator analysis. A total of 129 patients were included in this study. Spot sign was identified in 30 (23.3%) patients and black hole sign in 29 (22.5%) patients, respectively. Of 32 patients with HE, spot sign was observed in 19 (59.4%) and black hole sign was found in 14 (43.8%). The occurrence of black hole sign was significantly associated with spot sign (P black hole sign for predicting HE were 43.75, 84.54, 48.28, and 82.00%, respectively. The area under the curve was 0.740 for spot sign and 0.641 for black hole sign. (P = 0.228) Both spot sign and black hole sign appeared to have good predictive value for HE, and spot sign seemed to be a better predictor.

  10. Predictive Power of Primary and Secondary School Success Criterion on Transition to Higher Education Examination Scores

    OpenAIRE

    Atilla ÖZDEMİR; Selahattin GELBAL

    2016-01-01

    It is seen that education has a significant effect that changes an individual’s life in our country in which education is a way of moving up the social ladder. In order to continue to a higher education program after graduating from high school, students have to succeed in transition to higher education examination. Thus, the entrance exam is an important factor to determine the future of the students. In our country, middle school grades and high school grade point average that is added to u...

  11. Pre-transplant reversible pulmonary hypertension predicts higher risk for mortality after cardiac transplantation.

    Science.gov (United States)

    Butler, Javed; Stankewicz, Mark A; Wu, Jack; Chomsky, Don B; Howser, Renee L; Khadim, Ghazanfar; Davis, Stacy F; Pierson, Richard N; Wilson, John R

    2005-02-01

    Pre-transplant fixed pulmonary hypertension is associated with higher post-transplant mortality. In this study, we assessed the significance of pre-transplant reversible pulmonary hypertension in patients undergoing cardiac transplantation. Overall, we studied 182 patients with baseline normal pulmonary pressures or reversible pulmonary hypertension, defined as a decrease in pulmonary vascular resistance (PVR) to 50 mm Hg had a higher risk of death (odds ratio [OR] 5.96, 95% confidence interval [CI] 1.46 to 19.84 as compared with PAS 4.0 WU, but patients with TPG > or =16 had a higher risk of mortality (OR 4.93, 95% CI 1.84 to 13.17). PAS pressure was an independent predictor of mortality (OR 1.04, 95% CI 1.02 to 1.06). Recipient body mass index, history of sternotomy; and donor ischemic time were the other independent predictors of mortality. Pre-transplant pulmonary hypertension, even when reversible to a PVR of < or =2.5 WU, is associated with a higher mortality post-transplant.

  12. Positive Attitude toward Healthy Eating Predicts Higher Diet Quality at All Cost Levels of Supermarkets☆

    Science.gov (United States)

    Aggarwal, Anju; Monsivais, Pablo; Cook, Andrea J.; Drewnowski, Adam

    2014-01-01

    Shopping at low-cost supermarkets has been associated with higher obesity rates. This study examined whether attitudes toward healthy eating are independently associated with diet quality among shoppers at low-cost, medium-cost, and high-cost supermarkets. Data on socioeconomic status (SES), attitudes toward healthy eating, and supermarket choice were collected using a telephone survey of a representative sample of adult residents of King County, WA. Dietary intake data were based on a food frequency questionnaire. Thirteen supermarket chains were stratified into three categories: low, medium, and high cost, based on a market basket of 100 commonly eaten foods. Diet-quality measures were energy density, mean adequacy ratio, and total servings of fruits and vegetables. The analytical sample consisted of 963 adults. Multivariable regressions with robust standard error examined relations between diet quality, supermarket type, attitudes, and SES. Shopping at higher-cost supermarkets was associated with higher-quality diets. These associations persisted after adjusting for SES, but were eliminated after taking attitudinal measures into account. Supermarket shoppers with positive attitudes toward healthy eating had equally higher-quality diets, even if they shopped at low-, medium-, or high-cost supermarkets, independent of SES and other covariates. These findings imply that shopping at low-cost supermarkets does not prevent consumers from having high-quality diets, as long as they attach importance to good nutrition. Promoting nutrition-education strategies among supermarkets, particularly those catering to low-income groups, can help to improve diet quality. PMID:23916974

  13. Predicting a Taxonomy of Organisational Effectiveness in U.K. Higher Educational Institutions.

    Science.gov (United States)

    Lysons, Art; Hatherly, David

    1996-01-01

    The framework of a study of organizational effectiveness in Australian higher education institutions was applied to a similar study in the United Kingdom. The approach was found useful for classifying U.K. institutions as classical universities, former polytechnics and colleges of advanced technology, and greenfield universities. (Author/MSE)

  14. Specific psychological variables predict quality of diet in women of lower, but not higher, educational attainment

    DEFF Research Database (Denmark)

    Lawrence, Wendy; Schlotz, Wolff; Crozier, Sarah

    2011-01-01

    Our previous work found that perceived control over life was a significant predictor of the quality of diet of women of lower educational attainment. In this paper, we explore the influence on quality of diet of a range of psychological and social factors identified during focus group discussions......, and specify the way this differs in women of lower and higher educational attainment. We assessed educational attainment, quality of diet, and psycho-social factors in 378 women attending Sure Start Children's Centres and baby clinics in Southampton, UK. Multiple-group path analysis showed that in women...... of self-efficacy, perceived control or outcome expectancies on the quality of diet of women of higher educational attainment, though having more social support and food involvement were associated with improved quality of diet in these women. Our analysis confirms our hypothesis that control...

  15. Higher Levels of Albuminuria within the Normal Range Predict Incident Hypertension

    OpenAIRE

    Forman, John P.; Fisher, Naomi D.L.; Schopick, Emily L.; Curhan, Gary C.

    2008-01-01

    Higher levels of albumin excretion within the normal range are associated with cardiovascular disease in high-risk individuals. Whether incremental increases in urinary albumin excretion, even within the normal range, are associated with the development of hypertension in low-risk individuals is unknown. This study included 1065 postmenopausal women from the first Nurses’ Health Study and 1114 premenopausal women from the second Nurses’ Health Study who had an albumin/creatinine ratio

  16. Positive attitude toward healthy eating predicts higher diet quality at all cost levels of supermarkets.

    Science.gov (United States)

    Aggarwal, Anju; Monsivais, Pablo; Cook, Andrea J; Drewnowski, Adam

    2014-02-01

    Shopping at low-cost supermarkets has been associated with higher obesity rates. This study examined whether attitudes toward healthy eating are independently associated with diet quality among shoppers at low-cost, medium-cost, and high-cost supermarkets. Data on socioeconomic status (SES), attitudes toward healthy eating, and supermarket choice were collected using a telephone survey of a representative sample of adult residents of King County, WA. Dietary intake data were based on a food frequency questionnaire. Thirteen supermarket chains were stratified into three categories: low, medium, and high cost, based on a market basket of 100 commonly eaten foods. Diet-quality measures were energy density, mean adequacy ratio, and total servings of fruits and vegetables. The analytical sample consisted of 963 adults. Multivariable regressions with robust standard error examined relations between diet quality, supermarket type, attitudes, and SES. Shopping at higher-cost supermarkets was associated with higher-quality diets. These associations persisted after adjusting for SES, but were eliminated after taking attitudinal measures into account. Supermarket shoppers with positive attitudes toward healthy eating had equally higher-quality diets, even if they shopped at low-, medium-, or high-cost supermarkets, independent of SES and other covariates. These findings imply that shopping at low-cost supermarkets does not prevent consumers from having high-quality diets, as long as they attach importance to good nutrition. Promoting nutrition-education strategies among supermarkets, particularly those catering to low-income groups, can help to improve diet quality. Copyright © 2014 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

  17. Exploiting Academic Records for Predicting Student Drop Out: a case study in Brazilian higher education

    OpenAIRE

    Sales, Allan; Balby, Leandro; Cajueiro, Adalberto

    2017-01-01

    Students’ dropout is a major concern of the Brazilian higher education institutions as it may cause waste of resources and decrease graduation rates. The early detection of students with high probability of dropping out, as well as understanding the underlying causes, are crucial for defining more effective actions toward preventing this problem. In this paper, we cast the dropout detection problem as a classification problem. We use a large sample of academic records of students across 76 co...

  18. Enhanced detection of gametocytes by magnetic deposition microscopy predicts higher potential for Plasmodium falciparum transmission

    Directory of Open Access Journals (Sweden)

    Zborowski Maciej

    2008-04-01

    Full Text Available Abstract Background Aggregated haemozoin crystals within malaria-infected erythrocytes confer susceptibility of parasitized cells to a magnetic field. Here the utility of this method for diagnosis of human malaria is evaluated in a malaria-endemic region of Papua New Guinea (PNG. Methods and findings Individuals with Plasmodium falciparum malaria symptoms (n = 55 provided samples for conventional blood smear (CBS and magnetic deposition microscopy (MDM diagnosis. Standard Giemsa staining and light microscopy was performed to evaluate all preparations. Plasmodium falciparum parasitaemia observed on MDM slides was consistently higher than parasitaemia observed by (CBS for ring (CBS = 2.6 vs. MDM = 3.4%; t-test P-value = 0.13, trophozoite (CBS = 0.5 vs. MDM = 1.6%; t-test P-value = 0.01, schizont (CBS = 0.003 vs. MDM = 0.1%; t-test P-value = 0.08 and gametocyte (CBS = 0.001 vs. MDM = 0.4%; t-test P-value = 0.0002 parasitaemias. Gametocyte prevalence determined by CBS compared to MDM increased from 7.3% to 45%, respectively. Conclusion MDM increased detection sensitivity of P. falciparum-infected, haemozoin-containing erythrocytes from infected humans while maintaining detection of ring-stage parasites. Gametocyte prevalence five-fold higher than observed by CBS suggests higher malaria transmission potential in PNG endemic sites compared to previous estimates.

  19. Higher cortisol levels at diurnal trough predict greater attentional bias towards threat in healthy young adults.

    Science.gov (United States)

    Hakamata, Yuko; Izawa, Shuhei; Sato, Eisuke; Komi, Shotaro; Murayama, Norio; Moriguchi, Yoshiya; Hanakawa, Takashi; Inoue, Yusuke; Tagaya, Hirokuni

    2013-11-01

    Attentional bias (AB), selective information processing towards threat, can exacerbate anxiety and depression. Despite growing interest, physiological determinants of AB are yet to be understood. We examined whether stress hormone cortisol and its diurnal variation pattern contribute to AB. Eighty-seven healthy young adults underwent assessments for AB, anxious personality traits, depressive symptoms, and attentional function. Salivary cortisol was collected at three time points daily (at awakening, 30 min after awakening, and bedtime) for 2 consecutive days. We performed: (1) multiple regression analysis to examine the relationships between AB and the other measures and (2) analysis of variance (ANOVA) between groups with different cortisol variation patterns for the other measures. Multiple regression analysis revealed that higher cortisol levels at bedtime (pattention and cortisol measurement at three time points daily. We showed that higher cortisol levels at bedtime and blunted cortisol variation are associated with greater AB. Individuals who have higher cortisol levels at diurnal trough might be at risk of clinical anxiety or depression but could also derive more benefits from the attentional-bias-modification program. © 2013 Elsevier B.V. All rights reserved.

  20. Specific psychological variables predict quality of diet in women of lower, but not higher, educational attainment.

    Science.gov (United States)

    Lawrence, Wendy; Schlotz, Wolff; Crozier, Sarah; Skinner, Timothy C; Haslam, Cheryl; Robinson, Sian; Inskip, Hazel; Cooper, Cyrus; Barker, Mary

    2011-02-01

    Our previous work found that perceived control over life was a significant predictor of the quality of diet of women of lower educational attainment. In this paper, we explore the influence on quality of diet of a range of psychological and social factors identified during focus group discussions, and specify the way this differs in women of lower and higher educational attainment. We assessed educational attainment, quality of diet, and psycho-social factors in 378 women attending Sure Start Children's Centres and baby clinics in Southampton, UK. Multiple-group path analysis showed that in women of lower educational attainment, the effect of general self-efficacy on quality of diet was mediated through perceptions of control and through food involvement, but that there were also direct effects of social support for healthy eating and having positive outcome expectancies. There was no effect of self-efficacy, perceived control or outcome expectancies on the quality of diet of women of higher educational attainment, though having more social support and food involvement were associated with improved quality of diet in these women. Our analysis confirms our hypothesis that control-related factors are more important in determining dietary quality in women of lower educational attainment than in women of higher educational attainment. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. Maximal locality and predictive power in higher-dimensional, compactified field theories

    International Nuclear Information System (INIS)

    Kubo, Jisuke; Nunami, Masanori

    2004-01-01

    To realize maximal locality in a trivial field theory, we maximize the ultraviolet cutoff of the theory by fine tuning the infrared values of the parameters. This optimization procedure is applied to the scalar theory in D + 1 dimensional (D ≥ 4) with one extra dimension compactified on a circle of radius R. The optimized, infrared values of the parameters are then compared with the corresponding ones of the uncompactified theory in D dimensions, which is assumed to be the low-energy effective theory. We find that these values approximately agree with each other as long as R -1 > approx sM is satisfied, where s ≅ 10, 50, 50, 100 for D = 4,5,6,7, and M is a typical scale of the D-dimensional theory. This result supports the previously made claim that the maximization of the ultraviolet cutoff in a nonrenormalizable field theory can give the theory more predictive power. (author)

  2. Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

    Directory of Open Access Journals (Sweden)

    Schrooten Chris

    2009-01-01

    Full Text Available Abstract The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction.

  3. Pre-Operative Prediction of Advanced Prostatic Cancer Using Clinical Decision Support Systems: Accuracy Comparison between Support Vector Machine and Artificial Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Sang Youn; Moon, Sung Kyoung; Hwang, Sung Il; Sung, Chang Kyu; Cho, Jeong Yeon; Kim, Seung Hyup; Lee, Hak Jong [Seoul National University College of Medicine, Seoul (Korea, Republic of); Jung, Dae Chul [National Cancer Center, Ilsan (Korea, Republic of); Lee, Ji Won [Kangwon National University College of Medicine, Chuncheon (Korea, Republic of)

    2011-10-15

    The purpose of the current study was to develop support vector machine (SVM) and artificial neural network (ANN) models for the pre-operative prediction of advanced prostate cancer by using the parameters acquired from transrectal ultrasound (TRUS)-guided prostate biopsies, and to compare the accuracies between the two models. Five hundred thirty-two consecutive patients who underwent prostate biopsies and prostatectomies for prostate cancer were divided into the training and test groups (n = 300 versus n 232). From the data in the training group, two clinical decision support systems (CDSSs-[SVM and ANN]) were constructed with input (age, prostate specific antigen level, digital rectal examination, and five biopsy parameters) and output data (the probability for advanced prostate cancer [> pT3a]). From the data of the test group, the accuracy of output data was evaluated. The areas under the receiver operating characteristic (ROC) curve (AUC) were calculated to summarize the overall performances, and a comparison of the ROC curves was performed (p < 0.05). The AUC of SVM and ANN is 0.805 and 0.719, respectively (p = 0.020), in the pre-operative prediction of advanced prostate cancer. Te performance of SVM is superior to ANN in the pre-operative prediction of advanced prostate cancer.

  4. Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia

    NARCIS (Netherlands)

    Vollebregt, Karlijn Corien; Gisolf, Janneke; Guelen, Ilja; Boer, Kees; van Montfrans, Gert; Wolf, Hans

    2010-01-01

    Objective The aim of this study was to validate the hyperbaric index (HBI) for first trimester prediction of preeclampsia and gestational hypertension. Methods Participants were low-risk and high-risk nulliparous women and high-risk multiparous women, and were recruited between April 2004 and June

  5. Predicting acute uncomplicated urinary tract infection in women: a systematic review of the diagnostic accuracy of symptoms and signs

    LENUS (Irish Health Repository)

    Giesen, Leonie GM

    2010-10-24

    Abstract Background Acute urinary tract infections (UTI) are one of the most common bacterial infections among women presenting to primary care. However, there is a lack of consensus regarding the optimal reference standard threshold for diagnosing UTI. The objective of this systematic review is to determine the diagnostic accuracy of symptoms and signs in women presenting with suspected UTI, across three different reference standards (102 or 103 or 105 CFU\\/ml). We also examine the diagnostic value of individual symptoms and signs combined with dipstick test results in terms of clinical decision making. Methods Searches were performed through PubMed (1966 to April 2010), EMBASE (1973 to April 2010), Cochrane library (1973 to April 2010), Google scholar and reference checking. Studies that assessed the diagnostic accuracy of symptoms and signs of an uncomplicated UTI using a urine culture from a clean-catch or catherised urine specimen as the reference standard, with a reference standard of at least ≥ 102 CFU\\/ml were included. Synthesised data from a high quality systematic review were used regarding dipstick results. Studies were combined using a bivariate random effects model. Results Sixteen studies incorporating 3,711 patients are included. The weighted prior probability of UTI varies across diagnostic threshold, 65.1% at ≥ 102 CFU\\/ml; 55.4% at ≥ 103 CFU\\/ml and 44.8% at ≥ 102 CFU\\/ml ≥ 105 CFU\\/ml. Six symptoms are identified as useful diagnostic symptoms when a threshold of ≥ 102 CFU\\/ml is the reference standard. Presence of dysuria (+LR 1.30 95% CI 1.20-1.41), frequency (+LR 1.10 95% CI 1.04-1.16), hematuria (+LR 1.72 95%CI 1.30-2.27), nocturia (+LR 1.30 95% CI 1.08-1.56) and urgency (+LR 1.22 95% CI 1.11-1.34) all increase the probability of UTI. The presence of vaginal discharge (+LR 0.65 95% CI 0.51-0.83) decreases the probability of UTI. Presence of hematuria has the highest diagnostic utility, raising the post-test probability of

  6. Accuracy of Demirjian′s 8 teeth method for age prediction in South Indian children: A comparative study

    Directory of Open Access Journals (Sweden)

    Rezwana Begum Mohammed

    2015-01-01

    Full Text Available Introduction: Demirjian′s method of tooth development is most commonly used to assess age in individuals with emerging teeth. However, its application on numerous populations has resulted in wide variations in age estimates and consequent suggestions for the method′s adaptation to the local sample. Original Demirjian′s method utilized seven mandibular teeth, to which recently third molar is added so that the method can be applied on a wider age group. Furthermore, the revised method developed regression formulas for assessing age. In Indians, as these formulas resulted in underestimation, India-specific regression formulas were developed recently. The purpose of this cross-sectional study was to evaluate the accuracy and applicability of original regression formulas (Chaillet and Demirjian 2004 and India-specific regression formulas (Acharya 2010 using Demirjian′s 8 teeth method in South Indian children of age groups 9-20 years. Methods: The present study consisted of 660 randomly selected subjects (330 males and 330 females were in the aged ranging from 9 to 20 years divided into 11 groups according to their age. Demirjian′s 8 teeth method was used for staging of teeth. Results: Demirjian′s method underestimated the dental age (DA by 1.66 years for boys and 1.55 years for girls and 1.61 years in total. Acharya′s method over estimated DA by 0.21 years for boys and 0.85 years for girls and 0.53 years in total. The absolute accuracy was better for Acharya′s method compared with Demirjian method. Conclusion: This study concluded that both the Demirjian and Indian regression formulas were reliable in assessing age making Demirjian′s 8 teeth method applicable for South Indians.

