Frontal Theta Links Prediction Errors to Behavioral Adaptation in Reinforcement Learning

PubMed Central

Cavanagh, James F.; Frank, Michael J.; Klein, Theresa J.; Allen, John J.B.

2009-01-01

Investigations into action monitoring have consistently detailed a fronto-central voltage deflection in the Event-Related Potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the Feedback Related Negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Medio-frontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations: with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice. PMID:19969093

Characterization of single-file diffusion in one-dimensional dusty plasma

NASA Astrophysics Data System (ADS)

Theisen, W. L.; Sheridan, T. E.

2010-11-01

Single-file diffusion occurs in one-dimensional systems when particles cannot pass each other and the mean-squared displacement (msd) of these particles increases with time t. Diffusive processes that follow Ficks law predict that the msd increases as t, however, single-file diffusion is sub-Fickean meaning that the msd is predicted to increase as t^1/2. One-dimensional dusty plasma rings have been created under strongly coupled, over-damped conditions. Particle position data from these rings will be analyzed to determine the scaling of the msd with time. Results will be compared with predictions of single-file diffusion theory.

A Novel Prediction Method about Single Components of Analog Circuits Based on Complex Field Modeling

PubMed Central

Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments. PMID:25147853

Development of Single-Seed Near-Infrared Spectroscopic Predictions of Corn and Soybeans Constituents Using Bulk Teference Values and Mean Spectra

USDA-ARS?s Scientific Manuscript database

Near-Infrared reflectance spectroscopic prediction models were developed for common constituents of corn and soybeans using bulk reference values and mean spectra from single-seeds. The bulk reference model and a true single-seed model for soybean protein were compared to determine how well the bul...

Twelve- to 14-Month-Old Infants Can Predict Single-Event Probability with Large Set Sizes

ERIC Educational Resources Information Center

Denison, Stephanie; Xu, Fei

2010-01-01

Previous research has revealed that infants can reason correctly about single-event probabilities with small but not large set sizes (Bonatti, 2008; Teglas "et al.", 2007). The current study asks whether infants can make predictions regarding single-event probability with large set sizes using a novel procedure. Infants completed two trials: A…

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

Initial Comparison of Single Cylinder Stirling Engine Computer Model Predictions with Test Results

NASA Technical Reports Server (NTRS)

Tew, R. C., Jr.; Thieme, L. G.; Miao, D.

1979-01-01

A Stirling engine digital computer model developed at NASA Lewis Research Center was configured to predict the performance of the GPU-3 single-cylinder rhombic drive engine. Revisions to the basic equations and assumptions are discussed. Model predictions with the early results of the Lewis Research Center GPU-3 tests are compared.

Image Discrimination Predictions of a Single Channel Model with Contrast Gain Control

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Null, Cynthia H.

1995-01-01

Image discrimination models predict the number of just-noticeable-differences between two images. We report the predictions of a single channel model with contrast masking for a range of standard discrimination experiments. Despite its computational simplicity, this model has performed as well as a multiple channel model in an object detection task.

Anisotropic constitutive modeling for nickel base single crystal superalloys using a crystallographic approach

NASA Technical Reports Server (NTRS)

Stouffer, D. C.; Sheh, M. Y.

1988-01-01

A micromechanical model based on crystallographic slip theory was formulated for nickel-base single crystal superalloys. The current equations include both drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments have been conducted to evaluate the effect of back stress in single crystals. The results showed that (1) the back stress is orientation dependent; and (2) the back stress state variable in the inelastic flow equation is necessary for predicting anelastic behavior of the material. The model also demonstrated improved fatigue predictive capability. Model predictions and experimental data are presented for single crystal superalloy Rene N4 at 982 C.

Model predictive direct power control for active power decoupled single-phase quasi- Z -source inverter

DOE PAGES

Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham; ...

2016-06-14

In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at eachmore » sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.« less

Model predictive direct power control for active power decoupled single-phase quasi- Z -source inverter

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

Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham

In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at eachmore » sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.« less

NIR spectroscopic measurement of moisture content in Scots pine seeds.

PubMed

Lestander, Torbjörn A; Geladi, Paul

2003-04-01

When tree seeds are used for seedling production it is important that they are of high quality in order to be viable. One of the factors influencing viability is moisture content and an ideal quality control system should be able to measure this factor quickly for each seed. Seed moisture content within the range 3-34% was determined by near-infrared (NIR) spectroscopy on Scots pine (Pinus sylvestris L.) single seeds and on bulk seed samples consisting of 40-50 seeds. The models for predicting water content from the spectra were made by partial least squares (PLS) and ordinary least squares (OLS) regression. Different conditions were simulated involving both using less wavelengths and going from samples to single seeds. Reflectance and transmission measurements were used. Different spectral pretreatment methods were tested on the spectra. Including bias, the lowest prediction errors for PLS models based on reflectance within 780-2280 nm from bulk samples and single seeds were 0.8% and 1.9%, respectively. Reduction of the single seed reflectance spectrum to 850-1048 nm gave higher biases and prediction errors in the test set. In transmission (850-1048 nm) the prediction error was 2.7% for single seeds. OLS models based on simulated 4-sensor single seed system consisting of optical filters with Gaussian transmission indicated more than 3.4% error in prediction. A practical F-test based on test sets to differentiate models is introduced.

Frequency, probability, and prediction: easy solutions to cognitive illusions?

PubMed

Griffin, D; Buehler, R

1999-02-01

Many errors in probabilistic judgment have been attributed to people's inability to think in statistical terms when faced with information about a single case. Prior theoretical analyses and empirical results imply that the errors associated with case-specific reasoning may be reduced when people make frequentistic predictions about a set of cases. In studies of three previously identified cognitive biases, we find that frequency-based predictions are different from-but no better than-case-specific judgments of probability. First, in studies of the "planning fallacy, " we compare the accuracy of aggregate frequency and case-specific probability judgments in predictions of students' real-life projects. When aggregate and single-case predictions are collected from different respondents, there is little difference between the two: Both are overly optimistic and show little predictive validity. However, in within-subject comparisons, the aggregate judgments are significantly more conservative than the single-case predictions, though still optimistically biased. Results from studies of overconfidence in general knowledge and base rate neglect in categorical prediction underline a general conclusion. Frequentistic predictions made for sets of events are no more statistically sophisticated, nor more accurate, than predictions made for individual events using subjective probability. Copyright 1999 Academic Press.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Single Motherhood, Alcohol Dependence, and Smoking During Pregnancy: A Propensity Score Analysis.

PubMed

Waldron, Mary; Bucholz, Kathleen K; Lian, Min; Lessov-Schlaggar, Christina N; Miller, Ruth Huang; Lynskey, Michael T; Knopik, Valerie S; Madden, Pamela A F; Heath, Andrew C

2017-09-01

Few studies linking single motherhood and maternal smoking during pregnancy consider correlated risk from problem substance use beyond history of smoking and concurrent use of alcohol. In the present study, we used propensity score methods to examine whether the risk of smoking during pregnancy associated with single motherhood is the result of potential confounders, including alcohol dependence. Data were drawn from mothers participating in a birth cohort study of their female like-sex twin offspring (n = 257 African ancestry; n = 1,711 European or other ancestry). We conducted standard logistic regression models predicting smoking during pregnancy from single motherhood at twins' birth, followed by propensity score analyses comparing single-mother and two-parent families stratified by predicted probability of single motherhood. In standard models, single motherhood predicted increased risk of smoking during pregnancy in European ancestry but not African ancestry families. In propensity score analyses, rates of smoking during pregnancy were elevated in single-mother relative to two-parent European ancestry families across much of the spectrum a priori risk of single motherhood. Among African ancestry families, within-strata comparisons of smoking during pregnancy by single-mother status were nonsignificant. These findings highlight single motherhood as a unique risk factor for smoking during pregnancy in European ancestry mothers, over and above alcohol dependence. Additional research is needed to identify risks, beyond single motherhood, associated with smoking during pregnancy in African ancestry mothers.

Principal component analysis of binding energies for single-point mutants of hT2R16 bound to an agonist correlate with experimental mutant cell response.

PubMed

Chen, Derek E; Willick, Darryl L; Ruckel, Joseph B; Floriano, Wely B

2015-01-01

Directed evolution is a technique that enables the identification of mutants of a particular protein that carry a desired property by successive rounds of random mutagenesis, screening, and selection. This technique has many applications, including the development of G protein-coupled receptor-based biosensors and designer drugs for personalized medicine. Although effective, directed evolution is not without challenges and can greatly benefit from the development of computational techniques to predict the functional outcome of single-point amino acid substitutions. In this article, we describe a molecular dynamics-based approach to predict the effects of single amino acid substitutions on agonist binding (salicin) to a human bitter taste receptor (hT2R16). An experimentally determined functional map of single-point amino acid substitutions was used to validate the whole-protein molecular dynamics-based predictive functions. Molecular docking was used to construct a wild-type agonist-receptor complex, providing a starting structure for single-point substitution simulations. The effects of each single amino acid substitution in the functional response of the receptor to its agonist were estimated using three binding energy schemes with increasing inclusion of solvation effects. We show that molecular docking combined with molecular mechanics simulations of single-point mutants of the agonist-receptor complex accurately predicts the functional outcome of single amino acid substitutions in a human bitter taste receptor.

Motion compensation via redundant-wavelet multihypothesis.

PubMed

Fowler, James E; Cui, Suxia; Wang, Yonghui

2006-10-01

Multihypothesis motion compensation has been widely used in video coding with previous attention focused on techniques employing predictions that are diverse spatially or temporally. In this paper, the multihypothesis concept is extended into the transform domain by using a redundant wavelet transform to produce multiple predictions that are diverse in transform phase. The corresponding multiple-phase inverse transform implicitly combines the phase-diverse predictions into a single spatial-domain prediction for motion compensation. The performance advantage of this redundant-wavelet-multihypothesis approach is investigated analytically, invoking the fact that the multiple-phase inverse involves a projection that significantly reduces the power of a dense-motion residual modeled as additive noise. The analysis shows that redundant-wavelet multihypothesis is capable of up to a 7-dB reduction in prediction-residual variance over an equivalent single-phase, single-hypothesis approach. Experimental results substantiate the performance advantage for a block-based implementation.

Confirmation of theoretical colour predictions for layering dental composite materials.

PubMed

Mikhail, Sarah S; Johnston, William M

2014-04-01

The aim of this study is to confirm the theoretical colour predictions for single and double layers of dental composite materials on an opaque backing. Single and double layers of composite resins were fabricated, placed in optical contact with a grey backing and measured for spectral radiance. The spectral reflectance and colour were directly determined. Absorption and scattering coefficients as previously reported, the measured thickness of the single layers and the effective reflectance of the grey backing were utilized to theoretically predict the reflectance of the single layer using corrected Kubelka-Munk reflectance theory. For double layers the predicted effective reflectance of the single layer was used as the reflectance of the backing of the second layer and the thickness of the second layer was used to predict the reflectance of the double layer. Colour differences, using both the CIELAB and CIEDE2000 formulae, measured the discrepancy between each directly determined colour and its corresponding theoretical colour. The colour difference discrepancies generally ranged around the perceptibility threshold but were consistently below the respective acceptability threshold. This theory can predict the colour of layers of composite resin within acceptability limits and generally also within perceptibility limits. This theory could therefore be incorporated into computer-based optical measuring instruments that can automate the shade selections for layers of a more opaque first layer under a more translucent second layer for those clinical situations where an underlying background colour and a desirable final colour can be measured. Copyright © 2014 Elsevier Ltd. All rights reserved.

Predicting the language proficiency of Chinese student pilots within American airspace: Single-task versus dual-task English-language assessment

NASA Astrophysics Data System (ADS)

Noble, Clifford Elliott, II

2002-09-01

The problem. The purpose of this study was to investigate the ability of three single-task instruments---(a) the Test of English as a Foreign Language, (b) the Aviation Test of Spoken English, and (c) the Single Manual-Tracking Test---and three dual-task instruments---(a) the Concurrent Manual-Tracking and Communication Test, (b) the Certified Flight Instructor's Test, and (c) the Simulation-Based English Test---to predict the language performance of 10 Chinese student pilots speaking English as a second language when operating single-engine and multiengine aircraft within American airspace. Method. This research implemented a correlational design to investigate the ability of the six described instruments to predict the mean score of the criterion evaluation, which was the Examiner's Test. This test assessed the oral communication skill of student pilots on the flight portion of the terminal checkride in the Piper Cadet, Piper Seminole, and Beechcraft King Air airplanes. Results. Data from the Single Manual-Tracking Test, as well as the Concurrent Manual-Tracking and Communication Test, were discarded due to performance ceiling effects. Hypothesis 1, which stated that the average correlation between the mean scores of the dual-task evaluations and that of the Examiner's Test would predict the mean score of the criterion evaluation with a greater degree of accuracy than that of single-task evaluations, was not supported. Hypothesis 2, which stated that the correlation between the mean scores of the participants on the Simulation-Based English Test and the Examiner's Test would predict the mean score of the criterion evaluation with a greater degree of accuracy than that of all single- and dual-task evaluations, was also not supported. The findings suggest that single- and dual-task assessments administered after initial flight training are equivalent predictors of language performance when piloting single-engine and multiengine aircraft.

Multi-Model Combination techniques for Hydrological Forecasting: Application to Distributed Model Intercomparison Project Results

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

Ajami, N K; Duan, Q; Gao, X

2005-04-11

This paper examines several multi-model combination techniques: the Simple Multi-model Average (SMA), the Multi-Model Super Ensemble (MMSE), Modified Multi-Model Super Ensemble (M3SE) and the Weighted Average Method (WAM). These model combination techniques were evaluated using the results from the Distributed Model Intercomparison Project (DMIP), an international project sponsored by the National Weather Service (NWS) Office of Hydrologic Development (OHD). All of the multi-model combination results were obtained using uncalibrated DMIP model outputs and were compared against the best uncalibrated as well as the best calibrated individual model results. The purpose of this study is to understand how different combination techniquesmore » affect the skill levels of the multi-model predictions. This study revealed that the multi-model predictions obtained from uncalibrated single model predictions are generally better than any single member model predictions, even the best calibrated single model predictions. Furthermore, more sophisticated multi-model combination techniques that incorporated bias correction steps work better than simple multi-model average predictions or multi-model predictions without bias correction.« less

Limited Sampling Strategy for the Prediction of Area Under the Curve (AUC) of Statins: Reliability of a Single Time Point for AUC Prediction for Pravastatin and Simvastatin.

PubMed

Srinivas, N R

2016-02-01

Statins are widely prescribed medicines and are also available in fixed dose combinations with other drugs to treat several chronic ailments. Given the safety issues associated with statins it may be important to assess feasibility of a single time concentration strategy for prediction of exposure (area under the curve; AUC). The peak concentration (Cmax) was used to establish relationship with AUC separately for pravastatin and simvastatin using published pharmacokinetic data. The regression equations generated for statins were used to predict the AUC values from various literature references. The fold difference of the observed divided by predicted values along with correlation coefficient (r) were used to judge the feasibility of the single time point approach. Both pravastatin and simvastatin showed excellent correlation of Cmax vs. AUC values with r value ≥ 0.9638 (p<0.001). The fold difference was within 0.5-fold to 2-fold for 220 out of 227 AUC predictions and >81% of the predicted values were in a narrower range of >0.75-fold but <1.5-fold difference. Predicted vs. observed AUC values showed excellent correlation for pravastatin (r=0.9708, n=115; p<0.001) and simvastatin (r=0.9810; n=117; p<0.001) suggesting the utility of Cmax for AUC predictions. On the basis of the present work, it is feasible to develop a single concentration time point strategy that coincides with Cmax occurrence for both pravastatin and simvastatin from a therapeutic drug monitoring perspective. © Georg Thieme Verlag KG Stuttgart · New York.

Using single leg standing time to predict the fall risk in elderly.

PubMed

Chang, Chun-Ju; Chang, Yu-Shin; Yang, Sai-Wei

2013-01-01

In clinical evaluation, we used to evaluate the fall risk according to elderly falling experience or the balance assessment tool. Because of the tool limitation, sometimes we could not predict accurately. In this study, we first analyzed 15 healthy elderly (without falling experience) and 15 falling elderly (1~3 time falling experience) balance performance in previous research. After 1 year follow up, there was only 1 elderly fall down during this period. It seemed like that falling experience had a ceiling effect on the falling prediction. But we also found out that using single leg standing time could be more accurately to help predicting the fall risk, especially for the falling elderly who could not stand over 10 seconds by single leg, and with a significant correlation between the falling experience and single leg standing time (r = -0.474, p = 0.026). The results also showed that there was significant body sway just before they falling down, and the COP may be an important characteristic in the falling elderly group.

Incremental Value of Repeated Risk Factor Measurements for Cardiovascular Disease Prediction in Middle-Aged Korean Adults: Results From the NHIS-HEALS (National Health Insurance System-National Health Screening Cohort).

PubMed

Cho, In-Jeong; Sung, Ji Min; Chang, Hyuk-Jae; Chung, Namsik; Kim, Hyeon Chang

2017-11-01

Increasing evidence suggests that repeatedly measured cardiovascular disease (CVD) risk factors may have an additive predictive value compared with single measured levels. Thus, we evaluated the incremental predictive value of incorporating periodic health screening data for CVD prediction in a large nationwide cohort with periodic health screening tests. A total of 467 708 persons aged 40 to 79 years and free from CVD were randomly divided into development (70%) and validation subcohorts (30%). We developed 3 different CVD prediction models: a single measure model using single time point screening data; a longitudinal average model using average risk factor values from periodic screening data; and a longitudinal summary model using average values and the variability of risk factors. The development subcohort included 327 396 persons who had 3.2 health screenings on average and 25 765 cases of CVD over 12 years. The C statistics (95% confidence interval [CI]) for the single measure, longitudinal average, and longitudinal summary models were 0.690 (95% CI, 0.682-0.698), 0.695 (95% CI, 0.687-0.703), and 0.752 (95% CI, 0.744-0.760) in men and 0.732 (95% CI, 0.722-0.742), 0.735 (95% CI, 0.725-0.745), and 0.790 (95% CI, 0.780-0.800) in women, respectively. The net reclassification index from the single measure model to the longitudinal average model was 1.78% in men and 1.33% in women, and the index from the longitudinal average model to the longitudinal summary model was 32.71% in men and 34.98% in women. Using averages of repeatedly measured risk factor values modestly improves CVD predictability compared with single measurement values. Incorporating the average and variability information of repeated measurements can lead to great improvements in disease prediction. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02931500. © 2017 American Heart Association, Inc.

Prediction of Drug-Drug Interactions with Crizotinib as the CYP3A Substrate Using a Physiologically Based Pharmacokinetic Model.

PubMed

Yamazaki, Shinji; Johnson, Theodore R; Smith, Bill J

2015-10-01

An orally available multiple tyrosine kinase inhibitor, crizotinib (Xalkori), is a CYP3A substrate, moderate time-dependent inhibitor, and weak inducer. The main objectives of the present study were to: 1) develop and refine a physiologically based pharmacokinetic (PBPK) model of crizotinib on the basis of clinical single- and multiple-dose results, 2) verify the crizotinib PBPK model from crizotinib single-dose drug-drug interaction (DDI) results with multiple-dose coadministration of ketoconazole or rifampin, and 3) apply the crizotinib PBPK model to predict crizotinib multiple-dose DDI outcomes. We also focused on gaining insights into the underlying mechanisms mediating crizotinib DDIs using a dynamic PBPK model, the Simcyp population-based simulator. First, PBPK model-predicted crizotinib exposures adequately matched clinically observed results in the single- and multiple-dose studies. Second, the model-predicted crizotinib exposures sufficiently matched clinically observed results in the crizotinib single-dose DDI studies with ketoconazole or rifampin, resulting in the reasonably predicted fold-increases in crizotinib exposures. Finally, the predicted fold-increases in crizotinib exposures in the multiple-dose DDI studies were roughly comparable to those in the single-dose DDI studies, suggesting that the effects of crizotinib CYP3A time-dependent inhibition (net inhibition) on the multiple-dose DDI outcomes would be negligible. Therefore, crizotinib dose-adjustment in the multiple-dose DDI studies could be made on the basis of currently available single-dose results. Overall, we believe that the crizotinib PBPK model developed, refined, and verified in the present study would adequately predict crizotinib oral exposures in other clinical studies, such as DDIs with weak/moderate CYP3A inhibitors/inducers and drug-disease interactions in patients with hepatic or renal impairment. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Electrostatic placement of single ferritin molecules

NASA Astrophysics Data System (ADS)

Kumagai, Shinya; Yoshii, Shigeo; Yamada, Kiyohito; Matsukawa, Nozomu; Fujiwara, Isamu; Iwahori, Kenji; Yamashita, Ichiro

2006-04-01

We electrostatically placed a single ferritin molecule on a nanometric 3-aminopropyltriethoxysilane (APTES) pattern that was on an oxidized Si substrate. The numerical analysis of the total interaction free energy for ferritin predicted that a quadrilateral array of 15nm diameter APTES nanodisks placed at intervals of 100nm would accommodate a single molecule of ferritin in each disk under a Debye length of 14nm. The experiments we conducted conformed to theoretical predictions and we successfully placed a single ferritin molecule on each ATPES disk without ferritin adsorbing on the SiO2 substrate surface.

Assessing Model Characterization of Single Source Secondary Pollutant Impacts Using 2013 SENEX Field Study Measurements

EPA Science Inventory

Aircraft measurements made downwind from specific coal fired power plants during the 2013 Southeast Nexus field campaign provide a unique opportunity to evaluate single source photochemical model predictions of both O3 and secondary PM2.5 species. The model did well at predicting...

Moisture effects on the prediction performance of a single kernel near-infrared deoxynivalenol calibration

USDA-ARS?s Scientific Manuscript database

Effect of moisture content variation on the accuracy of single kernel deoxynivalenol (DON) prediction by near-infrared (NIR) spectroscopy was investigated. Sample moisture content (MC) considerably affected accuracy of the current NIR DON calibration by underestimating or over estimating DON at high...

Gaussian mixture models as flux prediction method for central receivers

NASA Astrophysics Data System (ADS)

Grobler, Annemarie; Gauché, Paul; Smit, Willie

2016-05-01

Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.

Foundations for computer simulation of a low pressure oil flooded single screw air compressor

NASA Astrophysics Data System (ADS)

Bein, T. W.

1981-12-01

The necessary logic to construct a computer model to predict the performance of an oil flooded, single screw air compressor is developed. The geometric variables and relationships used to describe the general single screw mechanism are developed. The governing equations to describe the processes are developed from their primary relationships. The assumptions used in the development are also defined and justified. The computer model predicts the internal pressure, temperature, and flowrates through the leakage paths throughout the compression cycle of the single screw compressor. The model uses empirical external values as the basis for the internal predictions. The computer values are compared to the empirical values, and conclusions are drawn based on the results. Recommendations are made for future efforts to improve the computer model and to verify some of the conclusions that are drawn.

Concentration Addition, Independent Action and Generalized Concentration Addition Models for Mixture Effect Prediction of Sex Hormone Synthesis In Vitro

PubMed Central

Hadrup, Niels; Taxvig, Camilla; Pedersen, Mikael; Nellemann, Christine; Hass, Ulla; Vinggaard, Anne Marie

2013-01-01

Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals. PMID:23990906

Enhancing emotional-based target prediction

NASA Astrophysics Data System (ADS)

Gosnell, Michael; Woodley, Robert

2008-04-01

This work extends existing agent-based target movement prediction to include key ideas of behavioral inertia, steady states, and catastrophic change from existing psychological, sociological, and mathematical work. Existing target prediction work inherently assumes a single steady state for target behavior, and attempts to classify behavior based on a single emotional state set. The enhanced, emotional-based target prediction maintains up to three distinct steady states, or typical behaviors, based on a target's operating conditions and observed behaviors. Each steady state has an associated behavioral inertia, similar to the standard deviation of behaviors within that state. The enhanced prediction framework also allows steady state transitions through catastrophic change and individual steady states could be used in an offline analysis with additional modeling efforts to better predict anticipated target reactions.

Wet-chemical fabrication of a single leakage-channel grating coupler

NASA Astrophysics Data System (ADS)

Weisenbach, Lori; Zelinski, Brian J. J.; Roncone, Ronald L.; Burke, James J.

1995-04-01

We demonstrate the fabrication of a unique optical device, the single leakage-channel grating coupler, using sol-gel techniques. Design specifications are outlined to establish the material criteria for the sol-gel compositions. Material choice and preparation are described. We evaluate the characteristics and performance of the single leakage-channel grating coupler by comparing the predicted and the measured branching ratios. The branching ratio of the solution-derived device is within 3% of the theoretically predicted value.

Time-resolved scattering of a single photon by a single atom

PubMed Central

Leong, Victor; Seidler, Mathias Alexander; Steiner, Matthias; Cerè, Alessandro; Kurtsiefer, Christian

2016-01-01

Scattering of light by matter has been studied extensively in the past. Yet, the most fundamental process, the scattering of a single photon by a single atom, is largely unexplored. One prominent prediction of quantum optics is the deterministic absorption of a travelling photon by a single atom, provided the photon waveform matches spatially and temporally the time-reversed version of a spontaneously emitted photon. Here we experimentally address this prediction and investigate the influence of the photon's temporal profile on the scattering dynamics using a single trapped atom and heralded single photons. In a time-resolved measurement of atomic excitation we find a 56(11)% increase of the peak excitation by photons with an exponentially rising profile compared with a decaying one. However, the overall scattering probability remains unchanged within the experimental uncertainties. Our results demonstrate that envelope tailoring of single photons enables precise control of the photon–atom interaction. PMID:27897173

Genomic predictability of single-step GBLUP for production traits in US Holstein

USDA-ARS?s Scientific Manuscript database

The objective of this study was to validate genomic predictability of single-step genomic BLUP for 305-day protein yield for US Holsteins. The genomic relationship matrix was created with the Algorithm of Proven and Young (APY) with 18,359 core animals. The full data set consisted of phenotypes coll...

Application of First Principles Model to Spacecraft Operations

NASA Technical Reports Server (NTRS)

Timmerman, Paul; Bugga, Ratnakumar; DiStefano, Salvidor

1996-01-01

Previous models use a single phase reaction; cycled cell predicts cannot be met with a single phase; interphase conversion provides means for film aging; aging cells predictions display typical behaviors: pressure changes in NiH² cells; voltage fading upon cycling; second plateau on discharge of cycled cells; negative limited behavior for Ni-Cds.

Interspecies scaling and prediction of human clearance: comparison of small- and macro-molecule drugs

PubMed Central

Huh, Yeamin; Smith, David E.; Feng, Meihau Rose

2014-01-01

Human clearance prediction for small- and macro-molecule drugs was evaluated and compared using various scaling methods and statistical analysis.Human clearance is generally well predicted using single or multiple species simple allometry for macro- and small-molecule drugs excreted renally.The prediction error is higher for hepatically eliminated small-molecules using single or multiple species simple allometry scaling, and it appears that the prediction error is mainly associated with drugs with low hepatic extraction ratio (Eh). The error in human clearance prediction for hepatically eliminated small-molecules was reduced using scaling methods with a correction of maximum life span (MLP) or brain weight (BRW).Human clearance of both small- and macro-molecule drugs is well predicted using the monkey liver blood flow method. Predictions using liver blood flow from other species did not work as well, especially for the small-molecule drugs. PMID:21892879

Criteria for predicting the formation of single-phase high-entropy alloys

DOE PAGES

Troparevsky, M Claudia; Morris, James R..; Kent, Paul R.; ...

2015-03-15

High entropy alloys constitute a new class of materials whose very existence poses fundamental questions. Originally thought to be stabilized by the large entropy of mixing, these alloys have attracted attention due to their potential applications, yet no model capable of robustly predicting which combinations of elements will form a single-phase currently exists. Here we propose a model that, through the use of high-throughput computation of the enthalpies of formation of binary compounds, is able to confirm all known high-entropy alloys while rejecting similar alloys that are known to form multiple phases. Despite the increasing entropy, our model predicts thatmore » the number of potential single-phase multicomponent alloys decreases with an increasing number of components: out of more than two million possible 7-component alloys considered, fewer than twenty single-phase alloys are likely.« less

Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls

PubMed Central

Arbabshirani, Mohammad R.; Plis, Sergey; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there are extensive evidences showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. PMID:27012503

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

PubMed

Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing; Calhoun, Vince D

2017-01-15

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information.

PubMed

Song, Jiangning; Burrage, Kevin; Yuan, Zheng; Huber, Thomas

2006-03-09

The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively. A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.

Multi-step rhodopsin inactivation schemes can account for the size variability of single photon responses in Limulus ventral photoreceptors

PubMed Central

1994-01-01

Limulus ventral photoreceptors generate highly variable responses to the absorption of single photons. We have obtained data on the size distribution of these responses, derived the distribution predicted from simple transduction cascade models and compared the theory and data. In the simplest of models, the active state of the visual pigment (defined by its ability to activate G protein) is turned off in a single reaction. The output of such a cascade is predicted to be highly variable, largely because of stochastic variation in the number of G proteins activated. The exact distribution predicted is exponential, but we find that an exponential does not adequately account for the data. The data agree much better with the predictions of a cascade model in which the active state of the visual pigment is turned off by a multi-step process. PMID:8057085

Local Burn-Up Effects in the NBSR Fuel Element

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

Brown N. R.; Hanson A.; Diamond, D.

2013-01-31

This study addresses the over-prediction of local power when the burn-up distribution in each half-element of the NBSR is assumed to be uniform. A single-element model was utilized to quantify the impact of axial and plate-wise burn-up on the power distribution within the NBSR fuel elements for both high-enriched uranium (HEU) and low-enriched uranium (LEU) fuel. To validate this approach, key parameters in the single-element model were compared to parameters from an equilibrium core model, including neutron energy spectrum, power distribution, and integral U-235 vector. The power distribution changes significantly when incorporating local burn-up effects and has lower power peakingmore » relative to the uniform burn-up case. In the uniform burn-up case, the axial relative power peaking is over-predicted by as much as 59% in the HEU single-element and 46% in the LEU single-element with uniform burn-up. In the uniform burn-up case, the plate-wise power peaking is over-predicted by as much as 23% in the HEU single-element and 18% in the LEU single-element. The degree of over-prediction increases as a function of burn-up cycle, with the greatest over-prediction at the end of Cycle 8. The thermal flux peak is always in the mid-plane gap; this causes the local cumulative burn-up near the mid-plane gap to be significantly higher than the fuel element average. Uniform burn-up distribution throughout a half-element also causes a bias in fuel element reactivity worth, due primarily to the neutronic importance of the fissile inventory in the mid-plane gap region.« less

Predictive Model for the Meniscus-Guided Coating of High-Quality Organic Single-Crystalline Thin Films.

PubMed

Janneck, Robby; Vercesi, Federico; Heremans, Paul; Genoe, Jan; Rolin, Cedric

2016-09-01

A model that describes solvent evaporation dynamics in meniscus-guided coating techniques is developed. In combination with a single fitting parameter, it is shown that this formula can accurately predict a processing window for various coating conditions. Organic thin-film transistors (OTFTs), fabricated by a zone-casting setup, indeed show the best performance at the predicted coating speeds with mobilities reaching 7 cm 2 V -1 s -1 . © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Translating landfill methane generation parameters among first-order decay models.

PubMed

Krause, Max J; Chickering, Giles W; Townsend, Timothy G

2016-11-01

Landfill gas (LFG) generation is predicted by a first-order decay (FOD) equation that incorporates two parameters: a methane generation potential (L 0 ) and a methane generation rate (k). Because non-hazardous waste landfills may accept many types of waste streams, multiphase models have been developed in an attempt to more accurately predict methane generation from heterogeneous waste streams. The ability of a single-phase FOD model to predict methane generation using weighted-average methane generation parameters and tonnages translated from multiphase models was assessed in two exercises. In the first exercise, waste composition from four Danish landfills represented by low-biodegradable waste streams was modeled in the Afvalzorg Multiphase Model and methane generation was compared to the single-phase Intergovernmental Panel on Climate Change (IPCC) Waste Model and LandGEM. In the second exercise, waste composition represented by IPCC waste components was modeled in the multiphase IPCC and compared to single-phase LandGEM and Australia's Solid Waste Calculator (SWC). In both cases, weight-averaging of methane generation parameters from waste composition data in single-phase models was effective in predicting cumulative methane generation from -7% to +6% of the multiphase models. The results underscore the understanding that multiphase models will not necessarily improve LFG generation prediction because the uncertainty of the method rests largely within the input parameters. A unique method of calculating the methane generation rate constant by mass of anaerobically degradable carbon was presented (k c ) and compared to existing methods, providing a better fit in 3 of 8 scenarios. Generally, single phase models with weighted-average inputs can accurately predict methane generation from multiple waste streams with varied characteristics; weighted averages should therefore be used instead of regional default values when comparing models. Translating multiphase first-order decay model input parameters by weighted average shows that single-phase models can predict cumulative methane generation within the level of uncertainty of many of the input parameters as defined by the Intergovernmental Panel on Climate Change (IPCC), which indicates that decreasing the uncertainty of the input parameters will make the model more accurate rather than adding multiple phases or input parameters.

Protein (multi-)location prediction: using location inter-dependencies in a probabilistic framework

PubMed Central

2014-01-01

Motivation Knowing the location of a protein within the cell is important for understanding its function, role in biological processes, and potential use as a drug target. Much progress has been made in developing computational methods that predict single locations for proteins. Most such methods are based on the over-simplifying assumption that proteins localize to a single location. However, it has been shown that proteins localize to multiple locations. While a few recent systems attempt to predict multiple locations of proteins, their performance leaves much room for improvement. Moreover, they typically treat locations as independent and do not attempt to utilize possible inter-dependencies among locations. Our hypothesis is that directly incorporating inter-dependencies among locations into both the classifier-learning and the prediction process can improve location prediction performance. Results We present a new method and a preliminary system we have developed that directly incorporates inter-dependencies among locations into the location-prediction process of multiply-localized proteins. Our method is based on a collection of Bayesian network classifiers, where each classifier is used to predict a single location. Learning the structure of each Bayesian network classifier takes into account inter-dependencies among locations, and the prediction process uses estimates involving multiple locations. We evaluate our system on a dataset of single- and multi-localized proteins (the most comprehensive protein multi-localization dataset currently available, derived from the DBMLoc dataset). Our results, obtained by incorporating inter-dependencies, are significantly higher than those obtained by classifiers that do not use inter-dependencies. The performance of our system on multi-localized proteins is comparable to a top performing system (YLoc+), without being restricted only to location-combinations present in the training set. PMID:24646119

Protein (multi-)location prediction: using location inter-dependencies in a probabilistic framework.

PubMed

Simha, Ramanuja; Shatkay, Hagit

2014-03-19

Knowing the location of a protein within the cell is important for understanding its function, role in biological processes, and potential use as a drug target. Much progress has been made in developing computational methods that predict single locations for proteins. Most such methods are based on the over-simplifying assumption that proteins localize to a single location. However, it has been shown that proteins localize to multiple locations. While a few recent systems attempt to predict multiple locations of proteins, their performance leaves much room for improvement. Moreover, they typically treat locations as independent and do not attempt to utilize possible inter-dependencies among locations. Our hypothesis is that directly incorporating inter-dependencies among locations into both the classifier-learning and the prediction process can improve location prediction performance. We present a new method and a preliminary system we have developed that directly incorporates inter-dependencies among locations into the location-prediction process of multiply-localized proteins. Our method is based on a collection of Bayesian network classifiers, where each classifier is used to predict a single location. Learning the structure of each Bayesian network classifier takes into account inter-dependencies among locations, and the prediction process uses estimates involving multiple locations. We evaluate our system on a dataset of single- and multi-localized proteins (the most comprehensive protein multi-localization dataset currently available, derived from the DBMLoc dataset). Our results, obtained by incorporating inter-dependencies, are significantly higher than those obtained by classifiers that do not use inter-dependencies. The performance of our system on multi-localized proteins is comparable to a top performing system (YLoc+), without being restricted only to location-combinations present in the training set.

Dissimilarity based Partial Least Squares (DPLS) for genomic prediction from SNPs.

PubMed

Singh, Priyanka; Engel, Jasper; Jansen, Jeroen; de Haan, Jorn; Buydens, Lutgarde Maria Celina

2016-05-04

Genomic prediction (GP) allows breeders to select plants and animals based on their breeding potential for desirable traits, without lengthy and expensive field trials or progeny testing. We have proposed to use Dissimilarity-based Partial Least Squares (DPLS) for GP. As a case study, we use the DPLS approach to predict Bacterial wilt (BW) in tomatoes using SNPs as predictors. The DPLS approach was compared with the Genomic Best-Linear Unbiased Prediction (GBLUP) and single-SNP regression with SNP as a fixed effect to assess the performance of DPLS. Eight genomic distance measures were used to quantify relationships between the tomato accessions from the SNPs. Subsequently, each of these distance measures was used to predict the BW using the DPLS prediction model. The DPLS model was found to be robust to the choice of distance measures; similar prediction performances were obtained for each distance measure. DPLS greatly outperformed the single-SNP regression approach, showing that BW is a comprehensive trait dependent on several loci. Next, the performance of the DPLS model was compared to that of GBLUP. Although GBLUP and DPLS are conceptually very different, the prediction quality (PQ) measured by DPLS models were similar to the prediction statistics obtained from GBLUP. A considerable advantage of DPLS is that the genotype-phenotype relationship can easily be visualized in a 2-D scatter plot. This so-called score-plot provides breeders an insight to select candidates for their future breeding program. DPLS is a highly appropriate method for GP. The model prediction performance was similar to the GBLUP and far better than the single-SNP approach. The proposed method can be used in combination with a wide range of genomic dissimilarity measures and genotype representations such as allele-count, haplotypes or allele-intensity values. Additionally, the data can be insightfully visualized by the DPLS model, allowing for selection of desirable candidates from the breeding experiments. In this study, we have assessed the DPLS performance on a single trait.

Sorting protein decoys by machine-learning-to-rank

PubMed Central

Jing, Xiaoyang; Wang, Kai; Lu, Ruqian; Dong, Qiwen

2016-01-01

Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset. PMID:27530967

Sorting protein decoys by machine-learning-to-rank.

PubMed

Jing, Xiaoyang; Wang, Kai; Lu, Ruqian; Dong, Qiwen

2016-08-17

Much progress has been made in Protein structure prediction during the last few decades. As the predicted models can span a broad range of accuracy spectrum, the accuracy of quality estimation becomes one of the key elements of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, and these methods could be roughly divided into three categories: the single-model methods, clustering-based methods and quasi single-model methods. In this study, we develop a single-model method MQAPRank based on the learning-to-rank algorithm firstly, and then implement a quasi single-model method Quasi-MQAPRank. The proposed methods are benchmarked on the 3DRobot and CASP11 dataset. The five-fold cross-validation on the 3DRobot dataset shows the proposed single model method outperforms other methods whose outputs are taken as features of the proposed method, and the quasi single-model method can further enhance the performance. On the CASP11 dataset, the proposed methods also perform well compared with other leading methods in corresponding categories. In particular, the Quasi-MQAPRank method achieves a considerable performance on the CASP11 Best150 dataset.

Single Nucleotide Polymorphisms Predict Symptom Severity of Autism Spectrum Disorder

ERIC Educational Resources Information Center

Jiao, Yun; Chen, Rong; Ke, Xiaoyan; Cheng, Lu; Chu, Kangkang; Lu, Zuhong; Herskovits, Edward H.

2012-01-01

Autism is widely believed to be a heterogeneous disorder; diagnosis is currently based solely on clinical criteria, although genetic, as well as environmental, influences are thought to be prominent factors in the etiology of most forms of autism. Our goal is to determine whether a predictive model based on single-nucleotide polymorphisms (SNPs)…

Screening and Predicting Posttraumatic Stress and Depression in Children Following Single-Incident Trauma

ERIC Educational Resources Information Center

Nixon, Reginald D. V.; Ellis, Alicia A.; Nehmy, Thomas J.; Ball, Shelley-Anne

2010-01-01

Three screening methods to predict posttraumatic stress disorder (PTSD) and depression symptoms in children following single-incident trauma were tested. Children and adolescents (N = 90; aged 7-17 years) were assessed within 4 weeks of an injury that led to hospital treatment and followed up 3 and 6 months later. Screening methods were adapted…

The Relation between Executive Functioning, Reaction Time, Naming Speed, and Single Word Reading in Children with Typical Development and Language Impairments

ERIC Educational Resources Information Center

Messer, David; Henry, Lucy A.; Nash, Gilly

2016-01-01

Background: Few investigations have examined the relationship between a comprehensive range of executive functioning (EF) abilities and reading. Aims: Our investigation identified components of EF that independently predicted single word reading, and determined whether their predictive role remained when additional variables were included in the…

Predictive value of serum HCG concentrations in pregnancies achieved after single fresh or vitrified-warmed blastocyst transfer.

PubMed

Oron, Galia; Shavit, Tal; Esh-Broder, Efrat; Weon-Young, Son; Tulandi, Togas; Holzer, Hananel

2017-09-01

Possible differences between serum HCG levels in pregnancies achieved after transfer of a single fresh or a vitrified-warmed blastocyst were evaluated. Out of 1130 single blastocyst transfers resulting in positive HCG results, 789 were single fresh blastocyst transfers and 341 single vitrified-warmed blastocyst transfers. The initial serum HCG levels of 869 clinical intrauterine pregnancies were evaluated, 638 after the transfer of a single fresh blastocysts and 231 after the transfer of a single vitrified-warmed blastocysts. The HCG levels from cycles resulting in a clinical intrauterine pregnancy were significantly higher after the transfer of a single vitrified-warmed blastocyst (383 ± 230 IU/l) versus a fresh transfer (334 ± 192 IU/l; P = 0.01). Threshold values for predicting a clinical pregnancy for a fresh blastocyst were 111 IU/l and for a vitrified-warmed blastocyst 137 IU/l. Our study shows that the overall beta-HCG levels are comparable after the transfer of a fresh or vitrified-warmed blastocyst, suggesting that vitrification most probably does not affect the ability of the embryos to produce beta-HCG. This study further shows that when clinicians counsel patients, they should take into account that higher HCG levels are needed after a vitrified-warmed blastocyst transfer to predict a clinical intrauterine pregnancy. Copyright © 2017 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

The value of integrating pre-clinical data to predict nausea and vomiting risk in humans as illustrated by AZD3514, a novel androgen receptor modulator

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

Grant, Claire, E-mail: claire.grant@astrazeneca.com; Ewart, Lorna; Muthas, Daniel

Nausea and vomiting are components of a complex mechanism that signals food avoidance and protection of the body against the absorption of ingested toxins. This response can also be triggered by pharmaceuticals. Predicting clinical nausea and vomiting liability for pharmaceutical agents based on pre-clinical data can be problematic as no single animal model is a universal predictor. Moreover, efforts to improve models are hampered by the lack of translational animal and human data in the public domain. AZD3514 is a novel, orally-administered compound that inhibits androgen receptor signaling and down-regulates androgen receptor expression. Here we have explored the utility ofmore » integrating data from several pre-clinical models to predict nausea and vomiting in the clinic. Single and repeat doses of AZD3514 resulted in emesis, salivation and gastrointestinal disturbances in the dog, and inhibited gastric emptying in rats after a single dose. AZD3514, at clinically relevant exposures, induced dose-responsive “pica” behaviour in rats after single and multiple daily doses, and induced retching and vomiting behaviour in ferrets after a single dose. We compare these data with the clinical manifestation of nausea and vomiting encountered in patients with castration-resistant prostate cancer receiving AZD3514. Our data reveal a striking relationship between the pre-clinical observations described and the experience of nausea and vomiting in the clinic. In conclusion, the emetic nature of AZD3514 was predicted across a range of pre-clinical models, and the approach presented provides a valuable framework for predicition of clinical nausea and vomiting. - Highlights: • Integrated pre-clinical data can be used to predict clinical nausea and vomiting. • Data integrated from standard toxicology studies is sufficient to make a prediction. • The use of the nausea algorithm developed by Parkinson (2012) aids the prediction. • Additional pre-clinical studies can be used to confirm and quantify the risk.« less

[Value of sepsis single-disease manage system in predicting mortality in patients with sepsis].

PubMed

Chen, J; Wang, L H; Ouyang, B; Chen, M Y; Wu, J F; Liu, Y J; Liu, Z M; Guan, X D

2018-04-03

Objective: To observe the effect of sepsis single-disease manage system on the improvement of sepsis treatment and the value in predicting mortality in patients with sepsis. Methods: A retrospective study was conducted. Patients with sepsis admitted to the Department of Surgical Intensive Care Unit of Sun Yat-Sen University First Affiliated Hospital from September 22, 2013 to May 5, 2015 were enrolled in this study. Sepsis single-disease manage system (Rui Xin clinical data manage system, China data, China) was used to monitor 25 clinical quality parameters, consisting of timeliness, normalization and outcome parameters. Based on whether these quality parameters could be completed or not, the clinical practice was evaluated by the system. The unachieved quality parameter was defined as suspicious parameters, and these suspicious parameters were used to predict mortality of patients with receiver operating characteristic curve (ROC). Results: A total of 1 220 patients with sepsis were enrolled, included 805 males and 415 females. The mean age was (59±17) years, and acute physiology and chronic health evaluation (APACHE Ⅱ) scores was 19±8. The area under ROC curve of total suspicious numbers for predicting 28-day mortality was 0.70; when the suspicious parameters number was more than 6, the sensitivity was 68.0% and the specificity was 61.0% for predicting 28-day mortality. In addition, the area under ROC curve of outcome suspicious number for predicting 28-day mortality was 0.89; when the suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 78.0% for predicting 28-day mortality. Moreover, the area under ROC curve of total suspicious number for predicting 90-day mortality was 0.73; when the total suspicious parameters number was more than 7, the sensitivity was 60.0% and the specificity was 74.0% for predicting 90-day mortality. Finally, the area under ROC curve of outcome suspicious numbers for predicting 90-day mortality was 0.92; when suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 81.0% for predicting 90-day mortality. Conclusion: The single center study suggests that this sepsis single-disease manage system could be used to monitor the completion of clinical practice for intensivist in managing sepsis, and the number of quality parameters failed to complete could be used to predict the mortality of the patients.

MobiDB-lite: fast and highly specific consensus prediction of intrinsic disorder in proteins.

PubMed

Necci, Marco; Piovesan, Damiano; Dosztányi, Zsuzsanna; Tosatto, Silvio C E

2017-05-01

Intrinsic disorder (ID) is established as an important feature of protein sequences. Its use in proteome annotation is however hampered by the availability of many methods with similar performance at the single residue level, which have mostly not been optimized to predict long ID regions of size comparable to domains. Here, we have focused on providing a single consensus-based prediction, MobiDB-lite, optimized for highly specific (i.e. few false positive) predictions of long disorder. The method uses eight different predictors to derive a consensus which is then filtered for spurious short predictions. Consensus prediction is shown to outperform the single methods when annotating long ID regions. MobiDB-lite can be useful in large-scale annotation scenarios and has indeed already been integrated in the MobiDB, DisProt and InterPro databases. MobiDB-lite is available as part of the MobiDB database from URL: http://mobidb.bio.unipd.it/. An executable can be downloaded from URL: http://protein.bio.unipd.it/mobidblite/. silvio.tosatto@unipd.it. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Short Term Rain Prediction For Sustainability of Tanks in the Tropic Influenced by Shadow Rains

NASA Astrophysics Data System (ADS)

Suresh, S.

2007-07-01

Rainfall and flow prediction, adapting the Venkataraman single time series approach and Wiener multiple time series approach were conducted for Aralikottai tank system, and Kothamangalam tank system, Tamilnadu, India. The results indicated that the raw prediction of daily values is closer to actual values than trend identified predictions. The sister seasonal time series were more amenable for prediction than whole parent time series. Venkataraman single time approach was more suited for rainfall prediction. Wiener approach proved better for daily prediction of flow based on rainfall. The major conclusion is that the sister seasonal time series of rain and flow have their own identities even though they form part of the whole parent time series. Further studies with other tropical small watersheds are necessary to establish this unique characteristic of independent but not exclusive behavior of seasonal stationary stochastic processes as compared to parent non stationary stochastic processes.

Mean Expected Error in Prediction of Total Body Water: A True Accuracy Comparison between Bioimpedance Spectroscopy and Single Frequency Regression Equations

PubMed Central

Abtahi, Shirin; Abtahi, Farhad; Ellegård, Lars; Johannsson, Gudmundur; Bosaeus, Ingvar

2015-01-01

For several decades electrical bioimpedance (EBI) has been used to assess body fluid distribution and body composition. Despite the development of several different approaches for assessing total body water (TBW), it remains uncertain whether bioimpedance spectroscopic (BIS) approaches are more accurate than single frequency regression equations. The main objective of this study was to answer this question by calculating the expected accuracy of a single measurement for different EBI methods. The results of this study showed that all methods produced similarly high correlation and concordance coefficients, indicating good accuracy as a method. Even the limits of agreement produced from the Bland-Altman analysis indicated that the performance of single frequency, Sun's prediction equations, at population level was close to the performance of both BIS methods; however, when comparing the Mean Absolute Percentage Error value between the single frequency prediction equations and the BIS methods, a significant difference was obtained, indicating slightly better accuracy for the BIS methods. Despite the higher accuracy of BIS methods over 50 kHz prediction equations at both population and individual level, the magnitude of the improvement was small. Such slight improvement in accuracy of BIS methods is suggested insufficient to warrant their clinical use where the most accurate predictions of TBW are required, for example, when assessing over-fluidic status on dialysis. To reach expected errors below 4-5%, novel and individualized approaches must be developed to improve the accuracy of bioimpedance-based methods for the advent of innovative personalized health monitoring applications. PMID:26137489

Single-Event Effects Ground Testing and On-Orbit Rate Prediction Methods: The Past, Present and Future

NASA Technical Reports Server (NTRS)

Reed, Robert A.; Kinnison, Jim; Pickel, Jim; Buchner, Stephen; Marshall, Paul W.; Kniffin, Scott; LaBel, Kenneth A.

2003-01-01

Over the past 27 years, or so, increased concern over single event effects in spacecraft systems has resulted in research, development and engineering activities centered around a better understanding of the space radiation environment, single event effects predictive methods, ground test protocols, and test facility developments. This research has led to fairly well developed methods for assessing the impact of the space radiation environment on systems that contain SEE sensitive devices and the development of mitigation strategies either at the system or device level.

Evaluation of CROES Nephrolithometry Nomogram as a Preoperative Predictive System for Percutaneous Nephrolithotomy Outcomes.

PubMed

Kumar, Sumit; Sreenivas, Jayaram; Karthikeyan, Vilvapathy Senguttuvan; Mallya, Ashwin; Keshavamurthy, Ramaiah

2016-10-01

Scoring systems have been devised to predict outcomes of percutaneous nephrolithotomy (PCNL). CROES nephrolithometry nomogram (CNN) is the latest tool devised to predict stone-free rate (SFR). We aim to compare predictive accuracy of CNN against Guy stone score (GSS) for SFR and postoperative outcomes. Between January 2013 and December 2015, 313 patients undergoing PCNL were analyzed for predictive accuracy of GSS, CNN, and stone burden (SB) for SFR, complications, operation time (OT), and length of hospitalization (LOH). We further stratified patients into risk groups based on CNN and GSS. Mean ± standard deviation (SD) SB was 298.8 ± 235.75 mm 2 . SB, GSS, and CNN (area under curve [AUC]: 0.662, 0.660, 0.673) were found to be predictors of SFR. However, predictability for complications was not as good (AUC: SB 0.583, GSS 0.554, CNN 0.580). Single implicated calix (Adj. OR 3.644; p = 0.027), absence of staghorn calculus (Adj. OR 3.091; p = 0.044), single stone (Adj. OR 3.855; p = 0.002), and single puncture (Adj. OR 2.309; p = 0.048) significantly predicted SFR on multivariate analysis. Charlson comorbidity index (CCI; p = 0.020) and staghorn calculus (p = 0.002) were independent predictors for complications on linear regression. SB and GSS independently predicted OT on multivariate analysis. SB and complications significantly predicted LOH, while GSS and CNN did not predict LOH. CNN offered better risk stratification for residual stones than GSS. CNN and GSS have good preoperative predictive accuracy for SFR. Number of implicated calices may affect SFR, and CCI affects complications. Studies should incorporate these factors in scoring systems and assess if predictability of PCNL outcomes improves.

Predictive Game Theory

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2005-01-01

Probability theory governs the outcome of a game; there is a distribution over mixed strat.'s, not a single "equilibrium". To predict a single mixed strategy must use our loss function (external to the game's players. Provides a quantification of any strategy's rationality. Prove rationality falls as cost of computation rises (for players who have not previously interacted). All extends to games with varying numbers of players.

Primary aldosteronism: results of adrenalectomy for nonsingle adenoma.

PubMed

Quillo, Amy R; Grant, Clive S; Thompson, Geoffrey B; Farley, David R; Richards, Melanie L; Young, William F

2011-07-01

Historically, treatment of confirmed primary aldosteronism has been adrenalectomy for unilateral adenoma; bilateral hypersecretion is treated medically. Increasingly, we use adrenal venous sampling (AVS) to define unilateral hypersecretion. Histology of glands resected based on AVS often reveals multiple nodules or hyperplasia. The aim of this study was to compare patients with multiple nodules or hyperplasia with those with single adenoma with regard to cure, preoperative imaging, AVS ratio, and biochemical evaluation to determine if a nonsingle adenoma (NSA) process could be predicted to impact extent of adrenalectomy. This was a retrospective study reviewing a single-institutional surgical experience at a tertiary academic center from 1993 to 2008, during which 215 patients with primary aldosteronism underwent unilateral adrenalectomy based on imaging of a single adenoma (normal contralateral gland) or AVS ratios. Histology included single adenoma versus NSA; cure was defined as normal immediate postoperative plasma or urine aldosterone level, normal aldosterone:renin ratio, or normotension without antihypertensive medications. Follow-up (mean 13 months, range 0 to 185 months) was available for 167 patients: 132 (79%) single adenoma and 35 (21%) NSA. All 35 patients with NSA and 128 patients (97%) with single adenoma were cured. Imaging studies correctly predicted NSA in 29% and 57% when combined with AVS. Identifying patients with NSA preoperatively was impossible biochemically: mean serum and urinary aldosterone levels and AVS ratios were not different than those of the single adenoma group. Twenty-one percent of patients had NSA, all cured by unilateral adrenalectomy. No preoperative evaluation reliably predicted NSA. Therefore, total unilateral adrenalectomy was safest given the potential for incomplete resection with partial adrenalectomy. Accurate AVS is highly predictive of cure irrespective of the unilateral adrenal histology. Copyright © 2011 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Decohesion Elements using Two and Three-Parameter Mixed-Mode Criteria

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Camanho, Pedro P.

2001-01-01

An eight-node decohesion element implementing different criteria to predict delamination growth under mixed-mode loading is proposed. The element is used at the interface between solid finite elements to model the initiation and propagation of delamination. A single displacement-based damage parameter is used in a softening law to track the damage state of the interface. The power law criterion and a three-parameter mixed-mode criterion are used to predict delamination growth. The accuracy of the predictions is evaluated in single mode delamination and in the mixed-mode bending tests.

Sub-Fickean Diffusion in a One-Dimensional Plasma Ring

NASA Astrophysics Data System (ADS)

Theisen, W. L.

2013-12-01

A one-dimensional dusty plasma ring is formed in a strongly-coupled complex plasma. The dust particles in the ring can be characterized as a one-dimensional system where the particles cannot pass each other. The particles perform random walks due to thermal motions. This single-file self diffusion is characterized by the mean-squared displacement (msd) of the individual particles which increases with time t. Diffusive processes that follow Ficks law predict that the msd increases as t, however, single-file diffusion is sub-Fickean meaning that the msd is predicted to increase as t^(1/2). Particle position data from the dusty plasma ring is analyzed to determine the scaling of the msd with time. Results are compared with predictions of single-file diffusion theory.

PPCM: Combing multiple classifiers to improve protein-protein interaction prediction

DOE PAGES

Yao, Jianzhuang; Guo, Hong; Yang, Xiaohan

2015-08-01

Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be improved. We developed a method called protein-protein interaction prediction classifiers merger (PPCM), and this method combines output from two PPI prediction tools, GO2PPI and Phyloprof, using Random Forests algorithm. The performance of PPCM was tested by area under the curve (AUC) using anmore » assembled Gold Standard database that contains both positive and negative PPI pairs. Our AUC test showed that PPCM significantly improved the PPI prediction accuracy over the corresponding individual classifiers. We found that additional classifiers incorporated into PPCM could lead to further improvement in the PPI prediction accuracy. Furthermore, cross species PPCM could achieve competitive and even better prediction accuracy compared to the single species PPCM. This study established a robust pipeline for PPI prediction by integrating multiple classifiers using Random Forests algorithm. Ultimately, this pipeline will be useful for predicting PPI in nonmodel species.« less

The influence of mindfulness, self-compassion, psychological flexibility, and posttraumatic stress disorder on disability and quality of life over time in war veterans.

PubMed

Meyer, Eric C; Frankfurt, Sheila B; Kimbrel, Nathan A; DeBeer, Bryann B; Gulliver, Suzy B; Morrisette, Sandra B

2018-07-01

Posttraumatic stress disorder (PTSD) strongly predicts greater disability and lower quality of life (QOL). Mindfulness-based and other third-wave behavior therapy interventions improve well-being by enhancing mindfulness, self-compassion, and psychological flexibility. We hypothesized that these mechanisms of therapeutic change would comprise a single latent factor that would predict disability and QOL after accounting for PTSD symptom severity. Iraq and Afghanistan war veterans (N = 117) completed a study of predictors of successful reintegration. Principal axis factor analysis tested whether mindfulness, self-compassion, and psychological flexibility comprised a single latent factor. Hierarchical regression tested whether this factor predicted disability and QOL 1 year later. Mindfulness, self-compassion, and psychological flexibility comprised a single factor that predicted disability and QOL after accounting for PTSD symptom severity. PTSD symptoms remained a significant predictor of disability but not QOL. Targeting these mechanisms may help veterans achieve functional recovery, even in the presence of PTSD symptoms. © 2018 Wiley Periodicals, Inc.

