Effects of life satisfaction and psychache on risk for suicidal behaviour: a cross-sectional study based on data from Chinese undergraduates

PubMed Central

You, Zhiqi; Song, Juanjuan; Wu, Caizhi; Qin, Ping; Zhou, Zongkui

2014-01-01

Objectives To examine predictive power of psychache and life satisfaction on risks for suicidal ideation and suicide attempt among young people. Design A cross-sectional study. Setting Data were collected from an online survey in Wuhan, China. Participants 5988 university students from six universities were selected by a stratified cluster sampling method. Primary and secondary outcome measures Suicidal ideation and suicide attempt at some point of the students’ lifetime were the outcomes of interest. Results Students with suicidal ideation or attempted suicide reported a lower level of life satisfaction and high degree of psychache than counterparts without suicidal ideation or attempt. Regression analyses indicated that life satisfaction and psychache were significantly associated with the risk of suicidal ideation and the risk of suicidal attempt. Though psychache showed a relatively stronger predictive power than life satisfaction, the effect of the two factors remained significant when they were individually adjusted for personal demographic characteristics. However, when the two factors were included in the model simultaneously to adjust for each other, psychache could fully explain the association between life satisfaction and suicidal attempt. Life satisfaction remained to contribute unique variance in the statistical prediction of suicidal ideation. Conclusions Psychache and life satisfaction both have a significant predictive power on risk for suicidal behaviour, and life satisfaction could relieve the predictive power of psychache when suicidal behaviour is just starting. Shneidman's theory that psychache is the pre-eminent psychological cause of suicide is perhaps applicable only to a more serious form of suicidal behaviour. PMID:24657883

Intelligent Prediction of Fan Rotation Stall in Power Plants Based on Pressure Sensor Data Measured In-Situ

PubMed Central

Xu, Xiaogang; Wang, Songling; Liu, Jinlian; Liu, Xinyu

2014-01-01

Blower and exhaust fans consume over 30% of electricity in a thermal power plant, and faults of these fans due to rotation stalls are one of the most frequent reasons for power plant outage failures. To accurately predict the occurrence of fan rotation stalls, we propose a support vector regression machine (SVRM) model that predicts the fan internal pressures during operation, leaving ample time for rotation stall detection. We train the SVRM model using experimental data samples, and perform pressure data prediction using the trained SVRM model. To prove the feasibility of using the SVRM model for rotation stall prediction, we further process the predicted pressure data via wavelet-transform-based stall detection. By comparison of the detection results from the predicted and measured pressure data, we demonstrate that the SVRM model can accurately predict the fan pressure and guarantee reliable stall detection with a time advance of up to 0.0625 s. This superior pressure data prediction capability leaves significant time for effective control and prevention of fan rotation stall faults. This model has great potential for use in intelligent fan systems with stall prevention capability, which will ensure safe operation and improve the energy efficiency of power plants. PMID:24854057

Effect of barnacle fouling on ship resistance and powering.

PubMed

Demirel, Yigit Kemal; Uzun, Dogancan; Zhang, Yansheng; Fang, Ho-Chun; Day, Alexander H; Turan, Osman

2017-11-01

Predictions of added resistance and the effective power of ships were made for varying barnacle fouling conditions. A series of towing tests was carried out using flat plates covered with artificial barnacles. The tests were designed to allow the examination of the effects of barnacle height and percentage coverage on the resistance and effective power of ships. The drag coefficients and roughness function values were evaluated for the flat plates. The roughness effects of the fouling conditions on the ships' frictional resistances were predicted. Added resistance diagrams were then plotted using these predictions, and powering penalties for these ships were calculated using the diagrams generated. The results indicate that the effect of barnacle size is significant, since a 10% coverage of barnacles each 5 mm in height caused a similar level of added power requirements to a 50% coverage of barnacles each 1.25 mm in height.

Methods of predicting aggregate voids.

DOT National Transportation Integrated Search

2013-03-01

Percent voids in combined aggregates vary significantly. Simplified methods of predicting aggregate : voids were studied to determine the feasibility of a range of gradations using aggregates available in Kansas. : The 0.45 Power Curve Void Predictio...

Electronic stopping powers for heavy ions in SiC and SiO{sub 2}

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

Jin, K.; Xue, H.; Zhang, Y., E-mail: Zhangy1@ornl.gov

2014-01-28

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO{sub 2}, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15 MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

Electronic Stopping Powers For Heavy Ions In SiC And SiO2

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

Jin, Ke; Zhang, Y.; Zhu, Zihua

2014-01-24

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO2, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

PubMed Central

Chen, Qihong; Long, Rong; Quan, Shuhai

2014-01-01

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

Wind Power Curve Modeling in Simple and Complex Terrain

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

Bulaevskaya, V.; Wharton, S.; Irons, Z.

2015-02-09

Our previous work on wind power curve modeling using statistical models focused on a location with a moderately complex terrain in the Altamont Pass region in northern California (CA). The work described here is the follow-up to that work, but at a location with a simple terrain in northern Oklahoma (OK). The goal of the present analysis was to determine the gain in predictive ability afforded by adding information beyond the hub-height wind speed, such as wind speeds at other heights, as well as other atmospheric variables, to the power prediction model at this new location and compare the resultsmore » to those obtained at the CA site in the previous study. While we reach some of the same conclusions at both sites, many results reported for the CA site do not hold at the OK site. In particular, using the entire vertical profile of wind speeds improves the accuracy of wind power prediction relative to using the hub-height wind speed alone at both sites. However, in contrast to the CA site, the rotor equivalent wind speed (REWS) performs almost as well as the entire profile at the OK site. Another difference is that at the CA site, adding wind veer as a predictor significantly improved the power prediction accuracy. The same was true for that site when air density was added to the model separately instead of using the standard air density adjustment. At the OK site, these additional variables result in no significant benefit for the prediction accuracy.« less

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

Hydrodynamic effects of kinetic power extraction by in-stream tidal turbines

NASA Astrophysics Data System (ADS)

Polagye, Brian L.

The hydrodynamic effects of extracting kinetic power from tidal streams presents unique challenges to the development of in-stream tidal power. In-stream tidal turbines superficially resemble wind turbines and extract kinetic power from the ebb and flood of strong tidal currents. Extraction increases the resistance to flow, leading to changes in tidal range, transport, mixing, and the kinetic resource itself. These far-field changes have environmental, social, and economic implications that must be understood to develop the in-stream resource. This dissertation describes the development of a one-dimensional numerical channel model and its application to the study of these effects. The model is applied to determine the roles played by site geometry, network topology, tidal regime, and device dynamics. A comparison is also made between theoretical and modeled predictions for the maximum amount of power which could be extracted from a tidal energy site. The model is extended to a simulation of kinetic power extraction from Puget Sound, Washington. In general, extracting tidal energy will have a number of far-field effects, in proportion to the level of power extraction. At the theoretical limit, these effects can be very significant (e.g., 50% reduction in transport), but are predicted to be immeasurably small for pilot-scale projects. Depending on the specifics of the site, far-field effects may either augment or reduce the existing tidal regime. Changes to the tide, in particular, have significant spatial variability. Since tidal streams are generally subcritical, effects are felt throughout the estuary, not just at the site of extraction. The one dimensional numerical modeling is supported by a robust theory for predicting the performance characteristics of in-stream devices. The far-field effects of tidal power depend on the total power dissipated by turbines, rather than the power extracted. When the low-speed wake downstream of a turbine mixes with the free-stream, power is lost, such that the total power dissipated by the turbine is significantly greater than the power extracted. This dissertation concludes with a framework for three-dimensional numerical modeling of near-field extraction effects.

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

Moslehi, Salim; Reddy, T. Agami; Katipamula, Srinivas

This research was undertaken to evaluate different inverse models for predicting power output of solar photovoltaic (PV) systems under different practical scenarios. In particular, we have investigated whether PV power output prediction accuracy can be improved if module/cell temperature was measured in addition to climatic variables, and also the extent to which prediction accuracy degrades if solar irradiation is not measured on the plane of array but only on a horizontal surface. We have also investigated the significance of different independent or regressor variables, such as wind velocity and incident angle modifier in predicting PV power output and cell temperature.more » The inverse regression model forms have been evaluated both in terms of their goodness-of-fit, and their accuracy and robustness in terms of their predictive performance. Given the accuracy of the measurements, expected CV-RMSE of hourly power output prediction over the year varies between 3.2% and 8.6% when only climatic data are used. Depending on what type of measured climatic and PV performance data is available, different scenarios have been identified and the corresponding appropriate modeling pathways have been proposed. The corresponding models are to be implemented on a controller platform for optimum operational planning of microgrids and integrated energy systems.« less

Analysis of significant factors for dengue fever incidence prediction.

PubMed

Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

2016-04-16

Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting models, as confirmed by AIC, BIC, and MAPE.

Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics.

PubMed

Ngo, L; Ho, H; Hunter, P; Quinn, K; Thomson, A; Pearson, G

2016-02-01

Post-mortem measurements (cold weight, grade and external carcass linear dimensions) as well as live animal data (age, breed, sex) were used to predict ovine primal and retail cut weights for 792 lamb carcases. Significant levels of variance could be explained using these predictors. The predictive power of those measurements on primal and retail cut weights was studied by using the results from principal component analysis and the absolute value of the t-statistics of the linear regression model. High prediction accuracy for primal cut weight was achieved (adjusted R(2) up to 0.95), as well as moderate accuracy for key retail cut weight: tenderloins (adj-R(2)=0.60), loin (adj-R(2)=0.62), French rack (adj-R(2)=0.76) and rump (adj-R(2)=0.75). The carcass cold weight had the best predictive power, with the accuracy increasing by around 10% after including the next three most significant variables. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effect of the equivalent refractive index on intraocular lens power prediction with ray tracing after myopic laser in situ keratomileusis.

PubMed

Canovas, Carmen; van der Mooren, Marrie; Rosén, Robert; Piers, Patricia A; Wang, Li; Koch, Douglas D; Artal, Pablo

2015-05-01

To determine the impact of the equivalent refractive index (ERI) on intraocular lens (IOL) power prediction for eyes with previous myopic laser in situ keratomileusis (LASIK) using custom ray tracing. AMO B.V., Groningen, the Netherlands, and the Department of Ophthalmology, Baylor College of Medicine, Houston, Texas, USA. Retrospective data analysis. The ERI was calculated individually from the post-LASIK total corneal power. Two methods to account for the posterior corneal surface were tested; that is, calculation from pre-LASIK data or from post-LASIK data only. Four IOL power predictions were generated using a computer-based ray-tracing technique, including individual ERI results from both calculation methods, a mean ERI over the whole population, and the ERI for normal patients. For each patient, IOL power results calculated from the four predictions as well as those obtained with the Haigis-L were compared with the optimum IOL power calculated after cataract surgery. The study evaluated 25 patients. The mean and range of ERI values determined using post-LASIK data were similar to those determined from pre-LASIK data. Introducing individual or an average ERI in the ray-tracing IOL power calculation procedure resulted in mean IOL power errors that were not significantly different from zero. The ray-tracing procedure that includes an average ERI gave a greater percentage of eyes with an IOL power prediction error within ±0.5 diopter than the Haigis-L (84% versus 52%). For IOL power determination in post-LASIK patients, custom ray tracing including a modified ERI was an accurate procedure that exceeded the current standards for normal eyes. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Early Changes in QRS Frequency Following Cardiac Resynchronization Predict Hemodynamic Response in Left Bundle Branch Block Patients.

PubMed

Niebauer, Mark J; Rickard, John; Tchou, Patrick J; Varma, Niraj

2016-05-01

QRS characteristics are the cornerstone of patient selection in cardiac resynchronization therapy (CRT) and the presence of left bundle branch block (LBBB) and baseline QRS ≥150 milliseconds portends a good outcome. We previously showed that baseline QRS frequency analysis adds predictive value to LBBB alone and have hypothesized that a change in frequency characteristics following CRT may produce additional predictive value. We examined the QRS frequency characteristics of 182 LBBB patients before and soon after CRT. Patients were assigned to responder and nonresponder groups. Responders were defined by a decrease in left ventricular end-systolic volume (LVESV) ≥15% following CRT. We analyzed the QRS in ECG leads I, AVF, and V3 before and soon after CRT using the discrete Fourier transform algorithm. The percentage of total QRS power within discrete frequency intervals before and after CRT was calculated. The reduction in lead V3 power <10 Hz was the best indicator of response. Baseline QRS width was similar between the responders and nonresponders (162.2 ± 17.2 milliseconds vs. 158 ± 22.1 milliseconds, respectively; P = 0.180). Responders exhibited a greater reduction in QRS power <10 Hz (-17.0 ± 11.9% vs. -6.6 ± 12.5%; P < 0.001) and a significant AUC (0.743; P < 0.001). A ≥8% decline in QRS power <10 Hz produced the best predictive values (PPV = 84%, NPV = 59%). Importantly, when patients with baseline QRS <150 milliseconds were compared, the AUC improved (0.892, P < 0.001). Successful CRT produces a significant reduction in QRS power below 10 Hz, particularly when baseline QRS <150 milliseconds. These results indicate that QRS frequency changes after CRT provide additional predictive value to QRS alone. © 2016 Wiley Periodicals, Inc.

Prediction and measurement of the electromagnetic environment of high-power medium-wave and short-wave broadcast antennas in far field.

PubMed

Tang, Zhanghong; Wang, Qun; Ji, Zhijiang; Shi, Meiwu; Hou, Guoyan; Tan, Danjun; Wang, Pengqi; Qiu, Xianbo

2014-12-01

With the increasing city size, high-power electromagnetic radiation devices such as high-power medium-wave (MW) and short-wave (SW) antennas have been inevitably getting closer and closer to buildings, which resulted in the pollution of indoor electromagnetic radiation becoming worsened. To avoid such radiation exceeding the exposure limits by national standards, it is necessary to predict and survey the electromagnetic radiation by MW and SW antennas before constructing the buildings. In this paper, a modified prediction method for the far-field electromagnetic radiation is proposed and successfully applied to predict the electromagnetic environment of an area close to a group of typical high-power MW and SW wave antennas. Different from currently used simplified prediction method defined in the Radiation Protection Management Guidelines (H J/T 10. 3-1996), the new method in this article makes use of more information such as antennas' patterns to predict the electromagnetic environment. Therefore, it improves the prediction accuracy significantly by the new feature of resolution at different directions. At the end of this article, a comparison between the prediction data and the measured results is given to demonstrate the effectiveness of the proposed new method. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A summary of wind power prediction methods

NASA Astrophysics Data System (ADS)

Wang, Yuqi

2018-06-01

The deterministic prediction of wind power, the probability prediction and the prediction of wind power ramp events are introduced in this paper. Deterministic prediction includes the prediction of statistical learning based on histor ical data and the prediction of physical models based on NWP data. Due to the great impact of wind power ramp events on the power system, this paper also introduces the prediction of wind power ramp events. At last, the evaluation indicators of all kinds of prediction are given. The prediction of wind power can be a good solution to the adverse effects of wind power on the power system due to the abrupt, intermittent and undulation of wind power.

Power output measurement during treadmill cycling.

PubMed

Coleman, D A; Wiles, J D; Davison, R C R; Smith, M F; Swaine, I L

2007-06-01

The study aim was to consider the use of a motorised treadmill as a cycling ergometry system by assessing predicted and recorded power output values during treadmill cycling. Fourteen male cyclists completed repeated cycling trials on a motorised treadmill whilst riding their own bicycle fitted with a mobile ergometer. The speed, gradient and loading via an external pulley system were recorded during 20-s constant speed trials and used to estimate power output with an assumption about the contribution of rolling resistance. These values were then compared with mobile ergometer measurements. To assess the reliability of measured power output values, four repeated trials were conducted on each cyclist. During level cycling, the recorded power output was 257.2 +/- 99.3 W compared to the predicted power output of 258.2 +/- 99.9 W (p > 0.05). For graded cycling, there was no significant difference between measured and predicted power output, 268.8 +/- 109.8 W vs. 270.1 +/- 111.7 W, p > 0.05, SEE 1.2 %. The coefficient of variation for mobile ergometer power output measurements during repeated trials ranged from 1.5 % (95 % CI 1.2 - 2.0 %) to 1.8 % (95 % CI 1.5 - 2.4 %). These results indicate that treadmill cycling can be used as an ergometry system to assess power output in cyclists with acceptable accuracy.

Increased prognostic accuracy of TBI when a brain electrical activity biomarker is added to loss of consciousness (LOC).

PubMed

Hack, Dallas; Huff, J Stephen; Curley, Kenneth; Naunheim, Roseanne; Ghosh Dastidar, Samanwoy; Prichep, Leslie S

2017-07-01

Extremely high accuracy for predicting CT+ traumatic brain injury (TBI) using a quantitative EEG (QEEG) based multivariate classification algorithm was demonstrated in an independent validation trial, in Emergency Department (ED) patients, using an easy to use handheld device. This study compares the predictive power using that algorithm (which includes LOC and amnesia), to the predictive power of LOC alone or LOC plus traumatic amnesia. ED patients 18-85years presenting within 72h of closed head injury, with GSC 12-15, were study candidates. 680 patients with known absence or presence of LOC were enrolled (145 CT+ and 535 CT- patients). 5-10min of eyes closed EEG was acquired using the Ahead 300 handheld device, from frontal and frontotemporal regions. The same classification algorithm methodology was used for both the EEG based and the LOC based algorithms. Predictive power was evaluated using area under the ROC curve (AUC) and odds ratios. The QEEG based classification algorithm demonstrated significant improvement in predictive power compared with LOC alone, both in improved AUC (83% improvement) and odds ratio (increase from 4.65 to 16.22). Adding RGA and/or PTA to LOC was not improved over LOC alone. Rapid triage of TBI relies on strong initial predictors. Addition of an electrophysiological based marker was shown to outperform report of LOC alone or LOC plus amnesia, in determining risk of an intracranial bleed. In addition, ease of use at point-of-care, non-invasive, and rapid result using such technology suggests significant value added to standard clinical prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

Modelling and Prediction of Spark-ignition Engine Power Performance Using Incremental Least Squares Support Vector Machines

NASA Astrophysics Data System (ADS)

Wong, Pak-kin; Vong, Chi-man; Wong, Hang-cheong; Li, Ke

2010-05-01

Modern automotive spark-ignition (SI) power performance usually refers to output power and torque, and they are significantly affected by the setup of control parameters in the engine management system (EMS). EMS calibration is done empirically through tests on the dynamometer (dyno) because no exact mathematical engine model is yet available. With an emerging nonlinear function estimation technique of Least squares support vector machines (LS-SVM), the approximate power performance model of a SI engine can be determined by training the sample data acquired from the dyno. A novel incremental algorithm based on typical LS-SVM is also proposed in this paper, so the power performance models built from the incremental LS-SVM can be updated whenever new training data arrives. With updating the models, the model accuracies can be continuously increased. The predicted results using the estimated models from the incremental LS-SVM are good agreement with the actual test results and with the almost same average accuracy of retraining the models from scratch, but the incremental algorithm can significantly shorten the model construction time when new training data arrives.

High Pressure Regenerative Turbine Engine: 21st Century Propulsion

NASA Technical Reports Server (NTRS)

Lear, W. E.; Laganelli, A. L.; Senick, Paul (Technical Monitor)

2001-01-01

A novel semi-closed cycle gas turbine engine was demonstrated and was found to meet the program goals. The proof-of-principle test of the High Pressure Regenerative Turbine Engine produced data that agreed well with models, enabling more confidence in designing future prototypes based on this concept. Emission levels were significantly reduced as predicted as a natural attribute of this power cycle. Engine testing over a portion of the operating range allowed verification of predicted power increases compared to the baseline.

Significant SNPs have limited prediction ability for thyroid cancer

PubMed Central

Guo, Shicheng; Wang, Yu-Long; Li, Yi; Jin, Li; Xiong, Momiao; Ji, Qing-Hai; Wang, Jiucun

2014-01-01

Recently, five thyroid cancer significantly associated genetic variants (rs965513, rs944289, rs116909374, rs966423, and rs2439302) have been discovered and validated in two independent GWAS and numerous case–control studies, which were conducted in different populations. We genotyped the above five single nucleotide polymorphisms (SNPs) in Han Chinese populations and performed thyroid cancer-risk predictions with nine machine learning methods. We found that four SNPs were significantly associated with thyroid cancer in Han Chinese population, while no polymorphism was observed for rs116909374. Small familial relative risks (1.02–1.05) and limited power to predict thyroid cancer (AUCs: 0.54–0.60) indicate limited clinical potential. Four significant SNPs have limited prediction ability for thyroid cancer. PMID:24591304

Calibration power of the Braden scale in predicting pressure ulcer development.

PubMed

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

2016-11-02

Calibration is the degree of correspondence between the estimated probability produced by a model and the actual observed probability. The aim of this study was to investigate the calibration power of the Braden scale in predicting pressure ulcer development (PU). A retrospective analysis was performed among consecutive patients in 2013. The patients were separated into training a group and a validation group. The predicted incidence was calculated using a logistic regression model in the training group and the Hosmer-Lemeshow test was used for assessing the goodness of fit. In the validation cohort, the observed and the predicted incidence were compared by the Chi-square (χ 2 ) goodness of fit test for calibration power. We included 2585 patients in the study, of these 78 patients (3.0%) developed a PU. Between the training and validation groups the patient characteristics were non-significant (p>0.05). In the training group, the logistic regression model for predicting pressure ulcer was Logit(P) = -0.433*Braden score+2.616. The Hosmer-Lemeshow test showed no goodness fit (χ 2 =13.472; p=0.019). In the validation group, the predicted pressure ulcer incidence also did not fit well with the observed incidence (χ 2 =42.154, p=0.000 by Braden scores; and χ 2 =17.223, p=0.001 by Braden scale risk classification). The Braden scale has low calibration power in predicting PU formation.

The spectrum of the geoid from altimeter data

NASA Technical Reports Server (NTRS)

Wagner, C. A.

1977-01-01

A variety of sources of detailed information has been analyzed to arrive at a geoid power spectrum from global altimeter data. Using the equivalent of only two revolutions of data (mostly from GEOS-3) from all the major oceans, the high frequency geoid power (rms) is estimated (most simply) to be 80.7 n to the minus 1.47th power meters, where n is in cycles/global revolutions. This law is valid for all frequencies above 19 cycles but includes sea state. The (simple) law has more power than predicted by Kaula's rule for the geopotential. However, the data shows significantly less power for frequencies below 100 cycles. A closer approximation to the altimetry accumulates 2.18m (rss) for all frequencies higher than 19 cycles/rev. (including sea state), somewhat less power than predicted by the rule. The data permits up to 1.25 (rms) non-gravitational departures from the high frequency marine geoid.

Multisensory stimuli elicit altered oscillatory brain responses at gamma frequencies in patients with schizophrenia

PubMed Central

Stone, David B.; Coffman, Brian A.; Bustillo, Juan R.; Aine, Cheryl J.; Stephen, Julia M.

2014-01-01

Deficits in auditory and visual unisensory responses are well documented in patients with schizophrenia; however, potential abnormalities elicited from multisensory audio-visual stimuli are less understood. Further, schizophrenia patients have shown abnormal patterns in task-related and task-independent oscillatory brain activity, particularly in the gamma frequency band. We examined oscillatory responses to basic unisensory and multisensory stimuli in schizophrenia patients (N = 46) and healthy controls (N = 57) using magnetoencephalography (MEG). Time-frequency decomposition was performed to determine regions of significant changes in gamma band power by group in response to unisensory and multisensory stimuli relative to baseline levels. Results showed significant behavioral differences between groups in response to unisensory and multisensory stimuli. In addition, time-frequency analysis revealed significant decreases and increases in gamma-band power in schizophrenia patients relative to healthy controls, which emerged both early and late over both sensory and frontal regions in response to unisensory and multisensory stimuli. Unisensory gamma-band power predicted multisensory gamma-band power differently by group. Furthermore, gamma-band power in these regions predicted performance in select measures of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) test battery differently by group. These results reveal a unique pattern of task-related gamma-band power in schizophrenia patients relative to controls that may indicate reduced inhibition in combination with impaired oscillatory mechanisms in patients with schizophrenia. PMID:25414652

Predicting Spouses Perceptions of Their Parenting Alliance

ERIC Educational Resources Information Center

Hughes, Farrah M.; Gordon, Kristina Coop; Gaertner, Lowell

2004-01-01

This study used marital and individual-level variables to predict spouses perceived parenting alliance. One hundred married couples completed measures of parenting alliance, marital consensus, marital power, and depression. Analyses revealed that marital consensus was a significant predictor of parenting alliance for both parents, and that…

Maternal role development: the impact of maternal distress and social support following childbirth.

PubMed

Emmanuel, Elizabeth N; Creedy, Debra K; St John, Winsome; Brown, Claire

2011-04-01

to explore the relationship between maternal role development (MRD), maternal distress (MD) and social support following childbirth. prospective longitudinal survey. three public hospital maternity units in Brisbane, Australia. 630 pregnant women were invited to participate in the study, with a 77% (n=473) completion rate. to measure MRD, the Prenatal Maternal Expectation Scale was used at 36 weeks of pregnancy, and the revised What Being the Parent of a New Baby is Like (with subscales of evaluation, centrality and life change) was used at six and 12 weeks post partum. At all three data collection points, the Edinburgh Postnatal Depression Scale was used to measure MD, and the Maternal Social Support Scale was used to measure social support. at 36 weeks of gestation, optimal scaling for MRD produced a parsimonious model with MD providing 39% of predictive power. At six weeks post partum, similar models predicting MRD were found (evaluation: r(2)=0.14, MD providing 64% of predictive power; centrality: r(2)=0.07, MD providing 11% of predictive power; life change: r(2)=0.26, MD providing 59% of predictive power). At 12 weeks post partum, MD was a predictor for evaluation (r(2)=0.11) and life change (r(2)=0.26, 54% of predictive power). there is a statistically significant but moderate correlation between MRD and MD. The transition to motherhood can be stressful, but may be facilitated by appropriate acknowledgement and support with an emphasis on MRD. Copyright © 2009 Elsevier Ltd. All rights reserved.

Using trading strategies to detect phase transitions in financial markets.

PubMed

Forró, Z; Woodard, R; Sornette, D

2015-04-01

We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.

Using trading strategies to detect phase transitions in financial markets

NASA Astrophysics Data System (ADS)

Forró, Z.; Woodard, R.; Sornette, D.

2015-04-01

We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.

The relationship between blood pressure and the structures of Pender's health promotion model in rural hypertensive patients.

PubMed

Kamran, Aziz; Azadbakht, Leila; Sharifirad, Gholamreza; Mahaki, Behzad; Mohebi, Siamak

2015-01-01

Perception is the most important predictor of behavior and there is a strong relation and correlation between behavior and believes. Thus, to improve self-care behaviors of patients, it is required to fully understand their perceptions about behavior. This paper aimed to assess the prediction power of health promotion model of systolic blood pressure (SBP) as the result of self-care behavior in rural hypertensive. This cross-sectional study has been carried out through random multistage sampling on 671 rural patients under the coverage of health center of Ardebil city in 2013. Data were collected through reliable and valid questionnaire based on the health promotion model in eight sectors. For data analysis, Pearson correlation statistical tests, multivariate linear regression, ANOVA and independent t-test were used and for confirmatory factor analysis, SPSS 18 and AMOS 18 (SPSS Inc., Chicago, IL, USA) were used. The results showed significant negative correlation between self-efficacy, perceived benefits, situational influences, affects related to behavior and commitment to action structures with SBP and showed a positive significant correlation between perceived barriers and SBP. Furthermore, age and body mass had direct significant relation with SBP. The age of patients showed inverse significant correlation with self-efficacy, perceived benefits, affects related to behavior, interpersonal influences and commitment and showed a direct significant correlation with perceived barriers, means that by increase of age, the perceived barriers also increased. The structures of health promotion model have in overall the prediction power of 71.4% of SBP changes. The diet perceptions of patients, the same as health promotion model, has good predictive power of SBP, especially the structures of perceived benefits and self-efficacy have inverse meaningful relation with systole blood pressure and predicted a higher percentage of this variable.

Does NASA SMAP Improve the Accuracy of Power Outage Models?

NASA Astrophysics Data System (ADS)

Quiring, S. M.; McRoberts, D. B.; Toy, B.; Alvarado, B.

2016-12-01

Electric power utilities make critical decisions in the days prior to hurricane landfall that are primarily based on the estimated impact to their service area. For example, utilities must determine how many repair crews to request from other utilities, the amount of material and equipment they will need to make repairs, and where in their geographically expansive service area to station crews and materials. Accurate forecasts of the impact of an approaching hurricane within their service area are critical for utilities in balancing the costs and benefits of different levels of resources. The Hurricane Outage Prediction Model (HOPM) are a family of statistical models that utilize predictions of tropical cyclone windspeed and duration of strong winds, along with power system and environmental variables (e.g., soil moisture, long-term precipitation), to forecast the number and location of power outages. This project assesses whether using NASA SMAP soil moisture improves the accuracy of power outage forecasts as compared to using model-derived soil moisture from NLDAS-2. A sensitivity analysis is employed since there have been very few tropical cyclones making landfall in the United States since SMAP was launched. The HOPM is used to predict power outages for 13 historical tropical cyclones and the model is run using twice, once with NLDAS soil moisture and once with SMAP soil moisture. Our results demonstrate that using SMAP soil moisture can have a significant impact on power outage predictions. SMAP has the potential to enhance the accuracy of power outage forecasts. Improved outage forecasts reduce the duration of power outages which reduces economic losses and accelerates recovery.

Joint probability of statistical success of multiple phase III trials.

PubMed

Zhang, Jianliang; Zhang, Jenny J

2013-01-01

In drug development, after completion of phase II proof-of-concept trials, the sponsor needs to make a go/no-go decision to start expensive phase III trials. The probability of statistical success (PoSS) of the phase III trials based on data from earlier studies is an important factor in that decision-making process. Instead of statistical power, the predictive power of a phase III trial, which takes into account the uncertainty in the estimation of treatment effect from earlier studies, has been proposed to evaluate the PoSS of a single trial. However, regulatory authorities generally require statistical significance in two (or more) trials for marketing licensure. We show that the predictive statistics of two future trials are statistically correlated through use of the common observed data from earlier studies. Thus, the joint predictive power should not be evaluated as a simplistic product of the predictive powers of the individual trials. We develop the relevant formulae for the appropriate evaluation of the joint predictive power and provide numerical examples. Our methodology is further extended to the more complex phase III development scenario comprising more than two (K > 2) trials, that is, the evaluation of the PoSS of at least k₀ (k₀≤ K) trials from a program of K total trials. Copyright © 2013 John Wiley & Sons, Ltd.

High plasma omentin predicts cardiovascular events independently from the presence and extent of angiographically determined atherosclerosis.

PubMed

Saely, Christoph H; Leiherer, Andreas; Muendlein, Axel; Vonbank, Alexander; Rein, Philipp; Geiger, Kathrin; Malin, Cornelia; Drexel, Heinz

2016-01-01

No prospective data on the power of the adipocytokine omentin to predict cardiovascular events are available. We aimed at investigating i) the association of plasma omentin with cardiometabolic risk markers, ii) its association with angiographically determined coronary atherosclerosis, and iii) its power to predict cardiovascular events. We measured plasma omentin in 295 patients undergoing coronary angiography for the evaluation of established or suspected stable coronary artery disease (CAD), of whom 161 had significant CAD with coronary artery stenoses ≥50% and 134 did not have significant CAD. Over 3.5 years, 17.6% of our patients suffered cardiovascular events, corresponding to an annual event rate of 5.0%. At baseline, plasma omentin was not significantly associated with metabolic syndrome stigmata and did not differ significantly between patients with and subjects without significant CAD (17.2 ± 13.6 ng/ml vs. 17.5 ± 15.1 ng/ml; p = 0.783). Prospectively, however, cardiovascular event risk significantly increased over tertiles of omentin (12.1%, 13.8%, and 29.5%, for tertiles 1 through 3; ptrend = 0.003), and omentin as a continuous variable significantly predicted cardiovascular events after adjustment for age, gender, BMI, diabetes, hypertension, LDL cholesterol, HDL cholesterol, and smoking (standardized adjusted hazard ratio (HR) 1.41 [95% CI 1.16-1.72]; p < 0.001), as well as after additional adjustment for the presence and extent of significant CAD at baseline (HR 1.59 [95% CI 1.29-1.97, p < 0.001). From this first prospective evaluation of the cardiovascular risk associated with omentin we conclude that elevated plasma omentin significantly predicts cardiovascular events independently from the presence and extent of angiographically determined baseline CAD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

EEG gamma synchronization is associated with response to paroxetine treatment.

PubMed

Arikan, Mehmet Kemal; Metin, Baris; Tarhan, Nevzat

2018-08-01

Resistance to medication is a significant problem in psychiatric practice, and effective methods for predicting response are needed to optimize treatment efficacy and limit morbidity. Gamma oscillations are considered as an index of the brain's general cognitive activity; however, the role of gamma oscillations in disease has not been studied sufficiently. This study aimed to determine if gamma power during rest can be used to predict response to anti-depressant medication treatment. Hamilton Depression Rating Scale (HDRS) score and resting state gamma power was measured in 18 medication-free patients during an episode of major depression. After 6 weeks of paroxetine monotherapy HDRS was administered again. Baseline gamma power at frontal, central and temporal electrodes before treatment was significantly related to post-treatment change in HDRS scores. The results indicate that gamma oscillations could be considered a marker of response to paroxetine treatment in patients with major depression. Copyright © 2018. Published by Elsevier B.V.

Electric Vehicles Charging Scheduling Strategy Considering the Uncertainty of Photovoltaic Output

NASA Astrophysics Data System (ADS)

Wei, Xiangxiang; Su, Su; Yue, Yunli; Wang, Wei; He, Luobin; Li, Hao; Ota, Yutaka

2017-05-01

The rapid development of electric vehicles and distributed generation bring new challenges to security and economic operation of the power system, so the collaborative research of the EVs and the distributed generation have important significance in distribution network. Under this background, an EVs charging scheduling strategy considering the uncertainty of photovoltaic(PV) output is proposed. The characteristics of EVs charging are analysed first. A PV output prediction method is proposed with a PV database then. On this basis, an EVs charging scheduling strategy is proposed with the goal to satisfy EVs users’ charging willingness and decrease the power loss in distribution network. The case study proves that the proposed PV output prediction method can predict the PV output accurately and the EVs charging scheduling strategy can reduce the power loss and stabilize the fluctuation of the load in distributed network.

Active optimal control strategies for increasing the efficiency of photovoltaic cells

NASA Astrophysics Data System (ADS)

Aljoaba, Sharif Zidan Ahmad

Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module edsigns toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter.

Wind farms production: Control and prediction

NASA Astrophysics Data System (ADS)

El-Fouly, Tarek Hussein Mostafa

Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect and the time delay of the incident wind speed of the different turbines on the farm, and to simulate the fluctuation in the generated power more accurately and more closer to real-time operation. Recently, wind farms with considerable output power ratings have been installed. Their integrating into the utility grid will substantially affect the electricity markets. This thesis investigates the possible impact of wind power variability, wind farm control strategy, wind energy penetration level, wind farm location, and wind power prediction accuracy on the total generation costs and close to real time electricity market prices. These issues are addressed by developing a single auction market model for determining the real-time electricity market prices.

The wind power prediction research based on mind evolutionary algorithm

NASA Astrophysics Data System (ADS)

Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

2018-04-01

When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

Predictability of depression severity based on posterior alpha oscillations.

PubMed

Jiang, H; Popov, T; Jylänki, P; Bi, K; Yao, Z; Lu, Q; Jensen, O; van Gerven, M A J

2016-04-01

We aimed to integrate neural data and an advanced machine learning technique to predict individual major depressive disorder (MDD) patient severity. MEG data was acquired from 22 MDD patients and 22 healthy controls (HC) resting awake with eyes closed. Individual power spectra were calculated by a Fourier transform. Sources were reconstructed via beamforming technique. Bayesian linear regression was applied to predict depression severity based on the spatial distribution of oscillatory power. In MDD patients, decreased theta (4-8 Hz) and alpha (8-14 Hz) power was observed in fronto-central and posterior areas respectively, whereas increased beta (14-30 Hz) power was observed in fronto-central regions. In particular, posterior alpha power was negatively related to depression severity. The Bayesian linear regression model showed significant depression severity prediction performance based on the spatial distribution of both alpha (r=0.68, p=0.0005) and beta power (r=0.56, p=0.007) respectively. Our findings point to a specific alteration of oscillatory brain activity in MDD patients during rest as characterized from MEG data in terms of spectral and spatial distribution. The proposed model yielded a quantitative and objective estimation for the depression severity, which in turn has a potential for diagnosis and monitoring of the recovery process. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

PubMed Central

Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

2009-01-01

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation. PMID:19805409

Exercise capacity in pediatric patients with inflammatory bowel disease.

PubMed

Ploeger, Hilde E; Takken, Tim; Wilk, Boguslaw; Issenman, Robert M; Sears, Ryan; Suri, Soni; Timmons, Brian W

2011-05-01

To examine exercise capacity in youth with Crohn's disease (CD) and ulcerative colitis (UC). Eleven males and eight females with CD and six males and four females with UC participated. Patients performed standard exercise tests to assess peak power (PP) and mean power (MP) and peak aerobic mechanical power (W(peak)) and peak oxygen uptake (VO(2peak)). Fitness variables were compared with reference data and also correlated with relevant clinical outcomes. Pediatric patients with inflammatory bowel disease had lower PP (∼90% of predicted), MP (∼88% of predicted), W(peak) (∼91% of predicted), and VO(2peak) (∼75% of predicted) compared with reference values. When patients with CD or UC were compared separately to reference values, W(peak) was significantly lower only in the CD group. No statistically significant correlations were found between any exercise variables and disease duration (r = 0.01 to 0.14, P = .47 to .95) or disease activity (r = -0.19 to -0.31, P = .11 to .38), measured by pediatric CD activity index or pediatric ulcerative colitis activity index. After controlling for chronological age, recent hemoglobin levels were significantly correlated with PP (r = 0.45, P = .049), MP (r = 0.63, P = .003), VO(2peak) (r = 0.62, P = .004), and W(peak) (r = 0.70, P = .001). Pediatric patients with inflammatory bowel disease exhibit impaired aerobic and anaerobic exercise capacity compared with reference values. Copyright © 2011 Mosby, Inc. All rights reserved.

Using Conversation Topics for Predicting Therapy Outcomes in Schizophrenia

PubMed Central

Howes, Christine; Purver, Matthew; McCabe, Rose

2013-01-01

Previous research shows that aspects of doctor-patient communication in therapy can predict patient symptoms, satisfaction and future adherence to treatment (a significant problem with conditions such as schizophrenia). However, automatic prediction has so far shown success only when based on low-level lexical features, and it is unclear how well these can generalize to new data, or whether their effectiveness is due to their capturing aspects of style, structure or content. Here, we examine the use of topic as a higher-level measure of content, more likely to generalize and to have more explanatory power. Investigations show that while topics predict some important factors such as patient satisfaction and ratings of therapy quality, they lack the full predictive power of lower-level features. For some factors, unsupervised methods produce models comparable to manual annotation. PMID:23943658

Psychopathy and community violence among civil psychiatric patients: results from the MacArthur Violence Risk Assessment Study.

PubMed

Skeem, J L; Mulvey, E P

2001-06-01

Although psychopathy is recognized as a relatively strong risk factor for violence among inmates and mentally disordered offenders, few studies have examined the extent to which its predictive power generalizes to civil psychiatric samples. Using data on 1,136 patients from the MacArthur Violence Risk Assessment project, this study examined whether the 2 scales that underlie the Psychopathy Checklist: Screening Version (PCL:SV) measure a unique personality construct that predicts violence among civil patients. The results indicate that the PCL:SV is a relatively strong predictor of violence. The PCL:SV's predictive power is substantially reduced, but remains significant, after controlling for a host of covariates that reflect antisocial behavior and personality disorders other than psychopathy. However, the predictive power of the PCL:SV is not based on its assessment of the core traits of psychopathy, as traditionally construed. Implications for the 2-factor model that underlies the PCL measures and for risk assessment practice are discussed.

Predicting Power Output of Upper Body using the OMNI-RES Scale.

PubMed

Bautista, Iker J; Chirosa, Ignacio J; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E; Chirosa, Luis J; Robertson, Robert J

2014-12-09

The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

Predicting Power Output of Upper Body using the OMNI-RES Scale

PubMed Central

Bautista, Iker J.; Chirosa, Ignacio J.; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E.; Chirosa, Luis J.; Robertson, Robert J.

2014-01-01

The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI–RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = −0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI–RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone. PMID:25713677

Dependency of exercise-induced T-wave alternans predictive power for the occurrence of ventricular arrhythmias from heart rate.

PubMed

Burattini, Laura; Man, Sumche; Fioretti, Sandro; Di Nardo, Francesco; Swenne, Cees A

2015-07-01

T-wave alternans (TWA) is a noninvasive index of risk for the occurrence of ventricular arrhythmias. It is known that TWA amplitude (TWAA) increases with heart rate (HR) but how the TWA predictive power varies with HR remains unknown. Thus, the aim of this study was to evaluate the dependency of exercise-induced TWA predictive power for the occurrence of ventricular arrhythmias from HR. TWA was identified using our HR adaptive match filter in exercise ECGs from 248 patients with implanted cardiac defibrillator (ICD), of which 72 developed ventricular tachycardia and/or fibrillation during the 4 year follow-up (ICD_Cases) and 176 did not (ICD_Controls). TWA predictive power was evaluated at HRs from 80 to 120 bpm by computing the area under the receiver operating characteristic curve (AUC) obtained using the maximum TWAA (maxTWAA) and the TWAA ratio (TWAAratio; i.e., the ratio between TWAA at a specific HR and at 80 bpm). TWAA increased with HR. At 80 bpm maxTWAA was lower than at 120 bpm in both ICD_Cases (22 μV vs 41 μV; P < 10(-2) ) and ICD_ Controls (16 μV vs 36 μV; P < 10(-4) ). However, only at 80 bpm ICD_Cases showed significantly higher maxTWAA than ICD_Controls (AUC = 0.6486; P = 0.0080). TWAAratio was higher in ICD_Controls than ICD_Cases for all HR but 120 bpm, and its predictive power was maximum at 115 bpm (AUC = 0.6914; P < 0.05). Exercise-induced TWA predictive power for the occurrence of ventricular arrhythmias, quantified using both maxTWAA and TWAAratio, was higher at low rather than at high HR. © 2014 Wiley Periodicals, Inc.

Predictive power of the grace score in population with diabetes.

PubMed

Baeza-Román, Anna; de Miguel-Balsa, Eva; Latour-Pérez, Jaime; Carrillo-López, Andrés

2017-12-01

Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score. The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model. Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement. The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model. The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Comparison of Newer IOL Power Calculation Methods for Eyes With Previous Radial Keratotomy

PubMed Central

Ma, Jack X.; Tang, Maolong; Wang, Li; Weikert, Mitchell P.; Huang, David; Koch, Douglas D.

2016-01-01

Purpose To evaluate the accuracy of the optical coherence tomography–based (OCT formula) and Barrett True K (True K) intraocular lens (IOL) calculation formulas in eyes with previous radial keratotomy (RK). Methods In 95 eyes of 65 patients, using the actual refraction following cataract surgery as target refraction, the predicted IOL power for each method was calculated. The IOL prediction error (PE) was obtained by subtracting the predicted IOL power from the implanted IOL power. The arithmetic IOL PE and median refractive PE were calculated and compared. Results All formulas except the True K produced hyperopic IOL PEs at 1 month, which decreased at ≥4 months (all P < 0.05). For the double-K Holladay 1, OCT formula, True K, and average of these three formulas (Average), the median absolute refractive PEs were, respectively, 0.78 diopters (D), 0.74 D, 0.60 D, and 0.59 D at 1 month; 0.69 D, 0.77 D, 0.77 D, and 0.61 D at 2 to 3 months; and 0.34 D, 0.65 D, 0.69 D, and 0.46 D at ≥4 months. The Average produced significantly smaller refractive PE than did the double-K Holladay 1 at 1 month (P < 0.05). There were no significant differences in refractive PEs among formulas at 4 months. Conclusions The OCT formula and True K were comparable to the double-K Holladay 1 method on the ASCRS (American Society of Cataract and Refractive Surgery) calculator. The Average IOL power on the ASCRS calculator may be considered when selecting the IOL power. Further improvements in the accuracy of IOL power calculation in RK eyes are desirable. PMID:27409468

Altered Neural Oscillations During Multisensory Integration in Adolescents with Fetal Alcohol Spectrum Disorder.

PubMed

Bolaños, Alfredo D; Coffman, Brian A; Candelaria-Cook, Felicha T; Kodituwakku, Piyadasa; Stephen, Julia M

2017-12-01

Children with fetal alcohol spectrum disorder (FASD), who were exposed to alcohol in utero, display a broad range of sensory, cognitive, and behavioral deficits, which are broadly theorized to be rooted in altered brain function and structure. Based on the role of neural oscillations in multisensory integration from past studies, we hypothesized that adolescents with FASD would show a decrease in oscillatory power during event-related gamma oscillatory activity (30 to 100 Hz), when compared to typically developing healthy controls (HC), and that such decrease in oscillatory power would predict behavioral performance. We measured sensory neurophysiology using magnetoencephalography (MEG) during passive auditory, somatosensory, and multisensory (synchronous) stimulation in 19 adolescents (12 to 21 years) with FASD and 23 age- and gender-matched HC. We employed a cross-hemisphere multisensory paradigm to assess interhemispheric connectivity deficits in children with FASD. Time-frequency analysis of MEG data revealed a significant decrease in gamma oscillatory power for both unisensory and multisensory conditions in the FASD group relative to HC, based on permutation testing of significant group differences. Greater beta oscillatory power (15 to 30 Hz) was also noted in the FASD group compared to HC in both unisensory and multisensory conditions. Regression analysis revealed greater predictive power of multisensory oscillations from unisensory oscillations in the FASD group compared to the HC group. Furthermore, multisensory oscillatory power, for both groups, predicted performance on the Intra-Extradimensional Set Shift Task and the Cambridge Gambling Task. Altered oscillatory power in the FASD group may reflect a restricted ability to process somatosensory and multisensory stimuli during day-to-day interactions. These alterations in neural oscillations may be associated with the neurobehavioral deficits experienced by adolescents with FASD and may carry over to adulthood. Copyright © 2017 by the Research Society on Alcoholism.

Exercise dependence and the drive for muscularity in male bodybuilders, power lifters, and fitness lifters.

PubMed

Hale, Bruce D; Roth, Andrew D; DeLong, Ryan E; Briggs, Michael S

2010-06-01

Researchers have hypothesized differences in exercise dependence and drive for muscularity between bodybuilders and power lifters, while others have not found the predicted differences. This study assessed 146 weight lifters (bodybuilders, n=59; power lifters, n=47; fitness lifters, n=40) on the Exercise Dependence Scale, Bodybuilding Dependence Scale, and the Drive for Muscularity Scale. Results showed that bodybuilders and power lifters were significantly higher than fitness lifters on EDS Total, 7 EDS scales, and the 3 BDS scales. In contrast, power lifters were found to be significantly higher on DMS Total and DMS Behavior scales than bodybuilders. The regression results suggest that exercise dependence may be directly related to the drive for muscularity. 2010 Elsevier Ltd. All rights reserved.

NASA Lewis Stirling SPRE testing and analysis with reduced number of cooler tubes

NASA Technical Reports Server (NTRS)

Wong, Wayne A.; Cairelli, James E.; Swec, Diane M.; Doeberling, Thomas J.; Lakatos, Thomas F.; Madi, Frank J.

1992-01-01

Free-piston Stirling power converters are candidates for high capacity space power applications. The Space Power Research Engine (SPRE), a free-piston Stirling engine coupled with a linear alternator, is being tested at the NASA Lewis Research Center in support of the Civil Space Technology Initiative. The SPRE is used as a test bed for evaluating converter modifications which have the potential to improve the converter performance and for validating computer code predictions. Reducing the number of cooler tubes on the SPRE has been identified as a modification with the potential to significantly improve power and efficiency. Experimental tests designed to investigate the effects of reducing the number of cooler tubes on converter power, efficiency and dynamics are described. Presented are test results from the converter operating with a reduced number of cooler tubes and comparisons between this data and both baseline test data and computer code predictions.

Horizontal axis wind turbine post stall airfoil characteristics synthesization

NASA Technical Reports Server (NTRS)

Tangler, James L.; Ostowari, Cyrus

1995-01-01

Blade-element/momentum performance prediction codes are routinely used for wind turbine design and analysis. A weakness of these codes is their inability to consistently predict peak power upon which the machine structural design and cost are strongly dependent. The purpose of this study was to compare post-stall airfoil characteristics synthesization theory to a systematically acquired wind tunnel data set in which the effects of aspect ratio, airfoil thickness, and Reynolds number were investigated. The results of this comparison identified discrepancies between current theory and the wind tunnel data which could not be resolved. Other factors not previously investigated may account for these discrepancies and have a significant effect on peak power prediction.

Critical analysis of 3-D organoid in vitro cell culture models for high-throughput drug candidate toxicity assessments.

PubMed

Astashkina, Anna; Grainger, David W

2014-04-01

Drug failure due to toxicity indicators remains among the primary reasons for staggering drug attrition rates during clinical studies and post-marketing surveillance. Broader validation and use of next-generation 3-D improved cell culture models are expected to improve predictive power and effectiveness of drug toxicological predictions. However, after decades of promising research significant gaps remain in our collective ability to extract quality human toxicity information from in vitro data using 3-D cell and tissue models. Issues, challenges and future directions for the field to improve drug assay predictive power and reliability of 3-D models are reviewed. Copyright © 2014 Elsevier B.V. All rights reserved.

Diagnostic potential of endotoxin scattering photometry for sepsis and septic shock.

PubMed

Shimizu, Tomoharu; Obata, Toru; Sonoda, Hiromichi; Akabori, Hiroya; Miyake, Tohru; Yamamoto, Hiroshi; Tabata, Takahisa; Eguchi, Yutaka; Tani, Tohru

2013-12-01

Endotoxin scattering photometry (ESP) is a novel Limulus amebocyte lysate (LAL) assay that uses a laser light-scattering particle-counting method. In the present study, we compared ESP, standard turbidimetric LAL assay, and procalcitonin assay for the evaluation of sepsis after emergency gastrointestinal surgery. A total of 174 samples were collected from 40 adult patients undergoing emergency gastrointestinal surgery and 10 patients with colorectal cancer undergoing elective surgery as nonseptic controls. Plasma endotoxin levels were measured with ESP and turbidimetric LAL assay, and plasma procalcitonin levels were assessed with a standard procalcitonin assay. Plasma endotoxin and procalcitonin levels increased corresponding to the degree of sepsis. Endotoxin scattering photometry significantly discriminated between patients with or without septic shock: sensitivity, 81.1%; specificity, 76.6%; positive predictive value, 48.4%; negative predictive value, 93.8%; and accuracy, 77.6%. The area under the receiver operating characteristic curve for septic shock with the ESP assay (endotoxin cutoff value, 23.8 pg/mL) was 0.8532 ± 0.0301 (95% confidence interval, 0.7841-0.9030; P < 0.0001). The predictive power of ESP was superior to that of turbidimetric assay (difference, 0.1965 ± 0.0588; 95% confidence interval, 0.0812-0.3117; P = 0.0008). There was no significant difference in predictive power between ESP and procalcitonin assay. Endotoxin scattering photometry also discriminated between patients with and without sepsis. Area under the receiver operating characteristic curve analysis showed that ESP had the best predictive power for diagnosing sepsis. In conclusion, compared with turbidimetric LAL assay, ESP more sensitively detected plasma endotoxin and significantly discriminated between sepsis and septic shock in patients undergoing gastrointestinal emergency surgery.

Using Reanalysis Data for the Prediction of Seasonal Wind Turbine Power Losses Due to Icing

NASA Astrophysics Data System (ADS)

Burtch, D.; Mullendore, G. L.; Delene, D. J.; Storm, B.

2013-12-01

The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data to investigate various methods of predicting seasonal losses (October-March) due to icing at two wind turbine sites located 121 km apart in North Dakota. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using three methods. For each of the three methods, the required atmospheric variables are determined in one of two ways: using industry-specific software to correlate anemometer data in conjunction with the MERRA dataset and using only the MERRA dataset for all variables. For each season, a percentage of the total expected generated power lost due to icing is determined and compared to observed losses from the production data. An optimization is performed in order to determine the relative humidity threshold that minimizes the difference between the predicted and observed values. Eight seasons of data are used to determine an optimal relative humidity threshold, and a further three seasons of data are used to test this threshold. Preliminary results have shown that the optimized relative humidity threshold for the northern turbine is higher than the southern turbine for all methods. For the three test seasons, the optimized thresholds tend to under-predict the icing losses. However, the threshold determined using boundary layer similarity theory most closely predicts the power losses due to icing versus the other methods. For the northern turbine, the average predicted power loss over the three seasons is 4.65 % while the observed power loss is 6.22 % (average difference of 1.57 %). For the southern turbine, the average predicted power loss and observed power loss over the same time period are 4.43 % and 6.16 %, respectively (average difference of 1.73 %). The three-year average, however, does not clearly capture the variability that exists season-to-season. On examination of each of the test seasons individually, the optimized relative humidity threshold methodology performs better than fixed power loss estimates commonly used in the wind energy industry.

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference

PubMed Central

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference (p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information. PMID:29479312

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference.

PubMed

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-Ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference ( p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information.

Is stair climb power a clinically relevant measure of leg power impairments in at-risk older adults?