  7. Accuracy of enhanced and unenhanced MRI in diagnosing scaphoid proximal pole avascular necrosis and predicting surgical outcome

    Energy Technology Data Exchange (ETDEWEB)

    Fox, M.G. [University of Virginia, Department of Radiology and Medical Imaging, Charlottesville, VA (United States); Wang, D.T. [University of Virginia, Department of Radiology and Medical Imaging, Charlottesville, VA (United States); Medical College of Wisconsin, Milwaukee, WI (United States); Chhabra, A.B. [University of Virginia Health System, Department of Orthopedics, Charlottesville, VA (United States)

    2015-11-15

    Determine the sensitivity, specificity and accuracy of unenhanced and enhanced MRI in diagnosing scaphoid proximal pole (PP) avascular necrosis (AVN) and correlate whether MRI can help guide the selection of a vascularized or nonvascularized bone graft. The study was approved by the IRB. Two MSK radiologists independently performed a retrospective review of unenhanced and enhanced MRIs from 18 patients (16 males, 2 females; median age, 17.5 years) with scaphoid nonunions and surgery performed within 65 days of the MRI. AVN was diagnosed on the unenhanced MRI when a diffusely decreased T1-W signal was present in the PP and on the enhanced MRI when PP enhancement was less than distal pole enhancement. Surgical absence of PP bleeding was diagnostic of PP AVN. Postoperative osseous union (OU) was assessed with computed tomography and/or radiographs. Sensitivity, specificity and accuracy for PP AVN were 71, 82 and 78 % for unenhanced and 43, 82 and 67 % for enhanced MRI. Patients with PP AVN on unenhanced MRI had 86 % (6/7) OU; 100 % (5/5) OU with vascularized bone grafts and 50 % (1/2) OU with nonvascularized grafts. Patients with PP AVN on enhanced MRI had 80 % (4/5) OU; 100 % (3/3) OU with vascularized bone grafts and 50 % (1/2) OU with nonvascularized grafts. Patients with viable PP on unenhanced and enhanced MRI had 91 % (10/11) and 92 % (12/13) OU, respectively, all but one with nonvascularized graft. When PP AVN is evident on MRI, OU is best achieved with vascularized grafts. If PP AVN is absent, OU is successful with nonvascularized grafts. (orig.)

  8. Accuracy of enhanced and unenhanced MRI in diagnosing scaphoid proximal pole avascular necrosis and predicting surgical outcome

    International Nuclear Information System (INIS)

    Fox, M.G.; Wang, D.T.; Chhabra, A.B.

    2015-01-01

    Determine the sensitivity, specificity and accuracy of unenhanced and enhanced MRI in diagnosing scaphoid proximal pole (PP) avascular necrosis (AVN) and correlate whether MRI can help guide the selection of a vascularized or nonvascularized bone graft. The study was approved by the IRB. Two MSK radiologists independently performed a retrospective review of unenhanced and enhanced MRIs from 18 patients (16 males, 2 females; median age, 17.5 years) with scaphoid nonunions and surgery performed within 65 days of the MRI. AVN was diagnosed on the unenhanced MRI when a diffusely decreased T1-W signal was present in the PP and on the enhanced MRI when PP enhancement was less than distal pole enhancement. Surgical absence of PP bleeding was diagnostic of PP AVN. Postoperative osseous union (OU) was assessed with computed tomography and/or radiographs. Sensitivity, specificity and accuracy for PP AVN were 71, 82 and 78 % for unenhanced and 43, 82 and 67 % for enhanced MRI. Patients with PP AVN on unenhanced MRI had 86 % (6/7) OU; 100 % (5/5) OU with vascularized bone grafts and 50 % (1/2) OU with nonvascularized grafts. Patients with PP AVN on enhanced MRI had 80 % (4/5) OU; 100 % (3/3) OU with vascularized bone grafts and 50 % (1/2) OU with nonvascularized grafts. Patients with viable PP on unenhanced and enhanced MRI had 91 % (10/11) and 92 % (12/13) OU, respectively, all but one with nonvascularized graft. When PP AVN is evident on MRI, OU is best achieved with vascularized grafts. If PP AVN is absent, OU is successful with nonvascularized grafts. (orig.)

  9. Accuracy of enhanced and unenhanced MRI in diagnosing scaphoid proximal pole avascular necrosis and predicting surgical outcome.

    Science.gov (United States)

    Fox, M G; Wang, D T; Chhabra, A B

    2015-11-01

    Determine the sensitivity, specificity and accuracy of unenhanced and enhanced MRI in diagnosing scaphoid proximal pole (PP) avascular necrosis (AVN) and correlate whether MRI can help guide the selection of a vascularized or nonvascularized bone graft. The study was approved by the IRB. Two MSK radiologists independently performed a retrospective review of unenhanced and enhanced MRIs from 18 patients (16 males, 2 females; median age, 17.5 years) with scaphoid nonunions and surgery performed within 65 days of the MRI. AVN was diagnosed on the unenhanced MRI when a diffusely decreased T1-W signal was present in the PP and on the enhanced MRI when PP enhancement was less than distal pole enhancement. Surgical absence of PP bleeding was diagnostic of PP AVN. Postoperative osseous union (OU) was assessed with computed tomography and/or radiographs. Sensitivity, specificity and accuracy for PP AVN were 71, 82 and 78% for unenhanced and 43, 82 and 67% for enhanced MRI. Patients with PP AVN on unenhanced MRI had 86% (6/7) OU; 100% (5/5) OU with vascularized bone grafts and 50% (1/2) OU with nonvascularized grafts. Patients with PP AVN on enhanced MRI had 80% (4/5) OU; 100% (3/3) OU with vascularized bone grafts and 50% (1/2) OU with nonvascularized grafts. Patients with viable PP on unenhanced and enhanced MRI had 91% (10/11) and 92% (12/13) OU, respectively, all but one with nonvascularized graft. When PP AVN is evident on MRI, OU is best achieved with vascularized grafts. If PP AVN is absent, OU is successful with nonvascularized grafts.

  10. Assessing the accuracy of ANFIS, EEMD-GRNN, PCR, and MLR models in predicting PM2.5

    Science.gov (United States)

    Ausati, Shadi; Amanollahi, Jamil

    2016-10-01

    Since Sanandaj is considered one of polluted cities of Iran, prediction of any type of pollution especially prediction of suspended particles of PM2.5, which are the cause of many diseases, could contribute to health of society by timely announcements and prior to increase of PM2.5. In order to predict PM2.5 concentration in the Sanandaj air the hybrid models consisting of an ensemble empirical mode decomposition and general regression neural network (EEMD-GRNN), Adaptive Neuro-Fuzzy Inference System (ANFIS), principal component regression (PCR), and linear model such as multiple liner regression (MLR) model were used. In these models the data of suspended particles of PM2.5 were the dependent variable and the data related to air quality including PM2.5, PM10, SO2, NO2, CO, O3 and meteorological data including average minimum temperature (Min T), average maximum temperature (Max T), average atmospheric pressure (AP), daily total precipitation (TP), daily relative humidity level of the air (RH) and daily wind speed (WS) for the year 2014 in Sanandaj were the independent variables. Among the used models, EEMD-GRNN model with values of R2 = 0.90, root mean square error (RMSE) = 4.9218 and mean absolute error (MAE) = 3.4644 in the training phase and with values of R2 = 0.79, RMSE = 5.0324 and MAE = 3.2565 in the testing phase, exhibited the best function in predicting this phenomenon. It can be concluded that hybrid models have accurate results to predict PM2.5 concentration compared with linear model.

  11. Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

    Science.gov (United States)

    Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

    2015-12-01

    Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

  12. The accuracy of the SONOBREAST statistical model in comparison to BI-RADS for the prediction of malignancy in solid breast nodules detected at ultrasonography.

    Science.gov (United States)

    Paulinelli, Regis R; Oliveira, Luis-Fernando P; Freitas-Junior, Ruffo; Soares, Leonardo R

    2016-01-01

    The objective of the present study was to compare the accuracy of SONOBREAST for the prediction of malignancy in solid breast nodules detected at ultrasonography with that of the BI-RADS system and to assess the agreement between these two methods. This prospective study included 274 women and evaluated 500 breast nodules detected at ultrasonography. The probability of malignancy was calculated based on the SONOBREAST model, available at www.sonobreast.com.br, and on the BI-RADS system, with results being compared with the anatomopathology report. The lesions were considered suspect in 171 cases (34.20%), according to both SONOBREAST and BI-RADS. Agreement between the methods was perfect, as shown by a Kappa coefficient of 1 (pBI-RADS proved identical insofar as sensitivity (95.40%), specificity (78.69%), positive predictive value (48.54%), negative predictive value (98.78%) and accuracy (81.60%) are concerned. With respect to the categorical variables (BI-RADS categories 3, 4 and 5), the area under the receiver operating characteristic (ROC) curve was 94.41 for SONOBREAST (range 92.20-96.62) and 89.99 for BI-RADS (range 86.60-93.37). The accuracy of the SONOBREAST model is identical to that found with BI-RADS when the same parameters are used with respect to the cut-off point at which malignancy is suspected. Regarding the continuous probability of malignancy with BI-RADS categories 3, 4 and 5, SONOBREAST permits a more precise and individualized evaluation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  13. Relative accuracy of spatial predictive models for lynx Lynx canadensis derived using logistic regression-AIC, multiple criteria evaluation and Bayesian approaches

    Directory of Open Access Journals (Sweden)

    Shelley M. ALEXANDER

    2009-02-01

    Full Text Available We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems (GIS-based approaches: logistic regression and Akaike’s Information Criterion (AIC, Multiple Criteria Evaluation (MCE, and Bayesian Analysis (specifically Dempster-Shafer theory. We used lynx Lynx canadensis as our focal species, and developed our environment relationship model using track data collected in Banff National Park, Alberta, Canada, during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified (overall accuracy, the failure to predict a species where it occurred (omission error and the prediction of presence where there was absence (commission error. Our overall accuracy showed the logistic regression approach was the most accurate (74.51%. The multiple criteria evaluation was intermediate (39.22%, while the Dempster-Shafer (D-S theory model was the poorest (29.90%. However, omission and commission error tell us a different story: logistic regression had the lowest commission error, while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least, the logistic regression model is optimal. However, where sample size is small or the species is very rare, it may also be useful to explore and/or use a more ecologically cautious modelling approach (e.g. Dempster-Shafer that would over-predict, protect more sites, and thereby minimize the risk of missing critical habitat in conservation plans[Current Zoology 55(1: 28 – 40, 2009].

  14. Prediction of Tubal Ectopic Pregnancy Using Offline Analysis of 3-Dimensional Transvaginal Ultrasonographic Data Sets: An Interobserver and Diagnostic Accuracy Study.

    Science.gov (United States)

    Infante, Fernando; Espada Vaquero, Mercedes; Bignardi, Tommaso; Lu, Chuan; Testa, Antonia C; Fauchon, David; Epstein, Elisabeth; Leone, Francesco P G; Van den Bosch, Thierry; Martins, Wellington P; Condous, George

    2017-12-08

    To assess interobserver reproducibility in detecting tubal ectopic pregnancies by reading data sets from 3-dimensional (3D) transvaginal ultrasonography (TVUS) and comparing it with real-time 2-dimensional (2D) TVUS. Images were initially classified as showing pregnancies of unknown location or tubal ectopic pregnancies on real time 2D TVUS by an experienced sonologist, who acquired 5 3D volumes. Data sets were analyzed offline by 5 observers who had to classify each case as ectopic pregnancy or pregnancy of unknown location. The interobserver reproducibility was evaluated by the Fleiss κ statistic. The performance of each observer in predicting ectopic pregnancies was compared to that of the experienced sonologist. Women were followed until they were reclassified as follows: (1) failed pregnancy of unknown location; (2) intrauterine pregnancy; (3) ectopic pregnancy; or (4) persistent pregnancy of unknown location. Sixty-one women were included. The agreement between reading offline 3D data sets and the first real-time 2D TVUS was very good (80%-82%; κ = 0.89). The overall interobserver agreement among observers reading offline 3D data sets was moderate (κ = 0.52). The diagnostic performance of experienced observers reading offline 3D data sets had accuracy of 78.3% to 85.0%, sensitivity of 66.7% to 81.3%, specificity of 79.5% to 88.4%, positive predictive value of 57.1% to 72.2%, and negative predictive value of 87.5% to 91.3%, compared to the experienced sonologist's real-time 2D TVUS: accuracy of 94.5%, sensitivity of 94.4%, specificity of 94.5%, positive predictive value of 85.0%, and negative predictive value of 98.1%. The diagnostic accuracy of 3D TVUS by reading offline data sets for predicting ectopic pregnancies is dependent on experience. Reading only static 3D data sets without clinical information does not match the diagnostic performance of real time 2D TVUS combined with clinical information obtained during the scan. © 2017 by the American

  15. Criteria of GenCall score to edit marker data and methods to handle missing markers have an influence on accuracy of genomic predictions

    DEFF Research Database (Denmark)

    Edriss, Vahid; Guldbrandtsen, Bernt; Lund, Mogens Sandø

    2013-01-01

    The aim of this study was to investigate the effect of different strategies for handling low-quality or missing data on prediction accuracy for direct genomic values of protein yield, mastitis and fertility using a Bayesian variable model and a GBLUP model in the Danish Jersey population. The data...... contained 1071 Jersey bulls that were genotyped with the Illumina Bovine 50K chip. After preliminary editing, 39227 SNP remained in the dataset. Four methods to handle missing genotypes were: 1) BEAGLE: missing markers were imputed using Beagle 3.3 software, 2) COMMON: missing genotypes at a locus were...

  16. Hijab and Depression: Does the Islamic Practice of Veiling Predict Higher Levels of Depressive Symptoms?

    Science.gov (United States)

    Hodge, David R; Husain, Altaf; Zidan, Tarek

    2017-07-01

    Hijab or veiling is commonly practiced by Muslim women but remains controversial in the broader secular society. Some Western feminists argue that veiling is an oppressive behavior that negatively affects women by, for example, engendering depression. This article tests this hypothesis with a national sample of American Muslim women (N = 194). The results of the regression analysis did not support the hypothesis. Indeed, women who veiled more frequently reported lower, rather than higher, levels of depressive symptoms. In other words, wearing the hijab appears to be a protective factor in the area of depression. Given the prevalence of depression among women, the results have important implications for practice with Muslim women at both the micro and the macro levels. © 2017 National Association of Social Workers.

  17. Higher levels of albuminuria within the normal range predict incident hypertension.

    Science.gov (United States)

    Forman, John P; Fisher, Naomi D L; Schopick, Emily L; Curhan, Gary C

    2008-10-01

    Higher levels of albumin excretion within the normal range are associated with cardiovascular disease in high-risk individuals. Whether incremental increases in urinary albumin excretion, even within the normal range, are associated with the development of hypertension in low-risk individuals is unknown. This study included 1065 postmenopausal women from the first Nurses' Health Study and 1114 premenopausal women from the second Nurses' Health Study who had an albumin/creatinine ratio who did not have diabetes or hypertension. Among the older women, 271 incident cases of hypertension occurred during 4 yr of follow-up, and among the younger women, 296 incident cases of hypertension occurred during 8 yr of follow-up. Cox proportional hazards regression was used to examine prospectively the association between the albumin/creatinine ratio and incident hypertension after adjustment for age, body mass index, estimated GFR, baseline BP, physical activity, smoking, and family history of hypertension. Participants who had an albumin/creatinine ratio in the highest quartile (4.34 to 24.17 mg/g for older women and 3.68 to 23.84 mg/g for younger women) were more likely to develop hypertension than those who had an albumin/creatinine ratio in the lowest quartile (hazard ratio 1.76 [95% confidence interval 1.21 to 2.56] and hazard ratio 1.35 [95% confidence interval 0.97 to 1.91] for older and younger women, respectively). Higher albumin/creatinine ratios, even within the normal range, are independently associated with increased risk for development of hypertension among women without diabetes. The definition of normal albumin excretion should be reevaluated.

  18. Is the Factor-of-2 Rule Broadly Applicable for Evaluating the Prediction Accuracy of Metal-Toxicity Models?

    Science.gov (United States)

    Meyer, Joseph S; Traudt, Elizabeth M; Ranville, James F

    2018-01-01

    In aquatic toxicology, a toxicity-prediction model is generally deemed acceptable if its predicted median lethal concentrations (LC50 values) or median effect concentrations (EC50 values) are within a factor of 2 of their paired, observed LC50 or EC50 values. However, that rule of thumb is based on results from only two studies: multiple LC50 values for the fathead minnow (Pimephales promelas) exposed to Cu in one type of exposure water, and multiple EC50 values for Daphnia magna exposed to Zn in another type of exposure water. We tested whether the factor-of-2 rule of thumb also is supported in a different dataset in which D. magna were exposed separately to Cd, Cu, Ni, or Zn. Overall, the factor-of-2 rule of thumb appeared to be a good guide to evaluating the acceptability of a toxicity model's underprediction or overprediction of observed LC50 or EC50 values in these acute toxicity tests.