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

NASA Technical Reports Server (NTRS)

Wilson, Robert M.

1990-01-01

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

Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).

PubMed

Schulthess, Albert W; Zhao, Yusheng; Longin, C Friedrich H; Reif, Jochen C

2018-03-01

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.

Genomic prediction using phenotypes from pedigreed lines with no marker data

USDA-ARS?s Scientific Manuscript database

Until now genomic prediction in plant breeding has only used information from individuals that have been genotyped. In practice, information from non-genotyped relatives of genotyped individuals can be used to improve the genomic prediction accuracy. Single-step genomic prediction integrates all the...

Blastocoele expansion degree predicts live birth after single blastocyst transfer for fresh and vitrified/warmed single blastocyst transfer cycles.

PubMed

Du, Qing-Yun; Wang, En-Yin; Huang, Yan; Guo, Xiao-Yi; Xiong, Yu-Jing; Yu, Yi-Ping; Yao, Gui-Dong; Shi, Sen-Lin; Sun, Ying-Pu

2016-04-01

To evaluate the independent effects of the degree of blastocoele expansion and re-expansion and the inner cell mass (ICM) and trophectoderm (TE) grades on predicting live birth after fresh and vitrified/warmed single blastocyst transfer. Retrospective study. Reproductive medical center. Women undergoing 844 fresh and 370 vitrified/warmed single blastocyst transfer cycles. None. Live-birth rate correlated with blastocyst morphology parameters by logistic regression analysis and Spearman correlations analysis. The degree of blastocoele expansion and re-expansion was the only blastocyst morphology parameter that exhibited a significant ability to predict live birth in both fresh and vitrified/warmed single blastocyst transfer cycles respectively by multivariate logistic regression and Spearman correlations analysis. Although the ICM grade was significantly related to live birth in fresh cycles according to the univariate model, its effect was not maintained in the multivariate logistic analysis. In vitrified/warmed cycles, neither ICM nor TE grade was correlated with live birth by logistic regression analysis. This study is the first to confirm that the degree of blastocoele expansion and re-expansion is a better predictor of live birth after both fresh and vitrified/warmed single blastocyst transfer cycles than ICM or TE grade. Copyright © 2016. Published by Elsevier Inc.

A Single-System Model Predicts Recognition Memory and Repetition Priming in Amnesia

PubMed Central

Kessels, Roy P.C.; Wester, Arie J.; Shanks, David R.

2014-01-01

We challenge the claim that there are distinct neural systems for explicit and implicit memory by demonstrating that a formal single-system model predicts the pattern of recognition memory (explicit) and repetition priming (implicit) in amnesia. In the current investigation, human participants with amnesia categorized pictures of objects at study and then, at test, identified fragmented versions of studied (old) and nonstudied (new) objects (providing a measure of priming), and made a recognition memory judgment (old vs new) for each object. Numerous results in the amnesic patients were predicted in advance by the single-system model, as follows: (1) deficits in recognition memory and priming were evident relative to a control group; (2) items judged as old were identified at greater levels of fragmentation than items judged new, regardless of whether the items were actually old or new; and (3) the magnitude of the priming effect (the identification advantage for old vs new items) overall was greater than that of items judged new. Model evidence measures also favored the single-system model over two formal multiple-systems models. The findings support the single-system model, which explains the pattern of recognition and priming in amnesia primarily as a reduction in the strength of a single dimension of memory strength, rather than a selective explicit memory system deficit. PMID:25122896

The impact of different aperture distribution models and critical stress criteria on equivalent permeability in fractured rocks

NASA Astrophysics Data System (ADS)

Bisdom, Kevin; Bertotti, Giovanni; Nick, Hamidreza M.

2016-05-01

Predicting equivalent permeability in fractured reservoirs requires an understanding of the fracture network geometry and apertures. There are different methods for defining aperture, based on outcrop observations (power law scaling), fundamental mechanics (sublinear length-aperture scaling), and experiments (Barton-Bandis conductive shearing). Each method predicts heterogeneous apertures, even along single fractures (i.e., intrafracture variations), but most fractured reservoir models imply constant apertures for single fractures. We compare the relative differences in aperture and permeability predicted by three aperture methods, where permeability is modeled in explicit fracture networks with coupled fracture-matrix flow. Aperture varies along single fractures, and geomechanical relations are used to identify which fractures are critically stressed. The aperture models are applied to real-world large-scale fracture networks. (Sub)linear length scaling predicts the largest average aperture and equivalent permeability. Barton-Bandis aperture is smaller, predicting on average a sixfold increase compared to matrix permeability. Application of critical stress criteria results in a decrease in the fraction of open fractures. For the applied stress conditions, Coulomb predicts that 50% of the network is critically stressed, compared to 80% for Barton-Bandis peak shear. The impact of the fracture network on equivalent permeability depends on the matrix hydraulic properties, as in a low-permeable matrix, intrafracture connectivity, i.e., the opening along a single fracture, controls equivalent permeability, whereas for a more permeable matrix, absolute apertures have a larger impact. Quantification of fracture flow regimes using only the ratio of fracture versus matrix permeability is insufficient, as these regimes also depend on aperture variations within fractures.

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

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2009-01-01

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

Airport Noise Prediction Model -- MOD 7

DOT National Transportation Integrated Search

1978-07-01

The MOD 7 Airport Noise Prediction Model is fully operational. The language used is Fortran, and it has been run on several different computer systems. Its capabilities include prediction of noise levels for single parameter changes, for multiple cha...

Predicted stem-loop structures and variation in nucleotide sequence of 3' noncoding regions among animal calicivirus genomes.

PubMed

Seal, B S; Neill, J D; Ridpath, J F

1994-07-01

Caliciviruses are nonenveloped with a polyadenylated genome of approximately 7.6 kb and a single capsid protein. The "RNA Fold" computer program was used to analyze 3'-terminal noncoding sequences of five feline calicivirus (FCV), rabbit hemorrhagic disease virus (RHDV), and two San Miguel sea lion virus (SMSV) isolates. The FCV 3'-terminal sequences are 40-46 nucleotides in length and 72-91% similar. The FCV sequences were predicted to contain two possible duplex structures and one stem-loop structure with free energies of -2.1 to -18.2 kcal/mole. The RHDV genomic 3'-terminal RNA sequences are 54 nucleotides in length and share 49% sequence similarity to homologous regions of the FCV genome. The RHDV sequence was predicted to form two duplex structures in the 3'-terminal noncoding region with a single stem-loop structure, resembling that of FCV. In contrast, the SMSV 1 and 4 genomic 3'-terminal noncoding sequences were 185 and 182 nucleotides in length, respectively. Ten possible duplex structures were predicted with an average structural free energy of -35 kcal/mole. Sequence similarity between the two SMSV isolates was 75%. Furthermore, extensive cloverleaflike structures are predicted in the 3' noncoding region of the SMSV genome, in contrast to the predicted single stem-loop structures of FCV or RHDV.

Application of GA-SVM method with parameter optimization for landslide development prediction

NASA Astrophysics Data System (ADS)

Li, X. Z.; Kong, J. M.

2013-10-01

Prediction of landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. Support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of SVM model. In this study, we presented an application of GA-SVM method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in some hydro - electrical engineering area of Southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multi-factor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that, the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest RSME of 0.0009 and the biggest RI of 0.9992.

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

PubMed Central

Puton, Tomasz; Kozlowski, Lukasz P.; Rother, Kristian M.; Bujnicki, Janusz M.

2013-01-01

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks. PMID:23435231

Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets.

PubMed

Sun, Jiangming; Carlsson, Lars; Ahlberg, Ernst; Norinder, Ulf; Engkvist, Ola; Chen, Hongming

2017-07-24

Conformal prediction has been proposed as a more rigorous way to define prediction confidence compared to other application domain concepts that have earlier been used for QSAR modeling. One main advantage of such a method is that it provides a prediction region potentially with multiple predicted labels, which contrasts to the single valued (regression) or single label (classification) output predictions by standard QSAR modeling algorithms. Standard conformal prediction might not be suitable for imbalanced data sets. Therefore, Mondrian cross-conformal prediction (MCCP) which combines the Mondrian inductive conformal prediction with cross-fold calibration sets has been introduced. In this study, the MCCP method was applied to 18 publicly available data sets that have various imbalance levels varying from 1:10 to 1:1000 (ratio of active/inactive compounds). Our results show that MCCP in general performed well on bioactivity data sets with various imbalance levels. More importantly, the method not only provides confidence of prediction and prediction regions compared to standard machine learning methods but also produces valid predictions for the minority class. In addition, a compound similarity based nonconformity measure was investigated. Our results demonstrate that although it gives valid predictions, its efficiency is much worse than that of model dependent metrics.

Prediction of successful memory encoding based on single-trial rhinal and hippocampal phase information.

PubMed

Höhne, Marlene; Jahanbekam, Amirhossein; Bauckhage, Christian; Axmacher, Nikolai; Fell, Juergen

2016-10-01

Mediotemporal EEG characteristics are closely related to long-term memory formation. It has been reported that rhinal and hippocampal EEG measures reflecting the stability of phases across trials are better suited to distinguish subsequently remembered from forgotten trials than event-related potentials or amplitude-based measures. Theoretical models suggest that the phase of EEG oscillations reflects neural excitability and influences cellular plasticity. However, while previous studies have shown that the stability of phase values across trials is indeed a relevant predictor of subsequent memory performance, the effect of absolute single-trial phase values has been little explored. Here, we reanalyzed intracranial EEG recordings from the mediotemporal lobe of 27 epilepsy patients performing a continuous word recognition paradigm. Two-class classification using a support vector machine was performed to predict subsequently remembered vs. forgotten trials based on individually selected frequencies and time points. We demonstrate that it is possible to successfully predict single-trial memory formation in the majority of patients (23 out of 27) based on only three single-trial phase values given by a rhinal phase, a hippocampal phase, and a rhinal-hippocampal phase difference. Overall classification accuracy across all subjects was 69.2% choosing frequencies from the range between 0.5 and 50Hz and time points from the interval between -0.5s and 2s. For 19 patients, above chance prediction of subsequent memory was possible even when choosing only time points from the prestimulus interval (overall accuracy: 65.2%). Furthermore, prediction accuracies based on single-trial phase surpassed those based on single-trial power. Our results confirm the functional relevance of mediotemporal EEG phase for long-term memory operations and suggest that phase information may be utilized for memory enhancement applications based on deep brain stimulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Predicting out-of-office blood pressure level using repeated measurements in the clinic: an observational cohort study

PubMed Central

Sheppard, James P.; Holder, Roger; Nichols, Linda; Bray, Emma; Hobbs, F.D. Richard; Mant, Jonathan; Little, Paul; Williams, Bryan; Greenfield, Sheila; McManus, Richard J.

2014-01-01

Objectives: Identification of people with lower (white-coat effect) or higher (masked effect) blood pressure at home compared to the clinic usually requires ambulatory or home monitoring. This study assessed whether changes in SBP with repeated measurement at a single clinic predict subsequent differences between clinic and home measurements. Methods: This study used an observational cohort design and included 220 individuals aged 35–84 years, receiving treatment for hypertension, but whose SBP was not controlled. The characteristics of change in SBP over six clinic readings were defined as the SBP drop, the slope and the quadratic coefficient using polynomial regression modelling. The predictive abilities of these characteristics for lower or higher home SBP readings were investigated with logistic regression and repeated operating characteristic analysis. Results: The single clinic SBP drop was predictive of the white-coat effect with a sensitivity of 90%, specificity of 50%, positive predictive value of 56% and negative predictive value of 88%. Predictive values for the masked effect and those of the slope and quadratic coefficient were slightly lower, but when the slope and quadratic variables were combined, the sensitivity, specificity, positive and negative predictive values for the masked effect were improved to 91, 48, 24 and 97%, respectively. Conclusion: Characteristics obtainable from multiple SBP measurements in a single clinic in patients with treated hypertension appear to reasonably predict those unlikely to have a large white-coat or masked effect, potentially allowing better targeting of out-of-office monitoring in routine clinical practice. PMID:25144295

Prediction of near-term breast cancer risk using a Bayesian belief network

NASA Astrophysics Data System (ADS)

Zheng, Bin; Ramalingam, Pandiyarajan; Hariharan, Harishwaran; Leader, Joseph K.; Gur, David

2013-03-01

Accurately predicting near-term breast cancer risk is an important prerequisite for establishing an optimal personalized breast cancer screening paradigm. In previous studies, we investigated and tested the feasibility of developing a unique near-term breast cancer risk prediction model based on a new risk factor associated with bilateral mammographic density asymmetry between the left and right breasts of a woman using a single feature. In this study we developed a multi-feature based Bayesian belief network (BBN) that combines bilateral mammographic density asymmetry with three other popular risk factors, namely (1) age, (2) family history, and (3) average breast density, to further increase the discriminatory power of our cancer risk model. A dataset involving "prior" negative mammography examinations of 348 women was used in the study. Among these women, 174 had breast cancer detected and verified in the next sequential screening examinations, and 174 remained negative (cancer-free). A BBN was applied to predict the risk of each woman having cancer detected six to 18 months later following the negative screening mammography. The prediction results were compared with those using single features. The prediction accuracy was significantly increased when using the BBN. The area under the ROC curve increased from an AUC=0.70 to 0.84 (p<0.01), while the positive predictive value (PPV) and negative predictive value (NPV) also increased from a PPV=0.61 to 0.78 and an NPV=0.65 to 0.75, respectively. This study demonstrates that a multi-feature based BBN can more accurately predict the near-term breast cancer risk than with a single feature.

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

APOLLO: a quality assessment service for single and multiple protein models.

PubMed

Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin

2011-06-15

We built a web server named APOLLO, which can evaluate the absolute global and local qualities of a single protein model using machine learning methods or the global and local qualities of a pool of models using a pair-wise comparison approach. Based on our evaluations on 107 CASP9 (Critical Assessment of Techniques for Protein Structure Prediction) targets, the predicted quality scores generated from our machine learning and pair-wise methods have an average per-target correlation of 0.671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure. http://sysbio.rnet.missouri.edu/apollo/. Single and pair-wise global quality assessment software is also available at the site.

Preliminary investigation of single-file diffusion in complex plasma rings

NASA Astrophysics Data System (ADS)

Theisen, W. L.; Sheridan, T. E.

2010-04-01

Particles in one-dimensional (1D) systems cannot pass each other. However, it is still possible to define a diffusion process where the mean-squared displacement (msd) of an ensemble of particles in a 1D chain increases with time t. This process is called single-file diffusion. In contrast to diffusive processes that follow Fick's law, msdt, single-file diffusion is sub-Fickean and the msd is predicted to increase as t^1/2. We have recently created 1D dusty (complex) plasma rings in the DONUT (Dusty ONU experimenT) apparatus. Particle position data from these rings will be analyzed to determine the scaling of the msd with time and results will be compared with predictions of single-file diffusion theory.

Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

Reducing hydrologic model uncertainty in monthly streamflow predictions using multimodel combination

NASA Astrophysics Data System (ADS)

Li, Weihua; Sankarasubramanian, A.

2012-12-01

Model errors are inevitable in any prediction exercise. One approach that is currently gaining attention in reducing model errors is by combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictions. A new dynamic approach (MM-1) to combine multiple hydrological models by evaluating their performance/skill contingent on the predictor state is proposed. We combine two hydrological models, "abcd" model and variable infiltration capacity (VIC) model, to develop multimodel streamflow predictions. To quantify precisely under what conditions the multimodel combination results in improved predictions, we compare multimodel scheme MM-1 with optimal model combination scheme (MM-O) by employing them in predicting the streamflow generated from a known hydrologic model (abcd model orVICmodel) with heteroscedastic error variance as well as from a hydrologic model that exhibits different structure than that of the candidate models (i.e., "abcd" model or VIC model). Results from the study show that streamflow estimated from single models performed better than multimodels under almost no measurement error. However, under increased measurement errors and model structural misspecification, both multimodel schemes (MM-1 and MM-O) consistently performed better than the single model prediction. Overall, MM-1 performs better than MM-O in predicting the monthly flow values as well as in predicting extreme monthly flows. Comparison of the weights obtained from each candidate model reveals that as measurement errors increase, MM-1 assigns weights equally for all the models, whereas MM-O assigns higher weights for always the best-performing candidate model under the calibration period. Applying the multimodel algorithms for predicting streamflows over four different sites revealed that MM-1 performs better than all single models and optimal model combination scheme, MM-O, in predicting the monthly flows as well as the flows during wetter months.

Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series

PubMed Central

Ferguson, Jake M; Ponciano, José M

2014-01-01

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series. PMID:24304946

Evaluation of single-point sampling strategies for the estimation of moclobemide exposure in depressive patients.

PubMed

Ignjatovic, Anita Rakic; Miljkovic, Branislava; Todorovic, Dejan; Timotijevic, Ivana; Pokrajac, Milena

2011-05-01

Because moclobemide pharmacokinetics vary considerably among individuals, monitoring of plasma concentrations lends insight into its pharmacokinetic behavior and enhances its rational use in clinical practice. The aim of this study was to evaluate whether single concentration-time points could adequately predict moclobemide systemic exposure. Pharmacokinetic data (full 7-point pharmacokinetic profiles), obtained from 21 depressive inpatients receiving moclobemide (150 mg 3 times daily), were randomly split into development (n = 18) and validation (n = 16) sets. Correlations between the single concentration-time points and the area under the concentration-time curve within a 6-hour dosing interval at steady-state (AUC(0-6)) were assessed by linear regression analyses. The predictive performance of single-point sampling strategies was evaluated in the validation set by mean prediction error, mean absolute error, and root mean square error. Plasma concentrations in the absorption phase yielded unsatisfactory predictions of moclobemide AUC(0-6). The best estimation of AUC(0-6) was achieved from concentrations at 4 and 6 hours following dosing. As the most reliable surrogate for moclobemide systemic exposure, concentrations at 4 and 6 hours should be used instead of predose trough concentrations as an indicator of between-patient variability and a guide for dose adjustments in specific clinical situations.

[Comparison of the factors influencing young adolescents' aggression according to family structure].

PubMed

Yun, Eun Kyoung; Shin, Sung Hee

2013-06-01

This cross-sectional study was done to compare factors influencing young adolescents' aggression according to family structure. Participants were 680 young adolescents aged 11 to 15 years (113 in single father families, 136 in single mother families, 49 in grandparent families, and 382 in both-parent families). All measures were self-administered. Data were analyzed using SPSS 18.0 program and factors affecting young adolescents' aggression were analyzed by stepwise multiple regression. Levels of young adolescents' aggression and all variables were significantly different among the four family structure groups. Factors influencing young adolescents' aggression were also different according to these 4 groups. For single father families, depression-anxiety and family hardiness significantly predicted the level of young adolescents' aggression (adjusted R square=.37, p<.001). For single mother families, depression-anxiety, gender, and friends' support significantly predicted the level of young adolescents' aggression (adjusted R square=.58, p<.001). For grandparent families, depression-anxiety and family support significantly predicted the level of young adolescents' aggression (adjusted R square=.58, p<.001). For both-parent families, depression-anxiety, family hardiness, and friends' support significantly predicted the level of young adolescents' aggression (adjusted R square=.48, p<.001). Nurses working with young adolescents should consider family structure-specific factors influencing aggression in this population.

SEAN: SNP prediction and display program utilizing EST sequence clusters.

PubMed

Huntley, Derek; Baldo, Angela; Johri, Saurabh; Sergot, Marek

2006-02-15

SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.

The work ability index and single-item question: associations with sick leave, symptoms, and health--a prospective study of women on long-term sick leave.

PubMed

Ahlstrom, Linda; Grimby-Ekman, Anna; Hagberg, Mats; Dellve, Lotta

2010-09-01

This study investigated the association between the work ability index (WAI) and the single-item question on work ability among women working in human service organizations (HSO) currently on long-term sick leave. It also examined the association between the WAI and the single-item question in relation to sick leave, symptoms, and health. Predictive values of the WAI, the changed WAI, the single-item question and the changed single-item question were investigated for degree of sick leave, symptoms, and health. This cohort study comprised 324 HSO female workers on long-term (>60 days) sick leave, with follow-ups at 6 and 12 months. Participants responded to questionnaires. Data on work ability, sick leave, health, and symptoms were analyzed with regard to associations and predictability. Spearman correlation and mixed-model analysis were performed for repeated measurements over time. The study showed a very strong association between the WAI and the single-item question among all participants. Both the WAI and the single-item question showed similar patterns of associations with sick leave, health, and symptoms. The predictive value for the degree of sick leave and health-related quality of life (HRQoL) was strong for both the WAI and the single-item question, and slightly less strong for vitality, neck pain, both self-rated general and mental health, and behavioral and current stress. This study suggests that the single-item question on work ability could be used as a simple indicator for assessing the status and progress of work ability among women on long-term sick leave.

Non-destructive analysis of sucrose, caffeine and trigonelline on single green coffee beans by hyperspectral imaging.

PubMed

Caporaso, Nicola; Whitworth, Martin B; Grebby, Stephen; Fisk, Ian D

2018-04-01

Hyperspectral imaging (HSI) is a novel technology for the food sector that enables rapid non-contact analysis of food materials. HSI was applied for the first time to whole green coffee beans, at a single seed level, for quantitative prediction of sucrose, caffeine and trigonelline content. In addition, the intra-bean distribution of coffee constituents was analysed in Arabica and Robusta coffees on a large sample set from 12 countries, using a total of 260 samples. Individual green coffee beans were scanned by reflectance HSI (980-2500nm) and then the concentration of sucrose, caffeine and trigonelline analysed with a reference method (HPLC-MS). Quantitative prediction models were subsequently built using Partial Least Squares (PLS) regression. Large variations in sucrose, caffeine and trigonelline were found between different species and origin, but also within beans from the same batch. It was shown that estimation of sucrose content is possible for screening purposes (R 2 =0.65; prediction error of ~0.7% w/w coffee, with observed range of ~6.5%), while the performance of the PLS model was better for caffeine and trigonelline prediction (R 2 =0.85 and R 2 =0.82, respectively; prediction errors of 0.2 and 0.1%, on a range of 2.3 and 1.1% w/w coffee, respectively). The prediction error is acceptable mainly for laboratory applications, with the potential application to breeding programmes and for screening purposes for the food industry. The spatial distribution of coffee constituents was also successfully visualised for single beans and this enabled mapping of the analytes across the bean structure at single pixel level. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, S. R.

2010-01-01

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Improved Prediction of Falls in Community-Dwelling Older Adults Through Phase-Dependent Entropy of Daily-Life Walking

PubMed Central

Ihlen, Espen A. F.; van Schooten, Kimberley S.; Bruijn, Sjoerd M.; van Dieën, Jaap H.; Vereijken, Beatrix; Helbostad, Jorunn L.; Pijnappels, Mirjam

2018-01-01

Age and age-related diseases have been suggested to decrease entropy of human gait kinematics, which is thought to make older adults more susceptible to falls. In this study we introduce a new entropy measure, called phase-dependent generalized multiscale entropy (PGME), and test whether this measure improves fall-risk prediction in community-dwelling older adults. PGME can assess phase-dependent changes in the stability of gait dynamics that result from kinematic changes in events such as heel strike and toe-off. PGME was assessed for trunk acceleration of 30 s walking epochs in a re-analysis of 1 week of daily-life activity data from the FARAO study, originally described by van Schooten et al. (2016). The re-analyzed data set contained inertial sensor data from 52 single- and 46 multiple-time prospective fallers in a 6 months follow-up period, and an equal number of non-falling controls matched by age, weight, height, gender, and the use of walking aids. The predictive ability of PGME for falls was assessed using a partial least squares regression. PGME had a superior predictive ability of falls among single-time prospective fallers when compared to the other gait features. The single-time fallers had a higher PGME (p < 0.0001) of their trunk acceleration at 60% of their step cycle when compared with non-fallers. No significant differences were found between PGME of multiple-time fallers and non-fallers, but PGME was found to improve the prediction model of multiple-time fallers when combined with other gait features. These findings suggest that taking into account phase-dependent changes in the stability of the gait dynamics has additional value for predicting falls in older people, especially for single-time prospective fallers. PMID:29556188

Improved Prediction of Falls in Community-Dwelling Older Adults Through Phase-Dependent Entropy of Daily-Life Walking.

PubMed

Ihlen, Espen A F; van Schooten, Kimberley S; Bruijn, Sjoerd M; van Dieën, Jaap H; Vereijken, Beatrix; Helbostad, Jorunn L; Pijnappels, Mirjam

2018-01-01

Age and age-related diseases have been suggested to decrease entropy of human gait kinematics, which is thought to make older adults more susceptible to falls. In this study we introduce a new entropy measure, called phase-dependent generalized multiscale entropy (PGME), and test whether this measure improves fall-risk prediction in community-dwelling older adults. PGME can assess phase-dependent changes in the stability of gait dynamics that result from kinematic changes in events such as heel strike and toe-off. PGME was assessed for trunk acceleration of 30 s walking epochs in a re-analysis of 1 week of daily-life activity data from the FARAO study, originally described by van Schooten et al. (2016). The re-analyzed data set contained inertial sensor data from 52 single- and 46 multiple-time prospective fallers in a 6 months follow-up period, and an equal number of non-falling controls matched by age, weight, height, gender, and the use of walking aids. The predictive ability of PGME for falls was assessed using a partial least squares regression. PGME had a superior predictive ability of falls among single-time prospective fallers when compared to the other gait features. The single-time fallers had a higher PGME ( p < 0.0001) of their trunk acceleration at 60% of their step cycle when compared with non-fallers. No significant differences were found between PGME of multiple-time fallers and non-fallers, but PGME was found to improve the prediction model of multiple-time fallers when combined with other gait features. These findings suggest that taking into account phase-dependent changes in the stability of the gait dynamics has additional value for predicting falls in older people, especially for single-time prospective fallers.

Genomic prediction of the polled and horned phenotypes in Merino sheep.

PubMed

Duijvesteijn, Naomi; Bolormaa, Sunduimijid; Daetwyler, Hans D; van der Werf, Julius H J

2018-05-22

In horned sheep breeds, breeding for polledness has been of interest for decades. The objective of this study was to improve prediction of the horned and polled phenotypes using horn scores classified as polled, scurs, knobs or horns. Derived phenotypes polled/non-polled (P/NP) and horned/non-horned (H/NH) were used to test four different strategies for prediction in 4001 purebred Merino sheep. These strategies include the use of single 'single nucleotide polymorphism' (SNP) genotypes, multiple-SNP haplotypes, genome-wide and chromosome-wide genomic best linear unbiased prediction and information from imputed sequence variants from the region including the RXFP2 gene. Low-density genotypes of these animals were imputed to the Illumina Ovine high-density (600k) chip and the 1.78-kb insertion polymorphism in RXFP2 was included in the imputation process to whole-genome sequence. We evaluated the mode of inheritance and validated models by a fivefold cross-validation and across- and between-family prediction. The most significant SNPs for prediction of P/NP and H/NH were OAR10_29546872.1 and OAR10_29458450, respectively, located on chromosome 10 close to the 1.78-kb insertion at 29.5 Mb. The mode of inheritance included an additive effect and a sex-dependent effect for dominance for P/NP and a sex-dependent additive and dominance effect for H/NH. Models with the highest prediction accuracies for H/NH used either single SNPs or 3-SNP haplotypes and included a polygenic effect estimated based on traditional pedigree relationships. Prediction accuracies for H/NH were 0.323 for females and 0.725 for males. For predicting P/NP, the best models were the same as for H/NH but included a genomic relationship matrix with accuracies of 0.713 for females and 0.620 for males. Our results show that prediction accuracy is high using a single SNP, but does not reach 1 since the causative mutation is not genotyped. Incomplete penetrance or allelic heterogeneity, which can influence expression of the phenotype, may explain why prediction accuracy did not approach 1 with any of the genetic models tested here. Nevertheless, a breeding program to eradicate horns from Merino sheep can be effective by selecting genotypes GG of SNP OAR10_29458450 or TT of SNP OAR10_29546872.1 since all sheep with these genotypes will be non-horned.

Methodology Developed for Modeling the Fatigue Crack Growth Behavior of Single-Crystal, Nickel-Base Superalloys

NASA Technical Reports Server (NTRS)

1996-01-01

Because of their superior high-temperature properties, gas generator turbine airfoils made of single-crystal, nickel-base superalloys are fast becoming the standard equipment on today's advanced, high-performance aerospace engines. The increased temperature capabilities of these airfoils has allowed for a significant increase in the operating temperatures in turbine sections, resulting in superior propulsion performance and greater efficiencies. However, the previously developed methodologies for life-prediction models are based on experience with polycrystalline alloys and may not be applicable to single-crystal alloys under certain operating conditions. One of the main areas where behavior differences between single-crystal and polycrystalline alloys are readily apparent is subcritical fatigue crack growth (FCG). The NASA Lewis Research Center's work in this area enables accurate prediction of the subcritical fatigue crack growth behavior in single-crystal, nickel-based superalloys at elevated temperatures.

Learning transitive verbs from single-word verbs in the input by young children acquiring English.

PubMed

Ninio, Anat

2016-09-01

The environmental context of verbs addressed by adults to young children is claimed to be uninformative regarding the verbs' meaning, yielding the Syntactic Bootstrapping Hypothesis that, for verb learning, full sentences are needed to demonstrate the semantic arguments of verbs. However, reanalysis of Gleitman's (1990) original data regarding input to a blind child revealed the context of single-word parental verbs to be more transparent than that of sentences. We tested the hypothesis that English-speaking children learn their early verbs from parents' single-word utterances. Distribution of single-word transitive verbs produced by a large sample of young children was strongly predicted by the relative token frequency of verbs in parental single-word utterances, but multiword sentences had no predictive value. Analysis of the interactive context showed that objects of verbs are retrievable by pragmatic inference, as is the meaning of the verbs. Single-word input appears optimal for learning an initial vocabulary of verbs.

Correlates of a single cortical action potential in the epidural EEG

PubMed Central

Teleńczuk, Bartosz; Baker, Stuart N; Kempter, Richard; Curio, Gabriel

2015-01-01

To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components > 800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes. PMID:25554430

Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

PubMed Central

Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Churchland, Mark M.; Cunningham, John P.; Shenoy, Krishna V.

2015-01-01

Increasing evidence suggests that neural population responses have their own internal drive, or dynamics, that describe how the neural population evolves through time. An important prediction of neural dynamical models is that previously observed neural activity is informative of noisy yet-to-be-observed activity on single-trials, and may thus have a denoising effect. To investigate this prediction, we built and characterized dynamical models of single-trial motor cortical activity. We find these models capture salient dynamical features of the neural population and are informative of future neural activity on single trials. To assess how neural dynamics may beneficially denoise single-trial neural activity, we incorporate neural dynamics into a brain–machine interface (BMI). In online experiments, we find that a neural dynamical BMI achieves substantially higher performance than its non-dynamical counterpart. These results provide evidence that neural dynamics beneficially inform the temporal evolution of neural activity on single trials and may directly impact the performance of BMIs. PMID:26220660

Prediction of area under the curve for a p-glycoprotein, a CYP3A4 and a CYP2C9 substrate using a single time point strategy: assessment using fexofenadine, itraconazole and losartan and metabolites.

PubMed

Srinivas, Nuggehally R

2016-01-01

In the present age of polypharmacy, limited sampling strategy becomes important to verify if drug levels are within the prescribed threshold limits from efficacy and safety considerations. The need to establish reliable single time concentration dependent models to predict exposure becomes important from cost and time perspectives. A simple unweighted linear regression model was developed to describe the relationship between Cmax versus AUC for fexofenadine, losartan, EXP3174, itraconazole and hydroxyitraconazole. The fold difference, defined as the quotient of the observed and predicted AUC values, were evaluated along with statistical comparison of the predicted versus observed values. The correlation between Cmax versus AUC was well established for all the five drugs with a correlation coefficient (r) ranging from 0.9130 to 0.9997. Majority of the predicted values for all the five drugs (77%) were contained within a narrow boundary of 0.75- to 1.5-fold difference. The r values for observed versus predicted AUC were 0.9653 (n = 145), 0.8342 (n = 76), 0.9524 (n = 88), 0.9339 (n = 89) and 0.9452 (n = 66) for fexofenadine, losartan, EXP3174, itraconazole and hydroxyitraconazole, respectively. Cmax versus AUC relationships were established for all drugs and were amenable for limited sampling strategy for AUC prediction. However, fexofenadine, EXP3174 and hydroxyitraconazole may be most relevant for AUC prediction by a single time concentration as judged by the various criteria applied in this study.

A statistical method for predicting seizure onset zones from human single-neuron recordings

NASA Astrophysics Data System (ADS)

Valdez, André B.; Hickman, Erin N.; Treiman, David M.; Smith, Kris A.; Steinmetz, Peter N.

2013-02-01

Objective. Clinicians often use depth-electrode recordings to localize human epileptogenic foci. To advance the diagnostic value of these recordings, we applied logistic regression models to single-neuron recordings from depth-electrode microwires to predict seizure onset zones (SOZs). Approach. We collected data from 17 epilepsy patients at the Barrow Neurological Institute and developed logistic regression models to calculate the odds of observing SOZs in the hippocampus, amygdala and ventromedial prefrontal cortex, based on statistics such as the burst interspike interval (ISI). Main results. Analysis of these models showed that, for a single-unit increase in burst ISI ratio, the left hippocampus was approximately 12 times more likely to contain a SOZ; and the right amygdala, 14.5 times more likely. Our models were most accurate for the hippocampus bilaterally (at 85% average sensitivity), and performance was comparable with current diagnostics such as electroencephalography. Significance. Logistic regression models can be combined with single-neuron recording to predict likely SOZs in epilepsy patients being evaluated for resective surgery, providing an automated source of clinically useful information.

Experimental and numerical investigations on spray characteristics of fatty acid methyl esters

NASA Astrophysics Data System (ADS)

Lanjekar, R. D.; Deshmukh, D.

2018-02-01

A comparative experimental and numerical study is conducted to establish the significance of the use of single-component over multi-component representatives of biodiesel, diesel and their blend for predicting spray tip penetration. Methyl oleate and methyl laurate are used as single-component representative fuels for biodiesel. The pure components n-heptane, n-dodecane and n-tetradecane are used as single-component representative fuels for diesel. Methyl laurate is found to represent biodiesel of coconut, whereas methyl oleate is found to represent biodiesel having high percentage of long-chain fatty acid esters. The spray tip penetration of methyl oleate is found to be in good agreement with the measured spray tip penetration of karanja biodiesel. The spray tip penetration prediction of n-heptane fuel is closely following diesel spray tip penetration along with that of n-tetradecane and n-dodecane. The study suggests that the knowledge of the single-component representatives of biodiesel, diesel and their blend is sufficient to predict the spray tip penetration of the corresponding biodiesel, diesel and their blend under non-evaporating environment.

Neural Prediction of Multidimensional Decisions in Monkey Superior Colliculus

NASA Astrophysics Data System (ADS)

Hasegawa, Ryohei P.; Hasegawa, Yukako T.; Segraves, Mark A.

To examine the function of the superior colliculus (SC) in decision-making processes and the application of its single trial activity for “neural mind reading,” we recorded from SC deep layers while two monkeys performed oculomotor go/no-go tasks. We have recently focused on monitoring single trial activities in single SC neurons, and designed a virtual decision function (VDF) to provide a good estimation of single-dimensional decisions (go/no-go decisions for a cue presented at a specific visual field, a response field of each neuron). In this study, we used two VDFs for multidimensional decisions (go/no-go decisions at two cue locations) with the ensemble activity which was simultaneously recorded from a small group (4 to 6) of neurons at both sides of the SC. VDFs predicted cue locations as well as go/no-go decisions. These results suggest that monitoring of ensemble SC activity had sufficient capacity to predict multidimensional decisions on a trial-by-trial basis, which is an ideal candidate to serve for cognitive brain-machine interfaces (BMI) such as two-dimensional word spellers.

Experimental and numerical investigations on spray characteristics of fatty acid methyl esters.

PubMed

Lanjekar, R D; Deshmukh, D

2018-02-01

A comparative experimental and numerical study is conducted to establish the significance of the use of single-component over multi-component representatives of biodiesel, diesel and their blend for predicting spray tip penetration. Methyl oleate and methyl laurate are used as single-component representative fuels for biodiesel. The pure components n -heptane, n -dodecane and n -tetradecane are used as single-component representative fuels for diesel. Methyl laurate is found to represent biodiesel of coconut, whereas methyl oleate is found to represent biodiesel having high percentage of long-chain fatty acid esters. The spray tip penetration of methyl oleate is found to be in good agreement with the measured spray tip penetration of karanja biodiesel. The spray tip penetration prediction of n -heptane fuel is closely following diesel spray tip penetration along with that of n -tetradecane and n -dodecane. The study suggests that the knowledge of the single-component representatives of biodiesel, diesel and their blend is sufficient to predict the spray tip penetration of the corresponding biodiesel, diesel and their blend under non-evaporating environment.

Experimental and numerical investigations on spray characteristics of fatty acid methyl esters

PubMed Central

Deshmukh, D.

2018-01-01

A comparative experimental and numerical study is conducted to establish the significance of the use of single-component over multi-component representatives of biodiesel, diesel and their blend for predicting spray tip penetration. Methyl oleate and methyl laurate are used as single-component representative fuels for biodiesel. The pure components n-heptane, n-dodecane and n-tetradecane are used as single-component representative fuels for diesel. Methyl laurate is found to represent biodiesel of coconut, whereas methyl oleate is found to represent biodiesel having high percentage of long-chain fatty acid esters. The spray tip penetration of methyl oleate is found to be in good agreement with the measured spray tip penetration of karanja biodiesel. The spray tip penetration prediction of n-heptane fuel is closely following diesel spray tip penetration along with that of n-tetradecane and n-dodecane. The study suggests that the knowledge of the single-component representatives of biodiesel, diesel and their blend is sufficient to predict the spray tip penetration of the corresponding biodiesel, diesel and their blend under non-evaporating environment. PMID:29515835

Building and verifying a severity prediction model of acute pancreatitis (AP) based on BISAP, MEWS and routine test indexes.

PubMed

Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei

2017-10-01

To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value<0.001), whereas RDW is not a prediction index of AP severity (P-value>0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value<0.001), and MEWS is not an independent prediction index of AP severity (P-value>0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-value<0.001). The constructed model is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP and serum Ca2+ individually (P-value<0.01). Verification of the internal validity of the models by bootstrapping is favorable. BISAP and serum Ca2+ have high predictive value for the severity of AP. However, the model built by combining BISAP and serum Ca2+ is remarkably superior to those of BISAP and serum Ca2+ individually. Furthermore, this model is simple, practical and appropriate for clinical use. Copyright © 2016. Published by Elsevier Masson SAS.

A comparison of optimisation methods and knee joint degrees of freedom on muscle force predictions during single-leg hop landings.

PubMed

Mokhtarzadeh, Hossein; Perraton, Luke; Fok, Laurence; Muñoz, Mario A; Clark, Ross; Pivonka, Peter; Bryant, Adam L

2014-09-22

The aim of this paper was to compare the effect of different optimisation methods and different knee joint degrees of freedom (DOF) on muscle force predictions during a single legged hop. Nineteen subjects performed single-legged hopping manoeuvres and subject-specific musculoskeletal models were developed to predict muscle forces during the movement. Muscle forces were predicted using static optimisation (SO) and computed muscle control (CMC) methods using either 1 or 3 DOF knee joint models. All sagittal and transverse plane joint angles calculated using inverse kinematics or CMC in a 1 DOF or 3 DOF knee were well-matched (RMS error<3°). Biarticular muscles (hamstrings, rectus femoris and gastrocnemius) showed more differences in muscle force profiles when comparing between the different muscle prediction approaches where these muscles showed larger time delays for many of the comparisons. The muscle force magnitudes of vasti, gluteus maximus and gluteus medius were not greatly influenced by the choice of muscle force prediction method with low normalised root mean squared errors (<48%) observed in most comparisons. We conclude that SO and CMC can be used to predict lower-limb muscle co-contraction during hopping movements. However, care must be taken in interpreting the magnitude of force predicted in the biarticular muscles and the soleus, especially when using a 1 DOF knee. Despite this limitation, given that SO is a more robust and computationally efficient method for predicting muscle forces than CMC, we suggest that SO can be used in conjunction with musculoskeletal models that have a 1 or 3 DOF knee joint to study the relative differences and the role of muscles during hopping activities in future studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

Defining and predicting structurally conserved regions in protein superfamilies

PubMed Central

Huang, Ivan K.; Grishin, Nick V.

2013-01-01

Motivation: The structures of homologous proteins are generally better conserved than their sequences. This phenomenon is demonstrated by the prevalence of structurally conserved regions (SCRs) even in highly divergent protein families. Defining SCRs requires the comparison of two or more homologous structures and is affected by their availability and divergence, and our ability to deduce structurally equivalent positions among them. In the absence of multiple homologous structures, it is necessary to predict SCRs of a protein using information from only a set of homologous sequences and (if available) a single structure. Accurate SCR predictions can benefit homology modelling and sequence alignment. Results: Using pairwise DaliLite alignments among a set of homologous structures, we devised a simple measure of structural conservation, termed structural conservation index (SCI). SCI was used to distinguish SCRs from non-SCRs. A database of SCRs was compiled from 386 SCOP superfamilies containing 6489 protein domains. Artificial neural networks were then trained to predict SCRs with various features deduced from a single structure and homologous sequences. Assessment of the predictions via a 5-fold cross-validation method revealed that predictions based on features derived from a single structure perform similarly to ones based on homologous sequences, while combining sequence and structural features was optimal in terms of accuracy (0.755) and Matthews correlation coefficient (0.476). These results suggest that even without information from multiple structures, it is still possible to effectively predict SCRs for a protein. Finally, inspection of the structures with the worst predictions pinpoints difficulties in SCR definitions. Availability: The SCR database and the prediction server can be found at http://prodata.swmed.edu/SCR. Contact: 91huangi@gmail.com or grishin@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics Online PMID:23193223

Responses to single photons in visual cells of Limulus

PubMed Central

Borsellino, A.; Fuortes, M. G. F.

1968-01-01

1. A system proposed in a previous article as a model of responses of visual cells has been analysed with the purpose of predicting the features of responses to single absorbed photons. 2. As a result of this analysis, the stochastic variability of responses has been expressed as a function of the amplification of the system. 3. The theoretical predictions have been compared to the results obtained by recording electrical responses of visual cells of Limulus to flashes delivering only few photons. 4. Experimental responses to single photons have been tentatively identified and it was shown that the stochastic variability of these responses is similar to that predicted for a model with a multiplication factor of at least twenty-five. 5. These results lead to the conclusion that the processes responsible for visual responses incorporate some form of amplification. This conclusion may prove useful for identifying the physical mechanisms underlying the transducer action of visual cells. PMID:5664231

Mismatch repair factor MSH2-MSH3 binds and alters the conformation of branched DNA structures predicted to form during genetic recombination.

PubMed

Surtees, Jennifer A; Alani, Eric

2006-07-14

Genetic studies in Saccharomyces cerevisiae predict that the mismatch repair (MMR) factor MSH2-MSH3 binds and stabilizes branched recombination intermediates that form during single strand annealing and gene conversion. To test this model, we constructed a series of DNA substrates that are predicted to form during these recombination events. We show in an electrophoretic mobility shift assay that S. cerevisiae MSH2-MSH3 specifically binds branched DNA substrates containing 3' single-stranded DNA and that ATP stimulates its release from these substrates. Chemical footprinting analyses indicate that MSH2-MSH3 specifically binds at the double-strand/single-strand junction of branched substrates, alters its conformation and opens up the junction. Therefore, MSH2-MSH3 binding to its substrates creates a unique nucleoprotein structure that may signal downstream steps in repair that include interactions with MMR and nucleotide excision repair factors.

Vibrational Dynamics of Biological Molecules: Multi-quantum Contributions

PubMed Central

Leu, Bogdan M.; Timothy Sage, J.; Zgierski, Marek Z.; Wyllie, Graeme R. A.; Ellison, Mary K.; Robert Scheidt, W.; Sturhahn, Wolfgang; Ercan Alp, E.; Durbin, Stephen M.

2006-01-01

High-resolution X-ray measurements near a nuclear resonance reveal the complete vibrational spectrum of the probe nucleus. Because of this, nuclear resonance vibrational spectroscopy (NRVS) is a uniquely quantitative probe of the vibrational dynamics of reactive iron sites in proteins and other complex molecules. Our measurements of vibrational fundamentals have revealed both frequencies and amplitudes of 57Fe vibrations in proteins and model compounds. Information on the direction of Fe motion has also been obtained from measurements on oriented single crystals, and provides an essential test of normal mode predictions. Here, we report the observation of weaker two-quantum vibrational excitations (overtones and combinations) for compounds that mimic the active site of heme proteins. The predicted intensities depend strongly on the direction of Fe motion. We compare the observed features with predictions based on the observed fundamentals, using information on the direction of Fe motion obtained either from DFT predictions or from single crystal measurements. Two-quantum excitations may become a useful tool to identify the directions of the Fe oscillations when single crystals are not available. PMID:16894397

dbWGFP: a database and web server of human whole-genome single nucleotide variants and their functional predictions.

PubMed

Wu, Jiaxin; Wu, Mengmeng; Li, Lianshuo; Liu, Zhuo; Zeng, Wanwen; Jiang, Rui

2016-01-01

The recent advancement of the next generation sequencing technology has enabled the fast and low-cost detection of all genetic variants spreading across the entire human genome, making the application of whole-genome sequencing a tendency in the study of disease-causing genetic variants. Nevertheless, there still lacks a repository that collects predictions of functionally damaging effects of human genetic variants, though it has been well recognized that such predictions play a central role in the analysis of whole-genome sequencing data. To fill this gap, we developed a database named dbWGFP (a database and web server of human whole-genome single nucleotide variants and their functional predictions) that contains functional predictions and annotations of nearly 8.58 billion possible human whole-genome single nucleotide variants. Specifically, this database integrates 48 functional predictions calculated by 17 popular computational methods and 44 valuable annotations obtained from various data sources. Standalone software, user-friendly query services and free downloads of this database are available at http://bioinfo.au.tsinghua.edu.cn/dbwgfp. dbWGFP provides a valuable resource for the analysis of whole-genome sequencing, exome sequencing and SNP array data, thereby complementing existing data sources and computational resources in deciphering genetic bases of human inherited diseases. © The Author(s) 2016. Published by Oxford University Press.

Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series.

PubMed

Ferguson, Jake M; Ponciano, José M

2014-02-01

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series. © 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

RNA-SSPT: RNA Secondary Structure Prediction Tools.

PubMed

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

RNA-SSPT: RNA Secondary Structure Prediction Tools

PubMed Central

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes. PMID:24250115

The potential of large studies for building genetic risk prediction models

Cancer.gov

NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

Application of System Identification Methods for Decoding Imagined Single-Joint Movements in an Individual with High Tetraplegia

PubMed Central

Ajiboye, A. Bolu; Hochberg, Leigh R.; Donoghue, John P.; Kirsch, Robert F.

2013-01-01

This study investigated the decoding of imagined arm movements from M1 in an individual with high level tetraplegia. The participant was instructed to imagine herself performing a series of single-joint arm movements, aided by the visual cue of an animate character performing these movements. System identification was used offline to predict the trajectories of the imagined movements and compare these predictions to the trajectories of the actual movements. We report rates of 25 – 50% for predicting completely imagined arm movements in the absence of a priori movements to aid in decoder building. PMID:21096197

Prediction of the effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes with flaps retracted

NASA Technical Reports Server (NTRS)

Weil, Joseph; Sleeman, William C , Jr

1949-01-01

The effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes are analyzed, and a simple method is presented for computing power-on pitching-moment curves for flap-retracted flight conditions. The methods evolved are based on the results of powered-model wind-tunnel investigations of 28 model configurations. Correlation curves are presented from which the effects of power on the downwash over the tail and the stabilizer effectiveness can be rapidly predicted. The procedures developed enable prediction of power-on longitudinal stability characteristics that are generally in very good agreement with experiment.

Prediction of Imagined Single-Joint Movements in a Person with High Level Tetraplegia

PubMed Central

Simeral, John D.; Donoghue, John P.; Hochberg, Leigh R.; Kirsch, Robert F.

2013-01-01

Cortical neuroprostheses for movement restoration require developing models for relating neural activity to desired movement. Previous studies have focused on correlating single-unit activities (SUA) in primary motor cortex to volitional arm movements in able-bodied primates. The extent of the cortical information relevant to arm movements remaining in severely paralyzed individuals is largely unknown. We record intracortical signals using a microelectrode array chronically implanted in the precentral gyrus of a person with tetraplegia, and estimate positions of imagined single-joint arm movements. Using visually guided motor imagery, the participant imagined performing eight distinct single-joint arm movements while SUA, multi-spike trains (MSP), multi-unit activity (MUA), and local field potential time (LFPrms) and frequency signals (LFPstft) were recorded. Using linear system identification, imagined joint trajectories were estimated with 20 – 60% variance explained, with wrist flexion/extension predicted the best and pronation/supination the poorest. Statistically, decoding of MSP and LFPstft yielded estimates that equaled those of SUA. Including multiple signal types in a decoder increased prediction accuracy in all cases. We conclude that signals recorded from a single restricted region of the precentral gyrus in this person with tetraplegia contained useful information regarding the intended movements of upper extremity joints. PMID:22851229

Predicting the Coupling Properties of Axially-Textured Materials.

PubMed

Fuentes-Cobas, Luis E; Muñoz-Romero, Alejandro; Montero-Cabrera, María E; Fuentes-Montero, Luis; Fuentes-Montero, María E

2013-10-30

A description of methods and computer programs for the prediction of "coupling properties" in axially-textured polycrystals is presented. Starting data are the single-crystal properties, texture and stereography. The validity and proper protocols for applying the Voigt, Reuss and Hill approximations to estimate coupling properties effective values is analyzed. Working algorithms for predicting mentioned averages are given. Bunge's symmetrized spherical harmonics expansion of orientation distribution functions, inverse pole figures and (single and polycrystals) physical properties is applied in all stages of the proposed methodology. The established mathematical route has been systematized in a working computer program. The discussion of piezoelectricity in a representative textured ferro-piezoelectric ceramic illustrates the application of the proposed methodology. Polycrystal coupling properties, predicted by the suggested route, are fairly close to experimentally measured ones.

Predicting the Coupling Properties of Axially-Textured Materials

PubMed Central

Fuentes-Cobas, Luis E.; Muñoz-Romero, Alejandro; Montero-Cabrera, María E.; Fuentes-Montero, Luis; Fuentes-Montero, María E.

2013-01-01

A description of methods and computer programs for the prediction of “coupling properties” in axially-textured polycrystals is presented. Starting data are the single-crystal properties, texture and stereography. The validity and proper protocols for applying the Voigt, Reuss and Hill approximations to estimate coupling properties effective values is analyzed. Working algorithms for predicting mentioned averages are given. Bunge’s symmetrized spherical harmonics expansion of orientation distribution functions, inverse pole figures and (single and polycrystals) physical properties is applied in all stages of the proposed methodology. The established mathematical route has been systematized in a working computer program. The discussion of piezoelectricity in a representative textured ferro-piezoelectric ceramic illustrates the application of the proposed methodology. Polycrystal coupling properties, predicted by the suggested route, are fairly close to experimentally measured ones. PMID:28788370

A Comparison of Metamodeling Techniques via Numerical Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2016-01-01

This paper presents a comparative analysis of a few metamodeling techniques using numerical experiments for the single input-single output case. These experiments enable comparing the models' predictions with the phenomenon they are aiming to describe as more data is made available. These techniques include (i) prediction intervals associated with a least squares parameter estimate, (ii) Bayesian credible intervals, (iii) Gaussian process models, and (iv) interval predictor models. Aspects being compared are computational complexity, accuracy (i.e., the degree to which the resulting prediction conforms to the actual Data Generating Mechanism), reliability (i.e., the probability that new observations will fall inside the predicted interval), sensitivity to outliers, extrapolation properties, ease of use, and asymptotic behavior. The numerical experiments describe typical application scenarios that challenge the underlying assumptions supporting most metamodeling techniques.

University Students from Single-Sex and Coeducational High Schools: Differences in Majors and Attitudes at a Catholic University

ERIC Educational Resources Information Center

Karpiak, Christie P.; Buchanan, James P.; Hosey, Megan; Smith, Allison

2007-01-01

We conducted an archival study at a coeducational Catholic university to test the proposition that single-sex secondary education predicts lasting differences in college majors. Men from single-sex schools were more likely to both declare and graduate in gender-neutral majors than those from coeducational schools. Women from single-sex schools…

Predicting lymphatic filariasis transmission and elimination dynamics using a multi-model ensemble framework.

PubMed

Smith, Morgan E; Singh, Brajendra K; Irvine, Michael A; Stolk, Wilma A; Subramanian, Swaminathan; Hollingsworth, T Déirdre; Michael, Edwin

2017-03-01

Mathematical models of parasite transmission provide powerful tools for assessing the impacts of interventions. Owing to complexity and uncertainty, no single model may capture all features of transmission and elimination dynamics. Multi-model ensemble modelling offers a framework to help overcome biases of single models. We report on the development of a first multi-model ensemble of three lymphatic filariasis (LF) models (EPIFIL, LYMFASIM, and TRANSFIL), and evaluate its predictive performance in comparison with that of the constituents using calibration and validation data from three case study sites, one each from the three major LF endemic regions: Africa, Southeast Asia and Papua New Guinea (PNG). We assessed the performance of the respective models for predicting the outcomes of annual MDA strategies for various baseline scenarios thought to exemplify the current endemic conditions in the three regions. The results show that the constructed multi-model ensemble outperformed the single models when evaluated across all sites. Single models that best fitted calibration data tended to do less well in simulating the out-of-sample, or validation, intervention data. Scenario modelling results demonstrate that the multi-model ensemble is able to compensate for variance between single models in order to produce more plausible predictions of intervention impacts. Our results highlight the value of an ensemble approach to modelling parasite control dynamics. However, its optimal use will require further methodological improvements as well as consideration of the organizational mechanisms required to ensure that modelling results and data are shared effectively between all stakeholders. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Evaluation of global climate model on performances of precipitation simulation and prediction in the Huaihe River basin

NASA Astrophysics Data System (ADS)

Wu, Yenan; Zhong, Ping-an; Xu, Bin; Zhu, Feilin; Fu, Jisi

2017-06-01

Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960-2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001-2010) and the predicting period (2011-2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.

A Multi-wavenumber Theory for Eddy Diffusivities: Applications to the DIMES Region

NASA Astrophysics Data System (ADS)

Chen, R.; Gille, S. T.; McClean, J.; Flierl, G.; Griesel, A.

2014-12-01

Climate models are sensitive to the representation of ocean mixing processes. This has motivated recent efforts to collect observations aimed at improving mixing estimates and parameterizations. The US/UK field program Diapycnal and Isopycnal Mixing Experiment in the Southern Ocean (DIMES), begun in 2009, is providing such estimates upstream of and within the Drake Passage. This region is characterized by topography, and strong zonal jets. In previous studies, mixing length theories, based on the assumption that eddies are dominated by a single wavenumber and phase speed, were formulated to represent the estimated mixing patterns in jets. However, in spite of the success of the single wavenumber theory in some other scenarios, it does not effectively predict the vertical structures of observed eddy diffusivities in the DIMES area. Considering that eddy motions encompass a wide range of wavenumbers, which all contribute to mixing, in this study we formulated a multi-wavenumber theory to predict eddy mixing rates. We test our theory for a domain encompassing the entire Southern Ocean. We estimated eddy diffusivities and mixing lengths from one million numerical floats in a global eddying model. These float-based mixing estimates were compared with the predictions from both the single-wavenumber and the multi-wavenumber theories. Our preliminary results in the DIMES area indicate that, compared to the single-wavenumber theory, the multi-wavenumber theory better predicts the vertical mixing structures in the vast areas where the mean flow is weak; however in the intense jet region, both theories have similar predictive skill.

Effectiveness of repeated examination to diagnose enterobiasis in nursery school groups.

PubMed

Remm, Mare; Remm, Kalle

2009-09-01

The aim of this study was to estimate the benefit from repeated examinations in the diagnosis of enterobiasis in nursery school groups, and to test the effectiveness of individual-based risk predictions using different methods. A total of 604 children were examined using double, and 96 using triple, anal swab examinations. The questionnaires for parents, structured observations, and interviews with supervisors were used to identify factors of possible infection risk. In order to model the risk of enterobiasis at individual level, a similarity-based machine learning and prediction software Constud was compared with data mining methods in the Statistica 8 Data Miner software package. Prevalence according to a single examination was 22.5%; the increase as a result of double examinations was 8.2%. Single swabs resulted in an estimated prevalence of 20.1% among children examined 3 times; double swabs increased this by 10.1%, and triple swabs by 7.3%. Random forest classification, boosting classification trees, and Constud correctly predicted about 2/3 of the results of the second examination. Constud estimated a mean prevalence of 31.5% in groups. Constud was able to yield the highest overall fit of individual-based predictions while boosting classification tree and random forest models were more effective in recognizing Enterobius positive persons. As a rule, the actual prevalence of enterobiasis is higher than indicated by a single examination. We suggest using either the values of the mean increase in prevalence after double examinations compared to single examinations or group estimations deduced from individual-level modelled risk predictions.

Effectiveness of Repeated Examination to Diagnose Enterobiasis in Nursery School Groups

PubMed Central

Remm, Kalle

2009-01-01

The aim of this study was to estimate the benefit from repeated examinations in the diagnosis of enterobiasis in nursery school groups, and to test the effectiveness of individual-based risk predictions using different methods. A total of 604 children were examined using double, and 96 using triple, anal swab examinations. The questionnaires for parents, structured observations, and interviews with supervisors were used to identify factors of possible infection risk. In order to model the risk of enterobiasis at individual level, a similarity-based machine learning and prediction software Constud was compared with data mining methods in the Statistica 8 Data Miner software package. Prevalence according to a single examination was 22.5%; the increase as a result of double examinations was 8.2%. Single swabs resulted in an estimated prevalence of 20.1% among children examined 3 times; double swabs increased this by 10.1%, and triple swabs by 7.3%. Random forest classification, boosting classification trees, and Constud correctly predicted about 2/3 of the results of the second examination. Constud estimated a mean prevalence of 31.5% in groups. Constud was able to yield the highest overall fit of individual-based predictions while boosting classification tree and random forest models were more effective in recognizing Enterobius positive persons. As a rule, the actual prevalence of enterobiasis is higher than indicated by a single examination. We suggest using either the values of the mean increase in prevalence after double examinations compared to single examinations or group estimations deduced from individual-level modelled risk predictions. PMID:19724696

Comparing Binaural Pre-processing Strategies III

PubMed Central

Warzybok, Anna; Ernst, Stephan M. A.