PubMed

Bean, Jonathan F; Kiely, Dan K; LaRose, Sharon; Alian, Joda; Frontera, Walter R

2007-05-01

To test the clinical relevance of the stair climb power test (SCPT) as a measure of leg power impairments in mobility-limited older adults. Cross-sectional analysis of baseline data from participants within a randomized controlled trial. Rehabilitation research gym. Community-dwelling older adults (N=138; mean age, 75.4 y) with mobility limitations as defined by the Short Physical Performance Battery (SPPB). Not applicable. Leg power measures included the SCPT and double leg press power measured at 40% (DLP40) and 70% (DLP70) of the 1 repetition maximum. Mobility performance tests included the SPPB and its 3 components: gait speed, chair stand time, and standing balance. Stair climb power per kilogram (SCP/kg) had correlations of moderate strength (r=.47, r=.52) with DLP40/kg and DLP70/kg, respectively. All 3 leg power measures correlated with each of the mobility performance measures with the exception of DLP40/kg (r=.11, P=.27) and DLP70/kg (r=.11, P=.18) with standing balance. Magnitudes of association, as described by the Pearson correlation coefficient, did not differ substantively among the separate power measures as they related to SPPB performance overall. Separate adjusted multivariate models evaluating the relationship between leg power and SPPB performance were all statistically significant and described equivalent amounts of the total variance (R(2)) in SPPB performance (SCP/kg, R(2)=.30; DLP40, R(2)=.32; DLP70, R(2)=.31). Analyses of the components of the SPPB show that the SCPT had stronger associations than the other leg power impairment measures with models predicting chair stand (SCP/kg, R(2)=.25; DLP40, R(2)=.12; DLP70, R(2)=.13), whereas both types of leg press power testing had stronger associations with models predicting gait speed (SCP/kg, R(2)=.16; DLP40, R(2)=.34; DLP70, R(2)=.34). Stair climb power was the only power measure that was a significant component of models predicting standing balance (SCP/kg R(2)=.20). The SCPT is a clinically relevant measure of leg power impairments. It is associated with more complex modes of testing leg power impairments and is meaningfully associated with mobility performance, making it suitable for clinical settings in which impairment-mobility relationships are of interest.

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

DOE PAGES

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-05-08

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k yρ s < 1) and short wavelength electron-scale (k yρ s > 1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. We observe significant nonlinear cross-scale couplings in the multiscalemore » simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E x B shearing rate γ E x B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. And while the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Though computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.« less

Gyrokinetic predictions of multiscale transport in a DIII-D ITER baseline discharge

NASA Astrophysics Data System (ADS)

Holland, C.; Howard, N. T.; Grierson, B. A.

2017-06-01

New multiscale gyrokinetic simulations predict that electron energy transport in a DIII-D ITER baseline discharge with dominant electron heating and low input torque is multiscale in nature, with roughly equal amounts of the electron energy flux Q e coming from long wavelength ion-scale (k y ρ s  <  1) and short wavelength electron-scale (k y ρ s  >  1) fluctuations when the gyrokinetic results match independent power balance calculations. Corresponding conventional ion-scale simulations are able to match the power balance ion energy flux Q i, but systematically underpredict Q e when doing so. Significant nonlinear cross-scale couplings are observed in the multiscale simulations, but the exact simulation predictions are found to be extremely sensitive to variations of model input parameters within experimental uncertainties. Most notably, depending upon the exact value of the equilibrium E  ×  B shearing rate γ E×B used, either enhancement or suppression of the long-wavelength turbulence and transport levels in the multiscale simulations is observed relative to what is predicted by ion-scale simulations. While the enhancement of the long wavelength fluctuations by inclusion of the short wavelength turbulence was previously observed in similar multiscale simulations of an Alcator C-Mod L-mode discharge, these new results show for the first time a complete suppression of long-wavelength turbulence in a multiscale simulation, for parameters at which conventional ion-scale simulation predicts small but finite levels of low-k turbulence and transport consistent with the power balance Q i. Although computational resource limitations prevent a fully rigorous validation assessment of these new results, they provide significant new evidence that electron energy transport in burning plasmas is likely to have a strong multiscale character, with significant nonlinear cross-scale couplings that must be fully understood to predict the performance of those plasmas with confidence.

The Effect of Sex on Heart Rate Variability at High Altitude.

PubMed

Boos, Christopher John; Vincent, Emma; Mellor, Adrian; O'Hara, John; Newman, Caroline; Cruttenden, Richard; Scott, Phylip; Cooke, Mark; Matu, Jamie; Woods, David Richard

2017-12-01

There is evidence suggesting that high altitude (HA) exposure leads to a fall in heart rate variability (HRV) that is linked to the development of acute mountain sickness (AMS). The effects of sex on changes in HRV at HA and its relationship to AMS are unknown. HRV (5-min single-lead ECG) was measured in 63 healthy adults (41 men and 22 women) 18-56 yr of age at sea level (SL) and during a HA trek at 3619, 4600, and 5140 m, respectively. The main effects of altitude (SL, 3619 m, 4600 m, and 5140 m) and sex (men vs women) and their potential interaction were assessed using a factorial repeated-measures ANOVA. Logistic regression analyses were performed to assess the ability of HRV to predict AMS. Men and women were of similar age (31.2 ± 9.3 vs 31.7 ± 7.5 yr), ethnicity, and body and mass index. There was main effect for altitude on heart rate, SD of normal-to-normal (NN) intervals (SDNN), root mean square of successive differences (RMSSD), number of pairs of successive NN differing by >50 ms (NN50), NN50/total number of NN, very low-frequency power, low-frequency (LF) power, high-frequency (HF) power, and total power (TP). The most consistent effect on post hoc analysis was reduction in these HRV measures between 3619 and 5140 m at HA. Heart rate was significantly lower and SDNN, RMSSD, LF power, HF power, and TP were higher in men compared with women at HA. There was no interaction between sex and altitude for any of the HRV indices measured. HRV was not predictive of AMS development. Increasing HA leads to a reduction in HRV. Significant differences between men and women emerge at HA. HRV was not predictive of AMS.

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

PubMed Central

Shen, Li; Qi, Yuan; Kim, Sungeun; Nho, Kwangsik; Wan, Jing; Risacher, Shannon L.; Saykin, Andrew J.

2010-01-01

We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accurate prediction and identify critical imaging markers relevant to AD at the same time. ARD is one of the most successful Bayesian feature selection methods. PARD is a powerful Bayesian feature selection method, and provides sparse models that is easy to interpret. PARD selects the model with the best estimate of the predictive performance instead of choosing the one with the largest marginal model likelihood. Comparative study with support vector machine (SVM) shows that ARD/PARD in general outperform SVM in terms of prediction accuracy. Additional comparison with surface-based general linear model (GLM) analysis shows that regions with strongest signals are identified by both GLM and ARD/PARD. While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures. PMID:20879451

Short-term load forecasting of power system

NASA Astrophysics Data System (ADS)

Xu, Xiaobin

2017-05-01

In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

Felt power explains the link between position power and experienced emotions.

PubMed

Bombari, Dario; Schmid Mast, Marianne; Bachmann, Manuel

2017-02-01

The approach/inhibition theory by Keltner, Gruenfeld, and Anderson (2003) predicts that powerful people should feel more positive and less negative emotions. To date, results of studies investigating this prediction are inconsistent. We fill this gap with four studies in which we investigated the role of different conceptualizations of power: felt power and position power. In Study 1, participants were made to feel more or less powerful and we tested how their felt power was related to different emotional states. In Studies 2, 3, and 4, participants were assigned to either a high or a low power role and engaged in an interaction with a virtual human, after which participants reported on how powerful they felt and the emotions they experienced during the interaction. We meta-analytically combined the results of the four studies and found that felt power was positively related to positive emotions (happiness and serenity) and negatively to negative emotions (fear, anger, and sadness), whereas position power did not show any significant overall relation with any of the emotional states. Importantly, felt power mediated the relationship between position power and emotion. In summary, we show that how powerful a person feels in a given social interaction is the driving force linking the person's position power to his or her emotional states. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

New algorithm for toric intraocular lens power calculation considering the posterior corneal astigmatism.

PubMed

Canovas, Carmen; Alarcon, Aixa; Rosén, Robert; Kasthurirangan, Sanjeev; Ma, Joseph J K; Koch, Douglas D; Piers, Patricia

2018-02-01

To assess the accuracy of toric intraocular lens (IOL) power calculations of a new algorithm that incorporates the effect of posterior corneal astigmatism (PCA). Abbott Medical Optics, Inc., Groningen, the Netherlands. Retrospective case report. In eyes implanted with toric IOLs, the exact vergence formula of the Tecnis toric calculator was used to predict refractive astigmatism from preoperative biometry, surgeon-estimated surgically induced astigmatism (SIA), and implanted IOL power, with and without including the new PCA algorithm. For each calculation method, the error in predicted refractive astigmatism was calculated as the vector difference between the prediction and the actual refraction. Calculations were also made using postoperative keratometry (K) values to eliminate the potential effect of incorrect SIA estimates. The study comprised 274 eyes. The PCA algorithm significantly reduced the centroid error in predicted refractive astigmatism (P < .001). With the PCA algorithm, the centroid error reduced from 0.50 @ 1 to 0.19 @ 3 when using preoperative K values and from 0.30 @ 0 to 0.02 @ 84 when using postoperative K values. Patients who had anterior corneal against-the-rule, with-the-rule, and oblique astigmatism had improvement with the PCA algorithm. In addition, the PCA algorithm reduced the median absolute error in all groups (P < .001). The use of the new PCA algorithm decreased the error in the prediction of residual refractive astigmatism in eyes implanted with toric IOLs. Therefore, the new PCA algorithm, in combination with an exact vergence IOL power calculation formula, led to an increased predictability of toric IOL power. Copyright © 2018 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

The value of reasons for encounter in early detection of colorectal cancer.

PubMed

van Boxtel-Wilms, Susan J M; van Boven, Kees; Bor, J H Hans; Bakx, J Carel; Lucassen, Peter; Oskam, Sibo; van Weel, Chris

2016-06-01

Symptoms with a high predictive power for colorectal cancer (CRC) do not exist. To explore the predictive value of patients' reason for encounter (RFE) in the two years prior to the diagnosis of CRC. A retrospective nested case-control study using prospectively collected data from electronic records in general practice over 20 years. Matching was done based on age (within two years), gender and practice. The positive likelihood ratios (LR+) and odds ratios (OR) were calculated for RFE between cases and controls in the two years before the index date. We identified 184 CRC cases and matched 366 controls. Six RFEs had significant LR + and ORs for CRC, which may have high predictive power. These RFEs are part of four chapters in the International Classification of Primary Care (ICPC) that include tiredness (significant at 3-6 months prior to the diagnosis; LR+ 2.6 and OR 3.07; and from 0 to 3 months prior to the diagnosis; LR+ 2.0 and OR 2.36), anaemia (significant at three months before diagnosis; LR+ 9.8 and OR 16.54), abdominal pain, rectal bleeding and constipation (significant at 3-6 months before diagnosis; LR+ 3.0 and OR 3.33; 3 months prior to the diagnosis LR+ 8.0 and OR 18.10) and weight loss (significant at three months before diagnosis; LR+ 14.9 and OR 14.53). Data capture and organization in ICPC permits study of the predictive value of RFE for CRC in primary care.

Assessment of Gasoline Prices and its Predictive Power on U.S. Consumers' Retail Spending and Savings

NASA Astrophysics Data System (ADS)

Alvarado-Bonilla, Joel

The rising costs of fuels and specifically gasoline pose an economic challenge to U.S. consumers. Thus, the specific problem considered in this study was a rise in gasoline prices can reduce consumer spending, disposable income, food service traffic, and spending on healthy food, medicines, or visits to the doctor. Aligned with the problem, the purpose of this quantitative multiple correlation study was to examine the economic aspects for a rise in gasoline prices to reduce the six elements in the problem. This study consisted of a correlational design based on a retrospective longitudinal analysis (RLA) to examine gasoline prices versus the economic indexes of: (a) Retail Spending and (b) personal savings (PS). The RLA consisted on historic archival public data from 1978 to 2015. This RLA involved two separate linear multiple regression analyses to measure gasoline price's predictive power (PP) on two indexes while controlling for Unemployment Rate (UR). In summary, regression Formula 1 revealed Gasoline Price had a significant 61.1% PP on Retail Spending. In contrast, Formula 2 had Gasoline Price not having a significant PP on PS. Formula 2 yielded UR with 38.8% PP on PS. Results were significant at p<.01. Gasoline Price's PP on Retail Spending means a spending link to retail items such as: food service traffic, healthy food, medicines, and consumer spending. The UR predictive power on PS was unexpected, but logical from an economic view. Also unexpected was Gasoline Price's non-predictive power on PS, which suggests Americans may not save money when gasoline prices drop. These results shed light on the link of gasoline and UR on U.S. consumer's economy through savings and spending, which can be useful for policy design on gasoline and fuels taxing and pricing. The results serve as a basis for future study on gasoline and economics.

Potential of laser for SPS power transmission

NASA Technical Reports Server (NTRS)

Bain, C. N.

1978-01-01

Research on the feasibility of using a laser subsystem as an additional option for the transmission of the satellite power system (STS) power is presented. Current laser work and predictions for future laser performance provide a level of confidence that the development of a laser power transmission system is technologically feasible in the time frame required to develop the SBS. There are significant economic advantages in lower ground distribution costs and a reduction of more than two orders of magnitude in real estate requirements for ground based receiving/conversion sites.

Pre-stimulus thalamic theta power predicts human memory formation.

PubMed

Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

2016-09-01

Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

PubMed

Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Influence of polygenic risk scores on lipid levels and dyslipidemia in a psychiatric population receiving weight gain-inducing psychotropic drugs.

PubMed

Delacrétaz, Aurélie; Lagares Santos, Patricia; Saigi Morgui, Nuria; Vandenberghe, Frederik; Glatard, Anaïs; Gholam-Rezaee, Mehdi; von Gunten, Armin; Conus, Philippe; Eap, Chin B

2017-12-01

Dyslipidemia represents a major health issue in psychiatry. We determined whether weighted polygenic risk scores (wPRSs) combining multiple single-nucleotide polymorphisms (SNPs) associated with lipid levels in the general population are associated with lipid levels [high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides] and/or dyslipidemia in patients receiving weight gain-inducing psychotropic drugs. We also determined whether genetics improve the predictive power of dyslipidemia. The influence of wPRS on lipid levels was firstly assessed in a discovery psychiatric sample (n=332) and was then tested for replication in an independent psychiatric sample (n=140). The contribution of genetic markers to predict dyslipidemia was evaluated in the combined psychiatric sample. wPRSs were significantly associated with the four lipid traits in the discovery (P≤0.02) and in the replication sample (P≤0.03). Patients whose wPRS was higher than the median wPRS had significantly higher LDL, TC, and triglyceride levels (0.20, 0.32 and 0.26 mmol/l, respectively; P≤0.004) and significantly lower HDL levels (0.13 mmol/l; P<0.0001) compared with others. Adding wPRS to clinical data significantly improved dyslipidemia prediction of HDL (P=0.03) and a trend for improvement was observed for the prediction of TC dyslipidemia (P=0.08). Population-based wPRSs have thus significant effects on lipid levels in the psychiatric population. As genetics improved the predictive power of dyslipidemia development, only 24 patients need to be genotyped to prevent the development of one case of HDL hypocholesterolemia. If confirmed by further prospective investigations, the present results could be used for individualizing psychotropic treatment.

Use of the Posterior/Anterior Corneal Curvature Radii Ratio to Improve the Accuracy of Intraocular Lens Power Calculation: Eom's Adjustment Method.

PubMed

Kim, Mingue; Eom, Youngsub; Lee, Hwa; Suh, Young-Woo; Song, Jong Suk; Kim, Hyo Myung

2018-02-01

To evaluate the accuracy of IOL power calculation using adjusted corneal power according to the posterior/anterior corneal curvature radii ratio. Nine hundred twenty-eight eyes from 928 reference subjects and 158 eyes from 158 cataract patients who underwent phacoemulsification surgery were enrolled. Adjusted corneal power of cataract patients was calculated using the fictitious refractive index that was obtained from the geometric mean posterior/anterior corneal curvature radii ratio of reference subjects and adjusted anterior and predicted posterior corneal curvature radii from conventional keratometry (K) using the posterior/anterior corneal curvature radii ratio. The median absolute error (MedAE) based on the adjusted corneal power was compared with that based on conventional K in the Haigis and SRK/T formulae. The geometric mean posterior/anterior corneal curvature radii ratio was 0.808, and the fictitious refractive index of the cornea for a single Scheimpflug camera was 1.3275. The mean difference between adjusted corneal power and conventional K was 0.05 diopter (D). The MedAE based on adjusted corneal power (0.31 D in the Haigis formula and 0.32 D in the SRK/T formula) was significantly smaller than that based on conventional K (0.41 D and 0.40 D, respectively; P < 0.001 and P < 0.001, respectively). The percentage of eyes with refractive prediction error within ± 0.50 D calculated using adjusted corneal power (74.7%) was significantly greater than that obtained using conventional K (62.7%) in the Haigis formula (P = 0.029). IOL power calculation using adjusted corneal power according to the posterior/anterior corneal curvature radii ratio provided more accurate refractive outcomes than calculation using conventional K.

Differentiating the effects of status and power: a justice perspective.

PubMed

Blader, Steven L; Chen, Ya-Ru

2012-05-01

Few empirical efforts have been devoted to differentiating status and power, and thus significant questions remain about differences in how status and power impact social encounters. We conducted 5 studies to address this gap. In particular, these studies tested the prediction that status and power would have opposing effects on justice enacted toward others. In the first 3 studies, we directly compared the effects of status and power on people's enactment of distributive (Study 1) and procedural (Studies 2 and 3) justice. In the last 2 studies, we orthogonally manipulated status and power and examined their main and interactive effects on people's enactment of distributive (Study 4) and procedural (Study 5) justice. As predicted, all 5 studies showed consistent evidence that status is positively associated with justice toward others, while power is negatively associated with justice toward others. The effects of power are moderated, however, by an individual's other orientation (Studies 2, 3, 4, and 5), and the effects of status are moderated by an individual's dispositional concern about status (Study 5). Furthermore, Studies 4 and 5 also demonstrated that status and power interact, such that the positive effect of status on justice emerges when power is low and not when power is high, providing further evidence for differential effects between power and status. Theoretical implications for the literatures on status, power, and distributive/procedural justice are discussed.

Lessons Learned from the Wide Field Camera 3 Flight Correlation

NASA Technical Reports Server (NTRS)

Peabody, Hume L.; Stavely, Richard A.; Townsend, Jackie; Abel, Josh; Mandi, Joe; Bast, William

2010-01-01

The Wide Field Camera 3 (WFC3) instrument was installed into the Hubble Space Telescope (HST) as part of the activities for STS (Space Transportation System)-125 (HST Servicing Mission 4). Initial model predictions for power and radiator temperature were not in good agreement with flight data during a relatively hot, stable period, with the flight power and temperatures being significantly higher than predictions. Significant efforts were undertaken to identify the causes of the discrepancies and to resolve the flight model correlation problems as the thermal vacuum test correlation indicated good agreement. The WFC3 thermal design performance has proven difficult to accurately predict, since the power dissipation on the radiator typically increases as the radiator temperature increases, due to a Thermo Electric Cooler (TEC) attached to the this radiator. This self beating continues until the radiative emissive capability is met for a given temperature, and only then does the system find a quasi-steady regime. Various other factors may also contribute to the radiator temperature, such as backloadlng from the observatory itself and the planet, local high-absorptivity regions near fasteners/holes, and temperature varying parasitic heat leaks from the instrument itself to the radiator. Each of these effects in turn may increase the radiator temperature, and furthermore the demand on the TEC.

Chapter 3: Photovoltaic Module Stability and Reliability

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

Jordan, Dirk; Kurtz, Sarah

2017-01-01

Profits realized from investment in photovoltaic will benefit from decades of reliable operation. Service life prediction through accelerated tests is only possible if indoor tests duplicate power loss and failure modes observed in fielded systems. Therefore, detailing and quantifying power loss and failure modes is imperative. In the first section, we examine recent trends in degradation rates, the gradual power loss observed for different technologies, climates and other significant factors. In the second section, we provide a summary of the most commonly observed failure modes in fielded systems.

Heat pipe cooling of power processing magnetics

NASA Technical Reports Server (NTRS)

Hansen, I. G.; Chester, M. S.

1979-01-01

A heat pipe cooled transformer and input filter were developed for the 2.4 kW beam supply of a 30 cm ion thruster system. This development yielded a mass reduction of 40% (1.76 kg) and lower mean winding temperature (20 C lower). While these improvements are significant, preliminary designs predict even greater benefits to be realized at higher power. The design details are presented along with the results of thermal vacuum operation and the component performance in a 3 kW breadboard power processor.

Sprinting performance on the Woodway Curve 3.0 is related to muscle architecture.

PubMed

Mangine, Gerald T; Fukuda, David H; Townsend, Jeremy R; Wells, Adam J; Gonzalez, Adam M; Jajtner, Adam R; Bohner, Jonathan D; LaMonica, Michael; Hoffman, Jay R; Fragala, Maren S; Stout, Jeffrey R

2015-01-01

To determine if unilateral measures of muscle architecture in the rectus femoris (RF) and vastus lateralis (VL) were related to (and predictive of) sprinting speed and unilateral (and bilateral) force (FRC) and power (POW) during a 30 s maximal sprint on the Woodway Curve 3.0 non-motorized treadmill. Twenty-eight healthy, physically active men (n = 14) and women (n = 14) (age = 22.9 ± 2.4 years; body mass = 77.1 ± 16.2 kg; height = 171.6 ± 11.2 cm; body-fa t = 19.4 ± 8.1%) completed one familiarization and one 30-s maximal sprint on the TM to obtain maximal sprinting speed, POW and FRC. Muscle thickness (MT), cross-sectional area (CSA) and echo intensity (ECHO) of the RF and VL in the dominant (DOM; determined by unilateral sprinting power) and non-dominant (ND) legs were measured via ultrasound. Pearson correlations indicated several significant (p < 0.05) relationships between sprinting performance [POW (peak, DOM and ND), FRC (peak, DOM, ND) and sprinting time] and muscle architecture. Stepwise regression indicated that POW(DOM) was predictive of ipsilateral RF (MT and CSA) and VL (CSA and ECHO), while POW(ND) was predictive of ipsilateral RF (MT and CSA) and VL (CSA); sprinting power/force asymmetry was not predictive of architecture asymmetry. Sprinting time was best predicted by peak power and peak force, though muscle quality (ECHO) and the bilateral percent difference in VL (CSA) were strong architectural predictors. Muscle architecture is related to (and predictive of) TM sprinting performance, while unilateral POW is predictive of ipsilateral architecture. However, the extent to which architecture and other factors (i.e. neuromuscular control and sprinting technique) affect TM performance remains unknown.

Simulating Fatigue Crack Growth in Spiral Bevel Gears

NASA Technical Reports Server (NTRS)

Spievak, Lisa E.; Wawrzynek, Paul A.; Ingraffea, Anthony R.

2000-01-01

The majority of helicopter transmission systems utilize spiral bevel gears to convert the horizontal power from the engine into vertical power for the rotor. Due to the cyclical loading on a gear's tooth, fatigue crack propagation can occur. In rotorcraft applications, a crack's trajectory determines whether the gear failure will be benign or catastrophic for the aircraft. As a result, the capability to predict crack growth in gears is significant. A spiral bevel gear's complex shape requires a three dimensional model of the geometry and cracks. The boundary element method in conjunction with linear elastic fracture mechanics theories is used to predict arbitrarily shaped three dimensional fatigue crack trajectories in a spiral bevel pinion under moving load conditions. The predictions are validated by comparison to experimental results. The sensitivity of the predictions to variations in loading conditions and crack growth rate model parameters is explored. Critical areas that must be understood in greater detail prior to predicting more accurate crack trajectories and crack growth rates in three dimensions are identified.

Tree morphologic plasticity explains deviation from metabolic scaling theory in semi-arid conifer forests, southwestern USA

Treesearch

Tyson L. Swetnam; Christopher D. O' Connor; Ann M. Lynch

2016-01-01

A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across...

Heat pipe cooling of power processing magnetics

NASA Technical Reports Server (NTRS)

Hansen, I. G.; Chester, M.

1979-01-01

The constant demand for increased power and reduced mass has raised the internal temperature of conventionally cooled power magnetics toward the upper limit of acceptability. The conflicting demands of electrical isolation, mechanical integrity, and thermal conductivity preclude significant further advancements using conventional approaches. However, the size and mass of multikilowatt power processing systems may be further reduced by the incorporation of heat pipe cooling directly into the power magnetics. Additionally, by maintaining lower more constant temperatures, the life and reliability of the magnetic devices will be improved. A heat pipe cooled transformer and input filter have been developed for the 2.4 kW beam supply of a 30-cm ion thruster system. This development yielded a mass reduction of 40% (1.76 kg) and lower mean winding temperature (20 C lower). While these improvements are significant, preliminary designs predict even greater benefits to be realized at higher power. This paper presents the design details along with the results of thermal vacuum operation and the component performance in a 3 kW breadboard power processor.

Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

PubMed

Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

2007-08-01

Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

Exploring the predictive power of polygenic scores derived from genome-wide association studies: a study of 10 complex traits.

PubMed

So, Hon-Cheong; Sham, Pak C

2017-03-15

It is hoped that advances in our knowledge in disease genomics will contribute to personalized medicine such as individualized preventive strategies or early diagnoses of diseases. With the growth of genome-wide association studies (GWAS) in the past decade, how far have we reached this goal? In this study we explored the predictive ability of polygenic risk scores (PRSs) derived from GWAS for a range of complex disease and traits. We first proposed a new approach to evaluate predictive performances of PRS at arbitrary P -value thresholds. The method was based on corrected estimates of effect sizes, accounting for possible false positives and selection bias. This approach requires no distributional assumptions and only requires summary statistics as input. The validity of the approach was verified in simulations. We explored the predictive power of PRS for ten complex traits, including type 2 diabetes (DM), coronary artery disease (CAD), triglycerides, high- and low-density lipoprotein, total cholesterol, schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder and anxiety disorders. We found that the predictive ability of PRS for CAD and DM were modest (best AUC = 0.608 and 0.607) while for lipid traits the prediction R-squared ranged from 16.1 to 29.8%. For psychiatric disorders, the predictive power for SCZ was estimated to be the highest (best AUC 0.820), followed by BD. Predictive performance of other psychiatric disorders ranged from 0.543 to 0.585. Psychiatric traits tend to have more gradual rise in AUC when significance thresholds increase and achieve the best predictive power at higher P -values than cardiometabolic traits. hcso@cuhk.edu.hk ; pcsham@hku.hk. 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

Two-point modeling of SOL losses of HHFW power in NSTX

NASA Astrophysics Data System (ADS)

Kish, Ayden; Perkins, Rory; Ahn, Joon-Wook; Diallo, Ahmed; Gray, Travis; Hosea, Joel; Jaworski, Michael; Kramer, Gerrit; Leblanc, Benoit; Sabbagh, Steve

2017-10-01

High-harmonic fast-wave (HHFW) heating is a heating and current-drive scheme on the National Spherical Torus eXperiment (NSTX) complimentary to neutral beam injection. Previous experiments suggest that a significant fraction, up to 50%, of the HHFW power is promptly lost to the scrape-off layer (SOL). Research indicates that the lost power reaches the divertor via wave propagation and is converted to a heat flux at the divertor through RF rectification rather than heating the SOL plasma at the midplane. This counter-intuitive hypothesis is investigated using a simplified two-point model, relating plasma parameters at the divertor to those at the midplane. Taking measurements at the divertor region of NSTX as input, this two-point model is used to predict midplane parameters, using the predicted heat flux as an indicator of power input to the SOL. These predictions are compared to measurements at the midplane to evaluate the extent to which they are consistent with experiment. This work was made possible by funding from the Department of Energy for the Summer Undergraduate Laboratory Internship (SULI) program. This work is supported by the US DOE Contract No. DE-AC02-09CH11466.

Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

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

Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng

This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA)more » models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.« less

Agent-Based Multicellular Modeling for Predictive Toxicology

EPA Science Inventory

Biological modeling is a rapidly growing field that has benefited significantly from recent technological advances, expanding traditional methods with greater computing power, parameter-determination algorithms, and the development of novel computational approaches to modeling bi...

Does power indicate capacity? 30-s Wingate anaerobic test vs. maximal accumulated O2 deficit.

PubMed

Minahan, C; Chia, M; Inbar, O

2007-10-01

The purpose of this study was to evaluate the relationship between anaerobic power and capacity. Seven men and seven women performed a 30-s Wingate Anaerobic Test on a cycle ergometer to determine peak power, mean power, and the fatigue index. Subjects also cycled at a work rate predicted to elicit 120 % of peak oxygen uptake to exhaustion to determine the maximal accumulated O (2) deficit. Peak power and the maximal accumulated O (2) deficit were significantly correlated (r = 0.782, p = 0.001). However, when the absolute difference in exercise values between groups (men and women) was held constant using a partial correlation, the relationship diminished (r = 0.531, p = 0.062). In contrast, we observed a significant correlation between fatigue index and the maximal accumulated O (2) deficit when controlling for gender (r = - 0.597, p = 0.024) and the relationship remained significant when values were expressed relative to active muscle mass. A higher anaerobic power does not indicate a greater anaerobic capacity. Furthermore, we suggest that the ability to maintain power output during a 30-s cycle sprint is related to anaerobic capacity.

Enhancing prediction power of chemometric models through manipulation of the fed spectrophotometric data: A comparative study

NASA Astrophysics Data System (ADS)

Saad, Ahmed S.; Hamdy, Abdallah M.; Salama, Fathy M.; Abdelkawy, Mohamed

2016-10-01

Effect of data manipulation in preprocessing step proceeding construction of chemometric models was assessed. The same set of UV spectral data was used for construction of PLS and PCR models directly and after mathematically manipulation as per well known first and second derivatives of the absorption spectra, ratio spectra and first and second derivatives of the ratio spectra spectrophotometric methods, meanwhile the optimal working wavelength ranges were carefully selected for each model and the models were constructed. Unexpectedly, number of latent variables used for models' construction varied among the different methods. The prediction power of the different models was compared using a validation set of 8 mixtures prepared as per the multilevel multifactor design and results were statistically compared using two-way ANOVA test. Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models. Although no significant difference was found between results obtained using Partial Least Squares (PLS) and Principal Component Regression (PCR) models, however, discrepancies among results was found to be attributed to the variation in the discrimination power of adopted spectrophotometric methods on spectral data.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

PubMed

Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

PubMed Central

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

Power hand tool kinetics associated with upper limb injuries in an automobile assembly plant.

PubMed

Ku, Chia-Hua; Radwin, Robert G; Karsh, Ben-Tzion

2007-06-01

This study investigated the relationship between pneumatic nutrunner handle reactions, workstation characteristics, and prevalence of upper limb injuries in an automobile assembly plant. Tool properties (geometry, inertial properties, and motor characteristics), fastener properties, orientation relative to the fastener, and the position of the tool operator (horizontal and vertical distances) were measured for 69 workstations using 15 different pneumatic nutrunners. Handle reaction response was predicted using a deterministic mechanical model of the human operator and tool that was previously developed in our laboratory, specific to the measured tool, workstation, and job factors. Handle force was a function of target torque, tool geometry and inertial properties, motor speed, work orientation, and joint hardness. The study found that tool target torque was not well correlated with predicted handle reaction force (r=0.495) or displacement (r=0.285). The individual tool, tool shape, and threaded fastener joint hardness all affected predicted forces and displacements (p<0.05). The average peak handle force and displacement for right-angle tools were twice as great as pistol grip tools. Soft-threaded fastener joints had the greatest average handle forces and displacements. Upper limb injury cases were identified using plant OSHA 200 log and personnel records. Predicted handle forces for jobs where injuries were reported were significantly greater than those jobs free of injuries (p<0.05), whereas target torque and predicted handle displacement did not show statistically significant differences. The study concluded that quantification of handle reaction force, rather than target torque alone, is necessary for identifying stressful power hand tool operations and for controlling exposure to forces in manufacturing jobs involving power nutrunners. Therefore, a combination of tool, work station, and task requirements should be considered.

The Challenge Posed by Geomagnetic Activity to Electric Power Reliability: Evidence From England and Wales

NASA Astrophysics Data System (ADS)

Forbes, Kevin F.; St. Cyr, O. C.

2017-10-01

This paper addresses whether geomagnetic activity challenged the reliability of the electric power system during part of the declining phase of solar cycle 23. Operations by National Grid in England and Wales are examined over the period of 11 March 2003 through 31 March 2005. This paper examines the relationship between measures of geomagnetic activity and a metric of challenged electric power reliability known as the net imbalance volume (NIV). Measured in megawatt hours, NIV represents the sum of all energy deployments initiated by the system operator to balance the electric power system. The relationship between geomagnetic activity and NIV is assessed using a multivariate econometric model. The model was estimated using half-hour settlement data over the period of 11 March 2003 through 31 December 2004. The results indicate that geomagnetic activity had a demonstrable effect on NIV over the sample period. Based on the parameter estimates, out-of-sample predictions of NIV were generated for each half hour over the period of 1 January to 31 March 2005. Consistent with the existence of a causal relationship between geomagnetic activity and the electricity market imbalance, the root-mean-square error of the out-of-sample predictions of NIV is smaller; that is, the predictions are more accurate, when the statistically significant estimated effects of geomagnetic activity are included as drivers in the predictions.

Maternal behavior predicts infant neurophysiological and behavioral attention processes in the first year.

PubMed

Swingler, Margaret M; Perry, Nicole B; Calkins, Susan D; Bell, Martha Ann

2017-01-01

We apply a biopsychosocial conceptualization to attention development in the 1st year and examine the role of neurophysiological and social processes on the development of early attention processes. We tested whether maternal behavior measured during 2 mother-child interaction tasks when infants (N = 388) were 5 months predicted infant medial frontal (F3/F4) EEG power and observed attention behavior during an attention task at 10 months. After controlling for infant attention behavior and EEG power in the same task measured at an earlier 5-month time point, results indicated a significant direct and positive association from 5-month maternal positive affect to infant attention behavior at 10 months. However, maternal positive affect was not related to medial frontal EEG power. In contrast, 5-month maternal intrusive behavior was associated with infants' task-related EEG power change at the left frontal location, F3, at 10 months of age. The test of indirect effects from 5-month maternal intrusiveness to 10-month infant attention behavior via infants' EEG power change at F3 was significant. These findings suggest that the development of neural networks serving attention processes may be 1 mechanism through which early maternal behavior is related to infant attention development in the 1st year and that intrusive maternal behavior may have a particularly disruptive effect on this process. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Selenide isotope generator for the Galileo mission. SIG/Galileo contract compliance power prediction technique

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

Hammel, T.E.; Srinivas, V.

1978-11-01

This initial definition of the power degradation prediction technique outlines a model for predicting SIG/Galileo mean EOM power using component test data and data from a module power degradation demonstration test program. (LCL)

Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2015-09-01

Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

Sex-specific predictive power of 6-minute walk test in chronic heart failure is not enhanced using percent achieved of published reference equations.

PubMed

Frankenstein, Lutz; Zugck, Christian; Nelles, Manfred; Schellberg, Dieter; Katus, Hugo; Remppis, Andrew

2008-04-01

The 6-minute walk test (6MWT) is an established prognostic tool in chronic heart failure. The strong influence of height, weight, age, and sex on 6MWT distance may be accounted for by using percentage achieved of predicted value rather than uncorrected 6MWT values. The study included 1069 patients (862 men) with a mean age 55.2 +/- 11.7 years and mean left ventricular ejection fraction of 29% +/- 10%, attending the heart failure clinic of the University of Heidelberg between 1995 and 2005. The predictive power and accuracy of 6MWT and achieved percentage values according to all available published equations for mortality and mortality or transplant combined were tested separately for each sex. The percentage values varied largely between equations. For all equations, women in New York Heart Association (NYHA) functional class I had higher values than men. Although the 6MWT significantly discriminated all NYHA classes for both sexes, only 1 equation discriminated all NYHA classes. No significant differences in the area under the receiver operating-characteristic curve were noted between achieved percentage values and 6MWT. Despite strong univariate significance, achieved percentage values did not retain multivariate significance. The 6MWT was independent from N-terminal brain natriuretic propeptide, NYHA, left ventricular ejection fraction, and peak oxygen uptake. We confirmed 6MWT to be a strong and independent risk predictor for both sexes. Because the prognostic power of 6MWT is not enhanced using percentage achieved of published reference equations, we suggest recalibration of these reference values rather than discarding this approach.

Lightweight Damage Tolerant Radiators for In-Space Nuclear Electric Power and Propulsion

NASA Technical Reports Server (NTRS)

Craven, Paul; SanSoucie, Michael P.; Tomboulian, Briana; Rogers, Jan; Hyers, Robert

2014-01-01

Nuclear electric propulsion (NEP) is a promising option for high-speed in-space travel due to the high energy density of nuclear power sources and efficient electric thrusters. Advanced power conversion technologies for converting thermal energy from the reactor to electrical energy at high operating temperatures would benefit from lightweight, high temperature radiator materials. Radiator performance dictates power output for nuclear electric propulsion systems. Pitch-based carbon fiber materials have the potential to offer significant improvements in operating temperature and mass. An effort at the NASA Marshall Space Flight Center to show that woven high thermal conductivity carbon fiber mats can be used to replace standard metal and composite radiator fins to dissipate waste heat from NEP systems is ongoing. The goals of this effort are to demonstrate a proof of concept, to show that a significant improvement of specific power (power/mass) can be achieved, and to develop a thermal model with predictive capabilities. A description of this effort is presented.

Error induced by the estimation of the corneal power and the effective lens position with a rotationally asymmetric refractive multifocal intraocular lens

PubMed Central

Piñero, David P.; Camps, Vicente J.; Ramón, María L.; Mateo, Verónica; Pérez-Cambrodí, Rafael J.

2015-01-01

AIM To evaluate the prediction error in intraocular lens (IOL) power calculation for a rotationally asymmetric refractive multifocal IOL and the impact on this error of the optimization of the keratometric estimation of the corneal power and the prediction of the effective lens position (ELP). METHODS Retrospective study including a total of 25 eyes of 13 patients (age, 50 to 83y) with previous cataract surgery with implantation of the Lentis Mplus LS-312 IOL (Oculentis GmbH, Germany). In all cases, an adjusted IOL power (PIOLadj) was calculated based on Gaussian optics using a variable keratometric index value (nkadj) for the estimation of the corneal power (Pkadj) and on a new value for ELP (ELPadj) obtained by multiple regression analysis. This PIOLadj was compared with the IOL power implanted (PIOLReal) and the value proposed by three conventional formulas (Haigis, Hoffer Q and Holladay I). RESULTS PIOLReal was not significantly different than PIOLadj and Holladay IOL power (P>0.05). In the Bland and Altman analysis, PIOLadj showed lower mean difference (-0.07 D) and limits of agreement (of 1.47 and -1.61 D) when compared to PIOLReal than the IOL power value obtained with the Holladay formula. Furthermore, ELPadj was significantly lower than ELP calculated with other conventional formulas (P<0.01) and was found to be dependent on axial length, anterior chamber depth and Pkadj. CONCLUSION Refractive outcomes after cataract surgery with implantation of the multifocal IOL Lentis Mplus LS-312 can be optimized by minimizing the keratometric error and by estimating ELP using a mathematical expression dependent on anatomical factors. PMID:26085998

Error induced by the estimation of the corneal power and the effective lens position with a rotationally asymmetric refractive multifocal intraocular lens.

PubMed

Piñero, David P; Camps, Vicente J; Ramón, María L; Mateo, Verónica; Pérez-Cambrodí, Rafael J

2015-01-01

To evaluate the prediction error in intraocular lens (IOL) power calculation for a rotationally asymmetric refractive multifocal IOL and the impact on this error of the optimization of the keratometric estimation of the corneal power and the prediction of the effective lens position (ELP). Retrospective study including a total of 25 eyes of 13 patients (age, 50 to 83y) with previous cataract surgery with implantation of the Lentis Mplus LS-312 IOL (Oculentis GmbH, Germany). In all cases, an adjusted IOL power (PIOLadj) was calculated based on Gaussian optics using a variable keratometric index value (nkadj) for the estimation of the corneal power (Pkadj) and on a new value for ELP (ELPadj) obtained by multiple regression analysis. This PIOLadj was compared with the IOL power implanted (PIOLReal) and the value proposed by three conventional formulas (Haigis, Hoffer Q and Holladay I). PIOLReal was not significantly different than PIOLadj and Holladay IOL power (P>0.05). In the Bland and Altman analysis, PIOLadj showed lower mean difference (-0.07 D) and limits of agreement (of 1.47 and -1.61 D) when compared to PIOLReal than the IOL power value obtained with the Holladay formula. Furthermore, ELPadj was significantly lower than ELP calculated with other conventional formulas (P<0.01) and was found to be dependent on axial length, anterior chamber depth and Pkadj. Refractive outcomes after cataract surgery with implantation of the multifocal IOL Lentis Mplus LS-312 can be optimized by minimizing the keratometric error and by estimating ELP using a mathematical expression dependent on anatomical factors.

A Copula-Based Conditional Probabilistic Forecast Model for Wind Power Ramps

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

Hodge, Brian S; Krishnan, Venkat K; Zhang, Jie

Efficient management of wind ramping characteristics can significantly reduce wind integration costs for balancing authorities. By considering the stochastic dependence of wind power ramp (WPR) features, this paper develops a conditional probabilistic wind power ramp forecast (cp-WPRF) model based on Copula theory. The WPRs dataset is constructed by extracting ramps from a large dataset of historical wind power. Each WPR feature (e.g., rate, magnitude, duration, and start-time) is separately forecasted by considering the coupling effects among different ramp features. To accurately model the marginal distributions with a copula, a Gaussian mixture model (GMM) is adopted to characterize the WPR uncertaintymore » and features. The Canonical Maximum Likelihood (CML) method is used to estimate parameters of the multivariable copula. The optimal copula model is chosen based on the Bayesian information criterion (BIC) from each copula family. Finally, the best conditions based cp-WPRF model is determined by predictive interval (PI) based evaluation metrics. Numerical simulations on publicly available wind power data show that the developed copula-based cp-WPRF model can predict WPRs with a high level of reliability and sharpness.« less

Beliefs about power and its relation to emotional experience: a comparison of Japan, France, Germany, and the United States.

PubMed

Mondillon, Laurie; Niedenthal, Paula M; Brauer, Markus; Rohmann, Anette; Dalle, Nathalie; Uchida, Yukiko

2005-08-01

This research examined the concept of power in Japan, France, Germany, and the United States, as well as beliefs about the emotions persons in power tend to elicit in others and about powerful people's regulation (specifically, inhibition) of certain emotions. Definitions of power were assessed by examining the importance of two main components: control over self versus other and freedom of action vis-à-vis social norms. Beliefs about both positive (pride, admiration) and negative (jealousy, contempt) emotions were measured. Analyses revealed that the concept of power differed across countries and that the definitions of power as well as country of origin significantly predicted beliefs about the emotions that are elicited in others by powerful people and also the regulation of expression of emotion by powerful people.

Brayton Power Conversion System Parametric Design Modelling for Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Ashe, Thomas L.; Otting, William D.

1993-01-01

The parametrically based closed Brayton cycle (CBC) computer design model was developed for inclusion into the NASA LeRC overall Nuclear Electric Propulsion (NEP) end-to-end systems model. The code is intended to provide greater depth to the NEP system modeling which is required to more accurately predict the impact of specific technology on system performance. The CBC model is parametrically based to allow for conducting detailed optimization studies and to provide for easy integration into an overall optimizer driver routine. The power conversion model includes the modeling of the turbines, alternators, compressors, ducting, and heat exchangers (hot-side heat exchanger and recuperator). The code predicts performance to significant detail. The system characteristics determined include estimates of mass, efficiency, and the characteristic dimensions of the major power conversion system components. These characteristics are parametrically modeled as a function of input parameters such as the aerodynamic configuration (axial or radial), turbine inlet temperature, cycle temperature ratio, power level, lifetime, materials, and redundancy.

Predictors of self-rated health in patients with chronic nonmalignant pain.

PubMed

Siedlecki, Sandra L

2006-09-01

Self-rated health (SRH) is an important outcome measure that has been found to accurately predict mortality, morbidity, function, and psychologic well-being. Chronic nonmalignant pain presents with a pattern that includes low levels of power and high levels of pain, depression, and disability. Differences in SRH may be related to variations within this pattern. The purpose of this analysis was to identify determinants of SRH and test their ability to predict SRH in patients with chronic nonmalignant pain. SRH was measured by response to a single three-option age-comparative question. The Power as Knowing Participation in Change Tool, McGill Pain Questionnaire Short Form, Center for Epidemiological Studies Depression Scale, and Pain Disability Index were used to measure independent variables. Multivariate analysis of variance revealed significant differences (p = .001) between SRH categories on the combined dependent variable. Analysis of variance conducted as a follow-up identified significant differences for power (p < .001) and depression (p = .003), but not for pain or pain-related disability; and discriminant analysis found that power and depression correctly classified patients with 75% accuracy. Findings suggest pain interventions designed to improve mood and provide opportunities for knowing participation may have a greater impact on overall health than those that target only pain and disability.

Changing the approach to treatment choice in epilepsy using big data.

PubMed

Devinsky, Orrin; Dilley, Cynthia; Ozery-Flato, Michal; Aharonov, Ranit; Goldschmidt, Ya'ara; Rosen-Zvi, Michal; Clark, Chris; Fritz, Patty

2016-03-01

A UCB-IBM collaboration explored the application of machine learning to large claims databases to construct an algorithm for antiepileptic drug (AED) choice for individual patients. Claims data were collected between January 2006 and September 2011 for patients with epilepsy > 16 years of age. A subset of patient claims with a valid index date of AED treatment change (new, add, or switch) were used to train the AED prediction model by retrospectively evaluating an index date treatment for subsequent treatment change. Based on the trained model, a model-predicted AED regimen with the lowest likelihood of treatment change was assigned to each patient in the group of test claims, and outcomes were evaluated to test model validity. The model had 72% area under receiver operator characteristic curve, indicating good predictive power. Patients who were given the model-predicted AED regimen had significantly longer survival rates (time until a treatment change event) and lower expected health resource utilization on average than those who received another treatment. The actual prescribed AED regimen at the index date matched the model-predicted AED regimen in only 13% of cases; there were large discrepancies in the frequency of use of certain AEDs/combinations between model-predicted AED regimens and those actually prescribed. Chances of treatment success were improved if patients received the model-predicted treatment. Using the model's prediction system may enable personalized, evidence-based epilepsy care, accelerating the match between patients and their ideal therapy, thereby delivering significantly better health outcomes for patients and providing health-care savings by applying resources more efficiently. Our goal will be to strengthen the predictive power of the model by integrating diverse data sets and potentially moving to prospective data collection. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Emergent self-similarity of cluster coagulation

NASA Astrophysics Data System (ADS)

Pushkin, Dmtiri O.

A wide variety of nonequilibrium processes, such as coagulation of colloidal particles, aggregation of bacteria into colonies, coalescence of rain drops, bond formation between polymerization sites, and formation of planetesimals, fall under the rubric of cluster coagulation. We predict emergence of self-similar behavior in such systems when they are 'forced' by an external source of the smallest particles. The corresponding self-similar coagulation spectra prove to be power laws. Starting from the classical Smoluchowski coagulation equation, we identify the conditions required for emergence of self-similarity and show that the power-law exponent value for a particular coagulation mechanism depends on the homogeneity index of the corresponding coagulation kernel only. Next, we consider the current wave of mergers of large American banks as an 'unorthodox' application of coagulation theory. We predict that the bank size distribution has propensity to become a power law, and verify our prediction in a statistical study of the available economical data. We conclude this chapter by discussing economically significant phenomenon of capital condensation and predicting emergence of power-law distributions in other economical and social data. Finally, we turn to apparent semblance between cluster coagulation and turbulence and conclude that it is not accidental: both of these processes are instances of nonlinear cascades. This class of processes also includes river network formation models, certain force-chain models in granular mechanics, fragmentation due to collisional cascades, percolation, and growing random networks. We characterize a particular cascade by three indicies and show that the resulting power-law spectrum exponent depends on the indicies values only. The ensuing algebraic formula is remarkable for its simplicity.

Suitability of the HAM-Nat test and TMS module "basic medical-scientific understanding" for medical school selection

PubMed Central

Hissbach, Johanna; Feddersen, Lena; Sehner, Susanne; Hampe, Wolfgang

2012-01-01

Aims: Tests with natural-scientific content are predictive of the success in the first semesters of medical studies. Some universities in the German speaking countries use the ‘Test for medical studies’ (TMS) for student selection. One of its test modules, namely “medical and scientific comprehension”, measures the ability for deductive reasoning. In contrast, the Hamburg Assessment Test for Medicine, Natural Sciences (HAM-Nat) evaluates knowledge in natural sciences. In this study the predictive power of the HAM-Nat test will be compared to that of the NatDenk test, which is similar to the TMS module “medical and scientific comprehension” in content and structure. Methods: 162 medical school beginners volunteered to complete either the HAM-Nat (N=77) or the NatDenk test (N=85) in 2007. Until spring 2011, 84.2% of these successfully completed the first part of the medical state examination in Hamburg. Via different logistic regression models we tested the predictive power of high school grade point average (GPA or “Abiturnote”) and the test results (HAM-Nat and NatDenk) with regard to the study success criterion “first part of the medical state examination passed successfully up to the end of the 7th semester” (Success7Sem). The Odds Ratios (OR) for study success are reported. Results: For both test groups a significant correlation existed between test results and study success (HAM-Nat: OR=2.07; NatDenk: OR=2.58). If both admission criteria are estimated in one model, the main effects (GPA: OR=2.45; test: OR=2.32) and their interaction effect (OR=1.80) are significant in the HAM-Nat test group, whereas in the NatDenk test group only the test result (OR=2.21) significantly contributes to the variance explained. Conclusions: On their own both HAM-Nat and NatDenk have predictive power for study success, but only the HAM-Nat explains additional variance if combined with GPA. The selection according to HAM-Nat and GPA has under the current circumstances of medical school selection (many good applicants and only a limited number of available spaces) the highest predictive power of all models. PMID:23255967

Power load prediction based on GM (1,1)

NASA Astrophysics Data System (ADS)

Wu, Di

2017-05-01

Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

A Predictive Model of Intein Insertion Site for Use in the Engineering of Molecular Switches

PubMed Central

Apgar, James; Ross, Mary; Zuo, Xiao; Dohle, Sarah; Sturtevant, Derek; Shen, Binzhang; de la Vega, Humberto; Lessard, Philip; Lazar, Gabor; Raab, R. Michael

2012-01-01

Inteins are intervening protein domains with self-splicing ability that can be used as molecular switches to control activity of their host protein. Successfully engineering an intein into a host protein requires identifying an insertion site that permits intein insertion and splicing while allowing for proper folding of the mature protein post-splicing. By analyzing sequence and structure based properties of native intein insertion sites we have identified four features that showed significant correlation with the location of the intein insertion sites, and therefore may be useful in predicting insertion sites in other proteins that provide native-like intein function. Three of these properties, the distance to the active site and dimer interface site, the SVM score of the splice site cassette, and the sequence conservation of the site showed statistically significant correlation and strong predictive power, with area under the curve (AUC) values of 0.79, 0.76, and 0.73 respectively, while the distance to secondary structure/loop junction showed significance but with less predictive power (AUC of 0.54). In a case study of 20 insertion sites in the XynB xylanase, two features of native insertion sites showed correlation with the splice sites and demonstrated predictive value in selecting non-native splice sites. Structural modeling of intein insertions at two sites highlighted the role that the insertion site location could play on the ability of the intein to modulate activity of the host protein. These findings can be used to enrich the selection of insertion sites capable of supporting intein splicing and hosting an intein switch. PMID:22649521

Effect of accuracy of wind power prediction on power system operator

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

Idiopathic normal pressure hydrocephalus, quantitative EEG findings, and the cerebrospinal fluid tap test: a pilot study.

PubMed

Seo, Jong-Geun; Kang, Kyunghun; Jung, Ji-Young; Park, Sung-Pa; Lee, Maan-Gee; Lee, Ho-Won

2014-12-01

In this pilot study, we analyzed relationships between quantitative EEG measurements and clinical parameters in idiopathic normal pressure hydrocephalus patients, along with differences in these quantitative EEG markers between cerebrospinal fluid tap test responders and nonresponders. Twenty-six idiopathic normal pressure hydrocephalus patients (9 cerebrospinal fluid tap test responders and 17 cerebrospinal fluid tap test nonresponders) constituted the final group for analysis. The resting EEG was recorded and relative powers were computed for seven frequency bands. Cerebrospinal fluid tap test nonresponders, when compared with responders, showed a statistically significant increase in alpha2 band power at the right frontal and centrotemporal regions. Higher delta2 band powers in the frontal, central, parietal, and occipital regions and lower alpha1 band powers in the right temporal region significantly correlated with poorer cognitive performance. Higher theta1 band powers in the left parietal and occipital regions significantly correlated with gait dysfunction. And higher delta1 band powers in the right frontal regions significantly correlated with urinary disturbance. Our findings may encourage further research using quantitative EEG in patients with ventriculomegaly as a potential electrophysiological marker for predicting cerebrospinal fluid tap test responders. This study additionally suggests that the delta, theta, and alpha bands are statistically correlated with the severity of symptoms in idiopathic normal pressure hydrocephalus patients.

Are power calculations useful? A multicentre neuroimaging study

PubMed Central

Suckling, John; Henty, Julian; Ecker, Christine; Deoni, Sean C; Lombardo, Michael V; Baron-Cohen, Simon; Jezzard, Peter; Barnes, Anna; Chakrabarti, Bhismadev; Ooi, Cinly; Lai, Meng-Chuan; Williams, Steven C; Murphy, Declan GM; Bullmore, Edward

2014-01-01

There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources. PMID:24644267

Modeling of detachment experiments at DIII-D

DOE PAGES

Canik, John M.; Briesemeister, Alexis R.; Lasnier, C. J.; ...

2014-11-26

Edge fluid–plasma/kinetic–neutral modeling of well-diagnosed DIII-D experiments is performed in order to document in detail how well certain aspects of experimental measurements are reproduced within the model as the transition to detachment is approached. Results indicate, that at high densities near detachment onset, the poloidal temperature profile produced in the simulations agrees well with that measured in experiment. However, matching the heat flux in the model requires a significant increase in the radiated power compared to what is predicted using standard chemical sputtering rates. Lastly, these results suggest that the model is adequate to predict the divertor temperature, provided thatmore » the discrepancy in radiated power level can be resolved.« less

Predicting High-Power Performance in Professional Cyclists.

PubMed

Sanders, Dajo; Heijboer, Mathieu; Akubat, Ibrahim; Meijer, Kenneth; Hesselink, Matthijs K

2017-03-01

To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists. Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model. The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model. This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

Prediction of silicon oxynitride plasma etching using a generalized regression neural network

NASA Astrophysics Data System (ADS)

Kim, Byungwhan; Lee, Byung Teak

2005-08-01

A prediction model of silicon oxynitride (SiON) etching was constructed using a neural network. Model prediction performance was improved by means of genetic algorithm. The etching was conducted in a C2F6 inductively coupled plasma. A 24 full factorial experiment was employed to systematically characterize parameter effects on SiON etching. The process parameters include radio frequency source power, bias power, pressure, and C2F6 flow rate. To test the appropriateness of the trained model, additional 16 experiments were conducted. For comparison, four types of statistical regression models were built. Compared to the best regression model, the optimized neural network model demonstrated an improvement of about 52%. The optimized model was used to infer etch mechanisms as a function of parameters. The pressure effect was noticeably large only as relatively large ion bombardment was maintained in the process chamber. Ion-bombardment-activated polymer deposition played the most significant role in interpreting the complex effect of bias power or C2F6 flow rate. Moreover, [CF2] was expected to be the predominant precursor to polymer deposition.