  19. Application of bias factor method using random sampling technique for prediction accuracy improvement of critical eigenvalue of BWR

    International Nuclear Information System (INIS)

    Ito, Motohiro; Endo, Tomohiro; Yamamoto, Akio; Kuroda, Yusuke; Yoshii, Takashi

    2017-01-01

    The bias factor method based on the random sampling technique is applied to the benchmark problem of Peach Bottom Unit 2. Validity and availability of the present method, i.e. correction of calculation results and reduction of uncertainty, are confirmed in addition to features and performance of the present method. In the present study, core characteristics in cycle 3 are corrected with the proposed method using predicted and 'measured' critical eigenvalues in cycles 1 and 2. As the source of uncertainty, variance-covariance of cross sections is considered. The calculation results indicate that bias between predicted and measured results, and uncertainty owing to cross section can be reduced. Extension to other uncertainties such as thermal hydraulics properties will be a future task. (author)

  20. Spatially resolved flux measurements of NOx from London suggest significantly higher emissions than predicted by inventories.

    Science.gov (United States)

    Vaughan, Adam R; Lee, James D; Misztal, Pawel K; Metzger, Stefan; Shaw, Marvin D; Lewis, Alastair C; Purvis, Ruth M; Carslaw, David C; Goldstein, Allen H; Hewitt, C Nicholas; Davison, Brian; Beevers, Sean D; Karl, Thomas G

    2016-07-18

    To date, direct validation of city-wide emissions inventories for air pollutants has been difficult or impossible. However, recent technological innovations now allow direct measurement of pollutant fluxes from cities, for comparison with emissions inventories, which are themselves commonly used for prediction of current and future air quality and to help guide abatement strategies. Fluxes of NOx were measured using the eddy-covariance technique from an aircraft flying at low altitude over London. The highest fluxes were observed over central London, with lower fluxes measured in suburban areas. A footprint model was used to estimate the spatial area from which the measured emissions occurred. This allowed comparison of the flux measurements to the UK's National Atmospheric Emissions Inventory (NAEI) for NOx, with scaling factors used to account for the actual time of day, day of week and month of year of the measurement. The comparison suggests significant underestimation of NOx emissions in London by the NAEI, mainly due to its under-representation of real world road traffic emissions. A comparison was also carried out with an enhanced version of the inventory using real world driving emission factors and road measurement data taken from the London Atmospheric Emissions Inventory (LAEI). The measurement to inventory agreement was substantially improved using the enhanced version, showing the importance of fully accounting for road traffic, which is the dominant NOx emission source in London. In central London there was still an underestimation by the inventory of 30-40% compared with flux measurements, suggesting significant improvements are still required in the NOx emissions inventory.

  1. Bottom-up coarse-grained models with predictive accuracy and transferability for both structural and thermodynamic properties of heptane-toluene mixtures.

    Science.gov (United States)

    Dunn, Nicholas J H; Noid, W G

    2016-05-28

    This work investigates the promise of a "bottom-up" extended ensemble framework for developing coarse-grained (CG) models that provide predictive accuracy and transferability for describing both structural and thermodynamic properties. We employ a force-matching variational principle to determine system-independent, i.e., transferable, interaction potentials that optimally model the interactions in five distinct heptane-toluene mixtures. Similarly, we employ a self-consistent pressure-matching approach to determine a system-specific pressure correction for each mixture. The resulting CG potentials accurately reproduce the site-site rdfs, the volume fluctuations, and the pressure equations of state that are determined by all-atom (AA) models for the five mixtures. Furthermore, we demonstrate that these CG potentials provide similar accuracy for additional heptane-toluene mixtures that were not included their parameterization. Surprisingly, the extended ensemble approach improves not only the transferability but also the accuracy of the calculated potentials. Additionally, we observe that the required pressure corrections strongly correlate with the intermolecular cohesion of the system-specific CG potentials. Moreover, this cohesion correlates with the relative "structure" within the corresponding mapped AA ensemble. Finally, the appendix demonstrates that the self-consistent pressure-matching approach corresponds to minimizing an appropriate relative entropy.

  2. Bottom-up coarse-grained models with predictive accuracy and transferability for both structural and thermodynamic properties of heptane-toluene mixtures

    Energy Technology Data Exchange (ETDEWEB)

    Dunn, Nicholas J. H.; Noid, W. G., E-mail: wnoid@chem.psu.edu [Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802 (United States)

    2016-05-28

    This work investigates the promise of a “bottom-up” extended ensemble framework for developing coarse-grained (CG) models that provide predictive accuracy and transferability for describing both structural and thermodynamic properties. We employ a force-matching variational principle to determine system-independent, i.e., transferable, interaction potentials that optimally model the interactions in five distinct heptane-toluene mixtures. Similarly, we employ a self-consistent pressure-matching approach to determine a system-specific pressure correction for each mixture. The resulting CG potentials accurately reproduce the site-site rdfs, the volume fluctuations, and the pressure equations of state that are determined by all-atom (AA) models for the five mixtures. Furthermore, we demonstrate that these CG potentials provide similar accuracy for additional heptane-toluene mixtures that were not included their parameterization. Surprisingly, the extended ensemble approach improves not only the transferability but also the accuracy of the calculated potentials. Additionally, we observe that the required pressure corrections strongly correlate with the intermolecular cohesion of the system-specific CG potentials. Moreover, this cohesion correlates with the relative “structure” within the corresponding mapped AA ensemble. Finally, the appendix demonstrates that the self-consistent pressure-matching approach corresponds to minimizing an appropriate relative entropy.

  3. How physical modelling can improve Life Cycle Inventory accuracy and allow predictive LCA: an application to the steel industry

    International Nuclear Information System (INIS)

    Mirgaux, O.; Ablitzer, D.; Iosif, A.M.

    2009-01-01

    Assessing traditional iron and steelmaking processes from an environmental point of view and developing breakthrough eco-efficient processes for the future are major challenges for the steel industry today. In the framework of the challenging European project ULCOS, which stands for Ultra Low CO 2 Steelmaking, Life Cycle Assessment (LCA) was chosen to assess breakthrough processes that could be part of the future iron and steel making landscape and to compare them to the reference classical integrated steel-mill. To carry out such a study we propose a new methodological concept which combines LCA thinking with physicochemical process modelling. Physicochemical models were developed for each processes of the classical integrated steelmaking route in order to generate the data required to draw the Life Cycle Inventory of the route. Such a method bypasses the traditional data collection and brings accuracy to the inventory by introducing rigorous mass and energy balances into the methodology. In addition it was shown that such an approach allows testing and assessing different operational practices of the processes in order to optimise the use of energy and the CO 2 emissions, which showed that it can be used as a powerful tool for eco-conception of processes. (authors)

  4. An NMR-based scoring function improves the accuracy of binding pose predictions by docking by two orders of magnitude

    Energy Technology Data Exchange (ETDEWEB)

    Orts, Julien [EMBL, Structure and Computational Biology Unit (Germany); Bartoschek, Stefan [Industriepark Hoechst, Sanofi-Aventis Deutschland GmbH, R and D LGCR/Parallel Synthesis and Natural Products (Germany); Griesinger, Christian [Max Planck Institute for Biophysical Chemistry (Germany); Monecke, Peter [Industriepark Hoechst, Sanofi-Aventis Deutschland GmbH, R and D LGCR/Structure, Design and Informatics (Germany); Carlomagno, Teresa, E-mail: teresa.carlomagno@embl.de [EMBL, Structure and Computational Biology Unit (Germany)

    2012-01-15

    Low-affinity ligands can be efficiently optimized into high-affinity drug leads by structure based drug design when atomic-resolution structural information on the protein/ligand complexes is available. In this work we show that the use of a few, easily obtainable, experimental restraints improves the accuracy of the docking experiments by two orders of magnitude. The experimental data are measured in nuclear magnetic resonance spectra and consist of protein-mediated NOEs between two competitively binding ligands. The methodology can be widely applied as the data are readily obtained for low-affinity ligands in the presence of non-labelled receptor at low concentration. The experimental inter-ligand NOEs are efficiently used to filter and rank complex model structures that have been pre-selected by docking protocols. This approach dramatically reduces the degeneracy and inaccuracy of the chosen model in docking experiments, is robust with respect to inaccuracy of the structural model used to represent the free receptor and is suitable for high-throughput docking campaigns.

  5. Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

    Science.gov (United States)

    Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

    2017-01-01

    Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

  6. Diagnostic accuracy of computed tomography and magnetic resonance imaging obtained after neoadjuvant chemoradiotherapy in predicting the local tumor stage and circumferential resection margin status of rectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Park, Jin Hoon; Kim, Young Hoon; Lee, Yoon Jin; Lee, Kyoung Ho; Kang, Sung Bum; Kim, Duck Woo; Kim, Jae Hyun; Kim, Jae Sung; Lee, Hye Seung [Dept. of Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam (Korea, Republic of); Lee, Sang Min [Dept. of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of)

    2014-02-15

    To measure the diagnostic accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) obtained after neoadjuvant chemoradiotherapy (CRT) in patients with rectal cancer for a prediction of the local tumor stage and circumferential resection margin (CRM). Two independent radiologists reviewed CT and MRI obtained after neoadjuvant CRT. The accuracy of the local tumor staging and the diagnostic performance for the prediction of CRM involvement were calculated. The agreement between the measurements of the distance to potential CRM on both imaging modalities and the histopathology findings was assessed using Bland-Altman plots. 57 patients (mean age, 59.2 years; 24 females) were included. The accuracy of T and N staging were 43.9% (95% confidence interval, 30.8-57.7%) and 77.2% (64.2-87.3%) on CT and 63.2% (49.4-75.6%) and 77.2% (64.2-87.3%) on MRI for Observer 1. The accuracy of T and N staging were 54.4% (40.7-67.7%) and 77.2% (64.2-87.3%) on CT and 68.4% (54.7-80.1%) and 80.7% (68.1-90.0%) on MRI for Observer 2. Sensitivity and specificity on CRM involvement were 83.3% (43.7-97.0%) and 88.2% (76.6-94.5%) on CT and 100% (61.0-100%) and 90.2% (79.0-95.7%) on MRI for Observer 1. Sensitivity and specificity on CRM involvement were 66.7% (30.0-90.3%) and 88.2% (76.7-94.5%) on CT and 100% (61.0-100%) and 90.2% (79.0-95.7%) on MRI for Observer 2. Bland-Altman plots showed wide discrepancies between measurements of the distance to CRM on each CT and MRI and those on histopathology findings. CT and MRI showed limited performance in predicting the local tumor staging and CRM involvement in patients with neoadjuvant CRT although MRI tended to show a better performance than CT.

  7. Diagnostic accuracy of computed tomography and magnetic resonance imaging obtained after neoadjuvant chemoradiotherapy in predicting the local tumor stage and circumferential resection margin status of rectal cancer

    International Nuclear Information System (INIS)

    Park, Jin Hoon; Kim, Young Hoon; Lee, Yoon Jin; Lee, Kyoung Ho; Kang, Sung Bum; Kim, Duck Woo; Kim, Jae Hyun; Kim, Jae Sung; Lee, Hye Seung; Lee, Sang Min

    2014-01-01

    To measure the diagnostic accuracy of computed tomography (CT) and magnetic resonance imaging (MRI) obtained after neoadjuvant chemoradiotherapy (CRT) in patients with rectal cancer for a prediction of the local tumor stage and circumferential resection margin (CRM). Two independent radiologists reviewed CT and MRI obtained after neoadjuvant CRT. The accuracy of the local tumor staging and the diagnostic performance for the prediction of CRM involvement were calculated. The agreement between the measurements of the distance to potential CRM on both imaging modalities and the histopathology findings was assessed using Bland-Altman plots. 57 patients (mean age, 59.2 years; 24 females) were included. The accuracy of T and N staging were 43.9% (95% confidence interval, 30.8-57.7%) and 77.2% (64.2-87.3%) on CT and 63.2% (49.4-75.6%) and 77.2% (64.2-87.3%) on MRI for Observer 1. The accuracy of T and N staging were 54.4% (40.7-67.7%) and 77.2% (64.2-87.3%) on CT and 68.4% (54.7-80.1%) and 80.7% (68.1-90.0%) on MRI for Observer 2. Sensitivity and specificity on CRM involvement were 83.3% (43.7-97.0%) and 88.2% (76.6-94.5%) on CT and 100% (61.0-100%) and 90.2% (79.0-95.7%) on MRI for Observer 1. Sensitivity and specificity on CRM involvement were 66.7% (30.0-90.3%) and 88.2% (76.7-94.5%) on CT and 100% (61.0-100%) and 90.2% (79.0-95.7%) on MRI for Observer 2. Bland-Altman plots showed wide discrepancies between measurements of the distance to CRM on each CT and MRI and those on histopathology findings. CT and MRI showed limited performance in predicting the local tumor staging and CRM involvement in patients with neoadjuvant CRT although MRI tended to show a better performance than CT

  8. Predicting Streptococcal Pharyngitis in Adults in Primary Care: A Systematic Review of the Diagnostic Accuracy of Symptoms and Signs and Validation of the Centor Score

    LENUS (Irish Health Repository)

    Aalbers, Jolien

    2011-06-01

    Abstract Background Stratifying patients with a sore throat into the probability of having an underlying bacterial or viral cause may be helpful in targeting antibiotic treatment. We sought to assess the diagnostic accuracy of signs and symptoms and validate a clinical prediction rule (CPR), the Centor score, for predicting group A β-haemolytic streptococcal (GABHS) pharyngitis in adults (> 14 years of age) presenting with sore throat symptoms. Methods A systematic literature search was performed up to July 2010. Studies that assessed the diagnostic accuracy of signs and symptoms and\\/or validated the Centor score were included. For the analysis of the diagnostic accuracy of signs and symptoms and the Centor score, studies were combined using a bivariate random effects model, while for the calibration analysis of the Centor score, a random effects model was used. Results A total of 21 studies incorporating 4,839 patients were included in the meta-analysis on diagnostic accuracy of signs and symptoms. The results were heterogeneous and suggest that individual signs and symptoms generate only small shifts in post-test probability (range positive likelihood ratio (+LR) 1.45-2.33, -LR 0.54-0.72). As a decision rule for considering antibiotic prescribing (score ≥ 3), the Centor score has reasonable specificity (0.82, 95% CI 0.72 to 0.88) and a post-test probability of 12% to 40% based on a prior prevalence of 5% to 20%. Pooled calibration shows no significant difference between the numbers of patients predicted and observed to have GABHS pharyngitis across strata of Centor score (0-1 risk ratio (RR) 0.72, 95% CI 0.49 to 1.06; 2-3 RR 0.93, 95% CI 0.73 to 1.17; 4 RR 1.14, 95% CI 0.95 to 1.37). Conclusions Individual signs and symptoms are not powerful enough to discriminate GABHS pharyngitis from other types of sore throat. The Centor score is a well calibrated CPR for estimating the probability of GABHS pharyngitis. The Centor score can enhance appropriate

  9. Higher Facebook use predicts greater body image dissatisfaction during pregnancy: The role of self-comparison.

    Science.gov (United States)

    Hicks, S; Brown, A

    2016-09-01

    poor body image during pregnancy is a growing issue. Similarly, emerging evidence is suggesting that social media use may increase the risk of poor well-being e.g. depression, anxiety and body image concerns amongst users. Research has not examined how social media use may influence women during pregnancy. The aim of this study was to therefore to explore the relationship between body image during pregnancy and Facebook use. a cross sectional self-report questionnaire. two hundred and sixty nine pregnant women. community groups and online forums. a self-report questionnaire exploring maternal body image, use of Facebook and how mothers perceived Facebook affected their body image. Descriptive statistics were used to explore body image perceptions. Partial correlations (controlling for maternal age, education, parity and gestation) were used to explore the association between Facebook use and body image during pregnancy. negative body image was common in the sample, increased with gestation and was unrelated to pre pregnancy weight. Mothers with a Facebook account had higher body image concerns than those without a Facebook account. Of those with an account, increased Facebook use was associated with increased body image dissatisfaction, particularly in terms of postnatal concerns for how their body would look with 56.5% reporting that they frequently compared their pregnant body to other pregnant women on the site. Facebook access was frequent with 85% of participants checking it at least once per day and the average participant spending over an hour per day on the site. although causality cannot be fully explained, Facebook use may increase mother's risk of poor body image dissatisfaction during pregnancy. Mothers with already poor body image may also be drawn to the site in order to make comparisons of their appearance. the potential impact of Facebook on increasing the risk of, or promoting existing poor body image is an important message for those working to

  10. IMPACT OF DIFFERENT TOPOGRAPHIC CORRECTIONS ON PREDICTION ACCURACY OF FOLIAGE PROJECTIVE COVER (FPC IN A TOPOGRAPHICALLY COMPLEX TERRAIN

    Directory of Open Access Journals (Sweden)

    S. Ediriweera

    2012-07-01

    Full Text Available Quantitative retrieval of land surface biological parameters (e.g. foliage projective cover [FPC] and Leaf Area Index is crucial for forest management, ecosystem modelling, and global change monitoring applications. Currently, remote sensing is a widely adopted method for rapid estimation of surface biological parameters in a landscape scale. Topographic correction is a necessary pre-processing step in the remote sensing application for topographically complex terrain. Selection of a suitable topographic correction method on remotely sensed spectral information is still an unresolved problem. The purpose of this study is to assess the impact of topographic corrections on the prediction of FPC in hilly terrain using an established regression model. Five established topographic corrections [C, Minnaert, SCS, SCS+C and processing scheme for standardised surface reflectance (PSSSR] were evaluated on Landsat TM5 acquired under low and high sun angles in closed canopied subtropical rainforest and eucalyptus dominated open canopied forest, north-eastern Australia. The effectiveness of methods at normalizing topographic influence, preserving biophysical spectral information, and internal data variability were assessed by statistical analysis and by comparing field collected FPC data. The results of statistical analyses show that SCS+C and PSSSR perform significantly better than other corrections, which were on less overcorrected areas of faintly illuminated slopes. However, the best relationship between FPC and Landsat spectral responses was obtained with the PSSSR by producing the least residual error. The SCS correction method was poor for correction of topographic effect in predicting FPC in topographically complex terrain.

  11. The accuracy of survival time prediction for patients with glioma is improved by measuring mitotic spindle checkpoint gene expression.