2015-01-01

A comprehensive evaluation of eight signal pre-processing strategies, including directional microphones, coherence filters, single-channel noise reduction, binaural beamformers, and their combinations, was undertaken with normal-hearing (NH) and hearing-impaired (HI) listeners. Speech reception thresholds (SRTs) were measured in three noise scenarios (multitalker babble, cafeteria noise, and single competing talker). Predictions of three common instrumental measures were compared with the general perceptual benefit caused by the algorithms. The individual SRTs measured without pre-processing and individual benefits were objectively estimated using the binaural speech intelligibility model. Ten listeners with NH and 12 HI listeners participated. The participants varied in age and pure-tone threshold levels. Although HI listeners required a better signal-to-noise ratio to obtain 50% intelligibility than listeners with NH, no differences in SRT benefit from the different algorithms were found between the two groups. With the exception of single-channel noise reduction, all algorithms showed an improvement in SRT of between 2.1 dB (in cafeteria noise) and 4.8 dB (in single competing talker condition). Model predictions with binaural speech intelligibility model explained 83% of the measured variance of the individual SRTs in the no pre-processing condition. Regarding the benefit from the algorithms, the instrumental measures were not able to predict the perceptual data in all tested noise conditions. The comparable benefit observed for both groups suggests a possible application of noise reduction schemes for listeners with different hearing status. Although the model can predict the individual SRTs without pre-processing, further development is necessary to predict the benefits obtained from the algorithms at an individual level. PMID:26721922

Genomic Selection in Multi-environment Crop Trials.

PubMed

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

Multiple dynamics in a single predator-prey system: experimental effects of food quality.

PubMed Central

Nelson, W A; McCauley, E; Wrona, F J

2001-01-01

Recent work with the freshwater zooplankton Daphnia has suggested that the quality of its algal prey can have a significant effect on its demographic rates and life-history patterns. Predator-prey theory linking food quantity and food quality predicts that a single system should be able to display two distinct patterns of population dynamics. One pattern is predicted to have high herbivore and low algal biomass dynamics (high HBD), whereas the other is predicted to have low herbivore and high algal biomass dynamics (low HBD). Despite these predictions and the stoichiometric evidence that many phytoplankton communities may have poor access to food of quality, there have been few tests of whether a dynamic predator-prey system can display both of these distinct patterns. Here we report, to the authors' knowledge, the first evidence for two dynamical patterns, as predicted by theory, in a single predator-prey system. We show that the high HBD is a result of food quantity effects and that the low HBD is a result of food quality effects, which are maintained by phosphorus limitation in the predator. These results provide an important link between the known effects of nutrient limitation in herbivores and the significance of prey quality in predator-prey population dynamics in natural zooplankton communities. PMID:11410147

Male production in stingless bees: variable outcomes of queen-worker conflict.

PubMed

Tóth, Eva; Strassmann, Joan E; Nogueira-Neto, Paulo; Imperatriz-Fonseca, Vera L; Queller, David C

2002-12-01

The genetic structure of social insect colonies is predicted to affect the balance between cooperation and conflict. Stingless bees are of special interest in this respect because they are singly mated relatives of the multiply mated honeybees. Multiple mating is predicted to lead to workers policing each others' male production with the result that virtually all males are produced by the queen, and this prediction is borne out in honey bees. Single mating by the queen, as in stingless bees, causes workers to be more related to each others' sons than to the queen's sons, so they should not police each other. We used microsatellite markers to confirm single mating in eight species of stingless bees and then tested the prediction that workers would produce males. Using a likelihood method, we found some worker male production in six of the eight species, although queens produced some males in all of them. Thus the predicted contrast with honeybees is observed, but not perfectly, perhaps because workers either lack complete control or because of costs of conflict. The data are consistent with the view that there is ongoing conflict over male production. Our method of estimating worker male production appears to be more accurate than exclusion, which sometimes underestimates the proportion of males that are worker produced.

Analyzing System on A Chip Single Event Upset Responses using Single Event Upset Data, Classical Reliability Models, and Space Environment Data

NASA Technical Reports Server (NTRS)

Berg, Melanie; LaBel, Kenneth; Campola, Michael; Xapsos, Michael

2017-01-01

We are investigating the application of classical reliability performance metrics combined with standard single event upset (SEU) analysis data. We expect to relate SEU behavior to system performance requirements. Our proposed methodology will provide better prediction of SEU responses in harsh radiation environments with confidence metrics. single event upset (SEU), single event effect (SEE), field programmable gate array devises (FPGAs)

Normalization and extension of single-collector efficiency correlation equation

NASA Astrophysics Data System (ADS)

Messina, Francesca; Marchisio, Daniele; Sethi, Rajandrea

2015-04-01

The colloidal transport and deposition are important phenomena involved in many engineering problems. In the environmental engineering field the use of micro- and nano-scale zerovalent iron (M-NZVI) is one of the most promising technologies for groundwater remediation. Colloid deposition is normally studied from a micro scale point of view and the results are then implemented in macro scale models that are used to design field-scale applications. The single collector efficiency concept predicts particles deposition onto a single grain of a complex porous medium in terms of probability that an approaching particle would be retained on the solid grain. In literature, many different approaches and equations exist to predict it, but most of them fail under specific conditions (e.g. very small or very big particle size and very low fluid velocity) because they predict efficiency values exceeding unity. By analysing particle fluxes and deposition mechanisms and performing a mass balance on the entire domain, the traditional definition of efficiency was reformulated and a novel total flux normalized correlation equation is proposed for predicting single-collector efficiency under a broad range of parameters. It has been formulated starting from a combination of Eulerian and Lagrangian numerical simulations, performed under Smoluchowski-Levich conditions, in a geometry which consists of a sphere enveloped by a control volume. In order to guarantee the independence of each term, the correlation equation is derived through a rigorous hierarchical parameter estimation process, accounting for single and mutual interacting transport mechanisms. The correlation equation provides efficiency values lower than one over a wide range of parameters and is valid both for point and finite-size particles. A reduced form is also proposed by elimination of the less relevant terms. References 1. Yao, K. M.; Habibian, M. M.; Omelia, C. R., Water and Waste Water Filtration - Concepts and Applications. Environ Sci Technol 1971, 5, (11), 1105-&. 2. Tufenkji, N., and M. Elimelech, Correlation equation for predicting single-collector efficiency in physicochemical filtration in saturated porous media. Environmental Science & Technology 2004 38(2):529-536. 3. Boccardo, G.; Marchisio, D. L.; Sethi, R., Microscale simulation of particle deposition in porous media. J Colloid Interface Sci 2014, 417, 227-37

Particle-laden weakly swirling free jets: Measurements and predictions. Ph.D. Thesis - Pennsylvania State Univ.

NASA Technical Reports Server (NTRS)

Bulzan, Daniel L.

1988-01-01

A theoretical and experimental investigation of particle-laden, weakly swirling, turbulent free jets was conducted. Glass particles, having a Sauter mean diameter of 39 microns, with a standard deviation of 15 microns, were used. A single loading ratio (the mass flow rate of particles per unit mass flow rate of air) of 0.2 was used in the experiments. Measurements are reported for three swirl numbers, ranging from 0 to 0.33. The measurements included mean and fluctuating velocities of both phases, and particle mass flux distributions. Measurements were also completed for single-phase non-swirling and swirling jets, as baselines. Measurements were compared with predictions from three types of multiphase flow analysis, as follows: (1) locally homogeneous flow (LHF) where slip between the phases was neglected; (2) deterministic separated flow (DSF), where slip was considered but effects of turbulence/particle interactions were neglected; and (3) stochastic separated flow (SSF), where effects of both interphase slip and turbulence/particle interactions were considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. Single-phase weakly swirling jets were considered first. Predictions using a standard k-epsilon turbulence model, as well as two versions modified to account for effects of streamline curvature, were compared with measurements. Predictions using a streamline curvature modification based on the flux Richardson number gave better agreement with measurements for the single-phase swirling jets than the standard k-epsilon model. For the particle-laden jets, the LHF and DSF models did not provide very satisfactory predictions. The LHF model generally overestimated the rate of decay of particle mean axial and angular velocities with streamwise distance, and predicted particle mass fluxes also showed poor agreement with measurements, due to the assumption of no-slip between phases. The DSF model also performed quite poorly for predictions of particle mass flux because turbulent dispersion of the particles was neglected. The SSF model, which accounts for both particle inertia and turbulent dispersion of the particles, yielded reasonably good predictions throughout the flow field for the particle-laden jets.

Population activity statistics dissect subthreshold and spiking variability in V1.

PubMed

Bányai, Mihály; Koman, Zsombor; Orbán, Gergő

2017-07-01

Response variability, as measured by fluctuating responses upon repeated performance of trials, is a major component of neural responses, and its characterization is key to interpret high dimensional population recordings. Response variability and covariability display predictable changes upon changes in stimulus and cognitive or behavioral state, providing an opportunity to test the predictive power of models of neural variability. Still, there is little agreement on which model to use as a building block for population-level analyses, and models of variability are often treated as a subject of choice. We investigate two competing models, the doubly stochastic Poisson (DSP) model assuming stochasticity at spike generation, and the rectified Gaussian (RG) model tracing variability back to membrane potential variance, to analyze stimulus-dependent modulation of both single-neuron and pairwise response statistics. Using a pair of model neurons, we demonstrate that the two models predict similar single-cell statistics. However, DSP and RG models have contradicting predictions on the joint statistics of spiking responses. To test the models against data, we build a population model to simulate stimulus change-related modulations in pairwise response statistics. We use single-unit data from the primary visual cortex (V1) of monkeys to show that while model predictions for variance are qualitatively similar to experimental data, only the RG model's predictions are compatible with joint statistics. These results suggest that models using Poisson-like variability might fail to capture important properties of response statistics. We argue that membrane potential-level modeling of stochasticity provides an efficient strategy to model correlations. NEW & NOTEWORTHY Neural variability and covariability are puzzling aspects of cortical computations. For efficient decoding and prediction, models of information encoding in neural populations hinge on an appropriate model of variability. Our work shows that stimulus-dependent changes in pairwise but not in single-cell statistics can differentiate between two widely used models of neuronal variability. Contrasting model predictions with neuronal data provides hints on the noise sources in spiking and provides constraints on statistical models of population activity. Copyright © 2017 the American Physiological Society.

The predictive value of single-photon emission computed tomography/computed tomography for sentinel lymph node localization in head and neck cutaneous malignancy.

PubMed

Remenschneider, Aaron K; Dilger, Amanda E; Wang, Yingbing; Palmer, Edwin L; Scott, James A; Emerick, Kevin S

2015-04-01

Preoperative localization of sentinel lymph nodes in head and neck cutaneous malignancies can be aided by single-photon emission computed tomography/computed tomography (SPECT/CT); however, its true predictive value for identifying lymph nodes intraoperatively remains unquantified. This study aims to understand the sensitivity, specificity, and positive and negative predictive values of SPECT/CT in sentinel lymph node biopsy for cutaneous malignancies of the head and neck. Blinded retrospective imaging review with comparison to intraoperative gamma probe confirmed sentinel lymph nodes. A consecutive series of patients with a head and neck cutaneous malignancy underwent preoperative SPECT/CT followed by sentinel lymph node biopsy with a gamma probe. Two nuclear medicine physicians, blinded to clinical data, independently reviewed each SPECT/CT. Activity within radiographically defined nodal basins was recorded and compared to intraoperative gamma probe findings. Sensitivity, specificity, and negative and positive predictive values were calculated with subgroup stratification by primary tumor site. Ninety-two imaging reads were performed on 47 patients with cutaneous malignancy who underwent SPECT/CT followed by sentinel lymph node biopsy. Overall sensitivity was 73%, specificity 92%, positive predictive value 54%, and negative predictive value 96%. The predictive ability of SPECT/CT to identify the basin or an adjacent basin containing the single hottest node was 92%. SPECT/CT overestimated uptake by an average of one nodal basin. In the head and neck, SPECT/CT has higher reliability for primary lesions of the eyelid, scalp, and cheek. SPECT/CT has high sensitivity, specificity, and negative predictive value, but may overestimate relevant nodal basins in sentinel lymph node biopsy. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Repeated Blood Pressure Measurements in Childhood in Prediction of Hypertension in Adulthood.

PubMed

Oikonen, Mervi; Nuotio, Joel; Magnussen, Costan G; Viikari, Jorma S A; Taittonen, Leena; Laitinen, Tomi; Hutri-Kähönen, Nina; Jokinen, Eero; Jula, Antti; Cheung, Michael; Sabin, Matthew A; Daniels, Stephen R; Raitakari, Olli T; Juonala, Markus

2016-01-01

Hypertension may be predicted from childhood risk factors. Repeated observations of abnormal blood pressure in childhood may enhance prediction of hypertension and subclinical atherosclerosis in adulthood compared with a single observation. Participants (1927, 54% women) from the Cardiovascular Risk in Young Finns Study had systolic and diastolic blood pressure measurements performed when aged 3 to 24 years. Childhood/youth abnormal blood pressure was defined as above 90th or 95th percentile. After a 21- to 31-year follow-up, at the age of 30 to 45 years, hypertension (>140/90 mm Hg or antihypertensive medication) prevalence was found to be 19%. Carotid intima-media thickness was examined, and high-risk intima-media was defined as intima-media thickness >90th percentile or carotid plaques. Prediction of adulthood hypertension and high-risk intima-media was compared between one observation of abnormal blood pressure in childhood/youth and multiple observations by improved Pearson correlation coefficients and area under the receiver operating curve. When compared with a single measurement, 2 childhood/youth observations improved the correlation for adult systolic (r=0.44 versus 0.35, P<0.001) and diastolic (r=0.35 versus 0.17, P<0.001) blood pressure. In addition, 2 abnormal childhood/youth blood pressure observations increased the prediction of hypertension in adulthood (0.63 for 2 versus 0.60 for 1 observation, P=0.003). When compared with 2 measurements, third observation did not provide any significant improvement for correlation or prediction (P always >0.05). A higher number of childhood/youth observations of abnormal blood pressure did not enhance prediction of adult high-risk intima-media thickness. Compared with a single measurement, the prediction of adult hypertension was enhanced by 2 observations of abnormal blood pressure in childhood/youth. © 2015 American Heart Association, Inc.

Single drug biomarker prediction for ER- breast cancer outcome from chemotherapy.

PubMed

Chen, Yong-Zi; Kim, Youngchul; Soliman, Hatem H; Ying, GuoGuang; Lee, Jae K

2018-06-01

ER-negative breast cancer includes most aggressive subtypes of breast cancer such as triple negative (TN) breast cancer. Excluded from hormonal and targeted therapies effectively used for other subtypes of breast cancer, standard chemotherapy is one of the primary treatment options for these patients. However, as ER- patients have shown highly heterogeneous responses to different chemotherapies, it has been difficult to select most beneficial chemotherapy treatments for them. In this study, we have simultaneously developed single drug biomarker models for four standard chemotherapy agents: paclitaxel (T), 5-fluorouracil (F), doxorubicin (A) and cyclophosphamide (C) to predict responses and survival of ER- breast cancer patients treated with combination chemotherapies. We then flexibly combined these individual drug biomarkers for predicting patient outcomes of two independent cohorts of ER- breast cancer patients who were treated with different drug combinations of neoadjuvant chemotherapy. These individual and combined drug biomarker models significantly predicted chemotherapy response for 197 ER- patients in the Hatzis cohort (AUC = 0.637, P  = 0.002) and 69 ER- patients in the Hess cohort (AUC = 0.635, P  = 0.056). The prediction was also significant for the TN subgroup of both cohorts (AUC = 0.60, 0.72, P  = 0.043, 0.009). In survival analysis, our predicted responder patients showed significantly improved survival with a >17 months longer median PFS than the predicted non-responder patients for both ER- and TN subgroups (log-rank test P -value = 0.018 and 0.044). This flexible prediction capability based on single drug biomarkers may allow us to even select new drug combinations most beneficial to individual patients with ER- breast cancer. © 2018 The authors.

Increased odds of patient-reported success at 2 years after anterior cruciate ligament reconstruction in patients without cartilage lesions: a cohort study from the Swedish National Knee Ligament Register.

PubMed

Hamrin Senorski, Eric; Alentorn-Geli, Eduard; Musahl, Volker; Fu, Freddie; Krupic, Ferid; Desai, Neel; Westin, Olof; Samuelsson, Kristian

2018-04-01

To investigate whether the surgical technique of single-bundle anterior cruciate ligament (ACL) reconstruction, the visualization of anatomic surgical factors and the presence or absence of concomitant injuries at primary ACL reconstruction are able to predict patient-reported success and failure. The hypothesis of this study was that anatomic single-bundle surgical procedures would be predictive of patient-reported success. This cohort study was based on data from the Swedish National Knee Ligament Register during the period of 1 January 2005 through 31 December 2014. Patients who underwent primary single-bundle ACL reconstruction with hamstring tendons were included. Details on surgical technique were collected using an online questionnaire comprising essential anatomic anterior cruciate ligament reconstruction scoring checklist items, defined as the utilization of accessory medial portal drilling, anatomic tunnel placement, the visualization of insertion sites and pertinent landmarks. A univariate logistic regression model adjusted for age and gender was used to determine predictors of patient-reported success and failure, i.e. 20th and 80th percentile, respectively, in the Knee injury and Osteoarthritis Outcome Score (KOOS), 2 years after ACL reconstruction. In the 6889 included patients, the surgical technique used for single-bundle ACL reconstruction did not predict the predefined patient-reported success or patient-reported failure in the KOOS 4 . Patient-reported success was predicted by the absence of concomitant injury to the meniscus (OR = 0.81 [95% CI, 0.72-0.92], p = 0.001) and articular cartilage (OR = 0.70 [95% CI, 0.61-0.81], p < 0.001). Patient-reported failure was predicted by the presence of a concomitant injury to the articular cartilage (OR = 1.27 [95% CI, 1.11-1.44], p < 0.001). Surgical techniques used in primary single-bundle ACL reconstruction did not predict the KOOS 2 years after the reconstruction. However, the absence of concomitant injuries at index surgery predicted patient-reported success in the KOOS. The results provide further evidence that concomitant injuries at ACL reconstruction affect subjective knee function and a detailed knowledge of the treatment of these concomitant injuries is needed. Retrospective cohort study, Level III.

Is Optimism Real?

ERIC Educational Resources Information Center

Simmons, Joseph P.; Massey, Cade

2012-01-01

Is optimism real, or are optimistic forecasts just cheap talk? To help answer this question, we investigated whether optimistic predictions persist in the face of large incentives to be accurate. We asked National Football League football fans to predict the winner of a single game. Roughly half (the partisans) predicted a game involving their…

Comparison of non-ideal solution theories for multi-solute solutions in cryobiology and tabulation of required coefficients.

PubMed

Zielinski, Michal W; McGann, Locksley E; Nychka, John A; Elliott, Janet A W

2014-10-01

Thermodynamic solution theories allow the prediction of chemical potentials in solutions of known composition. In cryobiology, such models are a critical component of many mathematical models that are used to simulate the biophysical processes occurring in cells and tissues during cryopreservation. A number of solution theories, both thermodynamically ideal and non-ideal, have been proposed for use with cryobiological solutions. In this work, we have evaluated two non-ideal solution theories for predicting water chemical potential (i.e. osmolality) in multi-solute solutions relevant to cryobiology: the Elliott et al. form of the multi-solute osmotic virial equation, and the Kleinhans and Mazur freezing point summation model. These two solution theories require fitting to only single-solute data, although they can make predictions in multi-solute solutions. The predictions of these non-ideal solution theories were compared to predictions made using ideal dilute assumptions and to available literature multi-solute experimental osmometric data. A single, consistent set of literature single-solute solution data was used to fit for the required solute-specific coefficients for each of the non-ideal models. Our results indicate that the two non-ideal solution theories have similar overall performance, and both give more accurate predictions than ideal models. These results can be used to select between the non-ideal models for a specific multi-solute solution, and the updated coefficients provided in this work can be used to make the desired predictions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Predictive discomfort in single- and combined-axis whole-body vibration considering different seated postures.

PubMed

DeShaw, Jonathan; Rahmatalla, Salam

2014-08-01

The aim of this study was to develop a predictive discomfort model in single-axis, 3-D, and 6-D combined-axis whole-body vibrations of seated occupants considering different postures. Non-neutral postures in seated whole-body vibration play a significant role in the resulting level of perceived discomfort and potential long-term injury. The current international standards address contact points but not postures. The proposed model computes discomfort on the basis of static deviation of human joints from their neutral positions and how fast humans rotate their joints under vibration. Four seated postures were investigated. For practical implications, the coefficients of the predictive discomfort model were changed into the Borg scale with psychophysical data from 12 volunteers in different vibration conditions (single-axis random fore-aft, lateral, and vertical and two magnitudes of 3-D). The model was tested under two magnitudes of 6-D vibration. Significant correlations (R = .93) were found between the predictive discomfort model and the reported discomfort with different postures and vibrations. The ISO 2631-1 correlated very well with discomfort (R2 = .89) but was not able to predict the effect of posture. Human discomfort in seated whole-body vibration with different non-neutral postures can be closely predicted by a combination of static posture and the angular velocities of the joint. The predictive discomfort model can assist ergonomists and human factors researchers design safer environments for seated operators under vibration. The model can be integrated with advanced computer biomechanical models to investigate the complex interaction between posture and vibration.

Anisotropic constitutive modeling for nickel-base single crystal superalloys. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Sheh, Michael Y.

1988-01-01

An anisotropic constitutive model was developed based on crystallographic slip theory for nickel base single crystal superalloys. The constitutive equations developed utilizes drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments were conducted to evaluate the existence of back stress in single crystal superalloy Rene N4 at 982 C. The results suggest that: (1) the back stress is orientation dependent; and (2) the back stress state variable is required for the current model to predict material anelastic recovery behavior. The model was evaluated for its predictive capability on single crystal material behavior including orientation dependent stress-strain response, tension/compression asymmetry, strain rate sensitivity, anelastic recovery behavior, cyclic hardening and softening, stress relaxation, creep and associated crystal lattice rotation. Limitation and future development needs are discussed.

Effect of gender composition of school on body concerns in adolescent women.

PubMed

Tiggemann, M

2001-03-01

This study aimed to investigate the role of gender composition of school on body figure preferences, eating disorder symptomology, and role concerns. Questionnaires were completed by 261 Australian adolescent girls in two private single-sex and two private coeducational school environments. There was no difference in nominated ideal figure or eating disorder scores between the schools. However, girls in the single-sex schools placed a greater emphasis on achievement than their counterparts at the coeducational schools. These role concerns had a differential impact on prediction of the ideal figure, whereby the importance placed on intelligence and professional success predicted the choice of a thinner ideal figure for the single-sex schools, but a larger ideal for the coeducational schools. It was concluded that the motivation for thinness differs between single-sex and coeducational schools.

Validation of Single-Item Screening Measures for Provider Burnout in a Rural Health Care Network.

PubMed

Waddimba, Anthony C; Scribani, Melissa; Nieves, Melinda A; Krupa, Nicole; May, John J; Jenkins, Paul

2016-06-01

We validated three single-item measures for emotional exhaustion (EE) and depersonalization (DP) among rural physician/nonphysician practitioners. We linked cross-sectional survey data (on provider demographics, satisfaction, resilience, and burnout) with administrative information from an integrated health care network (1 academic medical center, 6 community hospitals, 31 clinics, and 19 school-based health centers) in an eight-county underserved area of upstate New York. In total, 308 physicians and advanced-practice clinicians completed a self-administered, multi-instrument questionnaire (65.1% response rate). Significant proportions of respondents reported high EE (36.1%) and DP (9.9%). In multivariable linear mixed models, scores on EE/DP subscales of the Maslach Burnout Inventory were regressed on each single-item measure. The Physician Work-Life Study's single-item measure (classifying 32.8% of respondents as burning out/completely burned out) was correlated with EE and DP (Spearman's ρ = .72 and .41, p < .0001; Kruskal-Wallis χ(2) = 149.9 and 56.5, p < .0001, respectively). In multivariable models, it predicted high EE (but neither low EE nor low/high DP). EE/DP single items were correlated with parent subscales (Spearman's ρ = .89 and .81, p < .0001; Kruskal-Wallis χ(2) = 230.98 and 197.84, p < .0001, respectively). In multivariable models, the EE item predicted high/low EE, whereas the DP item predicted only low DP. Therefore, the three single-item measures tested varied in effectiveness as screeners for EE/DP dimensions of burnout. © The Author(s) 2015.

ISO Mid-Infrared Spectra of Reflection Nebulae

NASA Technical Reports Server (NTRS)

Werner, M.; Uchida, K.; Sellgren, K.; Houdashelt, M.

1999-01-01

Our goal is to test predictions of models attributing the IEFs to polycyclic aromatic hydrocarbons (PAHs). Interstellar models predict PAHs change from singly ionized to neutral as the UV intensity, Go, decreases.

Quantum limit of heat flow across a single electronic channel.

PubMed

Jezouin, S; Parmentier, F D; Anthore, A; Gennser, U; Cavanna, A; Jin, Y; Pierre, F

2013-11-01

Quantum physics predicts that there is a fundamental maximum heat conductance across a single transport channel and that this thermal conductance quantum, G(Q), is universal, independent of the type of particles carrying the heat. Such universality, combined with the relationship between heat and information, signals a general limit on information transfer. We report on the quantitative measurement of the quantum-limited heat flow for Fermi particles across a single electronic channel, using noise thermometry. The demonstrated agreement with the predicted G(Q) establishes experimentally this basic building block of quantum thermal transport. The achieved accuracy of below 10% opens access to many experiments involving the quantum manipulation of heat.

A crystallographic model for the tensile and fatigue response for Rene N4 at 982 C

NASA Technical Reports Server (NTRS)

Sheh, M. Y.; Stouffer, D. C.

1990-01-01

An anisotropic constitutive model based on crystallographic slip theory was formulated for nickel-base single-crystal superalloys. The current equations include both drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments have been conducted to evaluate the existence of back stress in single crystals. The results showed that the back stress effect of reverse inelastic flow on the unloading stress is orientation-dependent, and a back stress state variable in the inelastic flow equation is necessary for predicting inelastic behavior. Model correlations and predictions of experimental data are presented for the single crystal superalloy Rene N4 at 982 C.

Localized magnetism in liquid Al80Mn20 alloys: A first-principles investigation

NASA Astrophysics Data System (ADS)

Jakse, N.; LeBacq, O.; Pasturel, A.

2006-04-01

We present first-principles investigations of the formation of magnetic moments in liquid Al80Mn20 alloys as a function of temperature. We predict the existence of large magnetic moments on Mn atoms which are close to that of the single-impurity limit. The wide distribution of moments can be understood in terms of fluctuations in the local environment. Our calculations also predict that thermal expansion effects within the single-impurity model mainly explain the striking increase of magnetism with temperature.

Understanding the retention and fate prediction of copper ions in single and competitive system in two soils: An experimental and numerical investigation.

PubMed

Buragohain, Poly; Garg, Ankit; Feng, Song; Lin, Peng; Sreedeep, S

2018-09-01

The concept of sponge city has become very popular with major thrust on design of waste containment systems such as biofilter and green roofs. Factors that may influence pollutant ions retention in these systems will be soil type and also their interactions. The study investigated single and competitive interaction of copper in two soils and its influence on the fate prediction. Freundlich and Langmuir nonlinear isotherms were selected to quantify the retention results. Series of numerical simulations were conducted to model 1 D advection-dispersion transport for the two soils and analyse the role of isotherms. The results indicated that contaminant fate prediction of copper-soil interaction based on the two non-linear isotherms was different for both single and that in competition. Retardation factor obtained from Freundlich (R F ) isotherm predicts more than Langmuir (R La ). This observation is more explicit at the higher range of equilibrium concentration. Fate prediction based on retardation value obtained from retention isotherms exhibited some anomalous trends contradicting the experimental findings due to inherent assumptions in governing equations. The necessity to have an approximate assessment of contaminant concentration in the field to effectively use contaminant retention results for accurate fate prediction is highlighted here. The study is important for modellers in design or analysis of biolfilter system (sponge city), where multiple ions tend to exist in waste water. Copyright © 2018 Elsevier B.V. All rights reserved.

MQAPRank: improved global protein model quality assessment by learning-to-rank.

PubMed

Jing, Xiaoyang; Dong, Qiwen

2017-05-25

Protein structure prediction has achieved a lot of progress during the last few decades and a greater number of models for a certain sequence can be predicted. Consequently, assessing the qualities of predicted protein models in perspective is one of the key components of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, which could be roughly divided into three categories: single methods, quasi-single methods and clustering (or consensus) methods. Although these methods achieve much success at different levels, accurate protein model quality assessment is still an open problem. Here, we present the MQAPRank, a global protein model quality assessment program based on learning-to-rank. The MQAPRank first sorts the decoy models by using single method based on learning-to-rank algorithm to indicate their relative qualities for the target protein. And then it takes the first five models as references to predict the qualities of other models by using average GDT_TS scores between reference models and other models. Benchmarked on CASP11 and 3DRobot datasets, the MQAPRank achieved better performances than other leading protein model quality assessment methods. Recently, the MQAPRank participated in the CASP12 under the group name FDUBio and achieved the state-of-the-art performances. The MQAPRank provides a convenient and powerful tool for protein model quality assessment with the state-of-the-art performances, it is useful for protein structure prediction and model quality assessment usages.

mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2015-03-15

Proteins located in appropriate cellular compartments are of paramount importance to exert their biological functions. Prediction of protein subcellular localization by computational methods is required in the post-genomic era. Recent studies have been focusing on predicting not only single-location proteins but also multi-location proteins. However, most of the existing predictors are far from effective for tackling the challenges of multi-label proteins. This article proposes an efficient multi-label predictor, namely mPLR-Loc, based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins. Specifically, for each query protein, mPLR-Loc exploits the information from the Gene Ontology (GO) database by using its accession number (AC) or the ACs of its homologs obtained via BLAST. The frequencies of GO occurrences are used to construct feature vectors, which are then classified by an adaptive decision-based multi-label penalized logistic regression classifier. Experimental results based on two recent stringent benchmark datasets (virus and plant) show that mPLR-Loc remarkably outperforms existing state-of-the-art multi-label predictors. In addition to being able to rapidly and accurately predict subcellular localization of single- and multi-label proteins, mPLR-Loc can also provide probabilistic confidence scores for the prediction decisions. For readers' convenience, the mPLR-Loc server is available online (http://bioinfo.eie.polyu.edu.hk/mPLRLocServer). Copyright © 2014 Elsevier Inc. All rights reserved.

Protein single-model quality assessment by feature-based probability density functions.

PubMed

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Sensitivity to carbon dioxide in subjects with a single lifetime panic attack: possible clinical "bedside" predictive test for panic disorder after a first attack.

PubMed

Berzak, Elina; Reznik, Mila; Narsia, Oxana; Benjamin, Jonathan

2004-01-01

There is currently no way of knowing whether a patient who has recently had a single panic attack has incipient panic disorder. Sensitivity to carbon dioxide (CO2) is lower in healthy volunteers than in panic disorder patients. If this is also true of people who experience a single lifetime panic attack, it could be used as a prognostic test. Subjects with a single lifetime panic attack and subjects with panic disorder received an inhalation of 35% CO2. Subjects completed the panic symptoms scale (PSS), and also stated whether they considered that they had experienced an attack. None of 14 subjects with a single lifetime panic attack, compared to 7 of 17 subjects with panic disorder (P=.009), had an attack. The PSS also distinguished between the groups. The 35% CO2 challenge warrants further investigation as a predictive test after a first panic attack.

The best men are (not always) already taken: female preference for single versus attached males depends on conception risk.

PubMed

Bressan, Paola; Stranieri, Debora

2008-02-01

Because men of higher genetic quality tend to be poorer partners and parents than men of lower genetic quality, women may profit from securing a stable investment from the latter, while obtaining good genes via extrapair mating with the former. Only if conception occurs, however, do the evolutionary benefits of such a strategy overcome its costs. Accordingly, we predicted that (a) partnered women should prefer attached men, because such men are more likely than single men to have pair-bonding qualities, and hence to be good replacement partners, and (b) this inclination should reverse when fertility rises, because attached men are less available for impromptu sex than single men. In this study, 208 women rated the attractiveness of men described as single or attached. As predicted, partnered women favored attached men at the low-fertility phases of the menstrual cycle, but preferred single men (if masculine, i.e., advertising good genetic quality) when conception risk was high.

Binding configurations and intramolecular strain in single-molecule devices.

PubMed

Rascón-Ramos, Habid; Artés, Juan Manuel; Li, Yuanhui; Hihath, Joshua

2015-05-01

The development of molecular-scale electronic devices has made considerable progress over the past decade, and single-molecule transistors, diodes and wires have all been demonstrated. Despite this remarkable progress, the agreement between theoretically predicted conductance values and those measured experimentally remains limited. One of the primary reasons for these discrepancies lies in the difficulty to experimentally determine the contact geometry and binding configuration of a single-molecule junction. In this Article, we apply a small-amplitude, high-frequency, sinusoidal mechanical signal to a series of single-molecule devices during junction formation and breakdown. By measuring the current response at this frequency, it is possible to determine the most probable binding and contact configurations for the molecular junction at room temperature in solution, and to obtain information about how an applied strain is distributed within the molecular junction. These results provide insight into the complex configuration of single-molecule devices, and are in excellent agreement with previous predictions from theoretical models.

Accuracy of genomic breeding values in multibreed beef cattle populations derived from deregressed breeding values and phenotypes.

PubMed

Weber, K L; Thallman, R M; Keele, J W; Snelling, W M; Bennett, G L; Smith, T P L; McDaneld, T G; Allan, M F; Van Eenennaam, A L; Kuehn, L A

2012-12-01

Genomic selection involves the assessment of genetic merit through prediction equations that allocate genetic variation with dense marker genotypes. It has the potential to provide accurate breeding values for selection candidates at an early age and facilitate selection for expensive or difficult to measure traits. Accurate across-breed prediction would allow genomic selection to be applied on a larger scale in the beef industry, but the limited availability of large populations for the development of prediction equations has delayed researchers from providing genomic predictions that are accurate across multiple beef breeds. In this study, the accuracy of genomic predictions for 6 growth and carcass traits were derived and evaluated using 2 multibreed beef cattle populations: 3,358 crossbred cattle of the U.S. Meat Animal Research Center Germplasm Evaluation Program (USMARC_GPE) and 1,834 high accuracy bull sires of the 2,000 Bull Project (2000_BULL) representing influential breeds in the U.S. beef cattle industry. The 2000_BULL EPD were deregressed, scaled, and weighted to adjust for between- and within-breed heterogeneous variance before use in training and validation. Molecular breeding values (MBV) trained in each multibreed population and in Angus and Hereford purebred sires of 2000_BULL were derived using the GenSel BayesCπ function (Fernando and Garrick, 2009) and cross-validated. Less than 10% of large effect loci were shared between prediction equations trained on (USMARC_GPE) relative to 2000_BULL although locus effects were moderately to highly correlated for most traits and the traits themselves were highly correlated between populations. Prediction of MBV accuracy was low and variable between populations. For growth traits, MBV accounted for up to 18% of genetic variation in a pooled, multibreed analysis and up to 28% in single breeds. For carcass traits, MBV explained up to 8% of genetic variation in a pooled, multibreed analysis and up to 42% in single breeds. Prediction equations trained in multibreed populations were more accurate for Angus and Hereford subpopulations because those were the breeds most highly represented in the training populations. Accuracies were less for prediction equations trained in a single breed due to the smaller number of records derived from a single breed in the training populations.

The value of integrating pre-clinical data to predict nausea and vomiting risk in humans as illustrated by AZD3514, a novel androgen receptor modulator.

PubMed

Grant, Claire; Ewart, Lorna; Muthas, Daniel; Deavall, Damian; Smith, Simon A; Clack, Glen; Newham, Pete

2016-04-01

Nausea and vomiting are components of a complex mechanism that signals food avoidance and protection of the body against the absorption of ingested toxins. This response can also be triggered by pharmaceuticals. Predicting clinical nausea and vomiting liability for pharmaceutical agents based on pre-clinical data can be problematic as no single animal model is a universal predictor. Moreover, efforts to improve models are hampered by the lack of translational animal and human data in the public domain. AZD3514 is a novel, orally-administered compound that inhibits androgen receptor signaling and down-regulates androgen receptor expression. Here we have explored the utility of integrating data from several pre-clinical models to predict nausea and vomiting in the clinic. Single and repeat doses of AZD3514 resulted in emesis, salivation and gastrointestinal disturbances in the dog, and inhibited gastric emptying in rats after a single dose. AZD3514, at clinically relevant exposures, induced dose-responsive "pica" behaviour in rats after single and multiple daily doses, and induced retching and vomiting behaviour in ferrets after a single dose. We compare these data with the clinical manifestation of nausea and vomiting encountered in patients with castration-resistant prostate cancer receiving AZD3514. Our data reveal a striking relationship between the pre-clinical observations described and the experience of nausea and vomiting in the clinic. In conclusion, the emetic nature of AZD3514 was predicted across a range of pre-clinical models, and the approach presented provides a valuable framework for predicition of clinical nausea and vomiting. Copyright © 2016 Elsevier Inc. All rights reserved.

Testcross additive and dominance effects in best linear unbiased prediction of maize single-cross performance.

PubMed

Bernardo, R

1996-11-01

Best linear unbiased prediction (BLUP) has been found to be useful in maize (Zea mays L.) breeding. The advantage of including both testcross additive and dominance effects (Intralocus Model) in BLUP, rather than only testcross additive effects (Additive Model), has not been clearly demonstrated. The objective of this study was to compare the usefulness of Intralocus and Additive Models for BLUP of maize single-cross performance. Multilocation data from 1990 to 1995 were obtained from the hybrid testing program of Limagrain Genetics. Grain yield, moisture, stalk lodging, and root lodging of untested single crosses were predicted from (1) the performance of tested single crosses and (2) known genetic relationships among the parental inbreds. Correlations between predicted and observed performance were obtained with a delete-one cross-validation procedure. For the Intralocus Model, the correlations ranged from 0.50 to 0.66 for yield, 0.88 to 0.94 for moisture, 0.47 to 0.69 for stalk lodging, and 0.31 to 0.45 for root lodging. The BLUP procedure was consistently more effective with the Intralocus Model than with the Additive Model. When the Additive Model was used instead of the Intralocus Model, the reductions in the correlation were largest for root lodging (0.06-0.35), smallest for moisture (0.00-0.02), and intermediate for yield (0.02-0.06) and stalk lodging (0.02-0.08). The ratio of dominance variance (v D) to total genetic variance (v G) was highest for root lodging (0.47) and lowest for moisture (0.10). The Additive Model may be used if prior information indicates that VD for a given trait has little contribution to VG. Otherwise, the continued use of the Intralocus Model for BLUP of single-cross performance is recommended.

TRUNK LEAN DURING A SINGLE-LEG SQUAT IS ASSOCIATED WITH TRUNK LEAN DURING PITCHING.

PubMed

Plummer, Hillary A; Oliver, Gretchen D; Powers, Christopher M; Michener, Lori A

2018-02-01

Impaired trunk motion during pitching may be a risk factor for upper extremity injuries. Specifically, increased forces about the shoulder and elbow have been observed in pitchers with excessive contralateral trunk lean during pitching. Because of the difficulty in identifying abnormal trunk motions during a high-speed task such as pitching, a clinical screening test is needed to identify pitchers who have impaired trunk motion during pitching. The purpose of this study was to determine the relationship between the degree of lateral trunk lean during the single-leg squat and amount of trunk lean during pitching and if trunk lean during pitching can be predicted from lean during the single-leg squat. Controlled Laboratory Study; Cross-sectional. Seventy-three young baseball pitchers (11.4 ± 1.7 years; 156.3 ± 11.9 cm; 50.5 ± 8.8 kg) participated. An electromagnetic tracking system was used to obtain trunk kinematic data during a single-leg squat task (lead leg) and at maximum shoulder external rotation of a fastball pitch. Pearson correlation coefficients for trunk lean during the single-leg squat and pitching were calculated. A linear regression analysis was performed to determine if trunk lean during pitching can be predicted from lean during the single-leg squat. There was a positive correlation between trunk lean during the single-leg squat and trunk lean during pitching (r = 0.53; p<0.001). Lateral trunk lean during the single-leg squat predicted the amount of lateral trunk lean during pitching (R 2 = 0.28; p < 0.001). A moderate positive correlation was observed between trunk lean during an SLS and pitching. Trunk lean during the single-leg squat explained 28% of the variance in trunk lean during pitching. Diagnosis, level 3.

TRUNK LEAN DURING A SINGLE-LEG SQUAT IS ASSOCIATED WITH TRUNK LEAN DURING PITCHING

PubMed Central

Oliver, Gretchen D.; Powers, Christopher M.; Michener, Lori A.

2018-01-01

Background Impaired trunk motion during pitching may be a risk factor for upper extremity injuries. Specifically, increased forces about the shoulder and elbow have been observed in pitchers with excessive contralateral trunk lean during pitching. Because of the difficulty in identifying abnormal trunk motions during a high-speed task such as pitching, a clinical screening test is needed to identify pitchers who have impaired trunk motion during pitching. Hypothesis/Purpose The purpose of this study was to determine the relationship between the degree of lateral trunk lean during the single-leg squat and amount of trunk lean during pitching and if trunk lean during pitching can be predicted from lean during the single-leg squat. Study Design Controlled Laboratory Study; Cross-sectional. Methods Seventy-three young baseball pitchers (11.4 ± 1.7 years; 156.3 ± 11.9 cm; 50.5 ± 8.8 kg) participated. An electromagnetic tracking system was used to obtain trunk kinematic data during a single-leg squat task (lead leg) and at maximum shoulder external rotation of a fastball pitch. Pearson correlation coefficients for trunk lean during the single-leg squat and pitching were calculated. A linear regression analysis was performed to determine if trunk lean during pitching can be predicted from lean during the single-leg squat. Results There was a positive correlation between trunk lean during the single-leg squat and trunk lean during pitching (r = 0.53; p<0.001). Lateral trunk lean during the single-leg squat predicted the amount of lateral trunk lean during pitching (R2 = 0.28; p < 0.001). Conclusions A moderate positive correlation was observed between trunk lean during an SLS and pitching. Trunk lean during the single-leg squat explained 28% of the variance in trunk lean during pitching. Level of Evidence Diagnosis, level 3 PMID:29484242

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment

PubMed Central

2014-01-01

Background Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. Results MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Conclusions Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy. PMID:24731387

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment.

PubMed

Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

2014-04-15

Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

Structure, stability, and properties of the trans peroxo nitrate radical: the importance of nondynamic correlation.

PubMed

Dutta, Achintya Kumar; Dar, Manzoor; Vaval, Nayana; Pal, Sourav

2014-02-27

We report a comparative single-reference and multireference coupled-cluster investigation on the structure, potential energy surface, and IR spectroscopic properties of the trans peroxo nitrate radical, one of the key intermediates in stratospheric NOX chemistry. The previous single-reference ab initio studies predicted an unbound structure for the trans peroxo nitrate radical. However, our Fock space multireference coupled-cluster calculation confirms a bound structure for the trans peroxo nitrate radical, in accordance with the experimental results reported earlier. Further, the analysis of the potential energy surface in FSMRCC method indicates a well-behaved minima, contrary to the shallow minima predicted by the single-reference coupled-cluster method. The harmonic force field analysis, of various possible isomers of peroxo nitrate also reveals that only the trans structure leads to the experimentally observed IR peak at 1840 cm(-1). The present study highlights the critical importance of nondynamic correlation in predicting the structure and properties of high-energy stratospheric NOx radicals.

Using Single-trial EEG to Predict and Analyze Subsequent Memory

PubMed Central

Noh, Eunho; Herzmann, Grit; Curran, Tim; de Sa, Virginia R.

2013-01-01

We show that it is possible to successfully predict subsequent memory performance based on single-trial EEG activity before and during item presentation in the study phase. Two-class classification was conducted to predict subsequently remembered vs. forgotten trials based on subjects’ responses in the recognition phase. The overall accuracy across 18 subjects was 59.6 % by combining pre- and during-stimulus information. The single-trial classification analysis provides a dimensionality reduction method to project the high-dimensional EEG data onto a discriminative space. These projections revealed novel findings in the pre- and during-stimulus period related to levels of encoding. It was observed that the pre-stimulus information (specifically oscillatory activity between 25–35Hz) −300 to 0 ms before stimulus presentation and during-stimulus alpha (7–12 Hz) information between 1000–1400 ms after stimulus onset distinguished between recollection and familiarity while the during-stimulus alpha information and temporal information between 400–800 ms after stimulus onset mapped these two states to similar values. PMID:24064073

A linear shock cell model for jets of arbitrary exit geometry

NASA Technical Reports Server (NTRS)

Morris, P. J.; Bhat, T. R. S.; Chen, G.

1989-01-01

The shock cell structures of single supersonic non-ideally expanded jets with arbitrary exit geometry are studied. Both vortex sheets and realistic mean profiles are considered for the jet shear layer. The boundary element method is used to predict the shock spacing and screech tones in a vortex sheet model of a single jet. This formulation enables the calculations to be performed only on the vortex sheet. This permits the efficient and convenient study of complicated jet geometries. Results are given for circular, elliptic and rectangular jets and the results are compared with analysis and experiment. The agreement between the predictions and measurements is very good but depends on the assumptions made to predict the geometry of the fully expanded jet. A finite diffference technique is used to examine the effect of finite mixing layer thickness for a single jet. The finite thickness of the mixing layer is found to decrease the shock spacing by approximately 20 percent over the length of the jet potential core.

Early Numeracy Indicators: Examining Predictive Utility Across Years and States

ERIC Educational Resources Information Center

Conoyer, Sarah J.; Foegen, Anne; Lembke, Erica S.

2016-01-01

Two studies using similar methods in two states investigated the long-term predictive utility of two single-skill early numeracy Curriculum Based Measures (CBMs) and the degree to which they can adequately predict high-stakes test scores. Data were drawn from kindergarten and first-grade students. State standardized assessment data from the…

The Role of Multimodel Combination in Improving Streamflow Prediction

NASA Astrophysics Data System (ADS)

Arumugam, S.; Li, W.

2008-12-01

Model errors are the inevitable part in any prediction exercise. One approach that is currently gaining attention to reduce model errors is by optimally combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictability. In this study, we present a new approach to combine multiple hydrological models by evaluating their predictability contingent on the predictor state. We combine two hydrological models, 'abcd' model and Variable Infiltration Capacity (VIC) model, with each model's parameter being estimated by two different objective functions to develop multimodel streamflow predictions. The performance of multimodel predictions is compared with individual model predictions using correlation, root mean square error and Nash-Sutcliffe coefficient. To quantify precisely under what conditions the multimodel predictions result in improved predictions, we evaluate the proposed algorithm by testing it against streamflow generated from a known model ('abcd' model or VIC model) with errors being homoscedastic or heteroscedastic. Results from the study show that streamflow simulated from individual models performed better than multimodels under almost no model error. Under increased model error, the multimodel consistently performed better than the single model prediction in terms of all performance measures. The study also evaluates the proposed algorithm for streamflow predictions in two humid river basins from NC as well as in two arid basins from Arizona. Through detailed validation in these four sites, the study shows that multimodel approach better predicts the observed streamflow in comparison to the single model predictions.

Drug response in a genetically engineered mouse model of multiple myeloma is predictive of clinical efficacy

PubMed Central

Chesi, Marta; Matthews, Geoffrey M.; Garbitt, Victoria M.; Palmer, Stephen E.; Shortt, Jake; Lefebure, Marcus; Stewart, A. Keith; Johnstone, Ricky W.

2012-01-01

The attrition rate for anticancer drugs entering clinical trials is unacceptably high. For multiple myeloma (MM), we postulate that this is because of preclinical models that overemphasize the antiproliferative activity of drugs, and clinical trials performed in refractory end-stage patients. We validate the Vk*MYC transgenic mouse as a faithful model to predict single-agent drug activity in MM with a positive predictive value of 67% (4 of 6) for clinical activity, and a negative predictive value of 86% (6 of 7) for clinical inactivity. We identify 4 novel agents that should be prioritized for evaluation in clinical trials. Transplantation of Vk*MYC tumor cells into congenic mice selected for a more aggressive disease that models end-stage drug-resistant MM and responds only to combinations of drugs with single-agent activity in untreated Vk*MYC MM. We predict that combinations of standard agents, histone deacetylase inhibitors, bromodomain inhibitors, and hypoxia-activated prodrugs will demonstrate efficacy in the treatment of relapsed MM. PMID:22451422

Initial comparison of single cylinder Stirling engine computer model predictions with test results

NASA Technical Reports Server (NTRS)

Tew, R. C., Jr.; Thieme, L. G.; Miao, D.

1979-01-01

A NASA developed digital computer code for a Stirling engine, modelling the performance of a single cylinder rhombic drive ground performance unit (GPU), is presented and its predictions are compared to test results. The GPU engine incorporates eight regenerator/cooler units and the engine working space is modelled by thirteen control volumes. The model calculates indicated power and efficiency for a given engine speed, mean pressure, heater and expansion space metal temperatures and cooler water inlet temperature and flow rate. Comparison of predicted and observed powers implies that the reference pressure drop calculations underestimate actual pressure drop, possibly due to oil contamination in the regenerator/cooler units, methane contamination in the working gas or the underestimation of mechanical loss. For a working gas of hydrogen, the predicted values of brake power are from 0 to 6% higher than experimental values, and brake efficiency is 6 to 16% higher, while for helium the predicted brake power and efficiency are 2 to 15% higher than the experimental.

Morphological features of IFN-γ–stimulated mesenchymal stromal cells predict overall immunosuppressive capacity

PubMed Central

Klinker, Matthew W.; Marklein, Ross A.; Lo Surdo, Jessica L.; Wei, Cheng-Hong

2017-01-01

Human mesenchymal stromal cell (MSC) lines can vary significantly in their functional characteristics, and the effectiveness of MSC-based therapeutics may be realized by finding predictive features associated with MSC function. To identify features associated with immunosuppressive capacity in MSCs, we developed a robust in vitro assay that uses principal-component analysis to integrate multidimensional flow cytometry data into a single measurement of MSC-mediated inhibition of T-cell activation. We used this assay to correlate single-cell morphological data with overall immunosuppressive capacity in a cohort of MSC lines derived from different donors and manufacturing conditions. MSC morphology after IFN-γ stimulation significantly correlated with immunosuppressive capacity and accurately predicted the immunosuppressive capacity of MSC lines in a validation cohort. IFN-γ enhanced the immunosuppressive capacity of all MSC lines, and morphology predicted the magnitude of IFN-γ–enhanced immunosuppressive activity. Together, these data identify MSC morphology as a predictive feature of MSC immunosuppressive function. PMID:28283659

The vibration discomfort of standing people: evaluation of multi-axis vibration.

PubMed

Thuong, Olivier; Griffin, Michael J

2015-01-01

Few studies have investigated discomfort caused by multi-axis vibration and none has explored methods of predicting the discomfort of standing people from simultaneous fore-and-aft, lateral and vertical vibration of a floor. Using the method of magnitude estimation, 16 subjects estimated their discomfort caused by dual-axis and tri-axial motions (octave-bands centred on either 1 or 4 Hz with various magnitudes in the fore-and-aft, lateral and vertical directions) and the discomfort caused by single-axis motions. The method of predicting discomfort assumed in current standards (square-root of the sums of squares of the three components weighted according to their individual contributions to discomfort) provided reasonable predictions of the discomfort caused by multi-axis vibration. Improved predictions can be obtained for specific stimuli, but no single simple method will provide accurate predictions for all stimuli because the rate of growth of discomfort with increasing magnitude of vibration depends on the frequency and direction of vibration.

Within- and across-breed genomic predictions and genomic relationships for Western Pyrenees dairy sheep breeds Latxa, Manech, and Basco-Béarnaise.

PubMed

Legarra, A; Baloche, G; Barillet, F; Astruc, J M; Soulas, C; Aguerre, X; Arrese, F; Mintegi, L; Lasarte, M; Maeztu, F; Beltrán de Heredia, I; Ugarte, E

2014-05-01

Genotypes, phenotypes and pedigrees of 6 breeds of dairy sheep (including subdivisions of Latxa, Manech, and Basco-Béarnaise) from the Spain and France Western Pyrenees were used to estimate genetic relationships across breeds (together with genotypes from the Lacaune dairy sheep) and to verify by forward cross-validation single-breed or multiple-breed genetic evaluations. The number of rams genotyped fluctuated between 100 and 1,300 but generally represented the 10 last cohorts of progeny-tested rams within each breed. Genetic relationships were assessed by principal components analysis of the genomic relationship matrices and also by the conservation of linkage disequilibrium patterns at given physical distances in the genome. Genomic and pedigree-based evaluations used daughter yield performances of all rams, although some of them were not genotyped. A pseudo-single step method was used in this case for genomic predictions. Results showed a clear structure in blond and black breeds for Manech and Latxa, reflecting historical exchanges, and isolation of Basco-Béarnaise and Lacaune. Relatedness between any 2 breeds was, however, lower than expected. Single-breed genomic predictions had accuracies comparable with other breeds of dairy sheep or small breeds of dairy cattle. They were more accurate than pedigree predictions for 5 out of 6 breeds, with absolute increases in accuracy ranging from 0.05 to 0.30 points. They were significantly better, as assessed by bootstrapping of candidates, for 2 of the breeds. Predictions using multiple populations only marginally increased the accuracy for a couple of breeds. Pooling populations does not increase the accuracy of genomic evaluations in dairy sheep; however, single-breed genomic predictions are more accurate, even for small breeds, and make the consideration of genomic schemes in dairy sheep interesting. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Structure Predictions of Two Bauhinia variegata Lectins Reveal Patterns of C-Terminal Properties in Single Chain Legume Lectins

PubMed Central

Moreira, Gustavo M. S. G.; Conceição, Fabricio R.; McBride, Alan J. A.; Pinto, Luciano da S.

2013-01-01

Bauhinia variegata lectins (BVL-I and BVL-II) are single chain lectins isolated from the plant Bauhinia variegata. Single chain lectins undergo post-translational processing on its N-terminal and C-terminal regions, which determines their physiological targeting, carbohydrate binding activity and pattern of quaternary association. These two lectins are isoforms, BVL-I being highly glycosylated, and thus far, it has not been possible to determine their structures. The present study used prediction and validation algorithms to elucidate the likely structures of BVL-I and -II. The program Bhageerath-H was chosen from among three different structure prediction programs due to its better overall reliability. In order to predict the C-terminal region cleavage sites, other lectins known to have this modification were analysed and three rules were created: (1) the first amino acid of the excised peptide is small or hydrophobic; (2) the cleavage occurs after an acid, polar, or hydrophobic residue, but not after a basic one; and (3) the cleavage spot is located 5-8 residues after a conserved Leu amino acid. These rules predicted that BVL-I and –II would have fifteen C-terminal residues cleaved, and this was confirmed experimentally by Edman degradation sequencing of BVL-I. Furthermore, the C-terminal analyses predicted that only BVL-II underwent α-helical folding in this region, similar to that seen in SBA and DBL. Conversely, BVL-I and -II contained four conserved regions of a GS-I association, providing evidence of a previously undescribed X4+unusual oligomerisation between the truncated BVL-I and the intact BVL-II. This is the first report on the structural analysis of lectins from Bauhinia spp. and therefore is important for the characterisation C-terminal cleavage and patterns of quaternary association of single chain lectins. PMID:24260572

Structure predictions of two Bauhinia variegata lectins reveal patterns of C-terminal properties in single chain legume lectins.

PubMed

Moreira, Gustavo M S G; Conceição, Fabricio R; McBride, Alan J A; Pinto, Luciano da S

2013-01-01

Bauhinia variegata lectins (BVL-I and BVL-II) are single chain lectins isolated from the plant Bauhinia variegata. Single chain lectins undergo post-translational processing on its N-terminal and C-terminal regions, which determines their physiological targeting, carbohydrate binding activity and pattern of quaternary association. These two lectins are isoforms, BVL-I being highly glycosylated, and thus far, it has not been possible to determine their structures. The present study used prediction and validation algorithms to elucidate the likely structures of BVL-I and -II. The program Bhageerath-H was chosen from among three different structure prediction programs due to its better overall reliability. In order to predict the C-terminal region cleavage sites, other lectins known to have this modification were analysed and three rules were created: (1) the first amino acid of the excised peptide is small or hydrophobic; (2) the cleavage occurs after an acid, polar, or hydrophobic residue, but not after a basic one; and (3) the cleavage spot is located 5-8 residues after a conserved Leu amino acid. These rules predicted that BVL-I and -II would have fifteen C-terminal residues cleaved, and this was confirmed experimentally by Edman degradation sequencing of BVL-I. Furthermore, the C-terminal analyses predicted that only BVL-II underwent α-helical folding in this region, similar to that seen in SBA and DBL. Conversely, BVL-I and -II contained four conserved regions of a GS-I association, providing evidence of a previously undescribed X4+unusual oligomerisation between the truncated BVL-I and the intact BVL-II. This is the first report on the structural analysis of lectins from Bauhinia spp. and therefore is important for the characterisation C-terminal cleavage and patterns of quaternary association of single chain lectins.

Comparison of Alcohol Use Disorder Screens During College Athlete Pre-Participation Evaluations.