A First Look at Electric Motor Noise For Future Propulsion Systems

NASA Technical Reports Server (NTRS)

Huff, Dennis L.; Henderson, Brenda S.; Envia, Edmane

2016-01-01

Motor tone predictions using a vibration analysis and input from design parameters for high power density motors show that the noise can be significantly higher or lower than the empirical correlations and exceeds the stated uncertainty.

Relevance of genetic relationship in GWAS and genomic prediction.

PubMed

Pereira, Helcio Duarte; Soriano Viana, José Marcelo; Andrade, Andréa Carla Bastos; Fonseca E Silva, Fabyano; Paes, Geísa Pinheiro

2018-02-01

The objective of this study was to analyze the relevance of relationship information on the identification of low heritability quantitative trait loci (QTLs) from a genome-wide association study (GWAS) and on the genomic prediction of complex traits in human, animal and cross-pollinating populations. The simulation-based data sets included 50 samples of 1000 individuals of seven populations derived from a common population with linkage disequilibrium. The populations had non-inbred and inbred progeny structure (50 to 200) with varying number of members (5 to 20). The individuals were genotyped for 10,000 single nucleotide polymorphisms (SNPs) and phenotyped for a quantitative trait controlled by 10 QTLs and 90 minor genes showing dominance. The SNP density was 0.1 cM and the narrow sense heritability was 25%. The QTL heritabilities ranged from 1.1 to 2.9%. We applied mixed model approaches for both GWAS and genomic prediction using pedigree-based and genomic relationship matrices. For GWAS, the observed false discovery rate was kept below the significance level of 5%, the power of detection for the low heritability QTLs ranged from 14 to 50%, and the average bias between significant SNPs and a QTL ranged from less than 0.01 to 0.23 cM. The QTL detection power was consistently higher using genomic relationship matrix. Regardless of population and training set size, genomic prediction provided higher prediction accuracy of complex trait when compared to pedigree-based prediction. The accuracy of genomic prediction when there is relatedness between individuals in the training set and the reference population is much higher than the value for unrelated individuals.

Aerobic power and anthropometric characteristics of elite basketball referees.

PubMed

Leicht, A S

2007-03-01

The current study aimed to document the aerobic power and body composition of elite basketball referees. Prior to the 2000/2001 Men's National Basketball League season, 25 male elite referees completed the Multistage Shuttle run test followed by body composition (body fat%) determination via bioelectrical impedance (BI) (Adult and Athlete modes) and a restricted anthropometric profile. Significant correlations between BI and anthropometric measures were examined via Pearson product correlation coefficients. Referees demonstrated a mean (SD) aerobic power of 50.8 (3.2) mL . kg-1 . min(-1) and body fat% of 23.8% (8.4%). Body fat% was similar for BI (Adult) and several anthropometric equations. Significant correlations were obtained between BI (Adult) and body fat%, and BI (Adult) and sum of skinfolds. Similar correlations were obtained for BI (Athlete) mode despite a significantly lower body fat%. Regression equations for the prediction of body fat% and sum of skinfolds from BI (Adult) were determined. Elite basketball referees demonstrated significantly greater aerobic power and similar body composition to the general community. In the euhydrated state, BI (Adult) provided a valid measurement of body fat% in elite basketball referees.

Preschool Neuropsychological Measures as Predictors of Later Attention Deficit Hyperactivity Disorder

PubMed Central

Breaux, Rosanna P.; Griffith, Shayl F.; Harvey, Elizabeth A.

2016-01-01

The present study examined preschool neuropsychological measures as predictors of school-age attention deficit hyperactivity disorder (ADHD). Participants included 168 children (91 males) who completed neuropsychological measures at ages 3 and 4, and who were evaluated for ADHD and oppositional defiant disorder at age 6. The Conners’ Kiddie Continuous Performance Test (K-CPT), NEPSY Statue subtest, and a delay aversion task significantly distinguished at-risk children who later did and did not meet criteria for ADHD, with poor to fair overall predictive power, specificity, and sensitivity. However, only the K-CPT ADHD Confidence Index and battery added incremental predictive validity beyond early ADHD symptoms. This battery approach, which required impairment on at least 2 of the 3 significant measures, yielded fair overall predictive power, specificity, and sensitivity, and correctly classified 67% of children. In addition, there was some support for the specificity hypothesis, with evidence that cool executive function measures (K-CPT and Statue subtest) tended to predict inattentive symptoms. These findings suggest that neuropsychological deficits are evident by preschool-age in children with ADHD, but neuropsychological tests may still misclassify approximately one-third of children if used alone. Thus, neuropsychological measures may be a useful component of early ADHD assessments, but should be used with caution and in combination with other assessment methods. PMID:26936037

Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

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

Melin, Alexander M.; Olama, Mohammed M.; Dong, Jin

The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed tomore » estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.« less

The effects of power, leadership and psychological safety on resident event reporting.

PubMed

Appelbaum, Nital P; Dow, Alan; Mazmanian, Paul E; Jundt, Dustin K; Appelbaum, Eric N

2016-03-01

Although the reporting of adverse events is a necessary first step in identifying and addressing lapses in patient safety, such events are under-reported, especially by frontline providers such as resident physicians. This study describes and tests relationships between power distance and leader inclusiveness on psychological safety and the willingness of residents to report adverse events. A total of 106 resident physicians from the departments of neurosurgery, orthopaedic surgery, emergency medicine, otolaryngology, neurology, obstetrics and gynaecology, paediatrics and general surgery in a mid-Atlantic teaching hospital were asked to complete a survey on psychological safety, perceived power distance, leader inclusiveness and intention to report adverse events. Perceived power distance (β = -0.26, standard error [SE] 0.06, 95% confidence interval [CI] -0.37 to 0.15; p < 0.001) and leader inclusiveness (β = 0.51; SE 0.07, 95% CI 0.38-0.65; p < 0.001) both significantly predicted psychological safety, which, in turn, significantly predicted intention to report adverse events (β = 0.34; SE 0.08, 95% CI 0.18-0.49; p < 0.001). Psychological safety significantly mediated the direct relationship between power distance and intention to report adverse events (indirect effect: -0.09; SE 0.02, 95% CI -0.13 to 0.04; p < 0.001). Psychological safety also significantly mediated the direct relationship between leader inclusiveness and intention to report adverse events (indirect effect: 0.17; SE 0.02, 95% CI 0.08-0.27; p = 0.001). Psychological safety was found to be a predictor of intention to report adverse events. Perceived power distance and leader inclusiveness both influenced the reporting of adverse events through the concept of psychological safety. Because adverse event reporting is shaped by relationships and culture external to the individual, it should be viewed as an organisational as much as a personal function. Supervisors and other leaders in health care should ensure that policies, procedures and leadership practices build psychological safety and minimise power distance between low- and high-status members in order to support greater reporting of adverse events. © 2016 John Wiley & Sons Ltd.

Short-term load and wind power forecasting using neural network-based prediction intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Comparison of simulation results with sea-level experimental data on 10(14) - 10(16) air shower cores

NASA Technical Reports Server (NTRS)

Ash, A. G.

1985-01-01

Simulation predictions for the Leeds 35 sq m horizontal discharge chamber array for proton primaries with a approx. E sup 2.7 spectrum extrapolated from balloon data to 10 to the 16th power eV give power law rho (r)-spectra with constant slope approx. -2 consistent with the experimental data up to the point at which they steepen but overshooting them at higher densities, and at high shower sizes predicted cores which are significantly steeper than those observed. Further comparisons with results for heavy nuclei primaries (up to A = 56) point to the inadequacy of changes in primary composition to account for the observed density spectra and core flattening, and the shower size spectrum together, and point, therefore, to the failure of the scaling interaction model at approx. 10 to the 15th power eV primary energy.

Towards a renewal of the propeller in aeronautics

NASA Technical Reports Server (NTRS)

Berger, D.; Jacquet, P.

1985-01-01

The reasons for reconsidering the propeller for aircraft propulsion, the areas of application, and necessary developments are considered. Rising fuel costs and an increasing theoretical and experimental data base for turboprop engines have demonstrated that significant cost savings can be realized by the use of propellers. Propellers are well-suited to powering aircraft traveling at speeds up to Mach 0.65. Work is progressing on the development of a 150 seat aircraft which has a cruise speed of Mach 0.8, powered by a turboprop attached to an engine of 15,000 shp. Aeroelasticity analyses ae necessary in order to characterize the behavior of thin profile propfan blades, particularly to predict the oscillations through the entire functional range. High-power reducers must be developed, and the level of cabin noise must be controlled to less than 90 dB. Commercial applications are predicted for turboprops in specific instances.

Identification of the Best Anthropometric Predictors of Serum High- and Low-Density Lipoproteins Using Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2015-09-01

Serum high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol levels are associated with risk factors for various diseases and are related to anthropometric measures. However, controversy remains regarding the best anthropometric indicators of the HDL and LDL cholesterol levels. The objectives of this study were to identify the best predictors of HDL and LDL cholesterol using statistical analyses and two machine learning algorithms and to compare the predictive power of combined anthropometric measures in Korean adults. A total of 13,014 subjects participated in this study. The anthropometric measures were assessed with binary logistic regression (LR) to evaluate statistically significant differences between the subjects with normal and high LDL cholesterol levels and between the subjects with normal and low HDL cholesterol levels. LR and the naive Bayes algorithm (NB), which provides more reasonable and reliable results, were used in the analyses of the predictive power of individual and combined measures. The best predictor of HDL was the rib to hip ratio (p =< 0.0001; odds ratio (OR) = 1.895; area under curve (AUC) = 0.681) in women and the waist to hip ratio (WHR) (p =< 0.0001; OR = 1.624; AUC = 0.633) in men. In women, the strongest indicator of LDL was age (p =< 0.0001; OR = 1.662; AUC by NB = 0.653 ; AUC by LR = 0.636). Among the anthropometric measures, the body mass index (BMI), WHR, forehead to waist ratio, forehead to rib ratio, and forehead to chest ratio were the strongest predictors of LDL; these measures had similar predictive powers. The strongest predictor in men was BMI (p =< 0.0001; OR = 1.369; AUC by NB = 0.594; AUC by LR = 0.595 ). The predictive power of almost all individual anthropometric measures was higher for HDL than for LDL, and the predictive power for both HDL and LDL in women was higher than for men. A combination of anthropometric measures slightly improved the predictive power for both HDL and LDL cholesterol. The best indicator for HDL and LDL might differ according to the type of cholesterol and the gender. In women, but not men, age was the variable that strongly predicted HDL and LDL cholesterol levels. Our findings provide new information for the development of better initial screening tools for HDL and LDL cholesterol.

Power Relative to Body Mass Best Predicts Change in Core Temperature During Exercise-Heat Stress.

PubMed

Gibson, Oliver R; Willmott, Ashley G B; James, Carl A; Hayes, Mark; Maxwell, Neil S

2017-02-01

Gibson, OR, Willmott, AGB, James, CA, Hayes, M, and Maxwell, NS. Power relative to body mass best predicts change in core temperature during exercise-heat stress. J Strength Cond Res 31(2): 403-414, 2017-Controlling internal temperature is crucial when prescribing exercise-heat stress, particularly during interventions designed to induce thermoregulatory adaptations. This study aimed to determine the relationship between the rate of rectal temperature (Trec) increase, and various methods for prescribing exercise-heat stress, to identify the most efficient method of prescribing isothermic heat acclimation (HA) training. Thirty-five men cycled in hot conditions (40° C, 39% R.H.) for 29 ± 2 minutes. Subjects exercised at 60 ± 9% V[Combining Dot Above]O2peak, with methods for prescribing exercise retrospectively observed for each participant. Pearson product moment correlations were calculated for each prescriptive variable against the rate of change in Trec (° C·h), with stepwise multiple regressions performed on statistically significant variables (p ≤ 0.05). Linear regression identified the predicted intensity required to increase Trec by 1.0-2.0° C between 20- and 45-minute periods and the duration taken to increase Trec by 1.5° C in response to incremental intensities to guide prescription. Significant (p ≤ 0.05) relationships with the rate of change in Trec were observed for prescriptions based on relative power (W·kg; r = 0.764), power (%Powermax; r = 0.679), rating of perceived exertion (RPE) (r = 0.577), V[Combining Dot Above]O2 (%V[Combining Dot Above]O2peak; r = 0.562), heart rate (HR) (%HRmax; r = 0.534), and thermal sensation (r = 0.311). Stepwise multiple regressions observed relative power and RPE as variables to improve the model (r = 0.791), with no improvement after inclusion of any anthropometric variable. Prescription of exercise under heat stress using power (W·kg or %Powermax) has the strongest relationship with the rate of change in Trec with no additional requirement to correct for body composition within a normal range. Practitioners should therefore prescribe exercise intensity using relative power during isothermic HA training to increase Trec efficiently and maximize adaptation.

Spatiotemporal property and predictability of large-scale human mobility

NASA Astrophysics Data System (ADS)

Zhang, Hai-Tao; Zhu, Tao; Fu, Dongfei; Xu, Bowen; Han, Xiao-Pu; Chen, Duxin

2018-04-01

Spatiotemporal characteristics of human mobility emerging from complexity on individual scale have been extensively studied due to the application potential on human behavior prediction and recommendation, and control of epidemic spreading. We collect and investigate a comprehensive data set of human activities on large geographical scales, including both websites browse and mobile towers visit. Numerical results show that the degree of activity decays as a power law, indicating that human behaviors are reminiscent of scale-free random walks known as Lévy flight. More significantly, this study suggests that human activities on large geographical scales have specific non-Markovian characteristics, such as a two-segment power-law distribution of dwelling time and a high possibility for prediction. Furthermore, a scale-free featured mobility model with two essential ingredients, i.e., preferential return and exploration, and a Gaussian distribution assumption on the exploration tendency parameter is proposed, which outperforms existing human mobility models under scenarios of large geographical scales.

On-line self-learning time forward voltage prognosis for lithium-ion batteries using adaptive neuro-fuzzy inference system

NASA Astrophysics Data System (ADS)

Fleischer, Christian; Waag, Wladislaw; Bai, Ziou; Sauer, Dirk Uwe

2013-12-01

The battery management system (BMS) of a battery-electric road vehicle must ensure an optimal operation of the electrochemical storage system to guarantee for durability and reliability. In particular, the BMS must provide precise information about the battery's state-of-functionality, i.e. how much dis-/charging power can the battery accept at current state and condition while at the same time preventing it from operating outside its safe operating area. These critical limits have to be calculated in a predictive manner, which serve as a significant input factor for the supervising vehicle energy management (VEM). The VEM must provide enough power to the vehicle's drivetrain for certain tasks and especially in critical driving situations. Therefore, this paper describes a new approach which can be used for state-of-available-power estimation with respect to lowest/highest cell voltage prediction using an adaptive neuro-fuzzy inference system (ANFIS). The estimated voltage for a given time frame in the future is directly compared with the actual voltage, verifying the effectiveness and accuracy of a relative voltage prediction error of less than 1%. Moreover, the real-time operating capability of the proposed algorithm was verified on a battery test bench while running on a real-time system performing voltage prediction.

Development and validation of a shared decision-making instrument for health-related quality of life one year after total hip replacement based on quality registries data.

PubMed

Nemes, Szilard; Rolfson, Ola; Garellick, Göran

2018-02-01

Clinicians considering improvements in health-related quality of life (HRQoL) after total hip replacement (THR) must account for multiple pieces of information. Evidence-based decisions are important to best assess the effect of THR on HRQoL. This work aims at constructing a shared decision-making tool that helps clinicians assessing the future benefits of THR by offering predictions of 1-year postoperative HRQoL of THR patients. We used data from the Swedish Hip Arthroplasty Register. Data from 2008 were used as training set and data from 2009 to 2012 as validation set. We adopted two approaches. First, we assumed a continuous distribution for the EQ-5D index and modelled the postoperative EQ-5D index with regression models. Second, we modelled the five dimensions of the EQ-5D and weighted together the predictions using the UK Time Trade-Off value set. As predictors, we used preoperative EQ-5D dimensions and the EQ-5D index, EQ visual analogue scale, visual analogue scale pain, Charnley classification, age, gender, body mass index, American Society of Anesthesiologists, surgical approach and prosthesis type. Additionally, the tested algorithms were combined in a single predictive tool by stacking. Best predictive power was obtained by the multivariate adaptive regression splines (R 2  = 0.158). However, this was not significantly better than the predictive power of linear regressions (R 2  = 0.157). The stacked model had a predictive power of 17%. Successful implementation of a shared decision-making tool that can aid clinicians and patients in understanding expected improvement in HRQoL following THR would require higher predictive power than we achieved. For a shared decision-making tool to succeed, further variables, such as socioeconomics, need to be considered. © 2016 John Wiley & Sons, Ltd.

Predicting outcome of Internet-based treatment for depressive symptoms.

PubMed

Warmerdam, Lisanne; Van Straten, Annemieke; Twisk, Jos; Cuijpers, Pim

2013-01-01

In this study we explored predictors and moderators of response to Internet-based cognitive behavioral therapy (CBT) and Internet-based problem-solving therapy (PST) for depressive symptoms. The sample consisted of 263 participants with moderate to severe depressive symptoms. Of those, 88 were randomized to CBT, 88 to PST and 87 to a waiting list control condition. Outcomes were improvement and clinically significant change in depressive symptoms after 8 weeks. Higher baseline depression and higher education predicted improvement, while higher education, less avoidance behavior and decreased rational problem-solving skills predicted clinically significant change across all groups. No variables were found that differentially predicted outcome between Internet-based CBT and Internet-based PST. More research is needed with sufficient power to investigate predictors and moderators of response to reveal for whom Internet-based therapy is best suited.

The Power Spectrum of Ionic Nanopore Currents: The Role of Ion Correlations.

PubMed

Zorkot, Mira; Golestanian, Ramin; Bonthuis, Douwe Jan

2016-04-13

We calculate the power spectrum of electric-field-driven ion transport through nanometer-scale membrane pores using both linearized mean-field theory and Langevin dynamics simulations. Remarkably, the linearized mean-field theory predicts a plateau in the power spectral density at low frequency ω, which is confirmed by the simulations at low ion concentration. At high ion concentration, however, the power spectral density follows a power law that is reminiscent of the 1/ω(α) dependence found experimentally at low frequency. On the basis of simulations with and without ion-ion interactions, we attribute the low-frequency power-law dependence to ion-ion correlations. We show that neither a static surface charge density, nor an increased pore length, nor an increased ion valency have a significant effect on the shape of the power spectral density at low frequency.

Local Thermonuclear Runaways in Dwarf Novae?

NASA Astrophysics Data System (ADS)

Shara, Michael

2012-10-01

We have no hope of understanding the structure and evolution of a class of astrophysical objects if we cannot identify the dominant energy source of those objects.The Disk Instability Model {DIM} postulates that Dwarf Nova {DN} outbursts are powered by runaway accretion from an accretion disk onto a White Dwarf {WD} in a red dwarf-WD mass transferring binary. Ominously, HST observations {e.g. Sion et al. 2001} of WD surface abundances hint at a significant shortcoming of the DIM. The data from the present proposal will be able to unequivocally demonstrate if the observed highly Carbon-depleted and Nitrogen-enhanced abundances on WD surfaces {NOT predicted by DIM} vary with binary orbital phase, or throughout a DN quiescence cycle, or from cycle to cycle. These same data will test if predicted {but never observed} Local Thermonuclear Runaways {"Nuclear-powered mini-novas"} occur on the WDs of DN. Such events could trigger or even power DN, providing the long-sought physical mechanism of DN eruptions that DIM lacks. As a "free" bonus, the same data may also directly detect the diffusion of accreted metals in a WD atmosphere for the first time, or provide significant limits on the diffusion rate.

The phase of prestimulus alpha oscillations affects tactile perception.

PubMed

Ai, Lei; Ro, Tony

2014-03-01

Previous studies have shown that neural oscillations in the 8- to 12-Hz range influence sensory perception. In the current study, we examined whether both the power and phase of these mu/alpha oscillations predict successful conscious tactile perception. Near-threshold tactile stimuli were applied to the left hand while electroencephalographic (EEG) activity was recorded over the contralateral right somatosensory cortex. We found a significant inverted U-shaped relationship between prestimulus mu/alpha power and detection rate, suggesting that there is an intermediate level of alpha power that is optimal for tactile perception. We also found a significant difference in phase angle concentration at stimulus onset that predicted whether the upcoming tactile stimulus was perceived or missed. As has been shown in the visual system, these findings suggest that these mu/alpha oscillations measured over somatosensory areas exert a strong inhibitory control on tactile perception and that pulsed inhibition by these oscillations shapes the state of brain activity necessary for conscious perception. They further suggest that these common phasic processing mechanisms across different sensory modalities and brain regions may reflect a common underlying encoding principle in perceptual processing that leads to momentary windows of perceptual awareness.

Power-constrained supercomputing

NASA Astrophysics Data System (ADS)

Bailey, Peter E.

As we approach exascale systems, power is turning from an optimization goal to a critical operating constraint. With power bounds imposed by both stakeholders and the limitations of existing infrastructure, achieving practical exascale computing will therefore rely on optimizing performance subject to a power constraint. However, this requirement should not add to the burden of application developers; optimizing the runtime environment given restricted power will primarily be the job of high-performance system software. In this dissertation, we explore this area and develop new techniques that extract maximum performance subject to a particular power constraint. These techniques include a method to find theoretical optimal performance, a runtime system that shifts power in real time to improve performance, and a node-level prediction model for selecting power-efficient operating points. We use a linear programming (LP) formulation to optimize application schedules under various power constraints, where a schedule consists of a DVFS state and number of OpenMP threads for each section of computation between consecutive message passing events. We also provide a more flexible mixed integer-linear (ILP) formulation and show that the resulting schedules closely match schedules from the LP formulation. Across four applications, we use our LP-derived upper bounds to show that current approaches trail optimal, power-constrained performance by up to 41%. This demonstrates limitations of current systems, and our LP formulation provides future optimization approaches with a quantitative optimization target. We also introduce Conductor, a run-time system that intelligently distributes available power to nodes and cores to improve performance. The key techniques used are configuration space exploration and adaptive power balancing. Configuration exploration dynamically selects the optimal thread concurrency level and DVFS state subject to a hardware-enforced power bound. Adaptive power balancing efficiently predicts where critical paths are likely to occur and distributes power to those paths. Greater power, in turn, allows increased thread concurrency levels, CPU frequency/voltage, or both. We describe these techniques in detail and show that, compared to the state-of-the-art technique of using statically predetermined, per-node power caps, Conductor leads to a best-case performance improvement of up to 30%, and an average improvement of 19.1%. At the node level, an accurate power/performance model will aid in selecting the right configuration from a large set of available configurations. We present a novel approach to generate such a model offline using kernel clustering and multivariate linear regression. Our model requires only two iterations to select a configuration, which provides a significant advantage over exhaustive search-based strategies. We apply our model to predict power and performance for different applications using arbitrary configurations, and show that our model, when used with hardware frequency-limiting in a runtime system, selects configurations with significantly higher performance at a given power limit than those chosen by frequency-limiting alone. When applied to a set of 36 computational kernels from a range of applications, our model accurately predicts power and performance; our runtime system based on the model maintains 91% of optimal performance while meeting power constraints 88% of the time. When the runtime system violates a power constraint, it exceeds the constraint by only 6% in the average case, while simultaneously achieving 54% more performance than an oracle. Through the combination of the above contributions, we hope to provide guidance and inspiration to research practitioners working on runtime systems for power-constrained environments. We also hope this dissertation will draw attention to the need for software and runtime-controlled power management under power constraints at various levels, from the processor level to the cluster level.

Prediction of Wind Energy Resources (PoWER) Users Guide

DTIC Science & Technology

2016-01-01

ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER...2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) 09/2015–11/2015 4. TITLE AND SUBTITLE Prediction of Wind Energy Resources (PoWER) User’s

Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

PubMed

Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

2017-10-12

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

Age, body mass, and gender as predictors of masters olympic weightlifting performance.

PubMed

Thé, Dwight J; Ploutz-Snyder, Lori

2003-07-01

The purpose of this study was to examine previously collected performance scores from the 2000 World Masters Weightlifting Championships to 1). determine the extent to which age and body mass are related to and predictive of indirect estimates of absolute and relative muscular power, and 2). assess possible gender differences in these associations. Dependent variables were absolute load (ABS = heaviest snatch [kg] + heaviest clean and jerk [kg]) and relative load (REL = ABS [kg]/body mass [kg]), representing indirect estimates of absolute and relative muscular power, respectively. Predictor variables were age (yr) and body mass (kg). Linear regression and various diagnostic procedures were used to analyze the data. The linear model provided an adequate fit for the data because no departures from the usual assumptions of normally distributed variables and homoscedastic error variance were observed. All predictor variables were significantly (P < 0.05) predictive of the dependent variables, but the magnitude of associations (e.g., R(ABS|BM) = 0.18 among females vs R(ABS|BM) = 0.57 among males) and extent of predictive ability (e.g., R(adj)2 for regression of ABS on age and body mass was 0.18-0.58 among females vs 0.74-0.83 among males) were significantly (P < 0.05) higher among males versus females. The extent to which age and body mass explain differences in muscular power differs between female and male masters weightlifters, but the rate of decline (%.yr-1) in power with advancing age is similar and is in agreement with previous reports for world record holders, other masters athletes, and healthy, untrained individuals, suggesting the importance of the aging process itself over physical activity history.

Agreement and clinical comparison between a new swept-source optical coherence tomography-based optical biometer and an optical low-coherence reflectometry biometer

PubMed Central

Arriola-Villalobos, P; Almendral-Gómez, J; Garzón, N; Ruiz-Medrano, J; Fernández-Pérez, C; Martínez-de-la-Casa, J M; Díaz-Valle, D

2017-01-01

Purpose To compare measurements taken using a swept-source optical coherence tomography-based optical biometer (IOLmaster 700) and an optical low-coherence reflectometry biometer (Lenstar 900), and to determine the clinical impacts of differences in their measurements on intraocular lens (IOL) power predictions. Methods Eighty eyes of 80 patients scheduled to undergo cataract surgery were examined with both biometers. The measurements made using each device were axial length (AL), central corneal thickness (CCT), aqueous depth (AQD), lens thickness (LT), mean keratometry (MK), white-to-white distance (WTW), and pupil diameter (PD). Holladay 2 and SRK/T formulas were used to calculate IOL power. Differences in measurement between the two biometers were determined using the paired t-test. Agreement was assessed through intraclass correlation coefficients (ICC) and Bland–Altman plots. Results Mean patient age was 76.3±6.8 years (range 59–89). Using the Lenstar, AL and PD could not be measured in 12.5 and 5.25% of eyes, respectively, while IOLMaster 700 took all measurements in all eyes. The variables CCT, AQD, LT, and MK varied significantly between the two biometers. According to ICCs, correlation between measurements made with both devices was excellent except for WTW and PD. Using the SRK/T formula, IOL power prediction based on the data from the two devices were statistically different, but differences were not clinically significant. Conclusions No clinically relevant differences were detected between the biometers in terms of their measurements and IOL power predictions. Using the IOLMaster 700, it was easier to obtain biometric measurements in eyes with less transparent ocular media or longer AL. PMID:27834962

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

The aerodynamic cost of flight in the short-tailed fruit bat (Carollia perspicillata): comparing theory with measurement

PubMed Central

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Voigt, Christian C.; Breuer, Kenneth S.

2014-01-01

Aerodynamic theory has long been used to predict the power required for animal flight, but widely used models contain many simplifications. It has been difficult to ascertain how closely biological reality matches model predictions, largely because of the technical challenges of accurately measuring the power expended when an animal flies. We designed a study to measure flight speed-dependent aerodynamic power directly from the kinetic energy contained in the wake of bats flying in a wind tunnel. We compared these measurements with two theoretical predictions that have been used for several decades in diverse fields of vertebrate biology and to metabolic measurements from a previous study using the same individuals. A high-accuracy displaced laser sheet stereo particle image velocimetry experimental design measured the wake velocities in the Trefftz plane behind four bats flying over a range of speeds (3–7 m s−1). We computed the aerodynamic power contained in the wake using a novel interpolation method and compared these results with the power predicted by Pennycuick's and Rayner's models. The measured aerodynamic power falls between the two theoretical predictions, demonstrating that the models effectively predict the appropriate range of flight power, but the models do not accurately predict minimum power or maximum range speeds. Mechanical efficiency—the ratio of aerodynamic power output to metabolic power input—varied from 5.9% to 9.8% for the same individuals, changing with flight speed. PMID:24718450

Misalignment tolerable coil structure for biomedical applications with wireless power transfer.

PubMed

Chow, Jeff P W; Chen, Nan; Chung, Henry S H; Chan, Leanne L H

2013-01-01

Coil-misalignment is one of the major hurdles for inductively coupled wireless power transfer in applications like retinal prosthesis. Weak magnetic flux linkage due to coil misalignments would significantly impair the power efficiency. A novel receiver configuration with high misalignment tolerance is presented in this paper. The proposed receiver is composed of two receiver coils placed orthogonally, so as to reduce the variation of mutual inductance between transmitting and receiving coils under misalignment conditions. Three different receiver coil structures are analyzed and compared using the same length of wire. Theoretical predictions have been confirmed with measurement results.

Preliminary investigation of power flow and electrode phenomena in a multi-megawatt coaxial plasma thruster

NASA Technical Reports Server (NTRS)

Schoenberg, Kurt F.; Gerwin, Richard A.; Henins, Ivars; Mayo, Robert; Scheuer, Jay; Wurden, Glen

1992-01-01

The present report on preliminary results of theoretical and experimental investigations of power flow in a large, unoptimized, multimegawatt coaxial thruster evaluates the significance of these data for the development of efficient, megawatt-class magnetoplasmadynamic (MPD) thrusters. The good agreement obtained between thruster operational performance and model predictions suggests that ideal MHD processes, including those of a magnetic nozzle, play an important role in coaxial plasma thruster dynamics at power levels relevant to advanced space propulsion. An optimized magnetic nozzle design would aid the development of efficient, multimegawatt MPD thrusters.

Prediction of noise constrained optimum takeoff procedures

NASA Technical Reports Server (NTRS)

Padula, S. L.

1980-01-01

An optimization method is used to predict safe, maximum-performance takeoff procedures which satisfy noise constraints at multiple observer locations. The takeoff flight is represented by two-degree-of-freedom dynamical equations with aircraft angle-of-attack and engine power setting as control functions. The engine thrust, mass flow and noise source parameters are assumed to be given functions of the engine power setting and aircraft Mach number. Effective Perceived Noise Levels at the observers are treated as functionals of the control functions. The method is demonstrated by applying it to an Advanced Supersonic Transport aircraft design. The results indicate that automated takeoff procedures (continuously varying controls) can be used to significantly reduce community and certification noise without jeopardizing safety or degrading performance.

Fourier transform wavefront control with adaptive prediction of the atmosphere.

PubMed

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2016-01-01

The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The aims of the present study were to assess the association between the HW phenotype and type 2 diabetes in Korean adults and to evaluate the predictive power of various phenotypes consisting of combinations of individual anthropometric measurements and TG levels. Between November 2006 and August 2013, 11,937 subjects participated in this retrospective cross-sectional study. We measured fasting plasma glucose and TG levels and performed anthropometric measurements. We employed binary logistic regression (LR) to examine statistically significant differences between normal subjects and those with type 2 diabetes using HW and individual anthropometric measurements. For more reliable prediction results, two machine learning algorithms, naive Bayes (NB) and LR, were used to evaluate the predictive power of various phenotypes. All prediction experiments were performed using a tenfold cross validation method. Among all of the variables, the presence of HW was most strongly associated with type 2 diabetes (p < 0.001, adjusted odds ratio (OR) = 2.07 [95% CI, 1.72-2.49] in men; p < 0.001, adjusted OR = 2.09 [1.79-2.45] in women). When comparing waist circumference (WC) and TG levels as components of the HW phenotype, the association between WC and type 2 diabetes was greater than the association between TG and type 2 diabetes. The phenotypes tended to have higher predictive power in women than in men. Among the phenotypes, the best predictors of type 2 diabetes were waist-to-hip ratio + TG in men (AUC by NB = 0.653, AUC by LR = 0.661) and rib-to-hip ratio + TG in women (AUC by NB = 0.73, AUC by LR = 0.735). Although the presence of HW demonstrated the strongest association with type 2 diabetes, the predictive power of the combined measurements of the actual WC and TG values may not be the best manner of predicting type 2 diabetes. Our findings may provide clinical information concerning the development of clinical decision support systems for the initial screening of type 2 diabetes.

Prediction of anaerobic power values from an abbreviated WAnT protocol.

PubMed

Stickley, Christopher D; Hetzler, Ronald K; Kimura, Iris F

2008-05-01

The traditional 30-second Wingate anaerobic test (WAnT) is a widely used anaerobic power assessment protocol. An abbreviated protocol has been shown to decrease the mild to severe physical discomfort often associated with the WAnT. Therefore, the purpose of this study was to determine whether a 20-second WAnT protocol could be used to accurately predict power values of a standard 30-second WAnT. In 96 college females, anaerobic power variables were assessed using a standard 30-second WAnT protocol. Maximum power values as well as instantaneous power at 10, 15, and 20 seconds were recorded. Based on these results, stepwise regression analysis was performed to determine the accuracy with which mean power, minimum power, 30-second power, and percentage of fatigue for a standard 30-second WAnT could be predicted from values obtained during the first 20 seconds of testing. Mean power values showed the highest level of predictability (R2 = 0.99) from the 20-second values. Minimum power, 30-second power, and percentage of fatigue also showed high levels of predictability (R2 = 0.91, 0.84, and 0.84, respectively) using only values obtained during the first 20 seconds of the protocol. An abbreviated (20-second) WAnT protocol appears to effectively predict results of a standard 30-second WAnT in college-age females, allowing for comparison of data to published norms. A shortened test may allow for a decrease in unwanted side effects associated with the traditional WAnT protocol.

Applying a new mammographic imaging marker to predict breast cancer risk

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Danala, Gopichandh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-02-01

Identifying and developing new mammographic imaging markers to assist prediction of breast cancer risk has been attracting extensive research interest recently. Although mammographic density is considered an important breast cancer risk, its discriminatory power is lower for predicting short-term breast cancer risk, which is a prerequisite to establish a more effective personalized breast cancer screening paradigm. In this study, we presented a new interactive computer-aided detection (CAD) scheme to generate a new quantitative mammographic imaging marker based on the bilateral mammographic tissue density asymmetry to predict risk of cancer detection in the next subsequent mammography screening. An image database involving 1,397 women was retrospectively assembled and tested. Each woman had two digital mammography screenings namely, the "current" and "prior" screenings with a time interval from 365 to 600 days. All "prior" images were originally interpreted negative. In "current" screenings, these cases were divided into 3 groups, which include 402 positive, 643 negative, and 352 biopsy-proved benign cases, respectively. There is no significant difference of BIRADS based mammographic density ratings between 3 case groups (p < 0.6). When applying the CAD-generated imaging marker or risk model to classify between 402 positive and 643 negative cases using "prior" negative mammograms, the area under a ROC curve is 0.70+/-0.02 and the adjusted odds ratios show an increasing trend from 1.0 to 8.13 to predict the risk of cancer detection in the "current" screening. Study demonstrated that this new imaging marker had potential to yield significantly higher discriminatory power to predict short-term breast cancer risk.

The development and validation of a novel model for predicting surgical complications in colorectal cancer of elderly patients: Results from 1008 cases.

PubMed

Shen, Zhanlong; Lin, Yuanpei; Ye, Yingjiang; Jiang, Kewei; Xie, Qiwei; Gao, Zhidong; Wang, Shan

2018-04-01

To establish predicting models of surgical complications in elderly colorectal cancer patients. Surgical complications are usually critical and lethal in the elderly patients. However, none of the current models are specifically designed to predict surgical complications in elderly colorectal cancer patients. Details of 1008 cases of elderly colorectal cancer patients (age ≥ 65) were collected retrospectively from January 1998 to December 2013. Seventy-six clinicopathological variables which might affect postoperative complications in elderly patients were recorded. Multivariate stepwise logistic regression analysis was used to develop the risk model equations. The performance of the developed model was evaluated by measures of calibration (Hosmer-Lemeshow test) and discrimination (the area under the receiver-operator characteristic curve, AUC). The AUC of our established Surgical Complication Score for Elderly Colorectal Cancer patients (SCSECC) model was 0.743 (sensitivity, 82.1%; specificity, 78.3%). There was no significant discrepancy between observed and predicted incidence rates of surgical complications (AUC, 0.820; P = .812). The Surgical Site Infection Score for Elderly Colorectal Cancer patients (SSISECC) model showed significantly better prediction power compared to the National Nosocomial Infections Surveillance index (NNIS) (AUC, 0.732; P ˂ 0.001) and Efficacy of Nosocomial Infection Control index (SENIC) (AUC; 0.686; P˂0.001) models. The SCSECC and SSISECC models show good prediction power for postoperative surgical complication morbidity and surgical site infection in elderly colorectal cancer patients. Copyright © 2018 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Predicting the emissive power of hydrocarbon pool fires.

PubMed

Muñoz, Miguel; Planas, Eulàlia; Ferrero, Fabio; Casal, Joaquim

2007-06-18

The emissive power (E) of a flame depends on the size of the fire and the type of fuel. In fact, it changes significantly over the flame surface: the zones of luminous flame have high emittance, while those covered by smoke have low E values. The emissive power of each zone (that is, the luminous or clear flame and the non-luminous or smoky flame) and the portion of total flame area they occupy must be assessed when a two-zone model is used. In this study, data obtained from an experimental set-up were used to estimate the emissive power of fires and its behaviour as a function of pool size. The experiments were performed using gasoline and diesel oil as fuel. Five concentric circular pools (1.5, 3, 4, 5 and 6m in diameter) were used. Appropriate instruments were employed to determine the main features of the fires. By superimposing IR and VHS images it was possible to accurately identify the luminous and non-luminous zones of the fire. Mathematical expressions were obtained that give a more accurate prediction of E(lum), E(soot) and the average emissive power of a fire as a function of its luminous and smoky zones. These expressions can be used in a two-zone model to obtain a better prediction of the thermal radiation. The value of the radiative fraction was determined from the thermal flux measured with radiometers. An expression is also proposed for estimating the radiative fraction.

Heatpipe power system and heatpipe bimodal system design and development options

NASA Technical Reports Server (NTRS)

Houts, M. G.; Poston, D. I.; Emrich, W. J., Jr.

1997-01-01

The Heatpipe Power System (HPS) is a potential, near-term, low-cost space fission power system. The Heatpipe Bimodal System (HBS) is a potential, near-term, low-cost space fission power and/or propulsion system. Both systems will be composed of independent modules, and all components operate within the existing databases. The HPS and HBS have relatively few system integration issues; thus, the successful development of a module is a significant step toward verifying system feasibility and performance estimates. A prototypic HPS module is being fabricated, and testing is scheduled to begin in November 1996. A successful test will provide high confidence that the HPS can achieve its predicted performance.

Relationships between salivary free testosterone and the expression of force and power in elite athletes.

PubMed

Crewther, B T; Kilduff, L P; Cook, C J; Cunningham, D J; Bunce, P; Bracken, R M; Gaviglio, C M

2012-04-01

This study examined the predictive relationships between the salivary free testosterone (T) concentrations of elite athletes and the expression of force and power. A group of elite male rugby players (N.=64) were assessed for peak force (PF), peak rate of force development (PRFD), force at 100 milliseconds (F100 ms) and 250 milliseconds (F250 ms) during an isometric mid-thigh pull (IMTP), and/or peak power (PP) and height during a countermovement jump (CMJ). Saliva samples were collected before testing and assayed for free T. Relationships between individual T concentrations and performance were assessed as a pooled group and 4 sub-groups of equal size. As pooled data sets, none of the IMTP and CMJ performance variables were significantly correlated with free T in either the PF or PP groups (r=0.01-0.23). The PF and PP abilities of the 4 sub-groups were significantly different, so that PF1>PF2>PF3>PF4 (P<0.001) and PP1>PP2>PP3>PP4 (P<0.01). When the 4 sub-groups were analysed, the T concentrations of the PF4 group were significantly (P<0.05-0.01) correlated to PRFD (r=0.69) and F100 ms (r=0.55) during the IMTP, as was F100 ms in the PF1 group (r=0.66). In the PP1 group, free T also correlated to CMJ height (r=0.62). The key conclusion is that the expression of force and power in an elite athletic group may be dependent, to some extent, on individual variation in salivary free T concentrations and existing strength or power levels. The current results also confirm that the grouping of elite athletes of mixed strength or power ability may bias predictive results in a manner not reflective of sub-groups within this population.

[Studies of marker screening efficiency and corresponding influencing factors in QTL composite interval mapping].

PubMed

Gao, Yong-Ming; Wan, Ping

2002-06-01

Screening markers efficiently is the foundation of mapping QTLs by composite interval mapping. Main and interaction markers distinguished, besides using background control for genetic variation, could also be used to construct intervals of two-way searching for mapping QTLs with epistasis, which can save a lot of calculation time. Therefore, the efficiency of marker screening would affect power and precision of QTL mapping. A doubled haploid population with 200 individuals and 5 chromosomes was constructed, with 50 markers evenly distributed at 10 cM space. Among a total of 6 QTLs, one was placed on chromosome I, two linked on chromosome II, and the other three linked on chromosome IV. QTL setting included additive effects and epistatic effects of additive x additive, the corresponding QTL interaction effects were set if data were collected under multiple environments. The heritability was assumed to be 0.5 if no special declaration. The power of marker screening by stepwise regression, forward regression, and three methods for random effect prediction, e.g. best linear unbiased prediction (BLUP), linear unbiased prediction (LUP) and adjusted unbiased prediction (AUP), was studied and compared through 100 Monte Carlo simulations. The results indicated that the marker screening power by stepwise regression at 0.1, 0.05 and 0.01 significant level changed from 2% to 68%, the power changed from 2% to 72% by forward regression. The larger the QTL effects, the higher the marker screening power. While the power of marker screening by three random effect prediction was very low, the maximum was only 13%. That suggested that regression methods were much better than those by using the approaches of random effect prediction to identify efficient markers flanking QTLs, and forward selection method was more simple and efficient. The results of simulation study on heritability showed that heightening of both general heritability and interaction heritability of genotype x environments could enhance marker screening power, the former had a greater influence on QTLs with larger main and/or epistatic effects, while the later on QTLs with small main and/or epistatic effects. The simulation of 100 times was also conducted to study the influence of different marker number and density on marker screening power. It is indicated that the marker screening power would decrease if there were too many markers, especially with high density in a mapping population, which suggested that a mapping population with definite individuals could only hold limited markers. According to the simulation study, the reasonable number of markers should not be more than individuals. The simulation study of marker screening under multiple environments showed high total power of marker screening. In order to relieve the problem that marker screening power restricted the efficiency of QTL mapping, markers identified in multiple environments could be used to construct two search intervals.

The COMMAND trial of cognitive therapy to prevent harmful compliance with command hallucinations: predictors of outcome and mediators of change.

PubMed

Birchwood, Max; Dunn, Graham; Meaden, Alan; Tarrier, Nicholas; Lewis, Shon; Wykes, Til; Davies, Linda; Michail, Maria; Peters, Emmanuelle

2017-12-05

Acting on harmful command hallucinations is a major clinical concern. Our COMMAND CBT trial approximately halved the rate of harmful compliance (OR = 0.45, 95% CI 0.23-0.88, p = 0.021). The focus of the therapy was a single mechanism, the power dimension of voice appraisal, was also significantly reduced. We hypothesised that voice power differential (between voice and voice hearer) was the mediator of the treatment effect. The trial sample (n = 197) was used. A logistic regression model predicting 18-month compliance was used to identify predictors, and an exploratory principal component analysis (PCA) of baseline variables used as potential predictors (confounders) in their own right. Stata's paramed command used to obtain estimates of the direct, indirect and total effects of treatment. Voice omnipotence was the best predictor although the PCA identified a highly predictive cognitive-affective dimension comprising: voices' power, childhood trauma, depression and self-harm. In the mediation analysis, the indirect effect of treatment was fully explained by its effect on the hypothesised mediator: voice power differential. Voice power and treatment allocation were the best predictors of harmful compliance up to 18 months; post-treatment, voice power differential measured at nine months was the mediator of the effect of treatment on compliance at 18 months.

Effect of trabeculectomy on the accuracy of intraocular lens calculations in patients with open-angle glaucoma.

PubMed

Bae, Hyoung Won; Lee, Yun Ha; Kim, Do Wook; Lee, Taekjune; Hong, Samin; Seong, Gong Je; Kim, Chan Yun

2016-08-01

The objective of the study is to examine the effect of trabeculectomy on intraocular lens power calculations in patients with open-angle glaucoma (OAG) undergoing cataract surgery. The design is retrospective data analysis. There are a total of 55 eyes of 55 patients with OAG who had a cataract surgery alone or in combination with trabeculectomy. We classified OAG subjects into the following groups based on surgical history: only cataract surgery (OC group), cataract surgery after prior trabeculectomy (CAT group), and cataract surgery performed in combination with trabeculectomy (CCT group). Differences between actual and predicted postoperative refractive error. Mean error (ME, difference between postoperative and predicted SE) in the CCT group was significantly lower (towards myopia) than that of the OC group (P = 0.008). Additionally, mean absolute error (MAE, absolute value of ME) in the CAT group was significantly greater than in the OC group (P = 0.006). Using linear mixed models, the ME calculated with the SRK II formula was more accurate than the ME predicted by the SRK T formula in the CAT (P = 0.032) and CCT (P = 0.035) groups. The intraocular lens power prediction accuracy was lower in the CAT and CCT groups than in the OC group. The prediction error was greater in the CAT group than in the OC group, and the direction of the prediction error tended to be towards myopia in the CCT group. The SRK II formula may be more accurate in predicting residual refractive error in the CAT and CCT groups. © 2016 Royal Australian and New Zealand College of Ophthalmologists.

Exploring the Effects of Low Power Schemas in Mothers.

ERIC Educational Resources Information Center

Mills, Rosemary S. L.

1999-01-01

Assessed whether low perceived maternal power and temperamentally fearful preschool-aged daughters predicted subsequent maternal overcontrol and internalizing symptoms in daughters 2 years later. Found that low perceived maternal power predicted subsequent maternal overcontrol with initially fearful daughters but did not predict subsequent…

Does the OVX matter for volatility forecasting? Evidence from the crude oil market

NASA Astrophysics Data System (ADS)

Lv, Wendai

2018-02-01

In this paper, I investigate that whether the OVX and its truncated parts with a certain threshold can significantly help in forecasting the oil futures price volatility basing on the Heterogeneous Autoregressive model of Realized Volatility (HAR-RV). In-sample estimation results show that the OVX has a significantly positive impact on futures volatility. The impact of large OVX on future volatility has slightly powerful compared to the small ones. Moreover, the HARQ-RV model outperforms the HAR-RV in predicting the oil futures volatility. More importantly, the decomposed OVX have more powerful in forecasting the oil futures price volatility compared to the OVX itself.

Comparison of the economic impact of different wind power forecast systems for producers

NASA Astrophysics Data System (ADS)

Alessandrini, S.; Davò, F.; Sperati, S.; Benini, M.; Delle Monache, L.

2014-05-01

Deterministic forecasts of wind production for the next 72 h at a single wind farm or at the regional level are among the main end-users requirement. However, for an optimal management of wind power production and distribution it is important to provide, together with a deterministic prediction, a probabilistic one. A deterministic forecast consists of a single value for each time in the future for the variable to be predicted, while probabilistic forecasting informs on probabilities for potential future events. This means providing information about uncertainty (i.e. a forecast of the PDF of power) in addition to the commonly provided single-valued power prediction. A significant probabilistic application is related to the trading of energy in day-ahead electricity markets. It has been shown that, when trading future wind energy production, using probabilistic wind power predictions can lead to higher benefits than those obtained by using deterministic forecasts alone. In fact, by using probabilistic forecasting it is possible to solve economic model equations trying to optimize the revenue for the producer depending, for example, on the specific penalties for forecast errors valid in that market. In this work we have applied a probabilistic wind power forecast systems based on the "analog ensemble" method for bidding wind energy during the day-ahead market in the case of a wind farm located in Italy. The actual hourly income for the plant is computed considering the actual selling energy prices and penalties proportional to the unbalancing, defined as the difference between the day-ahead offered energy and the actual production. The economic benefit of using a probabilistic approach for the day-ahead energy bidding are evaluated, resulting in an increase of 23% of the annual income for a wind farm owner in the case of knowing "a priori" the future energy prices. The uncertainty on price forecasting partly reduces the economic benefit gained by using a probabilistic energy forecast system.

Lightning Scaling Laws Revisited

NASA Technical Reports Server (NTRS)

Boccippio, D. J.; Arnold, James E. (Technical Monitor)

2000-01-01

Scaling laws relating storm electrical generator power (and hence lightning flash rate) to charge transport velocity and storm geometry were originally posed by Vonnegut (1963). These laws were later simplified to yield simple parameterizations for lightning based upon cloud top height, with separate parameterizations derived over land and ocean. It is demonstrated that the most recent ocean parameterization: (1) yields predictions of storm updraft velocity which appear inconsistent with observation, and (2) is formally inconsistent with the theory from which it purports to derive. Revised formulations consistent with Vonnegut's original framework are presented. These demonstrate that Vonnegut's theory is, to first order, consistent with observation. The implications of assuming that flash rate is set by the electrical generator power, rather than the electrical generator current, are examined. The two approaches yield significantly different predictions about the dependence of charge transfer per flash on storm dimensions, which should be empirically testable. The two approaches also differ significantly in their explanation of regional variability in lightning observations.

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

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

NASA Astrophysics Data System (ADS)

Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

2017-05-01

The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

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

Evaluating the predictive power of multivariate tensor-based morphometry in Alzheimer's disease progression via convex fused sparse group Lasso

NASA Astrophysics Data System (ADS)

Tsao, Sinchai; Gajawelli, Niharika; Zhou, Jiayu; Shi, Jie; Ye, Jieping; Wang, Yalin; Lepore, Natasha

2014-03-01

Prediction of Alzheimers disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end we combine a predictive multi-task machine learning method1 with novel MR-based multivariate morphometric surface map of the hippocampus2 to predict future cognitive scores of patients. Previous work by Zhou et al.1 has shown that a multi-task learning framework that performs prediction of all future time points (or tasks) simultaneously can be used to encode both sparsity as well as temporal smoothness. They showed that this can be used in predicting cognitive outcomes of Alzheimers Disease Neuroimaging Initiative (ADNI) subjects based on FreeSurfer-based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied Shi et al.2s recently developed multivariate tensor-based (mTBM) parametric surface analysis method to extract features from the hippocampal surface. We show that by combining the power of the multi-task framework with the sensitivity of mTBM features of the hippocampus surface, we are able to improve significantly improve predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline.

Bayesian predictive power: choice of prior and some recommendations for its use as probability of success in drug development.

PubMed

Rufibach, Kaspar; Burger, Hans Ulrich; Abt, Markus

2016-09-01

Bayesian predictive power, the expectation of the power function with respect to a prior distribution for the true underlying effect size, is routinely used in drug development to quantify the probability of success of a clinical trial. Choosing the prior is crucial for the properties and interpretability of Bayesian predictive power. We review recommendations on the choice of prior for Bayesian predictive power and explore its features as a function of the prior. The density of power values induced by a given prior is derived analytically and its shape characterized. We find that for a typical clinical trial scenario, this density has a u-shape very similar, but not equal, to a β-distribution. Alternative priors are discussed, and practical recommendations to assess the sensitivity of Bayesian predictive power to its input parameters are provided. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Potential role of liver enzymes levels as predictor markers of glucose metabolism disorders in Tunisian population.

PubMed

Bouhajja, Houda; Abdelhedi, Rania; Amouri, Ali; Hadj Kacem, Faten; Marrakchi, Rim; Safi, Wajdi; Mrabet, Houcem; Chtourou, Lassaad; Charfi, Nadia; Fourati, Mouna; Bensassi, Salwa; Jamoussi, Kamel; Abid, Mohamed; Ayadi, Hammadi; Feki, Mouna Mnif; Elleuch, Noura Bougacha

2018-03-10

The relationship between liver enzymes and type 2 diabetes (T2D) risk is inconclusive. We aimed to evaluate the association between liver markers and risk of carbohydrate metabolism disorders and their discriminatory power for T2D prediction. This cross-sectional study enrolled 216 participants classified as normoglycemic, prediabetes, newly-diagnosed diabetes and diagnosed diabetes. All participants underwent anthropometric and biochemical measurements. The relationship between hepatic enzymes and glucose metabolism markers was evaluated by ANCOVA analyses. The associations between liver enzymes and incident carbohydrate metabolism disorders were analyzed through logistic regression and their discriminatory capacity for T2D by receiver operating characteristic (ROC) analysis. High alkaline phosphatase (AP), alanine aminotransferase (ALT), γ-glutamyltransferase (γGT) and aspartate aminotrasferase (AST) levels were independently related to decreased insulin sensitivity. Interestingly, higher AP level was significantly associated with increased risk of prediabetes (p=0.017), newly-diagnosed diabetes (p=0.004) and T2D (p=0.007). Elevated γGT level was an independent risk factor for T2D (p=0.032) and undiagnosed-T2D (p=0.010) in prediabetic and normoglycemic subjects, respectively. In ROC analysis, AP was a powerful predictor of incident diabetes and significantly improved T2D prediction. Liver enzymes within normal range, specifically AP levels, are associated with increased risk of carbohydrate metabolism disorders and significantly improved T2D prediction.

Self-controlled learning benefits: exploring contributions of self-efficacy and intrinsic motivation via path analysis.