    Directory of Open Access Journals (Sweden)

    Li Bie

    Full Text Available Identification of gene expression changes that improve prediction of survival time across all glioma grades would be clinically useful. Four Affymetrix GeneChip datasets from the literature, containing data from 771 glioma samples representing all WHO grades and eight normal brain samples, were used in an ANOVA model to screen for transcript changes that correlated with grade. Observations were confirmed and extended using qPCR assays on RNA derived from 38 additional glioma samples and eight normal samples for which survival data were available. RNA levels of eight major mitotic spindle assembly checkpoint (SAC genes (BUB1, BUB1B, BUB3, CENPE, MAD1L1, MAD2L1, CDC20, TTK significantly correlated with glioma grade and six also significantly correlated with survival time. In particular, the level of BUB1B expression was highly correlated with survival time (p<0.0001, and significantly outperformed all other measured parameters, including two standards; WHO grade and MIB-1 (Ki-67 labeling index. Measurement of the expression levels of a small set of SAC genes may complement histological grade and other clinical parameters for predicting survival time.

  12. Quantitative DCE-MRI for prediction of pathological complete response following neoadjuvant treatment for locally advanced breast cancer: the impact of breast cancer subtypes on the diagnostic accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Drisis, Stylianos; Stathopoulos, Konstantinos; Chao, Shih-Li; Lemort, Marc [Institute Jules Bordet, Radiology Department, Brussels (Belgium); Metens, Thierry [Erasme University Hospital, Radiology Department, Brussels (Belgium); Ignatiadis, Michael [Institute Jules Bordet, Oncology Department, Brussels (Belgium)

    2016-05-15

    To assess whether DCE-MRI pharmacokinetic (PK) parameters obtained before and during chemotherapy can predict pathological complete response (pCR) differently for different breast cancer groups. Eighty-four patients who received neoadjuvant chemotherapy for locally advanced breast cancer were retrospectively included. All patients underwent two DCE-MRI examinations, one before (EX1) and one during treatment (EX2). Tumours were classified into different breast cancer groups, namely triple negative (TNBC), HER2+ and ER+/HER2-, and compared with the whole population (WP). PK parameters Ktrans and Ve were extracted using a two-compartment Tofts model. At EX1, Ktrans predicted pCR for WP and TNBC. At EX2, maximum diameter (Dmax) predicted pCR for WP and ER+/HER2-. Both PK parameters predicted pCR in WP and TNBC and only Ktrans for the HER2+. pCR was predicted from relative difference (EX1 - EX2)/EX1 of Dmax and both PK parameters in the WP group and only for Ve in the TNBC group. No PK parameter could predict response for ER+/HER-. ROC comparison between WP and breast cancer groups showed higher but not statistically significant values for TNBC for the prediction of pCR Quantitative DCE-MRI can better predict pCR after neoadjuvant treatment for TNBC but not for the ER+/HER2- group. (orig.)

  13. The value of predicting restriction of fetal growth and compromise of its wellbeing: Systematic quantitative overviews (meta-analysis) of test accuracy literature.

    Science.gov (United States)

    Morris, Rachel K; Khan, Khalid S; Coomarasamy, Aravinthan; Robson, Stephen C; Kleijnen, Jos

    2007-03-08

    Restriction of fetal growth and compromise of fetal wellbeing remain significant causes of perinatal death and childhood disability. At present, there is a lack of scientific consensus about the best strategies for predicting these conditions before birth. Therefore, there is uncertainty about the best management of pregnant women who might have a growth restricted baby. This is likely to be due to a dearth of clear collated information from individual research studies drawn from different sources on this subject. A series of systematic reviews and meta-analyses will be undertaken to determine, among pregnant women, the accuracy of various tests to predict and/or diagnose fetal growth restriction and compromise of fetal wellbeing. We will search Medline, Embase, Cochrane Library, MEDION, citation lists of review articles and eligible primary articles and will contact experts in the field. Independent reviewers will select studies, extract data and assess study quality according to established criteria. Language restrictions will not be applied. Data synthesis will involve meta-analysis (where appropriate), exploration of heterogeneity and publication bias. The project will collate and synthesise the available evidence regarding the value of the tests for predicting restriction of fetal growth and compromise of fetal wellbeing. The systematic overviews will assess the quality of the available evidence, estimate the magnitude of potential benefits, identify those tests with good predictive value and help formulate practice recommendations.

  14. The value of predicting restriction of fetal growth and compromise of its wellbeing: Systematic quantitative overviews (meta-analysis of test accuracy literature

    Directory of Open Access Journals (Sweden)

    Robson Stephen C

    2007-03-01

    Full Text Available Abstract Background Restriction of fetal growth and compromise of fetal wellbeing remain significant causes of perinatal death and childhood disability. At present, there is a lack of scientific consensus about the best strategies for predicting these conditions before birth. Therefore, there is uncertainty about the best management of pregnant women who might have a growth restricted baby. This is likely to be due to a dearth of clear collated information from individual research studies drawn from different sources on this subject. Methods/Design A series of systematic reviews and meta-analyses will be undertaken to determine, among pregnant women, the accuracy of various tests to predict and/or diagnose fetal growth restriction and compromise of fetal wellbeing. We will search Medline, Embase, Cochrane Library, MEDION, citation lists of review articles and eligible primary articles and will contact experts in the field. Independent reviewers will select studies, extract data and assess study quality according to established criteria. Language restrictions will not be applied. Data synthesis will involve meta-analysis (where appropriate, exploration of heterogeneity and publication bias. Discussion The project will collate and synthesise the available evidence regarding the value of the tests for predicting restriction of fetal growth and compromise of fetal wellbeing. The systematic overviews will assess the quality of the available evidence, estimate the magnitude of potential benefits, identify those tests with good predictive value and help formulate practice recommendations.

  15. Improvement of life prediction accuracy by introduction of strain-rate effect into modified ductility exhaustion method

    International Nuclear Information System (INIS)

    Takahashi, Yukio

    1994-01-01

    It is important to use a reliable creep-fatigue damage evaluation method to prevent failures due to creep-fatigue damage accumulated during operation life in the structural design for fast breeder reactor plants. In this study, slow strain-rate fatigue tests were conducted for SUS316 steel for fast breeder application (316FR) and the improvement of creep-fatigue life estimation method was proposed based on test results. Main results can be summarized as follows: (1) In the slow strain-rate fatigue tests, life reduction caused by creep damage was observed as in the case of strain-hold creep-fatigue tests. (2) Strain-rate dependency of creep damage was introduced into the modified ductility exhaustion method previously proposed by the author. Good agreement of predicted lives with observed lives was achieved for SUS304 and 316FR steels with the method proposed here. (author)

  16. Plasma Lactate Dehydrogenase Levels Predict Mortality in Acute Aortic Syndromes: A Diagnostic Accuracy and Observational Outcome Study.

    Science.gov (United States)

    Morello, Fulvio; Ravetti, Anna; Nazerian, Peiman; Liedl, Giovanni; Veglio, Maria Grazia; Battista, Stefania; Vanni, Simone; Pivetta, Emanuele; Montrucchio, Giuseppe; Mengozzi, Giulio; Rinaldi, Mauro; Moiraghi, Corrado; Lupia, Enrico

    2016-02-01

    In acute aortic syndromes (AAS), organ malperfusion represents a key event impacting both on diagnosis and outcome. Increased levels of plasma lactate dehydrogenase (LDH), a biomarker of malperfusion, have been reported in AAS, but the performance of LDH for the diagnosis of AAS and the relation of LDH with outcome in AAS have not been evaluated so far.This was a bi-centric prospective diagnostic accuracy study and a cohort outcome study. From 2008 to 2014, patients from 2 Emergency Departments suspected of having AAS underwent LDH assay at presentation. A final diagnosis was obtained by aortic imaging. Patients diagnosed with AAS were followed-up for in-hospital mortality.One thousand five hundred seventy-eight consecutive patients were clinically eligible, and 999 patients were included in the study. The final diagnosis was AAS in 201 (20.1%) patients. Median LDH was 424 U/L (interquartile range [IQR] 367-557) in patients with AAS and 383 U/L (IQR 331-460) in patients with alternative diagnoses (P < 0.001). Using a cutoff of 450 U/L, the sensitivity of LDH for AAS was 44% (95% confidence interval [CI] 37-51) and the specificity was 73% (95% CI 69-76). Overall in-hospital mortality for AAS was 23.8%. Mortality was 32.6% in patients with LDH ≥ 450 U/L and 16.8% in patients with LDH < 450 U/L (P = 0.006). Following stratification according to LDH quartiles, in-hospital mortality was 12% in the first (lowest) quartile, 18.4% in the second quartile, 23.5% in the third quartile, and 38% in the fourth (highest) quartile (P = 0.01). LDH ≥ 450 U/L was further identified as an independent predictor of death in AAS both in univariate and in stepwise logistic regression analyses (odds ratio 2.28, 95% CI 1.11-4.66; P = 0.025), in addition to well-established risk markers such as advanced age and hypotension. Subgroup analysis showed excess mortality in association with LDH ≥ 450 U/L in elderly, hemodynamically stable and in nonsurgically

  17. Prediction of a missing higher charmonium around 4.26 GeV in J/ψ family

    International Nuclear Information System (INIS)

    He, Li-Ping; Chen, Dian-Yong; Liu, Xiang; Matsuki, Takayuki

    2014-01-01

    Inspired by the similarity between the mass gaps of the J/ψ and Υ families, the prediction of a missing higher charmonium with mass 4,263 MeV and very narrow width is made. In addition, the properties of two charmonium-like states, X(3940) and X(4160), and charmonium ψ(4415) are discussed, where our calculation shows that X(3940) as η c (3S) is established, while the explanation of X(4160) to be η c (4S) is fully excluded and that η c (4S) is typically a very narrow state. These predictions might be accessible at BESIII, Belle, and BelleII in near future

  18. Prediction of a missing higher charmonium around 4.26 GeV in J/ψ family

    Energy Technology Data Exchange (ETDEWEB)

    He, Li-Ping; Liu, Xiang [Institute of Modern Physics of CAS, Lanzhou University, Research Center for Hadron and CSR Physics, Lanzhou (China); Lanzhou University, School of Physical Science and Technology, Lanzhou (China); Chen, Dian-Yong [Institute of Modern Physics of CAS, Lanzhou University, Research Center for Hadron and CSR Physics, Lanzhou (China); Institute of Modern Physics of CAS, Nuclear Theory Group, Lanzhou (China); Matsuki, Takayuki [Tokyo Kasei University, Itabashi, Tokyo (Japan); Nishina Center, RIKEN, Theoretical Research Division, Saitama (Japan)

    2014-12-01

    Inspired by the similarity between the mass gaps of the J/ψ and Υ families, the prediction of a missing higher charmonium with mass 4,263 MeV and very narrow width is made. In addition, the properties of two charmonium-like states, X(3940) and X(4160), and charmonium ψ(4415) are discussed, where our calculation shows that X(3940) as η{sub c}(3S) is established, while the explanation of X(4160) to be η{sub c}(4S) is fully excluded and that η{sub c}(4S) is typically a very narrow state. These predictions might be accessible at BESIII, Belle, and BelleII in near future. (orig.)

  19. Prediction of a missing higher charmonium around 4.26 GeV in J/ψ family

    Energy Technology Data Exchange (ETDEWEB)

    He, Li-Ping, E-mail: help08@lzu.edu.cn [Research Center for Hadron and CSR Physics, Institute of Modern Physics of CAS, Lanzhou University, 730000, Lanzhou (China); School of Physical Science and Technology, Lanzhou University, 730000, Lanzhou (China); Chen, Dian-Yong, E-mail: chendy@impcas.ac.cn [Research Center for Hadron and CSR Physics, Institute of Modern Physics of CAS, Lanzhou University, 730000, Lanzhou (China); Nuclear Theory Group, Institute of Modern Physics of CAS, 730000, Lanzhou (China); Liu, Xiang, E-mail: xiangliu@lzu.edu.cn [Research Center for Hadron and CSR Physics, Institute of Modern Physics of CAS, Lanzhou University, 730000, Lanzhou (China); School of Physical Science and Technology, Lanzhou University, 730000, Lanzhou (China); Matsuki, Takayuki, E-mail: matsuki@tokyo-kasei.ac.jp [Tokyo Kasei University, 1-18-1 Kaga, 173-8602, Itabashi, Tokyo (Japan); Theoretical Research Division, Nishina Center, RIKEN, 351-0198, Saitama (Japan)

    2014-12-11

    Inspired by the similarity between the mass gaps of the J/ψ and Υ families, the prediction of a missing higher charmonium with mass 4,263 MeV and very narrow width is made. In addition, the properties of two charmonium-like states, X(3940) and X(4160), and charmonium ψ(4415) are discussed, where our calculation shows that X(3940) as η{sub c}(3S) is established, while the explanation of X(4160) to be η{sub c}(4S) is fully excluded and that η{sub c}(4S) is typically a very narrow state. These predictions might be accessible at BESIII, Belle, and BelleII in near future.

  20. Assessing the accuracy of globe thermometer method in predicting outdoor mean radiant temperature under Malaysia tropical microclimate

    Science.gov (United States)

    Khrit, N. G.; Alghoul, M. A.; Sopian, K.; Lahimer, A. A.; Elayeb, O. K.

    2017-11-01

    Assessing outdoor human thermal comfort and urban climate quality require experimental investigation of microclimatic conditions and their variations in open urban spaces. For this, it is essential to provide quantitative information on air temperature, humidity, wind velocity and mean radiant temperature. These parameters can be quantified directly except mean radiant temperature (Tmrt). The most accurate method to quantify Tmrt is integral radiation measurements (3-D shortwave and long-wave) which require using expensive radiometer instruments. To overcome this limitation the well-known globe thermometer method was suggested to calculate Tmrt. The aim of this study was to assess the possibility of using indoor globe thermometer method in predicting outdoor mean radiant temperature under Malaysia tropical microclimate. Globe thermometer method using small and large sizes of black-painted copper globes (50mm, 150mm) were used to estimate Tmrt and compare it with the reference Tmrt estimated by integral radiation method. The results revealed that the globe thermometer method considerably overestimated Tmrt during the middle of the day and slightly underestimated it in the morning and late evening. The difference between the two methods was obvious when the amount of incoming solar radiation was high. The results also showed that the effect of globe size on the estimated Tmrt is mostly small. Though, the estimated Tmrt by the small globe showed a relatively large amount of scattering caused by rapid changes in radiation and wind speed.

  1. Does simplicity compromise accuracy in ACS risk prediction? A retrospective analysis of the TIMI and GRACE risk scores.

    Directory of Open Access Journals (Sweden)

    Krishna G Aragam

    Full Text Available BACKGROUND: The Thrombolysis in Myocardial Infarction (TIMI risk scores for Unstable Angina/Non-ST-elevation myocardial infarction (UA/NSTEMI and ST-elevation myocardial infarction (STEMI and the Global Registry of Acute Coronary Events (GRACE risk scores for in-hospital and 6-month mortality are established tools for assessing risk in Acute Coronary Syndrome (ACS patients. The objective of our study was to compare the discriminative abilities of the TIMI and GRACE risk scores in a broad-spectrum, unselected ACS population and to assess the relative contributions of model simplicity and model composition to any observed differences between the two scoring systems. METHODOLOGY/PRINCIPAL FINDINGS: ACS patients admitted to the University of Michigan between 1999 and 2005 were divided into UA/NSTEMI (n = 2753 and STEMI (n = 698 subpopulations. The predictive abilities of the TIMI and GRACE scores for in-hospital and 6-month mortality were assessed by calibration and discrimination. There were 137 in-hospital deaths (4%, and among the survivors, 234 (7.4% died by 6 months post-discharge. In the UA/NSTEMI population, the GRACE risk scores demonstrated better discrimination than the TIMI UA/NSTEMI score for in-hospital (C = 0.85, 95% CI: 0.81-0.89, versus 0.54, 95% CI: 0.48-0.60; p<0.01 and 6-month (C = 0.79, 95% CI: 0.76-0.83, versus 0.56, 95% CI: 0.52-0.60; p<0.01 mortality. Among STEMI patients, the GRACE and TIMI STEMI scores demonstrated comparably excellent discrimination for in-hospital (C = 0.84, 95% CI: 0.78-0.90 versus 0.83, 95% CI: 0.78-0.89; p = 0.83 and 6-month (C = 0.72, 95% CI: 0.63-0.81, versus 0.71, 95% CI: 0.64-0.79; p = 0.79 mortality. An analysis of refitted multivariate models demonstrated a marked improvement in the discriminative power of the TIMI UA/NSTEMI model with the incorporation of heart failure and hemodynamic variables. Study limitations included unaccounted for confounders inherent to observational, single institution

  2. Gender differences in the accuracy of time-dependent blood pressure indices for predicting coronary heart disease: A random-effects modeling approach.

    Science.gov (United States)

    Brant, Larry J; Ferrucci, Luigi; Sheng, Shan L; Concin, Hans; Zonderman, Alan B; Kelleher, Cecily C; Longo, Dan L; Ulmer, Hanno; Strasak, Alexander M

    2010-12-01

    Previous studies on blood pressure (BP) indices as a predictor of coronary heart disease (CHD) have provided equivocal results and generally relied on Cox proportional hazards regression methodology, with age and sex accounting for most of the predictive capability of the model. The aim of the present study was to use serially collected BP measurements to examine age-and gender-related differences in BP indices for predicting CHD. The predictive accuracy of time-dependent BP indices for CHD was investigated using a method of risk prediction based on posterior probabilities calculated from mixed-effects regression to utilize intraindividual differences in serial BP measurements according to age changes within gender groups. Data were collected prospectively from 2 community-dwelling cohort studies in the United States (Baltimore Longitudinal Study of Aging [BLSA]) and Europe (Vorarlberg Health Monitoring and Promotion Program [VHM&PP]). The study comprised 152,633 participants (aged 30-74 years) and 610,061 BP measurements. During mean follow-up of 7.5 years, 2457 nonfatal and fatal CHD events were observed. In both study populations, pulse pressure (PP) and systolic blood pressure (SBP) performed best as individual predictors of CHD in women (area under the receiver operating characteristic curve [AUC(ROC)] was between 0.83 and 0.85 for PP, and between 0.77 and 0.81 for SBP). Mean arterial pressure (MAP) and diastolic blood pressure (DBP) performed better for men (AUC(ROC) = 0.67 and 0.65 for MAP and DBP, respectively, in the BLSA; AUC(ROC) = 0.77 and 0.75 in the VHM&PP) than for women (AUC(ROC) = 0.60 for both MAP and DBP in the BLSA; AUC(ROC) = 0.75 and 0.52, respectively, in the VHM&PP). The degree of discrimination in both populations was overall greater but more varied for all BP indices for women (AUC(ROC) estimates between 0.85 [PP in the VHM&PP] and 0.52 [DBP in the VHM&PP]) than for men (AUC(ROC) estimates between 0.78 [MAP + PP in the VHM&PP] and 0.63 [PP

  3. The accuracy of ab initio calculations without ab initio calculations for charged systems: Kriging predictions of atomistic properties for ions in aqueous solutions

    Science.gov (United States)

    Di Pasquale, Nicodemo; Davie, Stuart J.; Popelier, Paul L. A.