PubMed

Majka, Erek; Graves, Travis; Diaz, Vanessa A; Player, Marty S; Dickerson, Lori M; Gavin, Jennifer K; Wessell, Andrea

2016-05-01

The US Preventive Services Task Force (USPSTF) recommends screening adults for alcohol misuse, a challenge among young adults who may not have regular primary care. The pre-participation evaluation (PPE) provides an opportunity for screening, but traditional screening tools require extra time in an already busy visit. The objective of this study was to compare the 10-item Alcohol Use Disorders Identification Test (AUDIT) with a single-question alcohol misuse screen in a population of college-aged athletes. This cross-sectional study was performed during an athletic PPE clinic at a college in the Southeastern United States among athletes ages 18 years and older. Written AUDIT and single-question screen "How many times in the past year have you had X or more drinks in a day?" (five for men, four for women) asked orally were administered to each participant. Sensitivity, specificity, and positive and negative predictive values for the single-question screen were compared to AUDIT. A total of 225 athletes were screened; 60% were female; 29% screened positive by AUDIT; 59% positive by single-question instrument. Males were more likely to screen positive by both methods. Compared to the AUDIT, the brief single-question screen had 92% sensitivity for alcohol misuse and 55% specificity. The negative predictive value of the single-question screen was 95% compared to AUDIT. A single-question screen for alcohol misuse in college-aged athletes had a high sensitivity and negative predictive value compared to the more extensive AUDIT screen. Ease of administration of this screening tool is ideal for use within the pre-participation physical among college-aged athletes who may not seek regular medical care.

The Aeroacoustics of Supersonic Coaxial Jets

NASA Technical Reports Server (NTRS)

Dahl, Milo D.

1994-01-01

Instability waves have been established as the dominant source of mixing noise radiating into the downstream arc of a supersonic jet when the waves have phase velocities that are supersonic relative to ambient conditions. Recent theories for supersonic jet noise have used the concepts of growing and decaying linear instability waves for predicting radiated noise. This analysis is extended to the prediction of noise radiation from supersonic coaxial jets. Since the analysis requires a known mean flow and the coaxial jet mean flow is not described easily in terms of analytic functions, a numerical prediction is made for its development. The Reynolds averaged, compressible, boundary layer equations are solved using a mixing length turbulence model. Empirical correlations are developed for the effects of velocity and temperature ratios and Mach number. Both normal and inverted velocity profile coaxial jets are considered. Comparisons with measurements for both single and coaxial jets show good agreement. The results from mean flow and stability calculations are used to predict the noise radiation from coaxial jets with different operating conditions. Comparisons are made between different coaxial jets and a single equivalent jet with the same total thrust, mass flow, and exit area. Results indicate that normal velocity profile jets can have noise reductions compared to the single equivalent jet. No noise reductions are found for inverted velocity profile jets operated at the minimum noise condition compared to the single equivalent jet. However, it is inferred that changes in area ratio may provide noise reduction benefits for inverted velocity profile jets.

Single-cell RNA-seq of human induced pluripotent stem cells reveals cellular heterogeneity and cell state transitions between subpopulations.

PubMed

Nguyen, Quan; Lukowski, Samuel; Chiu, Han; Senabouth, Anne; Bruxner, Timothy; Christ, Angelika; Palpant, Nathan; Powell, Joseph

2018-05-11

Heterogeneity of cell states represented in pluripotent cultures have not been described at the transcriptional level. Since gene expression is highly heterogeneous between cells, single-cell RNA sequencing can be used to identify how individual pluripotent cells function. Here, we present results from the analysis of single-cell RNA sequencing data from 18,787 individual WTC CRISPRi human induced pluripotent stem cells. We developed an unsupervised clustering method, and through this identified four subpopulations distinguishable on the basis of their pluripotent state including: a core pluripotent population (48.3%), proliferative (47.8%), early-primed for differentiation (2.8%) and late-primed for differentiation (1.1%). For each subpopulation we were able to identify the genes and pathways that define differences in pluripotent cell states. Our method identified four discrete predictor gene sets comprised of 165 unique genes that denote the specific pluripotency states; and using these sets, we developed a multigenic machine learning prediction method to accurately classify single cells into each of the subpopulations. Compared against a set of established pluripotency markers, our method increases prediction accuracy by 10%, specificity by 20%, and explains a substantially larger proportion of deviance (up to 3-fold) from the prediction model. Finally, we developed an innovative method to predict cells transitioning between subpopulations, and support our conclusions with results from two orthogonal pseudotime trajectory methods. Published by Cold Spring Harbor Laboratory Press.

Non-integer expansion embedding techniques for reversible image watermarking

NASA Astrophysics Data System (ADS)

Xiang, Shijun; Wang, Yi

2015-12-01

This work aims at reducing the embedding distortion of prediction-error expansion (PE)-based reversible watermarking. In the classical PE embedding method proposed by Thodi and Rodriguez, the predicted value is rounded to integer number for integer prediction-error expansion (IPE) embedding. The rounding operation makes a constraint on a predictor's performance. In this paper, we propose a non-integer PE (NIPE) embedding approach, which can proceed non-integer prediction errors for embedding data into an audio or image file by only expanding integer element of a prediction error while keeping its fractional element unchanged. The advantage of the NIPE embedding technique is that the NIPE technique can really bring a predictor into full play by estimating a sample/pixel in a noncausal way in a single pass since there is no rounding operation. A new noncausal image prediction method to estimate a pixel with four immediate pixels in a single pass is included in the proposed scheme. The proposed noncausal image predictor can provide better performance than Sachnev et al.'s noncausal double-set prediction method (where data prediction in two passes brings a distortion problem due to the fact that half of the pixels were predicted with the watermarked pixels). In comparison with existing several state-of-the-art works, experimental results have shown that the NIPE technique with the new noncausal prediction strategy can reduce the embedding distortion for the same embedding payload.

Theoretical model of hardness anisotropy in brittle materials

NASA Astrophysics Data System (ADS)

Gao, Faming

2012-07-01

Anisotropy is prominent in the hardness test of single crystals. However, the anisotropic nature is not demonstrated quantitatively in previous hardness model. In this work, it is found that the electron transition energy per unit volume in the glide region and the orientation of glide region play critical roles in determining hardness value and hardness anisotropy for a single crystal material. We express the mathematical definition of hardness anisotropy through simple algebraic relations. The calculated Knoop hardnesses of the single crystals are in good agreement with observations. This theory, extended to polycrystalline materials by including hall-petch effect and quantum size effect, predicts that the polycrystalline diamond with low angle grain boundaries can be harder than single-crystal bulk diamond. Combining first-principles technique and the formula of hardness anisotropy the hardness of monoclinic M-carbon, orthorhombic W-carbon, Z-carbon, and T-carbon are predicted.

ProTSAV: A protein tertiary structure analysis and validation server.

PubMed

Singh, Ankita; Kaushik, Rahul; Mishra, Avinash; Shanker, Asheesh; Jayaram, B

2016-01-01

Quality assessment of predicted model structures of proteins is as important as the protein tertiary structure prediction. A highly efficient quality assessment of predicted model structures directs further research on function. Here we present a new server ProTSAV, capable of evaluating predicted model structures based on some popular online servers and standalone tools. ProTSAV furnishes the user with a single quality score in case of individual protein structure along with a graphical representation and ranking in case of multiple protein structure assessment. The server is validated on ~64,446 protein structures including experimental structures from RCSB and predicted model structures for CASP targets and from public decoy sets. ProTSAV succeeds in predicting quality of protein structures with a specificity of 100% and a sensitivity of 98% on experimentally solved structures and achieves a specificity of 88%and a sensitivity of 91% on predicted protein structures of CASP11 targets under 2Å.The server overcomes the limitations of any single server/method and is seen to be robust in helping in quality assessment. ProTSAV is freely available at http://www.scfbio-iitd.res.in/software/proteomics/protsav.jsp. Copyright © 2015 Elsevier B.V. All rights reserved.

Developments in Science and Technology.

DTIC Science & Technology

1980-01-01

control. Sucessful completion of the testing and cer- a single unduplicated track file, thereby reducing tification of readiness represents a...Navy shipboard surveillance radar systems Service Corp., is called the single radar performance has been successfully designed, developed, and tested at...for Navy deteciion/disclosure ranges. The single radar per- shipboard surveillance radar systems are reduced by formance prediction system can be

Child Sexual Abuse and Adult Romantic Adjustment: Comparison of Single- and Multiple-Indicator Measures

ERIC Educational Resources Information Center

Godbout, Natacha; Sabourin, Stephane; Lussier, Yvan

2009-01-01

This study compared the usefulness of single- and multiple-indicator strategies in a model examining the role of child sexual abuse (CSA) to predict later marital satisfaction through attachment and psychological distress. The sample included 1,092 women and men from a nonclinical population in cohabiting or marital relationships. The single-item…

Factors affecting GEBV accuracy with single-step Bayesian models.

PubMed

Zhou, Lei; Mrode, Raphael; Zhang, Shengli; Zhang, Qin; Li, Bugao; Liu, Jian-Feng

2018-01-01

A single-step approach to obtain genomic prediction was first proposed in 2009. Many studies have investigated the components of GEBV accuracy in genomic selection. However, it is still unclear how the population structure and the relationships between training and validation populations influence GEBV accuracy in terms of single-step analysis. Here, we explored the components of GEBV accuracy in single-step Bayesian analysis with a simulation study. Three scenarios with various numbers of QTL (5, 50, and 500) were simulated. Three models were implemented to analyze the simulated data: single-step genomic best linear unbiased prediction (GBLUP; SSGBLUP), single-step BayesA (SS-BayesA), and single-step BayesB (SS-BayesB). According to our results, GEBV accuracy was influenced by the relationships between the training and validation populations more significantly for ungenotyped animals than for genotyped animals. SS-BayesA/BayesB showed an obvious advantage over SSGBLUP with the scenarios of 5 and 50 QTL. SS-BayesB model obtained the lowest accuracy with the 500 QTL in the simulation. SS-BayesA model was the most efficient and robust considering all QTL scenarios. Generally, both the relationships between training and validation populations and LD between markers and QTL contributed to GEBV accuracy in the single-step analysis, and the advantages of single-step Bayesian models were more apparent when the trait is controlled by fewer QTL.

Predicting changes in cardiac myocyte contractility during early drug discovery with in vitro assays

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

Morton, M.J., E-mail: michael.morton@astrazeneca.com; Armstrong, D.; Abi Gerges, N.

2014-09-01

Cardiovascular-related adverse drug effects are a major concern for the pharmaceutical industry. Activity of an investigational drug at the L-type calcium channel could manifest in a number of ways, including changes in cardiac contractility. The aim of this study was to define which of the two assay technologies – radioligand-binding or automated electrophysiology – was most predictive of contractility effects in an in vitro myocyte contractility assay. The activity of reference and proprietary compounds at the L-type calcium channel was measured by radioligand-binding assays, conventional patch-clamp, automated electrophysiology, and by measurement of contractility in canine isolated cardiac myocytes. Activity inmore » the radioligand-binding assay at the L-type Ca channel phenylalkylamine binding site was most predictive of an inotropic effect in the canine cardiac myocyte assay. The sensitivity was 73%, specificity 83% and predictivity 78%. The radioligand-binding assay may be run at a single test concentration and potency estimated. The least predictive assay was automated electrophysiology which showed a significant bias when compared with other assay formats. Given the importance of the L-type calcium channel, not just in cardiac function, but also in other organ systems, a screening strategy emerges whereby single concentration ligand-binding can be performed early in the discovery process with sufficient predictivity, throughput and turnaround time to influence chemical design and address a significant safety-related liability, at relatively low cost. - Highlights: • The L-type calcium channel is a significant safety liability during drug discovery. • Radioligand-binding to the L-type calcium channel can be measured in vitro. • The assay can be run at a single test concentration as part of a screening cascade. • This measurement is highly predictive of changes in cardiac myocyte contractility.« less

Prediction of Human Cytochrome P450 Inhibition Using a Multitask Deep Autoencoder Neural Network.

PubMed

Li, Xiang; Xu, Youjun; Lai, Luhua; Pei, Jianfeng

2018-05-30

Adverse side effects of drug-drug interactions induced by human cytochrome P450 (CYP450) inhibition is an important consideration in drug discovery. It is highly desirable to develop computational models that can predict the inhibitive effect of a compound against a specific CYP450 isoform. In this study, we developed a multitask model for concurrent inhibition prediction of five major CYP450 isoforms, namely, 1A2, 2C9, 2C19, 2D6, and 3A4. The model was built by training a multitask autoencoder deep neural network (DNN) on a large dataset containing more than 13 000 compounds, extracted from the PubChem BioAssay Database. We demonstrate that the multitask model gave better prediction results than that of single-task models, previous reported classifiers, and traditional machine learning methods on an average of five prediction tasks. Our multitask DNN model gave average prediction accuracies of 86.4% for the 10-fold cross-validation and 88.7% for the external test datasets. In addition, we built linear regression models to quantify how the other tasks contributed to the prediction difference of a given task between single-task and multitask models, and we explained under what conditions the multitask model will outperform the single-task model, which suggested how to use multitask DNN models more effectively. We applied sensitivity analysis to extract useful knowledge about CYP450 inhibition, which may shed light on the structural features of these isoforms and give hints about how to avoid side effects during drug development. Our models are freely available at http://repharma.pku.edu.cn/deepcyp/home.php or http://www.pkumdl.cn/deepcyp/home.php .

Single-energy non-contrast hepatic steatosis criteria applied to virtual non-contrast images: is it still highly specific and positively predictive?

PubMed

Haji-Momenian, S; Parkinson, W; Khati, N; Brindle, K; Earls, J; Zeman, R K

2018-06-01

To determine the sensitivity, specificity, and predictive values of single-energy non-contrast hepatic steatosis criteria on dual-energy virtual non-contrast (VNC) images. Forty-eight computed tomography (CT) examinations, which included single-energy non-contrast (TNC) and contrast-enhanced dual-energy CT angiography (CTA) of the abdomen, were enrolled. VNC images were reconstructed from the CTA. Region of interest (ROI) attenuations were measured in the right and left hepatic lobes, spleen, and aorta on TNC and VNC images. The right and left hepatic lobes were treated as separate samples. Steatosis was diagnosed based on TNC liver attenuation of ≤40 HU or liver attenuation index (LAI) of ≤-10 HU, which are extremely specific and predictive for moderate to severe steatosis. The sensitivity, specificity, and predictive values of VNC images for steatosis were calculated. VNC-TNC deviations were correlated with aortic enhancement and patient water equivalent diameter (PWED). Thirty-two liver ROIs met steatosis criteria based on TNC attenuation; VNC attenuation had sensitivity, specificity, and a positive predictive value of 66.7%, 100%, and 100%, respectively. Twenty-one liver ROIs met steatosis criteria based on TNC LAI. VNC LAI had sensitivity, specificity, and positive predictive values of 61.9%, 90.7%, and 65%, respectively. Hepatic and splenic VNC-TNC deviations did not correlate with one another (R 2 =0.08), aortic enhancement (R 2 <0.06) or PWED (R 2 <0.09). Non-contrast hepatic attenuation criteria is extremely specific and positively predictive for moderate to severe steatosis on VNC reconstructions from the arterial phase. Hepatic attenuation performs better than LAI criteria. VNC deviations are independent of aortic enhancement and PWED. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Predictive value of painful popping for a posterior root tear of the medial meniscus in middle-aged to older Asian patients.

PubMed

Bae, Ji-Hoon; Paik, Nak Hwan; Park, Gyu-Won; Yoon, Jung-Ro; Chae, Dong-Ju; Kwon, Jae Ho; Kim, Jong In; Nha, Kyung-Wook

2013-03-01

The purpose of this study was to determine the accuracy, sensitivity, specificity, and predictive values of a single event of painful popping in the presence of a posterior root tear of the medial meniscus in middle-aged to older Asian patients. We conducted a retrospective review of medical records of 936 patients who underwent arthroscopic surgeries for an isolated medial meniscus tear between January 2000 and December 2010. There were 332 men and 604 women with a mean age of 41 years (range, 25 to 66 years). The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of a painful popping sensation for a posterior root tear of the medial meniscus were calculated. Arthroscopy confirmed the presence of posterior root tears of the medial menisci in 237 of 936 patients (25.3%). A single event of a painful popping sensation was present in 86 of these 936 patients (9.1%). Of these 86 patients with a painful popping sensation, 83 (96.5%) were categorized as having an isolated posterior root tear of the medial meniscus. The positive predictive value of a painful popping sensation in identifying a posterior root tear of the medial meniscus was 96.5%, the negative predictive value was 81.8%, the sensitivity was 35.0%, the specificity was 99.5%, and the diagnostic accuracy was 77.9%. A single event of painful popping can be a highly predictive clinical sign of a posterior root tear of the medial meniscus in the middle-aged to older Asian population. However, it has low sensitivity for the detection of a posterior root tear of the medial meniscus. Level IV, therapeutic case series. Copyright © 2013 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Analysis for predicting adiabatic wall temperatures with single hole coolant injection into a low speed crossflow

NASA Astrophysics Data System (ADS)

Wang, C. R.; Papell, S. S.; Graham, R. W.

Assuming the local adiabatic wall temperature equals the local total temperature in a low speed coolant mixing layer, integral conservation equations with and without the boundary layer effects are formulated for the mixing layer downstream of a single coolant injection hole oriented at a 30 degree angle to the crossflow. These equations are solved numerically to determine the center line local adiabatic wall temperature and the effective coolant coverage area. Comparison of the numerical results with an existing film cooling experiment indicates that the present analysis permits a simplified but reasonably accurate prediction of the centerline effectiveness and coolant coverage area downstream of a single hole crossflow streamwise injection at 30 degree inclination angle.

Analysis for predicting adiabatic wall temperatures with single hole coolant injection into a low speed crossflow

NASA Technical Reports Server (NTRS)

Wang, C. R.; Papell, S. S.; Graham, R. W.

1981-01-01

Assuming the local adiabatic wall temperature equals the local total temperature in a low speed coolant mixing layer, integral conservation equations with and without the boundary layer effects are formulated for the mixing layer downstream of a single coolant injection hole oriented at a 30 degree angle to the crossflow. These equations are solved numerically to determine the center line local adiabatic wall temperature and the effective coolant coverage area. Comparison of the numerical results with an existing film cooling experiment indicates that the present analysis permits a simplified but reasonably accurate prediction of the centerline effectiveness and coolant coverage area downstream of a single hole crossflow streamwise injection at 30 degree inclination angle.

Analysis for predicting adiabatic wall temperatures with single hole coolant injection into a low speed crossflow

NASA Astrophysics Data System (ADS)

Wang, C. R.; Papell, S. S.; Graham, R. W.

1981-03-01

Assuming the local adiabatic wall temperature equals the local total temperature in a low speed coolant mixing layer, integral conservation equations with and without the boundary layer effects are formulated for the mixing layer downstream of a single coolant injection hole oriented at a 30 degree angle to the crossflow. These equations are solved numerically to determine the center-line local adiabatic wall temperature and the effective coolant coverage area. Comparison of the numerical results with an existing film cooling experiment indicates that the present analysis permits a simplified but reasonably accurate prediction of the centerline effectiveness and coolant coverage area downstream of a single hole crossflow streamwise injection at 30-deg inclination angle.

Analysis for predicting adiabatic wall temperatures with single hole coolant injection into a low speed crossflow

NASA Technical Reports Server (NTRS)

Wang, C. R.; Papell, S. S.; Graham, R. W.

1981-01-01

Assuming the local adiabatic wall temperature equals the local total temperature in a low speed coolant mixing layer, integral conservation equations with and without the boundary layer effects are formulated for the mixing layer downstream of a single coolant injection hole oriented at a 30 degree angle to the crossflow. These equations are solved numerically to determine the center-line local adiabatic wall temperature and the effective coolant coverage area. Comparison of the numerical results with an existing film cooling experiment indicates that the present analysis permits a simplified but reasonably accurate prediction of the centerline effectiveness and coolant coverage area downstream of a single hole crossflow streamwise injection at 30-deg inclination angle.

Single-step methods for predicting orbital motion considering its periodic components

NASA Astrophysics Data System (ADS)

Lavrov, K. N.

1989-01-01

Modern numerical methods for integration of ordinary differential equations can provide accurate and universal solutions to celestial mechanics problems. The implicit single sequence algorithms of Everhart and multiple step computational schemes using a priori information on periodic components can be combined to construct implicit single sequence algorithms which combine their advantages. The construction and analysis of the properties of such algorithms are studied, utilizing trigonometric approximation of the solutions of differential equations containing periodic components. The algorithms require 10 percent more machine memory than the Everhart algorithms, but are twice as fast, and yield short term predictions valid for five to ten orbits with good accuracy and five to six times faster than algorithms using other methods.

A computational substrate for incentive salience.

PubMed

McClure, Samuel M; Daw, Nathaniel D; Montague, P Read

2003-08-01

Theories of dopamine function are at a crossroads. Computational models derived from single-unit recordings capture changes in dopaminergic neuron firing rate as a prediction error signal. These models employ the prediction error signal in two roles: learning to predict future rewarding events and biasing action choice. Conversely, pharmacological inhibition or lesion of dopaminergic neuron function diminishes the ability of an animal to motivate behaviors directed at acquiring rewards. These lesion experiments have raised the possibility that dopamine release encodes a measure of the incentive value of a contemplated behavioral act. The most complete psychological idea that captures this notion frames the dopamine signal as carrying 'incentive salience'. On the surface, these two competing accounts of dopamine function seem incommensurate. To the contrary, we demonstrate that both of these functions can be captured in a single computational model of the involvement of dopamine in reward prediction for the purpose of reward seeking.

Technology Solutions Case Study: Predicting Envelope Leakage in Attached Dwellings

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

None

2013-11-01

The most common method of measuring air leakage is to perform single (or solo) blower door pressurization and/or depressurization test. In detached housing, the single blower door test measures leakage to the outside. In attached housing, however, this “solo” test method measures both air leakage to the outside and air leakage between adjacent units through common surfaces. In an attempt to create a simplified tool for predicting leakage to the outside, Building America team Consortium for Advanced Residential Buildings (CARB) performed a preliminary statistical analysis on blower door test results from 112 attached dwelling units in four apartment complexes. Althoughmore » the subject data set is limited in size and variety, the preliminary analyses suggest significant predictors are present and support the development of a predictive model. Further data collection is underway to create a more robust prediction tool for use across different construction types, climate zones, and unit configurations.« less

Integrating alternative splicing detection into gene prediction.

PubMed

Foissac, Sylvain; Schiex, Thomas

2005-02-10

Alternative splicing (AS) is now considered as a major actor in transcriptome/proteome diversity and it cannot be neglected in the annotation process of a new genome. Despite considerable progresses in term of accuracy in computational gene prediction, the ability to reliably predict AS variants when there is local experimental evidence of it remains an open challenge for gene finders. We have used a new integrative approach that allows to incorporate AS detection into ab initio gene prediction. This method relies on the analysis of genomically aligned transcript sequences (ESTs and/or cDNAs), and has been implemented in the dynamic programming algorithm of the graph-based gene finder EuGENE. Given a genomic sequence and a set of aligned transcripts, this new version identifies the set of transcripts carrying evidence of alternative splicing events, and provides, in addition to the classical optimal gene prediction, alternative optimal predictions (among those which are consistent with the AS events detected). This allows for multiple annotations of a single gene in a way such that each predicted variant is supported by a transcript evidence (but not necessarily with a full-length coverage). This automatic combination of experimental data analysis and ab initio gene finding offers an ideal integration of alternatively spliced gene prediction inside a single annotation pipeline.

Single point estimation of phenytoin dosing: a reappraisal.

PubMed

Koup, J R; Gibaldi, M; Godolphin, W

1981-11-01

A previously proposed method for estimation of phenytoin dosing requirement using a single serum sample obtained 24 hours after intravenous loading dose (18 mg/Kg) has been re-evaluated. Using more realistic values for the volume of distribution of phenytoin (0.4 to 1.2 L/Kg), simulations indicate that the proposed method will fail to consistently predict dosage requirements. Additional simulations indicate that two samples obtained during the 24 hour interval following the iv loading dose could be used to more reliably predict phenytoin dose requirement. Because of the nonlinear relationship which exists between phenytoin dose administration rate (RO) and the mean steady state serum concentration (CSS), small errors in prediction of the required RO result in much larger errors in CSS.

Family Structure versus Family Relationships for Predicting to Substance Use/Abuse and Illegal Behavior.

ERIC Educational Resources Information Center

Friedman, Alfred S.; Terras, Arlene; Glassman, Kimberly

2000-01-01

Study looked at sample of African-American adolescent males to determine the degree to which family structure (e.g., single parent vs. two-parent families) vs. the nature of the family relationships predict sons' involvement in substance use/abuse and illegal behavior. Of 33 relationships measures analyzed, 3 predicted the degree of recent…

Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories

Treesearch

Steen Magnussen; Ronald E. McRoberts; Erkki O. Tomppo

2009-01-01

New model-based estimators of the uncertainty of pixel-level and areal k-nearest neighbour (knn) predictions of attribute Y from remotely-sensed ancillary data X are presented. Non-parametric functions predict Y from scalar 'Single Index Model' transformations of X. Variance functions generated...

Verification of elastic-wave static displacement in solids. [using ultrasonic techniques on Ge single crystals

NASA Technical Reports Server (NTRS)

Cantrell, J. H., Jr.; Winfree, W. P.

1980-01-01

The solution of the nonlinear differential equation which describes an initially sinusoidal finite-amplitude elastic wave propagating in a solid contains a static-displacement term in addition to the harmonic terms. The static-displacement amplitude is theoretically predicted to be proportional to the product of the squares of the driving-wave amplitude and the driving-wave frequency. The first experimental verification of the elastic-wave static displacement in a solid (the 111 direction of single-crystal germanium) is reported, and agreement is found with the theoretical predictions.

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

NASA Technical Reports Server (NTRS)

Kirtman, Ben P.; Min, Dughong; Infanti, Johnna M.; Kinter, James L., III; Paolino, Daniel A.; Zhang, Qin; vandenDool, Huug; Saha, Suranjana; Mendez, Malaquias Pena; Becker, Emily;

Bias in Prediction: A Test of Three Models with Elementary School Children

ERIC Educational Resources Information Center

Frazer, William G.; And Others

1975-01-01

Explores the differences among the traditional single-equation prediction model of test bias, the Cleary and the Thorndike model in a situation involving typical educational variables with young female and male children. (Author/DEP)

Allele-Specific Alternative mRNA processing (ASARP) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

A software pipeline for prediction of allele-specific alternative RNA processing events using single RNA-seq data. The current version focuses on prediction of alternative splicing and alternative polyadenylation modulated by genetic variants.

A REVIEW OF SINGLE SPECIES TOXICITY TESTS: ARE THE TESTS RELIABLE PREDICTORS OF AQUATIC ECOSYSTEM COMMUNITY RESPONSES?

EPA Science Inventory

This document provides a comprehensive review to evaluate the reliability of indicator species toxicity test results in predicting aquatic ecosystem impacts, also called the ecological relevance of laboratory single species toxicity tests.

Trends In Susceptibility To Single-Event Upset

NASA Technical Reports Server (NTRS)

Nichols, Donald K.; Price, William E.; Kolasinski, Wojciech A.; Koga, Rukotaro; Waskiewicz, Alvin E.; Pickel, James C.; Blandford, James T.

1989-01-01

Report provides nearly comprehensive body of data on single-event upsets due to irradiation by heavy ions. Combines new test data and previously published data from governmental and industrial laboratories. Clear trends emerge from data useful in predicting future performances of devices.

Boosting Contextual Information for Deep Neural Network Based Voice Activity Detection

DTIC Science & Technology

2015-02-01

multi-resolution stacking (MRS), which is a stack of ensemble classifiers. Each classifier in a building block inputs the concatenation of the predictions ...a base classifier in MRS, named boosted deep neural network (bDNN). bDNN first generates multiple base predictions from different contexts of a single...frame by only one DNN and then aggregates the base predictions for a better prediction of the frame, and it is different from computationally

Feelings of worthlessness during a single complicated major depressive episode predict postremission suicide attempt.

PubMed

Wakefield, J C; Schmitz, M F

2016-04-01

To establish which symptoms of major depressive episode (MDE) predict postremission suicide attempts in complicated single-episode cases. Using the nationally representative two-wave National Epidemiologic Survey on Alcohol and Related Conditions data set, we identified wave 1 lifetime single-episode MDE cases in which the episode remitted by the beginning of the wave 2 three-year follow-up period (N = 2791). The analytic sample was further limited to 'complicated' cases (N = 1872) known to have elevated suicide attempt rates, defined as having two or more of the following: suicidal ideation, marked role impairment, feeling worthless, psychomotor retardation, and prolonged (>6 months) duration. Logistic regression analyses showed that, after controlling for wave 1 suicide attempt which significantly predicted postremission suicide attempt (OR = 10.0), the additional complicated symptom 'feelings of worthlessness' during the wave 1 index episode significantly and very substantially predicted postremission suicide attempt (OR = 6.96). Neither wave 1 psychomotor retardation nor wave 1 suicidal ideation nor any of the other wave 1 depressive symptoms were significant predictors of wave 2 suicide attempt. Among depressive symptoms during an MDE, feelings of worthlessness is the only significant indicator of elevated risk of suicide attempt after the episode has remitted, beyond previous suicide attempts. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A statistical framework for applying RNA profiling to chemical hazard detection.

PubMed

Kostich, Mitchell S

2017-12-01

Use of 'omics technologies in environmental science is expanding. However, application is mostly restricted to characterizing molecular steps leading from toxicant interaction with molecular receptors to apical endpoints in laboratory species. Use in environmental decision-making is limited, due to difficulty in elucidating mechanisms in sufficient detail to make quantitative outcome predictions in any single species or in extending predictions to aquatic communities. Here we introduce a mechanism-agnostic statistical approach, supplementing mechanistic investigation by allowing probabilistic outcome prediction even when understanding of molecular pathways is limited, and facilitating extrapolation from results in laboratory test species to predictions about aquatic communities. We use concepts familiar to environmental managers, supplemented with techniques employed for clinical interpretation of 'omics-based biomedical tests. We describe the framework in step-wise fashion, beginning with single test replicates of a single RNA variant, then extending to multi-gene RNA profiling, collections of test replicates, and integration of complementary data. In order to simplify the presentation, we focus on using RNA profiling for distinguishing presence versus absence of chemical hazards, but the principles discussed can be extended to other types of 'omics measurements, multi-class problems, and regression. We include a supplemental file demonstrating many of the concepts using the open source R statistical package. Published by Elsevier Ltd.

Predicting the optimal process window for the coating of single-crystalline organic films with mobilities exceeding 7 cm2/Vs.

NASA Astrophysics Data System (ADS)

Janneck, Robby; Vercesi, Federico; Heremans, Paul; Genoe, Jan; Rolin, Cedric

2016-09-01

Organic thin film transistors (OTFTs) based on single crystalline thin films of organic semiconductors have seen considerable development in the recent years. The most successful method for the fabrication of single crystalline films are solution-based meniscus guided coating techniques such as dip-coating, solution shearing or zone casting. These upscalable methods enable rapid and efficient film formation without additional processing steps. The single-crystalline film quality is strongly dependent on solvent choice, substrate temperature and coating speed. So far, however, process optimization has been conducted by trial and error methods, involving, for example, the variation of coating speeds over several orders of magnitude. Through a systematic study of solvent phase change dynamics in the meniscus region, we develop a theoretical framework that links the optimal coating speed to the solvent choice and the substrate temperature. In this way, we can accurately predict an optimal processing window, enabling fast process optimization. Our approach is verified through systematic OTFT fabrication based on films grown with different semiconductors, solvents and substrate temperatures. The use of best predicted coating speeds delivers state of the art devices. In the case of C8BTBT, OTFTs show well-behaved characteristics with mobilities up to 7 cm2/Vs and onset voltages close to 0 V. Our approach also explains well optimal recipes published in the literature. This route considerably accelerates parameter screening for all meniscus guided coating techniques and unveils the physics of single crystalline film formation.

Scaling from single molecule to macroscopic adhesion at polymer/metal interfaces.

PubMed

Utzig, Thomas; Raman, Sangeetha; Valtiner, Markus

2015-03-10

Understanding the evolution of macroscopic adhesion based on fundamental molecular interactions is crucial to designing strong and smart polymer/metal interfaces that play an important role in many industrial and biomedical applications. Here we show how macroscopic adhesion can be predicted on the basis of single molecular interactions. In particular, we carry out dynamic single molecule-force spectroscopy (SM-AFM) in the framework of Bell-Evans' theory to gain information about the energy barrier between the bound and unbound states of an amine/gold junction. Furthermore, we use Jarzynski's equality to obtain the equilibrium ground-state energy difference of the amine/gold bond from these nonequilibrium force measurements. In addition, we perform surface forces apparatus (SFA) experiments to measure macroscopic adhesion forces at contacts where approximately 10(7) amine/gold bonds are formed simultaneously. The SFA approach provides an amine/gold interaction energy (normalized by the number of interacting molecules) of (36 ± 1)k(B)T, which is in excellent agreement with the interaction free energy of (35 ± 3)k(B)T calculated using Jarzynski's equality and single-molecule AFM experiments. Our results validate Jarzynski's equality for the field of polymer/metal interactions by measuring both sides of the equation. Furthermore, the comparison of SFA and AFM shows how macroscopic interaction energies can be predicted on the basis of single molecular interactions, providing a new strategy to potentially predict adhesive properties of novel glues or coatings as well as bio- and wet adhesion.

Anthology of the Development of Radiation Transport Tools as Applied to Single Event Effects

NASA Astrophysics Data System (ADS)

Reed, R. A.; Weller, R. A.; Akkerman, A.; Barak, J.; Culpepper, W.; Duzellier, S.; Foster, C.; Gaillardin, M.; Hubert, G.; Jordan, T.; Jun, I.; Koontz, S.; Lei, F.; McNulty, P.; Mendenhall, M. H.; Murat, M.; Nieminen, P.; O'Neill, P.; Raine, M.; Reddell, B.; Saigné, F.; Santin, G.; Sihver, L.; Tang, H. H. K.; Truscott, P. R.; Wrobel, F.

2013-06-01

This anthology contains contributions from eleven different groups, each developing and/or applying Monte Carlo-based radiation transport tools to simulate a variety of effects that result from energy transferred to a semiconductor material by a single particle event. The topics span from basic mechanisms for single-particle induced failures to applied tasks like developing websites to predict on-orbit single event failure rates using Monte Carlo radiation transport tools.

Monochorionic triplets after single embryo transfer.

PubMed

Rísquez, Francisco; Gil, Mónica; D'Ommar, Gustavo; Poo, María; Sosa, Anna; Piras, Marta

2004-10-01

A 40-year-old patient underwent intracytoplasmic sperm injection and assisted hatching, and a single embryo was transferred. Ultrasonography demonstrated a single gestational sac containing monochorionic tri-amniotic pregnancy. Several factors that have been implicated in the aetiology of monozygotic triple pregnancies after IVF appear to be present in this case. To avoid multiple pregnancies after IVF, it is time to have definite predictive factors for the occurrence of monozygotic multiple pregnancies as well as transferring only a single embryo.

Improved model quality assessment using ProQ2.

PubMed

Ray, Arjun; Lindahl, Erik; Wallner, Björn

2012-09-10

Employing methods to assess the quality of modeled protein structures is now standard practice in bioinformatics. In a broad sense, the techniques can be divided into methods relying on consensus prediction on the one hand, and single-model methods on the other. Consensus methods frequently perform very well when there is a clear consensus, but this is not always the case. In particular, they frequently fail in selecting the best possible model in the hard cases (lacking consensus) or in the easy cases where models are very similar. In contrast, single-model methods do not suffer from these drawbacks and could potentially be applied on any protein of interest to assess quality or as a scoring function for sampling-based refinement. Here, we present a new single-model method, ProQ2, based on ideas from its predecessor, ProQ. ProQ2 is a model quality assessment algorithm that uses support vector machines to predict local as well as global quality of protein models. Improved performance is obtained by combining previously used features with updated structural and predicted features. The most important contribution can be attributed to the use of profile weighting of the residue specific features and the use features averaged over the whole model even though the prediction is still local. ProQ2 is significantly better than its predecessors at detecting high quality models, improving the sum of Z-scores for the selected first-ranked models by 20% and 32% compared to the second-best single-model method in CASP8 and CASP9, respectively. The absolute quality assessment of the models at both local and global level is also improved. The Pearson's correlation between the correct and local predicted score is improved from 0.59 to 0.70 on CASP8 and from 0.62 to 0.68 on CASP9; for global score to the correct GDT_TS from 0.75 to 0.80 and from 0.77 to 0.80 again compared to the second-best single methods in CASP8 and CASP9, respectively. ProQ2 is available at http://proq2.wallnerlab.org.

The value of the injury severity score in pediatric trauma: Time for a new definition of severe injury?

PubMed

Brown, Joshua B; Gestring, Mark L; Leeper, Christine M; Sperry, Jason L; Peitzman, Andrew B; Billiar, Timothy R; Gaines, Barbara A

2017-06-01

The Injury Severity Score (ISS) is the most commonly used injury scoring system in trauma research and benchmarking. An ISS greater than 15 conventionally defines severe injury; however, no studies evaluate whether ISS performs similarly between adults and children. Our objective was to evaluate ISS and Abbreviated Injury Scale (AIS) to predict mortality and define optimal thresholds of severe injury in pediatric trauma. Patients from the Pennsylvania trauma registry 2000-2013 were included. Children were defined as younger than 16 years. Logistic regression predicted mortality from ISS for children and adults. The optimal ISS cutoff for mortality that maximized diagnostic characteristics was determined in children. Regression also evaluated the association between mortality and maximum AIS in each body region, controlling for age, mechanism, and nonaccidental trauma. Analysis was performed in single and multisystem injuries. Sensitivity analyses with alternative outcomes were performed. Included were 352,127 adults and 50,579 children. Children had similar predicted mortality at ISS of 25 as adults at ISS of 15 (5%). The optimal ISS cutoff in children was ISS greater than 25 and had a positive predictive value of 19% and negative predictive value of 99% compared to a positive predictive value of 7% and negative predictive value of 99% for ISS greater than 15 to predict mortality. In single-system-injured children, mortality was associated with head (odds ratio, 4.80; 95% confidence interval, 2.61-8.84; p < 0.01) and chest AIS (odds ratio, 3.55; 95% confidence interval, 1.81-6.97; p < 0.01), but not abdomen, face, neck, spine, or extremity AIS (p > 0.05). For multisystem injury, all body region AIS scores were associated with mortality except extremities. Sensitivity analysis demonstrated ISS greater than 23 to predict need for full trauma activation, and ISS greater than 26 to predict impaired functional independence were optimal thresholds. An ISS greater than 25 may be a more appropriate definition of severe injury in children. Pattern of injury is important, as only head and chest injury drive mortality in single-system-injured children. These findings should be considered in benchmarking and performance improvement efforts. Epidemiologic study, level III.

Molecular vibrations in metal-single-molecule-metal junctions

NASA Astrophysics Data System (ADS)

Yokota, Kazumichi; Taniguchi, Masateru; Kawai, Tomoji

2010-03-01

Molecular vibrations in a metal-single-molecule-metal junction were studied based on density functional theory using a single benzenedithiolate molecule connected between gold clusters. We found that the difference in vibrational energy between an isolated benzenedithiol and the single-molecule junction is less than 3% in the energy range above 540 cm -1, where sulfur atoms contribute little to molecular vibrations. The finding implies that we can predict the peak energy in the inelastic electron tunneling spectrum of the single-molecule junction in the high energy range by vibrational analyses of isolated molecules.

Toxin MqsR Cleaves Single-Stranded mRNA with Various 5 Ends

DTIC Science & Technology

2016-08-24

either protein ORIGINAL RESEARCH Toxin MqsR cleaves single- stranded mRNA with various 5’ ends Nityananda Chowdhury1,*, Brian W. Kwan1,*, Louise C...in which a single 5′- GCU site was predicted to be single- stranded (ssRNA), double- stranded (dsRNA), in the loop of a stem - loop (slRNA), or in a...single- stranded 5′- GCU sites since cleavage was approximately 20- fold higher than cleavage seen with the 5′- GCU site in the stem - loop and

PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations

PubMed Central

Bendl, Jaroslav; Stourac, Jan; Salanda, Ondrej; Pavelka, Antonin; Wieben, Eric D.; Zendulka, Jaroslav; Brezovsky, Jan; Damborsky, Jiri

2014-01-01

Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. PMID:24453961

Calculations of single crystal elastic constants for yttria partially stabilised zirconia from powder diffraction data

NASA Astrophysics Data System (ADS)

Lunt, A. J. G.; Xie, M. Y.; Baimpas, N.; Zhang, S. Y.; Kabra, S.; Kelleher, J.; Neo, T. K.; Korsunsky, A. M.

2014-08-01

Yttria Stabilised Zirconia (YSZ) is a tough, phase-transforming ceramic that finds use in a wide range of commercial applications from dental prostheses to thermal barrier coatings. Micromechanical modelling of phase transformation can deliver reliable predictions in terms of the influence of temperature and stress. However, models must rely on the accurate knowledge of single crystal elastic stiffness constants. Some techniques for elastic stiffness determination are well-established. The most popular of these involve exploiting frequency shifts and phase velocities of acoustic waves. However, the application of these techniques to YSZ can be problematic due to the micro-twinning observed in larger crystals. Here, we propose an alternative approach based on selective elastic strain sampling (e.g., by diffraction) of grain ensembles sharing certain orientation, and the prediction of the same quantities by polycrystalline modelling, for example, the Reuss or Voigt average. The inverse problem arises consisting of adjusting the single crystal stiffness matrix to match the polycrystal predictions to observations. In the present model-matching study, we sought to determine the single crystal stiffness matrix of tetragonal YSZ using the results of time-of-flight neutron diffraction obtained from an in situ compression experiment and Finite Element modelling of the deformation of polycrystalline tetragonal YSZ. The best match between the model predictions and observations was obtained for the optimized stiffness values of C11 = 451, C33 = 302, C44 = 39, C66 = 82, C12 = 240, and C13 = 50 (units: GPa). Considering the significant amount of scatter in the published literature data, our result appears reasonably consistent.

Intraindividual Variability in Executive Functions but Not Speed of Processing or Conflict Resolution Predicts Performance Differences in Gait Speed in Older Adults

PubMed Central

Mahoney, Jeannette; Verghese, Joe

2014-01-01

Background. The relationship between executive functions (EF) and gait speed is well established. However, with the exception of dual tasking, the key components of EF that predict differences in gait performance have not been determined. Therefore, the current study was designed to determine whether processing speed, conflict resolution, and intraindividual variability in EF predicted variance in gait performance in single- and dual-task conditions. Methods. Participants were 234 nondemented older adults (mean age 76.48 years; 55% women) enrolled in a community-based cohort study. Gait speed was assessed using an instrumented walkway during single- and dual-task conditions. The flanker task was used to assess EF. Results. Results from the linear mixed effects model showed that (a) dual-task interference caused a significant dual-task cost in gait speed (estimate = 35.99; 95% CI = 33.19–38.80) and (b) of the cognitive predictors, only intraindividual variability was associated with gait speed (estimate = −.606; 95% CI = −1.11 to −.10). In unadjusted analyses, the three EF measures were related to gait speed in single- and dual-task conditions. However, in fully adjusted linear regression analysis, only intraindividual variability predicted performance differences in gait speed during dual tasking (B = −.901; 95% CI = −1.557 to −.245). Conclusion. Among the three EF measures assessed, intraindividual variability but not speed of processing or conflict resolution predicted performance differences in gait speed. PMID:24285744

Prediction of objectively measured physical activity and sedentariness among blue-collar workers using survey questionnaires.

PubMed

Gupta, Nidhi; Heiden, Marina; Mathiassen, Svend Erik; Holtermann, Andreas

2016-05-01

We aimed at developing and evaluating statistical models predicting objectively measured occupational time spent sedentary or in physical activity from self-reported information available in large epidemiological studies and surveys. Two-hundred-and-fourteen blue-collar workers responded to a questionnaire containing information about personal and work related variables, available in most large epidemiological studies and surveys. Workers also wore accelerometers for 1-4 days measuring time spent sedentary and in physical activity, defined as non-sedentary time. Least-squares linear regression models were developed, predicting objectively measured exposures from selected predictors in the questionnaire. A full prediction model based on age, gender, body mass index, job group, self-reported occupational physical activity (OPA), and self-reported occupational sedentary time (OST) explained 63% (R (2)adjusted) of the variance of both objectively measured time spent sedentary and in physical activity since these two exposures were complementary. Single-predictor models based only on self-reported information about either OPA or OST explained 21% and 38%, respectively, of the variance of the objectively measured exposures. Internal validation using bootstrapping suggested that the full and single-predictor models would show almost the same performance in new datasets as in that used for modelling. Both full and single-predictor models based on self-reported information typically available in most large epidemiological studies and surveys were able to predict objectively measured occupational time spent sedentary or in physical activity, with explained variances ranging from 21-63%.

Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis

PubMed Central

Barrett, Jessica; Pennells, Lisa; Sweeting, Michael; Willeit, Peter; Di Angelantonio, Emanuele; Gudnason, Vilmundur; Nordestgaard, Børge G.; Psaty, Bruce M; Goldbourt, Uri; Best, Lyle G; Assmann, Gerd; Salonen, Jukka T; Nietert, Paul J; Verschuren, W. M. Monique; Brunner, Eric J; Kronmal, Richard A; Salomaa, Veikko; Bakker, Stephan J L; Dagenais, Gilles R; Sato, Shinichi; Jansson, Jan-Håkan; Willeit, Johann; Onat, Altan; de la Cámara, Agustin Gómez; Roussel, Ronan; Völzke, Henry; Dankner, Rachel; Tipping, Robert W; Meade, Tom W; Donfrancesco, Chiara; Kuller, Lewis H; Peters, Annette; Gallacher, John; Kromhout, Daan; Iso, Hiroyasu; Knuiman, Matthew; Casiglia, Edoardo; Kavousi, Maryam; Palmieri, Luigi; Sundström, Johan; Davis, Barry R; Njølstad, Inger; Couper, David; Danesh, John; Thompson, Simon G; Wood, Angela

2017-01-01

Abstract The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962–2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction. PMID:28549073

Application of biodynamic imaging for personalized chemotherapy in canine lymphoma

NASA Astrophysics Data System (ADS)

Custead, Michelle R.

Biodynamic imaging (BDI) is a novel phenotypic cancer profiling technology which characterizes changes in cellular and subcellular motion in living tumor tissue samples following in vitro or ex vivo treatment with chemotherapeutics. The ability of BDI to predict clinical response to single-agent doxorubicin chemotherapy was tested in ten dogs with naturally-occurring non-Hodgkin's lymphomas (NHL). Pre-treatment tumor biopsy samples were obtained from all dogs and treated with doxorubicin (10 muM) ex vivo. BDI captured cellular and subcellular motility measures on all biopsy samples at baseline and at regular intervals for 9 hours following drug application. All dogs subsequently received treatment with a standard single-agent doxorubicin protocol. Objective response (OR) to doxorubicin and progression-free survival time (PFST) following chemotherapy were recorded for all dogs. The dynamic biomarkers measured by BDI were entered into a multivariate logistic model to determine the extent to which BDI predicted OR and PFST following doxorubicin therapy. The model showed that the sensitivity, specificity, and accuracy of BDI for predicting treatment outcome were 95%, 91%, and 93%, respectively. To account for possible over-fitting of data to the predictive model, cross-validation with a one-left-out analysis was performed, and the adjusted sensitivity, specificity, and accuracy following this analysis were 93%, 87%, and 91%, respectively. These findings suggest that BDI can predict, with high accuracy, treatment outcome following single-agent doxorubicin chemotherapy in a relevant spontaneous canine cancer model, and is a promising novel technology for advancing personalized cancer medicine.

Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

PubMed

Zabor, Emily C; Coit, Daniel; Gershenwald, Jeffrey E; McMasters, Kelly M; Michaelson, James S; Stromberg, Arnold J; Panageas, Katherine S

2018-02-22

Prognostic models are increasingly being made available online, where they can be publicly accessed by both patients and clinicians. These online tools are an important resource for patients to better understand their prognosis and for clinicians to make informed decisions about treatment and follow-up. The goal of this analysis was to highlight the possible variability in multiple online prognostic tools in a single disease. To demonstrate the variability in survival predictions across online prognostic tools, we applied a single validation dataset to three online melanoma prognostic tools. Data on melanoma patients treated at Memorial Sloan Kettering Cancer Center between 2000 and 2014 were retrospectively collected. Calibration was assessed using calibration plots and discrimination was assessed using the C-index. In this demonstration project, we found important differences across the three models that led to variability in individual patients' predicted survival across the tools, especially in the lower range of predictions. In a validation test using a single-institution data set, calibration and discrimination varied across the three models. This study underscores the potential variability both within and across online tools, and highlights the importance of using methodological rigor when developing a prognostic model that will be made publicly available online. The results also reinforce that careful development and thoughtful interpretation, including understanding a given tool's limitations, are required in order for online prognostic tools that provide survival predictions to be a useful resource for both patients and clinicians.

On the predictiveness of single-field inflationary models

NASA Astrophysics Data System (ADS)

Burgess, C. P.; Patil, Subodh P.; Trott, Michael

2014-06-01

We re-examine the predictiveness of single-field inflationary models and discuss how an unknown UV completion can complicate determining inflationary model parameters from observations, even from precision measurements. Besides the usual naturalness issues associated with having a shallow inflationary potential, we describe another issue for inflation, namely, unknown UV physics modifies the running of Standard Model (SM) parameters and thereby introduces uncertainty into the potential inflationary predictions. We illustrate this point using the minimal Higgs Inflationary scenario, which is arguably the most predictive single-field model on the market, because its predictions for A S , r and n s are made using only one new free parameter beyond those measured in particle physics experiments, and run up to the inflationary regime. We find that this issue can already have observable effects. At the same time, this UV-parameter dependence in the Renormalization Group allows Higgs Inflation to occur (in principle) for a slightly larger range of Higgs masses. We comment on the origin of the various UV scales that arise at large field values for the SM Higgs, clarifying cut off scale arguments by further developing the formalism of a non-linear realization of SU L (2) × U(1) in curved space. We discuss the interesting fact that, outside of Higgs Inflation, the effect of a non-minimal coupling to gravity, even in the SM, results in a non-linear EFT for the Higgs sector. Finally, we briefly comment on post BICEP2 attempts to modify the Higgs Inflation scenario.

Single Fasting Plasma Glucose Versus 75-g Oral Glucose-Tolerance Test in Prediction of Adverse Perinatal Outcomes: A Cohort Study.

PubMed

Shen, Songying; Lu, Jinhua; Zhang, Lifang; He, Jianrong; Li, Weidong; Chen, Niannian; Wen, Xingxuan; Xiao, Wanqing; Yuan, Mingyang; Qiu, Lan; Cheng, Kar Keung; Xia, Huimin; Mol, Ben Willem J; Qiu, Xiu

2017-02-01

There remains uncertainty regarding whether a single fasting glucose measurement is sufficient to predict risk of adverse perinatal outcomes. We included 12,594 pregnant women who underwent a 75-g oral glucose-tolerance test (OGTT) at 22-28weeks' gestation in the Born in Guangzhou Cohort Study, China. Outcomes were large for gestational age (LGA) baby, cesarean section, and spontaneous preterm birth. We calculated the area under the receiver operator characteristic curves (AUCs) to assess the capacity of OGTT glucose values to predict adverse outcomes, and compared the AUCs of different components of OGTT. 1325 women had a LGA baby (10.5%). Glucose measurements were linearly associated with LGA, with strongest associations for fasting glucose (odds ratio 1.37, 95% confidence interval 1.30-1.45). Weaker associations were observed for cesarean section and spontaneous preterm birth. Fasting glucose have a comparable discriminative power for prediction of LGA to the combination of fasting, 1h, and 2h glucose values during OGTT (AUCs, 0.611 vs. 0.614, P=0.166). The LGA risk was consistently increased in women with abnormal fasting glucose (≥5.1mmol/l), irrespective of 1h or 2h glucose levels. A single fasting glucose measurement performs comparably to 75-g OGTT in predicting risk of having a LGA baby. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Novel near-infrared sampling apparatus for single kernel analysis of oil content in maize.

PubMed

Janni, James; Weinstock, B André; Hagen, Lisa; Wright, Steve

2008-04-01

A method of rapid, nondestructive chemical and physical analysis of individual maize (Zea mays L.) kernels is needed for the development of high value food, feed, and fuel traits. Near-infrared (NIR) spectroscopy offers a robust nondestructive method of trait determination. However, traditional NIR bulk sampling techniques cannot be applied successfully to individual kernels. Obtaining optimized single kernel NIR spectra for applied chemometric predictive analysis requires a novel sampling technique that can account for the heterogeneous forms, morphologies, and opacities exhibited in individual maize kernels. In this study such a novel technique is described and compared to less effective means of single kernel NIR analysis. Results of the application of a partial least squares (PLS) derived model for predictive determination of percent oil content per individual kernel are shown.

Predicting First Graders' Development of Calculation versus Word-Problem Performance: The Role of Dynamic Assessment.

PubMed

Seethaler, Pamela M; Fuchs, Lynn S; Fuchs, Douglas; Compton, Donald L

2012-02-01

The purpose of this study was to assess the value of dynamic assessment (DA; degree of scaffolding required to learn unfamiliar mathematics content) for predicting 1(st)-grade calculations (CA) and word problems (WP) development, while controlling for the role of traditional assessments. Among 184 1(st) graders, predictors (DA, Quantity Discrimination, Test of Mathematics Ability, language, and reasoning) were assessed near the start of 1(st) grade. CA and WP were assessed near the end of 1(st) grade. Planned regression and commonality analyses indicated that for forecasting CA development, Quantity Discrimination, which accounted for 8.84% of explained variance, was the single most powerful predictor, followed by Test of Mathematics Ability and DA; language and reasoning were not uniquely predictive. By contrast, for predicting WP development, DA was the single most powerful predictor, which accounted for 12.01% of explained variance, with Test of Mathematics Ability, Quantity Discrimination, and language also uniquely predictive. Results suggest that different constellations of cognitive resources are required for CA versus WP development and that DA may be useful in predicting 1(st)-grade mathematics development, especially WP.

Predicting First Graders’ Development of Calculation versus Word-Problem Performance: The Role of Dynamic Assessment

PubMed Central

Seethaler, Pamela M.; Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.

2012-01-01

The purpose of this study was to assess the value of dynamic assessment (DA; degree of scaffolding required to learn unfamiliar mathematics content) for predicting 1st-grade calculations (CA) and word problems (WP) development, while controlling for the role of traditional assessments. Among 184 1st graders, predictors (DA, Quantity Discrimination, Test of Mathematics Ability, language, and reasoning) were assessed near the start of 1st grade. CA and WP were assessed near the end of 1st grade. Planned regression and commonality analyses indicated that for forecasting CA development, Quantity Discrimination, which accounted for 8.84% of explained variance, was the single most powerful predictor, followed by Test of Mathematics Ability and DA; language and reasoning were not uniquely predictive. By contrast, for predicting WP development, DA was the single most powerful predictor, which accounted for 12.01% of explained variance, with Test of Mathematics Ability, Quantity Discrimination, and language also uniquely predictive. Results suggest that different constellations of cognitive resources are required for CA versus WP development and that DA may be useful in predicting 1st-grade mathematics development, especially WP. PMID:22347725

Guidelines and Parameter Selection for the Simulation of Progressive Delamination

NASA Technical Reports Server (NTRS)

Song, Kyongchan; Davila, Carlos G.; Rose, Cheryl A.

2008-01-01

Turon s methodology for determining optimal analysis parameters for the simulation of progressive delamination is reviewed. Recommended procedures for determining analysis parameters for efficient delamination growth predictions using the Abaqus/Standard cohesive element and relatively coarse meshes are provided for single and mixed-mode loading. The Abaqus cohesive element, COH3D8, and a user-defined cohesive element are used to develop finite element models of the double cantilever beam specimen, the end-notched flexure specimen, and the mixed-mode bending specimen to simulate progressive delamination growth in Mode I, Mode II, and mixed-mode fracture, respectively. The predicted responses are compared with their analytical solutions. The results show that for single-mode fracture, the predicted responses obtained with the Abaqus cohesive element correlate well with the analytical solutions. For mixed-mode fracture, it was found that the response predicted using COH3D8 elements depends on the damage evolution criterion that is used. The energy-based criterion overpredicts the peak loads and load-deflection response. The results predicted using a tabulated form of the BK criterion correlate well with the analytical solution and with the results predicted with the user-written element.

Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models

PubMed Central

Nilsaz-Dezfouli, Hamid; Abu-Bakar, Mohd Rizam; Arasan, Jayanthi; Adam, Mohd Bakri; Pourhoseingholi, Mohamad Amin

2017-01-01

In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve. PMID:28469384

Suicide Attempt Characteristics, Diagnoses, and Future Attempts: Comparing Multiple Attempters to Single Attempters and Ideators

ERIC Educational Resources Information Center

Miranda, Regina; Scott, Michelle; Hicks, Roger; Wilcox, Holly C.; Munfakh, Jimmie Lou Harris; Shaffer, David

2008-01-01

The study compares psychiatric diagnoses and future suicide attempt outcomes of multiple attempters (MAs), single attempters (SAs) and ideators. The results conclude that MAs strongly predict later suicide attempts and diagnosis than SAs and ideators.

GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

Charge generation by heavy ions in power MOSFETs, burnout space predictions, and dynamic SEB sensitivity

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.; Brucker, G. J.; Calvel, P.; Baiget, A.; Peyrotte, C.; Gaillard, R.

1992-01-01

The transport, energy loss, and charge production of heavy ions in the sensitive regions of IRF 150 power MOSFETs are described. The dependence and variation of transport parameters with ion type and energy relative to the requirements for single event burnout in this part type are discussed. Test data taken with this power MOSFET are used together with analyses by means of a computer code of the ion energy loss and charge production in the device to establish criteria for burnout and parameters for space predictions. These parameters are then used in an application to predict burnout rates in a geostationary orbit for power converters operating in a dynamic mode. Comparisons of rates for different geometries in simulating SEU (single event upset) sensitive volumes are presented.

Noise reduction as affected by the extent and distribution of acoustic treatment in a turbofan engine inlet

NASA Technical Reports Server (NTRS)

Minner, G. L.; Homyak, L.