PubMed

Ste-Marie, Diane M; Carter, Michael J; Law, Barbi; Vertes, Kelly; Smith, Victoria

2016-09-01

Research has shown learning advantages for self-controlled practice contexts relative to yoked (i.e., experimenter-imposed) contexts; yet, explanations for this phenomenon remain relatively untested. We examined, via path analysis, whether self-efficacy and intrinsic motivation are important constructs for explaining self-controlled learning benefits. The path model was created using theory-based and empirically supported relationships to examine causal links between these psychological constructs and physical performance. We hypothesised that self-efficacy and intrinsic motivation would have greater predictive power for learning under self-controlled compared to yoked conditions. Participants learned double-mini trampoline progressions, and measures of physical performance, self-efficacy and intrinsic motivation were collected over two practice days and a delayed retention day. The self-controlled group (M = 2.04, SD = .98) completed significantly more skill progressions in retention than their yoked counterparts (M = 1.3, SD = .65). The path model displayed adequate fit, and similar significant path coefficients were found for both groups wherein each variable was predominantly predicted by its preceding time point (e.g., self-efficacy time 1 predicts self-efficacy time 2). Interestingly, the model was not moderated by group; thus, failing to support the hypothesis that self-efficacy and intrinsic motivation have greater predictive power for learning under self-controlled relative to yoked conditions.

Plasma cytokines eotaxin, MIP-1α, MCP-4, and vascular endothelial growth factor in acute lower respiratory tract infection.

PubMed

Relster, Mette Marie; Holm, Anette; Pedersen, Court

2017-02-01

Major overlaps of clinical characteristics and the limitations of conventional diagnostic tests render the initial diagnosis and clinical management of pulmonary disorders difficult. In this pilot study, we analyzed the predictive value of eotaxin, macrophage inflammatory protein 1 alpha (MIP-1α), monocyte chemoattractant protein 4 (MCP-4), and vascular endothelial growth factor (VEGF) in 40 patients hospitalized with acute lower respiratory tract infections (LRTI). The cytokines contribute to the pathogenesis of several inflammatory respiratory diseases, indicating a potential as markers for LRTI. Patients were stratified according to etiology and severity of LRTI, based on baseline C-reactive protein and CURB-65 scores. Using a multiplex immunoassay of plasma, levels of eotaxin and MCP-4 were shown to increase from baseline until day 6 after admission to hospital. The four cytokines were unable to predict the etiology and severity. Eotaxin and MCP-4 were significantly lower in patients with C-reactive protein ≥100, and MIP-1α was significantly higher in the patients with CURB-65 > 3, but the predictive power was low. In conclusion, further evaluation, including more patients, is required to assess the full potential of eotaxin, MCP-4, MIP-1α, and VEGF as biomarkers for LRTI because of their low predictive power and a high interindividual variation of cytokine levels. © 2016 APMIS. Published by John Wiley & Sons Ltd.

Toward a Comprehensive Model of Frailty: An Emerging Concept From the Hong Kong Centenarian Study.

PubMed

Kwan, Joseph Shiu Kwong; Lau, Bobo Hi Po; Cheung, Karen Siu Lan

2015-06-01

A better understanding of the essential components of frailty is important for future developments of management strategies. We aimed to assess the incremental validity of a Comprehensive Model of Frailty (CMF) over Frailty Index (FI) in predicting self-rated health and functional dependency amongst near-centenarians and centenarians. Cross-sectional, community-based study. Two community-based social and clinical networks. One hundred twenty-four community-dwelling Chinese near-centenarians and centenarians. Frailty was first assessed using a 32-item FI (FI-32). Then, a new CMF was constructed by adding 12 items in the psychological, social/family, environmental, and economic domains to the FI-32. Hierarchical multiple regressions explored whether the new CMF provided significant additional predictive power for self-rated health and instrumental activities of daily living (IADL) dependency. Mean age was 97.7 (standard deviation 2.3) years, with a range from 95 to 108, and 74.2% were female. Overall, 16% of our participants were nonfrail, 59% were prefrail, and 25% were frail. Frailty according to FI-32 significantly predicted self-rated health and IADL dependency beyond the effect of age and gender. Inclusion of the new CMF into the regression models provided significant additional predictive power beyond FI-32 on self-rated health, but not IADL dependency. A CMF should ideally be a multidimensional and multidisciplinary construct including physical, cognitive, functional, psychosocial/family, environmental, and economic factors. Copyright © 2015 AMDA - The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Identification and Management of Pump Thrombus in the HeartWare Left Ventricular Assist Device System: A Novel Approach Using Log File Analysis.

PubMed

Jorde, Ulrich P; Aaronson, Keith D; Najjar, Samer S; Pagani, Francis D; Hayward, Christopher; Zimpfer, Daniel; Schlöglhofer, Thomas; Pham, Duc T; Goldstein, Daniel J; Leadley, Katrin; Chow, Ming-Jay; Brown, Michael C; Uriel, Nir

2015-11-01

The study sought to characterize patterns in the HeartWare (HeartWare Inc., Framingham, Massachusetts) ventricular assist device (HVAD) log files associated with successful medical treatment of device thrombosis. Device thrombosis is a serious adverse event for mechanical circulatory support devices and is often preceded by increased power consumption. Log files of the pump power are easily accessible on the bedside monitor of HVAD patients and may allow early diagnosis of device thrombosis. Furthermore, analysis of the log files may be able to predict the success rate of thrombolysis or the need for pump exchange. The log files of 15 ADVANCE trial patients (algorithm derivation cohort) with 16 pump thrombus events treated with tissue plasminogen activator (tPA) were assessed for changes in the absolute and rate of increase in power consumption. Successful thrombolysis was defined as a clinical resolution of pump thrombus including normalization of power consumption and improvement in biochemical markers of hemolysis. Significant differences in log file patterns between successful and unsuccessful thrombolysis treatments were verified in 43 patients with 53 pump thrombus events implanted outside of clinical trials (validation cohort). The overall success rate of tPA therapy was 57%. Successful treatments had significantly lower measures of percent of expected power (130.9% vs. 196.1%, p = 0.016) and rate of increase in power (0.61 vs. 2.87, p < 0.0001). Medical therapy was successful in 77.7% of the algorithm development cohort and 81.3% of the validation cohort when the rate of power increase and percent of expected power values were <1.25% and 200%, respectively. Log file parameters can potentially predict the likelihood of successful tPA treatments and if validated prospectively, could substantially alter the approach to thrombus management. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Power maximization of a point absorber wave energy converter using improved model predictive control

NASA Astrophysics Data System (ADS)

Milani, Farideh; Moghaddam, Reihaneh Kardehi

2017-08-01

This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

Adjusted Clinical Groups: Predictive Accuracy for Medicaid Enrollees in Three States

PubMed Central

Adams, E. Kathleen; Bronstein, Janet M.; Raskind-Hood, Cheryl

2002-01-01

Actuarial split-sample methods were used to assess predictive accuracy of adjusted clinical groups (ACGs) for Medicaid enrollees in Georgia, Mississippi (lagging in managed care penetration), and California. Accuracy for two non-random groups—high-cost and located in urban poor areas—was assessed. Measures for random groups were derived with and without short-term enrollees to assess the effect of turnover on predictive accuracy. ACGs improved predictive accuracy for high-cost conditions in all States, but did so only for those in Georgia's poorest urban areas. Higher and more unpredictable expenses of short-term enrollees moderated the predictive power of ACGs. This limitation was significant in Mississippi due in part, to that State's very high proportion of short-term enrollees. PMID:12545598

Towards energy-efficient photonic interconnects

NASA Astrophysics Data System (ADS)

Demir, Yigit; Hardavellas, Nikos

2015-03-01

Silicon photonics have emerged as a promising solution to meet the growing demand for high-bandwidth, low-latency, and energy-efficient on-chip and off-chip communication in many-core processors. However, current silicon-photonic interconnect designs for many-core processors waste a significant amount of power because (a) lasers are always on, even during periods of interconnect inactivity, and (b) microring resonators employ heaters which consume a significant amount of power just to overcome thermal variations and maintain communication on the photonic links, especially in a 3D-stacked design. The problem of high laser power consumption is particularly important as lasers typically have very low energy efficiency, and photonic interconnects often remain underutilized both in scientific computing (compute-intensive execution phases underutilize the interconnect), and in server computing (servers in Google-scale datacenters have a typical utilization of less than 30%). We address the high laser power consumption by proposing EcoLaser+, which is a laser control scheme that saves energy by predicting the interconnect activity and opportunistically turning the on-chip laser off when possible, and also by scaling the width of the communication link based on a runtime prediction of the expected message length. Our laser control scheme can save up to 62 - 92% of the laser energy, and improve the energy efficiency of a manycore processor with negligible performance penalty. We address the high trimming (heating) power consumption of the microrings by proposing insulation methods that reduce the impact of localized heating induced by highly-active components on the 3D-stacked logic die.

Multiple Off-Ice Performance Variables Predict On-Ice Skating Performance in Male and Female Division III Ice Hockey Players.

PubMed

Janot, Jeffrey M; Beltz, Nicholas M; Dalleck, Lance D

2015-09-01

The purpose of this study was to determine if off-ice performance variables could predict on-ice skating performance in Division III collegiate hockey players. Both men (n = 15) and women (n = 11) hockey players (age = 20.5 ± 1.4 years) participated in the study. The skating tests were agility cornering S-turn, 6.10 m acceleration, 44.80 m speed, modified repeat skate, and 15.20 m full speed. Off-ice variables assessed were years of playing experience, height, weight and percent body fat and off-ice performance variables included vertical jump (VJ), 40-yd dash (36.58m), 1-RM squat, pro-agility, Wingate peak power and peak power percentage drop (% drop), and 1.5 mile (2.4km) run. Results indicated that 40-yd dash (36.58m), VJ, 1.5 mile (2.4km) run, and % drop were significant predictors of skating performance for repeat skate (slowest, fastest, and average time) and 44.80 m speed time, respectively. Four predictive equations were derived from multiple regression analyses: 1) slowest repeat skate time = 2.362 + (1.68 x 40-yd dash time) + (0.005 x 1.5 mile run), 2) fastest repeat skate time = 9.762 - (0.089 x VJ) - (0.998 x 40-yd dash time), 3) average repeat skate time = 7.770 + (1.041 x 40-yd dash time) - (0.63 x VJ) + (0.003 x 1.5 mile time), and 4) 47.85 m speed test = 7.707 - (0.050 x VJ) - (0.01 x % drop). It was concluded that selected off-ice tests could be used to predict on-ice performance regarding speed and recovery ability in Division III male and female hockey players. Key pointsThe 40-yd dash (36.58m) and vertical jump tests are significant predictors of on-ice skating performance specific to speed.In addition to 40-yd dash and vertical jump, the 1.5 mile (2.4km) run for time and percent power drop from the Wingate anaerobic power test were also significant predictors of skating performance that incorporates the aspect of recovery from skating activity.Due to the specificity of selected off-ice variables as predictors of on-ice performance, coaches can elect to assess player performance off-ice and focus on other uses of valuable ice time for their individual teams.

Development and design of photovoltaic power prediction system

NASA Astrophysics Data System (ADS)

Wang, Zhijia; Zhou, Hai; Cheng, Xu

2018-02-01

In order to reduce the impact of power grid safety caused by volatility and randomness of the energy produced in photovoltaic power plants, this paper puts forward a construction scheme on photovoltaic power generation prediction system, introducing the technical requirements, system configuration and function of each module, and discussing the main technical features of the platform software development. The scheme has been applied in many PV power plants in the northwest of China. It shows that the system can produce reasonable prediction results, providing a right guidance for dispatching and efficient running for PV power plant.

High serum total cholesterol is a long-term cause of osteoporotic fracture.

PubMed

Trimpou, P; Odén, A; Simonsson, T; Wilhelmsen, L; Landin-Wilhelmsen, K

2011-05-01

Risk factors for osteoporotic fractures were evaluated in 1,396 men and women for a period of 20 years. Serum total cholesterol was found to be an independent osteoporotic fracture risk factor whose predictive power improves with time. The purpose of this study was to evaluate long-term risk factors for osteoporotic fracture. A population random sample of men and women aged 25-64 years (the Gothenburg WHO MONICA project, N = 1,396, 53% women) was studied prospectively. The 1985 baseline examination recorded physical activity at work and during leisure time, psychological stress, smoking habits, coffee consumption, BMI, waist/hip ratio, blood pressure, total, HDL and LDL cholesterol, triglycerides, and fibrinogen. Osteoporotic fractures over a period of 20 years were retrieved from the Gothenburg hospital registers. Poisson regression was used to analyze the predictive power for osteoporotic fracture of each risk factor. A total number of 258 osteoporotic fractures occurred in 143 participants (10.2%). As expected, we found that previous fracture, smoking, coffee consumption, and lower BMI each increase the risk for osteoporotic fracture independently of age and sex. More unexpectedly, we found that the gradient of risk of serum total cholesterol to predict osteoporotic fracture significantly increases over time (p = 0.0377). Serum total cholesterol is an independent osteoporotic fracture risk factor whose predictive power improves with time. High serum total cholesterol is a long-term cause of osteoporotic fracture.

A model for the release, dispersion and environmental impact of a postulated reactor accident from a submerged commercial nuclear power plant

NASA Astrophysics Data System (ADS)

Bertch, Timothy Creston

1998-12-01

Nuclear power plants are inherently suitable for submerged applications and could provide power to the shore power grid or support future underwater applications. The technology exists today and the construction of a submerged commercial nuclear power plant may become desirable. A submerged reactor is safer to humans because the infinite supply of water for heat removal, particulate retention in the water column, sedimentation to the ocean floor and inherent shielding of the aquatic environment would significantly mitigate the effects of a reactor accident. A better understanding of reactor operation in this new environment is required to quantify the radioecological impact and to determine the suitability of this concept. The impact of release to the environment from a severe reactor accident is a new aspect of the field of marine radioecology. Current efforts have been centered on radioecological impacts of nuclear waste disposal, nuclear weapons testing fallout and shore nuclear plant discharges. This dissertation examines the environmental impact of a severe reactor accident in a submerged commercial nuclear power plant, modeling a postulated site on the Atlantic continental shelf adjacent to the United States. This effort models the effects of geography, decay, particle transport/dispersion, bioaccumulation and elimination with associated dose commitment. The use of a source term equivalent to the release from Chernobyl allows comparison between the impacts of that accident and the postulated submerged commercial reactor plant accident. All input parameters are evaluated using sensitivity analysis. The effect of the release on marine biota is determined. Study of the pathways to humans from gaseous radionuclides, consumption of contaminated marine biota and direct exposure as contaminated water reaches the shoreline is conducted. The model developed by this effort predicts a significant mitigation of the radioecological impact of the reactor accident release with a submerged commercial nuclear power plant. The two box models predict the most of the radio-ecological impact occurs during the first eight days after release. The most significant risk to humans is from consumption of biota. The reduction in impact to humans from a large radioactive release makes the concept worthy of further study.

Midterm Stability Evaluation of Wide-area Power System by using Synchronized Phasor Measurements

NASA Astrophysics Data System (ADS)

Ota, Yutaka; Ukai, Hiroyuki; Nakamura, Koichi; Fujita, Hideki

In recent years, the PMU (Phasor Measurement Unit) receives a great deal of attention as a synchronized measurement system of power systems. Synchronized phasor angles obtained by the PMU provide the effective information for evaluating the stability of a bulk power system. The aspect of instability phenomena during midterm tends to be more complicated, and the stability analysis using the synchronized phasor measurements is significant in order to keep a complicated power system stable. This paper proposes a midterm stability evaluation method of the wide-area power system by using the synchronized phasor measurements. By clustering and aggregating the power system to some coherent groups, the step-out is effectively predicted on the basis of the two-machine equivalent power system model. The midterm stability of a longitudinal power system model of Japanese 60Hz systems constructed by the PSA, which is a hybrid-type power system simulator, is practically evaluated using the proposed method.

Performance of the SRK/T formula using A-Scan ultrasound biometry after phacoemulsification in eyes with short and long axial lengths.

PubMed

Karabela, Yunus; Eliacik, Mustafa; Kaya, Faruk

2016-07-08

The SRK/T formula is one of the third generation IOL calculation formulas. The purpose of this study was to evaluate the performance of the SRK/T formula in predicting a target refraction ±1.0D in short and long eyes using ultrasound biometry after phacoemulsification. The present study was a retrospective analysis, which included 38 eyes with an AL < 22.0 mm (short AL), and 62 eyes ≥24.6 mm (long AL) that underwent uncomplicated phacoemulsification. Preoperative AL was measured by ultrasound biometry and SRK/T formula was used for IOL calculation. Three different IOLs were implanted in the capsular bag. The prediction error was defined as the difference between the achieved postoperative refraction, and attempted predicted target refraction. Statistical analysis was performed with SPSS V21. In short ALs, the mean age was 65.13 ± 9.49 year, the mean AL was 21.55 ± 0.45 mm, the mean K1 and K2 were 45.76 ± 1.77D and 46.09 ± 1.61D, the mean IOL power was 23.96 ± 1.92D, the mean attempted (predicted) value was 0.07 ± 0.26D, the mean achieved value was 0.07 ± 0.63 D, the mean PE was 0.01 ± 0.60D, and the MAE was 0.51 ± 0.31D. A significant positive relationship with AL and K1, K2, IOL power and a strong negative relationship with PE and achieved postoperative was found. In long ALs, the mean age was 64.05 ± 7.31 year, the mean AL was 25.77 ± 1.64 mm, the mean K1 and K2 were 42.20 ± 1.57D and 42.17 ± 1.68D, the mean IOL power was 15.79 ± 5.17D, the mean attempted value was -0.434 ± 0.315D, the mean achieved value was -0.42 ± 0.96D, the mean PE was -0.004 ± 0.93D, the MAE was 0.68 ± 0.62D. A significant positive relationship with AL and K1, K2 and a significant positive relationship with PE and achieved value, otherwise a negative relationship with AL and IOL power was found. There was a little tendency towards hyperopic for short ALs and myopic for long ALs. The majority of eyes (94.74 %) for short ALs and (70.97 %) for long ALs were within ±1 D of the predicted refractive error. No significant relationship with PE and IOL types, AL, K1, K2, IOL power, and attempted value, besides with MAE and AL, K1, K2, age, attempted, achieved value were found in both groups. The SRK/T formula performs well and shows good predictability in eyes with short and long axial lengths.

Biometry and intraocular lens power calculation results with a new optical biometry device: comparison with the gold standard.

PubMed

Kaswin, Godefroy; Rousseau, Antoine; Mgarrech, Mohamed; Barreau, Emmanuel; Labetoulle, Marc

2014-04-01

To evaluate the agreement in axial length (AL), keratometry (K), anterior chamber depth (ACD) measurements; intraocular lens (IOL) power calculations; and predictability using a new partial coherence interferometry (PCI) optical biometer (AL-Scan) and a reference (gold standard) PCI optical biometer (IOLMaster 500). Service d'Ophtalmologie, Hopital Bicêtre, APHP Université, Paris, France. Evaluation of a diagnostic device. One eye of consecutive patients scheduled for cataract surgery was measured. Biometry was performed with the new biometer and the reference biometer. Comparisons were performed for AL, average K at 2.4 mm, ACD, IOL power calculations with the Haigis and SRK/T formulas, and postoperative predictability of the devices. A P value less than 0.05 was statistically significant. The study enrolled 50 patients (mean age 72.6 years±4.2 SEM). There was a good correlation between biometers for AL, K, and ACD measurements (r=0.999, r=0.933, and r=0.701, respectively) and between IOL power calculation with the Haigis formula (r=0.972) and the SRK/T formula (r=0.981). The mean absolute error (MAE) in IOL power prediction was 0.42±0.08 diopter (D) with the new biometer and 0.44±0.08 D with the reference biometer. The MAE was 0.20 D with the Haigis formula and 0.19 with the SRK/T formula (P=.36). The new PCI biometer provided valid measurements compared with the current gold standard, indicating that the new device can be used for IOL power calculations for routine cataract surgery. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2014 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Non-Nuclear Validation Test Results of a Closed Brayton Cycle Test-Loop

NASA Astrophysics Data System (ADS)

Wright, Steven A.

2007-01-01

Both NASA and DOE have programs that are investigating advanced power conversion cycles for planetary surface power on the moon or Mars, or for next generation nuclear power plants on earth. Although open Brayton cycles are in use for many applications (combined cycle power plants, aircraft engines), only a few closed Brayton cycles have been tested. Experience with closed Brayton cycles coupled to nuclear reactors is even more limited and current projections of Brayton cycle performance are based on analytic models. This report describes and compares experimental results with model predictions from a series of non-nuclear tests using a small scale closed loop Brayton cycle available at Sandia National Laboratories. A substantial amount of testing has been performed, and the information is being used to help validate models. In this report we summarize the results from three kinds of tests. These tests include: 1) test results that are useful for validating the characteristic flow curves of the turbomachinery for various gases ranging from ideal gases (Ar or Ar/He) to non-ideal gases such as CO2, 2) test results that represent shut down transients and decay heat removal capability of Brayton loops after reactor shut down, and 3) tests that map a range of operating power versus shaft speed curve and turbine inlet temperature that are useful for predicting stable operating conditions during both normal and off-normal operating behavior. These tests reveal significant interactions between the reactor and balance of plant. Specifically these results predict limited speed up behavior of the turbomachinery caused by loss of load, the conditions for stable operation, and for direct cooled reactors, the tests reveal that the coast down behavior during loss of power events can extend for hours provided the ultimate heat sink remains available.

Power spectrum for the small-scale Universe

NASA Astrophysics Data System (ADS)

Widrow, Lawrence M.; Elahi, Pascal J.; Thacker, Robert J.; Richardson, Mark; Scannapieco, Evan

2009-08-01

The first objects to arise in a cold dark matter (CDM) universe present a daunting challenge for models of structure formation. In the ultra small-scale limit, CDM structures form nearly simultaneously across a wide range of scales. Hierarchical clustering no longer provides a guiding principle for theoretical analyses and the computation time required to carry out credible simulations becomes prohibitively high. To gain insight into this problem, we perform high-resolution (N = 7203-15843) simulations of an Einstein-de Sitter cosmology where the initial power spectrum is P(k) ~ kn, with -2.5 <= n <= - 1. Self-similar scaling is established for n = -1 and -2 more convincingly than in previous, lower resolution simulations and for the first time, self-similar scaling is established for an n = -2.25 simulation. However, finite box-size effects induce departures from self-similar scaling in our n = -2.5 simulation. We compare our results with the predictions for the power spectrum from (one-loop) perturbation theory and demonstrate that the renormalization group approach suggested by McDonald improves perturbation theory's ability to predict the power spectrum in the quasi-linear regime. In the non-linear regime, our power spectra differ significantly from the widely used fitting formulae of Peacock & Dodds and Smith et al. and a new fitting formula is presented. Implications of our results for the stable clustering hypothesis versus halo model debate are discussed. Our power spectra are inconsistent with predictions of the stable clustering hypothesis in the high-k limit and lend credence to the halo model. Nevertheless, the fitting formula advocated in this paper is purely empirical and not derived from a specific formulation of the halo model.

Managing PV Power on Mars - MER Rovers

NASA Technical Reports Server (NTRS)

Stella, Paul M.; Chin, Keith; Wood, Eric; Herman, Jennifer; Ewell, Richard

2009-01-01

The MER Rovers have recently completed over 5 years of operation! This is a remarkable demonstration of the capabilities of PV power on the Martian surface. The extended mission required the development of an efficient process to predict the power available to the rovers on a day-to-day basis. The performance of the MER solar arrays is quite unlike that of any other Space array and perhaps more akin to Terrestrial PV operation, although even severe by that comparison. The impact of unpredictable factors, such as atmospheric conditions and dust accumulation (and removal) on the panels limits the accurate prediction of array power to short time spans. Based on the above, it is clear that long term power predictions are not sufficiently accurate to allow for detailed long term planning. Instead, the power assessment is essentially a daily activity, effectively resetting the boundary points for the overall predictive power model. A typical analysis begins with the importing of the telemetry from each rover's previous day's power subsystem activities. This includes the array power generated, battery state-of-charge, rover power loads, and rover orientation, all as functions of time. The predicted performance for that day is compared to the actual performance to identify the extent of any differences. The model is then corrected for these changes. Details of JPL's MER power analysis procedure are presented, including the description of steps needed to provide the final prediction for the mission planners. A dust cleaning event of the solar array is also highlighted to illustrate the impact of Martian weather on solar array performance

Experimental study on thrust and power of flapping-wing system based on rack-pinion mechanism.

PubMed

Nguyen, Tuan Anh; Vu Phan, Hoang; Au, Thi Kim Loan; Park, Hoon Cheol

2016-06-20

This experimental study investigates the effect of three parameters: wing aspect ratio (AR), wing offset, and flapping frequency, on thrust generation and power consumption of a flapping-wing system based on a rack-pinion mechanism. The new flapping-wing system is simple but robust, and is able to create a large flapping amplitude. The thrust measured by a load cell reveals that for a given power, the flapping-wing system using a higher wing AR produces larger thrust and higher flapping frequency at the wing offset of 0.15[Formula: see text] or 0.20[Formula: see text] ([Formula: see text] is the mean chord) than other wing offsets. Of the three parameters, the flapping frequency plays a more significant role on thrust generation than either the wing AR or the wing offset. Based on the measured thrusts, an empirical equation for thrust prediction is suggested, as a function of wing area, flapping frequency, flapping angle, and wing AR. The difference between the predicted and measured thrusts was less than 7%, which proved that the empirical equation for thrust prediction is reasonable. On average, the measured power consumption to flap the wings shows that 46.5% of the input power is spent to produce aerodynamic forces, 14.0% to overcome inertia force, 9.5% to drive the rack-pinion-based flapping mechanism, and 30.0% is wasted as the power loss of the installed motor. From the power analysis, it is found that the wing with an AR of 2.25 using a wing offset of 0.20[Formula: see text] showed the optimal power loading in the flapping-wing system. In addition, the flapping frequency of 25 Hz is recommended as the optimal frequency of the current flapping-wing system for high efficiency, which was 48.3%, using a wing with an AR of 2.25 and a wing offset of 0.20[Formula: see text] in the proposed design.

Enhanced charging kinetics of porous electrodes: surface conduction as a short-circuit mechanism.

PubMed

Mirzadeh, Mohammad; Gibou, Frederic; Squires, Todd M

2014-08-29

We use direct numerical simulations of the Poisson-Nernst-Planck equations to study the charging kinetics of porous electrodes and to evaluate the predictive capabilities of effective circuit models, both linear and nonlinear. The classic transmission line theory of de Levie holds for general electrode morphologies, but only at low applied potentials. Charging dynamics are slowed appreciably at high potentials, yet not as significantly as predicted by the nonlinear transmission line model of Biesheuvel and Bazant. We identify surface conduction as a mechanism which can effectively "short circuit" the high-resistance electrolyte in the bulk of the pores, thus accelerating the charging dynamics and boosting power densities. Notably, the boost in power density holds only for electrode morphologies with continuous conducting surfaces in the charging direction.

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-16

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal ... current POWER home page. The new POWER will include improved solar and meteorological data with all parameters available on a 0.5-degree ...

Communal and Agentic Interpersonal and Intergroup Motives Predict Preferences for Status Versus Power.

PubMed

Locke, Kenneth D; Heller, Sonja

2017-01-01

Seven studies involving 1,343 participants showed how circumplex models of social motives can help explain individual differences in preferences for status (having others' admiration) versus power (controlling valuable resources). Studies 1 to 3 and 7 concerned interpersonal motives in workplace contexts, and found that stronger communal motives (to have mutual trust, support, and cooperation) predicted being more attracted to status (but not power) and achieving more workplace status, while stronger agentic motives (to be firm, decisive, and influential) predicted being more attracted to and achieving more workplace power, and experiencing a stronger connection between workplace power and job satisfaction. Studies 4 to 6 found similar effects for intergroup motives: Stronger communal motives predicted wanting one's ingroup (e.g., country) to have status-but not power-relative to other groups. Finally, most people preferred status over power, and this was especially true for women, which was partially explained by women having stronger communal motives.

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

NASA Astrophysics Data System (ADS)

Lee, Joseph C. Y.; Lundquist, Julie K.

2017-11-01

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

DOE PAGES

Lee, Joseph C. Y.; Lundquist, Julie K.

2017-11-23

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. Our paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustratemore » with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.« less

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

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

Lee, Joseph C. Y.; Lundquist, Julie K.

Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. Our paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustratemore » with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.« less

Discriminatory power of common genetic variants in personalized breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Wu, Yirong; Abbey, Craig K.; Liu, Jie; Ong, Irene; Peissig, Peggy; Onitilo, Adedayo A.; Fan, Jun; Yuan, Ming; Burnside, Elizabeth S.

2016-03-01

Technology advances in genome-wide association studies (GWAS) has engendered optimism that we have entered a new age of precision medicine, in which the risk of breast cancer can be predicted on the basis of a person's genetic variants. The goal of this study is to evaluate the discriminatory power of common genetic variants in breast cancer risk estimation. We conducted a retrospective case-control study drawing from an existing personalized medicine data repository. We collected variables that predict breast cancer risk: 153 high-frequency/low-penetrance genetic variants, reflecting the state-of-the-art GWAS on breast cancer, mammography descriptors and BI-RADS assessment categories in the Breast Imaging Reporting and Data System (BI-RADS) lexicon. We trained and tested naïve Bayes models by using these predictive variables. We generated ROC curves and used the area under the ROC curve (AUC) to quantify predictive performance. We found that genetic variants achieved comparable predictive performance to BI-RADS assessment categories in terms of AUC (0.650 vs. 0.659, p-value = 0.742), but significantly lower predictive performance than the combination of BI-RADS assessment categories and mammography descriptors (0.650 vs. 0.751, p-value < 0.001). A better understanding of relative predictive capability of genetic variants and mammography data may benefit clinicians and patients to make appropriate decisions about breast cancer screening, prevention, and treatment in the era of precision medicine.

Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System.

PubMed

Kiral-Kornek, Isabell; Roy, Subhrajit; Nurse, Ewan; Mashford, Benjamin; Karoly, Philippa; Carroll, Thomas; Payne, Daniel; Saha, Susmita; Baldassano, Steven; O'Brien, Terence; Grayden, David; Cook, Mark; Freestone, Dean; Harrer, Stefan

2018-01-01

Seizure prediction can increase independence and allow preventative treatment for patients with epilepsy. We present a proof-of-concept for a seizure prediction system that is accurate, fully automated, patient-specific, and tunable to an individual's needs. Intracranial electroencephalography (iEEG) data of ten patients obtained from a seizure advisory system were analyzed as part of a pseudoprospective seizure prediction study. First, a deep learning classifier was trained to distinguish between preictal and interictal signals. Second, classifier performance was tested on held-out iEEG data from all patients and benchmarked against the performance of a random predictor. Third, the prediction system was tuned so sensitivity or time in warning could be prioritized by the patient. Finally, a demonstration of the feasibility of deployment of the prediction system onto an ultra-low power neuromorphic chip for autonomous operation on a wearable device is provided. The prediction system achieved mean sensitivity of 69% and mean time in warning of 27%, significantly surpassing an equivalent random predictor for all patients by 42%. This study demonstrates that deep learning in combination with neuromorphic hardware can provide the basis for a wearable, real-time, always-on, patient-specific seizure warning system with low power consumption and reliable long-term performance. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Lightweight Radiator for in Space Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Craven, Paul; Tomboulian, Briana; SanSoucie, Michael

2014-01-01

Nuclear electric propulsion (NEP) is a promising option for high-speed in-space travel due to the high energy density of nuclear fission power sources and efficient electric thrusters. Advanced power conversion technologies may require high operating temperatures and would benefit from lightweight radiator materials. Radiator performance dictates power output for nuclear electric propulsion systems. Game-changing propulsion systems are often enabled by novel designs using advanced materials. Pitch-based carbon fiber materials have the potential to offer significant improvements in operating temperature, thermal conductivity, and mass. These properties combine to allow advances in operational efficiency and high temperature feasibility. An effort at the NASA Marshall Space Flight Center to show that woven high thermal conductivity carbon fiber mats can be used to replace standard metal and composite radiator fins to dissipate waste heat from NEP systems is ongoing. The goals of this effort are to demonstrate a proof of concept, to show that a significant improvement of specific power (power/mass) can be achieved, and to develop a thermal model with predictive capabilities making use of constrained input parameter space. A description of this effort is presented.

Evolving biomarkers improve prediction of long-term mortality in patients with stable coronary artery disease: the BIO-VILCAD score.

PubMed

Kleber, M E; Goliasch, G; Grammer, T B; Pilz, S; Tomaschitz, A; Silbernagel, G; Maurer, G; März, W; Niessner, A

2014-08-01

Algorithms to predict the future long-term risk of patients with stable coronary artery disease (CAD) are rare. The VIenna and Ludwigshafen CAD (VILCAD) risk score was one of the first scores specifically tailored for this clinically important patient population. The aim of this study was to refine risk prediction in stable CAD creating a new prediction model encompassing various pathophysiological pathways. Therefore, we assessed the predictive power of 135 novel biomarkers for long-term mortality in patients with stable CAD. We included 1275 patients with stable CAD from the LUdwigshafen RIsk and Cardiovascular health study with a median follow-up of 9.8 years to investigate whether the predictive power of the VILCAD score could be improved by the addition of novel biomarkers. Additional biomarkers were selected in a bootstrapping procedure based on Cox regression to determine the most informative predictors of mortality. The final multivariable model encompassed nine clinical and biochemical markers: age, sex, left ventricular ejection fraction (LVEF), heart rate, N-terminal pro-brain natriuretic peptide, cystatin C, renin, 25OH-vitamin D3 and haemoglobin A1c. The extended VILCAD biomarker score achieved a significantly improved C-statistic (0.78 vs. 0.73; P = 0.035) and net reclassification index (14.9%; P < 0.001) compared to the original VILCAD score. Omitting LVEF, which might not be readily measureable in clinical practice, slightly reduced the accuracy of the new BIO-VILCAD score but still significantly improved risk classification (net reclassification improvement 12.5%; P < 0.001). The VILCAD biomarker score based on routine parameters complemented by novel biomarkers outperforms previous risk algorithms and allows more accurate classification of patients with stable CAD, enabling physicians to choose more personalized treatment regimens for their patients.

Impact of Balance Of System (BOS) costs on photovoltaic power systems

NASA Technical Reports Server (NTRS)

Hein, G. F.; Cusick, J. P.; Poley, W. A.

1978-01-01

The Department of Energy has developed a program to effect a large reduction in the price of photovoltaic modules, with significant progress already achieved toward the 1986 goal of 50 cents/watt (1975 dollars). Remaining elements of a P/V power system (structure, battery storage, regulation, control, and wiring) are also significant cost items. The costs of these remaining elements are commonly referred to as Balance-of-System (BOS) costs. The BOS costs are less well defined and documented than module costs. The Lewis Research Center (LeRC) in 1976/77 and with two village power experiments that will be installed in 1978. The costs were divided into five categories and analyzed. A regression analysis was performed to determine correlations of BOS Costs per peak watt, with power size for these photovoltaic systems. The statistical relationship may be used for flat-plate, DC systems ranging from 100 to 4,000 peak watts. A survey of suppliers was conducted for comparison with the predicted BOS cost relationship.

Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

PubMed

Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

2012-03-15

To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

Measurement and prediction of propeller flow field on the PTA aircraft at speeds of up to Mach 0.85. [Propfan Test Assessment

NASA Technical Reports Server (NTRS)

Aljabri, Abdullah S.

1988-01-01

High speed subsonic transports powered by advanced propellers provide significant fuel savings compared to turbofan powered transports. Unfortunately, however, propfans must operate in aircraft-induced nonuniform flow fields which can lead to high blade cyclic stresses, vibration and noise. To optimize the design and installation of these advanced propellers, therefore, detailed knowledge of the complex flow field is required. As part of the NASA Propfan Test Assessment (PTA) program, a 1/9 scale semispan model of the Gulfstream II propfan test-bed aircraft was tested in the NASA-Lewis 8 x 6 supersonic wind tunnel to obtain propeller flow field data. Detailed radial and azimuthal surveys were made to obtain the total pressure in the flow and the three components of velocity. Data was acquired for Mach numbers ranging from 0.6 to 0.85. Analytical predictions were also made using a subsonic panel method, QUADPAN. Comparison of wind-tunnel measurements and analytical predictions show good agreement throughout the Mach range.

Prediction of apparent extinction for optical transmission through rain

NASA Astrophysics Data System (ADS)

Vasseur, H.; Gibbins, C. J.

1996-12-01

At optical wavelengths, geometrical optics holds that the extinction efficiency of raindrops is equal to two. This approximation yields a wavelength-independent extinction coefficient that, however, can hardly be used to predict accurately rain extinction measured in optical transmissions. Actually, in addition to the extinct direct incoming light, a significant part of the power scattered by the rain particles reaches the receiver. This leads to a reduced apparent extinction that depends on both rain characteristics and link parameters. A simple method is proposed to evaluate this apparent extinction. It accounts for the additional scattered power that enters the receiver when one considers the forward-scattering pattern of the raindrops as well as the multiple-scattering effects using, respectively, the Fraunhofer diffraction and Twersky theory. It results in a direct analytical formula that enables a quick and accurate estimation of the rain apparent extinction and highlights the influence of the link parameters. Predictions of apparent extinction through rain are found in excellent agreement with measurements in the visible and IR regions.

Predicting College Success: The Relative Contributions of Five Social/Personality Factors, Five Cognitive/Learning Factors, and SAT Scores

PubMed Central

Hannon, Brenda

2014-01-01

To-date, studies have examined simultaneously the relative predictive powers of two or three factors on GPA. The present study examines the relative powers of five social/personality factors, five cognitive/learning factors, and SAT scores to predict freshmen and non-freshmen (sophomores, juniors, seniors) academic success (i.e., GPA). The results revealed many significant predictors of GPA for both freshmen and non-freshmen. However, subsequent regressions showed that only academic self-efficacy, epistemic belief of learning, and high-knowledge integration explained unique variance in GPA (19%-freshmen, 23.2%-non-freshmen). Further for freshmen, SAT scores explained an additional unique 10.6% variance after the influences attributed to these three predictors was removed whereas for non-freshmen, SAT scores failed to explain any additional variance. These results highlight the unique and important contributions of academic self-efficacy, epistemic belief of learning and high-knowledge integration to GPA beyond other previously-identified predictors. PMID:25568884

Intracranial mapping of auditory perception: Event-related responses and electrocortical stimulation

PubMed Central

Sinai, A.; Crone, N.E.; Wied, H.M.; Franaszczuk, P.J.; Miglioretti, D.; Boatman-Reich, D.

2010-01-01

Objective We compared intracranial recordings of auditory event-related responses with electrocortical stimulation mapping (ESM) to determine their functional relationship. Methods Intracranial recordings and ESM were performed, using speech and tones, in adult epilepsy patients with subdural electrodes implanted over lateral left cortex. Evoked N1 responses and induced spectral power changes were obtained by trial averaging and time-frequency analysis. Results ESM impaired perception and comprehension of speech, not tones, at electrode sites in the posterior temporal lobe. There was high spatial concordance between ESM sites critical for speech perception and the largest spectral power (100% concordance) and N1 (83%) responses to speech. N1 responses showed good sensitivity (0.75) and specificity (0.82), but poor positive predictive value (0.32). Conversely, increased high-frequency power (>60 Hz) showed high specificity (0.98), but poorer sensitivity (0.67) and positive predictive value (0.67). Stimulus-related differences were observed in the spatial-temporal patterns of event-related responses. Conclusions Intracranial auditory event-related responses to speech were associated with cortical sites critical for auditory perception and comprehension of speech. Significance These results suggest that the distribution and magnitude of intracranial auditory event-related responses to speech reflect the functional significance of the underlying cortical regions and may be useful for pre-surgical functional mapping. PMID:19070540

A Three-Pronged Approach for Overcoming Design Fixation

ERIC Educational Resources Information Center

Smith, Steven M.; Linsey, Julie

2011-01-01

Earthquakes, lightning, and history-changing ideas are classic examples of powerful, unpredictable forces of nature. These sorts of phenomena have been difficult to explain and predict, an often frustrating fact as humans try to understand and control the significant influences in our lives. Historically, such phenomena have been attributed to…

Quantifying Improbability: An Analysis of the Lloyd’s of London Business Blackout Cyber Attack Scenario

DTIC Science & Technology

Scenarios that describe cyber attacks on the electric grid consistently predict significant disruptions to the economy and citizens quality of life...phenomena that deserve further investigation, such as the importance of some individual power plants in influencing the adversarys probability of

Conditional power and predictive power based on right censored data with supplementary auxiliary information.

PubMed

Sun, Libo; Wan, Ying

2018-04-22

Conditional power and predictive power provide estimates of the probability of success at the end of the trial based on the information from the interim analysis. The observed value of the time to event endpoint at the interim analysis could be biased for the true treatment effect due to early censoring, leading to a biased estimate of conditional power and predictive power. In such cases, the estimates and inference for this right censored primary endpoint are enhanced by incorporating a fully observed auxiliary variable. We assume a bivariate normal distribution of the transformed primary variable and a correlated auxiliary variable. Simulation studies are conducted that not only shows enhanced conditional power and predictive power but also can provide the framework for a more efficient futility interim analysis in terms of an improved accuracy in estimator, a smaller inflation in type II error and an optimal timing for such analysis. We also illustrated the new approach by a real clinical trial example. Copyright © 2018 John Wiley & Sons, Ltd.

Culture and medical decision making: Healthcare consumer perspectives in Japan and the United States.

PubMed

Alden, Dana L; Friend, John M; Lee, Angela Y; de Vries, Marieke; Osawa, Ryosuke; Chen, Qimei

2015-12-01

Two studies identified core value influences on medical decision-making processes across and within cultures. In Study 1, Japanese and American adults reported desired levels of medical decision-making influence across conditions that varied in seriousness. Cultural antecedents (interdependence, independence, and power distance) were also measured. In Study 2, American adults reviewed a colorectal cancer screening decision aid. Decision preparedness was measured along with interdependence, independence, and desire for medical information. In Study 1, higher interdependence predicted stronger desire for decision-making information in both countries, but was significantly stronger in Japan. The path from information desire to decision-making influence desire was significant only in Japan. The independence path to desire for decision-making influence was significant only in the United States. Power distance effects negatively predicted desire for decision-making influence only in the United States. For Study 2, high (low) interdependents and women (men) in the United States felt that a colorectal cancer screening decision aid helped prepare them more (less) for a medical consultation. Low interdependent men were at significantly higher risk for low decision preparedness. Study 1 suggests that Japanese participants may tend to view medical decision-making influence as an interdependent, information sharing exchange, whereas American respondents may be more interested in power sharing that emphasizes greater independence. Study 2 demonstrates the need to assess value influences on medical decision-making processes within and across cultures and suggests that individually tailored versions of decision aids may optimize decision preparedness. (c) 2015 APA, all rights reserved).

Ultrasound-Assisted Extraction of Cannabinoids from Cannabis Sativa L. Optimized by Response Surface Methodology.

PubMed

Agarwal, Charu; Máthé, Katalin; Hofmann, Tamás; Csóka, Levente

2018-03-01

Ultrasonication was used to extract bioactive compounds from Cannabis sativa L. such as polyphenols, flavonoids, and cannabinoids. The influence of 3 independent factors (time, input power, and methanol concentration) was evaluated on the extraction of total phenols (TPC), flavonoids (TF), ferric reducing ability of plasma (FRAP) and the overall yield. A face-centered central composite design was used for statistical modelling of the response data, followed by regression and analysis of variance in order to determine the significance of the model and factors. Both the solvent composition and the time significantly affected the extraction while the sonication power had no significant impact on the responses. The response predictions obtained at optimum extraction conditions of 15 min time, 130 W power, and 80% methanol were 314.822 mg GAE/g DW of TPC, 28.173 mg QE/g DW of TF, 18.79 mM AAE/g DW of FRAP, and 10.86% of yield. A good correlation was observed between the predicted and experimental values of the responses, which validated the mathematical model. On comparing the ultrasonic process with the control extraction, noticeably higher values were obtained for each of the responses. Additionally, ultrasound considerably improved the extraction of cannabinoids present in Cannabis. Low frequency ultrasound was employed to extract bioactive compounds from the inflorescence part of Cannabis. The responses evaluated were-total phenols, flavonoids, ferric reducing assay and yield. The solvent composition and time significantly influenced the extraction process. Appreciably higher extraction of cannabinoids was achieved on sonication against control. © 2018 Institute of Food Technologists®.

The predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability.

PubMed

Hoshi, Masayuki; Hozawa, Atsushi; Kuriyama, Shinichi; Nakaya, Naoki; Ohmori-Matsuda, Kaori; Sone, Toshimasa; Kakizaki, Masako; Niu, Kaijun; Fujita, Kazuki; Ueki, Shouzoh; Haga, Hiroshi; Nagatomi, Ryoichi; Tsuji, Ichiro

2012-08-01

To compare the predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability in community-dwelling elderly persons. Prospective cohort study. Participants were 813 aged 70 years and older, elderly Japanese residing in the community, included in the Tsurugaya Project, who were not disabled at the baseline in 2003. Physical function was assessed by the questionnaire of "Motor Fitness Scale". Physical performance measures consisted of maximum walking velocity, timed up and go test (TUG), leg extension power, and functional reach test. The area under the curve (AUC) of the receiver operating characteristic curve for disability was used to compare screening accuracy between Motor Fitness Scale and physical performance measures. Incident disability, defined as certification for long-term care insurance, was used as the endpoint. We observed 135 cases of incident disability during follow-up. The third or fourth quartile for each measure was associated with a significantly increased risk of disability in comparison with the highest quartile. The AUC was 0.70, 0.72, 0.70, 0.68, 0.69 and 0.74, for Motor Fitness Scale, maxi- mum walking velocity, TUG, leg extension power, functional reach test, and total performance score, respectively. The predictive power of physical function assessed by the Motor Fitness Scale was equivalent to that assessed by physical performance measures. Since Motor Fitness Scale can evaluate physical function safely and simply in comparison with physical performance tests, it would be a practical tool for screening persons at high risk of disability.

On- and off-eye spherical aberration of soft contact lenses and consequent changes of effective lens power.

PubMed

Dietze, Holger H; Cox, Michael J

2003-02-01

Soft contact lenses produce a significant level of spherical aberration affecting their power on-eye. A simple model assuming that a thin soft contact lens aligns to the cornea predicts that these effects are similar on-eye and off-eye. The wavefront aberration for 17 eyes and 33 soft contact lenses on-eye was measured with a Shack-Hartmann wavefront sensor. The Zernike coefficients describing the on-eye spherical aberration of the soft contact lens were compared with off-eye ray-tracing results. Paraxial and effective lens power changes were determined. The model predicts the on-eye spherical aberration of soft contact lenses closely. The resulting power change for a +/- 7.00 D spherical soft contact lens is +/- 0.5 D for a 6-mm pupil diameter and +/- 0.1 D for a 3-mm pupil diameter. Power change is negligible for soft contact lenses corrected for off-eye spherical aberration. For thin soft contact lenses, the level of spherical aberration and the consequent power change is similar on-eye and off-eye. Soft contact lenses corrected for spherical aberration in air will be expected to be aberration-free on-eye and produce only negligibly small power changes. For soft contact lenses without aberration correction, for higher levels of ametropia and large pupils, the soft contact lens power should be determined with trial lenses with their power and p value similar to the prescribed lens. The benefit of soft contact lenses corrected for spherical aberration depends on the level of ocular spherical aberration.

EEG alpha frequency correlates of burnout and depression: The role of gender.

PubMed

Tement, Sara; Pahor, Anja; Jaušovec, Norbert

2016-02-01

EEG alpha frequency band biomarkers of depression are widely explored. Due to their trait-like features, they may help distinguish between depressive and burnout symptomatology, which is often referred to as "work-related depression". The present correlational study strived to examine whether individual alpha frequency (IAF), power, and coherence in the alpha band can provide evidence for establishing burnout as a separate diagnostic entity. Resting EEG (eyes closed) was recorded in 117 individuals (42 males). In addition, the participants filled-out questionnaires of burnout and depression. Regression analyses highlighted the differential value of IAF and power in predicting burnout and depression. IAF was significantly related to depressive symptomatology, whereas power was linked mostly to burnout. Moreover, seven out of twelve interactions between EEG indicators and gender were significant. Connectivity patterns were significant for depression displaying gender-related differences. The results offer tentative support for establishing burnout as a separate clinical syndrome. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluating Upper-Body Strength and Power From a Single Test: The Ballistic Push-up.

PubMed

Wang, Ran; Hoffman, Jay R; Sadres, Eliahu; Bartolomei, Sandro; Muddle, Tyler W D; Fukuda, David H; Stout, Jeffrey R

2017-05-01

Wang, R, Hoffman, JR, Sadres, E, Bartolomei, S, Muddle, TWD, Fukuda, DH, and Stout, JR. Evaluating upper-body strength and power from a single test: the ballistic push-up. J Strength Cond Res 31(5): 1338-1345, 2017-The purpose of this study was to examine the reliability of the ballistic push-up (BPU) exercise and to develop a prediction model for both maximal strength (1 repetition maximum [1RM]) in the bench press exercise and upper-body power. Sixty recreationally active men completed a 1RM bench press and 2 BPU assessments in 3 separate testing sessions. Peak and mean force, peak and mean rate of force development, net impulse, peak velocity, flight time, and peak and mean power were determined. Intraclass correlation coefficients were used to examine the reliability of the BPU. Stepwise linear regression was used to develop 1RM bench press and power prediction equations. Intraclass correlation coefficient's ranged from 0.849 to 0.971 for the BPU measurements. Multiple regression analysis provided the following 1RM bench press prediction equation: 1RM = 0.31 × Mean Force - 1.64 × Body Mass + 0.70 (R = 0.837, standard error of the estimate [SEE] = 11 kg); time-based power prediction equation: Peak Power = 11.0 × Body Mass + 2012.3 × Flight Time - 338.0 (R = 0.658, SEE = 150 W), Mean Power = 6.7 × Body Mass + 1004.4 × Flight Time - 224.6 (R = 0.664, SEE = 82 W); and velocity-based power prediction equation: Peak Power = 8.1 × Body Mass + 818.6 × Peak Velocity - 762.0 (R = 0.797, SEE = 115 W); Mean Power = 5.2 × Body Mass + 435.9 × Peak Velocity - 467.7 (R = 0.838, SEE = 57 W). The BPU is a reliable test for both upper-body strength and power. Results indicate that the mean force generated from the BPU can be used to predict 1RM bench press, whereas peak velocity and flight time measured during the BPU can be used to predict upper-body power. These findings support the potential use of the BPU as a valid method to evaluate upper-body strength and power.

Wind Power predictability a risk factor in the design, construction and operation of Wind Generation Turbines

NASA Astrophysics Data System (ADS)

Thiesen, J.; Gulstad, L.; Ristic, I.; Maric, T.

2010-09-01

Summit: The wind power predictability is often a forgotten decision and planning factor for most major wind parks, both onshore and offshore. The results of the predictability are presented after having examined a number of European offshore and offshore parks power predictability by using three(3) mesoscale model IRIE_GFS and IRIE_EC and WRF. Full description: It is well known that the potential wind production is changing with latitude and complexity in terrain, but how big are the changes in the predictability and the economic impacts on a project? The concept of meteorological predictability has hitherto to some degree been neglected as a risk factor in the design, construction and operation of wind power plants. Wind power plants are generally built in places where the wind resources are high, but these are often also sites where the predictability of the wind and other weather parameters is comparatively low. This presentation addresses the question of whether higher predictability can outweigh lower average wind speeds with regard to the overall economy of a wind power project. Low predictability also tends to reduce the value of the energy produced. If it is difficult to forecast the wind on a site, it will also be difficult to predict the power production. This, in turn, leads to increased balance costs and a less reduced carbon emission from the renewable source. By investigating the output from three(3) mesoscale models IRIE and WRF, using ECMWF and GFS as boundary data over a forecasting period of 3 months for 25 offshore and onshore wind parks in Europe, the predictability are mapped. Three operational mesoscale models with two different boundary data have been chosen in order to eliminate the uncertainty with one mesoscale model. All mesoscale models are running in a 10 km horizontal resolution. The model output are converted into "day a head" wind turbine generation forecasts by using a well proven advanced physical wind power model. The power models are using a number of weather parameters like wind speed in different heights, friction velocity and DTHV. The 25 wind sites are scattered around in Europe and contains 4 offshore parks and 21 onshore parks in various terrain complexity. The "day a head" forecasts are compared with production data and predictability for the period February 2010-April 2010 are given in Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE). The power predictability results are mapped for each turbine giving a clear picture of the predictability in Europe. . Finally a economic analysis are shown for each wind parks in different regimes of predictability will be compared with regard to the balance costs that result from errors in the wind power prediction. Analysis shows that it may very well be profitable to place wind parks in regions of lower, but more predictable wind ressource. Authors: Ivan Ristic, CTO Weather2Umberlla D.O.O Tomislav Maric, Meteorologist at Global Flow Solutions Vestas Wind Technology R&D Line Gulstad, Manager Global Flow Solutions Vestas Wind Technology R&D Jesper Thiesen, CEO ConWx ApS

Piezoelectric Power Requirements for Active Vibration Control

NASA Technical Reports Server (NTRS)

Brennan, Matthew C.; McGowan, Anna-Maria Rivas

1997-01-01

This paper presents a method for predicting the power consumption of piezoelectric actuators utilized for active vibration control. Analytical developments and experimental tests show that the maximum power required to control a structure using surface-bonded piezoelectric actuators is independent of the dynamics between the piezoelectric actuator and the host structure. The results demonstrate that for a perfectly-controlled system, the power consumption is a function of the quantity and type of piezoelectric actuators and the voltage and frequency of the control law output signal. Furthermore, as control effectiveness decreases, the power consumption of the piezoelectric actuators decreases. In addition, experimental results revealed a non-linear behavior in the material properties of piezoelectric actuators. The material non- linearity displayed a significant increase in capacitance with an increase in excitation voltage. Tests show that if the non-linearity of the capacitance was accounted for, a conservative estimate of the power can easily be determined.

Primordial black holes and uncertainties in the choice of the window function

NASA Astrophysics Data System (ADS)

Ando, Kenta; Inomata, Keisuke; Kawasaki, Masahiro

2018-05-01

Primordial black holes (PBHs) can be produced by the perturbations that exit the horizon during the inflationary phase. While inflation models predict the power spectrum of the perturbations in Fourier space, the PBH abundance depends on the probability distribution function of density perturbations in real space. To estimate the PBH abundance in a given inflation model, we must relate the power spectrum in Fourier space to the probability density function in real space by coarse graining the perturbations with a window function. However, there are uncertainties on what window function should be used, which could change the relation between the PBH abundance and the power spectrum. This is particularly important in considering PBHs with mass 30 M⊙, which account for the LIGO events because the required power spectrum is severely constrained by the observations. In this paper, we investigate how large an influence the uncertainties on the choice of a window function has over the power spectrum required for LIGO PBHs. As a result, it is found that the uncertainties significantly affect the prediction for the stochastic gravitational waves induced by the second-order effect of the perturbations. In particular, the pulsar timing array constraints on the produced gravitational waves could disappear for the real-space top-hat window function.