    2018-06-01

    Using the machine learning method kriging, we predict the energies of atoms in ion-water clusters, consisting of either Cl- or Na+ surrounded by a number of water molecules (i.e., without Na+Cl- interaction). These atomic energies are calculated following the topological energy partitioning method called Interacting Quantum Atoms (IQAs). Kriging predicts atomic properties (in this case IQA energies) by a model that has been trained over a small set of geometries with known property values. The results presented here are part of the development of an advanced type of force field, called FFLUX, which offers quantum mechanical information to molecular dynamics simulations without the limiting computational cost of ab initio calculations. The results reported for the prediction of the IQA components of the energy in the test set exhibit an accuracy of a few kJ/mol, corresponding to an average error of less than 5%, even when a large cluster of water molecules surrounding an ion is considered. Ions represent an important chemical system and this work shows that they can be correctly taken into account in the framework of the FFLUX force field.

  4. Four-hour quantitative real-time polymerase chain reaction-based comprehensive chromosome screening and accumulating evidence of accuracy, safety, predictive value, and clinical efficacy.

    Science.gov (United States)

    Treff, Nathan R; Scott, Richard T

    2013-03-15

    Embryonic comprehensive chromosomal euploidy may represent a powerful biomarker to improve the success of IVF. However, there are a number of aneuploidy screening strategies to consider, including different technologic platforms with which to interrogate the embryonic DNA, and different embryonic developmental stages from which DNA can be analyzed. Although there are advantages and disadvantages associated with each strategy, a series of experiments producing evidence of accuracy, safety, clinical predictive value, and clinical efficacy indicate that trophectoderm biopsy and quantitative real-time polymerase chain reaction (qPCR)-based comprehensive chromosome screening (CCS) may represent a useful strategy to improve the success of IVF. This Biomarkers in Reproductive Medicine special issue review summarizes the accumulated experience with the development and clinical application of a 4-hour blastocyst qPCR-based CCS technology. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  5. Enhancing predictive accuracy and reproducibility in clinical evaluation research: Commentary on the special section of the Journal of Evaluation in Clinical Practice.

    Science.gov (United States)

    Bryant, Fred B

    2016-12-01

    This paper introduces a special section of the current issue of the Journal of Evaluation in Clinical Practice that includes a set of 6 empirical articles showcasing a versatile, new machine-learning statistical method, known as optimal data (or discriminant) analysis (ODA), specifically designed to produce statistical models that maximize predictive accuracy. As this set of papers clearly illustrates, ODA offers numerous important advantages over traditional statistical methods-advantages that enhance the validity and reproducibility of statistical conclusions in empirical research. This issue of the journal also includes a review of a recently published book that provides a comprehensive introduction to the logic, theory, and application of ODA in empirical research. It is argued that researchers have much to gain by using ODA to analyze their data. © 2016 John Wiley & Sons, Ltd.

  6. Effects of Training and Feedback on Accuracy of Predicting Rectosigmoid Neoplastic Lesions and Selection of Surveillance Intervals by Endoscopists Performing Optical Diagnosis of Diminutive Polyps.

    Science.gov (United States)

    Vleugels, Jasper L A; Dijkgraaf, Marcel G W; Hazewinkel, Yark; Wanders, Linda K; Fockens, Paul; Dekker, Evelien

    2018-05-01

    Real-time differentiation of diminutive polyps (1-5 mm) during endoscopy could replace histopathology analysis. According to guidelines, implementation of optical diagnosis into routine practice would require it to identify rectosigmoid neoplastic lesions with a negative predictive value (NPV) of more than 90%, using histologic findings as a reference, and agreement with histology-based surveillance intervals for more than 90% of cases. We performed a prospective study with 39 endoscopists accredited to perform colonoscopies on participants with positive results from fecal immunochemical tests in the Bowel Cancer Screening Program at 13 centers in the Netherlands. Endoscopists were trained in optical diagnosis using a validated module (Workgroup serrAted polypS and Polyposis). After meeting predefined performance thresholds in the training program, the endoscopists started a 1-year program (continuation phase) in which they performed narrow band imaging analyses during colonoscopies of participants in the screening program and predicted histological findings with confidence levels. The endoscopists were randomly assigned to groups that received feedback or no feedback on the accuracy of their predictions. Primary outcome measures were endoscopists' abilities to identify rectosigmoid neoplastic lesions (using histology as a reference) with NPVs of 90% or more, and selecting surveillance intervals that agreed with those determined by histology for at least 90% of cases. Of 39 endoscopists initially trained, 27 (69%) completed the training program. During the continuation phase, these 27 endoscopists performed 3144 colonoscopies in which 4504 diminutive polyps were removed. The endoscopists identified neoplastic lesions with a pooled NPV of 90.8% (95% confidence interval 88.6-92.6); their proposed surveillance intervals agreed with those determined by histologic analysis for 95.4% of cases (95% confidence interval 94.0-96.6). Findings did not differ between the group

  7. From GenBank to GBIF: Phylogeny-Based Predictive Niche Modeling Tests Accuracy of Taxonomic Identifications in Large Occurrence Data Repositories.

    Science.gov (United States)

    Smith, B Eugene; Johnston, Mark K; Lücking, Robert

    2016-01-01

    Accuracy of taxonomic identifications is crucial to data quality in online repositories of species occurrence data, such as the Global Biodiversity Information Facility (GBIF), which have accumulated several hundred million records over the past 15 years. These data serve as basis for large scale analyses of macroecological and biogeographic patterns and to document environmental changes over time. However, taxonomic identifications are often unreliable, especially for non-vascular plants and fungi including lichens, which may lack critical revisions of voucher specimens. Due to the scale of the problem, restudy of millions of collections is unrealistic and other strategies are needed. Here we propose to use verified, georeferenced occurrence data of a given species to apply predictive niche modeling that can then be used to evaluate unverified occurrences of that species. Selecting the charismatic lichen fungus, Usnea longissima, as a case study, we used georeferenced occurrence records based on sequenced specimens to model its predicted niche. Our results suggest that the target species is largely restricted to a narrow range of boreal and temperate forest in the Northern Hemisphere and that occurrence records in GBIF from tropical regions and the Southern Hemisphere do not represent this taxon, a prediction tested by comparison with taxonomic revisions of Usnea for these regions. As a novel approach, we employed Principal Component Analysis on the environmental grid data used for predictive modeling to visualize potential ecogeographical barriers for the target species; we found that tropical regions conform a strong barrier, explaining why potential niches in the Southern Hemisphere were not colonized by Usnea longissima and instead by morphologically similar species. This approach is an example of how data from two of the most important biodiversity repositories, GenBank and GBIF, can be effectively combined to remotely address the problem of inaccuracy of

  8. Merging Real-Time Channel Sensor Networks with Continental-Scale Hydrologic Models: A Data Assimilation Approach for Improving Accuracy in Flood Depth Predictions

    Directory of Open Access Journals (Sweden)

    Amir Javaheri

    2018-01-01

    Full Text Available This study proposes a framework that (i uses data assimilation as a post processing technique to increase the accuracy of water depth prediction, (ii updates streamflow generated by the National Water Model (NWM, and (iii proposes a scope for updating the initial condition of continental-scale hydrologic models. Predicted flows by the NWM for each stream were converted to the water depth using the Height Above Nearest Drainage (HAND method. The water level measurements from the Iowa Flood Inundation System (a test bed sensor network in this study were converted to water depths and then assimilated into the HAND model using the ensemble Kalman filter (EnKF. The results showed that after assimilating the water depth using the EnKF, for a flood event during 2015, the normalized root mean square error was reduced by 0.50 m (51% for training tributaries. Comparison of the updated modeled water stage values with observations at testing locations showed that the proposed methodology was also effective on the tributaries with no observations. The overall error reduced from 0.89 m to 0.44 m for testing tributaries. The updated depths were then converted to streamflow using rating curves generated by the HAND model. The error between updated flows and observations at United States Geological Survey (USGS station at Squaw Creek decreased by 35%. For future work, updated streamflows could also be used to dynamically update initial conditions in the continental-scale National Water Model.

  9. Taxometric analyses and predictive accuracy of callous-unemotional traits regarding quality of life and behavior problems in non-conduct disorder diagnoses.

    Science.gov (United States)

    Herpers, Pierre C M; Klip, Helen; Rommelse, Nanda N J; Taylor, Mark J; Greven, Corina U; Buitelaar, Jan K

    2017-07-01

    Callous-unemotional (CU) traits have mainly been studied in relation to conduct disorder (CD), but can also occur in other disorder groups. However, it is unclear whether there is a clinically relevant cut-off value of levels of CU traits in predicting reduced quality of life (QoL) and clinical symptoms, and whether CU traits better fit a categorical (taxonic) or dimensional model. Parents of 979 youths referred to a child and adolescent psychiatric clinic rated their child's CU traits on the Inventory of Callous-Unemotional traits (ICU), QoL on the Kidscreen-27, and clinical symptoms on the Child Behavior Checklist. Experienced clinicians conferred DSM-IV-TR diagnoses of ADHD, ASD, anxiety/mood disorders and DBD-NOS/ODD. The ICU was also used to score the DSM-5 specifier 'with limited prosocial emotions' (LPE) of Conduct Disorder. Receiver operating characteristic (ROC) analyses revealed that the predictive accuracy of the ICU and LPE regarding QoL and clinical symptoms was poor to fair, and similar across diagnoses. A clinical cut-off point could not be defined. Taxometric analyses suggested that callous-unemotional traits on the ICU best reflect a dimension rather than taxon. More research is needed on the impact of CU traits on the functional adaptation, course, and response to treatment of non-CD conditions. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  10. Diagnostic accuracy of rapid urine dipstick test to predict urinary tract infection among pregnant women in Felege Hiwot Referral Hospital, Bahir Dar, North West Ethiopia.

    Science.gov (United States)

    Demilie, Tazebew; Beyene, Getenet; Melaku, Selabat; Tsegaye, Wondewosen

    2014-07-29

    Untreated bacteriuria during pregnancy has been shown to be associated with low birth-weight and premature delivery. Therefore, routine screening for bacteriuria is advocated. The decision about how to screen pregnant women for bacteriuria has always been a balance between the cost of screening versus the sensitivity and specificity. This study was designed to evaluate the diagnostic accuracy of the rapid dipstick test to predict urinary tract infection in pregnancy against the gold standard urine culture. A total of 367 mid stream urine samples were collected, inoculated on MacConkey, Manitol salt agar (MSA) and blood agar and incubated aerobically at 37°C for overnight. Specimens were classified as "positive" for urinary tract infection (UTI) if the growth of the pathogen(s) was at a count ≥ 10(5) colony-forming units per milliliter (cfu/mL) of urine and classified as "negative" with growth of UTI(ABU) and 71.4% and 86.7% for symptomatic UTI respectively and for nitrite 35.7% and 98.0% for ABU and 57.1% and 96.7% symptomatic UTI. This study revealed that the use of dipstick leukocyte esterase and nitrite for screening UTI particularly asymptomatic bacteriuria was associated with many false positive and negative results when it was compared against the gold standard culture method. The low sensitivity and positive predictive value of urine dipstick test proved that culture should be used for the diagnosis of UTI.

  11. Accuracy of the CT-estimated weight of the right hepatic lobe prior to living related liver donation (LRLD) for predicting the intraoperatively measured weight of the graft

    International Nuclear Information System (INIS)

    Lemke, A.-J.; Brinkmann, M.; Felix, R.; Pascher, A.; Steinmueller, T.; Settmacher, U.; Neuhaus, P.

    2003-01-01

    Purpose: Due to the shortage of cadaver donors, living related liver donation (LRLD) has emerged as an alternative to cadaver donation. The expected graft weight is one of the main determinants for donor selection. This study investigates the accuracy of preoperatively performed CT-volumetry to predict the actual weight of the right liver lobe graft. Materials and methods: In a prospective study the weight of the right hepatic lobe was calculated by volumetric analysis based on CT in 33 patients (21 females, 12 males, mean age 42.1 years, median age 41 years) prior to living related liver donation. Graft weight was calculated as the product of CT-based graft volume and 1.00 g/ml (the approximated density of healthy liver parenchyma). The calculated weight was compared with the intraoperatively measured weight of the harvested right hepatic lobe. The difference was used to determine a correction factor for estimating the actual graft weight. Results: Based on the assumption of a parenchymal density of 1.00 g/ml, the preoperatively estimated graft weight (mean 980 g ± 168 g) deviated + 33% from the intraoperatively measured right hepatic lobe weight (mean 749 g ± 170 g). By reducing the preoperatively predicted weight of the right hepatic lobe with a correction factor of 0.75, the actual graft weight can be calculated [de

  12. Predicting watershed sediment yields after wildland fire with the InVEST sediment retention model at large geographic extent in the western USA: accuracy and uncertainties

    Science.gov (United States)

    Sankey, J. B.; Kreitler, J.; McVay, J.; Hawbaker, T. J.; Vaillant, N.; Lowe, S. E.

    2014-12-01

    Wildland fire is a primary threat to watersheds that can impact water supply through increased sedimentation, water quality decline, and change the timing and amount of runoff leading to increased risk from flood and sediment natural hazards. It is of great societal importance in the western USA and throughout the world to improve understanding of how changing fire frequency, extent, and location, in conjunction with fuel treatments will affect watersheds and the ecosystem services they supply to communities. In this work we assess the utility of the InVEST Sediment Retention Model to accurately characterize vulnerability of burned watersheds to erosion and sedimentation. The InVEST tools are GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., RUSLE -Revised Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. We evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured post-fire sedimentation rates available for many watersheds in different rainfall regimes throughout the western USA from an existing, large USGS database of post-fire sediment yield [synthesized in Moody J, Martin D (2009) Synthesis of sediment yields after wildland fire in different rainfall regimes in the western United States. International Journal of Wildland Fire 18: 96-115]. The ultimate goal of this work is to calibrate and implement the model to accurately predict variability in post-fire sediment yield as a function of future landscape heterogeneity predicted by wildfire simulations, and future landscape fuel treatment scenarios, within watersheds.

  13. Accuracy of two optical chlorophyll meters in predicting chemical composition and in vitro ruminal organic matter degradability of Brachiaria hybrid, Megathyrsus maximus, and Paspalum atratum

    Directory of Open Access Journals (Sweden)

    Martin P. Hughes

    2017-03-01

    Full Text Available The objective of this study was to determine the accuracy and reliability of 2 optical chlorophyll meters: FieldScout CM 1,000 NDVI and Yara N-Tester, in predicting neutral detergent fibre (NDF, acid detergent fibre (ADF, acid detergent lignin (ADL, acid detergent insoluble nitrogen (ADIN and in vitro ruminal organic matter degradability (IVOMD of 3 tropical grasses. Optical chlorophyll measurements were taken at 3 stages (4, 8 and 12 weeks of regrowth in Brachiaria hybrid, and Megathyrsus maximus and at 6 and 12 weeks of regrowth in Paspalum atratum (cv. Ubon. Optical chlorophyll measurements showed the highest correlation (r = 0.57 to 0.85 with NDF concentration. The FieldScout CM 1,000 NDVI was better than the Yara N-Tester in predicting NDF (R2 = 0.70 and ADF (R2 = 0.79 concentrations in Brachiaria hybrid and NDF (R2 = 0.79 in M. maximus. Similarly, FieldScout CM 1,000 NDVI produced better estimates of 24 h IVOMD (IVOMD24h in Brachiaria hybrid (R2 = 0.81 and IVOMD48h in Brachiaria hybrid (R2 = 0.65 and M. maximus (R2 = 0.75. However, these prediction models had relatively low concordance correlation coefficients, i.e., CCC >0.90, but random errors were the main source of bias. It was, therefore, concluded that both optical chlorophyll meters were poor and unreliable predictors of ADIN and ADL concentrations. Overall, the FieldScout CM 1,000 NDVI shows potential to produce useful estimates of IVOMD24h and ADF in Brachiaria hybrid and IVOMD48h and NDF concentrations in M. maximus.

  14. Accuracy of Computed Tomography for Predicting Pathologic Nodal Extracapsular Extension in Patients With Head-and-Neck Cancer Undergoing Initial Surgical Resection

    Energy Technology Data Exchange (ETDEWEB)

    Prabhu, Roshan S., E-mail: roshansprabhu@gmail.com [Department of Radiation Oncology, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States); Magliocca, Kelly R. [Department of Pathology, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States); Hanasoge, Sheela [Department of Radiation Oncology, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States); Aiken, Ashley H.; Hudgins, Patricia A. [Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States); Hall, William A. [Department of Radiation Oncology, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States); Chen, Susie A. [Department of Radiation Oncology, University of Texas Southwestern, Dallas, Texas (United States); Eaton, Bree R.; Higgins, Kristin A. [Department of Radiation Oncology, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States); Saba, Nabil F. [Department of Hematology and Medical Oncology, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States); Beitler, Jonathan J. [Department of Radiation Oncology, Emory University, Atlanta, Georgia (United States); Winship Cancer Institute, Emory University, Atlanta, Georgia (United States)

    2014-01-01

    Purpose: Nodal extracapsular extension (ECE) in patients with head-and-neck cancer increases the loco-regional failure risk and is an indication for adjuvant chemoradiation therapy (CRT). To reduce the risk of requiring trimodality therapy, patients with head-and-neck cancer who are surgical candidates are often treated with definitive CRT when preoperative computed tomographic imaging suggests radiographic ECE. The purpose of this study was to assess the accuracy of preoperative CT imaging for predicting pathologic nodal ECE (pECE). Methods and Materials: The study population consisted of 432 consecutive patients with oral cavity or locally advanced/nonfunctional laryngeal cancer who underwent preoperative CT imaging before initial surgical resection and neck dissection. Specimens with pECE had the extent of ECE graded on a scale from 1 to 4. Results: Radiographic ECE was documented in 46 patients (10.6%), and pECE was observed in 87 (20.1%). Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 43.7%, 97.7%, 82.6%, and 87.3%, respectively. The sensitivity of radiographic ECE increased from 18.8% for grade 1 to 2 ECE, to 52.9% for grade 3, and 72.2% for grade 4. Radiographic ECE criteria of adjacent structure invasion was a better predictor than irregular borders/fat stranding for pECE. Conclusions: Radiographic ECE has poor sensitivity, but excellent specificity for pECE in patients who undergo initial surgical resection. PPV and NPV are reasonable for clinical decision making. The performance of preoperative CT imaging increased as pECE grade increased. Patients with resectable head-and-neck cancer with radiographic ECE based on adjacent structure invasion are at high risk for high-grade pECE requiring adjuvant CRT when treated with initial surgery; definitive CRT as an alternative should be considered where appropriate.