1976-01-01

An inlet noise suppressor for a TF-34 engine designed to have three acoustically treated rings was tested with several different ring arrangements. The configurations included: all three rings; two outer rings; single outer ring; single intermediate ring, and finally no rings. It was expected that as rings were removed, the acoustic performance would be degraded considerably. While a degradation occurred, it was not as large as predictions indicated. The prediction showed good agreement with the data only for the full-ring inlet configuration. The underpredictions which occurred with ring removal were believed a result of ignoring the presence of spinning modes which are known to damp more rapidly in cylindrical ducts than would be predicted by least attenuated mode or plane wave analysis.

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states

PubMed Central

Jang, Sumin; Choubey, Sandeep; Furchtgott, Leon; Zou, Ling-Nan; Doyle, Adele; Menon, Vilas; Loew, Ethan B; Krostag, Anne-Rachel; Martinez, Refugio A; Madisen, Linda; Levi, Boaz P; Ramanathan, Sharad

2017-01-01

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development. DOI: http://dx.doi.org/10.7554/eLife.20487.001 PMID:28296635

Linear prediction and single-channel recording.

PubMed

Carter, A A; Oswald, R E

1995-08-01

The measurement of individual single-channel events arising from the gating of ion channels provides a detailed data set from which the kinetic mechanism of a channel can be deduced. In many cases, the pattern of dwells in the open and closed states is very complex, and the kinetic mechanism and parameters are not easily determined. Assuming a Markov model for channel kinetics, the probability density function for open and closed time dwells should consist of a sum of decaying exponentials. One method of approaching the kinetic analysis of such a system is to determine the number of exponentials and the corresponding parameters which comprise the open and closed dwell time distributions. These can then be compared to the relaxations predicted from the kinetic model to determine, where possible, the kinetic constants. We report here the use of a linear technique, linear prediction/singular value decomposition, to determine the number of exponentials and the exponential parameters. Using simulated distributions and comparing with standard maximum-likelihood analysis, the singular value decomposition techniques provide advantages in some situations and are a useful adjunct to other single-channel analysis techniques.

Electronic Structure Control of Sub-nanometer 1D SnTe via Nanostructuring within Single-Walled Carbon Nanotubes.

PubMed

Vasylenko, Andrij; Marks, Samuel; Wynn, Jamie M; Medeiros, Paulo V C; Ramasse, Quentin M; Morris, Andrew J; Sloan, Jeremy; Quigley, David

2018-05-25

Nanostructuring, e. g., reduction of dimensionality in materials, offers a viable route toward regulation of materials electronic and hence functional properties. Here, we present the extreme case of nanostructuring, exploiting the capillarity of single-walled carbon nanotubes (SWCNTs) for the synthesis of the smallest possible SnTe nanowires with cross sections as thin as a single atom column. We demonstrate that by choosing the appropriate diameter of a template SWCNT, we can manipulate the structure of the quasi-one-dimensional (1D) SnTe to design electronic behavior. From first principles, we predict the structural re-formations that SnTe undergoes in varying encapsulations and confront the prediction with TEM imagery. To further illustrate the control of physical properties by nanostructuring, we study the evolution of transport properties in a homologous series of models of synthesized and isolated SnTe nanowires varying only in morphology and atomic layer thickness. This extreme scaling is predicted to significantly enhance thermoelectric performance of SnTe, offering a prospect for further experimental studies and future applications.

Strategies for enhanced deammonification performance and reduced nitrous oxide emissions.

PubMed

Leix, Carmen; Drewes, Jörg E; Ye, Liu; Koch, Konrad

2017-07-01

Deammonification's performance and associated nitrous oxide emissions (N 2 O) depend on operational conditions. While studies have investigated factors for high performances and low emissions separately, this study investigated optimizing deammonification performance while simultaneously reducing N 2 O emissions. Using a design of experiment (DoE) method, two models were developed for the prediction of the nitrogen removal rate and N 2 O emissions during single-stage deammonification considering three operational factors (i.e., pH value, feeding and aeration strategy). The emission factor varied between 0.7±0.5% and 4.1±1.2% at different DoE-conditions. The nitrogen removal rate was predicted to be maximized at settings of pH 7.46, intermittent feeding and aeration. Conversely, emissions were predicted to be minimized at the design edges at pH 7.80, single feeding, and continuous aeration. Results suggested a weak positive correlation between the nitrogen removal rate and N 2 O emissions, thus, a single optimizing operational set-point for maximized performance and minimized emissions did not exist. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discerning measures of conscious brain processes associated with superior early motor performance: Capacity, coactivation, and character.

PubMed

van Duijn, Tina; Buszard, Tim; Hoskens, Merel C J; Masters, Rich S W

2017-01-01

This study explored the relationship between working memory (WM) capacity, corticocortical communication (EEG coherence), and propensity for conscious control of movement during the performance of a complex far-aiming task. We were specifically interested in the role of these variables in predicting motor performance by novices. Forty-eight participants completed (a) an assessment of WM capacity (an adapted Rotation Span task), (b) a questionnaire that assessed the propensity to consciously control movement (the Movement Specific Reinvestment Scale), and (c) a hockey push-pass task. The hockey push-pass task was performed in a single task (movement only) condition and a combined task (movement plus decision) condition. Electroencephalography (EEG) was used to examine brain activity during the single task. WM capacity best predicted single task performance. WM capacity in combination with T8-Fz coherence (between the visuospatial and motor regions of the brain) best predicted combined task performance. We discuss the implied roles of visuospatial information processing capacity, neural coactivation, and propensity for conscious processing during performance of complex motor tasks. © 2017 Elsevier B.V. All rights reserved.

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

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

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

Seven lessons from manyfield inflation in random potentials

NASA Astrophysics Data System (ADS)

Dias, Mafalda; Frazer, Jonathan; Marsh, M. C. David

2018-01-01

We study inflation in models with many interacting fields subject to randomly generated scalar potentials. We use methods from non-equilibrium random matrix theory to construct the potentials and an adaption of the `transport method' to evolve the two-point correlators during inflation. This construction allows, for the first time, for an explicit study of models with up to 100 interacting fields supporting a period of `approximately saddle-point' inflation. We determine the statistical predictions for observables by generating over 30,000 models with 2–100 fields supporting at least 60 efolds of inflation. These studies lead us to seven lessons: i) Manyfield inflation is not single-field inflation, ii) The larger the number of fields, the simpler and sharper the predictions, iii) Planck compatibility is not rare, but future experiments may rule out this class of models, iv) The smoother the potentials, the sharper the predictions, v) Hyperparameters can transition from stiff to sloppy, vi) Despite tachyons, isocurvature can decay, vii) Eigenvalue repulsion drives the predictions. We conclude that many of the `generic predictions' of single-field inflation can be emergent features of complex inflation models.

Single Cigarette Sales: State Differences in FDA Advertising and Labeling Violations, 2014, United States

PubMed Central

Lee, Joseph G. L.; Ranney, Leah M.; Goldstein, Adam O.

2016-01-01

Importance: Single cigarettes, which are sold without warning labels and often evade taxes, can serve as a gateway for youth smoking. The Family Smoking Prevention and Tobacco Control Act of 2009 gives the US Food and Drug Administration (FDA) authority to regulate the manufacture, distribution, and marketing of tobacco products, including prohibiting the sale of single cigarettes. To enforce these regulations, the FDA conducted over 335 661 inspections between 2010 and September 30, 2014, and allocated over $115 million toward state inspections contracts. Objective: To examine differences in single cigarette violations across states and determine if likely correlates of single cigarette sales predict single cigarette violations at the state level. Design: Cross-sectional study of publicly available FDA warning letters from January 1 to July 31, 2014. Setting: All 50 states and the District of Columbia. Participants: Tobacco retailer inspections conducted by FDA (n = 33 543). Exposure(s) for Observational Studies: State cigarette tax, youth smoking prevalence, poverty, and tobacco production. Main Outcome(s) and Measure(s): State proportion of FDA warning letters issued for single cigarette violations. Results: There are striking differences in the number of single cigarette violations found by state, with 38 states producing no warning letters for selling single cigarettes even as state policymakers developed legislation to address retailer sales of single cigarettes. The state proportion of warning letters issued for single cigarettes is not predicted by state cigarette tax, youth smoking, poverty, or tobacco production, P = .12. Conclusions and Relevance: Substantial, unexplained variation exists in violations of single cigarette sales among states. These data suggest the possibility of differences in implementation of FDA inspections and the need for stronger quality monitoring processes across states implementing FDA inspections. PMID:25744967

Single Cigarette Sales: State Differences in FDA Advertising and Labeling Violations, 2014, United States.

PubMed

Baker, Hannah M; Lee, Joseph G L; Ranney, Leah M; Goldstein, Adam O

2016-02-01

Single cigarettes, which are sold without warning labels and often evade taxes, can serve as a gateway for youth smoking. The Family Smoking Prevention and Tobacco Control Act of 2009 gives the US Food and Drug Administration (FDA) authority to regulate the manufacture, distribution, and marketing of tobacco products, including prohibiting the sale of single cigarettes. To enforce these regulations, the FDA conducted over 335,661 inspections between 2010 and September 30, 2014, and allocated over $115 million toward state inspections contracts. To examine differences in single cigarette violations across states and determine if likely correlates of single cigarette sales predict single cigarette violations at the state level. Cross-sectional study of publicly available FDA warning letters from January 1 to July 31, 2014. All 50 states and the District of Columbia. Tobacco retailer inspections conducted by FDA (n = 33 543). State cigarette tax, youth smoking prevalence, poverty, and tobacco production. State proportion of FDA warning letters issued for single cigarette violations. There are striking differences in the number of single cigarette violations found by state, with 38 states producing no warning letters for selling single cigarettes even as state policymakers developed legislation to address retailer sales of single cigarettes. The state proportion of warning letters issued for single cigarettes is not predicted by state cigarette tax, youth smoking, poverty, or tobacco production, P = .12. Substantial, unexplained variation exists in violations of single cigarette sales among states. These data suggest the possibility of differences in implementation of FDA inspections and the need for stronger quality monitoring processes across states implementing FDA inspections. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

INTERSPECIES CORRELATION ESTIMATES PREDICT PROTECTIVE ENVIRONMENTAL CONCENTRATIONS

EPA Science Inventory

Environmental risk assessments often use multiple single species toxicity test results and species sensitivity distributions (SSDs) to derive a predicted no-effect concentration in the environment, typically the 5th percentile of the SSD, termed the HC5. The shape and location of...

Mysid Population Responses to Resource Limitation Differ from those Predicted by Cohort Studies

EPA Science Inventory

Effects of anthropogenic stressors on animal populations are often evaluated by assembling vital rate responses from isolated cohort studies into a single demographic model. However, models constructed from cohort studies are difficult to translate into ecological predictions be...

Life Prediction of Turbine Blade Nickel Base Superalloy Single Crystals.

DTIC Science & Technology

1986-08-01

mechanical properties between single crystals and the DS version of Mar-M200. Soon it was recognized again through the mechanical property - structure ... property achievements demonstrated by screening and simulated engine tests. 1 Single crystals are the results of extensive investigation on the mechanical ...behavior, (especially fatigue and creep) of, and the structure - property correlations in the equiaxed and directionally solidified (DS) nickel-base

Genomic predictions across Nordic Holstein and Nordic Red using the genomic best linear unbiased prediction model with different genomic relationship matrices.

PubMed

Zhou, L; Lund, M S; Wang, Y; Su, G

2014-08-01

This study investigated genomic predictions across Nordic Holstein and Nordic Red using various genomic relationship matrices. Different sources of information, such as consistencies of linkage disequilibrium (LD) phase and marker effects, were used to construct the genomic relationship matrices (G-matrices) across these two breeds. Single-trait genomic best linear unbiased prediction (GBLUP) model and two-trait GBLUP model were used for single-breed and two-breed genomic predictions. The data included 5215 Nordic Holstein bulls and 4361 Nordic Red bulls, which was composed of three populations: Danish Red, Swedish Red and Finnish Ayrshire. The bulls were genotyped with 50 000 SNP chip. Using the two-breed predictions with a joint Nordic Holstein and Nordic Red reference population, accuracies increased slightly for all traits in Nordic Red, but only for some traits in Nordic Holstein. Among the three subpopulations of Nordic Red, accuracies increased more for Danish Red than for Swedish Red and Finnish Ayrshire. This is because closer genetic relationships exist between Danish Red and Nordic Holstein. Among Danish Red, individuals with higher genomic relationship coefficients with Nordic Holstein showed more increased accuracies in the two-breed predictions. Weighting the two-breed G-matrices by LD phase consistencies, marker effects or both did not further improve accuracies of the two-breed predictions. © 2014 Blackwell Verlag GmbH.

Further Studies of the Response of Single Rotor Helicopters to Vortex Encounters

DOT National Transportation Integrated Search

1985-09-01

This report is a continuation of the studies described in Reference where a simplified approach to the problem of predicting the uncontrolled response of a single rotor helicopter to an encounter with the wing tip vortex of a large transport aircraft...

Single-Slit Diffraction Pattern of a Thermal Atomic Potassium Beam

ERIC Educational Resources Information Center

Leavitt, John A.; Bills, Francis A.

1969-01-01

The diffraction of a full thermal atomic potassium beam by a single slit was observed. Four experimental diffraction patterns were compared with that predicted by de Brogtie's hypothesis and simple scalar Fresnel diffraction theory. Possible reasons for the differences were discussed. (LC)

ADDITIVITY ASSESSMENT OF TRIHALOMETHANE MIXTURES BY PROPORTIONAL RESPONSE ADDITION

EPA Science Inventory

If additivity is known or assumed, the toxicity of a chemical mixture may be predicted from the dose response curves of the individual chemicals comprising the mixture. As single chemical data are abundant and mixture data sparse, mixture risk methods that utilize single chemical...

Non-invasive prediction of catheter ablation outcome in persistent atrial fibrillation by fibrillatory wave amplitude computation in multiple electrocardiogram leads.

PubMed

Zarzoso, Vicente; Latcu, Decebal G; Hidalgo-Muñoz, Antonio R; Meo, Marianna; Meste, Olivier; Popescu, Irina; Saoudi, Nadir

2016-12-01

Catheter ablation (CA) of persistent atrial fibrillation (AF) is challenging, and reported results are capable of improvement. A better patient selection for the procedure could enhance its success rate while avoiding the risks associated with ablation, especially for patients with low odds of favorable outcome. CA outcome can be predicted non-invasively by atrial fibrillatory wave (f-wave) amplitude, but previous works focused mostly on manual measures in single electrocardiogram (ECG) leads only. To assess the long-term prediction ability of f-wave amplitude when computed in multiple ECG leads. Sixty-two patients with persistent AF (52 men; mean age 61.5±10.4years) referred for CA were enrolled. A standard 1-minute 12-lead ECG was acquired before the ablation procedure for each patient. F-wave amplitudes in different ECG leads were computed by a non-invasive signal processing algorithm, and combined into a mutivariate prediction model based on logistic regression. During an average follow-up of 13.9±8.3months, 47 patients had no AF recurrence after ablation. A lead selection approach relying on the Wald index pointed to I, V1, V2 and V5 as the most relevant ECG leads to predict jointly CA outcome using f-wave amplitudes, reaching an area under the curve of 0.854, and improving on single-lead amplitude-based predictors. Analysing the f-wave amplitude in several ECG leads simultaneously can significantly improve CA long-term outcome prediction in persistent AF compared with predictors based on single-lead measures. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

CaPTHUS scoring model in primary hyperparathyroidism: can it eliminate the need for ioPTH testing?

PubMed

Elfenbein, Dawn M; Weber, Sara; Schneider, David F; Sippel, Rebecca S; Chen, Herbert

2015-04-01

The CaPTHUS model was reported to have a positive predictive value of 100 % to correctly predict single-gland disease in patients with primary hyperparathyroidism, thus obviating the need for intraoperative parathyroid hormone (ioPTH) testing. We sought to apply the CaPTHUS scoring model in our patient population and assess its utility in predicting long-term biochemical cure. We retrospective reviewed all parathyroidectomies for primary hyperparathyroidism performed at our university hospital from 2003 to 2012. We routinely perform ioPTH testing. Biochemical cure was defined as a normal calcium level at 6 months. A total of 1,421 patients met the inclusion criteria: 78 % of patients had a single adenoma at the time of surgery, 98 % had a normal serum calcium at 1 week postoperatively, and 96 % had a normal serum calcium level 6 months postoperatively. Using the CaPTHUS scoring model, 307 patients (22.5 %) had a score of ≥ 3, with a positive predictive value of 91 % for single adenoma. A CaPTHUS score of ≥ 3 had a positive predictive value of 98 % for biochemical cure at 1 week as well as at 6 months. In our population, where ioPTH testing is used routinely to guide use of bilateral exploration, patients with a preoperative CaPTHUS score of ≥ 3 had good long-term biochemical cure rates. However, the model only predicted adenoma in 91 % of cases. If minimally invasive parathyroidectomy without ioPTH testing had been done for these patients, the cure rate would have dropped from 98 % to an unacceptable 89 %. Even in these patients with high CaPTHUS scores, multigland disease is present in almost 10 %, and ioPTH testing is necessary.

Single-polymer dynamics under constraints: scaling theory and computer experiment.

PubMed

Milchev, Andrey

2011-03-16

The relaxation, diffusion and translocation dynamics of single linear polymer chains in confinement is briefly reviewed with emphasis on the comparison between theoretical scaling predictions and observations from experiment or, most frequently, from computer simulations. Besides cylindrical, spherical and slit-like constraints, related problems such as the chain dynamics in a random medium and the translocation dynamics through a nanopore are also considered. Another particular kind of confinement is imposed by polymer adsorption on attractive surfaces or selective interfaces--a short overview of single-chain dynamics is also contained in this survey. While both theory and numerical experiments consider predominantly coarse-grained models of self-avoiding linear chain molecules with typically Rouse dynamics, we also note some recent studies which examine the impact of hydrodynamic interactions on polymer dynamics in confinement. In all of the aforementioned cases we focus mainly on the consequences of imposed geometric restrictions on single-chain dynamics and try to check our degree of understanding by assessing the agreement between theoretical predictions and observations.

Improved Time-Lapsed Angular Scattering Microscopy of Single Cells

NASA Astrophysics Data System (ADS)

Cannaday, Ashley E.

By measuring angular scattering patterns from biological samples and fitting them with a Mie theory model, one can estimate the organelle size distribution within many cells. Quantitative organelle sizing of ensembles of cells using this method has been well established. Our goal is to develop the methodology to extend this approach to the single cell level, measuring the angular scattering at multiple time points and estimating the non-nuclear organelle size distribution parameters. The diameters of individual organelle-size beads were successfully extracted using scattering measurements with a minimum deflection angle of 20 degrees. However, the accuracy of size estimates can be limited by the angular range detected. In particular, simulations by our group suggest that, for cell organelle populations with a broader size distribution, the accuracy of size prediction improves substantially if the minimum angle of detection angle is 15 degrees or less. The system was therefore modified to collect scattering angles down to 10 degrees. To confirm experimentally that size predictions will become more stable when lower scattering angles are detected, initial validations were performed on individual polystyrene beads ranging in diameter from 1 to 5 microns. We found that the lower minimum angle enabled the width of this delta-function size distribution to be predicted more accurately. Scattering patterns were then acquired and analyzed from single mouse squamous cell carcinoma cells at multiple time points. The scattering patterns exhibit angular dependencies that look unlike those of any single sphere size, but are well-fit by a broad distribution of sizes, as expected. To determine the fluctuation level in the estimated size distribution due to measurement imperfections alone, formaldehyde-fixed cells were measured. Subsequent measurements on live (non-fixed) cells revealed an order of magnitude greater fluctuation in the estimated sizes compared to fixed cells. With our improved and better-understood approach to single cell angular scattering, we are now capable of reliably detecting changes in organelle size predictions due to biological causes above our measurement error of 20 nm, which enables us to apply our system to future studies of the investigation of various single cell biological processes.

ISOBAR MODEL ANALYSIS OF SINGLE PION PRODUCTION IN PION-NUCLEON COLLISIONS BELOW 1 Bev

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

Olsson, M.; Yodh, G.B.

1963-04-15

The isobar model of Bergia, Bonsignori, and Stanghellini for single ceramic materia production in ceramic materia -N collisions is shown to account for the majority of the observed mass spectra and the ratio of ceramic materia / sup 0/ to ceramic materia /sup +/ production in ceramic materia /sup +/-p collisions fr3350 Mev to 1 Bev when the p-wave decay of the isobar and requirements of Bose statistics are included. Predictions of this improved model are compared with experimental data and with the predictions of other models. (D.C.W.)

Study on Prediction of Underwater Radiated Noise from Propeller Tip Vortex Cavitation

NASA Astrophysics Data System (ADS)

Yamada, Takuyoshi; Sato, Kei; Kawakita, Chiharu; Oshima, Akira

2015-12-01

The method to predict underwater radiated noise from tip vortex cavitation was studied. The growth of a single cavitation bubble in tip vortex was estimated by substituting the tip vortex to Rankine combined vortex. The ideal spectrum function for the sound pressure generated by a single cavitation bubble was used, also the empirical factor for the number of collapsed bubbles per unit time was introduced. The estimated noise data were compared with measured ship's ones and it was found out that this method can estimate noise data within 3dB difference.

A comparative study of the effects of cone-plate and parallel-plate geometries on rheological properties under oscillatory shear flow

NASA Astrophysics Data System (ADS)

Song, Hyeong Yong; Salehiyan, Reza; Li, Xiaolei; Lee, Seung Hak; Hyun, Kyu

2017-11-01

In this study, the effects of cone-plate (C/P) and parallel-plate (P/P) geometries were investigated on the rheological properties of various complex fluids, e.g. single-phase (polymer melts and solutions) and multiphase systems (polymer blend and nanocomposite, and suspension). Small amplitude oscillatory shear (SAOS) tests were carried out to compare linear rheological responses while nonlinear responses were compared using large amplitude oscillatory shear (LAOS) tests at different frequencies. Moreover, Fourier-transform (FT)-rheology method was used to analyze the nonlinear responses under LAOS flow. Experimental results were compared with predictions obtained by single-point correction and shear rate correction. For all systems, SAOS data measured by C/P and P/P coincide with each other, but results showed discordance between C/P and P/P measurements in the nonlinear regime. For all systems except xanthan gum solutions, first-harmonic moduli were corrected using a single horizontal shift factor, whereas FT rheology-based nonlinear parameters ( I 3/1, I 5/1, Q 3, and Q 5) were corrected using vertical shift factors that are well predicted by single-point correction. Xanthan gum solutions exhibited anomalous corrections. Their first-harmonic Fourier moduli were superposed using a horizontal shift factor predicted by shear rate correction applicable to highly shear thinning fluids. The distinguished corrections were observed for FT rheology-based nonlinear parameters. I 3/1 and I 5/1 were superposed by horizontal shifts, while the other systems displayed vertical shifts of I 3/1 and I 5/1. Q 3 and Q 5 of xanthan gum solutions were corrected using both horizontal and vertical shift factors. In particular, the obtained vertical shift factors for Q 3 and Q 5 were twice as large as predictions made by single-point correction. Such larger values are rationalized by the definitions of Q 3 and Q 5. These results highlight the significance of horizontal shift corrections in nonlinear oscillatory shear data.

Growth parameters of Penicillium expansum calculated from mixed inocula as an alternative to account for intraspecies variability.

PubMed

Garcia, Daiana; Ramos, Antonio J; Sanchis, Vicente; Marín, Sonia

2014-09-01

The aim of this work was to compare the radial growth rate (μ) and the lag time (λ) for growth of 25 isolates of Penicillium expansum at 1 and 20 ºC with those of the mixed inoculum of the 25 isolates. Moreover, the evolution of probability of growth through time was also compared for the single strains and mixed inoculum. Working with a mixed inoculum would require less work, time and consumables than if a range of single strains has to be used in order to represent a given species. Suitable predictive models developed for a given species should represent as much as possible the behavior of all strains belonging to this species. The results suggested, on one hand, that the predictions based on growth parameters calculated on the basis of mixed inocula may not accurately predict the behavior of all possible strains but may represent a percentage of them, and the median/mean values of μ and λ obtained by the 25 strains may be substituted by the value obtained with the mixed inoculum. Moreover, the predictions may be biased, in particular, the predictions of λ which may be underestimated (fail-safe). Moreover, the prediction of time for a given probability of growth through a mixed inoculum may not be accurate for all single inocula, but it may represent 92% and 60% of them at 20 and 1 ºC, respectively, and also their overall mean and median values. In conclusion, mixed inoculum could be a good alternative to estimate the mean or median values of high number of isolates, but not to account for those strains with marginal behavior. In particular, estimation of radial growth rate, and time for 0.10 and 0.50 probability of growth using a cocktail inoculum accounted for the estimates of most single isolates tested. For the particular case of probability models, this is an interesting result as for practical applications in the food industry the estimation of t10 or lower probability may be required. Copyright © 2014 Elsevier B.V. All rights reserved.

The value of non-echo planar HASTE diffusion-weighted MR imaging in the detection, localisation and prediction of extent of postoperative cholesteatoma.

PubMed

Khemani, S; Lingam, R K; Kalan, A; Singh, A

2011-08-01

To evaluate the diagnostic performance of half-Fourier-acquisition single-shot turbo-spin-echo (HASTE) diffusion-weighted magnetic resonance imaging in the detection, localisation and prediction of extent of cholesteatoma following canal wall up mastoid surgery. Prospective blinded observational study. University affiliated teaching hospital. Forty-eight patients undergoing second-look surgery after previous canal wall up mastoid surgery for primary acquired cholesteatoma. All patients underwent non-echo planar HASTE diffusion-weighted imaging prior to being offered 'second-look' surgery. Radiological findings were correlated with second-look intra-operative findings in 38 cases with regard to presence, location and maximum dimensions of cholesteatoma. Half-Fourier-acquisition single-shot turbo-spin-echo diffusion-weighted imaging accurately predicted the presence of cholesteatoma in 23 of 28 cases, and it correctly excluded in nine of 10 cases. Five false negatives were caused by keratin pearls of <2 mm and in one case 5 mm. Overall sensitivity and specificity for detection of cholesteatoma were 82% (95% confidence interval [CI] 62-94%) and 90% (CI 55-100%), respectively. Positive predictive value and negative predictive value were 96% (CI 79-100%) and 64% (CI 35-87%), respectively. Overall accuracy for detection of cholesteatoma was 84% (CI 69-94%). Half-Fourier-acquisition single-shot turbo-spin-echo diffusion-weighted imaging has good performance in localising cholesteatoma to a number of anatomical sub-sites within the middle ear and mastoid (sensitivity ranging from 75% to 88% and specificity ranging from 94% to 100%). There was no statistically significant difference in the size of cholesteatoma detected radiologically and that found during surgery (paired t-test, P = 0.16). However, analysis of size agreement suggests possible radiological underestimation of size when using HASTE diffusion-weighted imaging (mean difference -0.6 mm, CI -5.3 to 4.6 mm). Half-Fourier-acquisition single-shot turbo-spin-echo diffusion-weighted imaging performs reasonably well in predicting the presence and location of postoperative cholesteatoma but may miss small foci of disease and may underestimate the true size of cholesteatoma. © 2011 Blackwell Publishing Ltd.

Neuroimaging-Aided Prediction of the Effect of Methylphenidate in Children with Attention-Deficit Hyperactivity Disorder: A Randomized Controlled Trial.

PubMed

Ishii-Takahashi, Ayaka; Takizawa, Ryu; Nishimura, Yukika; Kawakubo, Yuki; Hamada, Kasumi; Okuhata, Shiho; Kawasaki, Shingo; Kuwabara, Hitoshi; Shimada, Takafumi; Todokoro, Ayako; Igarashi, Takashi; Watanabe, Kei-Ichiro; Yamasue, Hidenori; Kato, Nobumasa; Kasai, Kiyoto; Kano, Yukiko

2015-11-01

Although methylphenidate hydrochloride (MPH) is a first-line treatment for children with attention-deficit hyperactivity disorder (ADHD), the non-response rate is 30%. Our aim was to develop a supplementary neuroimaging biomarker for predicting the clinical effect of continuous MPH administration by using near-infrared spectroscopy (NIRS). After baseline assessment, we performed a double-blind, placebo-controlled, crossover trial with a single dose of MPH, followed by a prospective 4-to-8-week open trial with continuous MPH administration, and an ancillary 1-year follow-up. Twenty-two drug-naïve and eight previously treated children with ADHD (NAÏVE and NON-NAÏVE) were compared with 20 healthy controls (HCs) who underwent multiple NIRS measurements without intervention. We tested whether NIRS signals at the baseline assessment or ΔNIRS (single dose of MPH minus baseline assessment) predict the Clinical Global Impressions-Severity (CGI-S) score after 4-to-8-week or 1-year MPH administration. The secondary outcomes were the effect of MPH on NIRS signals after single-dose, 4-to-8-week, and 1-year administration. ΔNIRS significantly predicted CGI-S after 4-to-8-week MPH administration. The leave-one-out classification algorithm had 81% accuracy using the NIRS signal. ΔNIRS also significantly predicted CGI-S scores after 1 year of MPH administration. For secondary analyses, NAÏVE exhibited significantly lower prefrontal activation than HCs at the baseline assessment, whereas NON-NAÏVE and HCs showed similar activation. A single dose of MPH significantly increased activation compared with the placebo in NAÏVE. After 4-to-8-week administration, and even after MPH washout following 1-year administration, NAÏVE demonstrated normalized prefrontal activation. Supplementary NIRS measurements may serve as an objective biomarker for clinical decisions and monitoring concerning continuous MPH treatment in children with ADHD.

Predictive factors for the methotrexate treatment outcome in ectopic pregnancy: A comparative study of 400 cases.

PubMed

Bonin, Lucie; Pedreiro, Cécile; Moret, Stéphanie; Chene, Gautier; Gaucherand, Pascal; Lamblin, Géry

2017-01-01

We sought to evaluate the global success rate of intramuscular methotrexate for the treatment of ectopic pregnancy, identify factors predictive of treatment success or failure, and study methotrexate tolerability in a large patient cohort. For this single-center retrospective observational study, we retrieved the records of all women who had a clinically or echographically confirmed ectopic pregnancy with a Fernandez score <13 and who were treated according to a 1mg/kg intramuscular single-dose methotrexate protocol. Medical treatment failure was defined by an obligation to proceed to laparoscopy. Needing a second injection was not considered to be medical treatment failure. Between February 2008 and November 2013 (69 months), 400 women received methotrexate for ectopic pregnancy. The medical treatment protocol was effective for 314 patients, i.e., an overall success rate of 78.5%. A single methotrexate dose was sufficient for 63.5% of the women and a second dose was successful for 73.2% of the remaining women. The medical treatment success rate fell as initial hCG levels climbed. The main factors associated with methotrexate failure included day (D) 0, D4 and D7 hCG levels, pretherapeutic blood progesterone, hematosalpinx at D0 and pain at D7. Early favorable kinetics of hCG levels was predictive of success. Methotrexate treatment was successful in 90% of women who had D0 hCG <1000IU/l. Methotrexate tolerability was good, with only 9% of the women reporting non-severe adverse effects. The fertility rate with delivery after medical treatment for ectopic pregnancy was 80.7%. In this study, we showed that an initial hCG value <1000IU/l and favorable early HCG kinetics were predictive factors for the successful medical treatment of ectopic pregnancy by methotrexate, and hematosalpinx and pretherapeutic blood progesterone >5ng/ml at diagnosis were predictive of its failure. We also confirmed good tolerability for single-dose methotrexate protocols. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Predicted phototoxicities of carbon nano-material by quantum mechanical calculations

EPA Science Inventory

The purpose of this research is to develop a predictive model for the phototoxicity potential of carbon nanomaterials (fullerenols and single-walled carbon nanotubes). This model is based on the quantum mechanical (ab initio) calculations on these carbon-based materials and compa...

Redundancy and Reduction: Speakers Manage Syntactic Information Density

ERIC Educational Resources Information Center

Jaeger, T. Florian

2010-01-01

A principle of efficient language production based on information theoretic considerations is proposed: Uniform Information Density predicts that language production is affected by a preference to distribute information uniformly across the linguistic signal. This prediction is tested against data from syntactic reduction. A single multilevel…

Algorithms and Parametric Studies for Assessing Effects of Two-Point Contact

DOT National Transportation Integrated Search

1984-02-01

This report describes analyses conducted to assess the effects of two-point wheel rail contact on a single wheel on the prediction of wheel-rail forces, and for including these effects in a computer program for predicting curving behavior of rail veh...

Evaluation of single nucleotide polymorphisms in chromosomal regions impacting pregnancy status in cattle

USDA-ARS?s Scientific Manuscript database

Reproductive success is an important component of commercial beef cattle production, and identification of DNA markers with predictive merit for reproductive success would facilitate accurate prediction of mean daughter pregnancy rate, enabling effective selection of bulls to improve female fertilit...

Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions

USGS Publications Warehouse

Viney, N.R.; Bormann, H.; Breuer, L.; Bronstert, A.; Croke, B.F.W.; Frede, H.; Graff, T.; Hubrechts, L.; Huisman, J.A.; Jakeman, A.J.; Kite, G.W.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Willems, P.

2009-01-01

This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non-stationarity of the climate series and possible cross-correlations between models. Crown Copyright ?? 2008.

Predicting the nature of supernova progenitors

NASA Astrophysics Data System (ADS)

Groh, Jose H.

2017-09-01

Stars more massive than about 8 solar masses end their lives as a supernova (SN), an event of fundamental importance Universe-wide. The physical properties of massive stars before the SN event are very uncertain, both from theoretical and observational perspectives. In this article, I briefly review recent efforts to predict the nature of stars before death, in particular, by performing coupled stellar evolution and atmosphere modelling of single stars in the pre-SN stage. These models are able to predict the high-resolution spectrum and broadband photometry, which can then be directly compared with the observations of core-collapse SN progenitors. The predictions for the spectral types of massive stars before death can be surprising. Depending on the initial mass and rotation, single star models indicate that massive stars die as red supergiants, yellow hypergiants, luminous blue variables and Wolf-Rayet stars of the WN and WO subtypes. I finish by assessing the detectability of SN Ibc progenitors. This article is part of the themed issue 'Bridging the gap: from massive stars to supernovae'.

A Technical Analysis Information Fusion Approach for Stock Price Analysis and Modeling

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

In this paper, we address the problem of technical analysis information fusion in improving stock market index-level prediction. We present an approach for analyzing stock market price behavior based on different categories of technical analysis metrics and a multiple predictive system. Each category of technical analysis measures is used to characterize stock market price movements. The presented predictive system is based on an ensemble of neural networks (NN) coupled with particle swarm intelligence for parameter optimization where each single neural network is trained with a specific category of technical analysis measures. The experimental evaluation on three international stock market indices and three individual stocks show that the presented ensemble-based technical indicators fusion system significantly improves forecasting accuracy in comparison with single NN. Also, it outperforms the classical neural network trained with index-level lagged values and NN trained with stationary wavelet transform details and approximation coefficients. As a result, technical information fusion in NN ensemble architecture helps improving prediction accuracy.

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

Multi input single output model predictive control of non-linear bio-polymerization process

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

Arumugasamy, Senthil Kumar; Ahmad, Z.

This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state spacemore » model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.« less

Evaluation of four methods for platelet compatibility testing

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

McFarland, J.G.; Aster, R.H.

1987-05-01

Four platelet compatibility assays were performed on serum and platelet or lymphocyte samples from 38 closely HLA-matched donor/recipient pairs involved in 55 single-donor platelet transfusions. The 22 patients studied were refractory to transfusions of pooled random-donor platelets. Of the four assays (platelet suspension immunofluorescence, PSIFT; /sup 51/Cr release; microlymphocytotoxicity; and a monoclonal anti-IgG assay, MAIA), the MAIA was most predictive of platelet transfusion outcome (predictability, 74% for one-hour posttransfusion platelet recovery and 76% for 24-hour recovery). The only other assay to reach statistical significance was the PSIFT (63% predictability for one-hour posttransfusion recovery). The degree of HLA compatibility between donormore » and recipient (exact matches v those utilizing cross-reactive associations) was unrelated to the ability of the MAIA to predict transfusion results. The MAIA may be capable of differentiating HLA antibodies, ABO antibodies, and platelet-specific antibodies responsible for failure of HLA-matched and selectively mismatched single-donor platelet transfusions.« less

Optimal strategy analysis based on robust predictive control for inventory system with random demand

NASA Astrophysics Data System (ADS)

Saputra, Aditya; Widowati, Sutrisno

2017-12-01

In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.

Double versus single reading of mammograms in a breast cancer screening programme: a cost-consequence analysis.

PubMed

Posso, Margarita C; Puig, Teresa; Quintana, Ma Jesus; Solà-Roca, Judit; Bonfill, Xavier

2016-09-01

To assess the costs and health-related outcomes of double versus single reading of digital mammograms in a breast cancer screening programme. Based on data from 57,157 digital screening mammograms from women aged 50-69 years, we compared costs, false-positive results, positive predictive value and cancer detection rate using four reading strategies: double reading with and without consensus and arbitration, and single reading with first reader only and second reader only. Four highly trained radiologists read the mammograms. Double reading with consensus and arbitration was 15 % (Euro 334,341) more expensive than single reading with first reader only. False-positive results were more frequent at double reading with consensus and arbitration than at single reading with first reader only (4.5 % and 4.2 %, respectively; p < 0.001). The positive predictive value (9.3 % and 9.1 %; p = 0.812) and cancer detection rate were similar for both reading strategies (4.6 and 4.2 per 1000 screens; p = 0.283). Our results suggest that changing to single reading of mammograms could produce savings in breast cancer screening. Single reading could reduce the frequency of false-positive results without changing the cancer detection rate. These results are not conclusive and cannot be generalized to other contexts with less trained radiologists. • Double reading of digital mammograms is more expensive than single reading. • Compared to single reading, double reading yields a higher proportion of false-positive results. • The cancer detection rate was similar for double and single readings. • Single reading may be a cost-effective strategy in breast cancer screening programmes.

Methods to approximate reliabilities in single-step genomic evaluation

USDA-ARS?s Scientific Manuscript database

Reliability of predictions from single-step genomic BLUP (ssGBLUP) can be calculated by inversion, but that is not feasible for large data sets. Two methods of approximating reliability were developed based on decomposition of a function of reliability into contributions from records, pedigrees, and...

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

NASA Astrophysics Data System (ADS)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

Comparison of forward flight effects theory of A. Michalke and U. Michel with measured data

NASA Technical Reports Server (NTRS)

Rawls, J. W., Jr.

1983-01-01

The scaling laws of a Michalke and Michel predict flyover noise of a single stream shock free circular jet from static data or static predictions. The theory is based on a farfield solution to Lighthill's equation and includes density terms which are important for heated jets. This theory is compared with measured data using two static jet noise prediction methods. The comparisons indicate the theory yields good results when the static noise levels are accurately predicted.

Single-Rooted Extraction Sockets: Classification and Treatment Protocol.

PubMed

El Chaar, Edgar; Oshman, Sarah; Fallah Abed, Pooria

2016-09-01

Clinicians have many treatment techniques from which to choose when extracting a failing tooth and replacing it with an implant-supported restoration and when successful management of an extraction socket during the course of tooth replacement is necessary to achieve predictable and esthetic outcomes. This article presents a straightforward, yet thorough, classification for extraction sockets of single-rooted teeth and provides guidance to clinicians in the selection of appropriate and predictable treatment. The presented classification of extraction sockets for single-rooted teeth focuses on the topography of the extraction socket, while the protocol for treatment of each socket type factors in the shape of the remaining bone, the biotype, and the location of the socket whether it be in the mandible or maxilla. This system is based on the biologic foundations of wound healing and can help guide clinicians to successful treatment outcomes.

Field Telemetry of Blade-rotor Coupled Torsional Vibration at Matuura Power Station Number 1 Unit

NASA Technical Reports Server (NTRS)

Isii, Kuniyoshi; Murakami, Hideaki; Otawara, Yasuhiko; Okabe, Akira

1991-01-01

The quasi-modal reduction technique and finite element model (FEM) were used to construct an analytical model for the blade-rotor coupled torsional vibration of a steam turbine generator of the Matuura Power Station. A single rotor test was executed in order to evaluate umbrella vibration characteristics. Based on the single rotor test results and the quasi-modal procedure, the total rotor system was analyzed to predict coupled torsional frequencies. Finally, field measurement of the vibration of the last stage buckets was made, which confirmed that the double synchronous resonance was 124.2 Hz, meaning that the machine can be safely operated. The measured eigen values are very close to the predicted value. The single rotor test and this analytical procedure thus proved to be a valid technique to estimate coupled torsional vibration.

Constitutive and life modeling of single crystal blade alloys for root attachment analysis

NASA Technical Reports Server (NTRS)

Meyer, T. G.; Mccarthy, G. J.; Favrow, L. H.; Anton, D. L.; Bak, Joe

1988-01-01

Work to develop fatigue life prediction and constitutive models for uncoated attachment regions of single crystal gas turbine blades is described. At temperatures relevant to attachment regions, deformation is dominated by slip on crystallographic planes. However, fatigue crack initiation and early crack growth are not always observed to be crystallographic. The influence of natural occurring microporosity will be investigated by testing both hot isostatically pressed and conventionally cast PWA 1480 single crystal specimens. Several differnt specimen configurations and orientations relative to the natural crystal axes are being tested to investigate the influence of notch acuity and the material's anisotropy. Global and slip system stresses in the notched regions were determined from three dimensional stress analyses and will be used to develop fatigue life prediction models consistent with the observed lives and crack characteristics.

Remote detection of single emitters via optical waveguides

NASA Astrophysics Data System (ADS)

Then, Patrick; Razinskas, Gary; Feichtner, Thorsten; Haas, Philippe; Wild, Andreas; Bellini, Nicola; Osellame, Roberto; Cerullo, Giulio; Hecht, Bert

2014-05-01

The integration of lab-on-a-chip technologies with single-molecule detection techniques may enable new applications in analytical chemistry, biotechnology, and medicine. We describe a method based on the reciprocity theorem of electromagnetic theory to determine and optimize the detection efficiency of photons emitted by single quantum emitters through truncated dielectric waveguides of arbitrary shape positioned in their proximity. We demonstrate experimentally that detection of single quantum emitters via such waveguides is possible, confirming the predicted behavior of the detection efficiency. Our findings blaze the trail towards efficient lensless single-emitter detection compatible with large-scale optofluidic integration.

Single-legged Hop Tests as Predictors of Self-reported Knee Function After Anterior Cruciate Ligament Reconstruction

PubMed Central

Logerstedt, David; Grindem, Hege; Lynch, Andrew; Eitzen, Ingrid; Engebretsen, Lars; Risberg, May Arna; Axe, Michael J.; Snyder-Mackler, Lynn

2012-01-01

Background Single-legged hop tests are commonly used functional performance measures that can capture limb asymmetries in patients after anterior cruciate ligament (ACL) reconstruction. Hop tests hold potential as predictive factors of self-reported knee function in individuals after ACL reconstruction. Hypothesis Single-legged hop tests conducted preoperatively would not and 6 months after ACL reconstruction would predict self-reported knee function (International Knee Documentation Committee [IKDC] 2000) 1 year after ACL reconstruction. Study Design Cohort study (prognosis); Level of evidence, 2. Methods One hundred twenty patients who were treated with ACL reconstruction performed 4 single-legged hop tests preoperatively and 6 months after ACL reconstruction. Self-reported knee function within normal ranges was defined as IKDC 2000 scores greater than or equal to the age- and sex-specific normative 15th percentile score 1 year after surgery. Logistic regression analyses were performed to identify predictors of self-reported knee function within normal ranges. The area under the curve (AUC) from receiver operating characteristic curves was used as a measure of discriminative accuracy. Results Eighty-five patients completed single-legged hop tests 6 months after surgery and the 1-year follow-up with 68 patients classified as having self-reported knee function within normal ranges 1 year after reconstruction. The crossover hop and 6-m timed hop limb symmetry index (LSI) 6 months after ACL reconstruction were the strongest individual predictors of self-reported knee function (odds ratio, 1.09 and 1.10) and the only 2 tests in which the confidence intervals of the discriminatory accuracy (AUC) were above 0.5 (AUC = 0.68). Patients with knee function below normal ranges were over 5 times more likely of having a 6-m timed hop LSI lower than the 88% cutoff than those with knee function within normal ranges. Patients with knee function within normal ranges were 4 times more likely to have a crossover hop LSI greater than the 95% cutoff than those with knee function below normal ranges. No preoperative single-legged hop test predicted self-reported knee function within normal ranges 1 year after ACL reconstruction (all P > .353). Conclusion Single-legged hop tests conducted 6 months after ACL reconstruction can predict the likelihood of successful and unsuccessful outcome 1 year after ACL reconstruction. Patients demonstrating less than the 88% cutoff score on the 6-m timed hop test at 6 months may benefit from targeted training to improve limb symmetry in an attempt to normalize function. Patients with minimal side-to-side differences on the crossover hop test at 6 months possibly will have good knee function at 1 year if they continue with their current training regimen. Preoperative single-legged hop tests are not able to predict postoperative outcomes. PMID:22926749

Effect of dislocation pile-up on size-dependent yield strength in finite single-crystal micro-samples

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

Pan, Bo; Shibutani, Yoji, E-mail: sibutani@mech.eng.osaka-u.ac.jp; Zhang, Xu

2015-07-07

Recent research has explained that the steeply increasing yield strength in metals depends on decreasing sample size. In this work, we derive a statistical physical model of the yield strength of finite single-crystal micro-pillars that depends on single-ended dislocation pile-up inside the micro-pillars. We show that this size effect can be explained almost completely by considering the stochastic lengths of the dislocation source and the dislocation pile-up length in the single-crystal micro-pillars. The Hall–Petch-type relation holds even in a microscale single-crystal, which is characterized by its dislocation source lengths. Our quantitative conclusions suggest that the number of dislocation sources andmore » pile-ups are significant factors for the size effect. They also indicate that starvation of dislocation sources is another reason for the size effect. Moreover, we investigated the explicit relationship between the stacking fault energy and the dislocation “pile-up” effect inside the sample: materials with low stacking fault energy exhibit an obvious dislocation pile-up effect. Our proposed physical model predicts a sample strength that agrees well with experimental data, and our model can give a more precise prediction than the current single arm source model, especially for materials with low stacking fault energy.« less

Measurement and Modeling of Ultrasonic Pitch/catch Grain Noise

NASA Astrophysics Data System (ADS)

Margetan, F. J.; Gray, T. A.; Thompson, R. B.

2008-02-01

Ultrasonic grain noise arises from the scattering of sound waves by microstructural boundaries, and can limit the detection of weakly-reflecting internal defects in metals. In some cases of practical interest, such as focused-transducer inspections of aircraft engine components, so-called "single scattering" or "independent scatterer" models have proven to be reasonably accurate in predicting grain noise characteristics. In pulse/echo inspections it is difficult to experimentally assess the relative contributions of single scattering and multiple scattering, because both can generally contribute to the backscattered noise seen at any given observation time. For pitch/catch inspections, however, it is relatively easy to construct inspection geometries for which single-scattered noise should be insignificant, and hence any observed noise is presumably due to multiple scattering. This concept is demonstrated using pitch/catch shear-wave measurements performed on a well-characterized stainless-steel specimen. The inspection geometry allows us to control the overlap volume of the intersecting radiation fields of the two transducers. As we proceed from maximally overlapping fields to zero overlap, the single-scattering contribution to the observed grain noise is expected to decrease. Measurements are compared to the predictions of a single-scatterer model, and the relative contributions of single and multiple scattering to the observed grain noise are estimated.

In silico lineage tracing through single cell transcriptomics identifies a neural stem cell population in planarians.

PubMed

Molinaro, Alyssa M; Pearson, Bret J

2016-04-27

The planarian Schmidtea mediterranea is a master regenerator with a large adult stem cell compartment. The lack of transgenic labeling techniques in this animal has hindered the study of lineage progression and has made understanding the mechanisms of tissue regeneration a challenge. However, recent advances in single-cell transcriptomics and analysis methods allow for the discovery of novel cell lineages as differentiation progresses from stem cell to terminally differentiated cell. Here we apply pseudotime analysis and single-cell transcriptomics to identify adult stem cells belonging to specific cellular lineages and identify novel candidate genes for future in vivo lineage studies. We purify 168 single stem and progeny cells from the planarian head, which were subjected to single-cell RNA sequencing (scRNAseq). Pseudotime analysis with Waterfall and gene set enrichment analysis predicts a molecularly distinct neoblast sub-population with neural character (νNeoblasts) as well as a novel alternative lineage. Using the predicted νNeoblast markers, we demonstrate that a novel proliferative stem cell population exists adjacent to the brain. scRNAseq coupled with in silico lineage analysis offers a new approach for studying lineage progression in planarians. The lineages identified here are extracted from a highly heterogeneous dataset with minimal prior knowledge of planarian lineages, demonstrating that lineage purification by transgenic labeling is not a prerequisite for this approach. The identification of the νNeoblast lineage demonstrates the usefulness of the planarian system for computationally predicting cellular lineages in an adult context coupled with in vivo verification.

Single wall penetration equations

NASA Technical Reports Server (NTRS)

Hayashida, K. B.; Robinson, J. H.

1991-01-01

Five single plate penetration equations are compared for accuracy and effectiveness. These five equations are two well-known equations (Fish-Summers and Schmidt-Holsapple), two equations developed by the Apollo project (Rockwell and Johnson Space Center (JSC), and one recently revised from JSC (Cour-Palais). They were derived from test results, with velocities ranging up to 8 km/s. Microsoft Excel software was used to construct a spreadsheet to calculate the diameters and masses of projectiles for various velocities, varying the material properties of both projectile and target for the five single plate penetration equations. The results were plotted on diameter versus velocity graphs for ballistic and spallation limits using Cricket Graph software, for velocities ranging from 2 to 15 km/s defined for the orbital debris. First, these equations were compared to each other, then each equation was compared with various aluminum projectile densities. Finally, these equations were compared with test results performed at JSC for the Marshall Space Flight Center. These equations predict a wide variety of projectile diameters at a given velocity. Thus, it is very difficult to choose the 'right' prediction equation. The thickness of a single plate could have a large variation by choosing a different penetration equation. Even though all five equations are empirically developed with various materials, especially for aluminum alloys, one cannot be confident in the shield design with the predictions obtained by the penetration equations without verifying by tests.

Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials.

PubMed

Dias, Kaio Olímpio Das Graças; Gezan, Salvador Alejandro; Guimarães, Claudia Teixeira; Nazarian, Alireza; da Costa E Silva, Luciano; Parentoni, Sidney Netto; de Oliveira Guimarães, Paulo Evaristo; de Oliveira Anoni, Carina; Pádua, José Maria Villela; de Oliveira Pinto, Marcos; Noda, Roberto Willians; Ribeiro, Carlos Alexandre Gomes; de Magalhães, Jurandir Vieira; Garcia, Antonio Augusto Franco; de Souza, João Cândido; Guimarães, Lauro José Moreira; Pastina, Maria Marta

2018-07-01

Breeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multi-environment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids' genotypes were inferred based on their parents' genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS and using CV1, the AD model doubled the predictive accuracy in comparison to the A model. Through CV2, GS models benefit from borrowing information of correlated trials, resulting in an increase of 40% and 9% in the predictive accuracy of GY under WS for A and AD models, respectively. These results highlight the importance of multi-environment trial analyses using GS models that incorporate additive and dominance effects for genomic predictions of GY under drought in maize single-cross hybrids.

Editorial Commentary: Single-Image Slice Magnetic Resonance Imaging Assessments Do Not Predict 3-Dimensional Muscle Volume.

PubMed

Brand, Jefferson C

2016-01-01

No single-image magnetic resonance imaging (MRI) assessment-Goutallier classification, Fuchs classification, or cross-sectional area-is predictive of whole-muscle volume or fatty atrophy of the supraspinatus or infraspinatus. Rather, 3-dimensional MRI measurement of whole-muscle volume and fat-free muscle volume is required and is associated with shoulder strength, which is clinically relevant. Three-dimensional MRI may represent a new gold standard for assessment of the rotator cuff musculature using imaging and may help to predict the feasibility of repair of a rotator cuff tear as well as the postoperative outcome. Unfortunately, 3-dimensional MRI assessment of muscle volume is labor intensive and is not widely available for clinical use. Copyright © 2016 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Aerodynamic/acoustic performance of YJ101/double bypass VCE with coannular plug nozzle

NASA Technical Reports Server (NTRS)

Vdoviak, J. W.; Knott, P. R.; Ebacker, J. J.

1981-01-01

Results of a forward Variable Area Bypass Injector test and a Coannular Nozzle test performed on a YJ101 Double Bypass Variable Cycle Engine are reported. These components are intended for use on a Variable Cycle Engine. The forward Variable Area Bypass Injector test demonstrated the mode shifting capability between single and double bypass operation with less than predicted aerodynamic losses in the bypass duct. The acoustic nozzle test demonstrated that coannular noise suppression was between 4 and 6 PNdB in the aft quadrant. The YJ101 VCE equipped with the forward VABI and the coannular exhaust nozzle performed as predicted with exhaust system aerodynamic losses lower than predicted both in single and double bypass modes. Extensive acoustic data were collected including far field, near field, sound separation/ internal probe measurements as Laser Velocimeter traverses.

A consensus least squares support vector regression (LS-SVR) for analysis of near-infrared spectra of plant samples.

PubMed

Li, Yankun; Shao, Xueguang; Cai, Wensheng

2007-04-15

Consensus modeling of combining the results of multiple independent models to produce a single prediction avoids the instability of single model. Based on the principle of consensus modeling, a consensus least squares support vector regression (LS-SVR) method for calibrating the near-infrared (NIR) spectra was proposed. In the proposed approach, NIR spectra of plant samples were firstly preprocessed using discrete wavelet transform (DWT) for filtering the spectral background and noise, then, consensus LS-SVR technique was used for building the calibration model. With an optimization of the parameters involved in the modeling, a satisfied model was achieved for predicting the content of reducing sugar in plant samples. The predicted results show that consensus LS-SVR model is more robust and reliable than the conventional partial least squares (PLS) and LS-SVR methods.

A coupled ductile fracture phase-field model for crystal plasticity

NASA Astrophysics Data System (ADS)

Hernandez Padilla, Carlos Alberto; Markert, Bernd

2017-07-01

Nowadays crack initiation and evolution play a key role in the design of mechanical components. In the past few decades, several numerical approaches have been developed with the objective to predict these phenomena. The objective of this work is to present a simplified, nonetheless representative phenomenological model to predict the crack evolution of ductile fracture in single crystals. The proposed numerical approach is carried out by merging a conventional elasto-plastic crystal plasticity model and a phase-field model modified to predict ductile fracture. A two-dimensional initial boundary value problem of ductile fracture is introduced considering a single-crystal setup and Nickel-base superalloy material properties. The model is implemented into the finite element context subjected to a quasi-static uniaxial tension test. The results are then qualitatively analyzed and briefly compared to current benchmark results in the literature.

A general mechanism for competitor-induced dissociation of molecular complexes

PubMed Central

Paramanathan, Thayaparan; Reeves, Daniel; Friedman, Larry J.; Kondev, Jane; Gelles, Jeff

2014-01-01

The kinetic stability of non-covalent macromolecular complexes controls many biological phenomena. Here we find that physical models of complex dissociation predict that competitor molecules will in general accelerate the breakdown of isolated bimolecular complexes by occluding rapid rebinding of the two binding partners. This prediction is largely independent of molecular details. We confirm the prediction with single-molecule fluorescence experiments on a well-characterized DNA strand dissociation reaction. Contrary to common assumptions, competitor–induced acceleration of dissociation can occur in biologically relevant competitor concentration ranges and does not necessarily implyternary association of competitor with the bimolecular complex. Thus, occlusion of complex rebinding may play a significant role in a variety of biomolecular processes. The results also show that single-molecule colocalization experiments can accurately measure dissociation rates despite their limited spatio temporal resolution. PMID:25342513

Vector Sum Excited Linear Prediction (VSELP) speech coding at 4.8 kbps

NASA Technical Reports Server (NTRS)

Gerson, Ira A.; Jasiuk, Mark A.

1990-01-01

Code Excited Linear Prediction (CELP) speech coders exhibit good performance at data rates as low as 4800 bps. The major drawback to CELP type coders is their larger computational requirements. The Vector Sum Excited Linear Prediction (VSELP) speech coder utilizes a codebook with a structure which allows for a very efficient search procedure. Other advantages of the VSELP codebook structure is discussed and a detailed description of a 4.8 kbps VSELP coder is given. This coder is an improved version of the VSELP algorithm, which finished first in the NSA's evaluation of the 4.8 kbps speech coders. The coder uses a subsample resolution single tap long term predictor, a single VSELP excitation codebook, a novel gain quantizer which is robust to channel errors, and a new adaptive pre/postfilter arrangement.

Classifier ensemble based on feature selection and diversity measures for predicting the affinity of A(2B) adenosine receptor antagonists.

PubMed

Bonet, Isis; Franco-Montero, Pedro; Rivero, Virginia; Teijeira, Marta; Borges, Fernanda; Uriarte, Eugenio; Morales Helguera, Aliuska

2013-12-23

A(2B) adenosine receptor antagonists may be beneficial in treating diseases like asthma, diabetes, diabetic retinopathy, and certain cancers. This has stimulated research for the development of potent ligands for this subtype, based on quantitative structure-affinity relationships. In this work, a new ensemble machine learning algorithm is proposed for classification and prediction of the ligand-binding affinity of A(2B) adenosine receptor antagonists. This algorithm is based on the training of different classifier models with multiple training sets (composed of the same compounds but represented by diverse features). The k-nearest neighbor, decision trees, neural networks, and support vector machines were used as single classifiers. To select the base classifiers for combining into the ensemble, several diversity measures were employed. The final multiclassifier prediction results were computed from the output obtained by using a combination of selected base classifiers output, by utilizing different mathematical functions including the following: majority vote, maximum and average probability. In this work, 10-fold cross- and external validation were used. The strategy led to the following results: i) the single classifiers, together with previous features selections, resulted in good overall accuracy, ii) a comparison between single classifiers, and their combinations in the multiclassifier model, showed that using our ensemble gave a better performance than the single classifier model, and iii) our multiclassifier model performed better than the most widely used multiclassifier models in the literature. The results and statistical analysis demonstrated the supremacy of our multiclassifier approach for predicting the affinity of A(2B) adenosine receptor antagonists, and it can be used to develop other QSAR models.