ULF Wave Activity in the Magnetosphere: Resolving Solar Wind Interdependencies to Identify Driving Mechanisms

NASA Astrophysics Data System (ADS)

Bentley, S. N.; Watt, C. E. J.; Owens, M. J.; Rae, I. J.

2018-04-01

Ultralow frequency (ULF) waves in the magnetosphere are involved in the energization and transport of radiation belt particles and are strongly driven by the external solar wind. However, the interdependency of solar wind parameters and the variety of solar wind-magnetosphere coupling processes make it difficult to distinguish the effect of individual processes and to predict magnetospheric wave power using solar wind properties. We examine 15 years of dayside ground-based measurements at a single representative frequency (2.5 mHz) and a single magnetic latitude (corresponding to L ˜ 6.6RE). We determine the relative contribution to ULF wave power from instantaneous nonderived solar wind parameters, accounting for their interdependencies. The most influential parameters for ground-based ULF wave power are solar wind speed vsw, southward interplanetary magnetic field component Bz<0, and summed power in number density perturbations δNp. Together, the subordinate parameters Bz and δNp still account for significant amounts of power. We suggest that these three parameters correspond to driving by the Kelvin-Helmholtz instability, formation, and/or propagation of flux transfer events and density perturbations from solar wind structures sweeping past the Earth. We anticipate that this new parameter reduction will aid comparisons of ULF generation mechanisms between magnetospheric sectors and will enable more sophisticated empirical models predicting magnetospheric ULF power using external solar wind driving parameters.

Relationship Power, Sexual Decision Making, and HIV Risk Among Midlife and Older Women.

PubMed

Altschuler, Joanne; Rhee, Siyon

2015-01-01

The number of midlife and older women with HIV/AIDS is high and increasing, especially among women of color. This article addresses these demographic realities by reporting on findings about self-esteem, relationship power, and HIV risk from a pilot study of midlife and older women. A purposive sample (N = 110) of ethnically, economically, and educationally diverse women 40 years and older from the Greater Los Angeles Area was surveyed to determine their levels of self-esteem, general relationship power, sexual decision-making power, safer sex behaviors, and HIV knowledge. Women with higher levels of self-esteem exercised greater power in their relationships with their partner. Women with higher levels of general relationship power and self-esteem tend to exercise greater power in sexual decision making, such as having sex and choosing sexual acts. Income and sexual decision-making power were statistically significant in predicting the use of condoms. Implications and recommendations for future HIV/AIDS research and intervention targeting midlife and older women are presented.

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

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

Abbas, Nikhar; Tom, Nathan M

2017-06-03

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

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

Abbas, Nikhar; Tom, Nathan

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

NASA Astrophysics Data System (ADS)

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

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Experimental validation of boundary element methods for noise prediction

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Oswald, Fred B.

1992-01-01

Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

Predicting Rediated Noise With Power Flow Finite Element Analysis

DTIC Science & Technology

2007-02-01

Defence R&D Canada – Atlantic DEFENCE DÉFENSE & Predicting Rediated Noise With Power Flow Finite Element Analysis D. Brennan T.S. Koko L. Jiang J...PREDICTING RADIATED NOISE WITH POWER FLOW FINITE ELEMENT ANALYSIS D.P. Brennan T.S. Koko L. Jiang J.C. Wallace Martec Limited Martec Limited...model- or full-scale data before it is available for general use. Brennan, D.P., Koko , T.S., Jiang, L., Wallace, J.C. 2007. Predicting Radiated

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

NASA Astrophysics Data System (ADS)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Social motives and cognitive power-sex associations: predictors of aggressive sexual behavior.

PubMed

Zurbriggen, E L

2000-03-01

The present study investigated whether implicit social motives and cognitive power-sex associations would predict self-reports of aggressive sexual behavior. Participants wrote stories in response to Thematic Apperception Test pictures, which were scored for power and affiliation-intimacy motives. They also completed a lexical-decision priming task that provided an index of the strength of the cognitive association between the concepts of "power" and "sexuality." For men, high levels of power motivation and strong power-sex associations predicted more frequent aggression. There was also an interaction: Power motivation was unrelated to aggression for men with the weakest power-sex associations. For women, high levels of affiliation-intimacy motivation were associated with more frequent aggression. Strong power-sex associations were also predictive for women but only when affiliation-intimacy motivation was high.

Usefulness of morning home blood pressure measurements in patients with type 2 diabetes mellitus: results of a 10-year, prospective, longitudinal study.

PubMed

Kamoi, Kyuzi

2015-01-01

Previous cross-sectional studies and 6-year longitudinal study have demonstrated that home blood pressure (HBP) measurements upon awakening have a stronger predictive power for death, micro- and macrovascular complications than clinic blood pressure (CBP) measurements in patients with type 2 diabetes (T2DM). This study investigated which of these measurements offers stronger predictive power for outcomes over 10 years. At baseline, 400 Japanese patients with T2DM were classified as having hypertension (HT) or normotension (NT) based on HBP and CBP. The mean survey duration was 95 months. Primary and secondary end-points were death and new or worsened micro- and macrovascular complications, respectively. Differences in outcomes for each end-point between HT and NT patients were analyzed using Kaplan-Meier survival curves and log-rank testing. Associated risk factors were assessed using Cox proportional hazards analysis. Based on HBP, death and micro- and macrovascular complications were significantly higher in patients with HT than with NT at baseline and end-point. Based on CBP, there were no significant differences in incidence of death, micro- or macrovascular complications between patients with HT and NT at baseline and end-point, although a significant difference in incidence of death was observed between the HT and NT groups at end-point. However, the significance was significantly lower in CBP than in HBP. One risk factor associated with micro- and macrovascular complications in patients with HBP was therapy for HT. This 10-year longitudinal study of patients with T2DM demonstrated that elevated HBP upon awakening is predictive of death, and micro- and macrovascular complications.

Using prediction markets to estimate the reproducibility of scientific research.

PubMed

Dreber, Anna; Pfeiffer, Thomas; Almenberg, Johan; Isaksson, Siri; Wilson, Brad; Chen, Yiling; Nosek, Brian A; Johannesson, Magnus

2015-12-15

Concerns about a lack of reproducibility of statistically significant results have recently been raised in many fields, and it has been argued that this lack comes at substantial economic costs. We here report the results from prediction markets set up to quantify the reproducibility of 44 studies published in prominent psychology journals and replicated in the Reproducibility Project: Psychology. The prediction markets predict the outcomes of the replications well and outperform a survey of market participants' individual forecasts. This shows that prediction markets are a promising tool for assessing the reproducibility of published scientific results. The prediction markets also allow us to estimate probabilities for the hypotheses being true at different testing stages, which provides valuable information regarding the temporal dynamics of scientific discovery. We find that the hypotheses being tested in psychology typically have low prior probabilities of being true (median, 9%) and that a "statistically significant" finding needs to be confirmed in a well-powered replication to have a high probability of being true. We argue that prediction markets could be used to obtain speedy information about reproducibility at low cost and could potentially even be used to determine which studies to replicate to optimally allocate limited resources into replications.

Impacts of past and future climate change on wind energy resources in the United States

NASA Astrophysics Data System (ADS)

McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.

2009-12-01

The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.

Impact of the 4 April 2014 Saharan dust outbreak on the photovoltaic power generation in Germany

NASA Astrophysics Data System (ADS)

Rieger, Daniel; Steiner, Andrea; Bachmann, Vanessa; Gasch, Philipp; Förstner, Jochen; Deetz, Konrad; Vogel, Bernhard; Vogel, Heike

2017-11-01

The importance for reliable forecasts of incoming solar radiation is growing rapidly, especially for those countries with an increasing share in photovoltaic (PV) power production. The reliability of solar radiation forecasts depends mainly on the representation of clouds and aerosol particles absorbing and scattering radiation. Especially under extreme aerosol conditions, numerical weather prediction has a systematic bias in the solar radiation forecast. This is caused by the design of numerical weather prediction models, which typically account for the direct impact of aerosol particles on radiation using climatological mean values and the impact on cloud formation assuming spatially and temporally homogeneous aerosol concentrations. These model deficiencies in turn can lead to significant economic losses under extreme aerosol conditions. For Germany, Saharan dust outbreaks occurring 5 to 15 times per year for several days each are prominent examples for conditions, under which numerical weather prediction struggles to forecast solar radiation adequately. We investigate the impact of mineral dust on the PV-power generation during a Saharan dust outbreak over Germany on 4 April 2014 using ICON-ART, which is the current German numerical weather prediction model extended by modules accounting for trace substances and related feedback processes. We find an overall improvement of the PV-power forecast for 65 % of the pyranometer stations in Germany. Of the nine stations with very high differences between forecast and measurement, eight stations show an improvement. Furthermore, we quantify the direct radiative effects and indirect radiative effects of mineral dust. For our study, direct effects account for 64 %, indirect effects for 20 % and synergistic interaction effects for 16 % of the differences between the forecast including mineral dust radiative effects and the forecast neglecting mineral dust.

Risk of mortality associated to chronic kidney disease in patients with type 2 diabetes mellitus: a 13-year follow-up.

PubMed

Gimeno-Orna, José Antonio; Blasco-Lamarca, Yolanda; Campos-Gutierrez, Belén; Molinero-Herguedas, Edmundo; Lou-Arnal, Luis Miguel; García-García, Blanca

2015-01-01

Our aim was to assess the usefulness of glomerular filtration rate (GFR) and urinary albumin excretion (UAE) to predict the risk of mortality in patients with type 2 diabetes mellitus. This is a prospective cohort study in patients with type 2 diabetes mellitus. Clinical end-point was mortality rate. GFR was measured in ml/min/1.73 m2 and stratified in 3 categories (≥60; 45-59; <45); UAE was measured in mg/24hours and was also stratified in 3 categories (<30; 30-300; >300). Mortality rates were reported per 1000 patient-years. Cox regression models were used to predict mortality risk associated with combined GFR and UAE. The predictive power was estimated with C-Harrell statistic. A total of 453 patients (39.3% males), aged 64.9 (SD 9.3) years were included; mean diabetes duration was 10.4 (SD 7.5) years. Median follow-up was 13 years. Total mortality rate was 39.5/1000. The progressive increase in mortality in the successive categories of GFR and UAE was statistically significant (P<.001). In a multivariable analysis, UAE (HR30-300=1.02 and HR>300=2.83; X2=11.6; P =.003) and GFR (HR45-59=1.34 and HR<45=1.84; X2=6.4; P =.041) were independent predictors for mortality, with no significant interaction. Simultaneous inclusion of GFR and UAE improved the predictive power of models (C-Harrell 0.741 vs. 0.726; P =.045). GFR and UAE are independent predictors for mortality in type 2 diabetic patients and do not show a statistically significant interaction. Copyright © 2015 The Authors. Published by Elsevier España, S.L.U. All rights reserved.

Effect of Adding McKenzie Syndrome, Centralization, Directional Preference, and Psychosocial Classification Variables to a Risk-Adjusted Model Predicting Functional Status Outcomes for Patients With Lumbar Impairments.

PubMed

Werneke, Mark W; Edmond, Susan; Deutscher, Daniel; Ward, Jason; Grigsby, David; Young, Michelle; McGill, Troy; McClenahan, Brian; Weinberg, Jon; Davidow, Amy L

2016-09-01

Study Design Retrospective cohort. Background Patient-classification subgroupings may be important prognostic factors explaining outcomes. Objectives To determine effects of adding classification variables (McKenzie syndrome and pain patterns, including centralization and directional preference; Symptom Checklist Back Pain Prediction Model [SCL BPPM]; and the Fear-Avoidance Beliefs Questionnaire subscales of work and physical activity) to a baseline risk-adjusted model predicting functional status (FS) outcomes. Methods Consecutive patients completed a battery of questionnaires that gathered information on 11 risk-adjustment variables. Physical therapists trained in Mechanical Diagnosis and Therapy methods classified each patient by McKenzie syndromes and pain pattern. Functional status was assessed at discharge by patient-reported outcomes. Only patients with complete data were included. Risk of selection bias was assessed. Prediction of discharge FS was assessed using linear stepwise regression models, allowing 13 variables to enter the model. Significant variables were retained in subsequent models. Model power (R(2)) and beta coefficients for model variables were estimated. Results Two thousand sixty-six patients with lumbar impairments were evaluated. Of those, 994 (48%), 10 (<1%), and 601 (29%) were excluded due to incomplete psychosocial data, McKenzie classification data, and missing FS at discharge, respectively. The final sample for analyses was 723 (35%). Overall R(2) for the baseline prediction FS model was 0.40. Adding classification variables to the baseline model did not result in significant increases in R(2). McKenzie syndrome or pain pattern explained 2.8% and 3.0% of the variance, respectively. When pain pattern and SCL BPPM were added simultaneously, overall model R(2) increased to 0.44. Although none of these increases in R(2) were significant, some classification variables were stronger predictors compared with some other variables included in the baseline model. Conclusion The small added prognostic capabilities identified when combining McKenzie or pain-pattern classifications with the SCL BPPM classification did not significantly improve prediction of FS outcomes in this study. Additional research is warranted to investigate the importance of classification variables compared with those used in the baseline model to maximize predictive power. Level of Evidence Prognosis, level 4. J Orthop Sports Phys Ther 2016;46(9):726-741. Epub 31 Jul 2016. doi:10.2519/jospt.2016.6266.

Power output of field-based downhill mountain biking.

PubMed

Hurst, Howard Thomas; Atkins, Stephen

2006-10-01

The purpose of this study was to assess the power output of field-based downhill mountain biking. Seventeen trained male downhill cyclists (age 27.1 +/- 5.1 years) competing nationally performed two timed runs of a measured downhill course. An SRM powermeter was used to simultaneously record power, cadence, and speed. Values were sampled at 1-s intervals. Heart rates were recorded at 5-s intervals using a Polar S710 heart rate monitor. Peak and mean power output were 834 +/- 129 W and 75 +/- 26 W respectively. Mean power accounted for only 9% of peak values. Paradoxically, mean heart rate was 168 +/- 9 beats x min(-1) (89% of age-predicted maximum heart rate). Mean cadence (27 +/- 5 rev x min(-1)) was significantly related to speed (r = 0.51; P < 0.01). Analysis revealed an average of 38 pedal actions per run, with average pedalling periods of 5 s. Power and cadence were not significantly related to run time or any other variable. Our results support the intermittent nature of downhill mountain biking. The poor relationships between power and run time and between cadence and run time suggest they are not essential pre-requisites to downhill mountain biking performance and indicate the importance of riding dynamics to overall performance.

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

Newman, Jennifer F.; Clifton, Andrew

Currently, cup anemometers on meteorological towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability; however, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install meteorological towers at potential sites. As a result, remote-sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. Although lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount ofmore » uncertainty surrounding the measurement of turbulence using these devices. Errors in lidar turbulence estimates are caused by a variety of factors, including instrument noise, volume averaging, and variance contamination, in which the magnitude of these factors is highly dependent on measurement height and atmospheric stability. As turbulence has a large impact on wind power production, errors in turbulence measurements will translate into errors in wind power prediction. The impact of using lidars rather than cup anemometers for wind power prediction must be understood if lidars are to be considered a viable alternative to cup anemometers.In this poster, the sensitivity of power prediction error to typical lidar turbulence measurement errors is assessed. Turbulence estimates from a vertically profiling WINDCUBE v2 lidar are compared to high-resolution sonic anemometer measurements at field sites in Oklahoma and Colorado to determine the degree of lidar turbulence error that can be expected under different atmospheric conditions. These errors are then incorporated into a power prediction model to estimate the sensitivity of power prediction error to turbulence measurement error. Power prediction models, including the standard binning method and a random forest method, were developed using data from the aeroelastic simulator FAST for a 1.5 MW turbine. The impact of lidar turbulence error on the predicted power from these different models is examined to determine the degree of turbulence measurement accuracy needed for accurate power prediction.« less

Perceived parental behaviour, self-esteem and happiness.

PubMed

Furnham, A; Cheng, H

2000-10-01

This study set out to determine to what extent recalled parental rearing styles (authoritarian, authoritativeness, permissiveness), personality (extraversion, neuroticism, psychoticism, lie), and self-esteem predicted self-rated happiness in a normal, nonclinical, population of young people in their late teens and early 20s. Each participant completed a few questionnaires: the Eysenck Personality Questionnaire (revised), the Rosenberg Self-Esteem Scale, the Parental Authority Questionnaire and the Oxford Happiness Inventory. It was predicted that sex, extraversion, neuroticism, self-esteem and both maternal and paternal authoritativeness would be significant predictors of happiness. Regressional and path analysis showed self-esteem to be the most dominant and powerful predictor of happiness. The effect of sex on happiness was moderated by neuroticism, which related to self-esteem, which directly influenced happiness. Stability, extraversion and maternal authoritativeness were significant predictors of self-esteem accounting for one-third of the variance. The results are considered in terms of the distinct literature on the relation between personality and happiness and on the relation between parental styles and self-esteem. Self-esteem was both a direct and a moderator variable for young people's self-reported happiness. Extraversion had both direct and indirect predictive power of happiness, whereas neuroticism predicted happiness mediating through self-esteem. Maternal authoritativeness was the only direct predictor of happiness when paternal and maternal rearing styles were examined together, suggesting that a reasonable discipline exercised by mothers towards their children was particularly beneficial in enhancing the offsprings' self-esteem.

A nationally representative study of emotional competence and health.

PubMed

Mikolajczak, Moïra; Avalosse, Hervé; Vancorenland, Sigrid; Verniest, Rebekka; Callens, Michael; van Broeck, Nady; Fantini-Hauwel, Carole; Mierop, Adrien

2015-10-01

Emotional competence (EC; also called "emotional intelligence"), which refers to individual differences in the identification, understanding, expression, regulation, and use of one's emotions and those of others, has been found to be an important predictor of individuals' adaptation to their environment. Higher EC is associated with greater happiness, better mental health, more satisfying social and marital relationships, and greater occupational success. Whereas a considerable amount of research has documented the significance of EC, 1 domain has been crucially under investigated: the relationship between EC and physical health. We examined the relationship between EC and objective health indicators in 2 studies (N1 = 1,310; N2 = 9,616) conducted in collaboration with the largest Mutual Benefit Society in Belgium. These studies allowed us (a) to compare the predictive power of EC with other well-known predictors of health such as age, sex, Body Mass Index, education level, health behaviors (diet, physical activity, smoking and drinking habits), positive and negative affect, and social support; (b) to clarify the relative weight of the various EC dimensions in predicting health; and (c) to determine to what extent EC moderates the effect of already known predictors on health. Results show that EC is a significant predictor of health that has incremental predictive power over and above other predictors. Findings also show that high EC significantly attenuates (and sometimes compensates for) the impact of other risk factors. Therefore, we argue that EC deserves greater interest and attention from health professionals and governments. (c) 2015 APA, all rights reserved).

POWER Web Access Data

Atmospheric Science Data Center

2018-05-27

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

Risk factors predict post-traumatic stress disorder differently in men and women

PubMed Central

Christiansen, Dorte M; Elklit, Ask

2008-01-01

Background About twice as many women as men develop post-traumatic stress disorder (PTSD), even though men as a group are exposed to more traumatic events. Exposure to different trauma types does not sufficiently explain why women are more vulnerable. Methods The present work examines the effect of age, previous trauma, negative affectivity (NA), anxiety, depression, persistent dissociation, and social support on PTSD separately in men and women. Subjects were exposed to either a series of explosions in a firework factory near a residential area or to a high school stabbing incident. Results Some gender differences were found in the predictive power of well known risk factors for PTSD. Anxiety predicted PTSD in men, but not in women, whereas the opposite was found for depression. Dissociation was a better predictor for PTSD in women than in men in the explosion sample but not in the stabbing sample. Initially, NA predicted PTSD better in women than men in the explosion sample, but when compared only to other significant risk factors, it significantly predicted PTSD for both men and women in both studies. Previous traumatic events and age did not significantly predict PTSD in either gender. Conclusion Gender differences in the predictive value of social support on PTSD appear to be very complex, and no clear conclusions can be made based on the two studies included in this article. PMID:19017412

High-Power Piezoelectric Acoustic-Electric Power Feedthru for Metal Walls

NASA Technical Reports Server (NTRS)

Bao, Xiaoqi; Biederman, Will; Sherrit, Stewart; Badescu, Mircea; Bar-Cohen, Yoseph; Jones, Christopher; Aldrich, Jack; Chang, Zensheu

2008-01-01

Piezoelectric acoustic-electric power feed-through devices transfer electric power wirelessly through a solid wall by using acoustic waves. This approach allows for the removal of holes through structures. The technology is applicable to power supply for electric equipment inside sealed containers, vacuum or pressure vessels, etc where the holes on the wall are prohibitive or result in significant performance degrade or complex designs. In the author's previous work, 100-W electric power was transferred through a metal wall by a small, simple-structure piezoelectric device. To meet requirements of higher power applications, the feasibility to transfer kilowatts level power was investigated. Pre-stressed longitudinal piezoelectric feedthru devices were analyzed by finite element model. An equivalent circuit model was developed to predict the power transfer characteristics to different electric loads. Based on the analysis results, a prototype device was designed, fabricated and a demonstration of the transmission of electric power up to 1-kW was successfully conducted. The methods to minimize the plate wave excitation on the wall were also analyzed. Both model analysis and experimental results are presented in detail in this presentation.

Wilkinson Microwave Anisotropy Probe (WMAP) First Year Observations: TE Polarization

NASA Technical Reports Server (NTRS)

Kogut, A.; Spergel, D. N.; Barnes, C.; Bennett, C. L.; Halpern, M.; Hinshaw, G.; Jarosik, N.; Limon, M.; Meyer, S. S.; Page, L.;

Heart rate variability measured early in patients with evolving acute coronary syndrome and 1-year outcomes of rehospitalization and mortality.

PubMed

Harris, Patricia R E; Stein, Phyllis K; Fung, Gordon L; Drew, Barbara J

2014-01-01

This study sought to examine the prognostic value of heart rate variability (HRV) measurement initiated immediately after emergency department presentation for patients with acute coronary syndrome (ACS). Altered HRV has been associated with adverse outcomes in heart disease, but the value of HRV measured during the earliest phases of ACS related to risk of 1-year rehospitalization and death has not been established. Twenty-four-hour Holter recordings of 279 patients with ACS were initiated within 45 minutes of emergency department arrival; recordings with ≥18 hours of sinus rhythm were selected for HRV analysis (number [N] =193). Time domain, frequency domain, and nonlinear HRV were examined. Survival analysis was performed. During the 1-year follow-up, 94 patients were event-free, 82 were readmitted, and 17 died. HRV was altered in relation to outcomes. Predictors of rehospitalization included increased normalized high frequency power, decreased normalized low frequency power, and decreased low/high frequency ratio. Normalized high frequency >42 ms(2) predicted rehospitalization while controlling for clinical variables (hazard ratio [HR] =2.3; 95% confidence interval [CI] =1.4-3.8, P=0.001). Variables significantly associated with death included natural logs of total power and ultra low frequency power. A model with ultra low frequency power <8 ms(2) (HR =3.8; 95% CI =1.5-10.1; P=0.007) and troponin >0.3 ng/mL (HR =4.0; 95% CI =1.3-12.1; P=0.016) revealed that each contributed independently in predicting mortality. Nonlinear HRV variables were significant predictors of both outcomes. HRV measured close to the ACS onset may assist in risk stratification. HRV cut-points may provide additional, incremental prognostic information to established assessment guidelines, and may be worthy of additional study.

Revising the predictions of inflation for the cosmic microwave background anisotropies.

PubMed

Agulló, Iván; Navarro-Salas, José; Olmo, Gonzalo J; Parker, Leonard

2009-08-07

We point out that, if quantum field renormalization is taken into account and the counterterms are evaluated at the Hubble-radius crossing time or few e-foldings after it, the predictions of slow-roll inflation for both the scalar and the tensorial power spectrum change significantly. This leads to a change in the consistency condition that relates the tensor-to-scalar amplitude ratio with spectral indices. A reexamination of the potentials varphi;{2} and varphi;{4} shows that both are compatible with five-year WMAP data. Only when the counterterms are evaluated at much larger times beyond the end of inflation does one recover the standard predictions. The alternative predictions presented here may soon come within the range of measurement of near-future experiments.

The impact of experimental measurement errors on long-term viscoelastic predictions. [of structural materials

NASA Technical Reports Server (NTRS)

Tuttle, M. E.; Brinson, H. F.

1986-01-01

The impact of flight error in measured viscoelastic parameters on subsequent long-term viscoelastic predictions is numerically evaluated using the Schapery nonlinear viscoelastic model. Of the seven Schapery parameters, the results indicated that long-term predictions were most sensitive to errors in the power law parameter n. Although errors in the other parameters were significant as well, errors in n dominated all other factors at long times. The process of selecting an appropriate short-term test cycle so as to insure an accurate long-term prediction was considered, and a short-term test cycle was selected using material properties typical for T300/5208 graphite-epoxy at 149 C. The process of selection is described, and its individual steps are itemized.

Chronic pain and praying to a higher power: useful or useless?

PubMed

Andersson, Gerhard

2008-06-01

In the present study a Swedish sample of 118 persons with chronic pain completed online tests on two occasions in association with treatment trials. A three item subscale measuring praying as a coping strategy was derived from the Coping Strategies Questionnaire (CSQ), but adapted to refer to "a higher power" instead of "God". Measures of pain and anxiety/depression were also included. Results revealed significant associations between praying and pain interference and impairment. Praying was also associated with anxiety and depression scores. Results also showed that prayer predicted depression scores at follow-up, and that follow-up prayer was predicted by pain interference at first measurement occasion. Overall, if prayer had any relation with the other variables it was in the negative direction of more distress being associated with more praying both concurrently and prospectively.

Improved pump turbine transient behaviour prediction using a Thoma number-dependent hillchart model

NASA Astrophysics Data System (ADS)

Manderla, M.; Kiniger, K.; Koutnik, J.

2014-03-01

Water hammer phenomena are important issues for high head hydro power plants. Especially, if several reversible pump-turbines are connected to the same waterways there may be strong interactions between the hydraulic machines. The prediction and coverage of all relevant load cases is challenging and difficult using classical simulation models. On the basis of a recent pump-storage project, dynamic measurements motivate an improved modeling approach making use of the Thoma number dependency of the actual turbine behaviour. The proposed approach is validated for several transient scenarios and turns out to increase correlation between measurement and simulation results significantly. By applying a fully automated simulation procedure broad operating ranges can be covered which provides a consistent insight into critical load case scenarios. This finally allows the optimization of the closing strategy and hence the overall power plant performance.

The potential distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Libya based on ecological niche model.

PubMed

Abdel-Dayem, M S; Annajar, B B; Hanafi, H A; Obenauer, P J

2012-05-01

The increased cases of cutaneous leishmaniasis vectored by Phlebotomus papatasi (Scopoli) in Libya have driven considerable effort to develop a predictive model for the potential geographical distribution of this disease. We collected adult P. papatasi from 17 sites in Musrata and Yefern regions of Libya using four different attraction traps. Our trap results and literature records describing the distribution of P. papatasi were incorporated into a MaxEnt algorithm prediction model that used 22 environmental variables. The model showed a high performance (AUC = 0.992 and 0.990 for training and test data, respectively). High suitability for P. papatasi was predicted to be largely confined to the coast at altitudes <600 m. Regions south of 300 degrees N latitude were calculated as unsuitable for this species. Jackknife analysis identified precipitation as having the most significant predictive power, while temperature and elevation variables were less influential. The National Leishmaniasis Control Program in Libya may find this information useful in their efforts to control zoonotic cutaneous leishmaniasis. Existing records are strongly biased toward a few geographical regions, and therefore, further sand fly collections are warranted that should include documentation of such factors as soil texture and humidity, land cover, and normalized difference vegetation index (NDVI) data to increase the model's predictive power.

Spur-Gear-System Efficiency at Part and Full Load

NASA Technical Reports Server (NTRS)

Anderson, N. E.; Loewenthal, S. H.

1980-01-01

A simple method for predicting the part- and full-load power loss of a steel spur gearset of arbitrary geometry supported by ball bearings is described. The analysis algebraically accounts for losses due to gear sliding, rolling traction, and windage in addition to support-ball-bearing losses. The analysis compares favorably with test data. A theoretical comparison of the component losses indicates that losses due to gear rolling traction, windage, and support bearings are significant and should be included along with gear sliding loss in a calculation of gear-system power loss.

Power, Status and Network Perceptions: The Effects of Network Bias on Organizational Outcomes

DTIC Science & Technology

2012-09-01

OF RESPONSIBLE PERSON Lisa Boyce a. REPORT UNCLAS b. ABSTRACT UNCLAS c. THIS PAGE UNCLAS 19b. TELEPHONE NUMBER (Include area code) +44 (0...with our prediction, we found that power was a significant predictor (B = .03, SE = .01, Wald χ² = 5.81, p < .01) while controlling for the actual...density of the advice network (B = 1.37, SE = .63, Wald χ² = 4.78, p < .05), likelihood ratio χ² (2, N = 124) = 206.13, p < .001. As before, we

Multigene interactions and the prediction of depression in the Wisconsin Longitudinal Study

PubMed Central

Roetker, Nicholas S; Yonker, James A; Lee, Chee; Chang, Vicky; Basson, Jacob J; Roan, Carol L; Hauser, Taissa S; Hauser, Robert M

2012-01-01

Objectives Single genetic loci offer little predictive power for the identification of depression. This study examined whether an analysis of gene–gene (G × G) interactions of 78 single nucleotide polymorphisms (SNPs) in genes associated with depression and age-related diseases would identify significant interactions with increased predictive power for depression. Design A retrospective cohort study. Setting A survey of participants in the Wisconsin Longitudinal Study. Participants A total of 4811 persons (2464 women and 2347 men) who provided saliva for genotyping; the group comes from a randomly selected sample of Wisconsin high school graduates from the class of 1957 as well as a randomly selected sibling, almost all of whom are non-Hispanic white. Primary outcome measure Depression as determine by the Composite International Diagnostic Interview–Short-Form. Results Using a classification tree approach (recursive partitioning (RP)), the authors identified a number of candidate G × G interactions associated with depression. The primary SNP splits revealed by RP (ANKK1 rs1800497 (also known as DRD2 Taq1A) in men and DRD2 rs224592 in women) were found to be significant as single factors by logistic regression (LR) after controlling for multiple testing (p=0.001 for both). Without considering interaction effects, only one of the five subsequent RP splits reached nominal significance in LR (FTO rs1421085 in women, p=0.008). However, after controlling for G × G interactions by running LR on RP-specific subsets, every split became significant and grew larger in magnitude (OR (before) → (after): men: GNRH1 novel SNP: (1.43 → 1.57); women: APOC3 rs2854116: (1.28 → 1.55), ACVR2B rs3749386: (1.11 → 2.17), FTO rs1421085: (1.32 → 1.65), IL6 rs1800795: (1.12 → 1.85)). Conclusions The results suggest that examining G × G interactions improves the identification of genetic associations predictive of depression. 4 of the SNPs identified in these interactions were located in two pathways well known to impact depression: neurotransmitter (ANKK1 and DRD2) and neuroendocrine (GNRH1 and ACVR2B) signalling. This study demonstrates the utility of RP analysis as an efficient and powerful exploratory analysis technique for uncovering genetic and molecular pathway interactions associated with disease aetiology. PMID:22761283

Experimental observations of nonlinearly enhanced 2omega-UH electromagnetic radiation excited by steady-state colliding electron beams

NASA Technical Reports Server (NTRS)

Intrator, T.; Hershkowitz, N.; Chan, C.

1984-01-01

Counterstreaming large-diameter electron beams in a steady-state laboratory experiment are observed to generate transverse radiation at twice the upper-hybrid frequency (2omega-UH) with a quadrupole radiation pattern. The electromagnetic wave power density is nonlinearly enhanced over the power density obtained from a single beam-plasma system. Electromagnetic power density scales exponentially with beam energy and increases with ion mass. Weak turbulence theory can predict similar (but weaker) beam energy scaling but not the high power density, or the predominance of the 2omega-UH radiation peak over the omega-UH peak. Significant noise near the upper-hybrid and ion plasma frequencies is also measured, with normalized electrostatic wave energy density W(ES)/n(e)T(e) approximately 0.01.

POWER/SSE Web Access Data

Atmospheric Science Data Center

2018-06-25

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

Global Contexts of Higher Education

ERIC Educational Resources Information Center

Lovett, Clara M.

2013-01-01

In his 2008 bestseller, "The Post-American World," Fareed Zakaria argued that the most significant development of the early 21st century is not, as others have predicted, the inevitable decline of the United States as the world's super-power but rather "the rise of the rest." In subsequent works, Zakaria and many others,…

Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

NASA Astrophysics Data System (ADS)

Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

2009-07-01

Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

Theory of energy harvesting from heartbeat including the effects of pleural cavity and respiration.

PubMed

Zhang, Yangyang; Lu, Bingwei; Lü, Chaofeng; Feng, Xue

2017-11-01

Self-powered implantable devices with flexible energy harvesters are of significant interest due to their potential to solve the problem of limited battery life and surgical replacement. The flexible electronic devices made of piezoelectric materials have been employed to harvest energy from the motion of biological organs. Experimental measurements show that the output voltage of the device mounted on porcine left ventricle in chest closed environment decreases significantly compared to the case of chest open. A restricted-space deformation model is proposed to predict the impeding effect of pleural cavity, surrounding tissues, as well as respiration on the efficiency of energy harvesting from heartbeat using flexible piezoelectric devices. The analytical solution is verified by comparing theoretical predictions to experimental measurements. A simple scaling law is established to analyse the intrinsic correlations between the normalized output power and the combined system parameters, i.e. the normalized permitted space and normalized electrical load. The results may provide guidelines for optimization of in vivo energy harvesting from heartbeat or the motions of other biological organs using flexible piezoelectric energy harvesters.

Theory of energy harvesting from heartbeat including the effects of pleural cavity and respiration

NASA Astrophysics Data System (ADS)

Zhang, Yangyang; Lu, Bingwei; Lü, Chaofeng; Feng, Xue

2017-11-01

Self-powered implantable devices with flexible energy harvesters are of significant interest due to their potential to solve the problem of limited battery life and surgical replacement. The flexible electronic devices made of piezoelectric materials have been employed to harvest energy from the motion of biological organs. Experimental measurements show that the output voltage of the device mounted on porcine left ventricle in chest closed environment decreases significantly compared to the case of chest open. A restricted-space deformation model is proposed to predict the impeding effect of pleural cavity, surrounding tissues, as well as respiration on the efficiency of energy harvesting from heartbeat using flexible piezoelectric devices. The analytical solution is verified by comparing theoretical predictions to experimental measurements. A simple scaling law is established to analyse the intrinsic correlations between the normalized output power and the combined system parameters, i.e. the normalized permitted space and normalized electrical load. The results may provide guidelines for optimization of in vivo energy harvesting from heartbeat or the motions of other biological organs using flexible piezoelectric energy harvesters.

Lung Cancer Survival Prediction using Ensemble Data Mining on Seer Data

DOE PAGES

Agrawal, Ankit; Misra, Sanchit; Narayanan, Ramanathan; ...

2012-01-01

We analyze the lung cancer data available from the SEER program with the aim of developing accurate survival prediction models for lung cancer. Carefully designed preprocessing steps resulted in removal/modification/splitting of several attributes, and 2 of the 11 derived attributes were found to have significant predictive power. Several supervised classification methods were used on the preprocessed data along with various data mining optimizations and validations. In our experiments, ensemble voting of five decision tree based classifiers and meta-classifiers was found to result in the best prediction performance in terms of accuracy and area under the ROC curve. We have developedmore » an on-line lung cancer outcome calculator for estimating the risk of mortality after 6 months, 9 months, 1 year, 2 year and 5 years of diagnosis, for which a smaller non-redundant subset of 13 attributes was carefully selected using attribute selection techniques, while trying to retain the predictive power of the original set of attributes. Further, ensemble voting models were also created for predicting conditional survival outcome for lung cancer (estimating risk of mortality after 5 years of diagnosis, given that the patient has already survived for a period of time), and included in the calculator. The on-line lung cancer outcome calculator developed as a result of this study is available at http://info.eecs.northwestern.edu:8080/LungCancerOutcomeCalculator/.« less

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

PubMed

Lee, Bum Ju; Lee, Jae Chul; Nam, Jiho; Kim, Jong Yeol

2018-01-01

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns. Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures. In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression. Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

Trait psychopathy, emotional intelligence, and criminal thinking: Predicting illegal behavior among college students.

PubMed

Fix, Rebecca L; Fix, Spencer T

2015-01-01

Research focusing on individuals high on trait psychopathy remains limited. Higher trait psychopathy is associated with lower levels of emotional intelligence and increased participation in illegal behavior. Additionally, research has confirmed significantly higher levels of criminal thinking and lower levels of empathy in the incarcerated psychopathic population. However, the relationships between trait psychopathy and criminal thinking have not been researched in the community or college population. To test for such differences, questionnaires containing relevant measures were administered to 111 college students. Results indicated that higher levels of trait psychopathy were significantly related to less caring for others, intrapersonal understanding, and general mood, and greater interpersonal functioning and stress management. Furthermore, trait psychopathy was a strong predictor of violent, property, drug, and status offenses. Power-oriented criminal thinking was also predictive of violent behaviors, and entitlement predicted property offending. Results suggest emotional intelligence is important for predicting psychopathy, and trait psychopathy is a strong predictor of all types of illegal behaviors among the non-incarcerated population. Published by Elsevier Ltd.

Geographic potential of disease caused by Ebola and Marburg viruses in Africa.

PubMed

Peterson, A Townsend; Samy, Abdallah M

2016-10-01

Filoviruses represent a significant public health threat worldwide. West Africa recently experienced the largest-scale and most complex filovirus outbreak yet known, which underlines the need for a predictive understanding of the geographic distribution and potential for transmission to humans of these viruses. Here, we used ecological niche modeling techniques to understand the relationship between known filovirus occurrences and environmental characteristics. Our study derived a picture of the potential transmission geography of Ebola virus species and Marburg, paired with views of the spatial uncertainty associated with model-to-model variation in our predictions. We found that filovirus species have diverged ecologically, but only three species are sufficiently well known that models could be developed with significant predictive power. We quantified uncertainty in predictions, assessed potential for outbreaks outside of known transmission areas, and highlighted the Ethiopian Highlands and scattered areas across East Africa as additional potentially unrecognized transmission areas. Copyright © 2016 Elsevier B.V. All rights reserved.

Does dissociation of emotional and physiological reactivity predict blood pressure change at 3- and 10-year follow-up?

PubMed

Levin, Anna Y; Linden, Wolfgang

2008-02-01

One of the major theories of psychosomatic medicine is that pervasive dissociations between physiological reactivity and simultaneous emotion awareness may be an important marker for the long-term development of cardiac problems. Subjective autonomic discrepancy (SAD) scores are proposed as a method of capturing the dissociation between physiological and emotional reactivity and increasing the explanatory power of predictive models of cardiac health outcomes. It was found that SAD scores for blood pressure indices show trait-like stability over a period of 3 years. Although linear 3-year prediction of systolic blood pressure came close to traditional definitions of significance, neither a linear nor a quadratic model was found to show significant prospective validity in predicting ambulatory blood pressure change over a 10-year period. Dissociation between physiological arousal and emotional awareness does not appear to be an important variable in the identification of individuals at risk for later cardiovascular health problems.

Predicting life satisfaction of the Angolan elderly: a structural model.

PubMed

Gutiérrez, M; Tomás, J M; Galiana, L; Sancho, P; Cebrià, M A

2013-01-01

Satisfaction with life is of particular interest in the study of old age well-being because it has arisen as an important component of old age. A considerable amount of research has been done to explain life satisfaction in the elderly, and there is growing empirical evidence on best predictors of life satisfaction. This research evaluates the predictive power of some aging process variables, on Angolan elderly people's life satisfaction, while including perceived health into the model. Data for this research come from a cross-sectional survey of elderly people living in the capital of Angola, Luanda. A total of 1003 Angolan elderly were surveyed on socio-demographic information, perceived health, active engagement, generativity, and life satisfaction. A Multiple Indicators Multiple Causes model was built to test variables' predictive power on life satisfaction. The estimated theoretical model fitted the data well. The main predictors were those related to active engagement with others. Perceived health also had a significant and positive effect on life satisfaction. Several processes together may predict life satisfaction in the elderly population of Angola, and the variance accounted for it is large enough to be considered relevant. The key factor associated to life satisfaction seems to be active engagement with others.

The Study of Rain Specific Attenuation for the Prediction of Satellite Propagation in Malaysia

NASA Astrophysics Data System (ADS)

Mandeep, J. S.; Ng, Y. Y.; Abdullah, H.; Abdullah, M.

2010-06-01

Specific attenuation is the fundamental quantity in the calculation of rain attenuation for terrestrial path and slant paths representing as rain attenuation per unit distance (dB/km). Specific attenuation is an important element in developing the predicted rain attenuation model. This paper deals with the empirical determination of the power law coefficients which allow calculating the specific attenuation in dB/km from the knowledge of the rain rate in mm/h. The main purpose of the paper is to obtain the coefficients of k and α of power law relationship between specific attenuation. Three years (from 1st January 2006 until 31st December 2008) rain gauge and beacon data taken from USM, Nibong Tebal have been used to do the empirical procedure analysis of rain specific attenuation. The data presented are semi-empirical in nature. A year-to-year variation of the coefficients has been indicated and the empirical measured data was compared with ITU-R provided regression coefficient. The result indicated that the USM empirical measured data was significantly vary from ITU-R predicted value. Hence, ITU-R recommendation for regression coefficients of rain specific attenuation is not suitable for predicting rain attenuation at Malaysia.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, Martin; Giebel, Gregor; Skov Nielsen, Torben; Hahmann, Andrea; Sørensen, Poul; Madsen, Henrik

2013-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the title "Integrated Wind Power Planning Tool". The goal is to integrate a mesoscale numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. Using the state-of-the-art mesoscale NWP model Weather Research & Forecasting model (WRF) the forecast error is sought quantified in dependence of the time scale involved. This task constitutes a preparative study for later implementation of features accounting for NWP forecast errors in the DTU Wind Energy maintained Corwind code - a long term wind power planning tool. Within the framework of PSO 10464 research related to operational short term wind power prediction will be carried out, including a comparison of forecast quality at different mesoscale NWP model resolutions and development of a statistical wind power prediction tool taking input from WRF. The short term prediction part of the project is carried out in collaboration with ENFOR A/S; a Danish company that specialises in forecasting and optimisation for the energy sector. The integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated short term prediction tool constitutes scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator. The need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2025 from the current 20%.

Method for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020, and for estimating water use for livestock and selected sectors of the food-processing industry in New Jersey in 1987

USGS Publications Warehouse

Clawges, R.M.; Titus, E.O.

1993-01-01

A method was developed to predict water demand for crop uses in New Jersey. A separate method was developed to estimate water use for livestock and selected sectors of the food-processing industry in 1987. Predictions of water demand for field- grown crops in New Jersey were made for 1990, 2000, 2010, and 2020 under three climatological scenarios: (1) wet year, (2) average year, and (3) drought year. These estimates ranged from 4.10 times 10 to the 9th power to 16.82 times 10 to the 9th power gal (gallons). Irrigation amounts calculated for the three climatological scenarios by using a daily water-balance model were multiplied by predicted numbers of irrigated acreage. Irrigated acreage was predicted from historical crop-irrigation data and from predictions of harvested acreage produced by using a statistical model relating population to harvested acreage. Predictions of water demand for cranberries and container-grown nursery crops also were made for 1990, 2000, 2010, and 2020. Predictions of water demand under the three climatological scenarios were made for container- grown nursery crops, but not for cranberries, because water demand for cranberries varies little in response to climatological factors. Water demand for cranberries was predicted to remain constant at 4.43 times 10 to the 9th power gal through the year 2020. Predictions of water demand for container-grown nursery crops ranged from 1.89 times 10 to the 9th power to 3.63 times 10 to the 9th power gal. Water-use for livestock in 1987 was estimated to be 0.78 times 10 to the 9th power gal, and water use for selected sectors of the food-processing industry was estimated to be 3.75 times 10 to the 9th power gal.

Velocity- and power-load relationships of the bench pull vs. bench press exercises.

PubMed

Sánchez-Medina, L; González-Badillo, J J; Pérez, C E; Pallarés, J G

2014-03-01

This study compared the velocity- and power-load relationships of the antagonistic upper-body exercises of prone bench pull (PBP) and bench press (BP). 75 resistance-trained athletes performed a progressive loading test in each exercise up to the one-repetition maximum (1RM) in random order. Velocity and power output across the 30-100% 1RM were significantly higher for PBP, whereas 1RM strength was greater for BP. A very close relationship was observed between relative load and mean propulsive velocity for both BP (R2=0.97) and PBP (R2=0.94) which enables us to estimate %1RM from velocity using the obtained prediction equations. Important differences in the load that maximizes power output (Pmax) and the power profiles of both exercises were found according to the outcome variable used: mean (MP), peak (PP) or mean propulsive power (MPP). When MP was considered, the Pmax load was higher (56% BP, 70% PBP) than when PP (37% BP, 41% PBP) or MPP (37% BP, 46% PBP) were used. For each variable there was a broad range of loads at which power output was not significantly different. The differing velocity- and power-load relationships between PBP and BP seem attributable to the distinct muscle architecture and moment arm levers involved in these exercises. © Georg Thieme Verlag KG Stuttgart · New York.

Overview of NASA Lewis Research Center free-piston Stirling engine technology activities applicable to space power systems

NASA Technical Reports Server (NTRS)

Slaby, J. G.

1986-01-01

Free piston Stirling technology is applicable for both solar and nuclear powered systems. As such, the Lewis Research Center serves as the project office to manage the newly initiated SP-100 Advanced Technology Program. This five year program provides the technology push for providing significant component and subsystem options for increased efficiency, reliability and survivability, and power output growth at reduced specific mass. One of the major elements of the program is the development of advanced power conversion concepts of which the Stirling cycle is a viable candidate. Under this program the research findings of the 25 kWe opposed piston Space Power Demonstrator Engine (SPDE) are presented. Included in the SPDE discussions are initial differences between predicted and experimental power outputs and power output influenced by variations in regenerators. Projections are made for future space power requirements over the next few decades. And a cursory comparison is presented showing the mass benefits that a Stirling system has over a Brayton system for the same peak temperature and output power.

Analysis of Application Power and Schedule Composition in a High Performance Computing Environment

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

Elmore, Ryan; Gruchalla, Kenny; Phillips, Caleb

As the capacity of high performance computing (HPC) systems continues to grow, small changes in energy management have the potential to produce significant energy savings. In this paper, we employ an extensive informatics system for aggregating and analyzing real-time performance and power use data to evaluate energy footprints of jobs running in an HPC data center. We look at the effects of algorithmic choices for a given job on the resulting energy footprints, and analyze application-specific power consumption, and summarize average power use in the aggregate. All of these views reveal meaningful power variance between classes of applications as wellmore » as chosen methods for a given job. Using these data, we discuss energy-aware cost-saving strategies based on reordering the HPC job schedule. Using historical job and power data, we present a hypothetical job schedule reordering that: (1) reduces the facility's peak power draw and (2) manages power in conjunction with a large-scale photovoltaic array. Lastly, we leverage this data to understand the practical limits on predicting key power use metrics at the time of submission.« less

Multi-center prediction of hemorrhagic transformation in acute ischemic stroke using permeability imaging features.

PubMed

Scalzo, Fabien; Alger, Jeffry R; Hu, Xiao; Saver, Jeffrey L; Dani, Krishna A; Muir, Keith W; Demchuk, Andrew M; Coutts, Shelagh B; Luby, Marie; Warach, Steven; Liebeskind, David S

2013-07-01

Permeability images derived from magnetic resonance (MR) perfusion images are sensitive to blood-brain barrier derangement of the brain tissue and have been shown to correlate with subsequent development of hemorrhagic transformation (HT) in acute ischemic stroke. This paper presents a multi-center retrospective study that evaluates the predictive power in terms of HT of six permeability MRI measures including contrast slope (CS), final contrast (FC), maximum peak bolus concentration (MPB), peak bolus area (PB), relative recirculation (rR), and percentage recovery (%R). Dynamic T2*-weighted perfusion MR images were collected from 263 acute ischemic stroke patients from four medical centers. An essential aspect of this study is to exploit a classifier-based framework to automatically identify predictive patterns in the overall intensity distribution of the permeability maps. The model is based on normalized intensity histograms that are used as input features to the predictive model. Linear and nonlinear predictive models are evaluated using a cross-validation to measure generalization power on new patients and a comparative analysis is provided for the different types of parameters. Results demonstrate that perfusion imaging in acute ischemic stroke can predict HT with an average accuracy of more than 85% using a predictive model based on a nonlinear regression model. Results also indicate that the permeability feature based on the percentage of recovery performs significantly better than the other features. This novel model may be used to refine treatment decisions in acute stroke. Copyright © 2013 Elsevier Inc. All rights reserved.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

PubMed

Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

2018-05-02

An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (p<0.0001). The wISS showed higher specificity, positive predictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

Neonatal Sleep-Wake Analyses Predict 18-month Neurodevelopmental Outcomes.

PubMed

Shellhaas, Renée A; Burns, Joseph W; Hassan, Fauziya; Carlson, Martha D; Barks, John D E; Chervin, Ronald D

2017-11-01

The neurological examination of critically ill neonates is largely limited to reflexive behavior. The exam often ignores sleep-wake physiology that may reflect brain integrity and influence long-term outcomes. We assessed whether polysomnography and concurrent cerebral near-infrared spectroscopy (NIRS) might improve prediction of 18-month neurodevelopmental outcomes. Term newborns with suspected seizures underwent standardized neurologic examinations to generate Thompson scores and had 12-hour bedside polysomnography with concurrent cerebral NIRS. For each infant, the distribution of sleep-wake stages and electroencephalogram delta power were computed. NIRS-derived fractional tissue oxygen extraction (FTOE) was calculated across sleep-wake stages. At age 18-22 months, surviving participants were evaluated with Bayley Scales of Infant Development (Bayley-III), 3rd edition. Twenty-nine participants completed Bayley-III. Increased newborn time in quiet sleep predicted worse 18-month cognitive and motor scores (robust regression models, adjusted r2 = 0.22, p = .007, and 0.27, .004, respectively). Decreased 0.5-2 Hz electroencephalograph (EEG) power during quiet sleep predicted worse 18-month language and motor scores (adjusted r2 = 0.25, p = .0005, and 0.33, .001, respectively). Predictive values remained significant after adjustment for neonatal Thompson scores or exposure to phenobarbital. Similarly, an attenuated difference in FTOE, between neonatal wakefulness and quiet sleep, predicted worse 18-month cognitive, language, and motor scores in adjusted analyses (each p < .05). These prospective, longitudinal data suggest that inefficient neonatal sleep-as quantified by increased time in quiet sleep, lower electroencephalogram delta power during that stage, and muted differences in FTOE between quiet sleep and wakefulness-may improve prediction of adverse long-term outcomes for newborns with neurological dysfunction. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Influence of performance level on anaerobic power and body composition in elite male judoists.

PubMed

Kim, Jongkyu; Cho, Hyun-Chul; Jung, Han-Sang; Yoon, Jong-Dae

2011-05-01

This study examined the relationship between 30-second anaerobic power and body composition by performance level in elite Judoists. During a 3-month period, 10 male Korean Judo national team athletes (NT), 26 male university varsity team athletes (VT), and 28 male junior varsity team athletes (JT) were assessed for 30-second anaerobic power and body composition at the Youngin University. Anaerobic power was measured using a 30-second Wingate test. Body composition was assessed via bioelectric impedance analysis in standardized conditions using BioSpace (Korean)-specific prediction formulas. All testing occurred at the beginning of the winter nonseason period but excluded a brief weight-loss period before the competition phase. Anaerobic power measures were significantly greater (p < 0.05) in NT and VT than in JT. Fat-free mass (FFM), muscle mass (MM), and total body water in JT were also greater than in VT and JT (p < 0.05). Muscle mass in VT was significantly lower than in NT (p < 0.05). Fat-free mass in NT was strongly correlated to mean and peak anaerobic power (r = 0.77, p = 0.009; r = 0.87, p < 0.001, respectively). Varsity team athletes also indicated a moderate association between FFM and peak and mean anaerobic power (r = 0.63, p < 0.001; r = 0.48, p = 0.013, respectively). However, relationship between FFM and anaerobic power was not statistically significantly correlated in JT (r = 0.14, p = 0.470; r = 0.23, p = 0.232, separately). In conclusion, our data indicated that anaerobic power is closely correlated with increase in FFM and MM and was different dependent among performance levels. Further research in the field is warranted to elucidate the Judo-specific relationship between FFM and performance.

Predicting therapy success for treatment as usual and blended treatment in the domain of depression.

PubMed

van Breda, Ward; Bremer, Vincent; Becker, Dennis; Hoogendoorn, Mark; Funk, Burkhardt; Ruwaard, Jeroen; Riper, Heleen

2018-06-01

In this paper, we explore the potential of predicting therapy success for patients in mental health care. Such predictions can eventually improve the process of matching effective therapy types to individuals. In the EU project E-COMPARED, a variety of information is gathered about patients suffering from depression. We use this data, where 276 patients received treatment as usual and 227 received blended treatment, to investigate to what extent we are able to predict therapy success. We utilize different encoding strategies for preprocessing, varying feature selection techniques, and different statistical procedures for this purpose. Significant predictive power is found with average AUC values up to 0.7628 for treatment as usual and 0.7765 for blended treatment. Adding daily assessment data for blended treatment does currently not add predictive accuracy. Cost effectiveness analysis is needed to determine the added potential for real-world applications.

Addition of 24-Hour Heart Rate Variability Parameters to the Cardiovascular Health Study Stroke Risk Score and Prediction of Incident Stroke: The Cardiovascular Health Study.