  15. Diagnostic Accuracies of Glycated Hemoglobin, Fructosamine, and Homeostasis Model Assessment of Insulin Resistance in Predicting Impaired Fasting Glucose, Impaired Glucose Tolerance, or New Onset Diabetes After Transplantation.

    Science.gov (United States)

    Rosettenstein, Kerri; Viecelli, Andrea; Yong, Kenneth; Nguyen, Hung Do; Chakera, Aron; Chan, Doris; Dogra, Gursharan; Lim, Ee Mun; Wong, Germaine; Lim, Wai H

    2016-07-01

    New onset diabetes after transplantation (NODAT) is associated with a 3-fold greater risk of cardiovascular disease events, with early identification and treatment potentially attenuating this risk. The optimal screening test to identify those with NODAT remains unclear, and the aim of this study was to examine the diagnostic accuracies of 4 screening tests in identifying impaired fasting glucose, impaired glucose tolerance (IGT), and NODAT. This is a single-center prospective cohort study of 83 nondiabetic kidney transplant recipients between 2008 and 2011. Oral glucose tolerance test was considered the gold standard in identifying IFG/IGT or NODAT. Diagnostic accuracies of random blood glucose, glycated hemoglobin (HBA1c), fructosamine, and Homeostasis Model Assessment-Insulin Resistance in predicting IFG/IGT or NODAT were assessed using the area under the receiver operating characteristic curve. Forty (48%) recipients had IFG/IGT or NODAT. Compared with HBA1c with adjusted area under the curve (AUC) of 0.88 (95% confidence interval [95% CI], 0.77-0.93), fructosamine was the most accurate test with adjusted AUC of 0.92 (95% CI, 0.83-0.96). The adjusted AUCs of random blood glucose and Homeostasis Model Assessment-Insulin Resistance in identifying IFG/IGT were between 0.81 and 0.85. Restricting to identifying IGT/NODAT using 2-hour oral glucose tolerance test (n = 66), fructosamine was the most accurate diagnostic test with adjusted AUC of 0.93 (95% CI, 0.84-0.99), but not statistically different to HBA1c with adjusted AUC of 0.88 (95% CI, 0.76-0.96). Although HBA1c is an acceptable and widely used screening test in detecting IFG/IGT or NODAT, fructosamine may be a more accurate diagnostic test but this needs to be further examined in larger cohorts.

  16. Accuracy and precision of the CKD-EPI and MDRD predictive equations compared with glomerular filtration rate measured by inulin clearance in a Saudi population.

    Science.gov (United States)

    Al-Wakeel, Jamal Saleh

    2016-01-01

    Predictive equations for estimating glomerular filtration rate (GFR) in different clinical conditions should be validated by comparing with the measurement of GFR using inulin clearance, a highly accurate measure of GFR. Our aim was to validate the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations by comparing it to the GFR measured using inulin clearance in chronic kidney disease (CKD) patients. Cross-sectional study performed in adult Saudi patients with CKD. King Saud University Affiliated Hospital, Riyadh, Saudi Arabia in 2014. We compared GFR measured by inulin clearance with the estimated GFR calculated using CKD-EPI and MDRD predictive formulas. Correlation, bias, precision and accuracy between the estimated GFR and inulin clearance. Comparisons were made in 31 participants (23 CKD and 8 transplanted), including 19 males (mean age 42.2 [15] years and weight 68.7 [18] kg). GFR using inulin was 51.54 (33.8) mL/min/1.73 m2 in comparison to inulin clearance, the GFR by the predictive equations was: CKD-EPI creatinine 52.6 (34.4) mL/ min/1.73 m2 (P=.490), CKD-EPI cystatin C 41.39 (30.30) mL/min/1.73 m2 (P=.002), CKD creatinine-cystatin C 45.03 (30.9) mL/min/1.73 m2 (P=.004) and MDRD GFR 48.35 (31.5) mL/min/1.73 m2 (P=.028) (statistical comparisons vs inulin). Bland-Altman plots demonstrated that GFR estimated by the CKD-EPI creatinine was the most accurate compared with inulin clearance, having a mean difference (estimated bias) and limits of agreement of -1.1 (15.6,-17.7). By comparison the mean differences for predictive equations were: CKD-EPI cystatin C 10.2 (43.7,-23.4), CKD creatinine-cystatin C 6.5 (29.3,-16.3) and MDRD 3.2 (18.3,-11.9). except for CKD-EPI creatinine, all of the equations underestimated GFR in comparison with inulin clearance. When compared with inulin clearance, the CKD-EPI creatinine equation is the most accurate, precise and least biased equation for estimation of GFR

  17. Does Prison Crowding Predict Higher Rates of Substance Use Related Parole Violations? A Recurrent Events Multi-Level Survival Analysis.

    Directory of Open Access Journals (Sweden)

    Michael A Ruderman

    Full Text Available This administrative data-linkage cohort study examines the association between prison crowding and the rate of post-release parole violations in a random sample of prisoners released with parole conditions in California, for an observation period of two years (January 2003 through December 2004.Crowding overextends prison resources needed to adequately protect inmates and provide drug rehabilitation services. Violence and lack of access to treatment are known risk factors for drug use and substance use disorders. These and other psychosocial effects of crowding may lead to higher rates of recidivism in California parolees.Rates of parole violation for parolees exposed to high and medium levels of prison crowding were compared to parolees with low prison crowding exposure. Hazard ratios (HRs with 95% confidence intervals (CIs were estimated using a Cox model for recurrent events. Our dataset included 13070 parolees in California, combining individual level parolee data with aggregate level crowding data for multilevel analysis.Comparing parolees exposed to high crowding with those exposed to low crowding, the effect sizes from greatest to least were absconding violations (HR 3.56 95% CI: 3.05-4.17, drug violations (HR 2.44 95% CI: 2.00-2.98, non-violent violations (HR 2.14 95% CI: 1.73-2.64, violent and serious violations (HR 1.88 95% CI: 1.45-2.43, and technical violations (HR 1.86 95% CI: 1.37-2.53.Prison crowding predicted higher rates of parole violations after release from prison. The effect was magnitude-dependent and particularly strong for drug charges. Further research into whether adverse prison experiences, such as crowding, are associated with recidivism and drug use in particular may be warranted.

  18. Does Prison Crowding Predict Higher Rates of Substance Use Related Parole Violations? A Recurrent Events Multi-Level Survival Analysis.

    Science.gov (United States)

    Ruderman, Michael A; Wilson, Deirdra F; Reid, Savanna

    2015-01-01

    This administrative data-linkage cohort study examines the association between prison crowding and the rate of post-release parole violations in a random sample of prisoners released with parole conditions in California, for an observation period of two years (January 2003 through December 2004). Crowding overextends prison resources needed to adequately protect inmates and provide drug rehabilitation services. Violence and lack of access to treatment are known risk factors for drug use and substance use disorders. These and other psychosocial effects of crowding may lead to higher rates of recidivism in California parolees. Rates of parole violation for parolees exposed to high and medium levels of prison crowding were compared to parolees with low prison crowding exposure. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using a Cox model for recurrent events. Our dataset included 13070 parolees in California, combining individual level parolee data with aggregate level crowding data for multilevel analysis. Comparing parolees exposed to high crowding with those exposed to low crowding, the effect sizes from greatest to least were absconding violations (HR 3.56 95% CI: 3.05-4.17), drug violations (HR 2.44 95% CI: 2.00-2.98), non-violent violations (HR 2.14 95% CI: 1.73-2.64), violent and serious violations (HR 1.88 95% CI: 1.45-2.43), and technical violations (HR 1.86 95% CI: 1.37-2.53). Prison crowding predicted higher rates of parole violations after release from prison. The effect was magnitude-dependent and particularly strong for drug charges. Further research into whether adverse prison experiences, such as crowding, are associated with recidivism and drug use in particular may be warranted.

  19. Does Prison Crowding Predict Higher Rates of Substance Use Related Parole Violations? A Recurrent Events Multi-Level Survival Analysis

    Science.gov (United States)

    Ruderman, Michael A.; Wilson, Deirdra F.; Reid, Savanna

    2015-01-01

    Objective This administrative data-linkage cohort study examines the association between prison crowding and the rate of post-release parole violations in a random sample of prisoners released with parole conditions in California, for an observation period of two years (January 2003 through December 2004). Background Crowding overextends prison resources needed to adequately protect inmates and provide drug rehabilitation services. Violence and lack of access to treatment are known risk factors for drug use and substance use disorders. These and other psychosocial effects of crowding may lead to higher rates of recidivism in California parolees. Methods Rates of parole violation for parolees exposed to high and medium levels of prison crowding were compared to parolees with low prison crowding exposure. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using a Cox model for recurrent events. Our dataset included 13070 parolees in California, combining individual level parolee data with aggregate level crowding data for multilevel analysis. Results Comparing parolees exposed to high crowding with those exposed to low crowding, the effect sizes from greatest to least were absconding violations (HR 3.56 95% CI: 3.05–4.17), drug violations (HR 2.44 95% CI: 2.00–2.98), non-violent violations (HR 2.14 95% CI: 1.73–2.64), violent and serious violations (HR 1.88 95% CI: 1.45–2.43), and technical violations (HR 1.86 95% CI: 1.37–2.53). Conclusions Prison crowding predicted higher rates of parole violations after release from prison. The effect was magnitude-dependent and particularly strong for drug charges. Further research into whether adverse prison experiences, such as crowding, are associated with recidivism and drug use in particular may be warranted. PMID:26492490

  20. Accuracy of a point-of-care ELISA test kit for predicting the presence of protective canine parvovirus and canine distemper virus antibody concentrations in dogs.

    Science.gov (United States)

    Litster, A L; Pressler, B; Volpe, A; Dubovi, E

    2012-08-01

    Canine parvovirus (CPV) and canine distemper virus (CDV) are highly infectious and often fatal diseases with worldwide distributions, and are important population management considerations in animal shelters. A point-of-care ELISA test kit is available to detect serum antibodies to CPV and CDV, and presumptively to predict protective status. The aim of this study was to determine the diagnostic accuracy of the test compared to CPV hemagglutination inhibition titers and CDV serum neutralization titers determined by a reference laboratory, using sera collected from dogs housed at animal shelters. The ELISA test was used under both field and laboratory conditions and duplicate specimens were processed using an extra wash step. The test kit yielded accurate results (CPV: sensitivity 92.3%, specificity 93.5%; CDV: sensitivity 75.7%, specificity 91.8%) under field conditions. CDV sensitivity was improved by performing the test under laboratory conditions and using an optical density (OD) meter (laboratory performed 94.0%; OD 88.1%). Point-of-care ELISA testing for serum CPV and CDV antibody titers was demonstrated to be a useful tool for determining antibody status when making decisions regarding the need for CPV and/or CDV vaccination and also in animal shelters for population management. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. COMPARISON ON ACCURACY OF LOGISTIC, GOMPERTZ AND VON BERTALANFFY MODELS IN PREDICTING GROWTH OF NEW BORN CALF UNTIL FIRST MATING OF HOLSTEIN FRIESIAN HEIFERS

    Directory of Open Access Journals (Sweden)

    L. Budimulyati S.

    2014-10-01

    Full Text Available The body weight records of 1221 heifers were used in this study collected from PT Taurus DairyFarm Sukabumi from year 2001 until 2011. The records that could be used for analysis were 373 out of1221 heifers, having completed data from birth to first mating period. Three different models i.e,Logistic, Gompertz, and von Bertalanffy were performed to analyze the growth rate of heifers. Theresults showed that the three models had different accuracy and heavily depend on age, environment andduration of recording. The body weights of sexual maturity and on certain ages were affected by theduration of recording. The Gompertz model was performed as the simpliest model in form ofcalculation. On the other hand, the Logistic was more difficult to calculate. All models indicated highaccuracy with the determination coefficient (R2 more than 90%. Based on the comparison, theGompertz and Logistic model are recommended for predicting the growth rate of heifers from birth tosexual maturity.

  2. Predictive Accuracy of Violence Risk Scale-Sexual Offender Version Risk and Change Scores in Treated Canadian Aboriginal and Non-Aboriginal Sexual Offenders.

    Science.gov (United States)

    Olver, Mark E; Sowden, Justina N; Kingston, Drew A; Nicholaichuk, Terry P; Gordon, Audrey; Beggs Christofferson, Sarah M; Wong, Stephen C P

    2018-04-01

    The present study examined the predictive properties of Violence Risk Scale-Sexual Offender version (VRS-SO) risk and change scores among Aboriginal and non-Aboriginal sexual offenders in a combined sample of 1,063 Canadian federally incarcerated men. All men participated in sexual offender treatment programming through the Correctional Service of Canada (CSC) at sites across its five regions. The Static-99R was also examined for comparison purposes. In total, 393 of the men were identified as Aboriginal (i.e., First Nations, Métis, Circumpolar) while 670 were non-Aboriginal and primarily White. Aboriginal men scored significantly higher on the Static-99R and VRS-SO and had higher rates of sexual and violent recidivism; however, there were no significant differences between Aboriginal and non-Aboriginal groups on treatment change with both groups demonstrating close to a half-standard deviation of change pre and post treatment. VRS-SO risk and change scores significantly predicted sexual and violent recidivism over fixed 5- and 10-year follow-ups for both racial/ancestral groups. Cox regression survival analyses also demonstrated positive treatment changes to be significantly associated with reductions in sexual and violent recidivism among Aboriginal and non-Aboriginal men after controlling baseline risk. A series of follow-up Cox regression analyses demonstrated that risk and change score information accounted for much of the observed differences between Aboriginal and non-Aboriginal men in rates of sexual recidivism; however, marked group differences persisted in rates of general violent recidivism even after controlling for these covariates. The results support the predictive properties of VRS-SO risk and change scores with treated Canadian Aboriginal sexual offenders.

  3. PAI-1 4G/5G and MTHFR C677T polymorphisms increased the accuracy of two prediction scores for the risk of acute lower extremity deep vein thrombosis.

    Science.gov (United States)

    Pop, Tudor Radu; Vesa, Ştefan Cristian; Trifa, Adrian Pavel; Crişan, Sorin; Buzoianu, Anca Dana

    2014-01-01

    This study investigates the accuracy of two scores in predicting the risk of acute lower extremity deep vein thrombosis. The study included 170 patients [85 (50%) women and 85 (50%) men] who were diagnosed with acute lower extremity deep vein thrombosis (DVT) with duplex ultrasonography. Median age was 62 (52.75; 72) years. The control group consisted of 166 subjects [96 (57.8%) women and 70 (42.2%) men], without DVT, matched for age (± one year) to those in the group with DVT. The patients and controls were selected from those admitted to the internal medicine, cardiology and geriatrics wards within the Municipal Hospital of Cluj-Napoca, Romania, between October 2009 and June 2011. Clinical, demographic and lab data were recorded for each patient. For each patient we calculated the prior risk of DVT using two prediction scores: Caprini and Padua. According to the Padua score only 93 (54.7%) patients with DVT had been at high risk of developing DVT, while 48 (28.9%) of controls were at high risk of developing DVT. When Padua score included PAI-1 4G/5G and MTHFR C677T polymorphisms, the sensitivity increased at 71.7%. Using the Caprini score, we determined that 147 (86.4%) patients with DVT had been at high risk of developing DVT, while 103 (62%) controls were at high risk of developing DVT. A Caprini score higher than 5 was the strongest predictor of acute lower extremity DVT risk. The Caprini prediction score was more sensitive than the Padua score in assessing the high risk of DVT in medical patients. PAI-1 4G/5G and MTHFR C677T polymorphisms increased the sensitivity of Padua score.

  4. Ventricular short-axis measurements in patients with pulmonary embolism: Effect of ECG-gating on variability, accuracy, and risk prediction

    International Nuclear Information System (INIS)

    Scheffel, Hans; Stolzmann, Paul; Leschka, Sebastian; Desbiolles, Lotus; Seifert, Burkhardt; Marincek, Borut; Alkadhi, Hatem

    2012-01-01

    Objective: To assess prospectively the intra- and interobserver variability, accuracy, and prognostic value of right and left ventricular short-axis diameter (RVd and LVd) measurements for risk stratification in patients with pulmonary embolism (PE) using ECG-gated compared to non-gated CT. Materials and methods: Sixty consecutive patients (33 women; mean age 58.7 ± 10.3 years) with suspicion of PE underwent both non-gated and ECG-gated chest CT. RVd and LVd on four-chamber views and intra- and interobserver agreements were calculated for both protocols. RVd/LVd ratios were calculated and were related to 30-days adverse clinical events using receiver operating characteristics with area-under-the-curve (AUC) analyses. Results: Both inter- and intraobserver variability showed narrower limits of agreement for all measurements with ECG-gated as compared to non-gated CT. Diameter measurements were significantly lower using non-ECG-gated CT as compared to ECG-gated CT for RVd and LVd (both p < .05). The AUC for the RVd/LVd ratio from ECG-gated CT was significantly larger than that from non-gated CT (0.956, 95% CI: 0.768–0.999 versus 0.675, 95% CI: 0.439–0.860; p = .048). Conclusion: RVd and LVd measurements from ECG-gated chest CT show less intra- and interobserver variability and more accurately reflect ventricular function. In our patient cohort ECG-gated chest CT allows better prediction of short-term outcome of patients with acute PE that needs to be validated in a larger outcome study

  5. Accuracy of single progesterone test to predict early pregnancy outcome in women with pain or bleeding: meta-analysis of cohort studies

    NARCIS (Netherlands)

    Verhaegen, Jorine; Gallos, Ioannis D.; van Mello, Norah M.; Abdel-Aziz, Mohamed; Takwoingi, Yemisi; Harb, Hoda; Deeks, Jonathan J.; Mol, Ben W. J.; Coomarasamy, Arri

    2012-01-01

    Objective To determine the accuracy with which a single progesterone measurement in early pregnancy discriminates between viable and non-viable pregnancy. Design Systematic review and meta-analysis of diagnostic accuracy studies. Data sources Medline, Embase, CINAHL, Web of Science, ProQuest,

  6. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

    Directory of Open Access Journals (Sweden)

    Santana Isabel

    2011-08-01

    Full Text Available Abstract Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI, but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

  7. Circulating irisin levels are lower in patients with either stable coronary artery disease (CAD) or myocardial infarction (MI) versus healthy controls, whereas follistatin and activin A levels are higher and can discriminate MI from CAD with similar to CK-MB accuracy.