Evaluation of Material Models within LS-DYNA(Registered TradeMark) for a Kevlar/Epoxy Composite Honeycomb

NASA Technical Reports Server (NTRS)

Polanco, Michael A.; Kellas, Sotiris; Jackson, Karen

2009-01-01

The performance of material models to simulate a novel composite honeycomb Deployable Energy Absorber (DEA) was evaluated using the nonlinear explicit dynamic finite element code LS-DYNA(Registered TradeMark). Prototypes of the DEA concept were manufactured using a Kevlar/Epoxy composite material in which the fibers are oriented at +/-45 degrees with respect to the loading axis. The development of the DEA has included laboratory tests at subcomponent and component levels such as three-point bend testing of single hexagonal cells, dynamic crush testing of single multi-cell components, and impact testing of a full-scale fuselage section fitted with a system of DEA components onto multi-terrain environments. Due to the thin nature of the cell walls, the DEA was modeled using shell elements. In an attempt to simulate the dynamic response of the DEA, it was first represented using *MAT_LAMINATED_COMPOSITE_FABRIC, or *MAT_58, in LS-DYNA. Values for each parameter within the material model were generated such that an in-plane isotropic configuration for the DEA material was assumed. Analytical predictions showed that the load-deflection behavior of a single-cell during three-point bending was within the range of test data, but predicted the DEA crush response to be very stiff. In addition, a *MAT_PIECEWISE_LINEAR_PLASTICITY, or *MAT_24, material model in LS-DYNA was developed, which represented the Kevlar/Epoxy composite as an isotropic elastic-plastic material with input from +/-45 degrees tensile coupon data. The predicted crush response matched that of the test and localized folding patterns of the DEA were captured under compression, but the model failed to predict the single-cell three-point bending response.

Predictive parameters for return to pre-injury level of sport 6 months following anterior cruciate ligament reconstruction surgery.

PubMed

Müller, Ulrike; Krüger-Franke, Michael; Schmidt, Michael; Rosemeyer, Bernd

2015-12-01

The aim of the study was to find predictive parameters for a successful resumption of pre-injury level of sport 6 months post anterior cruciate ligament (ACL) reconstruction. In a prospective study, 40 patients with a ruptured ACL were surgically treated with semitendinosus tendon autograft. Six months after surgery, strength of knee extensors and flexors, four single-leg hop tests, Anterior Cruciate Ligament-Return to Sport after Injury Scale (ACL-RSI), subjective International Knee Documentation Committee (IKDC) 2000 and the Tampa Scale of Kinesiophobia-11 (TSK-11) were assessed. Seven months post-operatively, a standardized interview was conducted to identify "return to sport" (RS) and "non-return to sport" (nRS) patients. Logistic regression and "Receiver Operating Characteristic" (ROC) analyses were used to determine predictive parameters. No significant differences could be detected between RS and nRS patients concerning socio-demographic data, muscle tests, square hop and TSK-11. In nRS patients, the Limb Symmetry Index (LSI) of single hop for distance (p = 0.005), crossover hop (p = 0.008) and triple hop (p = 0.001) were significantly lower, in addition to the ACL-RSI (p = 0.013) and IKDC 2000 (p = 0.037). The cut-off points for LSI single hop for distance were 75.4 % (sensitivity 0.74; specificity 0.88), and for ACL-RSI 51.3 points (sensitivity 0.97; specificity 0.63). Logistic regression distinguished between RS and nRS subjects (sensitivity 0.97; specificity 0.63). The single hop for distance and ACL-RSI were found to be the strongest predictive parameters, assessing both the objective functional and the subjective psychological aspects of returning to sport. Both tests may help to identify patients at risk of not returning to pre-injury sport. II.

Calculations of single crystal elastic constants for yttria partially stabilised zirconia from powder diffraction data

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

Lunt, A. J. G., E-mail: alexander.lunt@eng.ox.ac.uk; Xie, M. Y.; Baimpas, N.

2014-08-07

Yttria Stabilised Zirconia (YSZ) is a tough, phase-transforming ceramic that finds use in a wide range of commercial applications from dental prostheses to thermal barrier coatings. Micromechanical modelling of phase transformation can deliver reliable predictions in terms of the influence of temperature and stress. However, models must rely on the accurate knowledge of single crystal elastic stiffness constants. Some techniques for elastic stiffness determination are well-established. The most popular of these involve exploiting frequency shifts and phase velocities of acoustic waves. However, the application of these techniques to YSZ can be problematic due to the micro-twinning observed in larger crystals.more » Here, we propose an alternative approach based on selective elastic strain sampling (e.g., by diffraction) of grain ensembles sharing certain orientation, and the prediction of the same quantities by polycrystalline modelling, for example, the Reuss or Voigt average. The inverse problem arises consisting of adjusting the single crystal stiffness matrix to match the polycrystal predictions to observations. In the present model-matching study, we sought to determine the single crystal stiffness matrix of tetragonal YSZ using the results of time-of-flight neutron diffraction obtained from an in situ compression experiment and Finite Element modelling of the deformation of polycrystalline tetragonal YSZ. The best match between the model predictions and observations was obtained for the optimized stiffness values of C11 = 451, C33 = 302, C44 = 39, C66 = 82, C12 = 240, and C13 = 50 (units: GPa). Considering the significant amount of scatter in the published literature data, our result appears reasonably consistent.« less

An Experimental Study of Pressure Oscillation in a Capillary Pumped Loop with Multiple Evaporators and Condensers

NASA Technical Reports Server (NTRS)

Ku, Jen-Tung; Hoang, Triem T.

1998-01-01

The heat transport capability of a capillary pumped loop (CPL) is limited by the pressure drop that its evaporator wick can sustain. The pressure drop in a CPL is not constant even under seemingly steady operation, but rather exhibits an oscillatory behavior. A hydrodynamic theory based on a mass-spring-dashpot model was previously developed to predict the pressure oscillation in a CPL with a single evaporator and a single condenser. The theory states that the pressure oscillation is a function of physical dimensions of the CPL components and operating conditions. Experimental data agreed very well with theoretical predictions. The hydrodynamic stability theory has recently been extended to predict the pressure oscillations in CPLs with multiple evaporators and multiple condensers. Concurrently, an experimental study was conducted to verify the theory and to investigate the effects of various parameters on the pressure oscillation. Four evaporators with different wick properties were tested using a test loop containing two condenser plates. The test loop allowed the four evaporators to be tested in a single-pump, two-pump or four-pump configuration, and the two condenser plates to be plumbed either in parallel or in series. Test conditions included varying the power input, the reservoir set point temperature, the condenser sink temperature, and the flow resistance between the reservoir and the loop. Experimental results agreed well with theoretical predictions.

Prediction of peripheral neuropathy in multiple myeloma patients receiving bortezomib and thalidomide: a genetic study based on a single nucleotide polymorphism array.

PubMed

García-Sanz, Ramón; Corchete, Luis Antonio; Alcoceba, Miguel; Chillon, María Carmen; Jiménez, Cristina; Prieto, Isabel; García-Álvarez, María; Puig, Noemi; Rapado, Immaculada; Barrio, Santiago; Oriol, Albert; Blanchard, María Jesús; de la Rubia, Javier; Martínez, Rafael; Lahuerta, Juan José; González Díaz, Marcos; Mateos, María Victoria; San Miguel, Jesús Fernando; Martínez-López, Joaquín; Sarasquete, María Eugenia

2017-12-01

Bortezomib- and thalidomide-based therapies have significantly contributed to improved survival of multiple myeloma (MM) patients. However, treatment-induced peripheral neuropathy (TiPN) is a common adverse event associated with them. Risk factors for TiPN in MM patients include advanced age, prior neuropathy, and other drugs, but there are conflicting results about the role of genetics in predicting the risk of TiPN. Thus, we carried out a genome-wide association study based on more than 300 000 exome single nucleotide polymorphisms in 172 MM patients receiving therapy involving bortezomib and thalidomide. We compared patients developing and not developing TiPN under similar treatment conditions (GEM05MAS65, NCT00443235). The highest-ranking single nucleotide polymorphism was rs45443101, located in the PLCG2 gene, but no significant differences were found after multiple comparison correction (adjusted P = .1708). Prediction analyses, cytoband enrichment, and pathway analyses were also performed, but none yielded any significant findings. A copy number approach was also explored, but this gave no significant results either. In summary, our study did not find a consistent genetic component associated with TiPN under bortezomib and thalidomide therapies that could be used for prediction, which makes clinical judgment essential in the practical management of MM treatment. Copyright © 2016 John Wiley & Sons, Ltd.

Male scarcity is associated with higher prevalence of premature gestation and low birth weight births across the United States.

PubMed

Kruger, Daniel J; Clark, Jillian; Vanas, Sarah

2013-01-01

Modern adverse birth outcomes may partially result from mechanisms evolved to evaluate environmental conditions and regulate maternal investment trade-offs. Male scarcity in a population is associated with a cluster of characteristics related to higher mating effort and lower paternal investment. We predicted that modern populations with male scarcity would have shorter gestational times and lower birth weights on average. We compared US Centers for Disease Control and Prevention county-aggregated year 2000 birth records with US Decennial Census data. We combined these data in a path model with the degree of male scarcity and known socio-economic predictors of birth outcomes as exogenous predictors of prematurity and low birth weight, with single mother households as a proportion of families with children as a mediator (N = 450). Male scarcity was directly associated with higher rates of low birth weight. Male scarcity made significant indirect predictions of rates of prematurity and low birth weight, as mediated by the proportion of families headed by single mothers. Aggregate socio-economic status also indirectly predicted birth outcomes, as mediated by the proportion of families headed by single mothers, whereas the proportion African American retained both direct and indirect predictions of adverse birth outcomes. Male scarcity influences life history tradeoffs, with consequences for important social and public health issues such as adverse birth outcomes. Copyright © 2013 Wiley Periodicals, Inc.

Estimating needle tip deflection in biological tissue from a single transverse ultrasound image: application to brachytherapy.

PubMed

Rossa, Carlos; Sloboda, Ron; Usmani, Nawaid; Tavakoli, Mahdi

2016-07-01

This paper proposes a method to predict the deflection of a flexible needle inserted into soft tissue based on the observation of deflection at a single point along the needle shaft. We model the needle-tissue as a discretized structure composed of several virtual, weightless, rigid links connected by virtual helical springs whose stiffness coefficient is found using a pattern search algorithm that only requires the force applied at the needle tip during insertion and the needle deflection measured at an arbitrary insertion depth. Needle tip deflections can then be predicted for different insertion depths. Verification of the proposed method in synthetic and biological tissue shows a deflection estimation error of [Formula: see text]2 mm for images acquired at 35 % or more of the maximum insertion depth, and decreases to 1 mm for images acquired closer to the final insertion depth. We also demonstrate the utility of the model for prostate brachytherapy, where in vivo needle deflection measurements obtained during early stages of insertion are used to predict the needle deflection further along the insertion process. The method can predict needle deflection based on the observation of deflection at a single point. The ultrasound probe can be maintained at the same position during insertion of the needle, which avoids complications of tissue deformation caused by the motion of the ultrasound probe.

The Social Context of Undermining Behavior at Work

ERIC Educational Resources Information Center

Duffy, Michelle K.; Ganster, Daniel C.; Shaw, Jason D.; Johnson, Jonathan L.; Pagon, Milan

2006-01-01

We developed a fairness theory perspective to explain the experience of being "singled out" for social undermining from supervisors and coworkers, and tested our predictions across four distinct social contexts. We argued and predicted that attitudinal and behavioral reactions to undermining (from supervisors and coworkers) would be…

Development of standardized component\\0x2010based equipment specifications and transition plan into a predictive maintenance strategy.

DOT National Transportation Integrated Search

2015-12-01

This project investigated INDOT equipment records and equipment industry standards to produce standard equipment specifications : and a predictive maintenance schedule for the more than 1100 single and tandem axle trucks in use at INDOT. The research...

Optimal design of low-density SNP arrays for genomic prediction: algorithm and applications

USDA-ARS?s Scientific Manuscript database

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for their optimal design. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optim...

Intraindividual variability in executive functions but not speed of processing or conflict resolution predicts performance differences in gait speed in older adults.

PubMed

Holtzer, Roee; Mahoney, Jeannette; Verghese, Joe

2014-08-01

The relationship between executive functions (EF) and gait speed is well established. However, with the exception of dual tasking, the key components of EF that predict differences in gait performance have not been determined. Therefore, the current study was designed to determine whether processing speed, conflict resolution, and intraindividual variability in EF predicted variance in gait performance in single- and dual-task conditions. Participants were 234 nondemented older adults (mean age 76.48 years; 55% women) enrolled in a community-based cohort study. Gait speed was assessed using an instrumented walkway during single- and dual-task conditions. The flanker task was used to assess EF. Results from the linear mixed effects model showed that (a) dual-task interference caused a significant dual-task cost in gait speed (estimate = 35.99; 95% CI = 33.19-38.80) and (b) of the cognitive predictors, only intraindividual variability was associated with gait speed (estimate = -.606; 95% CI = -1.11 to -.10). In unadjusted analyses, the three EF measures were related to gait speed in single- and dual-task conditions. However, in fully adjusted linear regression analysis, only intraindividual variability predicted performance differences in gait speed during dual tasking (B = -.901; 95% CI = -1.557 to -.245). Among the three EF measures assessed, intraindividual variability but not speed of processing or conflict resolution predicted performance differences in gait speed. © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Circular dichroism in photo-single-ionization of unoriented atoms.

PubMed

Feagin, James M

2002-01-28

We predict circular dichroism in photo-single-ionization angular distributions from spherically symmetric atomic states if the ionized electron is detected using two-slit interferometry. We demonstrate that the resulting electron interference pattern captures phase information on quadrupole corrections to the photoionization amplitude lost in conventional angular distributions.

Use of causative variants and SNP weighting in a single-step GBLUP context

USDA-ARS?s Scientific Manuscript database

Much effort has been recently put into identifying causative quantitative trait nucleotides (QTN) in animal breeding, aiming genomic prediction. Among the genomic methods available, single-step GBLUP (ssGBLUP) became the choice because of its simplicity and potentially higher accuracy. When QTN are ...

CORMIX1: AN EXPERT SYSTEM FOR MIXING ZONE ANALYSIS OF TOXIC AND CONVENTIONAL, SINGLE PORT AQUATIC DISCHARGES

EPA Science Inventory

An expert system, CORMIX1, was developed to predict the dilution and trajectory of a single buoyant discharge into an unstratified aquatic environment with and without crossflow. The system uses knowledge and inference rules obtained from hydrodynamic experts to classify and pred...

Realized gain from breeding Eucalyptus grandis in Florida

Treesearch

George Meskimen

1983-01-01

E. grandis is in the fourth generation of selection in southwest Florida. The breeding strategy combines a provenance trial, genetic base population, seedling seed orchard, and progeny test in a single plantation where all families are completely randomized in single-tree plots. That planting configuration closely predicted the magnitude of genetic...

Preservice Teachers' Computer Use in Single Computer Training Courses; Relationships and Predictions

ERIC Educational Resources Information Center

Zogheib, Salah

2015-01-01

Single computer courses offered at colleges of education are expected to provide preservice teachers with the skills and expertise needed to adopt computer technology in their future classrooms. However, preservice teachers still find difficulty adopting such technology. This research paper investigated relationships among preservice teachers'…

Attentional Control via Parallel Target-Templates in Dual-Target Search

PubMed Central

Barrett, Doug J. K.; Zobay, Oliver

2014-01-01

Simultaneous search for two targets has been shown to be slower and less accurate than independent searches for the same two targets. Recent research suggests this ‘dual-target cost’ may be attributable to a limit in the number of target-templates than can guide search at any one time. The current study investigated this possibility by comparing behavioural responses during single- and dual-target searches for targets defined by their orientation. The results revealed an increase in reaction times for dual- compared to single-target searches that was largely independent of the number of items in the display. Response accuracy also decreased on dual- compared to single-target searches: dual-target accuracy was higher than predicted by a model restricting search guidance to a single target-template and lower than predicted by a model simulating two independent single-target searches. These results are consistent with a parallel model of dual-target search in which attentional control is exerted by more than one target-template at a time. The requirement to maintain two target-templates simultaneously, however, appears to impose a reduction in the specificity of the memory representation that guides search for each target. PMID:24489793

Collimator-free photon tomography

DOEpatents

Dilmanian, F. Avraham; Barbour, Randall L.

1998-10-06

A method of uncollimated single photon emission computed tomography includes administering a radioisotope to a patient for producing gamma ray photons from a source inside the patient. Emissivity of the photons is measured externally of the patient with an uncollimated gamma camera at a plurality of measurement positions surrounding the patient for obtaining corresponding energy spectrums thereat. Photon emissivity at the plurality of measurement positions is predicted using an initial prediction of an image of the source. The predicted and measured photon emissivities are compared to obtain differences therebetween. Prediction and comparison is iterated by updating the image prediction until the differences are below a threshold for obtaining a final prediction of the source image.

SVM and SVM Ensembles in Breast Cancer Prediction.

PubMed

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

SVM and SVM Ensembles in Breast Cancer Prediction

PubMed Central

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers. PMID:28060807

The importance of different frequency bands in predicting subcutaneous glucose concentration in type 1 diabetic patients.

PubMed

Lu, Yinghui; Gribok, Andrei V; Ward, W Kenneth; Reifman, Jaques

2010-08-01

We investigated the relative importance and predictive power of different frequency bands of subcutaneous glucose signals for the short-term (0-50 min) forecasting of glucose concentrations in type 1 diabetic patients with data-driven autoregressive (AR) models. The study data consisted of minute-by-minute glucose signals collected from nine deidentified patients over a five-day period using continuous glucose monitoring devices. AR models were developed using single and pairwise combinations of frequency bands of the glucose signal and compared with a reference model including all bands. The results suggest that: for open-loop applications, there is no need to explicitly represent exogenous inputs, such as meals and insulin intake, in AR models; models based on a single-frequency band, with periods between 60-120 min and 150-500 min, yield good predictive power (error <3 mg/dL) for prediction horizons of up to 25 min; models based on pairs of bands produce predictions that are indistinguishable from those of the reference model as long as the 60-120 min period band is included; and AR models can be developed on signals of short length (approximately 300 min), i.e., ignoring long circadian rhythms, without any detriment in prediction accuracy. Together, these findings provide insights into efficient development of more effective and parsimonious data-driven models for short-term prediction of glucose concentrations in diabetic patients.

DBH Prediction Using Allometry Described by Bivariate Copula Distribution

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The Influence of Viscous Effects on Ice Accretion Prediction and Airfoil Performance Predictions

NASA Technical Reports Server (NTRS)

Kreeger, Richard E.; Wright, William B.

2005-01-01

A computational study was conducted to evaluate the effectiveness of using a viscous flow solution in an ice accretion code and the resulting accuracy of aerodynamic performance prediction. Ice shapes were obtained for one single-element and one multi-element airfoil using both potential flow and Navier-Stokes flowfields in the LEWICE ice accretion code. Aerodynamics were then calculated using a Navier-Stokes flow solver.

Lumbar spine: pretest predictability of CT findings

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

Giles, D.J.; Thomas, R.J.; Osborn, A.G.

Demographic and symptomatic data gathered from 460 patients referred for lumbosacral CT examinations were analyzed to determine if the prescan probability of normal or abnormal findings could be predicted accurately. The authors were unable to predict the presence of herniated disk on the basis of patient-supplied data alone. Age was the single most significant predictor of an abnormality and was sharply related to degenerative disease and spinal stenosis.

In silico prediction of splice-altering single nucleotide variants in the human genome.

PubMed

Jian, Xueqiu; Boerwinkle, Eric; Liu, Xiaoming

2014-12-16

In silico tools have been developed to predict variants that may have an impact on pre-mRNA splicing. The major limitation of the application of these tools to basic research and clinical practice is the difficulty in interpreting the output. Most tools only predict potential splice sites given a DNA sequence without measuring splicing signal changes caused by a variant. Another limitation is the lack of large-scale evaluation studies of these tools. We compared eight in silico tools on 2959 single nucleotide variants within splicing consensus regions (scSNVs) using receiver operating characteristic analysis. The Position Weight Matrix model and MaxEntScan outperformed other methods. Two ensemble learning methods, adaptive boosting and random forests, were used to construct models that take advantage of individual methods. Both models further improved prediction, with outputs of directly interpretable prediction scores. We applied our ensemble scores to scSNVs from the Catalogue of Somatic Mutations in Cancer database. Analysis showed that predicted splice-altering scSNVs are enriched in recurrent scSNVs and known cancer genes. We pre-computed our ensemble scores for all potential scSNVs across the human genome, providing a whole genome level resource for identifying splice-altering scSNVs discovered from large-scale sequencing studies.

Mortality risk score prediction in an elderly population using machine learning.

PubMed

Rose, Sherri

2013-03-01

Standard practice for prediction often relies on parametric regression methods. Interesting new methods from the machine learning literature have been introduced in epidemiologic studies, such as random forest and neural networks. However, a priori, an investigator will not know which algorithm to select and may wish to try several. Here I apply the super learner, an ensembling machine learning approach that combines multiple algorithms into a single algorithm and returns a prediction function with the best cross-validated mean squared error. Super learning is a generalization of stacking methods. I used super learning in the Study of Physical Performance and Age-Related Changes in Sonomans (SPPARCS) to predict death among 2,066 residents of Sonoma, California, aged 54 years or more during the period 1993-1999. The super learner for predicting death (risk score) improved upon all single algorithms in the collection of algorithms, although its performance was similar to that of several algorithms. Super learner outperformed the worst algorithm (neural networks) by 44% with respect to estimated cross-validated mean squared error and had an R2 value of 0.201. The improvement of super learner over random forest with respect to R2 was approximately 2-fold. Alternatives for risk score prediction include the super learner, which can provide improved performance.

Prediction of global and local model quality in CASP8 using the ModFOLD server.

PubMed

McGuffin, Liam J

2009-01-01

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0--an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/. Copyright 2009 Wiley-Liss, Inc.

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

PubMed Central

Bandeira e Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-01-01

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. PMID:28455415

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

PubMed

Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-06-07

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

Genomic prediction of piglet response to infection with one of two porcine reproductive and respiratory syndrome virus isolates.

PubMed

Waide, Emily H; Tuggle, Christopher K; Serão, Nick V L; Schroyen, Martine; Hess, Andrew; Rowland, Raymond R R; Lunney, Joan K; Plastow, Graham; Dekkers, Jack C M

2018-02-01

Genomic prediction of the pig's response to the porcine reproductive and respiratory syndrome (PRRS) virus (PRRSV) would be a useful tool in the swine industry. This study investigated the accuracy of genomic prediction based on porcine SNP60 Beadchip data using training and validation datasets from populations with different genetic backgrounds that were challenged with different PRRSV isolates. Genomic prediction accuracy averaged 0.34 for viral load (VL) and 0.23 for weight gain (WG) following experimental PRRSV challenge, which demonstrates that genomic selection could be used to improve response to PRRSV infection. Training on WG data during infection with a less virulent PRRSV, KS06, resulted in poor accuracy of prediction for WG during infection with a more virulent PRRSV, NVSL. Inclusion of single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium with a major quantitative trait locus (QTL) on chromosome 4 was vital for accurate prediction of VL. Overall, SNPs that were significantly associated with either trait in single SNP genome-wide association analysis were unable to predict the phenotypes with an accuracy as high as that obtained by using all genotyped SNPs across the genome. Inclusion of data from close relatives into the training population increased whole genome prediction accuracy by 33% for VL and by 37% for WG but did not affect the accuracy of prediction when using only SNPs in the major QTL region. Results show that genomic prediction of response to PRRSV infection is moderately accurate and, when using all SNPs on the porcine SNP60 Beadchip, is not very sensitive to differences in virulence of the PRRSV in training and validation populations. Including close relatives in the training population increased prediction accuracy when using the whole genome or SNPs other than those near a major QTL.

Correlates of a Single-Item Indicator Versus a Multi-Item Scale of Outness About Same-Sex Attraction

PubMed Central

Noor, Syed W.; Galos, Dylan L.; Simon Rosser, B. R.

2017-01-01

In this study, we investigated if a single-item indicator measured the degree to which people were open about their same-sex attraction (“out”) as accurately as a multi-item scale. For the multi-item scale, we used the Outness Inventory, which includes three subscales: family, world, and religion. We examined correlations between the single- and multi-item measures; between the single-item indicator and the subscales of the multi-item scale; and between the measures and internalized homonegativity, social attitudes towards homosexuality, and depressive symptoms. In addition, we calculated Tjur’s R2 as a measure of predictive power of the single-item indicator, multi-item scale, and subscales of the multi-item scale in predicting two health-related outcomes: depressive symptoms and condomless anal sex with multiple partners. There was a strong correlation between the single- and multi-item measures (r = 0.73). Furthermore, there were strong correlations between the single-item indicator and each subscale of the multi-item scale: family (r = 0.70), world (r = 0.77), and religion (r = 0.50). In addition, the correlations between the single-item indicator and internalized homonegativity (r = −0.63), social attitudes towards homosexuality (r = −0.38), and depression (r = −0.14) were higher than those between the multi-item scale and internalized homonegativity (r = −0.55), social attitudes towards homosexuality (r = −0.21), and depression (r = −0.13). Contrary to the premise that multi-item measures are superior to single-item measures, our collective findings indicate that the single-item indicator of outness performs better than the multi-item scale of outness. PMID:26292840

Evaluation of an ensemble of genetic models for prediction of a quantitative trait.

PubMed

Milton, Jacqueline N; Steinberg, Martin H; Sebastiani, Paola

2014-01-01

Many genetic markers have been shown to be associated with common quantitative traits in genome-wide association studies. Typically these associated genetic markers have small to modest effect sizes and individually they explain only a small amount of the variability of the phenotype. In order to build a genetic prediction model without fitting a multiple linear regression model with possibly hundreds of genetic markers as predictors, researchers often summarize the joint effect of risk alleles into a genetic score that is used as a covariate in the genetic prediction model. However, the prediction accuracy can be highly variable and selecting the optimal number of markers to be included in the genetic score is challenging. In this manuscript we present a strategy to build an ensemble of genetic prediction models from data and we show that the ensemble-based method makes the challenge of choosing the number of genetic markers more amenable. Using simulated data with varying heritability and number of genetic markers, we compare the predictive accuracy and inclusion of true positive and false positive markers of a single genetic prediction model and our proposed ensemble method. The results show that the ensemble of genetic models tends to include a larger number of genetic variants than a single genetic model and it is more likely to include all of the true genetic markers. This increased sensitivity is obtained at the price of a lower specificity that appears to minimally affect the predictive accuracy of the ensemble.

Using Forecasting to Predict Long-Term Resource Utilization for Web Services

ERIC Educational Resources Information Center

Yoas, Daniel W.

2013-01-01

Researchers have spent years understanding resource utilization to improve scheduling, load balancing, and system management through short-term prediction of resource utilization. Early research focused primarily on single operating systems; later, interest shifted to distributed systems and, finally, into web services. In each case researchers…

Development of standardized component\\0x2010based equipment specifications and transition plan into a predictive maintenance strategy : final report.

DOT National Transportation Integrated Search

2015-12-01

This project investigated INDOT equipment records and equipment industry standards to produce standard equipment specifications : and a predictive maintenance schedule for the more than 1100 single and tandem axle trucks in use at INDOT. The research...

Relative Chemical Binding Affinities for Trout and Human Estrogen Receptor Using Different Competitive Binding Assays

EPA Science Inventory

Rainbow trout-based assays for estrogenicity are currently being used for development of predictive models based upon quantitative structure activity relationships. A predictive model based on a single species raises the question of whether this information is valid for other spe...

Dangerous Mindsets: How Beliefs about Intelligence Predict Motivational Change

ERIC Educational Resources Information Center

Haimovitz, Kyla; Wormington, Stephanie V.; Corpus, Jennifer Henderlong

2011-01-01

The present study examined how beliefs about intelligence, as mediated by ability-validation goals, predicted whether students lost or maintained levels of intrinsic motivation over the course of a single academic year. 978 third- through eighth-grade students were surveyed in the fall about their theories concerning the malleability of…

Predicting fire scars in Ozark timber species following prescribed burning

Treesearch

Aaron P. Stevenson; Richard P. Guyette; Rose-Marie Muzika

2009-01-01

A potential consequence of using prescribed fire is heat-related injury to timber trees. Scars formed following fire injuries are often associated with extensive decay in hardwoods. The ability to predict scarring caused by prescribed fire is important when multiple management goals are incorporated on a single forest site.

Development of burnup dependent fuel rod model in COBRA-TF

NASA Astrophysics Data System (ADS)

Yilmaz, Mine Ozdemir

The purpose of this research was to develop a burnup dependent fuel thermal conductivity model within Pennsylvania State University, Reactor Dynamics and Fuel Management Group (RDFMG) version of the subchannel thermal-hydraulics code COBRA-TF (CTF). The model takes into account first, the degradation of fuel thermal conductivity with high burnup; and second, the fuel thermal conductivity dependence on the Gadolinium content for both UO2 and MOX fuel rods. The modified Nuclear Fuel Industries (NFI) model for UO2 fuel rods and Duriez/Modified NFI Model for MOX fuel rods were incorporated into CTF and fuel centerline predictions were compared against Halden experimental test data and FRAPCON-3.4 predictions to validate the burnup dependent fuel thermal conductivity model in CTF. Experimental test cases from Halden reactor fuel rods for UO2 fuel rods at Beginning of Life (BOL), through lifetime without Gd2O3 and through lifetime with Gd 2O3 and a MOX fuel rod were simulated with CTF. Since test fuel rod and FRAPCON-3.4 results were based on single rod measurements, CTF was run for a single fuel rod surrounded with a single channel configuration. Input decks for CTF were developed for one fuel rod located at the center of a subchannel (rod-centered subchannel approach). Fuel centerline temperatures predicted by CTF were compared against the measurements from Halden experimental test data and the predictions from FRAPCON-3.4. After implementing the new fuel thermal conductivity model in CTF and validating the model with experimental data, CTF model was applied to steady state and transient calculations. 4x4 PWR fuel bundle configuration from Purdue MOX benchmark was used to apply the new model for steady state and transient calculations. First, one of each high burnup UO2 and MOX fuel rods from 4x4 matrix were selected to carry out single fuel rod calculations and fuel centerline temperatures predicted by CTF/TORT-TD were compared against CTF /TORT-TD /FRAPTRAN predictions. After confirming that the new fuel thermal conductivity model in CTF worked and provided consistent results with FRAPTRAN predictions for a single fuel rod configuration, the same type of analysis was carried out for a bigger system which is the 4x4 PWR bundle consisting of 15 fuel pins and one control guide tube. Steady- state calculations at Hot Full Power (HFP) conditions for control guide tube out (unrodded) were performed using the 4x4 PWR array with CTF/TORT-TD coupled code system. Fuel centerline, surface and average temperatures predicted by CTF/TORT-TD with and without the new fuel thermal conductivity model were compared against CTF/TORT-TD/FRAPTRAN predictions to demonstrate the improvement in fuel centerline predictions when new model was used. In addition to that constant and CTF dynamic gap conductance model were used with the new thermal conductivity model to show the performance of the CTF dynamic gap conductance model and its impact on fuel centerline and surface temperatures. Finally, a Rod Ejection Accident (REA) scenario using the same 4x4 PWR array was run both at Hot Zero Power (HZP) and Hot Full Power (HFP) condition, starting at a position where half of the control rod is inserted. This scenario was run using CTF/TORT-TD coupled code system with and without the new fuel thermal conductivity model. The purpose of this transient analysis was to show the impact of thermal conductivity degradation (TCD) on feedback effects, specifically Doppler Reactivity Coefficient (DRC) and, eventually, total core reactivity.

Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing.

PubMed

Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Chen, Charles; Porth, Ilga; El-Kassaby, Yousry A

2015-05-09

Genomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits of low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost. Genotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites in British Columbia, Canada. Four imputation algorithms were compared (mean value (MI), singular value decomposition (SVD), expectation maximization (EM), and a newly derived, family-based k-nearest neighbor (kNN-Fam)). Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about trait architecture. Finally, using PCA, multi-trait GS prediction models were developed. The EM and kNN-Fam imputation methods were superior for 30 and 60% missing data, respectively. The RR-BLUP GS prediction model produced better accuracies than the GRR indicating that the genetic architecture for these traits is complex. GS prediction accuracies for multi-site were high and better than those of single-sites while multi-site predictability produced the lowest accuracies reflecting type-b genetic correlations and deemed unreliable. The incorporation of genomic information in quantitative genetics analyses produced more realistic heritability estimates as half-sib pedigree tended to inflate the additive genetic variance and subsequently both heritability and gain estimates. Principle component scores as representatives of multi-trait GS prediction models produced surprising results where negatively correlated traits could be concurrently selected for using PCA2 and PCA3. The application of GS to open-pollinated family testing, the simplest form of tree improvement evaluation methods, was proven to be effective. Prediction accuracies obtained for all traits greatly support the integration of GS in tree breeding. While the within-site GS prediction accuracies were high, the results clearly indicate that single-site GS models ability to predict other sites are unreliable supporting the utilization of multi-site approach. Principle component scores provided an opportunity for the concurrent selection of traits with different phenotypic optima.

Analysis of Installed Measures and Energy Savings for Single-Family Residential Better Buildings Projects

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

Heaney, M.; Polly, B.

2015-04-30

This report presents an analysis of data for residential single-family projects reported by 37 organizations that were awarded federal financial assistance (cooperative agreements or grants) by the U.S. Department of Energy’s Better Buildings Neighborhood Program.1 The report characterizes the energy-efficiency measures installed for single-family residential projects and analyzes energy savings and savings prediction accuracy for measures installed in a subset of those projects.

Predictive test for chemotherapy response in resectable gastric cancer: a multi-cohort, retrospective analysis.

PubMed

Cheong, Jae-Ho; Yang, Han-Kwang; Kim, Hyunki; Kim, Woo Ho; Kim, Young-Woo; Kook, Myeong-Cherl; Park, Young-Kyu; Kim, Hyung-Ho; Lee, Hye Seung; Lee, Kyung Hee; Gu, Mi Jin; Kim, Ha Yan; Lee, Jinae; Choi, Seung Ho; Hong, Soonwon; Kim, Jong Won; Choi, Yoon Young; Hyung, Woo Jin; Jang, Eunji; Kim, Hyeseon; Huh, Yong-Min; Noh, Sung Hoon

2018-05-01

Adjuvant chemotherapy after surgery improves survival of patients with stage II-III, resectable gastric cancer. However, the overall survival benefit observed after adjuvant chemotherapy is moderate, suggesting that not all patients with resectable gastric cancer treated with adjuvant chemotherapy benefit from it. We aimed to develop and validate a predictive test for adjuvant chemotherapy response in patients with resectable, stage II-III gastric cancer. In this multi-cohort, retrospective study, we developed through a multi-step strategy a predictive test consisting of two rule-based classifier algorithms with predictive value for adjuvant chemotherapy response and prognosis. Exploratory bioinformatics analyses identified biologically relevant candidate genes in gastric cancer transcriptome datasets. In the discovery analysis, a four-gene, real-time RT-PCR assay was developed and analytically validated in formalin-fixed, paraffin-embedded (FFPE) tumour tissues from an internal cohort of 307 patients with stage II-III gastric cancer treated at the Yonsei Cancer Center with D2 gastrectomy plus adjuvant fluorouracil-based chemotherapy (n=193) or surgery alone (n=114). The same internal cohort was used to evaluate the prognostic and chemotherapy response predictive value of the single patient classifier genes using associations with 5-year overall survival. The results were validated with a subset (n=625) of FFPE tumour samples from an independent cohort of patients treated in the CLASSIC trial (NCT00411229), who received D2 gastrectomy plus capecitabine and oxaliplatin chemotherapy (n=323) or surgery alone (n=302). The primary endpoint was 5-year overall survival. We identified four classifier genes related to relevant gastric cancer features (GZMB, WARS, SFRP4, and CDX1) that formed the single patient classifier assay. In the validation cohort, the prognostic single patient classifier (based on the expression of GZMB, WARS, and SFRP4) identified 79 (13%) of 625 patients as low risk, 296 (47%) as intermediate risk, and 250 (40%) as high risk, and 5-year overall survival for these groups was 83·2% (95% CI 75·2-92·0), 74·8% (69·9-80·1), and 66·0% (60·1-72·4), respectively (p=0·012). The predictive single patient classifier (based on the expression of GZMB, WARS, and CDX1) assigned 281 (45%) of 625 patients in the validation cohort to the chemotherapy-benefit group and 344 (55%) to the no-benefit group. In the predicted chemotherapy-benefit group, 5-year overall survival was significantly improved in those patients who had received adjuvant chemotherapy after surgery compared with those who received surgery only (80% [95% CI 73·5-87·1] vs 64·5% [56·8-73·3]; univariate hazard ratio 0·47 [95% CI 0·30-0·75], p=0·0015), whereas no such improvement in 5-year overall survival was observed in the no-benefit group (72·9% [66·5-79·9] in patients who received chemotherapy plus surgery vs 72·5% [65·8-79·9] in patients who only had surgery; 0·93 [0·62-1·38], p=0·71). The predictive single patient classifier groups (chemotherapy benefit vs no-benefit) could predict adjuvant chemotherapy benefit in terms of 5-year overall survival in the validation cohort (p interaction =0·036 in univariate analysis). Similar results were obtained in the internal evaluation cohort. The single patient classifiers validated in this study provide clinically important prognostic information independent of standard risk-stratification methods and predicted chemotherapy response after surgery in two independent cohorts of patients with resectable, stage II-III gastric cancer. The single patient classifiers could complement TNM staging to optimise decision making in patients with resectable gastric cancer who are eligible for adjuvant chemotherapy after surgery. Further validation of these results in prospective studies is warranted. Ministry of ICT and Future Planning; Ministry of Trade, Industry, and Energy; and Ministry of Health and Welfare. Copyright © 2018 Elsevier Ltd. All rights reserved.

High speed turboprop aeroacoustic study (counterrotation). Volume 1: Model development

NASA Technical Reports Server (NTRS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-01-01

The isolated counterrotating high speed turboprop noise prediction program was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in NASA-Lewis' 8x6 and 9x15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counterotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attach was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combines into a single prediction program, results of which were compared with data taken during the flight test of the B727/UDF engine demonstrator aircraft. Satisfactory comparisons between prediction and measured data for the demonstrator airplane, together with the identification of a nontraditional radiation mechanism for propellers at angle of attack are achieved.

An investigation of gear mesh failure prediction techniques. M.S. Thesis - Cleveland State Univ.

NASA Technical Reports Server (NTRS)

Zakrajsek, James J.

1989-01-01

A study was performed in which several gear failure prediction methods were investigated and applied to experimental data from a gear fatigue test apparatus. The primary objective was to provide a baseline understanding of the prediction methods and to evaluate their diagnostic capabilities. The methods investigated use the signal average in both the time and frequency domain to detect gear failure. Data from eleven gear fatigue tests were recorded at periodic time intervals as the gears were run from initiation to failure. Four major failure modes, consisting of heavy wear, tooth breakage, single pits, and distributed pitting were observed among the failed gears. Results show that the prediction methods were able to detect only those gear failures which involved heavy wear or distributed pitting. None of the methods could predict fatigue cracks, which resulted in tooth breakage, or single pits. It is suspected that the fatigue cracks were not detected because of limitations in data acquisition rather than in methodology. Additionally, the frequency response between the gear shaft and the transducer was found to significantly affect the vibration signal. The specific frequencies affected were filtered out of the signal average prior to application of the methods.

High speed turboprop aeroacoustic study (counterrotation). Volume 1: Model development

NASA Astrophysics Data System (ADS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-07-01

The isolated counterrotating high speed turboprop noise prediction program was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in NASA-Lewis' 8x6 and 9x15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counterotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attach was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combines into a single prediction program, results of which were compared with data taken during the flight test of the B727/UDF engine demonstrator aircraft. Satisfactory comparisons between prediction and measured data for the demonstrator airplane, together with the identification of a nontraditional radiation mechanism for propellers at angle of attack are achieved.

The Effect of Electronic Structure on the Phases Present in High Entropy Alloys

PubMed Central

Leong, Zhaoyuan; Wróbel, Jan S.; Dudarev, Sergei L.; Goodall, Russell; Todd, Iain; Nguyen-Manh, Duc

2017-01-01

Multicomponent systems, termed High Entropy Alloys (HEAs), with predominantly single solid solution phases are a current area of focus in alloy development. Although different empirical rules have been introduced to understand phase formation and determine what the dominant phases may be in these systems, experimental investigation has revealed that in many cases their structure is not a single solid solution phase, and that the rules may not accurately distinguish the stability of the phase boundaries. Here, a combined modelling and experimental approach that looks into the electronic structure is proposed to improve accuracy of the predictions of the majority phase. To do this, the Rigid Band model is generalised for magnetic systems in prediction of the majority phase most likely to be found. Good agreement is found when the predictions are confronted with data from experiments, including a new magnetic HEA system (CoFeNiV). This also includes predicting the structural transition with varying levels of constituent elements, as a function of the valence electron concentration, n, obtained from the integrated spin-polarised density of states. This method is suitable as a new predictive technique to identify compositions for further screening, in particular for magnetic HEAs. PMID:28059106

The Effect of Electronic Structure on the Phases Present in High Entropy Alloys.

PubMed

Leong, Zhaoyuan; Wróbel, Jan S; Dudarev, Sergei L; Goodall, Russell; Todd, Iain; Nguyen-Manh, Duc

2017-01-06

Multicomponent systems, termed High Entropy Alloys (HEAs), with predominantly single solid solution phases are a current area of focus in alloy development. Although different empirical rules have been introduced to understand phase formation and determine what the dominant phases may be in these systems, experimental investigation has revealed that in many cases their structure is not a single solid solution phase, and that the rules may not accurately distinguish the stability of the phase boundaries. Here, a combined modelling and experimental approach that looks into the electronic structure is proposed to improve accuracy of the predictions of the majority phase. To do this, the Rigid Band model is generalised for magnetic systems in prediction of the majority phase most likely to be found. Good agreement is found when the predictions are confronted with data from experiments, including a new magnetic HEA system (CoFeNiV). This also includes predicting the structural transition with varying levels of constituent elements, as a function of the valence electron concentration, n, obtained from the integrated spin-polarised density of states. This method is suitable as a new predictive technique to identify compositions for further screening, in particular for magnetic HEAs.

[Prediction of the molecular response to pertubations from single cell measurements].

PubMed

Remacle, Françoise; Levine, Raphael D

2014-12-01

The response of protein signalization networks to perturbations is analysed from single cell measurements. This experimental approach allows characterizing the fluctuations in protein expression levels from cell to cell. The analysis is based on an information theoretic approach grounded in thermodynamics leading to a quantitative version of Le Chatelier principle which allows to predict the molecular response. Two systems are investigated: human macrophages subjected to lipopolysaccharide challenge, analogous to the immune response against Gram-negative bacteria and the response of the proteins involved in the mTOR signalizing network of GBM cancer cells to changes in partial oxygen pressure. © 2014 médecine/sciences – Inserm.

Application of higher harmonic blade feathering for helicopter vibration reduction

NASA Technical Reports Server (NTRS)

Powers, R. W.

1978-01-01

Higher harmonic blade feathering for helicopter vibration reduction is considered. Recent wind tunnel tests confirmed the effectiveness of higher harmonic control in reducing articulated rotor vibratory hub loads. Several predictive analyses developed in support of the NASA program were shown to be capable of calculating single harmonic control inputs required to minimize a single 4P hub response. In addition, a multiple-input, multiple-output harmonic control predictive analysis was developed. All techniques developed thus far obtain a solution by extracting empirical transfer functions from sampled data. Algorithm data sampling and processing requirements are minimal to encourage adaptive control system application of such techniques in a flight environment.

Distortion management in slow-light pulse delay.

PubMed

Stenner, Michael D; Neifeld, Mark A; Zhu, Zhaoming; Dawes, Andrew M C; Gauthier, Daniel J

2005-12-12

We describe a methodology to maximize slow-light pulse delay subject to a constraint on the allowable pulse distortion. We show that optimizing over a larger number of physical variables can increase the distortion-constrained delay. We demonstrate these concepts by comparing the optimum slow-light pulse delay achievable using a single Lorentzian gain line with that achievable using a pair of closely-spaced gain lines. We predict that distortion management using a gain doublet can provide approximately a factor of 2 increase in slow-light pulse delay as compared with the optimum single-line delay. Experimental results employing Brillouin gain in optical fiber confirm our theoretical predictions.

Nontangent, Developed Contour Bulkheads for a Single-Stage Launch Vehicle

NASA Technical Reports Server (NTRS)

Wu, K. Chauncey; Lepsch, Roger A., Jr.

2000-01-01

Dry weights for single-stage launch vehicles that incorporate nontangent, developed contour bulkheads are estimated and compared to a baseline vehicle with 1.414 aspect ratio ellipsoidal bulkheads. Weights, volumes, and heights of optimized bulkhead designs are computed using a preliminary design bulkhead analysis code. The dry weights of vehicles that incorporate the optimized bulkheads are predicted using a vehicle weights and sizing code. Two optimization approaches are employed. A structural-level method, where the vehicle's three major bulkhead regions are optimized separately and then incorporated into a model for computation of the vehicle dry weight, predicts a reduction of4365 lb (2.2 %) from the 200,679-lb baseline vehicle dry weight. In the second, vehicle-level, approach, the vehicle dry weight is the objective function for the optimization. For the vehicle-level analysis, modified bulkhead designs are analyzed and incorporated into the weights model for computation of a dry weight. The optimizer simultaneously manipulates design variables for all three bulkheads to reduce the dry weight. The vehicle-level analysis predicts a dry weight reduction of 5129 lb, a 2.6% reduction from the baseline weight. Based on these results, nontangent, developed contour bulkheads may provide substantial weight savings for single stage vehicles.

Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

STRUM: structure-based prediction of protein stability changes upon single-point mutation.

PubMed

Quan, Lijun; Lv, Qiang; Zhang, Yang

2016-10-01

Mutations in human genome are mainly through single nucleotide polymorphism, some of which can affect stability and function of proteins, causing human diseases. Several methods have been proposed to predict the effect of mutations on protein stability; but most require features from experimental structure. Given the fast progress in protein structure prediction, this work explores the possibility to improve the mutation-induced stability change prediction using low-resolution structure modeling. We developed a new method (STRUM) for predicting stability change caused by single-point mutations. Starting from wild-type sequences, 3D models are constructed by the iterative threading assembly refinement (I-TASSER) simulations, where physics- and knowledge-based energy functions are derived on the I-TASSER models and used to train STRUM models through gradient boosting regression. STRUM was assessed by 5-fold cross validation on 3421 experimentally determined mutations from 150 proteins. The Pearson correlation coefficient (PCC) between predicted and measured changes of Gibbs free-energy gap, ΔΔG, upon mutation reaches 0.79 with a root-mean-square error 1.2 kcal/mol in the mutation-based cross-validations. The PCC reduces if separating training and test mutations from non-homologous proteins, which reflects inherent correlations in the current mutation sample. Nevertheless, the results significantly outperform other state-of-the-art methods, including those built on experimental protein structures. Detailed analyses show that the most sensitive features in STRUM are the physics-based energy terms on I-TASSER models and the conservation scores from multiple-threading template alignments. However, the ΔΔG prediction accuracy has only a marginal dependence on the accuracy of protein structure models as long as the global fold is correct. These data demonstrate the feasibility to use low-resolution structure modeling for high-accuracy stability change prediction upon point mutations. http://zhanglab.ccmb.med.umich.edu/STRUM/ CONTACT: qiang@suda.edu.cn and zhng@umich.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

STRUM: structure-based prediction of protein stability changes upon single-point mutation

PubMed Central

Quan, Lijun; Lv, Qiang; Zhang, Yang

2016-01-01

Motivation: Mutations in human genome are mainly through single nucleotide polymorphism, some of which can affect stability and function of proteins, causing human diseases. Several methods have been proposed to predict the effect of mutations on protein stability; but most require features from experimental structure. Given the fast progress in protein structure prediction, this work explores the possibility to improve the mutation-induced stability change prediction using low-resolution structure modeling. Results: We developed a new method (STRUM) for predicting stability change caused by single-point mutations. Starting from wild-type sequences, 3D models are constructed by the iterative threading assembly refinement (I-TASSER) simulations, where physics- and knowledge-based energy functions are derived on the I-TASSER models and used to train STRUM models through gradient boosting regression. STRUM was assessed by 5-fold cross validation on 3421 experimentally determined mutations from 150 proteins. The Pearson correlation coefficient (PCC) between predicted and measured changes of Gibbs free-energy gap, ΔΔG, upon mutation reaches 0.79 with a root-mean-square error 1.2 kcal/mol in the mutation-based cross-validations. The PCC reduces if separating training and test mutations from non-homologous proteins, which reflects inherent correlations in the current mutation sample. Nevertheless, the results significantly outperform other state-of-the-art methods, including those built on experimental protein structures. Detailed analyses show that the most sensitive features in STRUM are the physics-based energy terms on I-TASSER models and the conservation scores from multiple-threading template alignments. However, the ΔΔG prediction accuracy has only a marginal dependence on the accuracy of protein structure models as long as the global fold is correct. These data demonstrate the feasibility to use low-resolution structure modeling for high-accuracy stability change prediction upon point mutations. Availability and Implementation: http://zhanglab.ccmb.med.umich.edu/STRUM/ Contact: qiang@suda.edu.cn and zhng@umich.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27318206

Protein subcellular localization prediction using multiple kernel learning based support vector machine.

PubMed

Hasan, Md Al Mehedi; Ahmad, Shamim; Molla, Md Khademul Islam

2017-03-28

Predicting the subcellular locations of proteins can provide useful hints that reveal their functions, increase our understanding of the mechanisms of some diseases, and finally aid in the development of novel drugs. As the number of newly discovered proteins has been growing exponentially, which in turns, makes the subcellular localization prediction by purely laboratory tests prohibitively laborious and expensive. In this context, to tackle the challenges, computational methods are being developed as an alternative choice to aid biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging issue, particularly, when query proteins have multi-label characteristics, i.e., if they exist simultaneously in more than one subcellular location or if they move between two or more different subcellular locations. To date, to address this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM) has been employed to provide potential solutions to the protein subcellular localization prediction problem. However, the practicability of an SVM is affected by the challenges of selecting an appropriate kernel and selecting the parameters of the selected kernel. To address this difficulty, in this study, we aimed to develop an efficient multi-label protein subcellular localization prediction system, named as MKLoc, by introducing multiple kernel learning (MKL) based SVM. We evaluated MKLoc using a combined dataset containing 5447 single-localized proteins (originally published as part of the Höglund dataset) and 3056 multi-localized proteins (originally published as part of the DBMLoc set). Note that this dataset was used by Briesemeister et al. in their extensive comparison of multi-localization prediction systems. Finally, our experimental results indicate that MKLoc not only achieves higher accuracy than a single kernel based SVM system but also shows significantly better results than those obtained from other top systems (MDLoc, BNCs, YLoc+). Moreover, MKLoc requires less computation time to tune and train the system than that required for BNCs and single kernel based SVM.

Polarization Transfer in Wide-Angle Compton Scattering and Single-Pion Photoproduction from the Proton

NASA Astrophysics Data System (ADS)

Fanelli, C.; Cisbani, E.; Hamilton, D. J.; Salmé, G.; Wojtsekhowski, B.; Ahmidouch, A.; Annand, J. R. M.; Baghdasaryan, H.; Beaufait, J.; Bosted, P.; Brash, E. J.; Butuceanu, C.; Carter, P.; Christy, E.; Chudakov, E.; Danagoulian, S.; Day, D.; Degtyarenko, P.; Ent, R.; Fenker, H.; Fowler, M.; Frlez, E.; Gaskell, D.; Gilman, R.; Horn, T.; Huber, G. M.; de Jager, C. W.; Jensen, E.; Jones, M. K.; Kelleher, A.; Keppel, C.; Khandaker, M.; Kohl, M.; Kumbartzki, G.; Lassiter, S.; Li, Y.; Lindgren, R.; Lovelace, H.; Luo, W.; Mack, D.; Mamyan, V.; Margaziotis, D. J.; Markowitz, P.; Maxwell, J.; Mbianda, G.; Meekins, D.; Meziane, M.; Miller, J.; Mkrtchyan, A.; Mkrtchyan, H.; Mulholland, J.; Nelyubin, V.; Pentchev, L.; Perdrisat, C. F.; Piasetzky, E.; Prok, Y.; Puckett, A. J. R.; Punjabi, V.; Shabestari, M.; Shahinyan, A.; Slifer, K.; Smith, G.; Solvignon, P.; Subedi, R.; Wesselmann, F. R.; Wood, S.; Ye, Z.; Zheng, X.

2015-10-01

Wide-angle exclusive Compton scattering and single-pion photoproduction from the proton have been investigated via measurement of the polarization transfer from a circularly polarized photon beam to the recoil proton. The wide-angle Compton scattering polarization transfer was analyzed at an incident photon energy of 3.7 GeV at a proton scattering angle of θcmp=70 ° . The longitudinal transfer KLL, measured to be 0.645 ±0.059 ±0.048 , where the first error is statistical and the second is systematic, has the same sign as predicted for the reaction mechanism in which the photon interacts with a single quark carrying the spin of the proton. However, the observed value is ˜3 times larger than predicted by the generalized-parton-distribution-based calculations, which indicates a significant unknown contribution to the scattering amplitude.

Creating Geologically Based Radon Potential Maps for Kentucky

NASA Astrophysics Data System (ADS)

Overfield, B.; Hahn, E.; Wiggins, A.; Andrews, W. M., Jr.

2017-12-01

Radon potential in the United States, Kentucky in particular, has historically been communicated using a single hazard level for each county; however, physical phenomena are not controlled by administrative boundaries, so single-value county maps do not reflect the significant variations in radon potential in each county. A more accurate approach uses bedrock geology as a predictive tool. A team of nurses, health educators, statisticians, and geologists partnered to create 120 county maps showing spatial variations in radon potential by intersecting residential radon test kit results (N = 60,000) with a statewide 1:24,000-scale bedrock geology coverage to determine statistically valid radon-potential estimates for each geologic unit. Maps using geology as a predictive tool for radon potential are inherently more detailed than single-value county maps. This mapping project revealed that areas in central and south-central Kentucky with the highest radon potential are underlain by shales and karstic limestones.

Mfold web server for nucleic acid folding and hybridization prediction.

PubMed

Zuker, Michael

2003-07-01

The abbreviated name, 'mfold web server', describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces), the server circumvents the problem of portability of this software. Detailed output, in the form of structure plots with or without reliability information, single strand frequency plots and 'energy dot plots', are available for the folding of single sequences. A variety of 'bulk' servers give less information, but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold. This URL will be referred to as 'MFOLDROOT'.

Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies.

PubMed

Soler, Miguel A; de Marco, Ario; Fortuna, Sara

2016-10-10

Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular recognition. Their small size represents a precious advantage for rational mutagenesis based on modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate mutations by developing a simulation protocol based on all-atom molecular dynamics and whole-molecule docking. The method was tested on two sets of nanobodies characterized experimentally for their biophysical features. One set contained point mutations introduced to humanize a wild type sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae and human hallmarks. The method resulted in accurate scoring approaches to predict experimental yields and enabled to identify the structural modifications induced by mutations. This work is a promising tool for the in silico development of single-domain antibodies and opens the opportunity to customize single functional domains of larger macromolecules.

Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies

NASA Astrophysics Data System (ADS)

Soler, Miguel A.; De Marco, Ario; Fortuna, Sara

2016-10-01

Nanobodies (VHHs) have proved to be valuable substitutes of conventional antibodies for molecular recognition. Their small size represents a precious advantage for rational mutagenesis based on modelling. Here we address the problem of predicting how Camelidae nanobody sequences can tolerate mutations by developing a simulation protocol based on all-atom molecular dynamics and whole-molecule docking. The method was tested on two sets of nanobodies characterized experimentally for their biophysical features. One set contained point mutations introduced to humanize a wild type sequence, in the second the CDRs were swapped between single-domain frameworks with Camelidae and human hallmarks. The method resulted in accurate scoring approaches to predict experimental yields and enabled to identify the structural modifications induced by mutations. This work is a promising tool for the in silico development of single-domain antibodies and opens the opportunity to customize single functional domains of larger macromolecules.

Estimating Single-Event Logic Cross Sections in Advanced Technologies

NASA Astrophysics Data System (ADS)

Harrington, R. C.; Kauppila, J. S.; Warren, K. M.; Chen, Y. P.; Maharrey, J. A.; Haeffner, T. D.; Loveless, T. D.; Bhuva, B. L.; Bounasser, M.; Lilja, K.; Massengill, L. W.

2017-08-01

Reliable estimation of logic single-event upset (SEU) cross section is becoming increasingly important for predicting the overall soft error rate. As technology scales and single-event transient (SET) pulse widths shrink to widths on the order of the setup-and-hold time of flip-flops, the probability of latching an SET as an SEU must be reevaluated. In this paper, previous assumptions about the relationship of SET pulsewidth to the probability of latching an SET are reconsidered and a model for transient latching probability has been developed for advanced technologies. A method using the improved transient latching probability and SET data is used to predict logic SEU cross section. The presented model has been used to estimate combinational logic SEU cross sections in 32-nm partially depleted silicon-on-insulator (SOI) technology given experimental heavy-ion SET data. Experimental SEU data show good agreement with the model presented in this paper.

Polarization Transfer in Wide-Angle Compton Scattering and Single-Pion Photoproduction from the Proton

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

Fanelli, C.; Cisbani, E.; Hamilton, D. J.