PubMed

Bodapati, Rohan K; Kizer, Jorge R; Kop, Willem J; Kamel, Hooman; Stein, Phyllis K

2017-07-21

Heart rate variability (HRV) characterizes cardiac autonomic functioning. The association of HRV with stroke is uncertain. We examined whether 24-hour HRV added predictive value to the Cardiovascular Health Study clinical stroke risk score (CHS-SCORE), previously developed at the baseline examination. N=884 stroke-free CHS participants (age 75.3±4.6), with 24-hour Holters adequate for HRV analysis at the 1994-1995 examination, had 68 strokes over ≤8 year follow-up (median 7.3 [interquartile range 7.1-7.6] years). The value of adding HRV to the CHS-SCORE was assessed with stepwise Cox regression analysis. The CHS-SCORE predicted incident stroke (HR=1.06 per unit increment, P =0.005). Two HRV parameters, decreased coefficient of variance of NN intervals (CV%, P =0.031) and decreased power law slope (SLOPE, P =0.033) also entered the model, but these did not significantly improve the c-statistic ( P =0.47). In a secondary analysis, dichotomization of CV% (LOWCV% ≤12.8%) was found to maximally stratify higher-risk participants after adjustment for CHS-SCORE. Similarly, dichotomizing SLOPE (LOWSLOPE <-1.4) maximally stratified higher-risk participants. When these HRV categories were combined (eg, HIGHCV% with HIGHSLOPE), the c-statistic for the model with the CHS-SCORE and combined HRV categories was 0.68, significantly higher than 0.61 for the CHS-SCORE alone ( P =0.02). In this sample of older adults, 2 HRV parameters, CV% and power law slope, emerged as significantly associated with incident stroke when added to a validated clinical risk score. After each parameter was dichotomized based on its optimal cut point in this sample, their composite significantly improved prediction of incident stroke during ≤8-year follow-up. These findings will require validation in separate, larger cohorts. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Jet Power vs. Black Hole Mass in Blazars: Exploring the Relationship in the Context of the B-Z Mechanism

NASA Astrophysics Data System (ADS)

Fernandes, Sunil; Schlegel, E.

2012-01-01

Recently, a tentative negative correlation between jet power and BH mass in a sample of GeV-TeV BL Lac objects(Zhang et al 2011). It was suggested that spin energy extraction could play a significant role in producing the jets and the jets are not purely accretion driven. Broderick et al (2011) recently explored the relationship between jet power and radio core luminosity building on Blanford et al (1979) theoretical work. Using this work we have studied the relationship between radio core luminosity (as a stand in for jet power) and black hole mass and have found a possible positive correlation in a sample of nearby BL Lac objects. The present poster attempts to explore this relationship in the context of the Blanford-Znajek mechanism which predicts jet power increases with black hole mass, spin rate, and accretion rate.

An Advanced Framework for Improving Situational Awareness in Electric Power Grid Operation

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

Chen, Yousu; Huang, Zhenyu; Zhou, Ning

With the deployment of new smart grid technologies and the penetration of renewable energy in power systems, significant uncertainty and variability is being introduced into power grid operation. Traditionally, the Energy Management System (EMS) operates the power grid in a deterministic mode, and thus will not be sufficient for the future control center in a stochastic environment with faster dynamics. One of the main challenges is to improve situational awareness. This paper reviews the current status of power grid operation and presents a vision of improving wide-area situational awareness for a future control center. An advanced framework, consisting of parallelmore » state estimation, state prediction, parallel contingency selection, parallel contingency analysis, and advanced visual analytics, is proposed to provide capabilities needed for better decision support by utilizing high performance computing (HPC) techniques and advanced visual analytic techniques. Research results are presented to support the proposed vision and framework.« less

Correlations between Preoperative Angle Parameters and Postoperative Unpredicted Refractive Errors after Cataract Surgery in Open Angle Glaucoma (AOD 500).

PubMed

Lee, Wonseok; Bae, Hyoung Won; Lee, Si Hyung; Kim, Chan Yun; Seong, Gong Je

2017-03-01

To assess the accuracy of intraocular lens (IOL) power prediction for cataract surgery with open angle glaucoma (OAG) and to identify preoperative angle parameters correlated with postoperative unpredicted refractive errors. This study comprised 45 eyes from 45 OAG subjects and 63 eyes from 63 non-glaucomatous cataract subjects (controls). We investigated differences in preoperative predicted refractive errors and postoperative refractive errors for each group. Preoperative predicted refractive errors were obtained by biometry (IOL-master) and compared to postoperative refractive errors measured by auto-refractometer 2 months postoperatively. Anterior angle parameters were determined using swept source optical coherence tomography. We investigated correlations between preoperative angle parameters [angle open distance (AOD); trabecular iris surface area (TISA); angle recess area (ARA); trabecular iris angle (TIA)] and postoperative unpredicted refractive errors. In patients with OAG, significant differences were noted between preoperative predicted and postoperative real refractive errors, with more myopia than predicted. No significant differences were recorded in controls. Angle parameters (AOD, ARA, TISA, and TIA) at the superior and inferior quadrant were significantly correlated with differences between predicted and postoperative refractive errors in OAG patients (-0.321 to -0.408, p<0.05). Superior quadrant AOD 500 was significantly correlated with postoperative refractive differences in multivariate linear regression analysis (β=-2.925, R²=0.404). Clinically unpredicted refractive errors after cataract surgery were more common in OAG than in controls. Certain preoperative angle parameters, especially AOD 500 at the superior quadrant, were significantly correlated with these unpredicted errors.

Correlations between Preoperative Angle Parameters and Postoperative Unpredicted Refractive Errors after Cataract Surgery in Open Angle Glaucoma (AOD 500)

PubMed Central

Lee, Wonseok; Bae, Hyoung Won; Lee, Si Hyung; Kim, Chan Yun

2017-01-01

Purpose To assess the accuracy of intraocular lens (IOL) power prediction for cataract surgery with open angle glaucoma (OAG) and to identify preoperative angle parameters correlated with postoperative unpredicted refractive errors. Materials and Methods This study comprised 45 eyes from 45 OAG subjects and 63 eyes from 63 non-glaucomatous cataract subjects (controls). We investigated differences in preoperative predicted refractive errors and postoperative refractive errors for each group. Preoperative predicted refractive errors were obtained by biometry (IOL-master) and compared to postoperative refractive errors measured by auto-refractometer 2 months postoperatively. Anterior angle parameters were determined using swept source optical coherence tomography. We investigated correlations between preoperative angle parameters [angle open distance (AOD); trabecular iris surface area (TISA); angle recess area (ARA); trabecular iris angle (TIA)] and postoperative unpredicted refractive errors. Results In patients with OAG, significant differences were noted between preoperative predicted and postoperative real refractive errors, with more myopia than predicted. No significant differences were recorded in controls. Angle parameters (AOD, ARA, TISA, and TIA) at the superior and inferior quadrant were significantly correlated with differences between predicted and postoperative refractive errors in OAG patients (-0.321 to -0.408, p<0.05). Superior quadrant AOD 500 was significantly correlated with postoperative refractive differences in multivariate linear regression analysis (β=-2.925, R2=0.404). Conclusion Clinically unpredicted refractive errors after cataract surgery were more common in OAG than in controls. Certain preoperative angle parameters, especially AOD 500 at the superior quadrant, were significantly correlated with these unpredicted errors. PMID:28120576

Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

NASA Astrophysics Data System (ADS)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

Periodicities in solar wind-magnetosphere coupling functions and geomagnetic activity during the past solar cycles

NASA Astrophysics Data System (ADS)

Andriyas, T.; Andriyas, S.

2017-09-01

In this paper, we study the solar-terrestrial relation through the wavelet analysis. We report periodicities common between multiple solar wind coupling functions and geomagnetic indices during five solar cycles and also and the strength of this correspondence. The Dst (found to be most predictable in Newell et al., J. Geophys. Res. Space Phys. 112(A1):A01206, 2007) and AL (least predictable in Newell et al., J. Geophys. Res. Space Phys. 112(A1):A01206, 2007) indices are used for this purpose. During the years 1966-2016 (which includes five solar cycles 20, 21, 22, 23, and 24), prominent periodicities ≤720 days with power above 95% confidence level were found to occur around 27, 182, 385, and 648 days in the Dst index while those in the AL index were found in bands around 27, 187, and 472 days. Ten solar wind coupling functions were then used to find periodicities common with the indices. All the coupling functions had significant power in bands centered around 27, 280, and 648 days while powers in fluctuations around 182, 385, and 472 days were only found in some coupling functions. All the drivers and their variants had power above the significant level in the 280-288 days band, which was absent in the Dst and AL indices. The normalized scale averaged spectral power around the common periods in the coupling functions and the indices indicated that the coupling functions most correlated with the Dst index were the Newell (27 and 385 days), Wygant (182 days), and Scurry-Russell and Boynton (648 days) functions. An absence of common power between the coupling functions and the Dst index around the annual periodicity was noted during the even solar cycles. A similar analysis for the AL index indicated that Newell (27 days), Rectified (187 days), and Boynton (472 days) were the most correlated functions. It was also found that the correlation numbers were relatively weaker for the AL index, specially for the 187 day periodicity. It is concluded that as the two indices respond to solar wind forcing with varying levels of strength at various prominent scales and the coupling function used, the response might be dependent on the scale (days or months or years) of interest at which the solar wind driving is to be predicted.

Predictive importance of anthropometric and training data in recreational male Ironman triathletes and marathon runners: comment on the study by Gianoli, et al. (2012).

PubMed

Burtscher, Martin; Gatterer, Hannes

2013-04-01

Anthropometric and training data have been reported as statistically significant predictors of race performance in endurance events. However, it is well established that physiological characteristics, i.e., maximal oxygen uptake (VO2max), the use of a high percentage of VO2max during sustained exercise, and work efficiency are predominant predictors of performance in those events. Thus, the essential issue is whether the anthropometric and training data give additional predictive power beyond these other measures.

The honeymoon effect in job performance - Temporal increases in the predictive power of achievement motivation

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.; Sawin, Linda L.; Carsrud, Alan L.

1986-01-01

Correlations between a job performance criterion and personality measures reflecting achievement motivation and an interpersonal orientation were examined at three points in time after completion of job training for a sample of airline reservations agents. Although correlations between the personality predictors and performance were small and nonsignificant for the 3-month period after beginning the job, by the end of six and eight months a number of significant relationships had emerged. Implications for the utility of personality measures in selection and performance prediction are discussed.

Low Data Drug Discovery with One-Shot Learning.

PubMed

Altae-Tran, Han; Ramsundar, Bharath; Pappu, Aneesh S; Pande, Vijay

2017-04-26

Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. 2015, 55, 263-274). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016).

Integrated modelling of H-mode pedestal and confinement in JET-ILW

NASA Astrophysics Data System (ADS)

Saarelma, S.; Challis, C. D.; Garzotti, L.; Frassinetti, L.; Maggi, C. F.; Romanelli, M.; Stokes, C.; Contributors, JET

2018-01-01

A pedestal prediction model Europed is built on the existing EPED1 model by coupling it with core transport simulation using a Bohm-gyroBohm transport model to self-consistently predict JET-ILW power scan for hybrid plasmas that display weaker power degradation than the IPB98(y, 2) scaling of the energy confinement time. The weak power degradation is reproduced in the coupled core-pedestal simulation. The coupled core-pedestal model is further tested for a 3.0 MA plasma with the highest stored energy achieved in JET-ILW so far, giving a prediction of the stored plasma energy within the error margins of the measured experimental value. A pedestal density prediction model based on the neutral penetration is tested on a JET-ILW database giving a prediction with an average error of 17% from the experimental data when a parameter taking into account the fuelling rate is added into the model. However the model fails to reproduce the power dependence of the pedestal density implying missing transport physics in the model. The future JET-ILW deuterium campaign with increased heating power is predicted to reach plasma energy of 11 MJ, which would correspond to 11-13 MW of fusion power in equivalent deuterium-tritium plasma but with isotope effects on pedestal stability and core transport ignored.

Maximum predictive power and the superposition principle

NASA Technical Reports Server (NTRS)

Summhammer, Johann

1994-01-01

In quantum physics the direct observables are probabilities of events. We ask how observed probabilities must be combined to achieve what we call maximum predictive power. According to this concept the accuracy of a prediction must only depend on the number of runs whose data serve as input for the prediction. We transform each probability to an associated variable whose uncertainty interval depends only on the amount of data and strictly decreases with it. We find that for a probability which is a function of two other probabilities maximum predictive power is achieved when linearly summing their associated variables and transforming back to a probability. This recovers the quantum mechanical superposition principle.

Multiple Off-Ice Performance Variables Predict On-Ice Skating Performance in Male and Female Division III Ice Hockey Players

PubMed Central

Janot, Jeffrey M.; Beltz, Nicholas M.; Dalleck, Lance D.

2015-01-01

The purpose of this study was to determine if off-ice performance variables could predict on-ice skating performance in Division III collegiate hockey players. Both men (n = 15) and women (n = 11) hockey players (age = 20.5 ± 1.4 years) participated in the study. The skating tests were agility cornering S-turn, 6.10 m acceleration, 44.80 m speed, modified repeat skate, and 15.20 m full speed. Off-ice variables assessed were years of playing experience, height, weight and percent body fat and off-ice performance variables included vertical jump (VJ), 40-yd dash (36.58m), 1-RM squat, pro-agility, Wingate peak power and peak power percentage drop (% drop), and 1.5 mile (2.4km) run. Results indicated that 40-yd dash (36.58m), VJ, 1.5 mile (2.4km) run, and % drop were significant predictors of skating performance for repeat skate (slowest, fastest, and average time) and 44.80 m speed time, respectively. Four predictive equations were derived from multiple regression analyses: 1) slowest repeat skate time = 2.362 + (1.68 x 40-yd dash time) + (0.005 x 1.5 mile run), 2) fastest repeat skate time = 9.762 - (0.089 x VJ) - (0.998 x 40-yd dash time), 3) average repeat skate time = 7.770 + (1.041 x 40-yd dash time) - (0.63 x VJ) + (0.003 x 1.5 mile time), and 4) 47.85 m speed test = 7.707 - (0.050 x VJ) - (0.01 x % drop). It was concluded that selected off-ice tests could be used to predict on-ice performance regarding speed and recovery ability in Division III male and female hockey players. Key points The 40-yd dash (36.58m) and vertical jump tests are significant predictors of on-ice skating performance specific to speed. In addition to 40-yd dash and vertical jump, the 1.5 mile (2.4km) run for time and percent power drop from the Wingate anaerobic power test were also significant predictors of skating performance that incorporates the aspect of recovery from skating activity. Due to the specificity of selected off-ice variables as predictors of on-ice performance, coaches can elect to assess player performance off-ice and focus on other uses of valuable ice time for their individual teams. PMID:26336338

The prospects for hybrid electric vehicles, 2005-2020 : results of a Delphi Study.

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

Ng, H. K.; Santini, D. J.; Vyas, A. D.

1999-07-22

The introduction of Toyota's hybrid electric vehicle (HEV), the Prius, in Japan has generated considerable interest in HEV technology among US automotive experts. In a follow-up survey to Argonne National Laboratory's two-stage Delphi Study on electric and hybrid electric vehicles (EVs and HEVs) during 1994-1996, Argonne researchers gathered the latest opinions of automotive experts on the future ''top-selling'' HEV attributes and costs. The experts predicted that HEVs would have a spark-ignition gasoline engine as a power plant in 2005 and a fuel cell power plant by 2020. The projected 2020 fuel shares were about equal for gasoline and hydrogen, withmore » methanol a distant third. In 2020, HEVs are predicted to have series-drive, moderate battery-alone range and cost significantly more than conventional vehicles (CVs). The HEV is projected to cost 66% more than a $20,000 CV initially and 33% more by 2020. Survey respondents view batteries as the component that contributes the most to the HEV cost increment. The mean projection for battery-alone range is 49 km in 2005, 70 km in 2010, and 92 km in 2020. Responding to a question relating to their personal vision of the most desirable HEV and its likely characteristics when introduced in the US market in the next decade, the experts predicted their ''vision'' HEV to have attributes very similar to those of the ''top-selling'' HEV. However, the ''vision'' HEV would cost significantly less. The experts projected attributes of three leading batteries for HEVs and projected acceleration times on battery power alone. The resulting battery packs are evaluated, and their initial and replacement costs are analyzed. These and several other opinions are summarized.« less

Allometric scaling in-vitro

NASA Astrophysics Data System (ADS)

Ahluwalia, Arti

2017-02-01

About two decades ago, West and coworkers established a model which predicts that metabolic rate follows a three quarter power relationship with the mass of an organism, based on the premise that tissues are supplied nutrients through a fractal distribution network. Quarter power scaling is widely considered a universal law of biology and it is generally accepted that were in-vitro cultures to obey allometric metabolic scaling, they would have more predictive potential and could, for instance, provide a viable substitute for animals in research. This paper outlines a theoretical and computational framework for establishing quarter power scaling in three-dimensional spherical constructs in-vitro, starting where fractal distribution ends. Allometric scaling in non-vascular spherical tissue constructs was assessed using models of Michaelis Menten oxygen consumption and diffusion. The models demonstrate that physiological scaling is maintained when about 5 to 60% of the construct is exposed to oxygen concentrations less than the Michaelis Menten constant, with a significant concentration gradient in the sphere. The results have important implications for the design of downscaled in-vitro systems with physiological relevance.

Periictal activity in cooled asphyxiated neonates with seizures.

PubMed

Major, Philippe; Lortie, Anne; Dehaes, Mathieu; Lodygensky, Gregory Anton; Gallagher, Anne; Carmant, Lionel; Birca, Ala

2017-04-01

Seizures are common in critically ill neonates. Both seizures and antiepileptic treatments may lead to short term complications and worsen the outcomes. Predicting the risks of seizure reoccurrence could enable individual treatment regimens and better outcomes. We aimed to identify EEG signatures of seizure reoccurrence by investigating periictal electrographic features and spectral power characteristics in hypothermic neonates with hypoxic-ischemic encephalopathy (HIE) with or without reoccurrence of seizures on rewarming. We recruited five consecutive HIE neonates, submitted to continuous EEG monitoring, with high seizure burden (>20% per hour) while undergoing therapeutic hypothermia. Two of them had reoccurrence of seizures on rewarming. We performed quantitative analysis of fifteen artifact-free consecutive seizures to appreciate spectral power changes between the interictal, preictal and ictal periods, separately for each patient. Visual analysis allowed description of electrographic features associated with ictal events. Every patient demonstrated a significant increase in overall spectral power from the interictal to preictal and ictal periods (p<0.01). Alpha power increase was more pronounced in the two patients with reoccurrence of seizures on rewarming and significant when comparing both interictal-to-preictal and interictal-to-ictal periods. This alpha activity increase could be also appreciated using visual analysis and distinguished neonates with and without seizure reoccurrence. This distinct alpha activity preceding ictal onset could represent a biomarker of propensity for seizure reoccurrence in neonates. Future studies should be performed to confirm whether quantitative periictal characteristics and electrographic features allow predicting the risks of seizure reoccurrence in HIE neonates and other critically ill patients. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

MiRNA Expression Analysis of Pretreatment Biopsies Predicts the Pathological Response of Esophageal Squamous Cell Carcinomas to Neoadjuvant Chemoradiotherapy.

PubMed

Wen, Jing; Luo, Kongjia; Liu, Hui; Liu, Shiliang; Lin, Guangrong; Hu, Yi; Zhang, Xu; Wang, Geng; Chen, Yuping; Chen, Zhijian; Li, Yi; Lin, Ting; Xie, Xiuying; Liu, Mengzhong; Wang, Huiyun; Yang, Hong; Fu, Jianhua

2016-05-01

To identify miRNA markers useful for esophageal squamous cell carcinoma (ESCC) neoadjuvant chemoradiotherapy (neo-CRT) response prediction. Neo-CRT followed by surgery improves ESCC patients' survival compared with surgery alone. However, CRT outcomes are heterogeneous, and no current methods can predict CRT responses. Differentially expressed miRNAs between ESCC pathological responders and nonresponders after neo-CRT were identified by miRNA profiling and verified by real-time quantitative polymerase chain reaction (qPCR) of 27 ESCCs in the training set. Several class prediction algorithms were used to build the response-classifying models with the qPCR data. Predictive powers of the models were further assessed with a second set of 79 ESCCs. Ten miRNAs with greater than a 1.5-fold change between pathological responders and nonresponders were identified and verified, respectively. A support vector machine (SVM) prediction model, composed of 4 miRNAs (miR-145-5p, miR-152, miR-193b-3p, and miR-376a-3p), were developed. It provided overall accuracies of 100% and 87.3% for discriminating pathological responders and nonresponders in the training and external validation sets, respectively. In multivariate analysis, the subgroup determined by the SVM model was the only independent factor significantly associated with neo-CRT response in the external validation sets. Combined qPCR of the 4 miRNAs provides the possibility of ESCC neo-CRT response prediction, which may facilitate individualized ESCC treatment. Further prospective validation in larger independent cohorts is necessary to fully assess its predictive power.

ACTN3 genotype does not influence muscle power.

PubMed

Hanson, E D; Ludlow, A T; Sheaff, A K; Park, J; Roth, S M

2010-11-01

The R577X polymorphism within the ACTN3 gene has been associated with elite athletic performance, strength, power, fat free mass, and adaptations to strength training, though inconsistencies exist in the literature. The specific muscle power phenotypes most influenced by the polymorphism are uncertain. The purpose of this study was to examine the association between ACTN3 R577X genotype and muscle power phenotypes. Recreationally active young men and women (N=57) were selected to complete 2 muscle performance assessments, an isokinetic fatigue protocol at testing speeds of 180°  s (-1) and 250°  s (-1) and a 30 s Wingate test. Isokinetic torque and Wingate power significantly decreased over the duration of each test, but no differences in the rate of decline were observed among ACTN3 genotype groups. Similarly, no significant genotype differences were observed for isokinetic peak torque, Wingate absolute or relative peak power, or fatigue index. These results indicate that in recreationally active individuals the ACTN3 R577X polymorphism is not associated with muscle performance phenotypes, supporting recent findings that R577X may only be important for predicting performance in elite athletes. Our data also indicate that using this polymorphism for genetic screening in the lay population is scientifically questionable.

Cultural variation in seasonal depression: cross-national differences in winter versus summer patterns of seasonal affective disorder.

PubMed

Kasof, Joseph

2009-05-01

Research suggests that two dimensions of national culture, individualism-collectivism and power distance, predict affective responses to the seasonally varying levels of ambient sunlight that may underlie regular cycles of mood and behavior in Seasonal Affective Disorder (SAD). Specifically, negative affect is predicted by the diminished sunlight of fall-winter in countries higher in individualism and lower in power distance, and by the increased sunlight of spring-summer in countries lower in individualism and higher in power distance. This study tests whether individualism correlates positively, and power distance negatively, with the frequency of winter-SAD relative to that of summer-SAD. A search for studies reporting frequencies of both winter-SAD and summer-SAD identified 55 samples encompassing 18 countries and 38,408 participants, including 1931 with SAD. The frequency of winter-SAD, relative to that of summer-SAD, correlated positively with individualism (r=.67, p=.001) and negatively with power distance (r=-.72, p=.0001). Countries in which winter-SAD was more common than summer-SAD were significantly more individualistic and less power-distant than countries in which summer-SAD was more common than winter-SAD. Results survived various tests of threats to validity. The study is limited by the quantity, quality, diversity, and representativeness of the research under review and by its correlational design. Individualism and power distance are strongly related to the relative prevalence of winter-SAD and summer-SAD. Culture may play an important but previously overlooked role in the etiology of SAD.

Common polygenic variation enhances risk prediction for Alzheimer’s disease

PubMed Central

Sims, Rebecca; Bannister, Christian; Harold, Denise; Vronskaya, Maria; Majounie, Elisa; Badarinarayan, Nandini; Morgan, Kevin; Passmore, Peter; Holmes, Clive; Powell, John; Brayne, Carol; Gill, Michael; Mead, Simon; Goate, Alison; Cruchaga, Carlos; Lambert, Jean-Charles; van Duijn, Cornelia; Maier, Wolfgang; Ramirez, Alfredo; Holmans, Peter; Jones, Lesley; Hardy, John; Seshadri, Sudha; Schellenberg, Gerard D.; Amouyel, Philippe

2015-01-01

The identification of subjects at high risk for Alzheimer’s disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer’s disease and the accuracy of Alzheimer’s disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer’s Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer’s disease (P = 4.9 × 10−26). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10−19). The best prediction accuracy AUC = 78.2% (95% confidence interval 77–80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer’s disease has a significant polygenic component, which has predictive utility for Alzheimer’s disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes. PMID:26490334

Does Spontaneous Favorability to Power (vs. Universalism) Values Predict Spontaneous Prejudice and Discrimination?

PubMed

Souchon, Nicolas; Maio, Gregory R; Hanel, Paul H P; Bardin, Brigitte

2017-10-01

We conducted five studies testing whether an implicit measure of favorability toward power over universalism values predicts spontaneous prejudice and discrimination. Studies 1 (N = 192) and 2 (N = 86) examined correlations between spontaneous favorability toward power (vs. universalism) values, achievement (vs. benevolence) values, and a spontaneous measure of prejudice toward ethnic minorities. Study 3 (N = 159) tested whether conditioning participants to associate power values with positive adjectives and universalism values with negative adjectives (or inversely) affects spontaneous prejudice. Study 4 (N = 95) tested whether decision bias toward female handball players could be predicted by spontaneous attitude toward power (vs. universalism) values. Study 5 (N = 123) examined correlations between spontaneous attitude toward power (vs. universalism) values, spontaneous importance toward power (vs. universalism) values, and spontaneous prejudice toward Black African people. Spontaneous positivity toward power (vs. universalism) values was associated with spontaneous negativity toward minorities and predicted gender bias in a decision task, whereas the explicit measures did not. These results indicate that the implicit assessment of evaluative responses attached to human values helps to model value-attitude-behavior relations. © 2016 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

Alcohol use, sexual relationship power, and unprotected sex among patrons in bars and taverns in rural areas of North West province, South Africa.

PubMed

Nkosi, Sebenzile; Rich, Eileen P; Morojele, Neo K

2014-11-01

We examined the relative importance of alcohol consumption and sexual relationship power (SRP) in predicting unprotected sex among 406 bar patrons in North West province, South Africa. We assessed participants' demographic characteristics, alcohol consumption, SRP, and number of unprotected sexual episodes in the past 6 months. In correlational analyses, alcohol consumption was significantly associated with frequency of unprotected sex for both males and females. SRP was significantly associated with frequency of unprotected sex for males and marginally associated for females. In multivariate regression analyses, alcohol consumption was significantly associated with frequency of unprotected sex for both males and females. SRP's association was marginally significant for females and not significant for males. Alcohol consumption is more strongly associated with unprotected sex than is SRP among bar patrons. Combination HIV prevention approaches to curb problem drinking and increase condom accessibility, and regular and effective use are needed in tavern settings. SRP needs further examination among tavern populations.

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

Improved techniques for predicting spacecraft power

NASA Technical Reports Server (NTRS)

Chmielewski, A. B.

1987-01-01

Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance.

ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

PubMed

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-08-15

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

PubMed Central

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-01-01

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

Test anxiety and academic performance in chiropractic students.

PubMed

Zhang, Niu; Henderson, Charles N R

2014-01-01

Objective : We assessed the level of students' test anxiety, and the relationship between test anxiety and academic performance. Methods : We recruited 166 third-quarter students. The Test Anxiety Inventory (TAI) was administered to all participants. Total scores from written examinations and objective structured clinical examinations (OSCEs) were used as response variables. Results : Multiple regression analysis shows that there was a modest, but statistically significant negative correlation between TAI scores and written exam scores, but not OSCE scores. Worry and emotionality were the best predictive models for written exam scores. Mean total anxiety and emotionality scores for females were significantly higher than those for males, but not worry scores. Conclusion : Moderate-to-high test anxiety was observed in 85% of the chiropractic students examined. However, total test anxiety, as measured by the TAI score, was a very weak predictive model for written exam performance. Multiple regression analysis demonstrated that replacing total anxiety (TAI) with worry and emotionality (TAI subscales) produces a much more effective predictive model of written exam performance. Sex, age, highest current academic degree, and ethnicity contributed little additional predictive power in either regression model. Moreover, TAI scores were not found to be statistically significant predictors of physical exam skill performance, as measured by OSCEs.

Predictors of Working Alliance Efficacy among State VR Counselors as a Function of Ex-Offender Status

ERIC Educational Resources Information Center

Bates, Julie K.

2012-01-01

The purpose of this study was to determine if statistically significant relationships existed between burnout, stigma, flourishing, caseload size, experience, and working alliance self-efficacy and to assess the predictive power of these variables on levels of working alliance self-efficacy with clients with disabilities alone and clients with…

Mechanistic linkage of hydrologic regime to summer growth of age-0 Atlantic salmon

Treesearch

K.H. Nislow; A.J. Sepulveda; C.L. Folt

2004-01-01

Significant reductions in juvenile stream salmonid growth have been observed in association with low summer flow, but underlying mechanisms are poorly understood and predictive power is limited. We conducted a stage-specific analysis of the relationship between summer flow and the growth of age-0 Atlantic salmon Salmo salar in two rearing sites in...

77 FR 50533 - Dominion Nuclear Connecticut, Inc.; Millstone Power Station, Unit 3

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-21

....A.5, requires the Baker-Just equation to be used to predict the rates of energy release, hydrogen concentration, and cladding oxidation for the metal-water reaction. The Baker-Just equation assumed the use of a... that the proposed action will not have a significant effect on the quality of the human environment...

The role of family, peers and school perceptions in predicting involvement in youth violence.

PubMed

Laufer, Avital; Harel, Yossi

2003-01-01

This study explored the relative importance of family, peers and school in predicting youth violence. The analysis was done on a nationally representative sample included 8,394 students from grade 6th-10th in Israel. Measures of youth violence included bullying, physical fights and weapon carrying. The findings suggested that all three social systems had significant relations with youth violence, respectively. Variables found to predict violence were: Family-lack of parental support regarding school; Peers-Lack of social integration or too many evenings out with friends; School-feeling of school alienation, low academic achievement and perceptions of frequent acts of violence in school. School perceptions had the strongest predicting power. Findings emphasized the importance of focusing on improving the daily school experience in reducing youth violence.

SINGLE NEURON ACTIVITY AND THETA MODULATION IN POSTRHINAL CORTEX DURING VISUAL OBJECT DISCRIMINATION

PubMed Central

Furtak, Sharon C.; Ahmed, Omar J.; Burwell, Rebecca D.

2012-01-01

Postrhinal cortex, the rodent homolog of the primate parahippocampal cortex, processes spatial and contextual information. Our hypothesis of postrhinal function is that it serves to encode context, in part, by forming representations that link objects to places. We recorded postrhinal neuronal activity and local field potentials (LFPs) in rats trained on a two-choice, visual discrimination task. As predicted, a large proportion of postrhinal neurons signaled object-location conjunctions. In addition, postrhinal LFPs exhibited strong oscillatory rhythms in the theta band, and many postrhinal neurons were phase locked to theta. Although correlated with running speed, theta power was lower than predicted by speed alone immediately before and after choice. However, theta power was significantly increased following incorrect decisions, suggesting a role in signaling error. These findings provide evidence that postrhinal cortex encodes representations that link objects to places and suggest that postrhinal theta modulation extends to cognitive as well as spatial functions. PMID:23217745

Enhanced thermoelectric performance of graphene nanoribbon-based devices

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

Hossain, Md Sharafat, E-mail: hossain@student.unimelb.edu.au; Huynh, Duc Hau; Nguyen, Phuong Duc

There have been numerous theoretical studies on exciting thermoelectric properties of graphene nano-ribbons (GNRs); however, most of these studies are mainly based on simulations. In this work, we measure and characterize the thermoelectric properties of GNRs and compare the results with theoretical predictions. Our experimental results verify that nano-structuring and patterning graphene into nano-ribbons significantly enhance its thermoelectric power, confirming previous predictions. Although patterning results in lower conductance (G), the overall power factor (S{sup 2}G) increases for nanoribbons. We demonstrate that edge roughness plays an important role in achieving such an enhanced performance and support it through first principles simulations.more » We show that uncontrolled edge roughness, which is considered detrimental in GNR-based electronic devices, leads to enhanced thermoelectric performance of GNR-based thermoelectric devices. The result validates previously reported theoretical studies of GNRs and demonstrates the potential of GNRs for the realization of highly efficient thermoelectric devices.« less

Large scale structure constraints for a class of f(R) theories of gravity

NASA Astrophysics Data System (ADS)

Abebe, Amare; de la Cruz-Dombriz, Álvaro; Dunsby, Peter K. S.

2013-08-01

Over the past few years much attention has been given to the study of modified gravity theories in order to find a more natural explanation for the late time acceleration of the Universe. Nevertheless, a comparison of the matter power spectrum predictions made by these theories with available data has not yet been subjected to a detailed analysis. In the context of f(R) theories of gravity we study the predicted power spectra using both a dynamical systems approach for the background and solving for the matter perturbations without using the quasistatic approximation, comparing the theoretical results with several Sloan Digital Sky Survey data. The importance of studying the first order perturbed equations by assuming the correct background evolution and the relevance of the initial conditions are also stressed. We determine the statistical significance in relation to the observational data and demonstrate their conflict with existing observations.

[Influence of educational status, burn area and coping behaviors on the complication of psychological disorders in severely burned patients].

PubMed

Cheng, Hua; Li, Xiao-jian; Cao, Wen-juan; Chen, Li-ying; Zhang, Zhi; Liu, Zhi-he; Yi, Xian-feng; Lai, Wen

2013-04-01

To discuss how the educational status, burn area and coping behaviors influence the psychological disorders in severely burned patients. Sixty-four severely burned patients hospitalized in Guangzhou Red Cross Hospital, Guangdong Provincial Work Injury Rehabilitation Center, and Guangdong General Hospital were enrolled with cluster random sampling method. Data of their demography and situation of burns were collected. Then their coping behavior, psychological disorders including anxiety, depression and post-traumatic stress disorder (PTSD) plus its core symptoms of flashback, avoidance, and hypervigilance were assessed by medical coping modes questionnaire, self-rating anxiety scale (SAS), self-rating depression scale (SDS), PTSD checklist-civilian version (PCL-C) respectively. Correlation was analyzed between demography, burn area, coping behavior and psychological disorders. The predictive powers of educational status, burn area and coping behaviors on the psychological disorders were analyzed. The qualitative variables were assigned values. Data were processed with t test, Spearman rank correlation analysis, and multiple linear regression analysis. (1) The patients scored (19.0 ± 3.4) points in confrontation coping behavior, which showed no statistically significant difference from the domestic norm score (19.5 ± 3.8) points (t = -1.13, P > 0.05). The patients scored (16.6 ± 2.4) and (11.0 ± 2.2) points in avoidance and resignation coping behaviors, which were significantly higher than the domestic norm score (14.4 ± 3.0), (8.8 ± 3.2) points (with t values respectively 7.06 and 7.76, P values both below 0.01). The patients' standard score of SAS, SDS, PCL-C were (50 ± 11), (54 ± 11), and (38 ± 12) points. Respectively 89.1% (57/64), 60.9% (39/64), 46.9% (30/64) of the patients showed anxiety, depression, and PTSD symptoms. (2) Four independent variables: age, gender, marital status, and time after burns, were correlated with the psychological disorders, but the correlativity was not statistically significant (with rs values from -0.089 to 0.245, P values all above 0.05). Educational status was significantly negatively correlated with anxiety, depression, PTSD and its core symptoms of flashback, avoidance (with rs values from -0.361 to -0.253, P values all below 0.05). Educational status was negatively correlated with hypervigilance, but the correlativity was not statistically significant (rs = -0.187, P > 0.05). Burn area was significantly positively correlated with the psychological disorders (with rs values from 0.306 to 0.478, P values all below 0.05). Confrontation coping behavior was positively correlated with the psychological disorders, but the correlativity was not statistically significant (with rs values from 0.121 to 0.550, P values all above 0.05). Avoidance coping behavior was correlated with the psychological disorders, but the correlativity was not statistically significant (with rs values from -0.144 to 0.193, P values all above 0.05). Resignation coping behavior was significantly positively correlated with the psychological disorder (with rs values from 0.377 to 0.596, P values all below 0.01). (3) Educational status had predictive power on the anxiety, PTSD and flash back symptoms of patients (with t values from -2.19 to -2.02, P values all below 0.05), but not on depression, avoidance and hypervigilance (with t values from -1.95 to -0.99, P values all above 0.05). Burn area had no predictive power on the psychological disorders (with t values from 0.55 to 1.78, P values all above 0.05). Resignation coping behavior had predictive power on the psychological disorders (with t values from 3.10 to 6.46, P values below 0.01). Confrontation and avoidance coping behaviors had no predictive power on the psychological disorders (with t values from 0.46 to 2.32 and -0.89 and 1.75 respectively, P values all above 0.05). The severely burned patients with lower educational status, larger burn area, and the more frequently adapted resignation coping behavior are more likely to suffer from anxiety, depression, and PTSD.

Predicting power-optimal kinematics of avian wings

PubMed Central

Parslew, Ben

2015-01-01

A theoretical model of avian flight is developed which simulates wing motion through a class of methods known as predictive simulation. This approach uses numerical optimization to predict power-optimal kinematics of avian wings in hover, cruise, climb and descent. The wing dynamics capture both aerodynamic and inertial loads. The model is used to simulate the flight of the pigeon, Columba livia, and the results are compared with previous experimental measurements. In cruise, the model unearths a vast range of kinematic modes that are capable of generating the required forces for flight. The most efficient mode uses a near-vertical stroke–plane and a flexed-wing upstroke, similar to kinematics recorded experimentally. In hover, the model predicts that the power-optimal mode uses an extended-wing upstroke, similar to hummingbirds. In flexing their wings, pigeons are predicted to consume 20% more power than if they kept their wings full extended, implying that the typical kinematics used by pigeons in hover are suboptimal. Predictions of climbing flight suggest that the most energy-efficient way to reach a given altitude is to climb as steeply as possible, subjected to the availability of power. PMID:25392398

Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Fihn, Stephan D

2009-01-01

To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.

In-class didactic versus self-directed teaching of the probe-based confocal laser endomicroscopy (pCLE) criteria for Barrett's esophagus.

PubMed

Rzouq, Fadi; Vennalaganti, Prashanth; Pakseresht, Kavous; Kanakadandi, Vijay; Parasa, Sravanthi; Mathur, Sharad C; Alsop, Benjamin R; Hornung, Benjamin; Gupta, Neil; Sharma, Prateek

2016-02-01

Optimal teaching methods for disease recognition using probe-based confocal laser endomicroscopy (pCLE) have not been developed. Our aim was to compare in-class didactic teaching vs. self-directed teaching of Barrett's neoplasia diagnosis using pCLE. This randomized controlled trial was conducted at a tertiary academic center. Study participants with no prior pCLE experience were randomized to in-class didactic (group 1) or self-directed teaching groups (group 2). For group 1, an expert conducted a classroom teaching session using standardized educational material. Participants in group 2 were provided with the same material on an audio PowerPoint. After initial training, all participants graded an initial set of 20 pCLE videos and reviewed correct responses with the expert (group 1) or on audio PowerPoint (group 2). Finally, all participants completed interpretations of a further 40 videos. Eighteen trainees (8 medical students, 10 gastroenterology trainees) participated in the study. Overall diagnostic accuracy for neoplasia prediction by pCLE was 77 % (95 % confidence interval [CI] 74.0 % - 79.2 %); of predictions made with high confidence (53 %), the accuracy was 85 % (95 %CI 81.8 % - 87.8 %). The overall accuracy and interobserver agreement was significantly higher in group 1 than in group 2 for all predictions (80.4 % vs. 73 %; P = 0.005) and for high confidence predictions (90 % vs. 80 %; P < 0.001). Following feedback (after the initial 20 videos), the overall accuracy improved from 73 % to 79 % (P = 0.04), mainly driven by a significant improvement in group 1 (74 % to 84 %; P < 0.01). Accuracy of prediction significantly improved with time in endoscopy training (72 % students, 77 % FY1, 82 % FY2, and 85 % FY3; P = 0.003). For novice trainees, in-class didactic teaching enables significantly better recognition of the pCLE features of Barrett's esophagus than self-directed teaching. The in-class didactic group had a shorter learning curve and were able to achieve 90 % accuracy for their high confidence predictions. © Georg Thieme Verlag KG Stuttgart · New York.

Prediction of light aircraft interior sound pressure level using the room equation

NASA Technical Reports Server (NTRS)

Atwal, M.; Bernhard, R.

1984-01-01

The room equation is investigated for predicting interior sound level. The method makes use of an acoustic power balance, by equating net power flow into the cabin volume to power dissipated within the cabin using the room equation. The sound power level transmitted through the panels was calculated by multiplying the measured space averaged transmitted intensity for each panel by its surface area. The sound pressure level was obtained by summing the mean square sound pressures radiated from each panel. The data obtained supported the room equation model in predicting the cabin interior sound pressure level.

Multi-Temporal Decomposed Wind and Load Power Models for Electric Energy Systems

NASA Astrophysics Data System (ADS)

Abdel-Karim, Noha

This thesis is motivated by the recognition that sources of uncertainties in electric power systems are multifold and may have potentially far-reaching effects. In the past, only system load forecast was considered to be the main challenge. More recently, however, the uncertain price of electricity and hard-to-predict power produced by renewable resources, such as wind and solar, are making the operating and planning environment much more challenging. The near-real-time power imbalances are compensated by means of frequency regulation and generally require fast-responding costly resources. Because of this, a more accurate forecast and look-ahead scheduling would result in a reduced need for expensive power balancing. Similarly, long-term planning and seasonal maintenance need to take into account long-term demand forecast as well as how the short-term generation scheduling is done. The better the demand forecast, the more efficient planning will be as well. Moreover, computer algorithms for scheduling and planning are essential in helping the system operators decide what to schedule and planners what to build. This is needed given the overall complexity created by different abilities to adjust the power output of generation technologies, demand uncertainties and by the network delivery constraints. Given the growing presence of major uncertainties, it is likely that the main control applications will use more probabilistic approaches. Today's predominantly deterministic methods will be replaced by methods which account for key uncertainties as decisions are made. It is well-understood that although demand and wind power cannot be predicted at very high accuracy, taking into consideration predictions and scheduling in a look-ahead way over several time horizons generally results in more efficient and reliable utilization, than when decisions are made assuming deterministic, often worst-case scenarios. This change is in approach is going to ultimately require new electricity market rules capable of providing the right incentives to manage uncertainties and of differentiating various technologies according to the rate at which they can respond to ever changing conditions. Given the overall need for modeling uncertainties in electric energy systems, we consider in this thesis the problem of multi-temporal modeling of wind and demand power, in particular. Historic data is used to derive prediction models for several future time horizons. Short-term prediction models derived can be used for look-ahead economic dispatch and unit commitment, while the long-term annual predictive models can be used for investment planning. As expected, the accuracy of such predictive models depends on the time horizons over which the predictions are made, as well as on the nature of uncertain signals. It is shown that predictive models obtained using the same general modeling approaches result in different accuracy for wind than for demand power. In what follows, we introduce several models which have qualitatively different patterns, ranging from hourly to annual. We first transform historic time-stamped data into the Fourier Transform (Fr) representation. The frequency domain data representation is used to decompose the wind and load power signals and to derive predictive models relevant for short-term and long-term predictions using extracted spectral techniques. The short-term results are interpreted next as a Linear Prediction Coding Model (LPC) and its accuracy is analyzed. Next, a new Markov-Based Sensitivity Model (MBSM) for short term prediction has been proposed and the dispatched costs of uncertainties for different predictive models with comparisons have been developed. Moreover, the Discrete Markov Process (DMP) representation is applied to help assess probabilities of most likely short-, medium- and long-term states and the related multi-temporal risks. In addition, this thesis discusses operational impacts of wind power integration in different scenario levels by performing more than 9,000 AC Optimal Power Flow runs. The effects of both wind and load variations on system constraints and costs are presented. The limitations of DC Optimal Power Flow (DCOPF) vs. ACOPF are emphasized by means of system convergence problems due to the effect of wind power on changing line flows and net power injections. By studying the effect of having wind power on line flows, we found that the divergence problem applies in areas with high wind and hydro generation capacity share (cheap generations). (Abstract shortened by UMI.).

In arthritis the Doppler based degree of hypervascularisation shows a positive correlation with synovial leukocyte count and distinguishes joints with leukocytes greater and less than 5/nL.

PubMed

Löffler, Christian; Sattler, Horst; Peters, Lena; Tuleweit, Anika; Löffler, Uta; Wadsack, Daniel; Uppenkamp, Michael; Bergner, Raoul

2016-10-01

Power Doppler ultrasound is used to assess joint vascularity in acute arthritis. PDUS signals have been correlated with synovial histology and bone deterioration. Little is known about the correlation between power Doppler signals and synovial white blood count. In our study, we analyzed power Doppler signals in inflammatory joint diseases including gout, calcium pyrophosphate deposition disease, rheumatoid arthritis, spondyloarthritis and others and correlated power Doppler signals with synovial white blood count and with serologic markers of inflammation. We retrospectively evaluated 194 patients with arthritis. All patients underwent joint sonography, power Doppler ultrasound, synovial fluid analysis and blood examination of C-reactive protein and erythrocyte sedimentation rate. Correlation analyses (Spearman and Pearson), Chi(2) test, t-tests, a unifactorial ANOVA and regression analyses were applied. Hypervascularisation in power Doppler was most prominent in gout and calcium pyrophosphate deposition disease. Spondyloarthritis and non-inflammatory joint diseases presented with low degrees of hypervascularisation. Mean synovial white blood count did not differ significantly between crystal-related arthritides, rheumatoid arthritis, spondyloarthritis or other inflammatory joint diseases. There was a positive but weak correlation between power Doppler signals and synovial white blood count (P<0.001, rs=0.283), erythrocyte sedimentation rate (P<0.001, rs=0.387) and C-reactive protein (P<0.001, rs=0.373) over all diagnoses. This was especially relevant in rheumatoid arthritis (P<0.01, rs=0.479). Power Doppler degrees 0 and 1 were able to predict synovial leukocytes<5/nL, degrees 2 and 3 predict leukocytes≥5/nL (P<0.001). Copyright © 2016 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

Comparison of newer IOL power calculation methods for post-corneal refractive surgery eyes

PubMed Central

Wang, Li; Tang, Maolong; Huang, David; Weikert, Mitchell P.; Koch, Douglas D.

2015-01-01

Objective To compare the newer formulae, the optical coherence tomography based intraocular lens (IOL) power formula (OCT formula) and the Barrett True-K formula (True-K), to the methods on the ASCRS calculator in eyes with previous myopic LASIK/PRK. Design Prospective case series. Participants One-hundred and four eyes of 80 patients who had previous myopic LASIK/PRK and subsequent cataract surgery and IOL implantation. Methods Using the actual refraction following cataract surgery as target refraction, predicted IOL power for each method was calculated. The IOL prediction error (PE) was obtained by subtracting the predicted IOL power from the power of IOL implanted. Main outcome measures Arithmetic IOL PEs, variances of mean arithmetic IOL PE, median refractive PE and percent of eyes within 0.5 D and 1.0 D of refractive PE. Results OCT produced smaller variance of IOL PE than did Wang-Koch-Maloney, and Shammas (P<0.05). With the OCT, True-K No History, Wang-Koch-Maloney, Shammas, Haigis-L, and Average of these 5 formulas, respectively, the median refractive PEs were 0.35 D, 0.42 D, 0.51 D, 0.48 D, 0.39 D, and 0.35 D, and the % of eyes within 0.5 D of refractive PE were 68.3%, 58.7%, 50.0%, 52.9%, 55.8%, and 67.3%, and within 1.0 D of RPE, 92.3%, 90.4%, 86.9%, 88.5%, 90.4%, and 94.2%, respectively. The OCT formula had smaller refractive PE compared to Wang-Koch-Maloney and Shammas, and the Average approach produced significantly smaller refractive PE than did all methods except OCT (all P<0.05). Conclusions The OCT and True-K No History are promising formulas. The ASCRS IOL calculator has been updated to include the OCT and Barrett True K formulas. Trial registration Intraocular Lens Power Calculation After Laser Refractive Surgery Based on Optical Coherence Tomography (OCT IOL); Identifier: NCT00532051; www.ClinicalTrials.gov PMID:26459996

The effects of load on system and lower-body joint kinetics during jump squats.

PubMed

Moir, Gavin L; Gollie, Jared M; Davis, Shala E; Guers, John J; Witmer, Chad A

2012-11-01

To investigate the effects of different loads on system and lower-body kinetics during jump squats, 12 resistance-trained men performed jumps under different loading conditions: 0%, 12%, 27%, 42%, 56%, 71%, and 85% of 1-repetition maximum (1-RM). System power output was calculated as the product of the vertical component of the ground reaction force and the vertical velocity of the bar during its ascent. Joint power output was calculated during bar ascent for the hip, knee, and ankle joints, and was also summed across the joints. System power output and joint power at knee and ankle joints were maximized at 0% 1-RM (p < 0.001) and followed the linear trends (p < 0.001) caused by power output decreasing as the load increased. Power output at the hip was maximized at 42% 1-RM (p = 0.016) and followed a quadratic trend (p = 0.030). Summed joint power could be predicted from system power (p < 0.05), while system power could predict power at the knee and ankle joints under some of the loading conditions. Power at the hip could not be predicted from system power. System power during loaded jumps reflects the power at the knee and ankle, while power at the hip does not correspond to system power.

Electroencephalographic identifiers of motor adaptation learning

NASA Astrophysics Data System (ADS)

Özdenizci, Ozan; Yalçın, Mustafa; Erdoğan, Ahmetcan; Patoğlu, Volkan; Grosse-Wentrup, Moritz; Çetin, Müjdat

2017-08-01

Objective. Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. Approach. Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. Main results. Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. Significance. Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

Replacement of SSE (Release 6) with NASA's Prediction of Worldwide Energy Resource (POWER) Project GIS-enabled Web Data Portal:

Atmospheric Science Data Center

2018-03-15

... effort has been developed under the Prediction Of Worldwide Energy Resource (POWER) Project funded largely by NASA Earth Applied Sciences ... to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A new POWER ...

POWER/SSE

Atmospheric Science Data Center

2018-06-15

... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ... continue to be focussed on the solar and wind Renewable Energy industry. New data sets will target Sustainable Buildings ... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ...

The Power Within: The Experimental Manipulation of Power Interacts with Trait BDD Symptoms to Predict Interoceptive Accuracy

PubMed Central

Kunstman, Jonathan W.; Clerkin, Elise M.; Palmer, Kateyln; Peters, M. Taylar; Dodd, Dorian R.; Smith, April R.

2015-01-01

Background and Objectives This study tested whether relatively low levels of interoceptive accuracy (IAcc) are associated with body dysmorphic disorder (BDD) symptoms. Additionally, given research indicating that power attunes individuals to their internal states, we sought to determine if state interoceptive accuracy could be improved through an experimental manipulation of power. Method Undergraduate women (N = 101) completed a baseline measure of interoceptive accuracy and then were randomized to a power or control condition. Participants were primed with power or a neutral control topic and then completed a post-manipulation measure of state IAcc. Trait BDD symptoms were assessed with a self-report measure. Results Controlling for baseline IAcc, within the control condition, there was a significant inverse relationship between trait BDD symptoms and interoceptive accuracy. Continuing to control for baseline IAcc, within the power condition, there was not a significant relationship between trait BDD symptoms and IAcc, suggesting that power may have attenuated this relationship. At high levels of BDD symptomology, there was also a significant simple effect of experimental condition, such that participants in the power (vs. control) condition had better interoceptive accuracy. These results provide initial evidence that power may positively impact interoceptive accuracy among those with high levels of BDD symptoms. Limitations This cross-sectional study utilized a demographically homogenous sample of women that reflected a broad range of symptoms; thus, although there were a number of participants reporting elevated BDD symptoms, these findings might not generalize to other populations or clinical samples. Conclusions . This study provides the first direct test of the relationship between trait BDD symptoms and IAcc, and provides preliminary evidence that among those with severe BDD symptoms, power may help connect individuals with their internal states. Future research testing the mechanisms linking BDD symptoms with IAcc, as well as how individuals can better connect with their internal experiences is needed. PMID:26295932

The power within: The experimental manipulation of power interacts with trait BDD symptoms to predict interoceptive accuracy.

PubMed

Kunstman, Jonathan W; Clerkin, Elise M; Palmer, Kateyln; Peters, M Taylar; Dodd, Dorian R; Smith, April R

2016-03-01

This study tested whether relatively low levels of interoceptive accuracy (IAcc) are associated with body dysmorphic disorder (BDD) symptoms. Additionally, given research indicating that power attunes individuals to their internal states, we sought to determine if state interoceptive accuracy could be improved through an experimental manipulation of power.. Undergraduate women (N = 101) completed a baseline measure of interoceptive accuracy and then were randomized to a power or control condition. Participants were primed with power or a neutral control topic and then completed a post-manipulation measure of state IAcc. Trait BDD symptoms were assessed with a self-report measure. Controlling for baseline IAcc, within the control condition, there was a significant inverse relationship between trait BDD symptoms and interoceptive accuracy. Continuing to control for baseline IAcc, within the power condition, there was not a significant relationship between trait BDD symptoms and IAcc, suggesting that power may have attenuated this relationship. At high levels of BDD symptomology, there was also a significant simple effect of experimental condition, such that participants in the power (vs. control) condition had better interoceptive accuracy. These results provide initial evidence that power may positively impact interoceptive accuracy among those with high levels of BDD symptoms.. This cross-sectional study utilized a demographically homogenous sample of women that reflected a broad range of symptoms; thus, although there were a number of participants reporting elevated BDD symptoms, these findings might not generalize to other populations or clinical samples. This study provides the first direct test of the relationship between trait BDD symptoms and IAcc, and provides preliminary evidence that among those with severe BDD symptoms, power may help connect individuals with their internal states. Future research testing the mechanisms linking BDD symptoms with IAcc, as well as how individuals can better connect with their internal experiences is needed.. Copyright © 2015 Elsevier Ltd. All rights reserved.

Association between diabetic peripheral neuropathy and heart rate variability in subjects with type 2 diabetes.