    Science.gov (United States)

    Anastasilakis, Athanasios D; Koulaxis, Dimitrios; Kefala, Nikoleta; Polyzos, Stergios A; Upadhyay, Jagriti; Pagkalidou, Eirini; Economou, Fotios; Anastasilakis, Chrysostomos D; Mantzoros, Christos S

    2017-08-01

    Several myokines are produced by cardiac muscle. We investigated changes in myokine levels at the time of acute myocardial infarction (MI) and following reperfusion in relation to controls. Patients with MI (MI Group, n=31) treated with percutaneous coronary intervention (PCI) were compared to patients with stable coronary artery disease (CAD) subjected to scheduled PCI (CAD Group, n=40) and controls with symptoms mimicking CAD without stenosis in angiography (Control Group, n=43). The number and degree of stenosis were recorded. Irisin, follistatin, follistatin-like 3, activin A and B, ALT, AST, CK and CK-MB were measured at baseline and 6 or 24h after the intervention. MI and CAD patients had lower irisin than controls (p<0.001). MI patients had higher follistatin, activin A, CK, CK-MB and AST than CAD patients and controls (all p≤0.001). None of the myokines changed following reperfusion. Circulating irisin was associated with the degree of stenosis in all patients (p=0.05). Irisin was not inferior to CK-MB in predicting MI while folistatin and activin A could discriminate MI from CAD patients with similar to CK-MB accuracy. None of these myokines was altered following PCI in contrast to CK-MB. Irisin levels are lower in MI and CAD implying that their production may depend on myocadial blood supply. Follistatin and activin A are higher in MI than in CAD suggesting increased release due to myocardial necrosis. They can predict MI with accuracy similar to CK-MB and their role in the diagnosis of MI remains to be confirmed by prospective large clinical studies. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Higher energy efficiency and better water quality by using model predictive flow control at water supply systems

    NARCIS (Netherlands)

    Bakker, M.; Verberk, J.Q.J.C.; Palmen, L.J.; Sperber, V.; Bakker, G.

    2011-01-01

    Half of all water supply systems in the Netherlands are controlled by model predictive flow control; the other half are controlled by conventional level based control. The differences between conventional level based control and model predictive control were investigated in experiments at five full

  9. Higher frequency network activity flow predicts lower frequency node activity in intrinsic low-frequency BOLD fluctuations.

    Science.gov (United States)

    Bajaj, Sahil; Adhikari, Bhim Mani; Dhamala, Mukesh

    2013-01-01

    The brain remains electrically and metabolically active during resting conditions. The low-frequency oscillations (LFO) of the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI) coherent across distributed brain regions are known to exhibit features of this activity. However, these intrinsic oscillations may undergo dynamic changes in time scales of seconds to minutes during resting conditions. Here, using wavelet-transform based time-frequency analysis techniques, we investigated the dynamic nature of default-mode networks from intrinsic BOLD signals recorded from participants maintaining visual fixation during resting conditions. We focused on the default-mode network consisting of the posterior cingulate cortex (PCC), the medial prefrontal cortex (mPFC), left middle temporal cortex (LMTC) and left angular gyrus (LAG). The analysis of the spectral power and causal flow patterns revealed that the intrinsic LFO undergo significant dynamic changes over time. Dividing the frequency interval 0 to 0.25 Hz of LFO into four intervals slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), slow-3 (0.073-0.198 Hz) and slow-2 (0.198-0.25 Hz), we further observed significant positive linear relationships of slow-4 in-out flow of network activity with slow-5 node activity, and slow-3 in-out flow of network activity with slow-4 node activity. The network activity associated with respiratory related frequency (slow-2) was found to have no relationship with the node activity in any of the frequency intervals. We found that the net causal flow towards a node in slow-3 band was correlated with the number of fibers, obtained from diffusion tensor imaging (DTI) data, from the other nodes connecting to that node. These findings imply that so-called resting state is not 'entirely' at rest, the higher frequency network activity flow can predict the lower frequency node activity, and the network activity flow can reflect underlying structural

  10. Current practices in the prediction and prevention of preterm birth in patients with higher-order multiple gestations.

    Science.gov (United States)

    Baker, Emily; Hunter, Tiffany; Okun, Nanette; Farine, Dan

    2015-05-01

    We sought to determine the interventions utilized by maternal-fetal medicine specialists in the prediction and prevention of preterm labor in higher-order multiple (HOM) gestations. Online questionnaires and email surveys were sent to all the maternal-fetal medicine specialists in Canada (n=122). Questionnaire items included interventions physicians routinely recommended for HOM gestations including: (1) bed rest; (2) cervical length measurement on transvaginal ultrasound; (3) corticosteroids use; (4) cerclage; and (5) tocolytic therapy. Response rate was 66% (81/122), with 68% of respondents in practice for >10 years. Of physicians, 91% did not routinely recommend bed rest (95% confidence interval [CI], 84.7-97.2). In all, 82% (95% CI, 73.63-90.4%) recommended routine cervical length assessment with 32.3% (95% CI, 20.7-43.2) and 37.1% (95% CI, 25.3-48.6) of this group suggesting assessment at 16-18 and 19-21 weeks, respectively. Frequency of assessment varied from biweekly (53.3%; 95% CI, 40.9-65.0), to monthly (23.3%; 95% CI, 12.8-33.1), to a single measurement repeated only if abnormal (12.5%; 95% CI, 4.5-20.8). In all, 28% (95% CI, 18.2-37.8) recommended routine administration of corticosteroids for lung maturation. Timing of administration varied, with 24% initiating steroids between 24-26 weeks, 59% between 27-28 weeks, and 17% after 28 weeks. None reported routine cerclage placement. However, 71% (95% CI, 61.1-80.8) would perform cerclage based on history or ultrasound. Of respondents, 81% (95% CI, 72.4-89.5) would consider using tocolytic agents for threatened preterm labor including calcium channel blockers (94%), nonsteroidal antiinflammatory drugs (5%), and nitroglycerin transdermal patch (24%). The variable practice guidelines and paucity of data for management of HOM pregnancy places the onus on individual practitioners to develop their own management schemes. This results in heterogeneous management, which is based on conflicting international

  11. Exploring the genetic architecture and improving genomic prediction accuracy for mastitis and milk production traits in dairy cattle by mapping variants to hepatic transcriptomic regions responsive to intra-mammary infection.

    Science.gov (United States)

    Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

    2017-05-12

    A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers [e.g. single nucleotide polymorphisms (SNPs)] from those regions, if included, may improve the predictive ability of a genomic model. We applied a genomic feature best linear unbiased prediction model (GFBLUP) to implement the above strategy by considering the hepatic transcriptomic regions responsive to IMI as genomic features. GFBLUP, an extension of GBLUP, includes a separate genomic effect of SNPs within a genomic feature, and allows differential weighting of the individual marker relationships in the prediction equation. Since GFBLUP is computationally intensive, we investigated whether a SNP set test could be a computationally fast way to preselect predictive genomic features. The SNP set test assesses the association between a genomic feature and a trait based on single-SNP genome-wide association studies. We applied these two approaches to mastitis and milk production traits (milk, fat and protein yield) in Holstein (HOL, n = 5056) and Jersey (JER, n = 1231) cattle. We observed that a majority of genomic features were enriched in genomic variants that were associated with mastitis and milk production traits. Compared to GBLUP, the accuracy of genomic prediction with GFBLUP was marginally improved (3.2 to 3.9%) in within-breed prediction. The highest increase (164.4%) in prediction accuracy was observed in across-breed prediction. The significance of genomic features based on the SNP set test were correlated with changes in prediction accuracy of GFBLUP (P layers of biological knowledge to provide novel insights into the biological basis of complex traits, and to improve the accuracy of genomic prediction. The SNP set

  12. Checking the predictive accuracy of basic symptoms against ultra high-risk criteria and testing of a multivariable prediction model: Evidence from a prospective three-year observational study of persons at clinical high-risk for psychosis.

    Science.gov (United States)

    Hengartner, M P; Heekeren, K; Dvorsky, D; Walitza, S; Rössler, W; Theodoridou, A

    2017-09-01

    The aim of this study was to critically examine the prognostic validity of various clinical high-risk (CHR) criteria alone and in combination with additional clinical characteristics. A total of 188 CHR positive persons from the region of Zurich, Switzerland (mean age 20.5 years; 60.2% male), meeting ultra high-risk (UHR) and/or basic symptoms (BS) criteria, were followed over three years. The test battery included the Structured Interview for Prodromal Syndromes (SIPS), verbal IQ and many other screening tools. Conversion to psychosis was defined according to ICD-10 criteria for schizophrenia (F20) or brief psychotic disorder (F23). Altogether n=24 persons developed manifest psychosis within three years and according to Kaplan-Meier survival analysis, the projected conversion rate was 17.5%. The predictive accuracy of UHR was statistically significant but poor (area under the curve [AUC]=0.65, Pthinking of binary at-risk criteria is necessary in order to improve the prognosis of psychotic disorders. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  13. Diagnostic accuracy of presepsin (soluble CD14 subtype) for prediction of bacteremia in patients with systemic inflammatory response syndrome in the Emergency Department.

    Science.gov (United States)

    Romualdo, Luis García de Guadiana; Torrella, Patricia Esteban; González, Monserrat Viqueira; Sánchez, Roberto Jiménez; Holgado, Ana Hernando; Freire, Alejandro Ortín; Acebes, Sergio Rebollo; Otón, María Dolores Albaladejo

    2014-05-01

    Bacteremia is indicative of severe bacterial infection with significant mortality. Its early diagnosis is extremely important for implementation of antimicrobial therapy but a diagnostic challenge. Although blood culture is the "gold standard" for diagnosis of bacteremia this method has limited usefulness for the early detection of blood-stream infection. In this study we assessed the presepsin as predictor of bacteremia in patients with systemic inflammatory response syndrome (SIRS) on admission to the Emergency Department and compare it with current available infection biomarkers. A total of 226 patients admitted to the Emergency Department with SIRS were included. In 37 patients blood culture had a positive result (bacteremic SIRS group) and 189 had a negative blood culture result (non-bacteremic SIRS group). Simultaneously with blood culture, presepsin, procalcitonin (PCT) and C-reactive protein (CRP) were measured. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker as predictor of bacteremia. Presepsin values were significantly higher in bacteremic SIRS group when compared with non-bacteremic SIRS group. ROC curve analysis and area under curve (AUC) revealed a value of 0.750 for presepsin in differentiating SIRS patients with bacteremia from those without, similar than that for PCT (0.787) and higher than that for CRP (0.602). The best cut-off value for presepsin was 729pg/mL, which was associated with a negative predictive value of 94.4%. Presepsin may contribute to rule out the diagnosis of bacteremia in SIRS patients admitted to the Emergency Department. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  14. Generating Lies Produces Lower Memory Predictions and Higher Memory Performance than Telling the Truth: Evidence for a Metacognitive Illusion

    Science.gov (United States)

    Besken, Miri

    2018-01-01

    Manipulations that induce disfluency during encoding generally produce lower memory predictions for the disfluent condition than for the fluent condition. Similar to other manipulations of disfluency, generating lies takes longer and requires more mental effort than does telling the truth; hence, a manipulation of lie generation might produce…

  15. Deep Learning Predicts Correlation between a Functional Signature of Higher Visual Areas and Sparse Firing of Neurons

    Directory of Open Access Journals (Sweden)

    Chengxu Zhuang

    2017-10-01

    Full Text Available Visual information in the visual cortex is processed in a hierarchical manner. Recent studies show that higher visual areas, such as V2, V3, and V4, respond more vigorously to images with naturalistic higher-order statistics than to images lacking them. This property is a functional signature of higher areas, as it is much weaker or even absent in the primary visual cortex (V1. However, the mechanism underlying this signature remains elusive. We studied this problem using computational models. In several typical hierarchical visual models including the AlexNet, VggNet, and SHMAX, this signature was found to be prominent in higher layers but much weaker in lower layers. By changing both the model structure and experimental settings, we found that the signature strongly correlated with sparse firing of units in higher layers but not with any other factors, including model structure, training algorithm (supervised or unsupervised, receptive field size, and property of training stimuli. The results suggest an important role of sparse neuronal activity underlying this special feature of higher visual areas.

  16. Prediction of outcome of bright light treatment in patients with seasonal affective disorder: Discarding the early response, confirming a higher atypical balance, and uncovering a higher body mass index at baseline as predictors of endpoint outcome.

    Science.gov (United States)

    Dimitrova, Tzvetelina D; Reeves, Gloria M; Snitker, Soren; Lapidus, Manana; Sleemi, Aamar R; Balis, Theodora G; Manalai, Partam; Tariq, Muhammad M; Cabassa, Johanna A; Karim, Naila N; Johnson, Mary A; Langenberg, Patricia; Rohan, Kelly J; Miller, Michael; Stiller, John W; Postolache, Teodor T

    2017-11-01

    We tested the hypothesis that the early improvement in mood after the first hour of bright light treatment compared to control dim-red light would predict the outcome at six weeks of bright light treatment for depressed mood in patients with Seasonal Affective Disorder (SAD). We also analyzed the value of Body Mass Index (BMI) and atypical symptoms of depression at baseline in predicting treatment outcome. Seventy-eight adult participants were enrolled. The first treatment was controlled crossover, with randomized order, and included one hour of active bright light treatment and one hour of control dim-red light, with one-hour washout. Depression was measured on the Structured Interview Guide for the Hamilton Rating Scale for Depression-SAD version (SIGH-SAD). The predictive association of depression scores changes after the first session. BMI and atypical score balance with treatment outcomes at endpoint were assessed using multivariable linear and logistic regressions. No significant prediction by changes in depression scores after the first session was found. However, higher atypical balance scores and BMI positively predicted treatment outcome. Absence of a control intervention for the six-weeks of treatment (only the first session in the laboratory was controlled). Exclusion of patients with comorbid substance abuse, suicidality and bipolar I disorder, and patients on antidepressant medications, reducing the generalizability of the study. Prediction of outcome by early response to light treatment was not replicated, and the previously reported prediction of baseline atypical balance was confirmed. BMI, a parameter routinely calculated in primary care, was identified as a novel predictor, and calls for replication and then exploration of possible mediating mechanisms. Published by Elsevier B.V.

  17. 100% classification accuracy considered harmful: the normalized information transfer factor explains the accuracy paradox.

    Directory of Open Access Journals (Sweden)

    Francisco J Valverde-Albacete

    Full Text Available The most widely spread measure of performance, accuracy, suffers from a paradox: predictive models with a given level of accuracy may have greater predictive power than models with higher accuracy. Despite optimizing classification error rate, high accuracy models may fail to capture crucial information transfer in the classification task. We present evidence of this behavior by means of a combinatorial analysis where every possible contingency matrix of 2, 3 and 4 classes classifiers are depicted on the entropy triangle, a more reliable information-theoretic tool for classification assessment. Motivated by this, we develop from first principles a measure of classification performance that takes into consideration the information learned by classifiers. We are then able to obtain the entropy-modulated accuracy (EMA, a pessimistic estimate of the expected accuracy with the influence of the input distribution factored out, and the normalized information transfer factor (NIT, a measure of how efficient is the transmission of information from the input to the output set of classes. The EMA is a more natural measure of classification performance than accuracy when the heuristic to maximize is the transfer of information through the classifier instead of classification error count. The NIT factor measures the effectiveness of the learning process in classifiers and also makes it harder for them to "cheat" using techniques like specialization, while also promoting the interpretability of results. Their use is demonstrated in a mind reading task competition that aims at decoding the identity of a video stimulus based on magnetoencephalography recordings. We show how the EMA and the NIT factor reject rankings based in accuracy, choosing more meaningful and interpretable classifiers.

  18. A comparison between genotyping-by-sequencing and array-based scoring of SNPs for genomic prediction accuracy in winter wheat.

    Science.gov (United States)

    Elbasyoni, Ibrahim S; Lorenz, A J; Guttieri, M; Frels, K; Baenziger, P S; Poland, J; Akhunov, E

    2018-05-01

    The utilization of DNA molecular markers in plant breeding to maximize selection response via marker-assisted selection (MAS) and genomic selection (GS) has revolutionized plant breeding. A key factor affecting GS applicability is the choice of molecular marker platform. Genotyping-by-sequencing scored SNPs (GBS-scored SNPs) provides a large number of markers, albeit with high rates of missing data. Array scored SNPs are of high quality, but the cost per sample is substantially higher. The objectives of this study were 1) compare GBS-scored SNPs, and array scored SNPs for genomic selection applications, and 2) compare estimates of genomic kinship and population structure calculated using the two marker platforms. SNPs were compared in a diversity panel consisting of 299 hard winter wheat (Triticum aestivum L.) accessions that were part of a multi-year, multi-environments association mapping study. The panel was phenotyped in Ithaca, Nebraska for heading date, plant height, days to physiological maturity and grain yield in 2012 and 2013. The panel was genotyped using GBS-scored SNPs, and array scored SNPs. Results indicate that GBS-scored SNPs is comparable to or better than Array-scored SNPs for genomic prediction application. Both platforms identified the same genetic patterns in the panel where 90% of the lines were classified to common genetic groups. Overall, we concluded that GBS-scored SNPs have the potential to be the marker platform of choice for genetic diversity and genomic selection in winter wheat. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. Predicting Student Engagement by Disability Type at Four-Year Baccalaureate Higher Education Institutions Using Self-Reported Data

    Science.gov (United States)

    Ziswiler, Korrin M.