Wide-angle exclusive Compton scattering and single-pion photoproduction from the proton have been investigated via measurement of the polarization transfer from a circularly polarized photon beam to the recoil proton. The wide-angle Compton scattering polarization transfer was analyzed at an incident photon energy of 3.7 GeV at a proton scattering angle of theta(p)(cm) cm = 70 degrees. The longitudinal transfer K-LL, measured to be 0.645 +/- 0.059 +/- 0.048, where the first error is statistical and the second is systematic, has the same sign as predicted for the reaction mechanism in which the photon interacts with a single quark carrying themore » spin of the proton. However, the observed value is similar to 3 times larger than predicted by the generalized-parton-distribution-based calculations, which indicates a significant unknown contribution to the scattering amplitude.« less

A study of sound generation in subsonic rotors, volume 1

NASA Technical Reports Server (NTRS)

Chalupnik, J. D.; Clark, L. T.

1975-01-01

A model for the prediction of wake related sound generation by a single airfoil is presented. It is assumed that the net force fluctuation on an airfoil may be expressed in terms of the net momentum fluctuation in the near wake of the airfoil. The forcing function for sound generation depends on the spectra of the two point velocity correlations in the turbulent region near the airfoil trailing edge. The spectra of the two point velocity correlations were measured for the longitudinal and transverse components of turbulence in the wake of a 91.4 cm chord airfoil. A scaling procedure was developed using the turbulent boundary layer thickness. The model was then used to predict the radiated sound from a 5.1 cm chord airfoil. Agreement between the predicted and measured sound radiation spectra was good. The single airfoil results were extended to a rotor geometry, and various aerodynamic parameters were studied.

Noise and diffusion of a vibrated self-propelled granular particle

NASA Astrophysics Data System (ADS)

Walsh, Lee; Wagner, Caleb G.; Schlossberg, Sarah; Olson, Christopher; Baskaran, Aparna; Menon, Narayanan

Granular materials are an important physical realization of active matter. In vibration-fluidized granular matter, both diffusion and self-propulsion derive from the same collisional forcing, unlike many other active systems where there is a clean separation between the origin of single-particle mobility and the coupling to noise. Here we present experimental studies of single-particle motion in a vibrated granular monolayer, along with theoretical analysis that compares grain motion at short and long time scales to the assumptions and predictions, respectively, of the active Brownian particle (ABP) model. The results demonstrate that despite the unique relation between noise and propulsion, granular media do show the generic features predicted by the ABP model and indicate that this is a valid framework to predict collective phenomena. Additionally, our scheme of analysis for validating the inputs and outputs of the model can be applied to other granular and non-granular systems.

Thermal vibration of rectangular single-layered black phosphorus predicted by orthotropic plate model

NASA Astrophysics Data System (ADS)

Zhang, Yiqing; Wang, Lifeng; Jiang, Jingnong

2018-03-01

Vibrational behavior is very important for nanostructure-based resonators. In this work, an orthotropic plate model together with a molecular dynamics (MD) simulation is used to investigate the thermal vibration of rectangular single-layered black phosphorus (SLBP). Two bending stiffness, two Poisson's ratios, and one shear modulus of SLBP are calculated using the MD simulation. The natural frequency of the SLBP predicted by the orthotropic plate model agrees with the one obtained from the MD simulation very well. The root of mean squared (RMS) amplitude of the SLBP is obtained by MD simulation and the orthotropic plate model considering the law of energy equipartition. The RMS amplitude of the thermal vibration of the SLBP is predicted well by the orthotropic plate model compared to the MD results. Furthermore, the thermal vibration of the SLBP with an initial stress is also well-described by the orthotropic plate model.

A method for predicting the noise levels of coannular jets with inverted velocity profiles

NASA Technical Reports Server (NTRS)

Russell, J. W.

1979-01-01

A coannular jet was equated with a single stream equivalent jet with the same mass flow, energy, and thrust. The acoustic characteristics of the coannular jet were then related to the acoustic characteristics of the single jet. Forward flight effects were included by incorporating a forward exponent, a Doppler amplification factor, and a Strouhal frequency shift. Model test data, including 48 static cases and 22 wind tunnel cases, were used to evaluate the prediction method. For the static cases and the low forward velocity wind tunnel cases, the spectral mean square pressure correlation coefficients were generally greater than 90 percent, and the spectral sound pressure level standard deviation were generally less than 3 decibels. The correlation coefficient and the standard deviation were not affected by changes in equivalent jet velocity. Limitations of the prediction method are also presented.

Internally generated preactivation of single neurons in human medial frontal cortex predicts volition

PubMed Central

Fried, Itzhak; Mukamel, Roy; Kreiman, Gabriel

2011-01-01

Understanding how self-initiated behavior is encoded by neuronal circuits in the human brain remains elusive. We recorded the activity of 1019 neurons while twelve subjects performed self-initiated finger movement. We report progressive neuronal recruitment over ~1500 ms before subjects report making the decision to move. We observed progressive increase or decrease in neuronal firing rate, particularly in the supplementary motor area (SMA), as the reported time of decision was approached. A population of 256 SMA neurons is sufficient to predict in single trials the impending decision to move with accuracy greater than 80% already 700 ms prior to subjects’ awareness. Furthermore, we predict, with a precision of a few hundred ms, the actual time point of this voluntary decision to move. We implement a computational model whereby volition emerges once a change in internally generated firing rate of neuronal assemblies crosses a threshold. PMID:21315264

A dual-porosity reactive-transport model of off-axis hydrothermal systems

NASA Astrophysics Data System (ADS)

Farahat, N. X.; Abbot, D. S.; Archer, D. E.

2017-12-01

We built a dual-porosity reactive-transport 2D numerical model of off-axis pillow basalt alteration. An "outer chamber" full of porous glassy material supports significant seawater flushing, and an "inner chamber", which represents the more crystalline interior of a pillow, supports diffusive alteration. Hydrothermal fluids in the two chambers interact, and the two chambers are coupled to 2D flows. In a few million years of low-temperature alteration, the dual-porosity model predicts progressive stages of alteration that have been observed in drilled crust. A single-porosity model, with all else being equal, does not predict alteration stages as well. The dual-chamber model also does a better job than the single-chamber model at predicting the types of minerals expected in off-axis environments. We validate the model's ability to reproduce observations by configuring it to represent a thoroughly-studied transect of the Juan de Fuca Ridge eastern flank.

Boron arsenide phonon dispersion from inelastic x-ray scattering: Potential for ultrahigh thermal conductivity

NASA Astrophysics Data System (ADS)

Ma, Hao; Li, Chen; Tang, Shixiong; Yan, Jiaqiang; Alatas, Ahmet; Lindsay, Lucas; Sales, Brian C.; Tian, Zhiting

2016-12-01

Cubic boron arsenide (BAs) was predicted to have an exceptionally high thermal conductivity (k ) ˜2000 W m-1K-1 at room temperature, comparable to that of diamond, based on first-principles calculations. Subsequent experimental measurements, however, only obtained a k of ˜200 W m-1K-1 . To gain insight into this discrepancy, we measured phonon dispersion of single-crystal BAs along high symmetry directions using inelastic x-ray scattering and compared these with first-principles calculations. Based on the measured phonon dispersion, we have validated the theoretical prediction of a large frequency gap between acoustic and optical modes and bunching of acoustic branches, which were considered the main reasons for the predicted ultrahigh k . This supports its potential to be a super thermal conductor if very-high-quality single-crystal samples can be synthesized.

Optimal weighted combinatorial forecasting model of QT dispersion of ECGs in Chinese adults.

PubMed

Wen, Zhang; Miao, Ge; Xinlei, Liu; Minyi, Cen

2016-07-01

This study aims to provide a scientific basis for unifying the reference value standard of QT dispersion of ECGs in Chinese adults. Three predictive models including regression model, principal component model, and artificial neural network model are combined to establish the optimal weighted combination model. The optimal weighted combination model and single model are verified and compared. Optimal weighted combinatorial model can reduce predicting risk of single model and improve the predicting precision. The reference value of geographical distribution of Chinese adults' QT dispersion was precisely made by using kriging methods. When geographical factors of a particular area are obtained, the reference value of QT dispersion of Chinese adults in this area can be estimated by using optimal weighted combinatorial model and reference value of the QT dispersion of Chinese adults anywhere in China can be obtained by using geographical distribution figure as well.

Managing distribution changes in time series prediction

NASA Astrophysics Data System (ADS)

Matias, J. M.; Gonzalez-Manteiga, W.; Taboada, J.; Ordonez, C.

2006-07-01

When a problem is modeled statistically, a single distribution model is usually postulated that is assumed to be valid for the entire space. Nonetheless, this practice may be somewhat unrealistic in certain application areas, in which the conditions of the process that generates the data may change; as far as we are aware, however, no techniques have been developed to tackle this problem.This article proposes a technique for modeling and predicting this change in time series with a view to improving estimates and predictions. The technique is applied, among other models, to the hypernormal distribution recently proposed. When tested on real data from a range of stock market indices the technique produces better results that when a single distribution model is assumed to be valid for the entire period of time studied.Moreover, when a global model is postulated, it is highly recommended to select the hypernormal distribution parameter in the same likelihood maximization process.

Single spin asymmetries in charged kaon production from semi-inclusive deep inelastic scattering on a transversely polarized He 3 target

DOE PAGES

Zhao, Y. X.; Wang, Y.; Allada, K.; ...

2014-11-03

We report the first measurement of target single spin asymmetries of charged kaons produced in semi-inclusive deep inelastic scattering of electrons off a transversely polarized 3He target. Both the Collins and Sivers moments, which are related to the nucleon transversity and Sivers distributions, respectively, are extracted over the kinematic range of 0.1 < x bj<0.4 for K + and K – production. While the Collins and Sivers moments for K + are consistent with zero within the experimental uncertainties, both moments for K – favor negative values. The Sivers moments are compared to the theoretical prediction from a phenomenological fitmore » to the world data. While the K + Sivers moments are consistent with the prediction, the K – results differ from the prediction at the 2-sigma level.« less

Predictive optimized adaptive PSS in a single machine infinite bus.

PubMed

Milla, Freddy; Duarte-Mermoud, Manuel A

2016-07-01

Power System Stabilizer (PSS) devices are responsible for providing a damping torque component to generators for reducing fluctuations in the system caused by small perturbations. A Predictive Optimized Adaptive PSS (POA-PSS) to improve the oscillations in a Single Machine Infinite Bus (SMIB) power system is discussed in this paper. POA-PSS provides the optimal design parameters for the classic PSS using an optimization predictive algorithm, which adapts to changes in the inputs of the system. This approach is part of small signal stability analysis, which uses equations in an incremental form around an operating point. Simulation studies on the SMIB power system illustrate that the proposed POA-PSS approach has better performance than the classical PSS. In addition, the effort in the control action of the POA-PSS is much less than that of other approaches considered for comparison. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Airborne sound transmission loss characteristics of wood-frame construction

NASA Astrophysics Data System (ADS)

Rudder, F. F., Jr.

1985-03-01

This report summarizes the available data on the airborne sound transmission loss properties of wood-frame construction and evaluates the methods for predicting the airborne sound transmission loss. The first part of the report comprises a summary of sound transmission loss data for wood-frame interior walls and floor-ceiling construction. Data bases describing the sound transmission loss characteristics of other building components, such as windows and doors, are discussed. The second part of the report presents the prediction of the sound transmission loss of wood-frame construction. Appropriate calculation methods are described both for single-panel and for double-panel construction with sound absorption material in the cavity. With available methods, single-panel construction and double-panel construction with the panels connected by studs may be adequately characterized. Technical appendices are included that summarize laboratory measurements, compare measurement with theory, describe details of the prediction methods, and present sound transmission loss data for common building materials.

Boron arsenide phonon dispersion from inelastic x-ray scattering: Potential for ultrahigh thermal conductivity

DOE PAGES

Ma, Hao; Li, Chen; Tang, Shixiong; ...

2016-12-14

Cubic boron arsenide (BAs) was predicted to have an exceptionally high thermal conductivity (k) ~2000 Wm -1K -1 at room temperature, comparable to that of diamond, based on first-principles calculations. Subsequent experimental measurements, however, only obtained a k of ~200 Wm-1K-1. To gain insight into this discrepancy, we measured phonon dispersion of single crystal BAs along high symmetry directions using inelastic x-ray scattering (IXS) and compared these with first-principles calculations. Based on the measured phonon dispersion, we have validated the theoretical prediction of a large frequency gap between acoustic and optical modes and bunching of acoustic branches, which were consideredmore » the main reasons for the predicted ultrahigh k. This supports its potential to be a super thermal conductor if very high-quality single crystal samples can be synthesized.« less

An integrated prediction and optimization model of biogas production system at a wastewater treatment facility.

PubMed

Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih

2015-11-01

This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility. Copyright © 2015 Elsevier Ltd. All rights reserved.

Resolving Mixed Algal Species in Hyperspectral Images

PubMed Central

Mehrubeoglu, Mehrube; Teng, Ming Y.; Zimba, Paul V.

2014-01-01

We investigated a lab-based hyperspectral imaging system's response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system's performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert's law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements. PMID:24451451

Using Speculative Execution to Automatically Hide I/O Latency

DTIC Science & Technology

2001-12-07

sion of the Lempel - Ziv algorithm and the Finite multi-order context models (FMOC) that originated from prediction-by-partial-match data compressors...allowed the cancellation of a single hint at a time.) 2.2.4 Predicting future data needs In order to take advantage of any of the algorithms described...modelling techniques generally used for data compression to perform probabilistic prediction of an application’s next page fault (or, in an object-oriented

Maydays and Murphies: A Study of the Effect of Organizational Design, Task, and Stress on Organizational Performance

DTIC Science & Technology

1992-07-29

provide a series of hypotheses which we can test both with human experiments and by using real organizational data. Since human experiments are costly to...able to predict organizational performance (e.g., Mackenzie, 1978; Krackhardt, 1989). Rarely have they been tested and contrasted. The formal...also tested and contrasted the predictability of existing measures of organizational design. They found that no single measure predicted performance

Genomic Prediction Accounting for Genotype by Environment Interaction Offers an Effective Framework for Breeding Simultaneously for Adaptation to an Abiotic Stress and Performance Under Normal Cropping Conditions in Rice.

PubMed

Ben Hassen, Manel; Bartholomé, Jérôme; Valè, Giampiero; Cao, Tuong-Vi; Ahmadi, Nourollah

2018-05-09

Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alternate wetting and drying and continuous flooding management systems. The predictive ability of genomic prediction for response variables (index of relative performance and the slope of the joint regression) and for multi-environment genomic prediction models were compared. For the three traits considered (days to flowering, panicle weight and nitrogen-balance index), significant genotype by environment interactions were observed in both populations. In cross validation, predictive ability for the index was on average lower (0.31) than that of the slope of the joint regression (0.64) whatever the trait considered. Similar results were found for progeny validation. Both cross-validation and progeny validation experiments showed that the performance of multi-environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in predictive ability ranging from -6% to 4% depending on the trait and on the statistical model concerned. The predictive ability of multi-environment models predicting unobserved phenotypes of entrees evaluated under both water management systems outperformed single environment models by an average of 30%. Practical implications for breeding rice for adaptation to alternate wetting and drying system are discussed. Copyright © 2018, G3: Genes, Genomes, Genetics.

Spiked GBS: A unified, open platform for single marker genotyping and whole-genome profiling

USDA-ARS?s Scientific Manuscript database

In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of t...

Stream network and stream segment temperature models software

USGS Publications Warehouse

Bartholow, John

2010-01-01

This set of programs simulates steady-state stream temperatures throughout a dendritic stream network handling multiple time periods per year. The software requires a math co-processor and 384K RAM. Also included is a program (SSTEMP) designed to predict the steady state stream temperature within a single stream segment for a single time period.

Predicting the Health of a Natural Water System

ERIC Educational Resources Information Center

Graves, Gregory H.

2010-01-01

This project was developed as an interdisciplinary application of the optimization of a single-variable function. It was used in a freshman-level single-variable calculus course. After the first month of the course, students had been exposed to the concepts of the derivative as a rate of change, average and instantaneous velocities, derivatives of…

Predicting Problem Behaviors with Multiple Expectancies: Expanding Expectancy-Value Theory

ERIC Educational Resources Information Center

Borders, Ashley; Earleywine, Mitchell; Huey, Stanley J.

2004-01-01

Expectancy-value theory emphasizes the importance of outcome expectancies for behavioral decisions, but most tests of the theory focus on a single behavior and a single expectancy. However, the matching law suggests that individuals consider expected outcomes for both the target behavior and alternative behaviors when making decisions. In this…

Single Event Effects (SEE) for Power Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs)

NASA Technical Reports Server (NTRS)

Lauenstein, Jean-Marie

2011-01-01

Single-event gate rupture (SEGR) continues to be a key failure mode in power MOSFETs. (1) SEGR is complex, making rate prediction difficult SEGR mechanism has two main components: (1) Oxide damage-- Reduces field required for rupture (2) Epilayer response -- Creates transient high field across the oxide.

Electron attachment to DNA single strands: gas phase and aqueous solution.

PubMed

Gu, Jiande; Xie, Yaoming; Schaefer, Henry F

2007-01-01

The 2'-deoxyguanosine-3',5'-diphosphate, 2'-deoxyadenosine-3',5'-diphosphate, 2'-deoxycytidine-3',5'-diphosphate and 2'-deoxythymidine-3',5'-diphosphate systems are the smallest units of a DNA single strand. Exploring these comprehensive subunits with reliable density functional methods enables one to approach reasonable predictions of the properties of DNA single strands. With these models, DNA single strands are found to have a strong tendency to capture low-energy electrons. The vertical attachment energies (VEAs) predicted for 3',5'-dTDP (0.17 eV) and 3',5'-dGDP (0.14 eV) indicate that both the thymine-rich and the guanine-rich DNA single strands have the ability to capture electrons. The adiabatic electron affinities (AEAs) of the nucleotides considered here range from 0.22 to 0.52 eV and follow the order 3',5'-dTDP > 3',5'-dCDP > 3',5'-dGDP > 3',5'-dADP. A substantial increase in the AEA is observed compared to that of the corresponding nucleic acid bases and the corresponding nucleosides. Furthermore, aqueous solution simulations dramatically increase the electron attracting properties of the DNA single strands. The present investigation illustrates that in the gas phase, the excess electron is situated both on the nucleobase and on the phosphate moiety for DNA single strands. However, the distribution of the extra negative charge is uneven. The attached electron favors the base moiety for the pyrimidine, while it prefers the 3'-phosphate subunit for the purine DNA single strands. In contrast, the attached electron is tightly bound to the base fragment for the cytidine, thymidine and adenosine nucleotides, while it almost exclusively resides in the vicinity of the 3'-phosphate group for the guanosine nucleotides due to the solvent effects. The comparatively low vertical detachment energies (VDEs) predicted for 3',5'-dADP(-) (0.26 eV) and 3',5'-dGDP(-) (0.32 eV) indicate that electron detachment might compete with reactions having high activation barriers such as glycosidic bond breakage. However, the radical anions of the pyrimidine nucleotides with high VDE are expected to be electronically stable. Thus the base-centered radical anions of the pyrimidine nucleotides might be the possible intermediates for DNA single-strand breakage.

Aeroacoustics of advanced propellers

NASA Technical Reports Server (NTRS)

Groeneweg, John F.

1990-01-01

The aeroacoustics of advanced, high speed propellers (propfans) are reviewed from the perspective of NASA research conducted in support of the Advanced Turboprop Program. Aerodynamic and acoustic components of prediction methods for near and far field noise are summarized for both single and counterrotation propellers in uninstalled and configurations. Experimental results from tests at both takeoff/approach and cruise conditions are reviewed with emphasis on: (1) single and counterrotation model tests in the NASA Lewis 9 by 15 (low speed) and 8 by 6 (high speed) wind tunnels, and (2) full scale flight tests of a 9 ft (2.74 m) diameter single rotation wing mounted tractor and a 11.7 ft (3.57 m) diameter counterrotation aft mounted pusher propeller. Comparisons of model data projected to flight with full scale flight data show good agreement validating the scale model wind tunnel approach. Likewise, comparisons of measured and predicted noise level show excellent agreement for both single and counterrotation propellers. Progress in describing angle of attack and installation effects is also summarized. Finally, the aeroacoustic issues associated with ducted propellers (very high bypass fans) are discussed.

Life prediction and constitutive models for engine hot section anisotropic materials program

NASA Technical Reports Server (NTRS)

Swanson, G. A.; Linask, I.; Nissley, D. M.; Norris, P. P.; Meyer, T. G.; Walker, K. P.

1986-01-01

This report presents the results of the first year of a program designed to develop life prediction and constitutive models for two coated single crystal alloys used in gas turbine airfoils. The two alloys are PWA 1480 and Alloy 185. The two oxidation resistant coatings are PWA 273, an aluminide coating, and PWA 286, an overlay NiCoCrAlY coating. To obtain constitutive and/or fatigue data, tests were conducted on coated and uncoated PWA 1480 specimens tensilely loaded in the 100 , 110 , 111 , and 123 directions. A literature survey of constitutive models was completed for both single crystal alloys and metallic coating materials; candidate models were selected. One constitutive model under consideration for single crystal alloys applies Walker's micromechanical viscoplastic formulation to all slip systems participating in the single crystal deformation. The constitutive models for the overlay coating correlate the viscoplastic data well. For the aluminide coating, a unique test method is under development. LCF and TMF tests are underway. The two coatings caused a significant drop in fatigue life, and each produced a much different failure mechanism.

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

PubMed

Kim, Hee-Ju; Abraham, Ivo

2017-01-01

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

Cloud prediction of protein structure and function with PredictProtein for Debian.

PubMed

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

PubMed Central

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

Anisotropic Laminar Piezocomposite Actuator Incorporating Machined PMN-PT Single Crystal Fibers

NASA Technical Reports Server (NTRS)

Wilkie, W. Keats; Inman, Daniel J.; Lloyd, Justin M.; High, James W.

2006-01-01

The design, fabrication, and testing of a flexible, laminar, anisotropic piezoelectric composite actuator utilizing machined PMN-32%PT single crystal fibers is presented. The device consists of a layer of rectangular single crystal piezoelectric fibers in an epoxy matrix, packaged between interdigitated electrode polyimide films. Quasistatic free-strain measurements of the single crystal device are compared with measurements from geometrically identical specimens incorporating polycrystalline PZT-5A and PZT-5H piezoceramic fibers. Free-strain actuation of the single crystal actuator at low bipolar electric fields (+/- 250 V/mm) is approximately 400% greater than that of the baseline PZT-5A piezoceramic device, and 200% greater than that of the PZT-5H device. Free-strain actuation under high unipolar electric fields (0-4kV/mm) is approximately 200% of the PZT-5A baseline device, and 150% of the PZT-5H alternate piezoceramic device. Performance increases at low field are qualitatively consistent with predicted increases based on scaling the low-field d33 piezoelectric constants of the respective piezoelectric materials. High-field increases are much less than scaled d33 estimates, but appear consistent with high-field freestrain measurements reported for similar bulk single-crystal and piezoceramic compositions. Measurements of single crystal actuator capacitance and coupling coefficient are also provided. These properties were poorly predicted using scaled bulk material dielectric and coupling coefficient data. Rules-of-mixtures calculations of the effective elastic properties of the single crystal device and estimated actuation work energy densities are also presented. Results indicate longitudinal stiffnesses significantly lower (50% less) than either piezoceramic device. This suggests that single-crystal piezocomposite actuators will be best suited to low induced-stress, high strain and deflection applications.

Anisotropic Piezocomposite Actuator Incorporating Machined PMN-PT Single Crystal Fibers

NASA Technical Reports Server (NTRS)

Wilkie, W. Keats; Inman, Daniel J.; Lloyd, Justin M.; High, James W.

2004-01-01

The design, fabrication, and testing of a flexible, planar, anisotropic piezoelectric composite actuator utilizing machined PMN-32%PT single crystal fibers is presented. The device consists of a layer of rectangular single crystal piezoelectric fibers in an epoxy matrix, packaged between interdigitated electrode polyimide films. Quasistatic free-strain measurements of the single crystal device are compared with measurements from geometrically identical specimens incorporating polycrystalline PZT-5A and PZT-5H piezoceramic fibers. Free-strain actuation of the single crystal actuator at low bipolar electric fields (+/- 250 V/mm) is approximately 400% greater than that of the baseline PZT-5A piezoceramic device, and 200% greater than that of the PZT-5H device. Free-strain actuation under high unipolar electric fields (0-4kV/mm) is approximately 200% of the PZT-5A baseline device, and 150% of the PZT-5H alternate piezoceramic device. Performance increases at low field are qualitatively consistent with predicted increases based on scaling the low-field d(sub 33) piezoelectric constants of the respective piezoelectric materials. High-field increases are much less than scaled d(sub 33) estimates, but appear consistent with high-field freestrain measurements reported for similar bulk single-crystal and piezoceramic compositions. Measurements of single crystal actuator capacitance and coupling coefficient are also provided. These properties were poorly predicted using scaled bulk material dielectric and coupling coefficient data. Rules-of-mixtures calculations of the effective elastic properties of the single crystal device and estimated actuation work energy densities are also presented. Results indicate longitudinal stiffnesses significantly lower (50% less) than either piezoceramic device. This suggests that single-crystal piezocomposite actuators will be best suited to low induced-stress, high strain and deflection applications.

Warped Linear Prediction of Physical Model Excitations with Applications in Audio Compression and Instrument Synthesis

NASA Astrophysics Data System (ADS)

Glass, Alexis; Fukudome, Kimitoshi

2004-12-01

A sound recording of a plucked string instrument is encoded and resynthesized using two stages of prediction. In the first stage of prediction, a simple physical model of a plucked string is estimated and the instrument excitation is obtained. The second stage of prediction compensates for the simplicity of the model in the first stage by encoding either the instrument excitation or the model error using warped linear prediction. These two methods of compensation are compared with each other, and to the case of single-stage warped linear prediction, adjustments are introduced, and their applications to instrument synthesis and MPEG4's audio compression within the structured audio format are discussed.

Collimator-free photon tomography

DOEpatents

Dilmanian, F.A.; Barbour, R.L.

1998-10-06

A method of uncollimated single photon emission computed tomography includes administering a radioisotope to a patient for producing gamma ray photons from a source inside the patient. Emissivity of the photons is measured externally of the patient with an uncollimated gamma camera at a plurality of measurement positions surrounding the patient for obtaining corresponding energy spectrums thereat. Photon emissivity at the plurality of measurement positions is predicted using an initial prediction of an image of the source. The predicted and measured photon emissivities are compared to obtain differences therebetween. Prediction and comparison is iterated by updating the image prediction until the differences are below a threshold for obtaining a final prediction of the source image. 6 figs.

Helicopter external noise prediction and correlation with flight test

NASA Technical Reports Server (NTRS)

Gupta, B. P.

1978-01-01

Mathematical analysis procedures for predicting the main and tail rotor rotational and broadband noise are presented. The aerodynamic and acoustical data from Operational Loads Survey (OLS) flight program are used for validating the analysis and noise prediction methodology. For the long method of rotational noise prediction, the spanwise, chordwise, and azimuthwise airloading is used. In the short method, the airloads are assumed to be concentrated at a single spanwise station and for higher harmonics an airloading harmonic exponent of 2.0 is assumed. For the same flight condition, the predictions from long and short methods of rotational noise prediction are compared with the flight test results. The short method correlates as well or better than the long method.

Conflict Probability Estimation for Free Flight

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Erzberger, Heinz

1996-01-01

The safety and efficiency of free flight will benefit from automated conflict prediction and resolution advisories. Conflict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however. An estimate is therefore needed of the probability that a conflict will occur, given a pair of predicted trajectories and their levels of uncertainty. A method is developed in this paper to estimate that conflict probability. The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and Monte Carlo validation are presented.

Is it useful to ask "Está deprimido?" ("Are you depressed?") to terminally-ill Portuguese patients? Results from outpatient research.

PubMed

Julião, Miguel; Nunes, Baltazar; Sobral, Maria Ana; Dias, Daniela; Inocêncio, Inês; Barbosa, António

2016-04-01

Depression is a serious psychological problem in the palliative care setting. Brief screening tools for depression are lacking and need to be brief and acceptable. This study aimed to identify the properties of the single Portuguese question "Está deprimido?" ("Are you depressed?") to screen for depression. Retrospective study from 100 patient's medical records identifying the answers on the single Portuguese question for depression "Está deprimido?" ("Are you depressed?") and the HADS depression sub-scale, using a score ≥11 on the latter as the gold standard for clinically significant depressive symptoms. Sensitivity, specificity, positive predictive and negative values were calculated. Response rate for the single Portuguese question for depression was 100%. Prevalence of depression symptoms (HADS-d ≥ 11) was 43%. To the question "Está deprimido?" 60 patients responded "yes." Sixteen patients who replied "no" to the single question had clinically significant depressive symptoms based on the HADS depression sub-scale. The single tool had 65.2% sensitivity, 49.2% specificity and 50.0% and 64.4% of positive predictive and negative values, respectively. In this first preliminary retrospective Portuguese study, the single question for depression has shown poor screening properties. Future research in larger and mixed patientś samples of Portuguese terminally ill is necessary to find more accurate and robust properties of this brief tool.

Life prediction and constitutive models for engine hot section anisotropic materials program

NASA Technical Reports Server (NTRS)

Nissley, D. M.; Meyer, T. G.

1992-01-01

This report presents the results from a 35 month period of a program designed to develop generic constitutive and life prediction approaches and models for nickel-based single crystal gas turbine airfoils. The program is composed of a base program and an optional program. The base program addresses the high temperature coated single crystal regime above the airfoil root platform. The optional program investigates the low temperature uncoated single crystal regime below the airfoil root platform including the notched conditions of the airfoil attachment. Both base and option programs involve experimental and analytical efforts. Results from uniaxial constitutive and fatigue life experiments of coated and uncoated PWA 1480 single crystal material form the basis for the analytical modeling effort. Four single crystal primary orientations were used in the experiments: (001), (011), (111), and (213). Specific secondary orientations were also selected for the notched experiments in the optional program. Constitutive models for an overlay coating and PWA 1480 single crystal material were developed based on isothermal hysteresis loop data and verified using thermomechanical (TMF) hysteresis loop data. A fatigue life approach and life models were selected for TMF crack initiation of coated PWA 1480. An initial life model used to correlate smooth and notched fatigue data obtained in the option program shows promise. Computer software incorporating the overlay coating and PWA 1480 constitutive models was developed.

Predictive Models for the Free Energy of Hydrogen Bonded Complexes with Single and Cooperative Hydrogen Bonds.

PubMed

Glavatskikh, Marta; Madzhidov, Timur; Solov'ev, Vitaly; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2016-12-01

In this work, we report QSPR modeling of the free energy ΔG of 1 : 1 hydrogen bond complexes of different H-bond acceptors and donors. The modeling was performed on a large and structurally diverse set of 3373 complexes featuring a single hydrogen bond, for which ΔG was measured at 298 K in CCl 4 . The models were prepared using Support Vector Machine and Multiple Linear Regression, with ISIDA fragment descriptors. The marked atoms strategy was applied at fragmentation stage, in order to capture the location of H-bond donor and acceptor centers. Different strategies of model validation have been suggested, including the targeted omission of individual H-bond acceptors and donors from the training set, in order to check whether the predictive ability of the model is not limited to the interpolation of H-bond strength between two already encountered partners. Successfully cross-validating individual models were combined into a consensus model, and challenged to predict external test sets of 629 and 12 complexes, in which donor and acceptor formed single and cooperative H-bonds, respectively. In all cases, SVM models outperform MLR. The SVM consensus model performs well both in 3-fold cross-validation (RMSE=1.50 kJ/mol), and on the external test sets containing complexes with single (RMSE=3.20 kJ/mol) and cooperative H-bonds (RMSE=1.63 kJ/mol). © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predictions of the spontaneous symmetry-breaking theory for visual code completeness and spatial scaling in single-cell learning rules.

PubMed

Webber, C J

2001-05-01

This article shows analytically that single-cell learning rules that give rise to oriented and localized receptive fields, when their synaptic weights are randomly and independently initialized according to a plausible assumption of zero prior information, will generate visual codes that are invariant under two-dimensional translations, rotations, and scale magnifications, provided that the statistics of their training images are sufficiently invariant under these transformations. Such codes span different image locations, orientations, and size scales with equal economy. Thus, single-cell rules could account for the spatial scaling property of the cortical simple-cell code. This prediction is tested computationally by training with natural scenes; it is demonstrated that a single-cell learning rule can give rise to simple-cell receptive fields spanning the full range of orientations, image locations, and spatial frequencies (except at the extreme high and low frequencies at which the scale invariance of the statistics of digitally sampled images must ultimately break down, because of the image boundary and the finite pixel resolution). Thus, no constraint on completeness, or any other coupling between cells, is necessary to induce the visual code to span wide ranges of locations, orientations, and size scales. This prediction is made using the theory of spontaneous symmetry breaking, which we have previously shown can also explain the data-driven self-organization of a wide variety of transformation invariances in neurons' responses, such as the translation invariance of complex cell response.

Integrating discrete stochastic models and single-cell experiments to infer predictive models of MAPK-induced transcription dynamics

NASA Astrophysics Data System (ADS)

Munsky, Brian

2015-03-01

MAPK signal-activated transcription plays central roles in myriad biological processes including stress adaptation responses and cell fate decisions. Recent single-cell and single-molecule experiments have advanced our ability to quantify the spatial, temporal, and stochastic fluctuations for such signals and their downstream effects on transcription regulation. This talk explores how integrating such experiments with discrete stochastic computational analyses can yield quantitative and predictive understanding of transcription regulation in both space and time. We use single-molecule mRNA fluorescence in situ hybridization (smFISH) experiments to reveal locations and numbers of multiple endogenous mRNA species in 100,000's of individual cells, at different times and under different genetic and environmental perturbations. We use finite state projection methods to precisely and efficiently compute the full joint probability distributions of these mRNA, which capture measured spatial, temporal and correlative fluctuations. By combining these experimental and computational tools with uncertainty quantification, we systematically compare models of varying complexity and select those which give optimally precise and accurate predictions in new situations. We use these tools to explore two MAPK-activated gene regulation pathways. In yeast adaptation to osmotic shock, we analyze Hog1 kinase activation of transcription for three different genes STL1 (osmotic stress), CTT1 (oxidative stress) and HSP12 (heat shock). In human osteosarcoma cells under serum induction, we analyze ERK activation of c-Fos transcription.

Predictive models of radiative neutrino masses

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

Julio, J., E-mail: julio@lipi.go.id

2016-06-21

We discuss two models of radiative neutrino mass generation. The first model features one–loop Zee model with Z{sub 4} symmetry. The second model is the two–loop neutrino mass model with singly- and doubly-charged scalars. These two models fit neutrino oscillation data well and predict some interesting rates for lepton flavor violation processes.

Competition Processes and Proactive Interference in Short-Term Memory

ERIC Educational Resources Information Center

Bennett, Raymond W.; Kurzeja, Paul L.

1976-01-01

In an experiment using single-word items, subjects are run under three different speed-accuracy trade-off conditions. A competition model would predict that when subjects are forced to respond quickly, there will be an increase in errors, and these will be from recent past items. The prediction was confirmed. (CHK)

Dropout Prediction in E-Learning Courses through the Combination of Machine Learning Techniques

ERIC Educational Resources Information Center

Lykourentzou, Ioanna; Giannoukos, Ioannis; Nikolopoulos, Vassilis; Mpardis, George; Loumos, Vassili

2009-01-01

In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to…

A MIXTURE OF SEVEN ANTIANDROGENIC COMPOUNDS ELICITS ADDITIVE EFFECTS ON THE MALE RAT REPRODUCTIVE TRACT THAT CORRESPOND TO MODELED PREDICTIONS

EPA Science Inventory

The main objectives of this study were to: (1) determine whether dissimilar antiandrogenic compounds display additive effects when present in combination and (2) to assess the ability of modelling approaches to accurately predict these mixture effects based on data from single ch...

Predicting fire spread in Arizona's oak chaparral

Treesearch

A. W. Lindenmuth; James R. Davis

1973-01-01

Five existing fire models, both experimental and theoretical, did not adequately predict rate-of-spread (ROS) when tested on single- and multiclump fires in oak chaparral in Arizona. A statistical model developed using essentially the same input variables but weighted differently accounted for 81 percent ofthe variation in ROS. A chemical coefficient that accounts for...

Subtypes of Developmental Dyslexia: Testing the Predictions of the Dual-Route and Connectionist Frameworks

ERIC Educational Resources Information Center

Peterson, Robin L.; Pennington, Bruce F.; Olson, Richard K.

2013-01-01

We investigated the phonological and surface subtypes of developmental dyslexia in light of competing predictions made by two computational models of single word reading, the Dual-Route Cascaded Model (DRC; Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) and Harm and Seidenberg's connectionist model (HS model; Harm & Seidenberg, 1999). The…

QUANTITATIVE STRUCTURE—PROPERTY RELATIONSHIPS FOR ENHANCING PREDICTIONS OF SYNTHETIC ORGANIC CHEMICAL REMOVAL FROM DRINKING WATER BY GRANULAR ACTIVATED CARBON

EPA Science Inventory

A number of mathematical models have been developed to predict activated carbon column performance using single-solute isotherm data as inputs. Many assumptions are built into these models to account for kinetics of adsorption and competition for adsorption sites. This work...

How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females

USDA-ARS?s Scientific Manuscript database

The promise of genomic selection is accurate prediction of animals' genetic potential from their genotypes. Simple DNA tests might replace low accuracy predictions for expensive or lowly heritable measures of puberty and fertility based on performance and pedigree. Knowing which DNA variants affec...

Updating and Not Shifting Predicts Learning Performance in Young and Middle-Aged Adults

ERIC Educational Resources Information Center

Gijselaers, Hieronymus J. M.; Meijs, Celeste; Neroni, Joyce; Kirschner, Paul A.; de Groot, Renate H. M.

2017-01-01

The goal of this study was to investigate whether single executive function (EF) tests were predictive for learning performance in mainly young and middle-aged adults. The tests measured shifting and updating. Processing speed was also measured. In an observational study, cognitive performance and learning performance were measured objectively in…

Bayesian whole-genome prediction and genome-wide association analysis with missing genotypes using variable selection

USDA-ARS?s Scientific Manuscript database

Single-step Genomic Best Linear Unbiased Predictor (ssGBLUP) has become increasingly popular for whole-genome prediction (WGP) modeling as it utilizes any available pedigree and phenotypes on both genotyped and non-genotyped individuals. The WGP accuracy of ssGBLUP has been demonstrated to be greate...

Single-Event Transgene Product Levels Predict Levels in Genetically Modified Breeding Stacks.

PubMed

Gampala, Satyalinga Srinivas; Fast, Brandon J; Richey, Kimberly A; Gao, Zhifang; Hill, Ryan; Wulfkuhle, Bryant; Shan, Guomin; Bradfisch, Greg A; Herman, Rod A

2017-09-13

The concentration of transgene products (proteins and double-stranded RNA) in genetically modified (GM) crop tissues is measured to support food, feed, and environmental risk assessments. Measurement of transgene product concentrations in breeding stacks of previously assessed and approved GM events is required by many regulatory authorities to evaluate unexpected transgene interactions that might affect expression. Research was conducted to determine how well concentrations of transgene products in single GM events predict levels in breeding stacks composed of these events. The concentrations of transgene products were compared between GM maize, soybean, and cotton breeding stacks (MON-87427 × MON-89034 × DAS-Ø15Ø7-1 × MON-87411 × DAS-59122-7 × DAS-40278-9 corn, DAS-81419-2 × DAS-44406-6 soybean, and DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 × MON-88913-8 × DAS-81910-7 cotton) and their component single events (MON-87427, MON-89034, DAS-Ø15Ø7-1, MON-87411, DAS-59122-7, and DAS-40278-9 corn, DAS-81419-2, and DAS-44406-6 soybean, and DAS-21023-5, DAS-24236-5, SYN-IR102-7, MON-88913-8, and DAS-81910-7 cotton). Comparisons were made within a crop and transgene product across plant tissue types and were also made across transgene products in each breeding stack for grain/seed. Scatter plots were generated comparing expression in the stacks to their component events, and the percent of variability accounted for by the line of identity (y = x) was calculated (coefficient of identity, I 2 ). Results support transgene concentrations in single events predicting similar concentrations in breeding stacks containing the single events. Therefore, food, feed, and environmental risk assessments based on concentrations of transgene products in single GM events are generally applicable to breeding stacks composed of these events.

Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation.

PubMed

Baumgärtel, Regina M; Krawczyk-Becker, Martin; Marquardt, Daniel; Völker, Christoph; Hu, Hongmei; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Ernst, Stephan M A; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-12-30

In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. © The Author(s) 2015.

Individualization of controlled ovarian stimulation in vitro fertilization using ovarian reserve markers.

PubMed

Grisendi, Valentina; La Marca, Antonio

2017-06-01

In assisted reproduction technologies (ART) the controlled ovarian stimulation (COS) therapy is the starting point from which a good oocytes retrieval depends. Treatment individualization is based on ovarian response prediction, which largely depends on a woman's ovarian reserve. Anti-Müllerian hormone (AMH) and antral follicle count (AFC) are considered the most accurate and reliable markers of ovarian reserve. A literature search was carried out for studies that addressed the ability of AMH and AFC to predict poor and/or excessive ovarian response in IVF cycles. According to the predicted response to ovarian stimulation (poor- normal- or high-response) is today possible not only to personalize pre-treatment counseling with the couple, but also to individualize the ovarian stimulation protocol, choosing among GnRH-agonists or antagonists for endogenous follicle-stimulating hormone (FSH) suppression and formulating the FSH starting dose most adequate for the single patients. In this review we discuss how to choose the best COS therapy for the single patient, on the basis of the markers-guided ovarian response prediction.

Phonological neighborhood and word frequency effects on the stuttered disfluencies of children who stutter: comments on Anderson (2007).

PubMed

Howell, Peter

2010-10-01

This letter comments on a study by Anderson (2007) that compared the effects of word frequency, neighborhood density, and phonological neighborhood frequency on part-word repetitions, prolongations, and single-syllable word repetitions produced by children who stutter. Anderson discussed her results with respect to 2 theories about stuttering: the covert repair hypothesis and execution planning (EXPLAN) theory. Her remarks about EXPLAN theory are examined. Anderson considered that EXPLAN does not predict the relationship between word and neighborhood frequency and stuttering for part-word repetitions and prolongations (she considered that EXPLAN predicts that stuttering occurs on simple words for children). The actual predictions that EXPLAN makes are upheld by her results. She also considered that EXPLAN cannot account for why stuttering is affected by the same variables that lead to speech errors, and it is shown that this is incorrect. The effects of word frequency, neighborhood density, and phonological neighborhood frequency on part-word repetitions, prolongations, and single-syllable word repetitions reported by Anderson (2007) are consistent with the predictions of the EXPLAN model.

Predicting the nature of supernova progenitors.

PubMed

Groh, Jose H

2017-10-28

Stars more massive than about 8 solar masses end their lives as a supernova (SN), an event of fundamental importance Universe-wide. The physical properties of massive stars before the SN event are very uncertain, both from theoretical and observational perspectives. In this article, I briefly review recent efforts to predict the nature of stars before death, in particular, by performing coupled stellar evolution and atmosphere modelling of single stars in the pre-SN stage. These models are able to predict the high-resolution spectrum and broadband photometry, which can then be directly compared with the observations of core-collapse SN progenitors. The predictions for the spectral types of massive stars before death can be surprising. Depending on the initial mass and rotation, single star models indicate that massive stars die as red supergiants, yellow hypergiants, luminous blue variables and Wolf-Rayet stars of the WN and WO subtypes. I finish by assessing the detectability of SN Ibc progenitors.This article is part of the themed issue 'Bridging the gap: from massive stars to supernovae'. © 2017 The Author(s).

High speed turboprop aeroacoustic study (counterrotation). Volume 2: Computer programs

NASA Technical Reports Server (NTRS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-01-01

The isolated counterrotating high speed turboprop noise prediction program developed and funded by GE Aircraft Engines was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in the NASA-Lewis 8 x 6 and 9 x 15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counter rotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attack was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combined into a single prediction program. The results were compared with data taken during the flight test of the B727/UDF (trademark) engine demonstrator aircraft.

High speed turboprop aeroacoustic study (counterrotation). Volume 2: Computer programs

NASA Astrophysics Data System (ADS)

Whitfield, C. E.; Mani, R.; Gliebe, P. R.

1990-07-01

The isolated counterrotating high speed turboprop noise prediction program developed and funded by GE Aircraft Engines was compared with model data taken in the GE Aircraft Engines Cell 41 anechoic facility, the Boeing Transonic Wind Tunnel, and in the NASA-Lewis 8 x 6 and 9 x 15 wind tunnels. The predictions show good agreement with measured data under both low and high speed simulated flight conditions. The installation effect model developed for single rotation, high speed turboprops was extended to include counter rotation. The additional effect of mounting a pylon upstream of the forward rotor was included in the flow field modeling. A nontraditional mechanism concerning the acoustic radiation from a propeller at angle of attack was investigated. Predictions made using this approach show results that are in much closer agreement with measurement over a range of operating conditions than those obtained via traditional fluctuating force methods. The isolated rotors and installation effects models were combined into a single prediction program. The results were compared with data taken during the flight test of the B727/UDF (trademark) engine demonstrator aircraft.

Experimental and numerical simulation of a rotor/stator interaction event localized on a single blade within an industrial high-pressure compressor

NASA Astrophysics Data System (ADS)

Batailly, Alain; Agrapart, Quentin; Millecamps, Antoine; Brunel, Jean-François

2016-08-01

This contribution addresses a confrontation between the experimental simulation of a rotor/stator interaction case initiated by structural contacts with numerical predictions made with an in-house numerical strategy. Contrary to previous studies carried out within the low-pressure compressor of an aircraft engine, this interaction is found to be non-divergent: high amplitudes of vibration are experimentally observed and numerically predicted over a short period of time. An in-depth analysis of experimental data first allows for a precise characterization of the interaction as a rubbing event involving the first torsional mode of a single blade. Numerical results are in good agreement with experimental observations: the critical angular speed, the wear patterns on the casing as well as the blade dynamics are accurately predicted. Through out the article, the in-house numerical strategy is also confronted to another numerical strategy that may be found in the literature for the simulation of rubbing events: key differences are underlined with respect to the prediction of non-linear interaction phenomena.

Comparing Binaural Pre-processing Strategies I

PubMed Central

Krawczyk-Becker, Martin; Marquardt, Daniel; Völker, Christoph; Hu, Hongmei; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Ernst, Stephan M. A.; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-01-01

In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. PMID:26721920

Beyond SaGMRotI: Conversion to SaArb, SaSN, and SaMaxRot

USGS Publications Warehouse

Watson-Lamprey, J. A.; Boore, D.M.

2007-01-01

In the seismic design of structures, estimates of design forces are usually provided to the engineer in the form of elastic response spectra. Predictive equations for elastic response spectra are derived from empirical recordings of ground motion. The geometric mean of the two orthogonal horizontal components of motion is often used as the response value in these predictive equations, although it is not necessarily the most relevant estimate of forces within the structure. For some applications it is desirable to estimate the response value on a randomly chosen single component of ground motion, and in other applications the maximum response in a single direction is required. We give adjustment factors that allow converting the predictions of geometric-mean ground-motion predictions into either of these other two measures of seismic ground-motion intensity. In addition, we investigate the relation of the strike-normal component of ground motion to the maximum response values. We show that the strike-normal component of ground motion seldom corresponds to the maximum horizontal-component response value (in particular, at distances greater than about 3 km from faults), and that focusing on this case in exclusion of others can result in the underestimation of the maximum component. This research provides estimates of the maximum response value of a single component for all cases, not just near-fault strike-normal components. We provide modification factors that can be used to convert predictions of ground motions in terms of the geometric mean to the maximum spectral acceleration (SaMaxRot) and the random component of spectral acceleration (SaArb). Included are modification factors for both the mean and the aleatory standard deviation of the logarithm of the motions.

Germline contamination and leakage in whole genome somatic single nucleotide variant detection.

PubMed

Sendorek, Dorota H; Caloian, Cristian; Ellrott, Kyle; Bare, J Christopher; Yamaguchi, Takafumi N; Ewing, Adam D; Houlahan, Kathleen E; Norman, Thea C; Margolin, Adam A; Stuart, Joshua M; Boutros, Paul C

2018-01-31

The clinical sequencing of cancer genomes to personalize therapy is becoming routine across the world. However, concerns over patient re-identification from these data lead to questions about how tightly access should be controlled. It is not thought to be possible to re-identify patients from somatic variant data. However, somatic variant detection pipelines can mistakenly identify germline variants as somatic ones, a process called "germline leakage". The rate of germline leakage across different somatic variant detection pipelines is not well-understood, and it is uncertain whether or not somatic variant calls should be considered re-identifiable. To fill this gap, we quantified germline leakage across 259 sets of whole-genome somatic single nucleotide variant (SNVs) predictions made by 21 teams as part of the ICGC-TCGA DREAM Somatic Mutation Calling Challenge. The median somatic SNV prediction set contained 4325 somatic SNVs and leaked one germline polymorphism. The level of germline leakage was inversely correlated with somatic SNV prediction accuracy and positively correlated with the amount of infiltrating normal cells. The specific germline variants leaked differed by tumour and algorithm. To aid in quantitation and correction of leakage, we created a tool, called GermlineFilter, for use in public-facing somatic SNV databases. The potential for patient re-identification from leaked germline variants in somatic SNV predictions has led to divergent open data access policies, based on different assessments of the risks. Indeed, a single, well-publicized re-identification event could reshape public perceptions of the values of genomic data sharing. We find that modern somatic SNV prediction pipelines have low germline-leakage rates, which can be further reduced, especially for cloud-sharing, using pre-filtering software.

Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers

PubMed Central

Xu, Li; Fengji, Liang; Changning, Liu; Liangcai, Zhang; Yinghui, Li; Yu, Li; Shanguang, Chen; Jianghui, Xiong

2015-01-01

Introduction Advances in high-throughput technologies have generated diverse informative molecular markers for cancer outcome prediction. Long non-coding RNA (lncRNA) and DNA methylation as new classes of promising markers are emerging as key molecules in human cancers; however, the prognostic utility of such diverse molecular data remains to be explored. Materials and Methods We proposed a computational pipeline (IDFO) to predict patient survival by identifying prognosis-related biomarkers using multi-type molecular data (mRNA, microRNA, DNA methylation, and lncRNA) from 3198 samples of five cancer types. We assessed the predictive performance of both single molecular data and integrated multi-type molecular data in patient survival stratification, and compared their relative importance in each type of cancer, respectively. Survival analysis using multivariate Cox regression was performed to investigate the impact of the IDFO-identified markers and traditional variables on clinical outcome. Results Using the IDFO approach, we obtained good predictive performance of the molecular datasets (bootstrap accuracy: 0.71–0.97) in five cancer types. Impressively, lncRNA was identified as the best prognostic predictor in the validated cohorts of four cancer types, followed by DNA methylation, mRNA, and then microRNA. We found the incorporating of multi-type molecular data showed similar predictive power to single-type molecular data, but with the exception of the lncRNA + DNA methylation combinations in two cancers. Survival analysis of proportional hazard models confirmed a high robustness for lncRNA and DNA methylation as prognosis factors independent of traditional clinical variables. Conclusion Our study provides insight into systematically understanding the prognostic performance of diverse molecular data in both single and aggregate patterns, which may have specific reference to subsequent related studies. PMID:26606135

Dynamic imaging of adaptive stress response pathway activation for prediction of drug induced liver injury.

PubMed

Wink, Steven; Hiemstra, Steven W; Huppelschoten, Suzanne; Klip, Janna E; van de Water, Bob

2018-05-01

Drug-induced liver injury remains a concern during drug treatment and development. There is an urgent need for improved mechanistic understanding and prediction of DILI liabilities using in vitro approaches. We have established and characterized a panel of liver cell models containing mechanism-based fluorescent protein toxicity pathway reporters to quantitatively assess the dynamics of cellular stress response pathway activation at the single cell level using automated live cell imaging. We have systematically evaluated the application of four key adaptive stress pathway reporters for the prediction of DILI liability: SRXN1-GFP (oxidative stress), CHOP-GFP (ER stress/UPR response), p21 (p53-mediated DNA damage-related response) and ICAM1 (NF-κB-mediated inflammatory signaling). 118 FDA-labeled drugs in five human exposure relevant concentrations were evaluated for reporter activation using live cell confocal imaging. Quantitative data analysis revealed activation of single or multiple reporters by most drugs in a concentration and time dependent manner. Hierarchical clustering of time course dynamics and refined single cell analysis allowed the allusion of key events in DILI liability. Concentration response modeling was performed to calculate benchmark concentrations (BMCs). Extracted temporal dynamic parameters and BMCs were used to assess the predictive power of sub-lethal adaptive stress pathway activation. Although cellular adaptive responses were activated by non-DILI and severe-DILI compounds alike, dynamic behavior and lower BMCs of pathway activation were sufficiently distinct between these compound classes. The high-level detailed temporal- and concentration-dependent evaluation of the dynamics of adaptive stress pathway activation adds to the overall understanding and prediction of drug-induced liver liabilities.

A novel single-parameter approach for forecasting algal blooms.

PubMed

Xiao, Xi; He, Junyu; Huang, Haomin; Miller, Todd R; Christakos, George; Reichwaldt, Elke S; Ghadouani, Anas; Lin, Shengpan; Xu, Xinhua; Shi, Jiyan

2017-01-01

Harmful algal blooms frequently occur globally, and forecasting could constitute an essential proactive strategy for bloom control. To decrease the cost of aquatic environmental monitoring and increase the accuracy of bloom forecasting, a novel single-parameter approach combining wavelet analysis with artificial neural networks (WNN) was developed and verified based on daily online monitoring datasets of algal density in the Siling Reservoir, China and Lake Winnebago, U.S.A. Firstly, a detailed modeling process was illustrated using the forecasting of cyanobacterial cell density in the Chinese reservoir as an example. Three WNN models occupying various prediction time intervals were optimized through model training using an early stopped training approach. All models performed well in fitting historical data and predicting the dynamics of cyanobacterial cell density, with the best model predicting cyanobacteria density one-day ahead (r = 0.986 and mean absolute error = 0.103 × 10 4  cells mL -1 ). Secondly, the potential of this novel approach was further confirmed by the precise predictions of algal biomass dynamics measured as chl a in both study sites, demonstrating its high performance in forecasting algal blooms, including cyanobacteria as well as other blooming species. Thirdly, the WNN model was compared to current algal forecasting methods (i.e. artificial neural networks, autoregressive integrated moving average model), and was found to be more accurate. In addition, the application of this novel single-parameter approach is cost effective as it requires only a buoy-mounted fluorescent probe, which is merely a fraction (∼15%) of the cost of a typical auto-monitoring system. As such, the newly developed approach presents a promising and cost-effective tool for the future prediction and management of harmful algal blooms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural Network Burst Pressure Prediction in Graphite/Epoxy Pressure Vessels from Acoustic Emission Amplitude Data

NASA Technical Reports Server (NTRS)

Hill, Eric v. K.; Walker, James L., II; Rowell, Ginger H.

1995-01-01

Acoustic emission (AE) data were taken during hydroproof for three sets of ASTM standard 5.75 inch diameter filament wound graphite/epoxy bottles. All three sets of bottles had the same design and were wound from the same graphite fiber; the only difference was in the epoxies used. Two of the epoxies had similar mechanical properties, and because the acoustic properties of materials are a function of their stiffnesses, it was thought that the AE data from the two sets might also be similar; however, this was not the case. Therefore, the three resin types were categorized using dummy variables, which allowed the prediction of burst pressures all three sets of bottles using a single neural network. Three bottles from each set were used to train the network. The resin category, the AE amplitude distribution data taken up to 25 % of the expected burst pressure, and the actual burst pressures were used as inputs. Architecturally, the network consisted of a forty-three neuron input layer (a single categorical variable defining the resin type plus forty-two continuous variables for the AE amplitude frequencies), a fifteen neuron hidden layer for mapping, and a single output neuron for burst pressure prediction. The network trained on all three bottle sets was able to predict burst pressures in the remaining bottles with a worst case error of + 6.59%, slightly greater than the desired goal of + 5%. This larger than desired error was due to poor resolution in the amplitude data for the third bottle set. When the third set of bottles was eliminated from consideration, only four hidden layer neurons were necessary to generate a worst case prediction error of - 3.43%, well within the desired goal.

Multi-model ensemble hydrologic prediction using Bayesian model averaging

NASA Astrophysics Data System (ADS)

Duan, Qingyun; Ajami, Newsha K.; Gao, Xiaogang; Sorooshian, Soroosh

2007-05-01

Multi-model ensemble strategy is a means to exploit the diversity of skillful predictions from different models. This paper studies the use of Bayesian model averaging (BMA) scheme to develop more skillful and reliable probabilistic hydrologic predictions from multiple competing predictions made by several hydrologic models. BMA is a statistical procedure that infers consensus predictions by weighing individual predictions based on their probabilistic likelihood measures, with the better performing predictions receiving higher weights than the worse performing ones. Furthermore, BMA provides a more reliable description of the total predictive uncertainty than the original ensemble, leading to a sharper and better calibrated probability density function (PDF) for the probabilistic predictions. In this study, a nine-member ensemble of hydrologic predictions was used to test and evaluate the BMA scheme. This ensemble was generated by calibrating three different hydrologic models using three distinct objective functions. These objective functions were chosen in a way that forces the models to capture certain aspects of the hydrograph well (e.g., peaks, mid-flows and low flows). Two sets of numerical experiments were carried out on three test basins in the US to explore the best way of using the BMA scheme. In the first set, a single set of BMA weights was computed to obtain BMA predictions, while the second set employed multiple sets of weights, with distinct sets corresponding to different flow intervals. In both sets, the streamflow values were transformed using Box-Cox transformation to ensure that the probability distribution of the prediction errors is approximately Gaussian. A split sample approach was used to obtain and validate the BMA predictions. The test results showed that BMA scheme has the advantage of generating more skillful and equally reliable probabilistic predictions than original ensemble. The performance of the expected BMA predictions in terms of daily root mean square error (DRMS) and daily absolute mean error (DABS) is generally superior to that of the best individual predictions. Furthermore, the BMA predictions employing multiple sets of weights are generally better than those using single set of weights.

Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data.