PubMed

Islam, S K M Azizul; Kim, Dongkyu; Lee, Young-Sil; Moon, Seong-Su

2018-06-01

This study evaluated the association of Heart rate variability (HRV) measurements with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes. This study included 102 Korean subjects with type 2 diabetes. The Michigan neuropathy screening instrument (MNSI) questionnaire score, the MNSI examination score (MNSIES) and the total symptom score were examined for DPN evaluation. Noninvasive HRV measurements were performed using photoelectric plethysmography. Patients with a MNSIES > 2 were considered to have DPN. The MNSIES showed significant negative associations with the high frequency (HF) (r = -0.212, p = 0.033) and low frequency (LF) (r = -0.286, p = 0.004) powers. Multiple linear regression analysis revealed that only HF power maintained a significant negative association with the MNSIES (β = -0.184; 95% CI -0.365 to -0.003; p = 0.047), after controlling for significant related confounders, with HRV parameters in male patients with type 2 diabetes. The HF (p = 0.010) and LF (p = 0.025) powers differed significantly between male patients without and those with DPN according to the MNSIES. This study revealed a negative association of DPN, as assessed by the MNSIES, with HF power in male patients with type 2 diabetes. DPN defined by foot examination was predictive of cardiac autonomic neuropathy. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Experimental Evaluation of a Water Shield for a Surface Power Reactor

NASA Technical Reports Server (NTRS)

Pearson, J. B.; Reid, R.; Sadasivan, P.; Stewart, E.

2007-01-01

A water based shielding system is being investigated for use on initial lunar surface power systems. The use of water may lower overall cost (as compared to development cost for other materials) and simplify operations in the setup and handling. The thermal hydraulic performance of the shield is of significant interest. The mechanism for transferring heat through the shield is natural convection. A representative lunar surface reactor design is evaluated at various power levels in the Water Shield Testbed (WST) at the NASA Marshall Space Flight Center. The evaluation compares the experimental data from the WST to CFD models. Performance of a water shield on the lunar surface is predicted by CFD models anchored to test data, and by matching relevant dimensionless parameters.

High-power piezoelectric acoustic-electric power feedthru for metal walls

NASA Astrophysics Data System (ADS)

Bao, Xiaoqi; Biederman, Will; Sherrit, Stewart; Badescu, Mircea; Bar-Cohen, Yoseph; Jones, Christopher; Aldrich, Jack; Chang, Zensheu

2008-03-01

Piezoelectric acoustic-electric power feed-through devices transfer electric power wirelessly through a solid wall using elastic waves. This approach allows for the elimination of the need for holes through structures for cabling or electrical feed-thrus . The technology supplies power to electric equipment inside sealed containers, vacuum or pressure vessels, etc where holes in the wall are prohibitive or may result in significant performance degradation or requires complex designs. In the our previous work, 100-W of electric power was transferred through a metal wall by a small, piezoelectric device with a simple-structure. To meet requirements of higher power applications, the feasibility to transfer kilowatts level power was investigated. Pre-stressed longitudinal piezoelectric feed-thru devices were analyzed by finite element modeling. An equivalent circuit model was developed to predict the characteristics of power transfer to different electric loads. Based on the analytical results, a prototype device was designed, fabricated and successfully demonstrated to transfer electric power at a level of 1-kW. Methods of minimizing plate wave excitation on the wall were also analyzed. Both model analysis and experimental results are presented in detail in this paper.

Bisubstrate inhibition: Theory and application to N-acetyltransferases.

PubMed

Yu, Michael; Magalhães, Maria L B; Cook, Paul F; Blanchard, John S

2006-12-12

Bisubstrate inhibitors represent a potentially powerful group of compounds that have found significant therapeutic utility. Although these compounds have been synthesized and tested against a number of enzymes that catalyze sequential bireactant reactions, the detailed theory for predicting the expected patterns of inhibition against the two substrates for various bireactant kinetic mechanisms has, heretofore, not been presented. We have derived the rate equations for all likely sequential bireactant mechanisms and provide two examples in which bisubstrate inhibitors allow the kinetic mechanism to be determined. Bisubstrate inhibitor kinetics is a powerful diagnostic for the determination of kinetic mechanisms.

Confirmation of shutdown cooling effects

NASA Astrophysics Data System (ADS)

Sato, Kotaro; Tabuchi, Masato; Sugimura, Naoki; Tatsumi, Masahiro

2015-12-01

After the Fukushima accidents, all nuclear power plants in Japan have gradually stopped their operations and have long periods of shutdown. During those periods, reactivity of fuels continues to change significantly especially for high-burnup UO2 fuels and MOX fuels due to radioactive decays. It is necessary to consider these isotopic changes precisely, to predict neutronics characteristics accurately. In this paper, shutdown cooling (SDC) effects of UO2 and MOX fuels that have unusual operation histories are confirmed by the advanced lattice code, AEGIS. The calculation results show that the effects need to be considered even after nuclear power plants come back to normal operation.

Graphene surface emitting terahertz laser: Diffusion pumping concept

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

Davoyan, Arthur R., E-mail: davoyan@seas.upenn.edu; Morozov, Mikhail Yu.; Popov, Vyacheslav V.

2013-12-16

We suggest a concept of a tunable graphene-based terahertz (THz) surface emitting laser with diffusion pumping. We employ significant difference in the electronic energy gap of graphene and a typical wide-gap semiconductor, and demonstrate that carriers generated in the semiconductor can be efficiently captured by graphene resulting in population inversion and corresponding THz lasing from graphene. We develop design principles for such a laser and estimate its performance. We predict up to 50 W/cm{sup 2} terahertz power output for 100 kW/cm{sup 2} pump power at frequency around 10 THz at room temperature.

The utility of Bayesian predictive probabilities for interim monitoring of clinical trials

PubMed Central

Connor, Jason T.; Ayers, Gregory D; Alvarez, JoAnn

2014-01-01

Background Bayesian predictive probabilities can be used for interim monitoring of clinical trials to estimate the probability of observing a statistically significant treatment effect if the trial were to continue to its predefined maximum sample size. Purpose We explore settings in which Bayesian predictive probabilities are advantageous for interim monitoring compared to Bayesian posterior probabilities, p-values, conditional power, or group sequential methods. Results For interim analyses that address prediction hypotheses, such as futility monitoring and efficacy monitoring with lagged outcomes, only predictive probabilities properly account for the amount of data remaining to be observed in a clinical trial and have the flexibility to incorporate additional information via auxiliary variables. Limitations Computational burdens limit the feasibility of predictive probabilities in many clinical trial settings. The specification of prior distributions brings additional challenges for regulatory approval. Conclusions The use of Bayesian predictive probabilities enables the choice of logical interim stopping rules that closely align with the clinical decision making process. PMID:24872363

The relationship of plasma decoy receptor 3 and coronary collateral circulation in patients with coronary artery disease.

PubMed

Yan, Youyou; Song, Dandan; Liu, Lulu; Meng, Xiuping; Qi, Chao; Wang, Junnan

2017-11-15

Previously, decoy receptor 3 (DcR3) was found to be a potential angiogenetic factor, while the relationship of DcR3 with coronary collateral circulation formation has not been investigated. In this study, we aimed to investigate whether plasma decoy receptor 3 levels was associated with CCC formation and evaluate its predictive power for CCC status in patients with coronary artery disease. Among patients who underwent coronary angiography with coronary artery disease and had a stenosis of ≥90% were included in our study. Collateral degree was graded according to Rentrope Cohen classification. Patients with grade 2 or 3 collateral degree were enrolled in good CCC group and patients with grade 0 or 1 collateral degree were enrolled in poor CCC group. Plasma DcR3 level was significantly higher in good CCC group (328.00±230.82 vs 194.84±130.63ng/l, p<0.01) and positively correlated with Rentrope grade (p<0.01). In addition, plasma DcR3 was also positively correlated with VEGF-A. Both ROC (receiver operating characteristic curve) and multinomial logistical regression analysis showed that plasma DcR3 displayed potent predictive power for CCC status. Higher plasma DcR3 level was related to better CCC formation and displayed potent predictive power for CCC status. Copyright © 2017. Published by Elsevier Inc.

Migrants, health, and happiness: Evidence that health assessments travel with migrants and predict well-being.

PubMed

Ljunge, Martin

2016-09-01

Health assessments correlate with health outcomes and subjective well-being. Immigrants offer an opportunity to study persistent social influences on health where the social conditions are not endogenous to individual outcomes. This approach provides a clear direction of causality from social conditions to health, and in a second stage to well-being. Natives and immigrants from across the world residing in 30 European countries are studied using survey data. The paper applies within country analysis using both linear regressions and two stage least squares. Natives' and immigrants' individual characteristics have similar predictive power for health, except Muslim immigrants who experience a sizeable health penalty. Average health reports in the immigrant's birth country have a significant association with the immigrant's current health. Almost a quarter of the birth country health variation is brought by the immigrants, while conditioning on socioeconomic characteristics. There is no evidence of the birth country predictive power declining neither as the immigrant spends more time in the residence country nor over the life course. The second stage estimates indicate that a one standard deviation improvement in health predicts higher happiness by 1.72 point or 0.82 of a standard deviation, more than four times the happiness difference of changing employment status from unemployed to employed. Studying life satisfaction yields similar results. Health improvements predict substantial increases in individual happiness. Copyright © 2016 Elsevier B.V. All rights reserved.

Neuropsychological test performance and prediction of functional capacities among Spanish-speaking and English-speaking patients with dementia.

PubMed

Loewenstein, D A; Rubert, M P; Argüelles, T; Duara, R

1995-03-01

Neuropsychological measures have been widely used by clinicians to assist them in making judgments regarding a cognitively impaired patient's ability to independently perform important activities of daily living. However, important questions have been raised concerning the degree to which neuropsychological instruments can predict a broad array of specific functional capacities required in the home environment. In the present study, we examined 127 English-speaking and 56 Spanish-speaking patients with Alzheimer's disease (AD) and determined the extent to which various neuropsychological measures and demographic variables were predictive of performance on functional measures administered within the clinical setting. Among English-speaking AD patients, Block Design and Digit-Span of the WAIS-R, as well as tests of language were among the strongest predictors of functional performance. For Spanish-speakers, Block Design, The Mini-Mental State Evaluation (MMSE) and Digit Span had the optimal predictive power. When stepwise regression was conducted on the entire sample of 183 subjects, ethnicity emerged as a statistically significant predictor variable on one of the seven functional tests (writing a check). Despite the predictive power of several of the neuropsychological measures for both groups, most of the variability in objective functional performance could not be explained in our regression models. As a result, it would appear prudent to include functional measures as part of a comprehensive neuropsychological evaluation for dementia.

Integration of element specific persistent homology and machine learning for protein-ligand binding affinity prediction.

PubMed

Cang, Zixuan; Wei, Guo-Wei

2018-02-01

Protein-ligand binding is a fundamental biological process that is paramount to many other biological processes, such as signal transduction, metabolic pathways, enzyme construction, cell secretion, and gene expression. Accurate prediction of protein-ligand binding affinities is vital to rational drug design and the understanding of protein-ligand binding and binding induced function. Existing binding affinity prediction methods are inundated with geometric detail and involve excessively high dimensions, which undermines their predictive power for massive binding data. Topology provides the ultimate level of abstraction and thus incurs too much reduction in geometric information. Persistent homology embeds geometric information into topological invariants and bridges the gap between complex geometry and abstract topology. However, it oversimplifies biological information. This work introduces element specific persistent homology (ESPH) or multicomponent persistent homology to retain crucial biological information during topological simplification. The combination of ESPH and machine learning gives rise to a powerful paradigm for macromolecular analysis. Tests on 2 large data sets indicate that the proposed topology-based machine-learning paradigm outperforms other existing methods in protein-ligand binding affinity predictions. ESPH reveals protein-ligand binding mechanism that can not be attained from other conventional techniques. The present approach reveals that protein-ligand hydrophobic interactions are extended to 40Å  away from the binding site, which has a significant ramification to drug and protein design. Copyright © 2017 John Wiley & Sons, Ltd.

Use of a least absolute shrinkage and selection operator (LASSO) model to selected ion flow tube mass spectrometry (SIFT-MS) analysis of exhaled breath to predict the efficacy of dialysis: a pilot study.

PubMed

Wang, Maggie Haitian; Chong, Ka Chun; Storer, Malina; Pickering, John W; Endre, Zoltan H; Lau, Steven Yf; Kwok, Chloe; Lai, Maria; Chung, Hau Yin; Ying Zee, Benny Chung

2016-09-28

Selected ion flow tube-mass spectrometry (SIFT-MS) provides rapid, non-invasive measurements of a full-mass scan of volatile compounds in exhaled breath. Although various studies have suggested that breath metabolites may be indicators of human disease status, many of these studies have included few breath samples and large numbers of compounds, limiting their power to detect significant metabolites. This study employed a least absolute shrinkage and selective operator (LASSO) approach to SIFT-MS data of breath samples to preliminarily evaluate the ability of exhaled breath findings to monitor the efficacy of dialysis in hemodialysis patients. A process of model building and validation showed that blood creatinine and urea concentrations could be accurately predicted by LASSO-selected masses. Using various precursors, the LASSO models were able to predict creatinine and urea concentrations with high adjusted R-square (>80%) values. The correlation between actual concentrations and concentrations predicted by the LASSO model (using precursor H 3 O + ) was high (Pearson correlation coefficient  =  0.96). Moreover, use of full mass scan data provided a better prediction than compounds from selected ion mode. These findings warrant further investigations in larger patient cohorts. By employing a more powerful statistical approach to predict disease outcomes, breath analysis using SIFT-MS technology could be applicable in future to daily medical diagnoses.

Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis.

PubMed

Vanni, Michael J; McIntyre, Peter B

2016-12-01

The metabolic theory of ecology (MTE) and ecological stoichiometry (ES) are both prominent frameworks for understanding energy and nutrient budgets of organisms. We tested their separate and joint power to predict nitrogen (N) and phosphorus (P) excretion rates of ectothermic aquatic invertebrate and vertebrate animals (10,534 observations worldwide). MTE variables (body size, temperature) performed better than ES variables (trophic guild, vertebrate classification, body N:P) in predicting excretion rates, but the best models included variables from both frameworks. Size scaling coefficients were significantly lower than predicted by MTE (<0.75), were lower for P than N, and varied greatly among species. Contrary to expectations under ES, vertebrates excreted both N and P at higher rates than invertebrates despite having more nutrient-rich bodies, and primary consumers excreted as much nutrients as carnivores despite having nutrient-poor diets. Accounting for body N:P hardly improved upon predictions from treating vertebrate classification categorically. We conclude that basic data on body size, water temperature, trophic guild, and vertebrate classification are sufficient to make general estimates of nutrient excretion rates for any animal taxon or aquatic ecosystem. Nonetheless, dramatic interspecific variation in size-scaling coefficients and counter-intuitive patterns with respect to diet and body composition underscore the need for field data on consumption and egestion rates. Together, MTE and ES provide a powerful conceptual basis for interpreting and predicting nutrient recycling rates of aquatic animals worldwide. © 2016 by the Ecological Society of America.

Is laughter a better vocal change detector than a growl?

PubMed

Pinheiro, Ana P; Barros, Carla; Vasconcelos, Margarida; Obermeier, Christian; Kotz, Sonja A

2017-07-01

The capacity to predict what should happen next and to minimize any discrepancy between an expected and an actual sensory input (prediction error) is a central aspect of perception. Particularly in vocal communication, the effective prediction of an auditory input that informs the listener about the emotionality of a speaker is critical. What is currently unknown is how the perceived valence of an emotional vocalization affects the capacity to predict and detect a change in the auditory input. This question was probed in a combined event-related potential (ERP) and time-frequency analysis approach. Specifically, we examined the brain response to standards (Repetition Positivity) and to deviants (Mismatch Negativity - MMN), as well as the anticipatory response to the vocal sounds (pre-stimulus beta oscillatory power). Short neutral, happy (laughter), and angry (growls) vocalizations were presented both as standard and deviant stimuli in a passive oddball listening task while participants watched a silent movie and were instructed to ignore the vocalizations. MMN amplitude was increased for happy compared to neutral and angry vocalizations. The Repetition Positivity was enhanced for happy standard vocalizations. Induced pre-stimulus upper beta power was increased for happy vocalizations, and predicted the modulation of the standard Repetition Positivity. These findings indicate enhanced sensory prediction for positive vocalizations such as laughter. Together, the results suggest that positive vocalizations are more effective predictors in social communication than angry and neutral ones, possibly due to their high social significance. Copyright © 2017 Elsevier Ltd. All rights reserved.

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

Radon emissions from natural gas power plants at The Pennsylvania State University.

PubMed

Stidworthy, Alison G; Davis, Kenneth J; Leavey, Jeff

2016-11-01

Burning natural gas in power plants may emit radon ( 222 Rn) into the atmosphere. On the University Park campus of The Pennsylvania State University, atmospheric radon enhancements were measured and modeled in the vicinity of their two power plants. The three-part study first involved measuring ambient outdoor radon concentrations from August 2014 through January 2015 at four sites upwind and downwind of the power plants at distances ranging from 80 m to 310 m. For each plant, one site served as a background site, while three other sites measured radon concentration enhancements downwind. Second, the radon content of natural gas flowing into the power plant was measured, and third, a plume dispersion model was used to predict the radon concentrations downwind of the power plants. These predictions are compared to the measured downwind enhancements in radon to determine whether the observed radon concentration enhancements could be attributed to the power plants' emissions. Atmospheric radon concentrations were consistently low as compared to the EPA action level of 148 Bq m -3 , averaging 34.5 ± 2.7 Bq m -3 around the East Campus Steam Plant (ECSP) and 31.6 ± 2.7 Bq m -3 around the West Campus Steam Plant (WCSP). Significant concentrations of radon, ranging from 516 to 1,240 Bq m -3 , were detected in the natural gas. The measured enhancements downwind of the ECSP averaged 6.2 Bq m -3 compared to modeled enhancements of 0.08 Bq m -3 . Measured enhancements around the WCSP averaged -0.2 Bq m -3 compared to the modeled enhancements of 0.05 Bq m -3 , which were not significant compared to observational error. The comparison of the measured to modeled downwind radon enhancements shows no correlation over time. The measurements of radon levels in the vicinity of the power plants appear to be unaffected by the emissions from the power plants. Radon measurements at sites surrounding power plants that utilize natural gas did not indicate that the radon concentrations originated from the plants' emissions. There were elevated radon concentrations in the natural gas supply flowing into the power plants, but combustion dilution puts the concentration below EPA action levels coming out of the stack, so no hazardous levels were expected downwind. Power plant combustion of natural gas is not likely to pose a radiation health hazard unless very different gas radon concentrations or combustion dilution ratios are encountered.

Supporting Disaster Assessment and Response with the VIIRS Day-Night Band

NASA Technical Reports Server (NTRS)

Schultz, Lori A.; Cole, Tony; Molthan, Andrew L.

2015-01-01

When meteorological or man-made disasters occur, first responders often focus on impacts to the affected population and other human activities. Often, these disasters result in significant impacts to local infrastructure and power, resulting in widespread power outages. For minor events, these power outages are often short-lived, but major disasters often include long-term outages that have a significant impact on wellness, safety, and recovery efforts within the affected areas. Staff at NASA's Short-term Prediction Research and Transition (SPoRT) Center have been investigating the use of the VIIRS day-night band for monitoring power outages that result from significant disasters, and developing techniques to identify damaged areas in near real-time following events. In addition to immediate assessment, the VIIRS DNB can be used to monitor and assess ongoing recovery efforts. In this presentation, we will highlight previous applications of the VIIRS DNB following Superstorm Sandy in 2012, and other applications of the VIIRS DNB to more recent disaster events, including detection of outages following the Moore, Oklahoma tornado of May 2013 and the Chilean earthquake of April 2014. Examples of current products will be shown, along with future work and other goals for supporting disaster assessment and response with VIIRS capabilities.

Developing a comprehensive training curriculum for integrated predictive maintenance

NASA Astrophysics Data System (ADS)

Wurzbach, Richard N.

2002-03-01

On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of key technologies such as vibration analysis, infrared thermography, and oil analysis not as singular entities, but as a toolbox resource from which to address overall equipment and plant reliability in a structured program and decision environment.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Using Bayes to get the most out of non-significant results.

PubMed

Dienes, Zoltan

2014-01-01

No scientific conclusion follows automatically from a statistically non-significant result, yet people routinely use non-significant results to guide conclusions about the status of theories (or the effectiveness of practices). To know whether a non-significant result counts against a theory, or if it just indicates data insensitivity, researchers must use one of: power, intervals (such as confidence or credibility intervals), or else an indicator of the relative evidence for one theory over another, such as a Bayes factor. I argue Bayes factors allow theory to be linked to data in a way that overcomes the weaknesses of the other approaches. Specifically, Bayes factors use the data themselves to determine their sensitivity in distinguishing theories (unlike power), and they make use of those aspects of a theory's predictions that are often easiest to specify (unlike power and intervals, which require specifying the minimal interesting value in order to address theory). Bayes factors provide a coherent approach to determining whether non-significant results support a null hypothesis over a theory, or whether the data are just insensitive. They allow accepting and rejecting the null hypothesis to be put on an equal footing. Concrete examples are provided to indicate the range of application of a simple online Bayes calculator, which reveal both the strengths and weaknesses of Bayes factors.

New Computational Methods for the Prediction and Analysis of Helicopter Noise

NASA Technical Reports Server (NTRS)

Strawn, Roger C.; Oliker, Leonid; Biswas, Rupak

1996-01-01

This paper describes several new methods to predict and analyze rotorcraft noise. These methods are: 1) a combined computational fluid dynamics and Kirchhoff scheme for far-field noise predictions, 2) parallel computer implementation of the Kirchhoff integrations, 3) audio and visual rendering of the computed acoustic predictions over large far-field regions, and 4) acoustic tracebacks to the Kirchhoff surface to pinpoint the sources of the rotor noise. The paper describes each method and presents sample results for three test cases. The first case consists of in-plane high-speed impulsive noise and the other two cases show idealized parallel and oblique blade-vortex interactions. The computed results show good agreement with available experimental data but convey much more information about the far-field noise propagation. When taken together, these new analysis methods exploit the power of new computer technologies and offer the potential to significantly improve our prediction and understanding of rotorcraft noise.

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.

Noninvasive prediction of shunt operation outcome in idiopathic normal pressure hydrocephalus

PubMed Central

Aoki, Yasunori; Kazui, Hiroaki; Tanaka, Toshihisa; Ishii, Ryouhei; Wada, Tamiki; Ikeda, Shunichiro; Hata, Masahiro; Canuet, Leonides; Katsimichas, Themistoklis; Musha, Toshimitsu; Matsuzaki, Haruyasu; Imajo, Kaoru; Kanemoto, Hideki; Yoshida, Tetsuhiko; Nomura, Keiko; Yoshiyama, Kenji; Iwase, Masao; Takeda, Masatoshi

2015-01-01

Idiopathic normal pressure hydrocephalus (iNPH) is a syndrome characterized by gait disturbance, cognitive deterioration and urinary incontinence in elderly individuals. These symptoms can be improved by shunt operation in some but not all patients. Therefore, discovering predictive factors for the surgical outcome is of great clinical importance. We used normalized power variance (NPV) of electroencephalography (EEG) waves, a sensitive measure of the instability of cortical electrical activity, and found significantly higher NPV in beta frequency band at the right fronto-temporo-occipital electrodes (Fp2, T4 and O2) in shunt responders compared to non-responders. By utilizing these differences, we were able to correctly identify responders and non-responders to shunt operation with a positive predictive value of 80% and a negative predictive value of 88%. Our findings indicate that NPV can be useful in noninvasively predicting the clinical outcome of shunt operation in patients with iNPH. PMID:25585705

The relationship of plasma miR-503 and coronary collateral circulation in patients with coronary artery disease.

PubMed

Fei, Yu; Hou, Jianhua; Xuan, Wei; Zhang, Chenghua; Meng, Xiuping

2018-06-02

Although angiogenesis plays an important role in coronary collateral circulation (CCC) formation and there are many determinants of coronary angiogenesis, they cannot fully explain the mechanism of CCC formation or as potent biomarker for CCC status. Therefore, there is of great clinical significance to identify the novel molecules associated with CCC. Previously, miR-503 exerts anti-angiogenesis effect via inhibition of VEGF-A and its expression is associated with many angiogenesis-related factors. Thus, we aimed to investigate the relationship of plasma miR-503 with CCC formation as well as its predictive power for CCC status in patients with coronary artery disease. Among patients who underwent coronary angiography with coronary artery disease and a stenosis of ≥90% were included in our study. Collateral degree was graded according to Rentrop Cohen classification. The patients were divided to good CCC group (grade 2 or 3) and poor CCC group (grade 0 or 1) according to Rentrop grade. We investigated the plasma levels of miR-503 and VEGF-A by ELISA or q RT-PCR, respectively. In addition, we assayed the correlations of plasma miR-503 with VEGF-A or Rentrop grade using the spearman correlation test and its predictive power by receiver operating characteristic (ROC) and binary logistical regression analysis. Our data showed that plasma VEGF-A was significantly higher in good CCC group than that in poor group. Plasma miR-503 was lower in CAD patients with good CCC or poor CCC compared with control subjects and lowest in good CCC group. In addition, miR-503 negatively correlated with VEGF-A and Rentrop grade, respectively. Moreover, miR-503 displayed more potent predictive power for CCC status than VEGF-A, but its sensitivity and specificity for CCC status were only 72.4 or 60.9%, respectively. Lower plasma miR-503 level was related to better CCC formation, accompanied by up-regulation of VEGF-A. In addition, miR-503 displayed potent predictive power for CCC status, but its sensitivity and specificity were not high enough, indicating that miR-503 might be as an additional prognosis biomarker for CCC. Copyright © 2017. Published by Elsevier Inc.

Forecasting Electric Power Generation of Photovoltaic Power System for Energy Network

NASA Astrophysics Data System (ADS)

Kudo, Mitsuru; Takeuchi, Akira; Nozaki, Yousuke; Endo, Hisahito; Sumita, Jiro

Recently, there has been an increase in concern about the global environment. Interest is growing in developing an energy network by which new energy systems such as photovoltaic and fuel cells generate power locally and electric power and heat are controlled with a communications network. We developed the power generation forecast method for photovoltaic power systems in an energy network. The method makes use of weather information and regression analysis. We carried out forecasting power output of the photovoltaic power system installed in Expo 2005, Aichi Japan. As a result of comparing measurements with a prediction values, the average prediction error per day was about 26% of the measured power.

FOUR Score Predicts Early Outcome in Patients After Traumatic Brain Injury.

PubMed

Nyam, Tee-Tau Eric; Ao, Kam-Hou; Hung, Shu-Yu; Shen, Mei-Li; Yu, Tzu-Chieh; Kuo, Jinn-Rung

2017-04-01

The aim of the study was to determine whether the Full Outline of UnResponsiveness (FOUR) score, which includes eyes opening (E), motor function (M), brainstem reflex (B), and respiratory pattern (R), can be used as an alternate method to the Glasgow Coma Scale (GCS) in predicting intensive care unit (ICU) mortality in traumatic brain injury (TBI) patients. From January 2015 to June 2015, patients with isolated TBI admitted to the ICU were enrolled. Three advanced practice nurses administered the FOUR score, GCS, Acute Physiology and Chronic Health Evaluation II (APACHE II), and Therapeutic Intervention Scoring System (TISS) concurrently from ICU admissions. The endpoint of observation was mortality when the patients left the ICU. Data are presented as frequency with percentages, mean with standard deviation, or median with interquartile range. Each measurement tool used area under the receiver operating characteristic curve to compare the predictive power between these four tools. In addition, the difference between survival and death was estimated using the Wilcoxon rank sum test. From 55 TBI patients, males (72.73 %) were represented more than females, the mean age was 63.1 ± 17.9, and 19 of 55 observations (35 %) had a maximum FOUR score of 16. The overall mortality rate was 14.6 %. The area under the receiver operating characteristic curve was 74.47 % for the FOUR score, 74.73 % for the GCS, 81.78 % for the APACHE II, and 53.32 % for the TISS. The FOUR score has similar predictive power of mortality compared to the GCS and APACHE II. Each of the parameters-E, M, B, and R-of the FOUR score showed a significant difference between mortality and survival group, while the verbal and eye-opening components of the GCS did not. Having similar predictive power of mortality compared to the GCS and APACHE II, the FOUR score can be used as an alternative in the prediction of early mortality in TBI patients in the ICU.

SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE.

PubMed

Docherty, A R; Moscati, A; Peterson, R; Edwards, A C; Adkins, D E; Bacanu, S A; Bigdeli, T B; Webb, B T; Flint, J; Kendler, K S

2016-10-25

Biometrical genetic studies suggest that the personality dimensions, including neuroticism, are moderately heritable (~0.4 to 0.6). Quantitative analyses that aggregate the effects of many common variants have recently further informed genetic research on European samples. However, there has been limited research to date on non-European populations. This study examined the personality dimensions in a large sample of Han Chinese descent (N=10 064) from the China, Oxford, and VCU Experimental Research on Genetic Epidemiology study, aimed at identifying genetic risk factors for recurrent major depression among a rigorously ascertained cohort. Heritability of neuroticism as measured by the Eysenck Personality Questionnaire (EPQ) was estimated to be low but statistically significant at 10% (s.e.=0.03, P=0.0001). In addition to EPQ, neuroticism based on a three-factor model, data for the Big Five (BF) personality dimensions (neuroticism, openness, conscientiousness, extraversion and agreeableness) measured by the Big Five Inventory were available for controls (n=5596). Heritability estimates of the BF were not statistically significant despite high power (>0.85) to detect heritabilities of 0.10. Polygenic risk scores constructed by best linear unbiased prediction weights applied to split-half samples failed to significantly predict any of the personality traits, but polygenic risk for neuroticism, calculated with LDpred and based on predictive variants previously identified from European populations (N=171 911), significantly predicted major depressive disorder case-control status (P=0.0004) after false discovery rate correction. The scores also significantly predicted EPQ neuroticism (P=6.3 × 10 -6 ). Factor analytic results of the measures indicated that any differences in heritabilities across samples may be due to genetic variation or variation in haplotype structure between samples, rather than measurement non-invariance. Findings demonstrate that neuroticism can be significantly predicted across ancestry, and highlight the importance of studying polygenic contributions to personality in non-European populations.

Initial Assessment of the Risk Assessment and Prediction Tool in a Heterogeneous Neurosurgical Patient Population.

PubMed

Piazza, Matthew; Sharma, Nikhil; Osiemo, Benjamin; McClintock, Scott; Missimer, Emily; Gardiner, Diana; Maloney, Eileen; Callahan, Danielle; Smith, J Lachlan; Welch, William; Schuster, James; Grady, M Sean; Malhotra, Neil R

2018-05-21

Bundled care payments are increasingly being explored for neurosurgical interventions. In this setting, skilled nursing facility (SNF) is less desirable from a cost perspective than discharge to home, underscoring the need for better preoperative prediction of postoperative disposition. To assess the capability of the Risk Assessment and Prediction Tool (RAPT) and other preoperative variables to determine expected disposition prior to surgery in a heterogeneous neurosurgical cohort, through observational study. Patients aged 50 yr or more undergoing elective neurosurgery were enrolled from June 2016 to February 2017 (n = 623). Logistic regression was used to identify preoperative characteristics predictive of discharge disposition. Results from multivariate analysis were used to create novel grading scales for the prediction of discharge disposition that were subsequently compared to the RAPT Score using Receiver Operating Characteristic analysis. Higher RAPT Score significantly predicted home disposition (P < .001). Age 65 and greater, dichotomized RAPT walk score, and spinal surgery below L2 were independent predictors of SNF discharge in multivariate analysis. A grading scale utilizing these variables had superior discriminatory power between SNF and home/rehab discharge when compared with RAPT score alone (P = .004). Our analysis identified age, lower lumbar/lumbosacral surgery, and RAPT walk score as independent predictors of discharge to SNF, and demonstrated superior predictive power compared with the total RAPT Score when combined in a novel grading scale. These tools may identify patients who may benefit from expedited discharge to subacute care facilities and decrease inpatient hospital resource utilization following surgery.

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

PubMed

Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

2018-05-10

Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

Non-Dimensional Formulation of Ventricular Work-Load Severity Under Concomitant Heart Valve Disease

NASA Astrophysics Data System (ADS)

Dong, Melody; Simon-Walker, Rachael; Dasi, Lakshmi

2012-11-01

Current guidelines on assessing the severity of heart valve disease rely on dimensional disease specific measures and are thus unable to capture severity under a concomitant heart valve disease scenario. Experiments were conducted to measure ventricular work-load in an in-house in-vitro left heart simulator. In-house tri-leaflet heart valves were built and parameterized to model concomitant heart valve disease. Measured ventricular power varied non-linearly with cardiac output and mean aortic pressure. Significant data collapse could be achieved by the non-dimensionalization of ventricular power with cardiac output, fluid density, and a length scale. The dimensionless power, Circulation Energy Dissipation Index (CEDI), indicates that concomitant conditions require a significant increase in the amount of work needed to sustain cardiac function. It predicts severity without the need to quantify individual disease severities. This indicates the need for new fluid-dynamics similitude based clinical guidelines to assist patients with multiple heart valve diseases. Funded by the American Heart Association.

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

NASA Astrophysics Data System (ADS)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer.

PubMed

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Chang, Shu-Shya; Rau, Cheng-Shyuan; Tai, Hsueh-Ling; Peng, Shu-Hui; Lin, Yi-Chun; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-03-02

The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR). There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score. ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P <0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance. The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer.

Balancing computation and communication power in power constrained clusters

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

Piga, Leonardo; Paul, Indrani; Huang, Wei

Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agentmore » may be configured to reassign the unused power to the active nodes to expedite workload processing.« less

Differences in participation based on self-esteem in power and manual wheelchair users on a university campus: a pilot study.

PubMed

Rice, Ian M; Wong, Alex W K; Salentine, Benjamin A; Rice, Laura A

2015-03-01

To examine the relationship of self-esteem and wheelchair type with participation of young adult manual and power wheelchair users with diverse physical disabilities. Cross-sectional survey study. Large University Campus. A convenience sample of college students (N = 39) with self-reported physical disabilities who are full time wheelchair users (>40 per week) and are two or more years post illness or injury. Not applicable. The Rosenberg Self-Esteem Scale was used to measure self-esteem, and the Craig Handicap Assessment and Reporting Technique was used to measure participation. Self-esteem correlated highly with cognitive independence (CI) (r = 0.58), mobility (r = 0.67) and social integration (SI) (r = 0.52). Use of manual wheelchair was significantly related to higher levels of CI and mobility while longer use of any wheelchair (power or manual) was significantly associated with higher levels of mobility and SI. In addition higher self-esteem independently predicted a significant proportion of the variance in CI, mobility and SI, while type of wheelchair predicted a significant proportion of the variance in CI (p < 0.005). High self-esteem was found to be the strongest predictor of participation in a population of young adults with mobility limitations. Better understanding of the factors influencing participation may help to facilitate new interventions to minimize the disparities between persons with disabilities and their able bodied peers. Implication for Rehabilitation A total of 46.8% of wheelchair users report the desire for increased community participant but face significant barriers. The type of wheelchair has been identified as having a large impact on participation. This study found self-esteem to be the strongest predictor of participation, which is notable because self-esteem is a characteristic that is potentially modifiable with treatment.

Modeling of a resonant heat engine

NASA Astrophysics Data System (ADS)

Preetham, B. S.; Anderson, M.; Richards, C.

2012-12-01

A resonant heat engine in which the piston assembly is replaced by a sealed elastic cavity is modeled and analyzed. A nondimensional lumped-parameter model is derived and used to investigate the factors that control the performance of the engine. The thermal efficiency predicted by the model agrees with that predicted from the relation for the Otto cycle based on compression ratio. The predictions show that for a fixed mechanical load, increasing the heat input results in increased efficiency. The output power and power density are shown to depend on the loading for a given heat input. The loading condition for maximum output power is different from that required for maximum power density.

Synchrophasor-Assisted Prediction of Stability/Instability of a Power System

NASA Astrophysics Data System (ADS)

Saha Roy, Biman Kumar; Sinha, Avinash Kumar; Pradhan, Ashok Kumar

2013-05-01

This paper presents a technique for real-time prediction of stability/instability of a power system based on synchrophasor measurements obtained from phasor measurement units (PMUs) at generator buses. For stability assessment the technique makes use of system severity indices developed using bus voltage magnitude obtained from PMUs and generator electrical power. Generator power is computed using system information and PMU information like voltage and current phasors obtained from PMU. System stability/instability is predicted when the indices exceeds a threshold value. A case study is carried out on New England 10-generator, 39-bus system to validate the performance of the technique.

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.

Internal exposure dynamics drive the Adverse Outcome Pathways of synthetic glucocorticoids in fish

NASA Astrophysics Data System (ADS)

Margiotta-Casaluci, Luigi; Owen, Stewart F.; Huerta, Belinda; Rodríguez-Mozaz, Sara; Kugathas, Subramanian; Barceló, Damià; Rand-Weaver, Mariann; Sumpter, John P.

2016-02-01

The Adverse Outcome Pathway (AOP) framework represents a valuable conceptual tool to systematically integrate existing toxicological knowledge from a mechanistic perspective to facilitate predictions of chemical-induced effects across species. However, its application for decision-making requires the transition from qualitative to quantitative AOP (qAOP). Here we used a fish model and the synthetic glucocorticoid beclomethasone dipropionate (BDP) to investigate the role of chemical-specific properties, pharmacokinetics, and internal exposure dynamics in the development of qAOPs. We generated a qAOP network based on drug plasma concentrations and focused on immunodepression, skin androgenisation, disruption of gluconeogenesis and reproductive performance. We showed that internal exposure dynamics and chemical-specific properties influence the development of qAOPs and their predictive power. Comparing the effects of two different glucocorticoids, we highlight how relatively similar in vitro hazard-based indicators can lead to different in vivo risk. This discrepancy can be predicted by their different uptake potential, pharmacokinetic (PK) and pharmacodynamic (PD) profiles. We recommend that the development phase of qAOPs should include the application of species-species uptake and physiologically-based PK/PD models. This integration will significantly enhance the predictive power, enabling a more accurate assessment of the risk and the reliable transferability of qAOPs across chemicals.

An Operating Method Using Prediction of Photovoltaic Power for a Photovoltaic-Diesel Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Yamamoto, Shigehiro; Sumi, Kazuyoshi; Nishikawa, Eiichi; Hashimoto, Takeshi

This paper describes a novel operating method using prediction of photovoltaic (PV) power for a photovoltaic-diesel hybrid power generation system. The system is composed of a PV array, a storage battery, a bi-directional inverter and a diesel engine generator (DG). The proposed method enables the system to save fuel consumption by using PV energy effectively, reducing charge and discharge energy of the storage battery, and avoiding low-load operation of the DG. The PV power is simply predicted from a theoretical equation of solar radiation and the observed PV energy for a constant time before the prediction. The amount of fuel consumption of the proposed method is compared with that of other methods by a simulation based on measurement data of the PV power at an actual PV generation system for one year. The simulation results indicate that the amount of fuel consumption of the proposed method is smaller than that of any other methods, and is close to that of the ideal operation of the DG.

A Comparison between Bench Press Throw and Ballistic Push-Up tests to assess upper-body power in trained individuals.

PubMed

Bartolomei, Sandro; Nigro, Federico; Ruggeri, Sandro; Lanzoni, Ivan Malagoli; Ciacci, Simone; Merni, Franco; Sadres, Eliahu; Hoffman, Jay R; Semprini, Gabriele

2018-03-06

The purpose of the present study was to validate the ballistic push-up test performed with hands on a force plate (BPU) as a method to measure upper-body power. Twenty-eight experienced resistance trained men (age = 25.4 ± 5.2 y; body mass = 78.5 ± 9.0 kg; body height = 179.6 ± 7.8 cm) performed, two days apart, a bench press 1RM test and upper-body power tests. Mean power and peak power were assessed using the bench press throw test (BT) and the BPU test performed in randomized order. The area under the force/power curve (AUC) obtained at BT was also calculated. Power expressed at BPU was estimated using a time-based prediction equation. Mean force and the participant's body weight were used to predict the bench press 1RM. Pearson product moment correlations were used to examine relationships between the power assessment methods and between the predicted 1RM bench and the actual value. Large correlations (0.79; p < 0.001) were found between AUC and mean power expressed at BPU. Large correlations were also detected between mean power and peak power expressed at BT and BPU (0.75; p < 0.001 and 0.74; p < 0.001, respectively). Very large correlations (0.87; p < 0.001) were found between the 1RM bench and the 1RM predicted by the BPU. Results of the present study indicate that BPU represents a valid and reliable method to estimate the upper-body power in resistance-trained individuals.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation.

PubMed

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-08-01

The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient ( P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation

PubMed Central

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-01-01

Background and Aims: The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. Materials and Methods: In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. Results: The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient (P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). Conclusion: The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning. PMID:28904477

A cross-national analysis of how economic inequality predicts biodiversity loss.

PubMed

Holland, Tim G; Peterson, Garry D; Gonzalez, Andrew

2009-10-01

We used socioeconomic models that included economic inequality to predict biodiversity loss, measured as the proportion of threatened plant and vertebrate species, across 50 countries. Our main goal was to evaluate whether economic inequality, measured as the Gini index of income distribution, improved the explanatory power of our statistical models. We compared four models that included the following: only population density, economic footprint (i.e., the size of the economy relative to the country area), economic footprint and income inequality (Gini index), and an index of environmental governance. We also tested the environmental Kuznets curve hypothesis, but it was not supported by the data. Statistical comparisons of the models revealed that the model including both economic footprint and inequality was the best predictor of threatened species. It significantly outperformed population density alone and the environmental governance model according to the Akaike information criterion. Inequality was a significant predictor of biodiversity loss and significantly improved the fit of our models. These results confirm that socioeconomic inequality is an important factor to consider when predicting rates of anthropogenic biodiversity loss.

Predicting Attitudes toward Press- and Speech Freedom across the U.S.A.: A Test of Climato-Economic, Parasite Stress, and Life History Theories

PubMed Central

Zhang, Jinguang; Reid, Scott A.; Xu, Jing

2015-01-01

National surveys reveal notable individual differences in U.S. citizens’ attitudes toward freedom of expression, including freedom of the press and speech. Recent theoretical developments and empirical findings suggest that ecological factors impact censorship attitudes in addition to individual difference variables (e.g., education, conservatism), but no research has compared the explanatory power of prominent ecological theories. This study tested climato-economic, parasite stress, and life history theories using four measures of attitudes toward censoring the press and offensive speech obtained from two national surveys in the U.S.A. Neither climate demands nor its interaction with state wealth—two key variables for climato-economic theory—predicted any of the four outcome measures. Interstate parasite stress significantly predicted two, with a marginally significant effect on the third, but the effects became non-significant when the analyses were stratified for race (as a control for extrinsic risks). Teenage birth rates (a proxy of human life history) significantly predicted attitudes toward press freedom during wartime, but the effect was the opposite of what life history theory predicted. While none of the three theories provided a fully successful explanation of individual differences in attitudes toward freedom of expression, parasite stress and life history theories do show potentials. Future research should continue examining the impact of these ecological factors on human psychology by further specifying the mechanisms and developing better measures for those theories. PMID:26030736

Predicting Attitudes toward Press- and Speech Freedom across the U.S.A.: A Test of Climato-Economic, Parasite Stress, and Life History Theories.

PubMed

Zhang, Jinguang; Reid, Scott A; Xu, Jing

2015-01-01

National surveys reveal notable individual differences in U.S. citizens' attitudes toward freedom of expression, including freedom of the press and speech. Recent theoretical developments and empirical findings suggest that ecological factors impact censorship attitudes in addition to individual difference variables (e.g., education, conservatism), but no research has compared the explanatory power of prominent ecological theories. This study tested climato-economic, parasite stress, and life history theories using four measures of attitudes toward censoring the press and offensive speech obtained from two national surveys in the U.S.A. Neither climate demands nor its interaction with state wealth--two key variables for climato-economic theory--predicted any of the four outcome measures. Interstate parasite stress significantly predicted two, with a marginally significant effect on the third, but the effects became non-significant when the analyses were stratified for race (as a control for extrinsic risks). Teenage birth rates (a proxy of human life history) significantly predicted attitudes toward press freedom during wartime, but the effect was the opposite of what life history theory predicted. While none of the three theories provided a fully successful explanation of individual differences in attitudes toward freedom of expression, parasite stress and life history theories do show potentials. Future research should continue examining the impact of these ecological factors on human psychology by further specifying the mechanisms and developing better measures for those theories.

The skew ray ambiguity in the analysis of videokeratoscopic data.

PubMed

Iskander, D Robert; Davis, Brett A; Collins, Michael J

2007-05-01

Skew ray ambiguity is present in most videokeratoscopic measurements when azimuthal components of the corneal curvature are not taken into account. There have been some reported studies based on theoretical predictions and measured test surfaces suggesting that skew ray ambiguity is significant for highly deformed corneas or decentered corneal measurements. However, the effect of skew ray ambiguity in ray tracing through videokeratoscopic data has not been studied in depth. We have evaluated the significance of the skew ray ambiguity and its effect on the analyzed corneal optics. This has been achieved by devising a procedure in which we compared the corneal wavefront aberrations estimated from 3D ray tracing with those determined from 2D (meridional based) estimates of the refractive power. The latter was possible due to recently developed concept of refractive Zernike power polynomials which links the refractive power domain with that of the wavefront. Simulated corneal surfaces as well as data from a range of corneas (from two different Placido disk-based videokeratoscopes) were used to find the limit at which the difference in estimated corneal wavefronts (or the corresponding refractive powers) would have clinical significance (e.g., equivalent to 0.125 D or more). The inclusion/exclusion of the skew ray in the analyses showed some differences in the results. However, the proposed procedure showed clinically significant differences only for highly deformed corneas and only for large corneal diameters. For the overwhelming majority of surfaces, the skew ray ambiguity is not a clinically significant issue in the analysis of the videokeratoscopic data indicating that the meridional processing such as that encountered in calculation of the refractive power maps is adequate.

Lead optimization using matched molecular pairs: inclusion of contextual information for enhanced prediction of HERG inhibition, solubility, and lipophilicity.

PubMed

Papadatos, George; Alkarouri, Muhammad; Gillet, Valerie J; Willett, Peter; Kadirkamanathan, Visakan; Luscombe, Christopher N; Bravi, Gianpaolo; Richmond, Nicola J; Pickett, Stephen D; Hussain, Jameed; Pritchard, John M; Cooper, Anthony W J; Macdonald, Simon J F

2010-10-25

Previous studies of the analysis of molecular matched pairs (MMPs) have often assumed that the effect of a substructural transformation on a molecular property is independent of the context (i.e., the local structural environment in which that transformation occurs). Experiments with large sets of hERG, solubility, and lipophilicity data demonstrate that the inclusion of contextual information can enhance the predictive power of MMP analyses, with significant trends (both positive and negative) being identified that are not apparent when using conventional, context-independent approaches.

The Power of the Pygmalion Effect: Teachers' Expectations Strongly Predict College Completion

ERIC Educational Resources Information Center

Boser, Ulrich; Wilhelm, Megan; Hanna, Robert

2014-01-01

People do better when more is expected of them. In education circles, this is called the Pygmalion Effect. It has been demonstrated in study after study, and the results can sometimes be quite significant. In one research project, for instance, teacher expectations of a pre-schooler's ability was a robust predictor of the child's high school GPA.…

Value of Combining Left Atrial Diameter and Amino-terminal Pro-brain Natriuretic Peptide to the CHA2DS2-VASc Score for Predicting Stroke and Death in Patients with Sick Sinus Syndrome after Pacemaker Implantation.

PubMed

Mo, Bin-Feng; Lu, Qiu-Fen; Lu, Shang-Biao; Xie, Yu-Quan; Feng, Xiang-Fei; Li, Yi-Gang

2017-08-20

The CHA2DS2-VASc score is used clinically for stroke risk stratification in patients with atrial fibrillation (AF). We sought to investigate whether the CHA2DS2-VASc score predicts stroke and death in Chinese patients with sick sinus syndrome (SSS) after pacemaker implantation and to evaluate whether the predictive power of the CHA2DS2-VASc score could be improved by combining it with left atrial diameter (LAD) and amino-terminal pro-brain natriuretic peptide (NT-proBNP). A total of 481 consecutive patients with SSS who underwent pacemaker implantation from January 2004 to December 2014 in our department were included. The CHA2DS2-VASc scores were retrospectively calculated according to the hospital medical records before pacemaker implantation. The outcome data (stroke and death) were collected by pacemaker follow-up visits and telephonic follow-up until December 31, 2015. During 2151 person-years of follow-up, 46 patients (9.6%) suffered stroke and 52 (10.8%) died. The CHA2DS2-VASc score showed a significant association with the development of stroke (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.20-1.75, P< 0.001) and death (HR 1.45, 95% CI 1.22-1.71, P< 0.001). The combination of increased LAD and the CHA2DS2-VASc score improved the predictive power for stroke (C-stat 0.69, 95% CI 0.61-0.77 vs. C-stat 0.66, 95% CI 0.57-0.74, P= 0.013), and the combination of increased NT-proBNP and the CHA2DS2-VASc score improved the predictive power for death (C-stat 0.70, 95% CI 0.64-0.77 vs. C-stat 0.67, 95% CI 0.60--0.75, P= 0.023). CHA2DS2-VASc score is valuable for predicting stroke and death risk in patients with SSS after pacemaker implantation. The addition of LAD and NT-proBNP to the CHA2DS2-VASc score improved its predictive power for stroke and death, respectively, in this patient cohort. Future prospective studies are warranted to validate the benefit of adding LAD and NT-proBNP to the CHA2DS2-VASc score for predicting stroke and death risk in non-AF populations.

Comparison of Parallel and Series Hybrid Power Trains for Transit Bus Applications

DOE PAGES

Gao, Zhiming; Daw, C. Stuart; Smith, David E.; ...

2016-08-01

The fuel economy and emissions of conventional and hybrid buses equipped with emissions after treatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicated that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar carbon monoxide and hydrocarbon tailpipe emissions but were also predicted to have reduced tailpipe emissions of nitrogen oxides compared with the conventional bus in higher speed cycles. For the New York bus cycle, which hasmore » the lowest average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus; the parallel hybrid bus had significantly lower tailpipe emissions. All three bus power trains were found to require periodic active diesel particulate filter regeneration to maintain control of particulate matter. Finally, plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed because of the relatively large battery capacity that is typical of the series hybrid configuration.« less

Comparison of Parallel and Series Hybrid Power Trains for Transit Bus Applications

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

Gao, Zhiming; Daw, C. Stuart; Smith, David E.

The fuel economy and emissions of conventional and hybrid buses equipped with emissions after treatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicated that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar carbon monoxide and hydrocarbon tailpipe emissions but were also predicted to have reduced tailpipe emissions of nitrogen oxides compared with the conventional bus in higher speed cycles. For the New York bus cycle, which hasmore » the lowest average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus; the parallel hybrid bus had significantly lower tailpipe emissions. All three bus power trains were found to require periodic active diesel particulate filter regeneration to maintain control of particulate matter. Finally, plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed because of the relatively large battery capacity that is typical of the series hybrid configuration.« less

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

PubMed

Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

2011-12-01

This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

Performance of Comorbidity, Risk Adjustment, and Functional Status Measures in Expenditure Prediction for Patients With Diabetes

PubMed Central

Maciejewski, Matthew L.; Liu, Chuan-Fen; Fihn, Stephan D.

2009-01-01

OBJECTIVE—To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. RESEARCH DESIGN AND METHODS—This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R2 statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. RESULTS—Administrative data–based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. CONCLUSIONS—Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed. PMID:18945927

Modeling chlorophyll-a and dissolved oxygen concentration in tropical floodplain lakes (Paraná River, Brazil).

PubMed

Rocha, R R A; Thomaz, S M; Carvalho, P; Gomes, L C

2009-06-01

The need for prediction is widely recognized in limnology. In this study, data from 25 lakes of the Upper Paraná River floodplain were used to build models to predict chlorophyll-a and dissolved oxygen concentrations. Akaike's information criterion (AIC) was used as a criterion for model selection. Models were validated with independent data obtained in the same lakes in 2001. Predictor variables that significantly explained chlorophyll-a concentration were pH, electrical conductivity, total seston (positive correlation) and nitrate (negative correlation). This model explained 52% of chlorophyll variability. Variables that significantly explained dissolved oxygen concentration were pH, lake area and nitrate (all positive correlations); water temperature and electrical conductivity were negatively correlated with oxygen. This model explained 54% of oxygen variability. Validation with independent data showed that both models had the potential to predict algal biomass and dissolved oxygen concentration in these lakes. These findings suggest that multiple regression models are valuable and practical tools for understanding the dynamics of ecosystems and that predictive limnology may still be considered a powerful approach in aquatic ecology.

Predictive validity of the Sødring Motor Evaluation of Stroke Patients (SMES).

PubMed

Wyller, T B; Sødring, K M; Sveen, U; Ljunggren, A E; Bautz-Holter, E

1996-12-01

The Sødring Motor Evaluation of Stroke Patients (SMES) has been developed as an instrument for the evaluation by physiotherapists of motor function and activities in stroke patients. The predictive validity of the instrument was studied in a consecutive sample of 93 acute stroke patients, assessed in the acute phase and after one year. The outcome measures were: survival, residence at home or in institution, the Barthel ADL index (dichotomized at 19/20), and the Frenchay Activities Index (FAI) (dichotomized at 9/10). The SMES, scored in the acute phase, demonstrated a marginally significant predictive power regarding survival, but was a highly significant predictor regarding the other outcomes. The adjusted odds ratio for a good versus a poor outcome for patients in the upper versus the lower tertile of the SMES arm subscore was 5.4 (95% confidence interval 0.9-59) for survival, 11.5 (2.1-88) for living at home, 86.3 (11-infinity) for a high Barthel score, and 31.4 (5.2-288) for a high FAI score. We conclude that SMES has high predictive validity.

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

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

Flueck, Alex

The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform formore » modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to model three­phase and single­ phase networks and devices.« less

Measured and predicted rotor performance for the SERI advanced wind turbine blades

NASA Astrophysics Data System (ADS)

Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

1992-02-01

Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

Magnetic storm effects in electric power systems and prediction needs

NASA Technical Reports Server (NTRS)

Albertson, V. D.; Kappenman, J. G.

1979-01-01

Geomagnetic field fluctuations produce spurious currents in electric power systems. These currents enter and exit through points remote from each other. The fundamental period of these currents is on the order of several minutes which is quasi-dc compared to the normal 60 Hz or 50 Hz power system frequency. Nearly all of the power systems problems caused by the geomagnetically induced currents result from the half-cycle saturation of power transformers due to simultaneous ac and dc excitation. The effects produced in power systems are presented, current research activity is discussed, and magnetic storm prediction needs of the power industry are listed.

The aerodynamic cost of flight in bats--comparing theory with measurement

NASA Astrophysics Data System (ADS)

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Breuer, Kenneth S.