    2014-01-01

    The number of students with disabilities accessing higher education continues to increase, yet persistence and graduation rates for this population of students are considerably lower than those of students without disabilities. Previous research suggests that a key factor in improving post-secondary outcomes is increasing the level with which…

  20. Accuracy of genomic selection in European maize elite breeding populations.

    Science.gov (United States)

    Zhao, Yusheng; Gowda, Manje; Liu, Wenxin; Würschum, Tobias; Maurer, Hans P; Longin, Friedrich H; Ranc, Nicolas; Reif, Jochen C

    2012-03-01

    Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.

  1. Prediction of isoscalar charmoniumlike structures in the hidden-charm di-eta decays of higher charmonia

    International Nuclear Information System (INIS)

    Chen, Dian-Yong; Liu, Xiang; Matsuki, Takayuki

    2015-01-01

    Considering the situation that a single chiral particle, η is initially emitted, we study the hidden-charm di-eta decays of the charmoniumlike state Y(4660) and the predicted charmonium ψ(4790), i.e., Y(4660)/ψ(4790)→J/ψηη through the inetermediates η[D (∗) D-bar (∗) ] and/or η [D s +(∗) D s −(∗) ], and answer the important question of whether there exist isoscalar charmoniumlike structures in the D (∗) D-bar (∗) and/or D s +(∗) D s −(∗) channels. Our results predict that there will be enhancement structures near D D-bar ∗ , D ∗ D-bar ∗ and D s D-bar s ∗ thresholds for Y(4660) and near D ∗ D-bar ∗ , D s D-bar s ∗ and D s ∗ D-bar s ∗ thresholds for ψ(4790) in the M max (J/ψη) distributions of Y(4660)/ψ(4790)→ηηJ/ψ, respectively. These peaks are accessible in future experiments, especially BESIII, Belle, BaBar, and the forthcoming BelleII. (paper)

  2. Predicting higher selection in elite junior Australian Rules football: The influence of physical performance and anthropometric attributes.

    Science.gov (United States)

    Robertson, Sam; Woods, Carl; Gastin, Paul

    2015-09-01

    To develop a physiological performance and anthropometric attribute model to predict Australian Football League draft selection. Cross-sectional observational. Data was obtained (n=4902) from three Under-18 Australian football competitions between 2010 and 2013. Players were allocated into one of the three groups, based on their highest level of selection in their final year of junior football (Australian Football League Drafted, n=292; National Championship, n=293; State-level club, n=4317). Physiological performance (vertical jumps, agility, speed and running endurance) and anthropometric (body mass and height) data were obtained. Hedge's effect sizes were calculated to assess the influence of selection-level and competition on these physical attributes, with logistic regression models constructed to discriminate Australian Football League Drafted and National Championship players. Rule induction analysis was undertaken to determine a set of rules for discriminating selection-level. Effect size comparisons revealed a range of small to moderate differences between State-level club players and both other groups for all attributes, with trivial to small differences between Australian Football League Drafted and National Championship players noted. Logistic regression models showed multistage fitness test, height and 20 m sprint time as the most important attributes in predicting Draft success. Rule induction analysis showed that players displaying multistage fitness test scores of >14.01 and/or 20 m sprint times of football players being recruited to the highest level of the sport. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  3. Modeling the distribution of white spruce (Picea glauca) for Alaska with high accuracy: an open access role-model for predicting tree species in last remaining wilderness areas

    Science.gov (United States)

    Bettina Ohse; Falk Huettmann; Stefanie M. Ickert-Bond; Glenn P. Juday

    2009-01-01

    Most wilderness areas still lack accurate distribution information on tree species. We met this need with a predictive GIS modeling approach, using freely available digital data and computer programs to efficiently obtain high-quality species distribution maps. Here we present a digital map with the predicted distribution of white spruce (Picea glauca...

  4. Prediction of Stator Terminal Voltages in IPMSM based on Static and Transient FEM Solution: Trade-off between Accuracy and Speed of Computation

    Directory of Open Access Journals (Sweden)

    Hichem Bouras

    2017-12-01

    Full Text Available The present work deals with the calculation of the time varying induced emf in permanent magnet synchronous machines from the numerical finite element solution. A review of the existing methods is presented; their intrinsic merits, in terms of accuracy and speed of computation, are compared. The currently used method, which relies on a weighting averaging procedure of the magnetic vector potential (MVP over the slot area in order to derive the winding flux linkage and the stator induced, has been modified to enhance its accuracy. An alternative method, which relies on the magnetic vector potential distribution along the mid airgap line, is proposed to carry out the same task. This approach has turned out to be very efficient since it enables a straightforward data handling, signal reconstruction, filtering and spectrum analysis of the relevant waveforms to be easily implemented in a single post-processing function. Finally, the relevance and efficiency of each method, in terms of accuracy and speed of computation, has been confirmed by the experimental results.

  5. Evaluate the capability and accuracy of response-2000 program in prediction of the shear capacities of reinforced and prestressed concrete members

    Directory of Open Access Journals (Sweden)

    Ibrahim M. Metwally

    2012-08-01

    Member response analysis and sectional analysis were both used in Response-2000 to predict the behavior of the beams. Member response calculates the full member behavior including the deflection and curvature along the member length, as well as predicted failure modes. The analysis was performed by specifying the length subjected to shear and any constant moment region. Response-2000 provided a very good prediction of experimental behavior when compared to a database of 534 beams tested in shear. These include prestressed and reinforced sections, very large footing-like sections, sections made with very high strength concrete and elements with unusual geometry. All are predicted well. The results include that Response-2000 can predict the failure shear with an average experimental over predicted shear ratio of 1.05 with a coefficient of variation of 12%. This compares favorably to the ACI 318-08 [2] Code prediction ratios that have an average of 1.20 and a coefficient of variation of 32%.

  6. The accuracy of {sup 18}F-FDG PET/CT in predicting the pathological response to neoadjuvant chemotherapy in patients with breast cancer. A meta-analysis and systematic review

    Energy Technology Data Exchange (ETDEWEB)

    Tian, Fangfang; Shen, Guohua; Diao, Wei; Jia, Zhiyun [West China Hospital of Sichuan University, Department of Nuclear Medicine, Chengdu, Sichuan (China); Deng, Yunfu [West China Hospital of Sichuan University, Department of Oncology, Chengdu (China)

    2017-11-15

    The aim of this meta-analysis was to evaluate the accuracy of {sup 18}F-FDG PET/CT in predicting the pathological response to neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients. PubMed, Embase, the Cochrane Library (Central), and the Web of Science (SCI-Expanded) were systematically searched to identify pertinent studies. The methodologic quality of the included studies was assessed by the Quality Assessment of Diagnostic Accuracy Studies-2. The Spearman correlation coefficient was used to explore the existence of a threshold effect. Heterogeneity was assessed by the likelihood ratio I {sup 2} index. The pooled values calculated with a mixed-effects model for the sensitivity, specificity and diagnostic odds ratio with 95% confidence intervals were 81.9% (76.0-86.6%), 79.3% (72.1-85.1%) and 17.35 (10.98-27.42), respectively. {sup 18}F-FDG PET/CT has a moderate accuracy in predicting the pathological response during the early process of NAC in breast cancer patients. To increase the role of {sup 18}F-FDG PET/CT in monitoring the therapy response, future prospective studies are needed to explore how chemotherapy regimens and different subtypes affect the levels of glucose metabolism. (orig.)

  7. 50 Hz hippocampal stimulation in refractory epilepsy: Higher level of basal glutamate predicts greater release of glutamate.

    Science.gov (United States)

    Cavus, Idil; Widi, Gabriel A; Duckrow, Robert B; Zaveri, Hitten; Kennard, Jeremy T; Krystal, John; Spencer, Dennis D

    2016-02-01

    The effect of electrical stimulation on brain glutamate release in humans is unknown. Glutamate is elevated at baseline in the epileptogenic hippocampus of patients with refractory epilepsy, and increases during spontaneous seizures. We examined the effect of 50 Hz stimulation on glutamate release and its relationship to interictal levels in the hippocampus of patients with epilepsy. In addition, we measured basal and stimulated glutamate levels in a subset of these patients where stimulation elicited a seizure. Subjects (n = 10) were patients with medically refractory epilepsy who were undergoing intracranial electroencephalography (EEG) evaluation in an epilepsy monitoring unit. Electrical stimulation (50 Hz) was delivered through implanted hippocampal electrodes (n = 11), and microdialysate samples were collected every 2 min. Basal glutamate, changes in glutamate efflux with stimulation, and the relationships between peak stimulation-associated glutamate concentrations, basal zero-flow levels, and stimulated seizures were examined. Stimulation of epileptic hippocampi in patients with refractory epilepsy caused increases in glutamate efflux (p = 0.005, n = 10), and 4 of ten patients experienced brief stimulated seizures. Stimulation-induced increases in glutamate were not observed during the evoked seizures, but rather were related to the elevation in interictal basal glutamate (R(2) = 0.81, p = 0.001). The evoked-seizure group had lower basal glutamate levels than the no-seizure group (p = 0.04), with no stimulation-induced change in glutamate efflux (p = 0.47, n = 4). Conversely, increased glutamate was observed following stimulation in the no-seizure group (p = 0.005, n = 7). Subjects with an atrophic hippocampus had higher basal glutamate levels (p = 0.03, n = 7) and higher stimulation-induced glutamate efflux. Electrical stimulation of the epileptic hippocampus either increased extracellular glutamate efflux or induced seizures. The magnitude of stimulated

  8. Higher adsorption capacity of Spirulina platensis alga for Cr(VI) ions removal: parameter optimisation, equilibrium, kinetic and thermodynamic predictions.

    Science.gov (United States)

    Gunasundari, Elumalai; Senthil Kumar, Ponnusamy

    2017-04-01

    This study discusses about the biosorption of Cr(VI) ion from aqueous solution using ultrasonic assisted Spirulina platensis (UASP). The prepared UASP biosorbent was characterised by Fourier transform infrared spectroscopy, X-ray diffraction, Brunauer-Emmet-Teller, scanning electron spectroscopy and energy dispersive X-ray and thermogravimetric analyses. The optimum condition for the maximum removal of Cr(VI) ions for an initial concentration of 50 mg/l by UASP was measured as: adsorbent dose of 1 g/l, pH of 3.0, contact time of 30 min and temperature of 303 K. Adsorption isotherm, kinetics and thermodynamic parameters were calculated. Freundlich model provided the best results for the removal of Cr(VI) ions by UASP. The adsorption kinetics of Cr(VI) ions onto UASP showed that the pseudo-first-order model was well in line with the experimental data. In the thermodynamic study, the parameters like Gibb's free energy, enthalpy and entropy changes were evaluated. This result explains that the adsorption of Cr(VI) ions onto the UASP was exothermic and spontaneous in nature. Desorption of the biosorbent was done using different desorbing agents in which NaOH gave the best result. The prepared material showed higher affinity for the removal of Cr(VI) ions and this may be an alternative material to the existing commercial adsorbents.

  9. A Prospective Study of the Timing and Accuracy of Neutrophil Gelatinase-Associated Lipocalin Levels in Predicting Acute Kidney Injury in High-Risk Cardiac Surgery Patients.

    Science.gov (United States)

    Fanning, Niall; Galvin, Sinead; Parke, Rachael; Gilroy, James; Bellomo, Rinaldo; McGuinness, Shay

    2016-01-01

    Neutrophil gelatinase-associated lipocalin (NGAL) appears to be a promising biomarker in the effort to predict acute kidney injury (AKI) after cardiac surgery. The authors aimed to identify the specific time point in the perioperative period at which measurement of either urinary or serum concentrations of NGAL would have the highest predictive power for AKI. The authors also investigated whether change in NGAL from baseline was a better predictor of AKI than absolute NGAL values. A prospective, investigator-blinded observational study. The cardiac surgical unit of a university teaching hospital. The study consisted of 50 patients undergoing cardiac surgery who were classified preoperatively as high risk for developing postoperative AKI. No changes to standard practice were required. The authors performed serial measurements of urinary and serum NGAL concentrations at 18 time points throughout the first 48 postoperative hours and assessed the variables required to diagnose AKI with standard criteria. Statistical analysis of predictive ability was performed using the area under receiver operator curves (AUROC) calculated for each time point. It was demonstrated that urinary NGAL performed marginally better than serum NGAL in predicting AKI. Urinary sampling at 4 and 24 hours after initiation of cardiopulmonary bypass provided the greatest diagnostic ability (AUROC, 0.702 and 0.712, respectively). Absolute NGAL values performed better than changes in NGAL values in predicting AKI. Urinary NGAL performed better than serum NGAL in predicting AKI and was most accurate when measured at 24 hours after initiation of cardiopulmonary bypass; however, NGAL appeared to be at best only a fair predictor of cardiac surgery-associated AKI. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Accuracy of 'My Gut Feeling:' Comparing System 1 to System 2 Decision-Making for Acuity Prediction, Disposition and Diagnosis in an Academic Emergency Department.

    Science.gov (United States)

    Cabrera, Daniel; Thomas, Jonathan F; Wiswell, Jeffrey L; Walston, James M; Anderson, Joel R; Hess, Erik P; Bellolio, M Fernanda

    2015-09-01

    Current cognitive sciences describe decision-making using the dual-process theory, where a System 1 is intuitive and a System 2 decision is hypothetico-deductive. We aim to compare the performance of these systems in determining patient acuity, disposition and diagnosis. Prospective observational study of emergency physicians assessing patients in the emergency department of an academic center. Physicians were provided the patient's chief complaint and vital signs and allowed to observe the patient briefly. They were then asked to predict acuity, final disposition (home, intensive care unit (ICU), non-ICU bed) and diagnosis. A patient was classified as sick by the investigators using previously published objective criteria. We obtained 662 observations from 289 patients. For acuity, the observers had a sensitivity of 73.9% (95% CI [67.7-79.5%]), specificity 83.3% (95% CI [79.5-86.7%]), positive predictive value 70.3% (95% CI [64.1-75.9%]) and negative predictive value 85.7% (95% CI [82.0-88.9%]). For final disposition, the observers made a correct prediction in 80.8% (95% CI [76.1-85.0%]) of the cases. For ICU admission, emergency physicians had a sensitivity of 33.9% (95% CI [22.1-47.4%]) and a specificity of 96.9% (95% CI [94.0-98.7%]). The correct diagnosis was made 54% of the time with the limited data available. System 1 decision-making based on limited information had a sensitivity close to 80% for acuity and disposition prediction, but the performance was lower for predicting ICU admission and diagnosis. System 1 decision-making appears insufficient for final decisions in these domains but likely provides a cognitive framework for System 2 decision-making.

  11. Accuracies of fecal calprotectin, lactoferrin, M2-pyruvate kinase, neopterin and zonulin to predict the response to infliximab in ulcerative colitis.

    Science.gov (United States)

    Frin, Anne-Claire; Filippi, Jérôme; Boschetti, Gilles; Flourie, Bernard; Drai, Jocelyne; Ferrari, Patricia; Hebuterne, Xavier; Nancey, Stéphane

    2017-01-01

    Fecal markers might predict the response to anti-TNFα in ulcerative colitis (UC). To compare the performance of fecal calprotectin (fCal), lactoferrin (fLact), M2-PK (fM2-PK), neopterin (fNeo), and zonulin (fZon) to predict the response to therapy in active UC patients. Disease activity from 31 consecutive patients with an active UC, treated with infliximab (IFX) was assessed by the Mayo score at baseline and at week 14 and by the partial Mayo score at W52 and stool samples collected for fecal marker measurements at W0, W2, and W14. At W14, 19 patients (61%) were responders to IFX induction. The median levels of fCal, fLact and fM2-PK drop dramatically from baseline to W14 in clinical responders. At W2, fM2-PK, fLact and fCal levels predicted accurately the response to IFX induction. At W14, fLact, fCal, and fM2-PK were individually reliable markers to predict sustained response at W52. The performances of fNeo and fZon were weaker in this setting. The performance of fM2-PK at W2 to predict response to induction therapy with IFX was superior to that of fLact and fCal, whereas monitoring fLact was the best tool to predict adequately the course of the disease at one year under maintenance IFX in UC. Copyright © 2016. Published by Elsevier Ltd.

  12. Taxometric analyses and predictive accuracy of callous-unemotional traits regarding quality of life and behavior problems in non-conduct disorder diagnoses

    NARCIS (Netherlands)

    Herpers, P.C.M.; Klip, H.; Rommelse, N.N.J.; Taylor, M.J.; Greven, C.U.; Buitelaar, J.K.

    2017-01-01

    Callous-unemotional (CU) traits have mainly been studied in relation to conduct disorder (CD), but can also occur in other disorder groups. However, it is unclear whether there is a clinically relevant cut-off value of levels of CU traits in predicting reduced quality of life (QoL) and clinical

  13. Study of the stiffness for predicting the accuracy of machine tools; Estudio de la rigidez para la prediccion de la precision de las maquinas-herramientas

    Energy Technology Data Exchange (ETDEWEB)

    Ortega, N.; Campa, F.J.; Fernandez Valdivielso, A.; Alonso, U.; Olvera, D.; Compean, F.I.

    2010-07-01

    Machining processes are frequently faced with the challenge of achieving more and more precision and surface qualities. These requirements are usually attained taking into account some process variables, including the cutting parameters and the use or not of refrigerant, leaving aside the mechanical aspects associated with the influence of machine tool itself. There are many sources of error linked with machine-workpiece interaction, but, in general, we can summarize them into two types of error: quasi-static and dynamic. This paper shows the influence of quasi-static error caused by low machine rigidity on the accuracy applied on two very different processes: turning and grinding. For the study of the static stiffness of these two machines, two different methods are proposed, both of them equally valid. The first one is based on separated parameters and the second one on finite elements. (Author).

  14. Impact of obesity on the predictive accuracy of prostate-specific antigen density and prostate-specific antigen in native Korean men