PubMed

Chen, Shuonan; Mar, Jessica C

2018-06-19

A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequencing methods now becoming accessible, general network inference algorithms that were initially developed for data collected from bulk samples may not be suitable for single cells. Meanwhile, although methods that are specific for single cell data are now emerging, whether they have improved performance over general methods is unknown. In this study, we evaluate the applicability of five general methods and three single cell methods for inferring gene regulatory networks from both experimental single cell gene expression data and in silico simulated data. Standard evaluation metrics using ROC curves and Precision-Recall curves against reference sets sourced from the literature demonstrated that most of the methods performed poorly when they were applied to either experimental single cell data, or simulated single cell data, which demonstrates their lack of performance for this task. Using default settings, network methods were applied to the same datasets. Comparisons of the learned networks highlighted the uniqueness of some predicted edges for each method. The fact that different methods infer networks that vary substantially reflects the underlying mathematical rationale and assumptions that distinguish network methods from each other. This study provides a comprehensive evaluation of network modeling algorithms applied to experimental single cell gene expression data and in silico simulated datasets where the network structure is known. Comparisons demonstrate that most of these assessed network methods are not able to predict network structures from single cell expression data accurately, even if they are specifically developed for single cell methods. Also, single cell methods, which usually depend on more elaborative algorithms, in general have less similarity to each other in the sets of edges detected. The results from this study emphasize the importance for developing more accurate optimized network modeling methods that are compatible for single cell data. Newly-developed single cell methods may uniquely capture particular features of potential gene-gene relationships, and caution should be taken when we interpret these results.

Impact of Different Correlations on TRACEv4.160 Predicted Critical Heat Flux

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

Jasiulevicius, A.; Macian-Juan, R.

2006-07-01

This paper presents an independent assessment of the Critical Heat Flux (CHF) models implemented in TRACEv4.160 with data from the experiments carried out at the Royal Institute of Technology (RIT) in Stockholm, Sweden, with single vertical uniformly heated 7.0 m long tubes. In previous CHF assessment studies with TRACE, it was noted that, although the overall code predictions in long single tubes with inner diameters of 1.0 to 2.49 cm agreed rather well with the results of experiments (with r.m.s. error being 25.6%), several regions of pressure and coolant mass flux could be identified, in which the code strongly under-predictsmore » or over-predicts the CHF. In order to evaluate the possibility of improving the code performance, some of the most widely used and assessed CHF correlations were additionally implemented in TRACEv4.160, namely Bowring, Levitan - Lantsman, and Tong-W3. The results obtained for the CHF predictions in single tubes with uniform axial heat flux by using these correlations, were compared to the results produced with the standard TRACE correlations (Biasi and CISE-GE), and with the experimental data from RIT, which covered a broad range of pressures (3-20 MPa) and coolant mass fluxes (500-3000 kg/m{sup 2}s). Several hundreds of experimental points were calculated to cover the parameter range mentioned above for the evaluation of the newly implemented correlations in the TRACEv4.160 code. (author)« less

Effects of complex life cycles on genetic diversity: cyclical parthenogenesis.

PubMed

Rouger, R; Reichel, K; Malrieu, F; Masson, J P; Stoeckel, S

2016-11-01

Neutral patterns of population genetic diversity in species with complex life cycles are difficult to anticipate. Cyclical parthenogenesis (CP), in which organisms undergo several rounds of clonal reproduction followed by a sexual event, is one such life cycle. Many species, including crop pests (aphids), human parasites (trematodes) or models used in evolutionary science (Daphnia), are cyclical parthenogens. It is therefore crucial to understand the impact of such a life cycle on neutral genetic diversity. In this paper, we describe distributions of genetic diversity under conditions of CP with various clonal phase lengths. Using a Markov chain model of CP for a single locus and individual-based simulations for two loci, our analysis first demonstrates that strong departures from full sexuality are observed after only a few generations of clonality. The convergence towards predictions made under conditions of full clonality during the clonal phase depends on the balance between mutations and genetic drift. Second, the sexual event of CP usually resets the genetic diversity at a single locus towards predictions made under full sexuality. However, this single recombination event is insufficient to reshuffle gametic phases towards full-sexuality predictions. Finally, for similar levels of clonality, CP and acyclic partial clonality (wherein a fixed proportion of individuals are clonally produced within each generation) differentially affect the distribution of genetic diversity. Overall, this work provides solid predictions of neutral genetic diversity that may serve as a null model in detecting the action of common evolutionary or demographic processes in cyclical parthenogens (for example, selection or bottlenecks).

Oxygen Uptake Efficiency Plateau Best Predicts Early Death in Heart Failure

PubMed Central

Hansen, James E.; Stringer, William W.

2012-01-01

Background: The responses of oxygen uptake efficiency (ie, oxygen uptake/ventilation = V˙o2/V˙e) and its highest plateau (OUEP) during incremental cardiopulmonary exercise testing (CPET) in patients with chronic left heart failure (HF) have not been previously reported. We planned to test the hypothesis that OUEP during CPET is the best single predictor of early death in HF. Methods: We evaluated OUEP, slope of V˙o2 to log(V˙e) (oxygen uptake efficiency slope), oscillatory breathing, and all usual resting and CPET measurements in 508 patients with low-ejection-fraction (< 35%) HF. Each had further evaluations at other sites, including cardiac catheterization. Outcomes were 6-month all-reason mortality and morbidity (death or > 24 h cardiac hospitalization). Statistical analyses included area under curve of receiver operating characteristics, ORs, univariate and multivariate Cox regression, and Kaplan-Meier plots. Results: OUEP, which requires only moderate exercise, was often reduced in patients with HF. A low % predicted OUEP was the single best predictor of mortality (P < .0001), with an OR of 13.0 (P < .001). When combined with oscillatory breathing, the OR increased to 56.3, superior to all other resting or exercise parameters or combinations of parameters. Other statistical analyses and morbidity analysis confirmed those findings. Conclusions: OUEP is often reduced in patients with HF. Low % predicted OUEP (< 65% predicted) is the single best predictor of early death, better than any other CPET or other cardiovascular measurement. Paired with oscillatory breathing, it is even more powerful. PMID:22030802

Lung transplantation for non-cystic fibrosis bronchiectasis: analysis of a 13-year experience.

PubMed

Beirne, Paul Adrian; Banner, Nicholas R; Khaghani, Asghar; Hodson, Margaret E; Yacoub, Magdi H

2005-10-01

Lung transplantation is a well-established treatment for end-stage cystic fibrosis, and there are considerable data on medium- and long-term results. However, less information exists about transplantation for non-cystic fibrosis bronchiectasis. Between December 1988 and June 2001, 22 patients (12 men, 10 women) underwent transplantation for bronchiectasis not due to cystic fibrosis. Procedures were bilateral sequential single-lung transplants (BSSLTX) in 4 patients, en bloc double lung transplants (DLTX) in 5, heart-lung transplants (HLTX) in 6, and single-lung transplants (SLTX) in 7. Lifelong outpatient follow-up was continued at a minimum of every 6 months. One-year Kaplan-Meier survival for all patients was 68% (95% confidence interval [CI], 54%-91%), and 5-year survival was 62% (95% CI, 41-83%). One-year survival after SLTX was 57% (95% CI, 20%-94%) vs 73% (95% CI, 51-96%) for those receiving 2 lungs. At 6 months, mean forced expiratory volume in 1 second was 73% predicted (range, 58%-97%), and mean forced vital capacity was 68% predicted (range, 53%-94%) after receiving 2 lungs (n = 10); in the SLTX group at 6 months, mean forced expiratory volume in 1 second was 50% predicted (range, 34%-61%), and mean forced vital capacity was 53% predicted (range 46-63%) (n = 4). Survival and lung function after transplantation for non-cystic fibrosis bronchiectasis was similar to that after transplantation for cystic fibrosis. A good outcome is possible after single lung transplantation in selected patients.

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

PubMed

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 <37 and <35 weeks of gestation with pooled sensitivities and specificities, and summary positive and negative likelihood ratios ranging from 49% to 74%, 44% to 85%, 1.3 to 4.1, and 0.3 to 0.7, respectively. In women with twin gestations, the shortening of cervical length over time had a low to moderate predictive accuracy for preterm birth at <34, <32, <30, and <28 weeks of gestation with pooled sensitivities and specificities, and summary positive and negative likelihood ratios ranging from 47% to 73%, 84% to 89%, 3.8 to 5.3, and 0.3 to 0.6, respectively. There were no statistically significant differences between the 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.

Prediction and Testing of Biological Networks Underlying Intestinal Cancer

PubMed Central

Mariadason, John M.; Wang, Donghai; Augenlicht, Leonard H.; Chance, Mark R.

2010-01-01

Colorectal cancer progresses through an accumulation of somatic mutations, some of which reside in so-called “driver” genes that provide a growth advantage to the tumor. To identify points of intersection between driver gene pathways, we implemented a network analysis framework using protein interactions to predict likely connections – both precedented and novel – between key driver genes in cancer. We applied the framework to find significant connections between two genes, Apc and Cdkn1a (p21), known to be synergistic in tumorigenesis in mouse models. We then assessed the functional coherence of the resulting Apc-Cdkn1a network by engineering in vivo single node perturbations of the network: mouse models mutated individually at Apc (Apc1638N+/−) or Cdkn1a (Cdkn1a−/−), followed by measurements of protein and gene expression changes in intestinal epithelial tissue. We hypothesized that if the predicted network is biologically coherent (functional), then the predicted nodes should associate more specifically with dysregulated genes and proteins than stochastically selected genes and proteins. The predicted Apc-Cdkn1a network was significantly perturbed at the mRNA-level by both single gene knockouts, and the predictions were also strongly supported based on physical proximity and mRNA coexpression of proteomic targets. These results support the functional coherence of the proposed Apc-Cdkn1a network and also demonstrate how network-based predictions can be statistically tested using high-throughput biological data. PMID:20824133

Severe community-acquired pneumonia. Assessment of severity criteria.

PubMed

Ewig, S; Ruiz, M; Mensa, J; Marcos, M A; Martinez, J A; Arancibia, F; Niederman, M S; Torres, A

1998-10-01

The purpose of the study was to validate the criteria used in the guidelines of the American Thoracic Society (ATS) for severe community-acquired pneumonia (CAP). Severe pneumonia was defined as admission to the intensive care unit (ICU). Overall 331 nonsevere (84%) and 64 severe cases (16%) of CAP were prospectively studied. Mortality was 19 of 395 (5%) and 19 of 64 (30%), respectively. Single severity criteria as well as the ATS definition of severe pneumonia were assessed calculating the operative indices. A modified prediction rule including minor (baseline) and major (baseline or evolutionary) criteria was derived. Single minor criteria at admission had a low sensitivity and positive predictive value. Defining severe pneumonia according to the ATS guidelines had a high sensitivity (98%). However, specificity and positive predictive value were low (32% and 24%, respectively). A modified prediction rule (presence of two or three minor criteria [systolic blood pressure < 90 mm Hg, multilobar involvement, PaO2/FIO2 < 250] or one of two major criteria [requirement of mechanical ventilation, presence of septic shock]) had a sensitivity of 78%, a specificity of 94%, a positive predictive value of 75%, and a negative predictive value of 95%. The ATS definition of severe pneumonia was highly sensitive but insufficiently specific and had a low positive predictive value. Our suggested modified rule had a more balanced performance and, if validated in an independent population, may represent a more accurate definition of severe CAP.

Integrating environmental and genetic effects to predict responses of tree populations to climate.

PubMed

Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

2010-01-01

Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

Reliability Estimation for Single-unit Ceramic Crown Restorations

PubMed Central

Lekesiz, H.

2014-01-01

The objective of this study was to evaluate the potential of a survival prediction method for the assessment of ceramic dental restorations. For this purpose, fast-fracture and fatigue reliabilities for 2 bilayer (metal ceramic alloy core veneered with fluorapatite leucite glass-ceramic, d.Sign/d.Sign-67, by Ivoclar; glass-infiltrated alumina core veneered with feldspathic porcelain, VM7/In-Ceram Alumina, by Vita) and 3 monolithic (leucite-reinforced glass-ceramic, Empress, and ProCAD, by Ivoclar; lithium-disilicate glass-ceramic, Empress 2, by Ivoclar) single posterior crown restorations were predicted, and fatigue predictions were compared with the long-term clinical data presented in the literature. Both perfectly bonded and completely debonded cases were analyzed for evaluation of the influence of the adhesive/restoration bonding quality on estimations. Material constants and stress distributions required for predictions were calculated from biaxial tests and finite element analysis, respectively. Based on the predictions, In-Ceram Alumina presents the best fast-fracture resistance, and ProCAD presents a comparable resistance for perfect bonding; however, ProCAD shows a significant reduction of resistance in case of complete debonding. Nevertheless, it is still better than Empress and comparable with Empress 2. In-Ceram Alumina and d.Sign have the highest long-term reliability, with almost 100% survivability even after 10 years. When compared with clinical failure rates reported in the literature, predictions show a promising match with clinical data, and this indicates the soundness of the settings used in the proposed predictions. PMID:25048249

Prediction of Adulthood Obesity Using Genetic and Childhood Clinical Risk Factors in the Cardiovascular Risk in Young Finns Study.

PubMed

Seyednasrollah, Fatemeh; Mäkelä, Johanna; Pitkänen, Niina; Juonala, Markus; Hutri-Kähönen, Nina; Lehtimäki, Terho; Viikari, Jorma; Kelly, Tanika; Li, Changwei; Bazzano, Lydia; Elo, Laura L; Raitakari, Olli T

2017-06-01

Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3-18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, P <0.0001) and validation data (AUC=0.769 versus AUC=0.747, P =0.026). WGRS97 improved the accuracy in training (AUC=0.782 versus AUC=0.744, P <0.0001) but not in validation data (AUC=0.749 versus AUC=0.747, P =0.785). Higher WGRS19 associated with higher body mass index at 9 years and WGRS97 at 6 years. Replication in BHS confirmed our findings that WGRS19 and WGRS97 are associated with body mass index. WGRS19 improves prediction of adulthood obesity. Predictive accuracy is highest among young children (3-6 years), whereas among older children (9-18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity. © 2017 American Heart Association, Inc.

Contribution of domestic production records, Interbull estimated breeding values, and single nucleotide polymorphism genetic markers to the single-step genomic evaluation of milk production.

PubMed

Přibyl, J; Madsen, P; Bauer, J; Přibylová, J; Simečková, M; Vostrý, L; Zavadilová, L

2013-03-01

Estimated breeding values (EBV) for first-lactation milk production of Holstein cattle in the Czech Republic were calculated using a conventional animal model and by single-step prediction of the genomic enhanced breeding value. Two overlapping data sets of milk production data were evaluated: (1) calving years 1991 to 2006, with 861,429 lactations and 1,918,901 animals in the pedigree and (2) calving years 1991 to 2010, with 1,097,319 lactations and 1,906,576 animals in the pedigree. Global Interbull (Uppsala, Sweden) deregressed proofs of 114,189 bulls were used in the analyses. Reliabilities of Interbull values were equivalent to an average of 8.53 effective records, which were used in a weighted analysis. A total of 1,341 bulls were genotyped using the Illumina BovineSNP50 BeadChip V2 (Illumina Inc., San Diego, CA). Among the genotyped bulls were 332 young bulls with no daughters in the first data set but more than 50 daughters (88.41, on average) with performance records in the second data set. For young bulls, correlations of EBV and genomic enhanced breeding value before and after progeny testing, corresponding average expected reliabilities, and effective daughter contributions (EDC) were calculated. The reliability of prediction pedigree EBV of young bulls was 0.41, corresponding to EDC=10.6. Including Interbull deregressed proofs improved the reliability of prediction by EDC=13.4 and including genotyping improved prediction reliability by EDC=6.2. Total average expected reliability of prediction reached 0.67, corresponding to EDC=30.2. The combination of domestic and Interbull sources for both genotyped and nongenotyped animals is valuable for improving the accuracy of genetic prediction in small populations of dairy cattle. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Re-Analysis of the Solar Phase Curves of the Icy Galilean Satellites

NASA Technical Reports Server (NTRS)

Domingue, Deborah; Verbiscer, Anne

1997-01-01

Re-analysis of the solar phase curves of the icy Galilean satellites demonstrates that the quantitative results are dependent on the single particle scattering function incorporated into the photometric model; however, the qualitative properties are independent. The results presented here show that the general physical characteristics predicted by a Hapke model (B. Hapke, 1986, Icarus 67, 264-280) incorporating a two parameter double Henyey-Greenstein scattering function are similar to the predictions given by the same model incorporating a three parameter double Henyey-Greenstein scattering function as long as the data set being modeled has adequate coverage in phase angle. Conflicting results occur when the large phase angle coverage is inadequate. Analysis of the role of isotropic versus anisotropic multiple scattering shows that for surfaces as bright as Europa the two models predict very similar results over phase angles covered by the data. Differences arise only at those phase angles for which there are no data. The single particle scattering behavior between the leading and trailing hemispheres of Europa and Ganymede is commensurate with magnetospheric alterations of their surfaces. Ion bombardment will produce more forward scattering single scattering functions due to annealing of potential scattering centers within regolith particles (N. J. Sack et al., 1992, Icarus 100, 534-540). Both leading and trailing hemispheres of Europa are consistent with a high porosity model and commensurate with a frost surface. There are no strong differences in predicted porosity between the two hemispheres of Callisto, both are consistent with model porosities midway between that deduced for Europa and the Moon. Surface roughness model estimates predict that surface roughness increases with satellite distance from Jupiter, with lunar surface roughness values falling midway between those measured for Ganymede and Callisto. There is no obvious variation in predicted surface roughness with hemisphere for any of the Galilean satellites.

Reduced Antiplatelet Effect of Aspirin Does Not Predict Cardiovascular Events in Patients With Stable Coronary Artery Disease.

PubMed

Larsen, Sanne Bøjet; Grove, Erik Lerkevang; Neergaard-Petersen, Søs; Würtz, Morten; Hvas, Anne-Mette; Kristensen, Steen Dalby

2017-08-05

Increased platelet aggregation during antiplatelet therapy may predict cardiovascular events in patients with coronary artery disease. The majority of these patients receive aspirin monotherapy. We aimed to investigate whether high platelet-aggregation levels predict cardiovascular events in stable coronary artery disease patients treated with aspirin. We included 900 stable coronary artery disease patients with either previous myocardial infarction, type 2 diabetes mellitus, or both. All patients received single antithrombotic therapy with 75 mg aspirin daily. Platelet aggregation was evaluated 1 hour after aspirin intake using the VerifyNow Aspirin Assay (Accriva Diagnostics) and Multiplate Analyzer (Roche; agonists: arachidonic acid and collagen). Adherence to aspirin was confirmed by serum thromboxane B 2 . The primary end point was the composite of nonfatal myocardial infarction, ischemic stroke, and cardiovascular death. At 3-year follow-up, 78 primary end points were registered. The primary end point did not occur more frequently in patients with high platelet-aggregation levels (first versus fourth quartile) assessed by VerifyNow (hazard ratio: 0.5 [95% CI, 0.3-1.1], P =0.08) or Multiplate using arachidonic acid (hazard ratio: 1.0 [95% CI, 0.5-2.1], P =0.92) or collagen (hazard ratio: 1.4 [95% CI, 0.7-2.8], P =0.38). Similar results were found for the composite secondary end point (nonfatal myocardial infarction, ischemic stroke, stent thrombosis, and all-cause death) and the single end points. Thromboxane B 2 levels did not predict any end points. Renal insufficiency was the only clinical risk factor predicting the primary and secondary end points. This study is the largest to investigate platelet aggregation in stable coronary artery disease patients receiving aspirin as single antithrombotic therapy. We found that high platelet-aggregation levels did not predict cardiovascular events. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Waveguide-integrated single- and multi-photon detection at telecom wavelengths using superconducting nanowires

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

Ferrari, Simone; Kahl, Oliver; Kovalyuk, Vadim

We investigate single- and multi-photon detection regimes of superconducting nanowire detectors embedded in silicon nitride nanophotonic circuits. At near-infrared wavelengths, simultaneous detection of up to three photons is observed for 120 nm wide nanowires biased far from the critical current, while narrow nanowires below 100 nm provide efficient single photon detection. A theoretical model is proposed to determine the different detection regimes and to calculate the corresponding internal quantum efficiency. The predicted saturation of the internal quantum efficiency in the single photon regime agrees well with plateau behavior observed at high bias currents.

AGARD Manual on Aeroelasticity in Axial-Flow Turbomachines. Volume 2. Structural Dynamics and Aeroelasticity,

DTIC Science & Technology

1988-06-01

LEVELSKSI C. Q ac ca VANE OVERALL TOTAL-STATIC EXPANSION RATOS * Figure 12. Prediction of Response due to Second Stage Vane. 22-12 SAP /- MAXIMUM...assessment methods, written by Armstrong. The problem of life time prediction is reviewed by Labourdette, who also summarizes ONERA’s research in...applicable to single blades and bladed assemblies. The blade fatigue problem and its assessment methods, and life-time- prediction are considered. Aeroelastic

Structural behavior of composites with progressive fracture

NASA Technical Reports Server (NTRS)

Minnetyan, L.; Murthy, P. L. N.; Chamis, C. C.

1989-01-01

The objective of the study is to unify several computational tools developed for the prediction of progressive damage and fracture with efforts for the prediction of the overall response of damaged composite structures. In particular, a computational finite element model for the damaged structure is developed using a computer program as a byproduct of the analysis of progressive damage and fracture. Thus, a single computational investigation can predict progressive fracture and the resulting variation in structural properties of angleplied composites.

Accuracies of univariate and multivariate genomic prediction models in African cassava.

PubMed

Okeke, Uche Godfrey; Akdemir, Deniz; Rabbi, Ismail; Kulakow, Peter; Jannink, Jean-Luc

2017-12-04

Genomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for crop species such as cassava that have long breeding cycles. Practically, to implement GS in cassava breeding, it is necessary to evaluate different GS models and to develop suitable models for an optimized breeding pipeline. In this paper, we compared (1) prediction accuracies from a single-trait (uT) and a multi-trait (MT) mixed model for a single-environment genetic evaluation (Scenario 1), and (2) accuracies from a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model to a multivariate (ME) multi-environment mixed model that accounts for genotype-by-environment interaction for multi-environment genetic evaluation (Scenario 2). For these analyses, we used 16 years of public cassava breeding data for six target cassava traits and a fivefold cross-validation scheme with 10-repeat cycles to assess model prediction accuracies. In Scenario 1, the MT models had higher prediction accuracies than the uT models for all traits and locations analyzed, which amounted to on average a 40% improved prediction accuracy. For Scenario 2, we observed that the ME model had on average (across all locations and traits) a 12% improved prediction accuracy compared to the uE model. We recommend the use of multivariate mixed models (MT and ME) for cassava genetic evaluation. These models may be useful for other plant species.

Predictive equations for the estimation of body size in seals and sea lions (Carnivora: Pinnipedia)

PubMed Central

Churchill, Morgan; Clementz, Mark T; Kohno, Naoki

2014-01-01

Body size plays an important role in pinniped ecology and life history. However, body size data is often absent for historical, archaeological, and fossil specimens. To estimate the body size of pinnipeds (seals, sea lions, and walruses) for today and the past, we used 14 commonly preserved cranial measurements to develop sets of single variable and multivariate predictive equations for pinniped body mass and total length. Principal components analysis (PCA) was used to test whether separate family specific regressions were more appropriate than single predictive equations for Pinnipedia. The influence of phylogeny was tested with phylogenetic independent contrasts (PIC). The accuracy of these regressions was then assessed using a combination of coefficient of determination, percent prediction error, and standard error of estimation. Three different methods of multivariate analysis were examined: bidirectional stepwise model selection using Akaike information criteria; all-subsets model selection using Bayesian information criteria (BIC); and partial least squares regression. The PCA showed clear discrimination between Otariidae (fur seals and sea lions) and Phocidae (earless seals) for the 14 measurements, indicating the need for family-specific regression equations. The PIC analysis found that phylogeny had a minor influence on relationship between morphological variables and body size. The regressions for total length were more accurate than those for body mass, and equations specific to Otariidae were more accurate than those for Phocidae. Of the three multivariate methods, the all-subsets approach required the fewest number of variables to estimate body size accurately. We then used the single variable predictive equations and the all-subsets approach to estimate the body size of two recently extinct pinniped taxa, the Caribbean monk seal (Monachus tropicalis) and the Japanese sea lion (Zalophus japonicus). Body size estimates using single variable regressions generally under or over-estimated body size; however, the all-subset regression produced body size estimates that were close to historically recorded body length for these two species. This indicates that the all-subset regression equations developed in this study can estimate body size accurately. PMID:24916814

Single-stage experimental evaluation of tandem-airfoil rotor and stator blading for compressors, part 8

NASA Technical Reports Server (NTRS)

Brent, J. A.; Clemmons, D. R.

1974-01-01

An experimental investigation was conducted with an 0.8 hub/tip ratio, single-stage, axial flow compressor to determine the potential of tandem-airfoil blading for improving the efficiency and stable operating range of compressor stages. The investigation included testing of a baseline stage with single-airfoil blading and two tandem-blade stages. The overall performance of the baseline stage and the tandem-blade stage with a 20-80% loading split was considerably below the design prediction. The other tandem-blade stage, which had a rotor with a 50-50% loading split, came within 4.5% of the design pressure rise (delta P(bar)/P(bar) sub 1) and matched the design stage efficiency. The baseline stage with single-airfoil blading, which was designed to account for the actual rotor inlet velocity profile and the effects of axial velocity ratio and secondary flow, achieved the design predicted performance. The corresponding tandem-blade stage (50-50% loading split in both blade rows) slightly exceeded the design pressure rise but was 1.5 percentage points low in efficiency. The tandem rotors tested during both phases demonstrated higher pressure rise and efficiency than the corresponding single-airfoil rotor, with identical inlet and exit airfoil angles.

Negative differential conductance and super-Poissonian shot noise in single-molecule magnet junctions

PubMed Central

Xue, Hai-Bin; Liang, Jiu-Qing; Liu, Wu-Ming

2015-01-01

Molecular spintroinic device based on a single-molecule magnet is one of the ultimate goals of semiconductor nanofabrication technologies. It is thus necessary to understand the electron transport properties of a single-molecule magnet junction. Here we study the negative differential conductance and super-Poissonian shot noise properties of electron transport through a single-molecule magnet weakly coupled to two electrodes with either one or both of them being ferromagnetic. We predict that the negative differential conductance and super-Poissonian shot noise, which can be tuned by a gate voltage, depend sensitively on the spin polarization of the source and drain electrodes. In particular, the shot noise in the negative differential conductance region can be enhanced or decreased originating from the different formation mechanisms of negative differential conductance. The effective competition between fast and slow transport channels is responsible for the observed negative differential conductance and super-Poissonian shot noise. In addition, we further discuss the skewness and kurtosis properties of transport current in the super-Poissonian shot noise regions. Our findings suggest a tunable negative differential conductance molecular device, and the predicted properties of high-order current cumulants are very interesting for a better understanding of electron transport through single-molecule magnet junctions. PMID:25736094

Systematic assessment of the performance of whole-genome amplification for SNP/CNV detection and β-thalassemia genotyping.

PubMed

He, Fei; Zhou, Wanjun; Cai, Ren; Yan, Tizhen; Xu, Xiangmin

2018-04-01

In this study, we aimed to assess the performance of two whole-genome amplification methods, multiple displacement amplification (MDA), and multiple annealing and looping-based amplification cycle (MALBAC), for β-thalassemia genotyping and single-nucleotide polymorphism (SNP)/copy-number variant (CNV) detection using two DNA sequencing assays. We collected peripheral blood, cell lines, and discarded embryos, and carried out MALBAC and MDA on single-cell and five-cell samples. We detected and statistically analyzed differences in the amplification efficiency, positive predictive value, sensitivity, allele dropout (ADO) rate, SNPs, and CV values between the two methods. Through Sanger sequencing at the single-cell and five-cell levels, we showed that both the amplification rate and ADO rate of MDA were better than those using MALBAC, and the sensitivity and positive predictive value obtained from MDA were higher than those from MALBAC for β-thalassemia genotyping. Using next-generation sequencing (NGS) at the single-cell level, we confirmed that MDA has better properties than MALBAC for SNP detection. However, MALBAC was more stable and homogeneous than MDA using low-depth NGS at the single-cell level for CNV detection. We conclude that MALBAC is the better option for CNV detection, while MDA is better suited for SNV detection.

Negative differential conductance and super-Poissonian shot noise in single-molecule magnet junctions.

PubMed

Xue, Hai-Bin; Liang, Jiu-Qing; Liu, Wu-Ming

2015-03-04

Molecular spintroinic device based on a single-molecule magnet is one of the ultimate goals of semiconductor nanofabrication technologies. It is thus necessary to understand the electron transport properties of a single-molecule magnet junction. Here we study the negative differential conductance and super-Poissonian shot noise properties of electron transport through a single-molecule magnet weakly coupled to two electrodes with either one or both of them being ferromagnetic. We predict that the negative differential conductance and super-Poissonian shot noise, which can be tuned by a gate voltage, depend sensitively on the spin polarization of the source and drain electrodes. In particular, the shot noise in the negative differential conductance region can be enhanced or decreased originating from the different formation mechanisms of negative differential conductance. The effective competition between fast and slow transport channels is responsible for the observed negative differential conductance and super-Poissonian shot noise. In addition, we further discuss the skewness and kurtosis properties of transport current in the super-Poissonian shot noise regions. Our findings suggest a tunable negative differential conductance molecular device, and the predicted properties of high-order current cumulants are very interesting for a better understanding of electron transport through single-molecule magnet junctions.

Theory of single-molecule controlled rotation experiments, predictions, tests, and comparison with stalling experiments in F1-ATPase.

PubMed

Volkán-Kacsó, Sándor; Marcus, Rudolph A

2016-10-25

A recently proposed chemomechanical group transfer theory of rotary biomolecular motors is applied to treat single-molecule controlled rotation experiments. In these experiments, single-molecule fluorescence is used to measure the binding and release rate constants of nucleotides by monitoring the occupancy of binding sites. It is shown how missed events of nucleotide binding and release in these experiments can be corrected using theory, with F 1 -ATP synthase as an example. The missed events are significant when the reverse rate is very fast. Using the theory the actual rate constants in the controlled rotation experiments and the corrections are predicted from independent data, including other single-molecule rotation and ensemble biochemical experiments. The effective torsional elastic constant is found to depend on the binding/releasing nucleotide, and it is smaller for ADP than for ATP. There is a good agreement, with no adjustable parameters, between the theoretical and experimental results of controlled rotation experiments and stalling experiments, for the range of angles where the data overlap. This agreement is perhaps all the more surprising because it occurs even though the binding and release of fluorescent nucleotides is monitored at single-site occupancy concentrations, whereas the stalling and free rotation experiments have multiple-site occupancy.

Identification and Characterization of Novel Variations in Platelet G-Protein Coupled Receptor (GPCR) Genes in Patients Historically Diagnosed with Type 1 von Willebrand Disease.

PubMed

Stockley, Jacqueline; Nisar, Shaista P; Leo, Vincenzo C; Sabi, Essa; Cunningham, Margaret R; Eikenboom, Jeroen C; Lethagen, Stefan; Schneppenheim, Reinhard; Goodeve, Anne C; Watson, Steve P; Mundell, Stuart J; Daly, Martina E

2015-01-01

The clinical expression of type 1 von Willebrand disease may be modified by co-inheritance of other mild bleeding diatheses. We previously showed that mutations in the platelet P2Y12 ADP receptor gene (P2RY12) could contribute to the bleeding phenotype in patients with type 1 von Willebrand disease. Here we investigated whether variations in platelet G protein-coupled receptor genes other than P2RY12 also contributed to the bleeding phenotype. Platelet G protein-coupled receptor genes P2RY1, F2R, F2RL3, TBXA2R and PTGIR were sequenced in 146 index cases with type 1 von Willebrand disease and the potential effects of identified single nucleotide variations were assessed using in silico methods and heterologous expression analysis. Seven heterozygous single nucleotide variations were identified in 8 index cases. Two single nucleotide variations were detected in F2R; a novel c.-67G>C transversion which reduced F2R transcriptional activity and a rare c.1063C>T transition predicting a p.L355F substitution which did not interfere with PAR1 expression or signalling. Two synonymous single nucleotide variations were identified in F2RL3 (c.402C>G, p.A134 =; c.1029 G>C p.V343 =), both of which introduced less commonly used codons and were predicted to be deleterious, though neither of them affected PAR4 receptor expression. A third single nucleotide variation in F2RL3 (c.65 C>A; p.T22N) was co-inherited with a synonymous single nucleotide variation in TBXA2R (c.6680 C>T, p.S218 =). Expression and signalling of the p.T22N PAR4 variant was similar to wild-type, while the TBXA2R variation introduced a cryptic splice site that was predicted to cause premature termination of protein translation. The enrichment of single nucleotide variations in G protein-coupled receptor genes among type 1 von Willebrand disease patients supports the view of type 1 von Willebrand disease as a polygenic disorder.

Westerlund 1 is a Galactic Treasure Chest: The Wolf-Rayet Stars

NASA Astrophysics Data System (ADS)

Rosslowe, C. K.; Crowther, P. A.

2015-01-01

The Westerlund 1 Galactic cluster hosts an eclectic mix of coeval massive stars. At a modest distance of 4-5 kpc, it offers a unique opportunity to study the resolved stellar content of a young (~5 Myr) high mass (5.104 M ⊙) star cluster. With the aim of testing single-star evolutionary predictions, and revealing any signatures of binary evolution, we discuss on-going analyses of NTT/SOFI near-IR spectroscopy of Wolf-Rayet stars in Westerlund 1. We find that late WN stars are H-poor compared to their counterparts in the Milky Way field, and nearly all are less luminous than predicted by single-star Geneva isochrones at the age of Westerlund 1.

Turbine airfoil deposition models and their hot corrosion implications

NASA Technical Reports Server (NTRS)

Rosner, D. E.; Nagarajan, R.

1985-01-01

This research project deals with the prediction of single- and multi-component salt(-solution) deposition, flow and oxide dissolution and their effects on the lifetime of turbine blades. Goals include rationalizing and helping to predict corrosion patterns on operational gas turbine (GT) rotor blades and stator vanes, and ultimately providing some of the tools required to design laboratory simulators and future corrosion resistant high-performance engines. Necessary background developments are reviewed. Results and tentative conclusions for single species (Na sub 2 SO sub 4 (1)) condensation, binary salt-solution (Na sub 2 SO sub 4-K sub 2 SO sub 4) condensation, and burner-rig testing of alloy materials are outlined.

Tensile Strength of Carbon Nanotubes Under Realistic Temperature and Strain Rate

NASA Technical Reports Server (NTRS)

Wei, Chen-Yu; Cho, Kyeong-Jae; Srivastava, Deepak; Biegel, Bryan (Technical Monitor)

2002-01-01

Strain rate and temperature dependence of the tensile strength of single-wall carbon nanotubes has been investigated with molecular dynamics simulations. The tensile failure or yield strain is found to be strongly dependent on the temperature and strain rate. A transition state theory based predictive model is developed for the tensile failure of nanotubes. Based on the parameters fitted from high-strain rate and temperature dependent molecular dynamics simulations, the model predicts that a defect free micrometer long single-wall nanotube at 300 K, stretched with a strain rate of 1%/hour, fails at about 9 plus or minus 1% tensile strain. This is in good agreement with recent experimental findings.

Unfolding neutron spectra from simulated response of thermoluminescence dosimeters inside a polyethylene sphere using GRNN neural network

NASA Astrophysics Data System (ADS)

Lotfalizadeh, F.; Faghihi, R.; Bahadorzadeh, B.; Sina, S.

2017-07-01

Neutron spectrometry using a single-sphere containing dosimeters has been developed recently, as an effective replacement for Bonner sphere spectrometry. The aim of this study is unfolding the neutron energy spectra using GRNN artificial neural network, from the response of thermoluminescence dosimeters, TLDs, located inside a polyethylene sphere. The spectrometer was simulated using MCNP5. TLD-600 and TLD-700 dosimeters were simulated at different positions in all directions. Then the GRNN was used for neutron spectra prediction, using the TLDs' readings. Comparison of spectra predicted by the network with the real spectra, show that the single-sphere dosimeter is an effective instrument in unfolding neutron spectra.

The value of the UK Clinical Aptitude Test in predicting pre-clinical performance: a prospective cohort study at Nottingham Medical School.

PubMed

Yates, Janet; James, David

2010-07-28

The UK Clinical Aptitude Test (UKCAT) was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis), and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown.The study objective was to determine whether UKCAT scores predict performance during the first two years of the 5-year undergraduate medical course at Nottingham. We studied a single cohort of students, who entered Nottingham Medical School in October 2007 and had taken the UKCAT. We used linear regression analysis to identify independent predictors of marks for different parts of the 2-year preclinical course. Data were available for 204/260 (78%) of the entry cohort. The UKCAT total score had little predictive value. Quantitative Reasoning was a significant independent predictor of course marks in Theme A ('The Cell'), (p = 0.005), and Verbal Reasoning predicted Theme C ('The Community') (p < 0.001), but otherwise the effects were slight or non-existent. This limited study from a single entry cohort at one medical school suggests that the predictive value of the UKCAT, particularly the total score, is low. Section scores may predict success in specific types of course assessment.The ultimate test of validity will not be available for some years, when current cohorts of students graduate. However, if this test of mental ability does not predict preclinical performance, it is arguably less likely to predict the outcome in the clinical years. Further research from medical schools with different types of curriculum and assessment is needed, with longitudinal studies throughout the course.

Proceedings of the symposium on effects of air pollutants on Mediterranean and temperate forest ecosystems, June 22-27

Treesearch

Paul R. Miller

1980-01-01

These proceedings papers and poster summaries discuss the influence of air pollution on relationships; interactions of producers, consumers, and decomposers under pollutant terrestrial and related aquatic ecosystems. They describe single species-single pollutant stress; and the use of ecological systems models for interpreting and predicting pollutant effects.

AN EXPERT SYSTEM FOR HYDRODYNAMIC MIXING ZONE ANAYLSIS OF CONVENTIONAL AND TOXIC SUBMERGED SINGLE PORT DISCHARGES (CORMIX1)

EPA Science Inventory

U.S. water quality policy includes the concept of a mixing zone, a limited area or volume of water where the initial dilution of a discharge occurs. he Cornell Mixing Zone Expert System (CORMIX1) was developed to predict the dilution and trajectory of a submerged single port disc...

Predicting the cover-up of dead branches using a simple single regressor equation

Treesearch

Christopher M. Oswalt; Wayne K. Clatterbuck; E.C. Burkhardt

2007-01-01

Information on the effects of branch diameter on branch occlusion is necessary for building models capable of forecasting the effect of management decisions on tree or log grade. We investigated the relationship between branch size and subsequent branch occlusion through diameter growth with special attention toward the development of a simple single regressor equation...

Seebeck coefficient of one electron

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

Durrani, Zahid A. K., E-mail: z.durrani@imperial.ac.uk

2014-03-07

The Seebeck coefficient of one electron, driven thermally into a semiconductor single-electron box, is investigated theoretically. With a finite temperature difference ΔT between the source and charging island, a single electron can charge the island in equilibrium, directly generating a Seebeck effect. Seebeck coefficients for small and finite ΔT are calculated and a thermally driven Coulomb staircase is predicted. Single-electron Seebeck oscillations occur with increasing ΔT, as one electron at a time charges the box. A method is proposed for experimental verification of these effects.

Diamond turning of Si and Ge single crystals

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

Blake, P.; Scattergood, R.O.

Single-point diamond turning studies have been completed on Si and Ge crystals. A new process model was developed for diamond turning which is based on a critical depth of cut for plastic flow-to-brittle fracture transitions. This concept, when combined with the actual machining geometry for single-point turning, predicts that {open_quotes}ductile{close_quotes} machining is a combined action of plasticity and fracture. Interrupted cutting experiments also provide a meant to directly measure the critical depth parameter for given machining conditions.

Single-electron thermal noise

NASA Astrophysics Data System (ADS)

Nishiguchi, Katsuhiko; Ono, Yukinori; Fujiwara, Akira

2014-07-01

We report the observation of thermal noise in the motion of single electrons in an ultimately small dynamic random access memory (DRAM). The nanometer-scale transistors that compose the DRAM resolve the thermal noise in single-electron motion. A complete set of fundamental tests conducted on this single-electron thermal noise shows that the noise perfectly follows all the aspects predicted by statistical mechanics, which include the occupation probability, the law of equipartition, a detailed balance, and the law of kT/C. In addition, the counting statistics on the directional motion (i.e., the current) of the single-electron thermal noise indicate that the individual electron motion follows the Poisson process, as it does in shot noise.

Single-electron thermal noise.

PubMed

Nishiguchi, Katsuhiko; Ono, Yukinori; Fujiwara, Akira

2014-07-11

We report the observation of thermal noise in the motion of single electrons in an ultimately small dynamic random access memory (DRAM). The nanometer-scale transistors that compose the DRAM resolve the thermal noise in single-electron motion. A complete set of fundamental tests conducted on this single-electron thermal noise shows that the noise perfectly follows all the aspects predicted by statistical mechanics, which include the occupation probability, the law of equipartition, a detailed balance, and the law of kT/C. In addition, the counting statistics on the directional motion (i.e., the current) of the single-electron thermal noise indicate that the individual electron motion follows the Poisson process, as it does in shot noise.

Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease.

PubMed

Collij, Lyduine E; Heeman, Fiona; Kuijer, Joost P A; Ossenkoppele, Rik; Benedictus, Marije R; Möller, Christiane; Verfaillie, Sander C J; Sanz-Arigita, Ernesto J; van Berckel, Bart N M; van der Flier, Wiesje M; Scheltens, Philip; Barkhof, Frederik; Wink, Alle Meije

2016-12-01

Purpose To investigate whether multivariate pattern recognition analysis of arterial spin labeling (ASL) perfusion maps can be used for classification and single-subject prediction of patients with Alzheimer disease (AD) and mild cognitive impairment (MCI) and subjects with subjective cognitive decline (SCD) after using the W score method to remove confounding effects of sex and age. Materials and Methods Pseudocontinuous 3.0-T ASL images were acquired in 100 patients with probable AD; 60 patients with MCI, of whom 12 remained stable, 12 were converted to a diagnosis of AD, and 36 had no follow-up; 100 subjects with SCD; and 26 healthy control subjects. The AD, MCI, and SCD groups were divided into a sex- and age-matched training set (n = 130) and an independent prediction set (n = 130). Standardized perfusion scores adjusted for age and sex (W scores) were computed per voxel for each participant. Training of a support vector machine classifier was performed with diagnostic status and perfusion maps. Discrimination maps were extracted and used for single-subject classification in the prediction set. Prediction performance was assessed with receiver operating characteristic (ROC) analysis to generate an area under the ROC curve (AUC) and sensitivity and specificity distribution. Results Single-subject diagnosis in the prediction set by using the discrimination maps yielded excellent performance for AD versus SCD (AUC, 0.96; P < .01), good performance for AD versus MCI (AUC, 0.89; P < .01), and poor performance for MCI versus SCD (AUC, 0.63; P = .06). Application of the AD versus SCD discrimination map for prediction of MCI subgroups resulted in good performance for patients with MCI diagnosis converted to AD versus subjects with SCD (AUC, 0.84; P < .01) and fair performance for patients with MCI diagnosis converted to AD versus those with stable MCI (AUC, 0.71; P > .05). Conclusion With automated methods, age- and sex-adjusted ASL perfusion maps can be used to classify and predict diagnosis of AD, conversion of MCI to AD, stable MCI, and SCD with good to excellent accuracy and AUC values. © RSNA, 2016.

Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties.

PubMed

Yue, Zhenyu; Zhang, Wenna; Lu, Yongming; Yang, Qiaoyue; Ding, Qiuying; Xia, Junfeng; Chen, Yan

2015-01-01

Natural products play a significant role in cancer chemotherapy. They are likely to provide many lead structures, which can be used as templates for the construction of novel drugs with enhanced antitumor activity. Traditional research approaches studied structure-activity relationship of natural products and obtained key structural properties, such as chemical bond or group, with the purpose of ascertaining their effect on a single cell line or a single tissue type. Here, for the first time, we develop a machine learning method to comprehensively predict natural products responses against a panel of cancer cell lines based on both the gene expression and the chemical properties of natural products. The results on two datasets, training set and independent test set, show that this proposed method yields significantly better prediction accuracy. In addition, we also demonstrate the predictive power of our proposed method by modeling the cancer cell sensitivity to two natural products, Curcumin and Resveratrol, which indicate that our method can effectively predict the response of cancer cell lines to these two natural products. Taken together, the method will facilitate the identification of natural products as cancer therapies and the development of precision medicine by linking the features of patient genomes to natural product sensitivity.

Functional neuroimaging of psychotherapeutic processes in anxiety and depression: from mechanisms to predictions.

PubMed

Lueken, Ulrike; Hahn, Tim

2016-01-01

The review provides an update of functional neuroimaging studies that identify neural processes underlying psychotherapy and predict outcomes following psychotherapeutic treatment in anxiety and depressive disorders. Following current developments in this field, studies were classified as 'mechanistic' or 'predictor' studies (i.e., informing neurobiological models about putative mechanisms versus aiming to provide predictive information). Mechanistic evidence points toward a dual-process model of psychotherapy in anxiety disorders with abnormally increased limbic activation being decreased, while prefrontal activity is increased. Partly overlapping findings are reported for depression, albeit with a stronger focus on prefrontal activation following treatment. No studies directly comparing neural pathways of psychotherapy between anxiety and depression were detected. Consensus is accumulating for an overarching role of the anterior cingulate cortex in modulating treatment response across disorders. When aiming to quantify clinical utility, the need for single-subject predictions is increasingly recognized and predictions based on machine learning approaches show high translational potential. Present findings encourage the search for predictors providing clinically meaningful information for single patients. However, independent validation as a crucial prerequisite for clinical use is still needed. Identifying nonresponders a priori creates the need for alternative treatment options that can be developed based on an improved understanding of those neural mechanisms underlying effective interventions.

Single Nucleotide Polymorphisms of Stemness Genes Predicted to Regulate RNA Splicing, microRNA and Oncogenic Signaling are Associated with Prostate Cancer Survival.

PubMed

Freedman, Jennifer A; Wang, Yanru; Li, Xuechan; Liu, Hongliang; Moorman, Patricia G; George, Daniel J; Lee, Norman H; Hyslop, Terry; Wei, Qingyi; Patierno, Steven R

2018-05-03

Prostate cancer is a clinically and molecularly heterogeneous disease, with variation in outcomes only partially predicted by grade and stage. Additional tools to distinguish indolent from aggressive disease are needed. Phenotypic characteristics of stemness correlate with poor cancer prognosis. Given this correlation, we identified single nucleotide polymorphisms (SNPs) of stemness-related genes and examined their associations with prostate cancer survival. SNPs within stemness-related genes were analyzed for association with overall survival of prostate cancer in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Significant SNPs predicted to be functional were selected for linkage disequilibrium analysis and combined and stratified analyses. Identified SNPs were evaluated for association with gene expression. SNPs of CD44 (rs9666607), ABCC1 (rs35605 and rs212091) and GDF15 (rs1058587) were associated with prostate cancer survival and predicted to be functional. A role for rs9666607 of CD44 and rs35605 of ABCC1 in RNA splicing regulation, rs212091 of ABCC1 in miRNA binding site activity and rs1058587 of GDF15 in causing an amino acid change was predicted. These SNPs represent potential novel prognostic markers for overall survival of prostate cancer and support a contribution of the stemness pathway to prostate cancer patient outcome.

Forecasting the Water Demand in Chongqing, China Using a Grey Prediction Model and Recommendations for the Sustainable Development of Urban Water Consumption.

PubMed

Wu, Hua'an; Zeng, Bo; Zhou, Meng

2017-11-15

High accuracy in water demand predictions is an important basis for the rational allocation of city water resources and forms the basis for sustainable urban development. The shortage of water resources in Chongqing, the youngest central municipality in Southwest China, has significantly increased with the population growth and rapid economic development. In this paper, a new grey water-forecasting model (GWFM) was built based on the data characteristics of water consumption. The parameter estimation and error checking methods of the GWFM model were investigated. Then, the GWFM model was employed to simulate the water demands of Chongqing from 2009 to 2015 and forecast it in 2016. The simulation and prediction errors of the GWFM model was checked, and the results show the GWFM model exhibits better simulation and prediction precisions than those of the classical Grey Model with one variable and single order equation GM(1,1) for short and the frequently-used Discrete Grey Model with one variable and single order equation, DGM(1,1) for short. Finally, the water demand in Chongqing from 2017 to 2022 was forecasted, and some corresponding control measures and recommendations were provided based on the prediction results to ensure a viable water supply and promote the sustainable development of the Chongqing economy.

Evaluating the Performance of a New Model for Predicting the Growth of Clostridium perfringens in Cooked, Uncured Meat and Poultry Products under Isothermal, Heating, and Dynamically Cooling Conditions.

PubMed

Huang, Lihan

2016-07-01

Clostridium perfringens type A is a significant public health threat and its spores may germinate, outgrow, and multiply during cooling of cooked meats. This study applies a new C. perfringens growth model in the USDA Integrated Pathogen Modeling Program-Dynamic Prediction (IPMP Dynamic Prediction) Dynamic Prediction to predict the growth from spores of C. perfringens in cooked uncured meat and poultry products using isothermal, dynamic heating, and cooling data reported in the literature. The residual errors of predictions (observation-prediction) are analyzed, and the root-mean-square error (RMSE) calculated. For isothermal and heating profiles, each data point in growth curves is compared. The mean residual errors (MRE) of predictions range from -0.40 to 0.02 Log colony forming units (CFU)/g, with a RMSE of approximately 0.6 Log CFU/g. For cooling, the end point predictions are conservative in nature, with an MRE of -1.16 Log CFU/g for single-rate cooling and -0.66 Log CFU/g for dual-rate cooling. The RMSE is between 0.6 and 0.7 Log CFU/g. Compared with other models reported in the literature, this model makes more accurate and fail-safe predictions. For cooling, the percentage for accurate and fail-safe predictions is between 97.6% and 100%. Under criterion 1, the percentage of accurate predictions is 47.5% for single-rate cooling and 66.7% for dual-rate cooling, while the fail-dangerous predictions are between 0% and 2.4%. This study demonstrates that IPMP Dynamic Prediction can be used by food processors and regulatory agencies as a tool to predict the growth of C. perfringens in uncured cooked meats and evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules. This study also demonstrates the need for more accurate data collection during cooling. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Profiles of Verbal Working Memory Growth Predict Speech and Language Development in Children with Cochlear Implants

ERIC Educational Resources Information Center

Kronenberger, William G.; Pisoni, David B.; Harris, Michael S.; Hoen, Helena M.; Xu, Huiping; Miyamoto, Richard T.

2013-01-01

Purpose: Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of…

Predicting bending stiffness of randomly oriented hybrid panels

Treesearch

Laura Moya; William T.Y. Tze; Jerrold E. Winandy

2010-01-01

This study was conducted to develop a simple model to predict the bending modulus of elasticity (MOE) of randomly oriented hybrid panels. The modeling process involved three modules: the behavior of a single layer was computed by applying micromechanics equations, layer properties were adjusted for densification effects, and the entire panel was modeled as a three-...

Predicting Child Abuse Potential: An Empirical Investigation of Two Theoretical Frameworks

ERIC Educational Resources Information Center

Begle, Angela Moreland; Dumas, Jean E.; Hanson, Rochelle F.

2010-01-01

This study investigated two theoretical risk models predicting child maltreatment potential: (a) Belsky's (1993) developmental-ecological model and (b) the cumulative risk model in a sample of 610 caregivers (49% African American, 46% European American; 53% single) with a child between 3 and 6 years old. Results extend the literature by using a…

Executive Functioning Predicts School Readiness and Success: Implications for Assessment and Intervention

ERIC Educational Resources Information Center

Cantin, Rachelle H.; Mann, Trisha D.; Hund, Alycia M.

2012-01-01

In recent years, executive functioning (EF) has received increasing attention from researchers and practitioners focusing on how EF predicts important outcomes such as success at school and in life. For example, EF has been described as the single best predictor of school readiness (Blair & Razza, 2007). Moreover, EF has been implicated in…

Calculation of single chain cellulose elasticity using fully atomistic modeling

Treesearch

Xiawa Wu; Robert J. Moon; Ashlie Martini

2011-01-01

Cellulose nanocrystals, a potential base material for green nanocomposites, are ordered bundles of cellulose chains. The properties of these chains have been studied for many years using atomic-scale modeling. However, model predictions are difficult to interpret because of the significant dependence of predicted properties on model details. The goal of this study is...

Validation of a probabilistic post-fire erosion model

Treesearch

Pete Robichaud; William J. Elliot; Sarah A. Lewis; Mary Ellen Miller

2016-01-01

Post-fire increases of runoff and erosion often occur and land managers need tools to be able to project the increased risk. The Erosion Risk Management Tool (ERMiT) uses the Water Erosion Prediction Project (WEPP) model as the underlying processor. ERMiT predicts the probability of a given amount of hillslope sediment delivery from a single rainfall or...

Predicting the toxicity of metal mixtures

USGS Publications Warehouse

Balistrieri, Laurie S.; Mebane, Christopher A.

2013-01-01

The toxicity of single and multiple metal (Cd, Cu, Pb, and Zn) solutions to trout is predicted using an approach that combines calculations of: (1) solution speciation; (2) competition and accumulation of cations (H, Ca, Mg, Na, Cd, Cu, Pb, and Zn) on low abundance, high affinity and high abundance, low affinity biotic ligand sites; (3) a toxicity function that accounts for accumulation and potency of individual toxicants; and (4) biological response. The approach is evaluated by examining water composition from single metal toxicity tests of trout at 50% mortality, results of theoretical calculations of metal accumulation on fish gills and associated mortality for single, binary, ternary, and quaternary metal solutions, and predictions for a field site impacted by acid rock drainage. These evaluations indicate that toxicity of metal mixtures depends on the relative affinity and potency of toxicants for a given aquatic organism, suites of metals in the mixture, dissolved metal concentrations and ratios, and background solution composition (temperature, pH, and concentrations of major ions and dissolved organic carbon). A composite function that incorporates solution composition, affinity and competition of cations for two types of biotic ligand sites, and potencies of hydrogen and individual metals is proposed as a tool to evaluate potential toxicity of environmental solutions to trout.

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection

PubMed Central

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-01-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices. PMID:25177107

Predicting sugar-sweetened behaviours with theory of planned behaviour constructs: Outcome and process results from the SIPsmartER behavioural intervention.

PubMed

Zoellner, Jamie M; Porter, Kathleen J; Chen, Yvonnes; Hedrick, Valisa E; You, Wen; Hickman, Maja; Estabrooks, Paul A

2017-05-01

Guided by the theory of planned behaviour (TPB) and health literacy concepts, SIPsmartER is a six-month multicomponent intervention effective at improving SSB behaviours. Using SIPsmartER data, this study explores prediction of SSB behavioural intention (BI) and behaviour from TPB constructs using: (1) cross-sectional and prospective models and (2) 11 single-item assessments from interactive voice response (IVR) technology. Quasi-experimental design, including pre- and post-outcome data and repeated-measures process data of 155 intervention participants. Validated multi-item TPB measures, single-item TPB measures, and self-reported SSB behaviours. Hypothesised relationships were investigated using correlation and multiple regression models. TPB constructs explained 32% of the variance cross sectionally and 20% prospectively in BI; and explained 13-20% of variance cross sectionally and 6% prospectively. Single-item scale models were significant, yet explained less variance. All IVR models predicting BI (average 21%, range 6-38%) and behaviour (average 30%, range 6-55%) were significant. Findings are interpreted in the context of other cross-sectional, prospective and experimental TPB health and dietary studies. Findings advance experimental application of the TPB, including understanding constructs at outcome and process time points and applying theory in all intervention development, implementation and evaluation phases.

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

PubMed

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-11-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task

PubMed Central

Miconi, Thomas; Groomes, Laura; Kreiman, Gabriel

2016-01-01

When searching for an object in a scene, how does the brain decide where to look next? Visual search theories suggest the existence of a global “priority map” that integrates bottom-up visual information with top-down, target-specific signals. We propose a mechanistic model of visual search that is consistent with recent neurophysiological evidence, can localize targets in cluttered images, and predicts single-trial behavior in a search task. This model posits that a high-level retinotopic area selective for shape features receives global, target-specific modulation and implements local normalization through divisive inhibition. The normalization step is critical to prevent highly salient bottom-up features from monopolizing attention. The resulting activity pattern constitues a priority map that tracks the correlation between local input and target features. The maximum of this priority map is selected as the locus of attention. The visual input is then spatially enhanced around the selected location, allowing object-selective visual areas to determine whether the target is present at this location. This model can localize objects both in array images and when objects are pasted in natural scenes. The model can also predict single-trial human fixations, including those in error and target-absent trials, in a search task involving complex objects. PMID:26092221

Life prediction and constitutive models for engine hot section anisotropic materials

NASA Technical Reports Server (NTRS)

Swanson, G. A.; Linask, I.; Nissley, D. M.; Norris, P. P.; Meyer, T. G.; Walker, K. P.

1987-01-01

The results are presented of a program designed to develop life prediction and constitutive models for two coated single crystal alloys used in gas turbine airfoils. The two alloys are PWA 1480 and Alloy 185. The two oxidation resistant coatings are PWA 273, an aluminide coating, and PWA 286, an overlay NiCoCrAlY coating. To obtain constitutive and fatigue data, tests were conducted on uncoated and coated specimens loaded in the CH76 100 CH110 , CH76 110 CH110 , CH76 111 CH110 and CH76 123 CH110 crystallographic directions. Two constitutive models are being developed and evaluated for the single crystal materials: a micromechanic model based on crystallographic slip systems, and a macroscopic model which employs anisotropic tensors to model inelastic deformation anisotropy. Based on tests conducted on the overlay coating material, constitutive models for coatings also appear feasible and two initial models were selected. A life prediction approach was proposed for coated single crystal materials, including crack initiation either in the coating or in the substrate. The coating initiated failures dominated in the tests at load levels typical of gas turbine operation. Coating life was related to coating stress/strain history which was determined from specimen data using the constitutive models.