2012-11-01

Aerodynamic theory has long been used to predict the aerodynamic power required for animal flight. However, even though the actuator disk model does not account for the flapping motion of a wing, it is used for lack of any better model. The question remains: how close are these predictions to reality? We designed a study to compare predicted aerodynamic power to measured power from the kinetic energy contained in the wake shed behind a bat flying in a wind tunnel. A high-accuracy displaced light-sheet stereo PIV system was used in the Trefftz plane to capture the wake behind four bats flown over a range of flight speeds (1-6m/s). The total power in the wake was computed from the wake vorticity and these estimates were compared with the power predicted using Pennycuick's model for bird flight as well as estimates derived from measurements of the metabolic cost of flight, previously acquired from the same individuals.

The Importance of Strength and Power on Key Performance Indicators in Elite Youth Soccer.

PubMed

Wing, Christopher E; Turner, Anthony N; Bishop, Chris J

2018-01-24

The purpose of this investigation was to examine the importance of strength and power in relation to key performance indicators (KPI's) within competitive soccer match play. This was achieved through using an experimental approach where fifteen subjects were recruited from a professional soccer club's scholarship squad during the 2013/14 season. Following anthropometric measures, power and strength were assessed across a range of tests which included the squat jump (SJ), countermovement jump (CMJ), 20 metre (m) sprint and arrowhead change of direction test. A predicted 1-repetition maximum (RM) was also obtained for strength by performing a 3RM test for both the back squat and bench press and a total score of athleticism (TSA) was provided by summing z-scores for all fitness tests together, providing one complete score for athleticism. Performance analysis data was collected during 16 matches for the following KPIs: passing, shooting, dribbling, tackling and heading. Alongside this, data concerning player ball involvements (touches) was recorded. Results showed that there was a significant correlation (p < 0.05) between CMJ (r = 0.80), SJ (r = 0.79) and TSA (r = 0.64) in relation to heading success. Similarly, a significant correlation (p < 0.05) between predicted 1RM squat strength and tackle success (r = 0.61). These data supports the notion that strength and power training are important to soccer performance, particularly when players are required to win duels of a physical nature. There were no other relationships found between the fitness data and the KPI's recorded during match play which may indicate that other aspects of player's development such as technical skill, cognitive function and sensory awareness are more important for soccer-specific performance.

A new method of power load prediction in electrification railway

NASA Astrophysics Data System (ADS)

Dun, Xiaohong

2018-04-01

Aiming at the character of electrification railway, the paper mainly studies the problem of load prediction in electrification railway. After the preprocessing of data, and the similar days are separated on the basis of its statistical characteristics. Meanwhile the accuracy of different methods is analyzed. The paper provides a new thought of prediction and a new method of accuracy of judgment for the load prediction of power system.

Thin-Slice Forecasts of Gubernatorial Elections

PubMed Central

Benjamin, Daniel J.; Shapiro, Jesse M.

2010-01-01

We showed 10-second, silent video clips of unfamiliar gubernatorial debates to a group of experimental participants and asked them to predict the election outcomes. The participants’ predictions explain more than 20 percent of the variation in the actual two-party vote share across the 58 elections in our study, and their importance survives a range of controls, including state fixed effects. In a horse race of alternative forecasting models, participants’ forecasts significantly outperform economic variables in predicting vote shares, and are comparable in predictive power to a measure of incumbency status. Participants’ forecasts seem to rest on judgments of candidates’ personal attributes (such as likeability), rather than inferences about candidates’ policy positions. Though conclusive causal inference is not possible in our context, our findings may be seen as suggestive evidence of a causal effect of candidate appeal on election outcomes. PMID:20431718

Quantitative property-property relationship (QPPR) approach in predicting flotation efficiency of chelating agents as mineral collectors.

PubMed

Natarajan, R; Nirdosh, I; Venuvanalingam, P; Ramalingam, M

2002-07-01

The QPPR approach has been used to model cupferrons as mineral collectors. Separation efficiencies (Es) of these chelating agents have been correlated with property parameters namely, log P, log Koc, substituent-constant sigma, Mullikan and ESP derived charges using multiple regression analysis. Es of substituted-cupferrons in the flotation of a uranium ore could be predicted within experimental error either by log P or log Koc and an electronic parameter. However, when a halo, methoxy or phenyl substituent was in para to the chelating group, experimental Es was greater than the predicted values. Inclusion of a Boolean type indicative parameter improved significantly the predictability power. This approach has been extended to 2-aminothiophenols that were used to float a zinc ore and the correlations were found to be reasonably good.

Prediction of clinical behaviour and treatment for cancers.

PubMed

Futschik, Matthias E; Sullivan, Mike; Reeve, Anthony; Kasabov, Nikola

2003-01-01

Prediction of clinical behaviour and treatment for cancers is based on the integration of clinical and pathological parameters. Recent reports have demonstrated that gene expression profiling provides a powerful new approach for determining disease outcome. If clinical and microarray data each contain independent information then it should be possible to combine these datasets to gain more accurate prognostic information. Here, we have used existing clinical information and microarray data to generate a combined prognostic model for outcome prediction for diffuse large B-cell lymphoma (DLBCL). A prediction accuracy of 87.5% was achieved. This constitutes a significant improvement compared to the previously most accurate prognostic model with an accuracy of 77.6%. The model introduced here may be generally applicable to the combination of various types of molecular and clinical data for improving medical decision support systems and individualising patient care.

Effect of walking velocity on hindlimb kinetics during stance in normal horses.

PubMed

Khumsap, S; Clayton, H M; Lanovaz, J L

2001-04-01

The objectives of this study were to measure the effect of walking velocity on net joint moments and joint powers in the hindlimb during stance and to use the data to predict these variables at different walking velocities. Videographic and force data were collected synchronously from 5 sound horses walking over a force plate at a range of velocities. Force and kinematic data from 56 trials were combined using an inverse dynamic solution to determine net joint moments and joint powers. Analysis by simple regression and correlation (P < 0.05, r2 > or = 0.30, r > 0.50) showed that, in early stance, there were significant velocity-dependent increases in the peak magnitudes of the following variables: extensor moment and positive power at the hip, flexor moment and positive power at the stifle, extensor moment, negative and positive power at the tarsus, and flexor moment and negative power at the fetlock. In late stance, there were significant velocity-dependent increases in the peak magnitudes of the following variables: flexor moment at the hip, negative power at the stifle and flexor moment and positive power at the tarsus. As velocity increased, the hip showed an increase in energy generation, whereas the tarsus showed increases in both energy generation and absorption. It is concluded that an increase in walking velocity is associated with increases in peak magnitudes of the net joint moments and joint powers in the hindlimb; and that energy generation at the hip makes the largest contribution to the increase in velocity.

Power Calculations to Select Instruments for Clinical Trial Secondary Endpoints. A Case Study of Instrument Selection for Post-Traumatic Stress Symptoms in Subjects with Acute Respiratory Distress Syndrome.

PubMed

Sjoding, Michael W; Schoenfeld, David A; Brown, Samuel M; Hough, Catherine L; Yealy, Donald M; Moss, Marc; Angus, Derek C; Iwashyna, Theodore J

2017-01-01

After the sample size of a randomized clinical trial (RCT) is set by the power requirement of its primary endpoint, investigators select secondary endpoints while unable to further adjust sample size. How the sensitivity and specificity of an instrument used to measure these outcomes, together with their expected underlying event rates, affect an RCT's power to measure significant differences in these outcomes is poorly understood. Motivated by the design of an RCT of neuromuscular blockade in acute respiratory distress syndrome, we examined how power to detect a difference in secondary endpoints varies with the sensitivity and specificity of the instrument used to measure such outcomes. We derived a general formula and Stata code for calculating an RCT's power to detect differences in binary outcomes when such outcomes are measured with imperfect sensitivity and specificity. The formula informed the choice of instrument for measuring post-traumatic stress-like symptoms in the Reevaluation of Systemic Early Neuromuscular Blockade RCT ( www.clinicaltrials.gov identifier NCT02509078). On the basis of published sensitivities and specificities, the Impact of Events Scale-Revised was predicted to measure a 36% symptom rate, whereas the Post-Traumatic Stress Symptoms instrument was predicted to measure a 23% rate, if the true underlying rate of post-traumatic stress symptoms were 25%. Despite its lower sensitivity, the briefer Post-Traumatic Stress Symptoms instrument provided superior power to detect a difference in rates between trial arms, owing to its higher specificity. Examining instruments' power to detect differences in outcomes may guide their selection when multiple instruments exist, each with different sensitivities and specificities.

Power Calculations to Select Instruments for Clinical Trial Secondary Endpoints. A Case Study of Instrument Selection for Post-Traumatic Stress Symptoms in Subjects with Acute Respiratory Distress Syndrome

PubMed Central

Schoenfeld, David A.; Brown, Samuel M.; Hough, Catherine L.; Yealy, Donald M.; Moss, Marc; Angus, Derek C.; Iwashyna, Theodore J.

2017-01-01

Rationale: After the sample size of a randomized clinical trial (RCT) is set by the power requirement of its primary endpoint, investigators select secondary endpoints while unable to further adjust sample size. How the sensitivity and specificity of an instrument used to measure these outcomes, together with their expected underlying event rates, affect an RCT’s power to measure significant differences in these outcomes is poorly understood. Objectives: Motivated by the design of an RCT of neuromuscular blockade in acute respiratory distress syndrome, we examined how power to detect a difference in secondary endpoints varies with the sensitivity and specificity of the instrument used to measure such outcomes. Methods: We derived a general formula and Stata code for calculating an RCT’s power to detect differences in binary outcomes when such outcomes are measured with imperfect sensitivity and specificity. The formula informed the choice of instrument for measuring post-traumatic stress–like symptoms in the Reevaluation of Systemic Early Neuromuscular Blockade RCT (www.clinicaltrials.gov identifier NCT02509078). Measurements and Main Results: On the basis of published sensitivities and specificities, the Impact of Events Scale-Revised was predicted to measure a 36% symptom rate, whereas the Post-Traumatic Stress Symptoms instrument was predicted to measure a 23% rate, if the true underlying rate of post-traumatic stress symptoms were 25%. Despite its lower sensitivity, the briefer Post-Traumatic Stress Symptoms instrument provided superior power to detect a difference in rates between trial arms, owing to its higher specificity. Conclusions: Examining instruments’ power to detect differences in outcomes may guide their selection when multiple instruments exist, each with different sensitivities and specificities. PMID:27788018

MEASUREMENTS OF SUB-DEGREE B -MODE POLARIZATION IN THE COSMIC MICROWAVE BACKGROUND FROM 100 SQUARE DEGREES OF SPTPOL DATA

DOE PAGES

Keisler, R.; Hoover, S.; Harrington, N.; ...

2015-07-09

We present a measurement of themore » $B$-mode polarization power spectrum (the $BB$ spectrum) from 100 $$\\mathrm{deg}^2$$ of sky observed with SPTpol, a polarization-sensitive receiver currently installed on the South Pole Telescope. The observations used in this work were taken during 2012 and early 2013 and include data in spectral bands centered at 95 and 150 GHz. We report the $BB$ spectrum in five bins in multipole space, spanning the range $$300 \\le \\ell \\le 2300$$, and for three spectral combinations: 95 GHz $$\\times$$ 95 GHz, 95 GHz $$\\times$$ 150 GHz, and 150 GHz $$\\times$$ 150 GHz. We subtract small ($$< 0.5 \\sigma$$ in units of statistical uncertainty) biases from these spectra and account for the uncertainty in those biases. The resulting power spectra are inconsistent with zero power but consistent with predictions for the $BB$ spectrum arising from the gravitational lensing of $E$-mode polarization. If we assume no other source of $BB$ power besides lensed $B$ modes, we determine a preference for lensed $B$ modes of $$4.9 \\sigma$$. After marginalizing over tensor power and foregrounds, namely polarized emission from galactic dust and extragalactic sources, this significance is $$4.3 \\sigma$$. Fitting for a single parameter, $$A_\\mathrm{lens}$$, that multiplies the predicted lensed $B$-mode spectrum, and marginalizing over tensor power and foregrounds, we find $$A_\\mathrm{lens} = 1.08 \\pm 0.26$$, indicating that our measured spectra are consistent with the signal expected from gravitational lensing. The data presented here provide the best measurement to date of the $B$-mode power spectrum on these angular scales.« less

A statistical approach to evaluate the performance of cardiac biomarkers in predicting death due to acute myocardial infarction: time-dependent ROC curve

PubMed

Karaismailoğlu, Eda; Dikmen, Zeliha Günnur; Akbıyık, Filiz; Karaağaoğlu, Ahmet Ergun

2018-04-30

Background/aim: Myoglobin, cardiac troponin T, B-type natriuretic peptide (BNP), and creatine kinase isoenzyme MB (CK-MB) are frequently used biomarkers for evaluating risk of patients admitted to an emergency department with chest pain. Recently, time- dependent receiver operating characteristic (ROC) analysis has been used to evaluate the predictive power of biomarkers where disease status can change over time. We aimed to determine the best set of biomarkers that estimate cardiac death during follow-up time. We also obtained optimal cut-off values of these biomarkers, which differentiates between patients with and without risk of death. A web tool was developed to estimate time intervals in risk. Materials and methods: A total of 410 patients admitted to the emergency department with chest pain and shortness of breath were included. Cox regression analysis was used to determine an optimal set of biomarkers that can be used for estimating cardiac death and to combine the significant biomarkers. Time-dependent ROC analysis was performed for evaluating performances of significant biomarkers and a combined biomarker during 240 h. The bootstrap method was used to compare statistical significance and the Youden index was used to determine optimal cut-off values. Results : Myoglobin and BNP were significant by multivariate Cox regression analysis. Areas under the time-dependent ROC curves of myoglobin and BNP were about 0.80 during 240 h, and that of the combined biomarker (myoglobin + BNP) increased to 0.90 during the first 180 h. Conclusion: Although myoglobin is not clinically specific to a cardiac event, in our study both myoglobin and BNP were found to be statistically significant for estimating cardiac death. Using this combined biomarker may increase the power of prediction. Our web tool can be useful for evaluating the risk status of new patients and helping clinicians in making decisions.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

PubMed

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Performance evaluation of an evaporative pad greenhouse system for utilization of power plant reject heat

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

Olszewski, M.; Trezek, G.J.

1976-01-01

The overall performance of an evaporative pad greenhouse is considered in terms of the pad heat and mass transfer, the energy budget of the vegetation, and the performance of the power plant. An analytical predictive model for the pad performance was developed utilizing the Merkel total heat approximation. Data obtained from actual greenhouse performance provides an experimental verification of the pad model. Energy balance considerations on the vegetation provide a means of viewing optimal plant growth in terms of the power plant energy dissipation. In general, the results indicate that when an evaporative pad greenhouse system is used for wastemore » heat dispersal, the vegetation can be maintained within its thermal requirement zone, crop irrigation requirements are significantly reduced, and the power plant performance is comparable with conventional closed loop heat rejection systems.« less

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

Kim, Hyeokjin; Chen, Hua; Maksimovic, Dragan

An experimental 30 kW boost composite converter is described in this paper. The composite converter architecture, which consists of a buck module, a boost module, and a dual active bridge module that operates as a DC transformer (DCX), leads to substantial reductions in losses at partial power points, and to significant improvements in weighted efficiency in applications that require wide variations in power and conversion ratio. A comprehensive loss model is developed, accounting for semiconductor conduction and switching losses, capacitor losses, as well as dc and ac losses in magnetic components. Based on the developed loss model, the module andmore » system designs are optimized to maximize efficiency at a 50% power point. Experimental results for the 30 kW prototype demonstrate 98.5%peak efficiency, very high efficiency over wide ranges of power and voltage conversion ratios, as well as excellent agreements between model predictions and measured efficiency curves.« less

Current drive at plasma densities required for thermonuclear reactors.

PubMed

Cesario, R; Amicucci, L; Cardinali, A; Castaldo, C; Marinucci, M; Panaccione, L; Santini, F; Tudisco, O; Apicella, M L; Calabrò, G; Cianfarani, C; Frigione, D; Galli, A; Mazzitelli, G; Mazzotta, C; Pericoli, V; Schettini, G; Tuccillo, A A

2010-08-10

Progress in thermonuclear fusion energy research based on deuterium plasmas magnetically confined in toroidal tokamak devices requires the development of efficient current drive methods. Previous experiments have shown that plasma current can be driven effectively by externally launched radio frequency power coupled to lower hybrid plasma waves. However, at the high plasma densities required for fusion power plants, the coupled radio frequency power does not penetrate into the plasma core, possibly because of strong wave interactions with the plasma edge. Here we show experiments performed on FTU (Frascati Tokamak Upgrade) based on theoretical predictions that nonlinear interactions diminish when the peripheral plasma electron temperature is high, allowing significant wave penetration at high density. The results show that the coupled radio frequency power can penetrate into high-density plasmas due to weaker plasma edge effects, thus extending the effective range of lower hybrid current drive towards the domain relevant for fusion reactors.

Constraints on the power spectrum of the primordial density field from large-scale data - Microwave background and predictions of inflation

NASA Technical Reports Server (NTRS)

Kashlinsky, A.

1992-01-01

It is shown here that, by using galaxy catalog correlation data as input, measurements of microwave background radiation (MBR) anisotropies should soon be able to test two of the inflationary scenario's most basic predictions: (1) that the primordial density fluctuations produced were scale-invariant and (2) that the universe is flat. They should also be able to detect anisotropies of large-scale structure formed by gravitational evolution of density fluctuations present at the last scattering epoch. Computations of MBR anisotropies corresponding to the minimum of the large-scale variance of the MBR anisotropy are presented which favor an open universe with P(k) significantly different from the Harrison-Zeldovich spectrum predicted by most inflationary models.

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

PubMed

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

2013-03-01

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

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.

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

Lopez, Anthony; Maclaurin, Galen; Roberts, Billy

Long-term variability of solar resource is an important factor in planning a utility-scale photovoltaic (PV) generation plant, and annual generation for a given location can vary significantly from year to year. Based on multiple years of solar irradiance data, an exceedance probability is the amount of energy that could potentially be produced by a power plant in any given year. An exceedance probability accounts for long-term variability and climate cycles (e.g., monsoons or changes in aerosols), which ultimately impact PV energy generation. Study results indicate that a significant bias could be associated with relying solely on typical meteorological year (TMY)more » resource data to capture long-term variability. While the TMY tends to under-predict annual generation overall compared to the P50, there appear to be pockets of over-prediction as well.« less

A model combining age, equivalent uniform dose and IL-8 may predict radiation esophagitis in patients with non-small cell lung cancer.

PubMed

Wang, Shulian; Campbell, Jeff; Stenmark, Matthew H; Stanton, Paul; Zhao, Jing; Matuszak, Martha M; Ten Haken, Randall K; Kong, Feng-Ming

2018-03-01

To study whether cytokine markers may improve predictive accuracy of radiation esophagitis (RE) in non-small cell lung cancer (NSCLC) patients. A total of 129 patients with stage I-III NSCLC treated with radiotherapy (RT) from prospective studies were included. Thirty inflammatory cytokines were measured in platelet-poor plasma samples. Logistic regression was performed to evaluate the risk factors of RE. Stepwise Akaike information criterion (AIC) and likelihood ratio test were used to assess model predictions. Forty-nine of 129 patients (38.0%) developed grade ≥2 RE. Univariate analysis showed that age, stage, concurrent chemotherapy, and eight dosimetric parameters were significantly associated with grade ≥2 RE (p < 0.05). IL-4, IL-5, IL-8, IL-13, IL-15, IL-1α, TGFα and eotaxin were also associated with grade ≥2 RE (p < 0.1). Age, esophagus generalized equivalent uniform dose (EUD), and baseline IL-8 were independently associated grade ≥2 RE. The combination of these three factors had significantly higher predictive power than any single factor alone. Addition of IL-8 to toxicity model significantly improves RE predictive accuracy (p = 0.019). Combining baseline level of IL-8, age and esophagus EUD may predict RE more accurately. Refinement of this model with larger sample sizes and validation from multicenter database are warranted. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

High energy density propulsion systems and small engine dynamometer

NASA Astrophysics Data System (ADS)

Hays, Thomas

2009-07-01

Scope and Method of Study. This study investigates all possible methods of powering small unmanned vehicles, provides reasoning for the propulsion system down select, and covers in detail the design and production of a dynamometer to confirm theoretical energy density calculations for small engines. Initial energy density calculations are based upon manufacturer data, pressure vessel theory, and ideal thermodynamic cycle efficiencies. Engine tests are conducted with a braking type dynamometer for constant load energy density tests, and show true energy densities in excess of 1400 WH/lb of fuel. Findings and Conclusions. Theory predicts lithium polymer, the present unmanned system energy storage device of choice, to have much lower energy densities than other conversion energy sources. Small engines designed for efficiency, instead of maximum power, would provide the most advantageous method for powering small unmanned vehicles because these engines have widely variable power output, loss of mass during flight, and generate rotational power directly. Theoretical predictions for the energy density of small engines has been verified through testing. Tested values up to 1400 WH/lb can be seen under proper operating conditions. The implementation of such a high energy density system will require a significant amount of follow-on design work to enable the engines to tolerate the higher temperatures of lean operation. Suggestions are proposed to enable a reliable, small-engine propulsion system in future work. Performance calculations show that a mature system is capable of month long flight times, and unrefueled circumnavigation of the globe.

Alpha Oscillations during Incidental Encoding Predict Subsequent Memory for New "Foil" Information.

PubMed

Vogelsang, David A; Gruber, Matthias; Bergström, Zara M; Ranganath, Charan; Simons, Jon S

2018-05-01

People can employ adaptive strategies to increase the likelihood that previously encoded information will be successfully retrieved. One such strategy is to constrain retrieval toward relevant information by reimplementing the neurocognitive processes that were engaged during encoding. Using EEG, we examined the temporal dynamics with which constraining retrieval toward semantic versus nonsemantic information affects the processing of new "foil" information encountered during a memory test. Time-frequency analysis of EEG data acquired during an initial study phase revealed that semantic compared with nonsemantic processing was associated with alpha decreases in a left frontal electrode cluster from around 600 msec after stimulus onset. Successful encoding of semantic versus nonsemantic foils during a subsequent memory test was related to decreases in alpha oscillatory activity in the same left frontal electrode cluster, which emerged relatively late in the trial at around 1000-1600 msec after stimulus onset. Across participants, left frontal alpha power elicited by semantic processing during the study phase correlated significantly with left frontal alpha power associated with semantic foil encoding during the memory test. Furthermore, larger left frontal alpha power decreases elicited by semantic foil encoding during the memory test predicted better subsequent semantic foil recognition in an additional surprise foil memory test, although this effect did not reach significance. These findings indicate that constraining retrieval toward semantic information involves reimplementing semantic encoding operations that are mediated by alpha oscillations and that such reimplementation occurs at a late stage of memory retrieval, perhaps reflecting additional monitoring processes.

A phenomenological model of muscle fatigue and the power-endurance relationship.

PubMed

James, A; Green, S

2012-11-01

The relationship between power output and the time that it can be sustained during exercise (i.e., endurance) at high intensities is curvilinear. Although fatigue is implicit in this relationship, there is little evidence pertaining to it. To address this, we developed a phenomenological model that predicts the temporal response of muscle power during submaximal and maximal exercise and which was based on the type, contractile properties (e.g., fatiguability), and recruitment of motor units (MUs) during exercise. The model was first used to predict power outputs during all-out exercise when fatigue is clearly manifest and for several distributions of MU type. The model was then used to predict times that different submaximal power outputs could be sustained for several MU distributions, from which several power-endurance curves were obtained. The model was simultaneously fitted to two sets of human data pertaining to all-out exercise (power-time profile) and submaximal exercise (power-endurance relationship), yielding a high goodness of fit (R(2) = 0.96-0.97). This suggested that this simple model provides an accurate description of human power output during submaximal and maximal exercise and that fatigue-related processes inherent in it account for the curvilinearity of the power-endurance relationship.

Estimation of Power Consumption in the Circular Sawing of Stone Based on Tangential Force Distribution

NASA Astrophysics Data System (ADS)

Huang, Guoqin; Zhang, Meiqin; Huang, Hui; Guo, Hua; Xu, Xipeng

2018-04-01

Circular sawing is an important method for the processing of natural stone. The ability to predict sawing power is important in the optimisation, monitoring and control of the sawing process. In this paper, a predictive model (PFD) of sawing power, which is based on the tangential force distribution at the sawing contact zone, was proposed, experimentally validated and modified. With regard to the influence of sawing speed on tangential force distribution, the modified PFD (MPFD) performed with high predictive accuracy across a wide range of sawing parameters, including sawing speed. The mean maximum absolute error rate was within 6.78%, and the maximum absolute error rate was within 11.7%. The practicability of predicting sawing power by the MPFD with few initial experimental samples was proved in case studies. On the premise of high sample measurement accuracy, only two samples are required for a fixed sawing speed. The feasibility of applying the MPFD to optimise sawing parameters while lowering the energy consumption of the sawing system was validated. The case study shows that energy use was reduced 28% by optimising the sawing parameters. The MPFD model can be used to predict sawing power, optimise sawing parameters and control energy.

Predicted impact of thermal power generation emission control measures in the Beijing-Tianjin-Hebei region on air pollution over Beijing, China.

PubMed

Wang, Liqiang; Li, Pengfei; Yu, Shaocai; Mehmood, Khalid; Li, Zhen; Chang, Shucheng; Liu, Weiping; Rosenfeld, Daniel; Flagan, Richard C; Seinfeld, John H

2018-01-17

Widespread economic growth in China has led to increasing episodes of severe air pollution, especially in major urban areas. Thermal power plants represent a particularly important class of emissions. Here we present an evaluation of the predicted effectiveness of a series of recently proposed thermal power plant emission controls in the Beijing-Tianjin-Hebei (BTH) region on air quality over Beijing using the Community Multiscale Air Quality(CMAQ) atmospheric chemical transport model to predict CO, SO 2 , NO 2 , PM 2.5 , and PM 10 levels. A baseline simulation of the hypothetical removal of all thermal power plants in the BTH region is predicted to lead to 38%, 23%, 23%, 24%, and 24% reductions in current annual mean levels of CO, SO 2 , NO 2 , PM 2.5 , and PM 10 in Beijing, respectively. Similar percentage reductions are predicted in the major cities in the BTH region. Simulations of the air quality impact of six proposed thermal power plant emission reduction strategies over the BTH region provide an estimate of the potential improvement in air quality in the Beijing metropolitan area, as a function of the time of year.

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

Jin, Ke; Zhang, Yanwen; Zhu, Zihua

Accurate information of electronic stopping power is fundamental for broad advances in electronic industry, space exploration, national security, and sustainable energy technologies. The Stopping and Range of Ions in Matter (SRIM) code has been widely applied to predict stopping powers and ion distributions for decades. Recent experimental results have, however, shown considerable errors in the SRIM predictions for stopping of heavy ions in compounds containing light elements, indicating an urgent need to improve current stopping power models. The electronic stopping powers of 35Cl, 80Br, 127I, and 197Au ions are experimentally determined in two important functional materials, SiC and SiO2, frommore » tens to hundreds keV/u based on a single ion technique. By combining with the reciprocity theory, new electronic stopping powers are suggested in a region from 0 to 15 MeV, where large deviations from SRIM predictions are observed. For independent experimental validation of the electronic stopping powers we determined, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC with energies from 700 keV to 15 MeV. The measured ion distributions from both RBS and SIMS are considerably deeper (up to ~30%) than the predictions from the commercial SRIM code. In comparison, the new electronic stopping power values are utilized in a modified TRIM-85 (the original version of the SRIM) code, M-TRIM, to predict ion distributions, and the results are in good agreement with the experimentally measured ion distributions.« less

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-01

The Prediction Of Worldwide Energy Resource (POWER) Project facilitates access to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A   new ...

Serosal Laceration During Firing of Powered Linear Stapler Is a Predictor of Staple Malformation.

PubMed

Matsuzawa, Fumihiko; Homma, Shigenori; Yoshida, Tadashi; Konishi, Yuji; Shibasaki, Susumu; Ishikawa, Takahisa; Kawamura, Hideki; Takahashi, Norihiko; Iijima, Hiroaki; Taketomi, Akinobu

2017-12-01

Although several types of staplers have been developed, staple-line leaks have been a great problem in gastrointestinal surgery. Powered linear staplers were recently developed to further reduce the risk of tissue trauma during laparoscopic surgery. The aim of this study was to identify the factors that predict staple malformation and determine the effect of precompression and slow firing on the staple formation of this novel powered stapling method. Porcine stomachs were divided using an endoscopic powered linear stapler with gold reloads. We divided the specimens into 9 groups according to the precompression time (0/60/180 seconds) and firing time (0/60/180 seconds). The occurrence and length of laceration and the shape of the staples were evaluated. We examined the factors influencing successful stapling and investigated the key factors for staple malformation. Precompression significantly decreased the occurrence and length of serosal laceration. Precompression and slow firing significantly improved the optimal stapling formation rate. Univariate analysis showed that the precompression time (0 seconds), firing time (0 seconds), and presence of serosal laceration were significantly associated with a low optimal formation rate. Multivariate analysis showed that these three factors were associated independently with low optimal formation rate and that the presence of serosal laceration was the only factor that could be detected during the stapling procedure. We have shown that serosal laceration is a predictor of staple malformation and demonstrated the importance of precompression and slow stapling when using the powered stapling method.

Investigation of Rotor Performance and Loads of a UH-60A Individual Blade Control System

NASA Technical Reports Server (NTRS)

Yeo, Hyeonsoo; Romander, Ethan A.; Norman, Thomas R.

2011-01-01

Wind tunnel measurements of performance, loads, and vibration of a full-scale UH-60A Black Hawk main rotor with an individual blade control (IBC) system are compared with calculations obtained using the comprehensive helicopter analysis CAMRAD II and a coupled CAMRAD II/OVERFLOW 2 analysis. Measured data show a 5.1% rotor power reduction (8.6% rotor lift to effective-drag ratio increase) using 2/rev IBC actuation with 2.0 amplitude at = 0.4. At the optimum IBC phase for rotor performance, IBC actuator force (pitch link force) decreased, and neither flap nor chord bending moments changed significantly. CAMRAD II predicts the rotor power variations with the IBC phase reasonably well at = 0.35. However, the correlation degrades at = 0.4. Coupled CAMRAD II/OVERFLOW 2 shows excellent correlation with the measured rotor power variations with the IBC phase at both = 0.35 and = 0.4. Maximum reduction of IBC actuator force is better predicted with CAMRAD II, but general trends are better captured with the coupled analysis. The correlation of vibratory hub loads is generally poor by both methods, although the coupled analysis somewhat captures general trends.

Resting state glutamate predicts elevated pre-stimulus alpha during self-relatedness: A combined EEG-MRS study on "rest-self overlap".

PubMed

Bai, Yu; Nakao, Takashi; Xu, Jiameng; Qin, Pengmin; Chaves, Pedro; Heinzel, Alexander; Duncan, Niall; Lane, Timothy; Yen, Nai-Shing; Tsai, Shang-Yueh; Northoff, Georg

2016-01-01

Recent studies have demonstrated neural overlap between resting state activity and self-referential processing. This "rest-self" overlap occurs especially in anterior cortical midline structures like the perigenual anterior cingulate cortex (PACC). However, the exact neurotemporal and biochemical mechanisms remain to be identified. Therefore, we conducted a combined electroencephalography (EEG)-magnetic resonance spectroscopy (MRS) study. EEG focused on pre-stimulus (e.g., prior to stimulus presentation or perception) power changes to assess the degree to which those changes can predict subjects' perception (and judgment) of subsequent stimuli as high or low self-related. MRS measured resting state concentration of glutamate, focusing on PACC. High pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power significantly correlated with both perception of stimuli judged to be highly self-related and with resting state glutamate concentrations in the PACC. In sum, our results show (i) pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power and resting state glutamate concentration to mediate rest-self overlap that (ii) dispose or incline subjects to assign high degrees of self-relatedness to perceptual stimuli.

EXPERIMENTAL EVALUATION OF THE THERMAL PERFORMANCE OF A WATER SHIELD FOR A SURFACE POWER REACTOR

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

REID, ROBERT S.; PEARSON, J. BOSIE; STEWART, ERIC T.

2007-01-16

Water based reactor shielding is being investigated for use on initial lunar surface power systems. A water shield may lower overall cost (as compared to development cost for other materials) and simplify operations in the setup and handling. The thermal hydraulic performance of the shield is of significant interest. The mechanism for transferring heat through the shield is natural convection. Natural convection in a 100 kWt lunar surface reactor shield design is evaluated with 2 kW power input to the water in the Water Shield Testbed (WST) at the NASA Marshall Space Flight Center. The experimental data from the WSTmore » is used to validate a CFD model. Performance of the water shield on the lunar surface is then predicted with a CFD model anchored to test data. The experiment had a maximum water temperature of 75 C. The CFD model with 1/6-g predicts a maximum water temperature of 88 C with the same heat load and external boundary conditions. This difference in maximum temperature does not greatly affect the structural design of the shield, and demonstrates that it may be possible to use water for a lunar reactor shield.« less

A clustering-based fuzzy wavelet neural network model for short-term load forecasting.

PubMed

Kodogiannis, Vassilis S; Amina, Mahdi; Petrounias, Ilias

2013-10-01

Load forecasting is a critical element of power system operation, involving prediction of the future level of demand to serve as the basis for supply and demand planning. This paper presents the development of a novel clustering-based fuzzy wavelet neural network (CB-FWNN) model and validates its prediction on the short-term electric load forecasting of the Power System of the Greek Island of Crete. The proposed model is obtained from the traditional Takagi-Sugeno-Kang fuzzy system by replacing the THEN part of fuzzy rules with a "multiplication" wavelet neural network (MWNN). Multidimensional Gaussian type of activation functions have been used in the IF part of the fuzzyrules. A Fuzzy Subtractive Clustering scheme is employed as a pre-processing technique to find out the initial set and adequate number of clusters and ultimately the number of multiplication nodes in MWNN, while Gaussian Mixture Models with the Expectation Maximization algorithm are utilized for the definition of the multidimensional Gaussians. The results corresponding to the minimum and maximum power load indicate that the proposed load forecasting model provides significantly accurate forecasts, compared to conventional neural networks models.

Investigation of Rotor Performance and Loads of a UH-60A Individual Blade Control System

NASA Technical Reports Server (NTRS)

Yeo, Hyeonsoo; Romander, Ethan A.; Norman, Thomas R.

2011-01-01

Wind tunnel measurements of performance, loads, and vibration of a full-scale UH-60A Black Hawk main rotor with an individual blade control (IBC) system are compared with calculations obtained using the comprehensive helicopter analysis CAMRAD II and a coupled CAMRAD II/OVERFLOW 2 analysis. Measured data show a 5.1% rotor power reduction (8.6% rotor lift to effective-drag ratio increase) using 2/rev IBC actuation with 2.0. amplitude at u = 0.4. At the optimum IBC phase for rotor performance, IBC actuator force (pitch link force) decreased, and neither flap nor chord bending moments changed significantly. CAMRAD II predicts the rotor power variations with IBC phase reasonably well at u = 0.35. However, the correlation degrades at u = 0.4. Coupled CAMRAD II/OVERFLOW 2 shows excellent correlation with the measured rotor power variations with IBC phase at both u = 0.35 and u = 0.4. Maximum reduction of IBC actuator force is better predicted with CAMRAD II, but general trends are better captured with the coupled analysis. The correlation of vibratory hub loads is generally poor by both methods, although the coupled analysis somewhat captures general trends.

Presenting Your Best Self(ie): The Influence of Gender on Vertical Orientation of Selfies on Tinder.

PubMed

Sedgewick, Jennifer R; Flath, Meghan E; Elias, Lorin J

2017-01-01

When taking a self-portrait or "selfie" to display in an online dating profile, individuals may intuitively manipulate the vertical camera angle to embody how they want to be perceived by the opposite sex. Concepts from evolutionary psychology and grounded cognition suggest that this manipulation can provide cues of physical height and impressions of power to the viewer which are qualities found to influence mate-selection. We predicted that men would orient selfies more often from below to appear taller (i.e., more powerful) than the viewer, and women, from an above perspective to appear shorter (i.e., less powerful). A content analysis was conducted which coded the vertical orientation of 557 selfies from profile pictures on the popular mobile dating application, Tinder. In general, selfies were commonly used by both men (54%) and women (90%). Consistent with our predictions, a gender difference emerged; men's selfies were angled significantly more often from below, whereas women's were angled more often from above. Our findings suggest that selfies presented in a mate-attraction context are intuitively or perhaps consciously selected to adhere to ideal mate qualities. Further discussion proposes that biological or individual differences may also facilitate vertical compositions of selfies.

Analysis of 2D Transport and Performance Characteristics for Lateral Power Devices Based on AlGaN Alloys

DOE PAGES

Coltrin, Michael E.; Baca, Albert G.; Kaplar, Robert J.

2017-10-26

In this paper, predicted lateral power device performance as a function of alloy composition is characterized by a standard lateral device figure-of-merit (LFOM) that depends on mobility, critical electric field, and sheet carrier density. The paper presents calculations of AlGaN electron mobility in lateral devices such as HEMTs across the entire alloy composition range. Alloy scattering and optical polar phonon scattering are the dominant mechanisms limiting carrier mobility. Due to the significant degradation of mobility from alloy scattering, at room temperature Al fractions greater than about 85% are required for improved LFOM relative to GaN using a conservative sheet chargemore » density of 1 × 10 13 cm –2. However, at higher temperatures at which AlGaN power devices are anticipated to operate, this “breakeven” composition decreases to about 65% at 500 K, for example. For high-frequency applications, the Johnson figure-of-merit (JFOM) is the relevant metric to compare potential device performance across materials platforms. At room temperature, the JFOM for AlGaN alloys is predicted to surpass that of GaN for Al fractions greater than about 40%.« less

Analysis of 2D Transport and Performance Characteristics for Lateral Power Devices Based on AlGaN Alloys

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

Coltrin, Michael E.; Baca, Albert G.; Kaplar, Robert J.

In this paper, predicted lateral power device performance as a function of alloy composition is characterized by a standard lateral device figure-of-merit (LFOM) that depends on mobility, critical electric field, and sheet carrier density. The paper presents calculations of AlGaN electron mobility in lateral devices such as HEMTs across the entire alloy composition range. Alloy scattering and optical polar phonon scattering are the dominant mechanisms limiting carrier mobility. Due to the significant degradation of mobility from alloy scattering, at room temperature Al fractions greater than about 85% are required for improved LFOM relative to GaN using a conservative sheet chargemore » density of 1 × 10 13 cm –2. However, at higher temperatures at which AlGaN power devices are anticipated to operate, this “breakeven” composition decreases to about 65% at 500 K, for example. For high-frequency applications, the Johnson figure-of-merit (JFOM) is the relevant metric to compare potential device performance across materials platforms. At room temperature, the JFOM for AlGaN alloys is predicted to surpass that of GaN for Al fractions greater than about 40%.« less

Experimental Evaluation of the Thermal Performance of a Water Shield for a Surface Power Reactor

NASA Technical Reports Server (NTRS)

Pearson, J. Boise; Stewart, Eric T.; Reid, Robert S.

2007-01-01

A water based shielding system is being investigated for use on initial lunar surface power systems. The use of water may lower overall cost (as compared to development cost for other materials) and simplify operations in the setup and handling. The thermal hydraulic performance of the shield is of significant interest. The mechanism for transferring heat through the shield is natural convection. Natural convection in a representative lunar surface reactor shield design is evaluated at various power levels in the Water Shield Testbed (WST) at the NASA Marshall Space Flight Center. The experimental data from the WST is used to anchor a CFD model. Performance of a water shield on the lunar surface is then predicted by CFD models anchored to test data. The accompanying viewgraph presentation includes the following topics: 1) Testbed Configuration; 2) Core Heater Placement and Instrumentation; 3) Thermocouple Placement; 4) Core Thermocouple Placement; 5) Outer Tank Thermocouple Placement; 6) Integrated Testbed; 7) Methodology; 8) Experimental Results: Core Temperatures; 9) Experimental Results; Outer Tank Temperatures; 10) CFD Modeling; 11) CFD Model: Anchored to Experimental Results (1-g); 12) CFD MOdel: Prediction for 1/6-g; and 13) CFD Model: Comparison of 1-g to 1/6-g.

Development scenario for laser fusion

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

Maniscalco, J.A.; Hovingh, J.; Buntzen, R.R.

1976-03-30

This scenario proposes establishment of test and engineering facilities to (1) investigate the technological problems associated with laser fusion, (2) demonstrate fissile fuel production, and (3) demonstrate competitive electrical power production. Such facilities would be major milestones along the road to a laser-fusion power economy. The relevant engineering and economic aspects of each of these research and development facilities are discussed. Pellet design and gain predictions corresponding to the most promising laser systems are presented for each plant. The results show that laser fusion has the potential to make a significant contribution to our energy needs. Beginning in the earlymore » 1990's, this new technology could be used to produce fissile fuel, and after the turn of the century it could be used to generate electrical power.« less

Radiative Performance of Rare Earth Garnet Thin Film Selective Emitters

NASA Technical Reports Server (NTRS)

Lowe, Roland A.; Chubb, Donald L.; Good, Brian S.

1994-01-01

In this paper we present the first emitter efficiency results for the thin film 40 percent Er-1.5 percent Ho YAG (Yttrium Aluminum Garnet, Y3Al5O12) and 25 percent Ho YAG selective emitter at 1500 K with a platinum substrate. Spectral emittance and emissive power measurements were made (1.2 less than lambda less than 3.2 microns). Emitter efficiency and power density are significantly improved with the addition of multiple rare earth dopants. Predicted efficiency results are presented for an optimized (equal power density in the Er, (4)I(sub 15/2)-(4)I(sub 13/2) at 1.5 microns, and Ho, (5)I(sub 7)-(5)I(sub 8) at 2.0 micron emission bands) Er-Ho YAG thin film selective emitter.

Predictability of Brayton electric power system performance

NASA Technical Reports Server (NTRS)

Klann, J. L.; Hettel, H. J.

1972-01-01

Data from the first tests of the 2- to 15-kilowatt space power system in a vacuum chamber were compared with predictions of both a pretest analysis and a modified version of that analysis. The pretest analysis predicted test results with differences of no more than 9 percent of the largest measured value for each quantity. The modified analysis correlated measurements. Differences in conversion efficiency and power output were no greater than plus or minus 2.5 percent. This modified analysis was used to project space performance maps for the current test system.

Low Data Drug Discovery with One-Shot Learning

PubMed Central

2017-01-01

Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. Model.2015, 55, 263–27425635324). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016). PMID:28470045

Progress update of NASA's free-piston Stirling space power converter technology project

NASA Technical Reports Server (NTRS)

Dudenhoefer, James E.; Winter, Jerry M.; Alger, Donald

1992-01-01

A progress update is presented of the NASA LeRC Free-Piston Stirling Space Power Converter Technology Project. This work is being conducted under NASA's Civil Space Technology Initiative (CSTI). The goal of the CSTI High Capacity Power Element is to develop the technology base needed to meet the long duration, high capacity power requirements for future NASA space initiatives. Efforts are focused upon increasing system power output and system thermal and electric energy conversion efficiency at least five fold over current SP-100 technology, and on achieving systems that are compatible with space nuclear reactors. This paper will discuss progress toward 1050 K Stirling Space Power Converters. Fabrication is nearly completed for the 1050 K Component Test Power Converter (CTPC); results of motoring tests of the cold end (525 K), are presented. The success of these and future designs is dependent upon supporting research and technology efforts including heat pipes, bearings, superalloy joining technologies, high efficiency alternators, life and reliability testing, and predictive methodologies. This paper will compare progress in significant areas of component development from the start of the program with the Space Power Development Engine (SPDE) to the present work on CTPC.

Thermoelectric Power Factor Limit of a 1D Nanowire

NASA Astrophysics Data System (ADS)

Chen, I.-Ju; Burke, Adam; Svilans, Artis; Linke, Heiner; Thelander, Claes

2018-04-01

In the past decade, there has been significant interest in the potentially advantageous thermoelectric properties of one-dimensional (1D) nanowires, but it has been challenging to find high thermoelectric power factors based on 1D effects in practice. Here we point out that there is an upper limit to the thermoelectric power factor of nonballistic 1D nanowires, as a consequence of the recently established quantum bound of thermoelectric power output. We experimentally test this limit in quasiballistic InAs nanowires by extracting the maximum power factor of the first 1D subband through I -V characterization, finding that the measured maximum power factors conform to the theoretical limit. The established limit allows the prediction of the achievable power factor of a specific nanowire material system with 1D electronic transport based on the nanowire dimension and mean free path. The power factor of state-of-the-art semiconductor nanowires with small cross section and high crystal quality can be expected to be highly competitive (on the order of mW /m K2 ) at low temperatures. However, they have no clear advantage over bulk materials at, or above, room temperature.

Thermoelectric Power Factor Limit of a 1D Nanowire.

PubMed

Chen, I-Ju; Burke, Adam; Svilans, Artis; Linke, Heiner; Thelander, Claes

2018-04-27

In the past decade, there has been significant interest in the potentially advantageous thermoelectric properties of one-dimensional (1D) nanowires, but it has been challenging to find high thermoelectric power factors based on 1D effects in practice. Here we point out that there is an upper limit to the thermoelectric power factor of nonballistic 1D nanowires, as a consequence of the recently established quantum bound of thermoelectric power output. We experimentally test this limit in quasiballistic InAs nanowires by extracting the maximum power factor of the first 1D subband through I-V characterization, finding that the measured maximum power factors conform to the theoretical limit. The established limit allows the prediction of the achievable power factor of a specific nanowire material system with 1D electronic transport based on the nanowire dimension and mean free path. The power factor of state-of-the-art semiconductor nanowires with small cross section and high crystal quality can be expected to be highly competitive (on the order of mW/m K^{2}) at low temperatures. However, they have no clear advantage over bulk materials at, or above, room temperature.

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

NASA Technical Reports Server (NTRS)

Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

1999-01-01

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

Preliminary Empirical Models for Predicting Shrinkage, Part Geometry and Metallurgical Aspects of Ti-6Al-4V Shaped Metal Deposition Builds

NASA Astrophysics Data System (ADS)

Escobar-Palafox, Gustavo; Gault, Rosemary; Ridgway, Keith

2011-12-01

Shaped Metal Deposition (SMD) is an additive manufacturing process which creates parts layer by layer by weld depositions. In this work, empirical models that predict part geometry (wall thickness and outer diameter) and some metallurgical aspects (i.e. surface texture, portion of finer Widmanstätten microstructure) for the SMD process were developed. The models are based on an orthogonal fractional factorial design of experiments with four factors at two levels. The factors considered were energy level (a relationship between heat source power and the rate of raw material input.), step size, programmed diameter and travel speed. The models were validated using previous builds; the prediction error for part geometry was under 11%. Several relationships between the factors and responses were identified. Current had a significant effect on wall thickness; thickness increases with increasing current. Programmed diameter had a significant effect on percentage of shrinkage; this decreased with increasing component size. Surface finish decreased with decreasing step size and current.

Grading system for blood vessel tumor emboli of invasive ductal carcinoma of the breast.

PubMed

Sugiyama, Michiko; Hasebe, Takahiro; Shimada, Hiroko; Takeuchi, Hideki; Shimizu, Kyoko; Shimizu, Michio; Yasuda, Masanori; Ueda, Shigeto; Shigekawa, Takashi; Osaki, Akihiko; Saeki, Toshiaki

2015-06-01

We previously reported that the number of mitotic and apoptotic figures in tumor cells in blood vessel tumor emboli had the greatest significant power for the accurate prediction of the outcome of patients with invasive ductal carcinoma of the breast. The purpose of the present study was to devise a grading system for blood vessel tumor emboli based on the mitotic and apoptotic figures of tumor cells in blood vessel tumor emboli, enabling accurate prediction of the outcome of patients with invasive ductal carcinoma of the breast. We classified 263 invasive ductal carcinomas into the following 3 grades according to the numbers of mitotic and apoptotic figures in tumor cells located in blood vessels within 1 high-power field: grade 0, no blood vessel invasion; grade 1, absence of mitotic figures and presence of any number of apoptotic figures, or 1 mitotic figure and 0 to 2 apoptotic figures; and grade 2, 1 mitotic figure and 3 or more apoptotic figures, or 2 or more mitotic figures and 1 or more apoptotic figures. Multivariate analyses with well-known prognostic factors demonstrated that grade 2 blood vessel tumor emboli significantly increased the hazard ratios for tumor recurrence independent of the nodal status, pathological TNM stage, hormone receptor status, or HER2 status. The presently reported grading system for blood vessel tumor emboli is the strongest histologic factor for accurate prediction of the outcome of patients with invasive ductal carcinoma of the breast. Copyright © 2015 Elsevier Inc. All rights reserved.

Statistical analysis of quiet stance sway in 2-D

PubMed Central

DiZio, Paul; Lackner, James R.

2014-01-01

Subjects exposed to a rotating environment that perturbs their postural sway show adaptive changes in their voluntary spatially directed postural motion to restore accurate movement paths but do not exhibit any obvious learning during passive stance. We have found, however, that a variable known to characterize the degree of stochasticity in quiet stance can also reveal subtle learning phenomena in passive stance. We extended Chow and Collins (Phys Rev E 52(1):909–912, 1995) one-dimensional pinned-polymer model (PPM) to two dimensions (2-D) and then evaluated the model’s ability to make analytical predictions for 2-D quiet stance. To test the model, we tracked center of mass and centers of foot pressures, and compared and contrasted stance sway for the anterior–posterior versus medio-lateral directions before, during, and after exposure to rotation at 10 rpm. Sway of the body during rotation generated Coriolis forces that acted perpendicular to the direction of sway. We found significant adaptive changes for three characteristic features of the mean square displacement (MSD) function: the exponent of the power law defined at short time scales, the proportionality constant of the power law, and the saturation plateau value defined at longer time scales. The exponent of the power law of MSD at a short time scale lies within the bounds predicted by the 2-D PPM. The change in MSD during exposure to rotation also had a power-law exponent in the range predicted by the theoretical model. We discuss the Coriolis force paradigm for studying postural and movement control and the applicability of the PPM model in 2-D for studying postural adaptation. PMID:24477760

Fluorine-18-fluorodeoxyglucose positron emission tomography as an objective substitute for CT morphologic response criteria in patients undergoing chemotherapy for colorectal liver metastases.

PubMed

Nishioka, Yujiro; Yoshioka, Ryuji; Gonoi, Wataru; Sugawara, Toshitaka; Yoshida, Shuntaro; Hashimoto, Masaji; Shindoh, Junichi

2018-05-01

The computed tomography (CT) morphologic response of colorectal liver metastases (CLM) after chemotherapy is reportedly correlated with pathologic response and survival outcomes of patients undergoing surgery. However, they are rather subjective criteria and not evaluable without adequate quality of contrast-enhanced CT images. This study sought the potential use of fluorine-18-fluorodeoxyglucose (FDG) positron emission tomography (PET) as an objective substitute for predicting pathological viability of CLM after chemotherapy. Predictive ability of tumor viability of ≤10% was compared between FDG-PET/CT and contrast-enhanced CT in 34 patients who underwent curative surgical resection for CLM after chemotherapy. The CT morphology and response were defined according to the reported criteria (Chun YS, JAMA 2009). The mean standard uptake value (SUV-mean) in CLM was significantly lower in patients with group 1 and group 2 CT morphology (median, 2.53 and 3.00, respectively) than in group 3 (median, 3.32). The tumor SUV-mean showed moderate correlation with the tumor pathologic viability (r = 0.660, P < 0.0001). A receiver operating characteristic curve analysis revealed that both the tumor SUV-mean (area under the curve [AUC], 0.916; the cut-off value, 3.00) and the CT morphology (AUC, 0.882) have excellent predictive power for ≤10% of tumor viability, while degree of tumor shrinkage showed lower predictive power (AUC, 0.692). FDG-PET shows significant correlation with pathologic viability of CLM after chemotherapy and may offer additional objective information for estimating tumor viability when the CT morphologic response is not evaluable.

Weather conditions and visits to the medical wing of emergency rooms in a metropolitan area during the warm season in Israel: a predictive model

NASA Astrophysics Data System (ADS)

Novikov, Ilya; Kalter-Leibovici, Ofra; Chetrit, Angela; Stav, Nir; Epstein, Yoram

2012-01-01

Global climate changes affect health and present new challenges to healthcare systems. The aim of the present study was to analyze the pattern of visits to the medical wing of emergency rooms (ERs) in public hospitals during warm seasons, and to develop a predictive model that will forecast the number of visits to ERs 2 days ahead. Data on daily visits to the ERs of the four largest medical centers in the Tel-Aviv metropolitan area during the warm months of the year (April-October, 2001-2004), the corresponding daily meteorological data, daily electrical power consumption (a surrogate marker for air-conditioning), air-pollution parameters, and calendar information were obtained and used in the analyses. The predictive model employed a time series analysis with transitional Poisson regression. The concise multivariable model was highly accurate ( r 2 = 0.819). The contribution of mean daily temperature was small but significant: an increase of 1°C in ambient temperature was associated with a 1.47% increase in the number of ER visits ( P < 0.001). An increase in electrical power consumption significantly attenuated the effect of weather conditions on ER visits by 4% per 1,000 MWh ( P < 0.001). Higher daily mean SO2 concentrations were associated with a greater number of ER visits (1% per 1 ppb increment; P = 0.017). Calendar data were the main predictors of ER visits ( r 2 = 0.794). The predictive model was highly accurate in forecasting the number of visits to ERs 2 days ahead. The marginal effect of temperature on the number of ER visits can be attributed to behavioral adaptations, including the use of air-conditioning.

Relationship of physical fitness test results and hockey playing potential in elite-level ice hockey players.

PubMed

Burr, Jaime F; Jamnik, Roni K; Baker, Joseph; Macpherson, Alison; Gledhill, Norman; McGuire, E J

2008-09-01

The primary purpose of this study was to determine the fitness variables with the highest capability for predicting hockey playing potential at the elite level as determined by entry draft selection order. We also examined the differences associated with the predictive abilities of the test components among playing positions. The secondary purpose of this study was to update the physiological profile of contemporary hockey players including positional differences. Fitness test results conducted by our laboratory at the National Hockey League Entry Draft combine were compared with draft selection order on a total of 853 players. Regression models revealed peak anaerobic power output to be important for higher draft round selection in all positions; however, the degree of importance of this measurement varied with playing position. The body index, which is a composite score of height, lean mass, and muscular development, was similarly important in all models, with differing influence by position. Removal of the goalies' data increased predictive capacity, suggesting that talent identification using physical fitness testing of this sort may be more appropriate for skating players. Standing long jump was identified as a significant predictor variable for forwards and defense and could be a useful surrogate for assessing overall hockey potential. Significant differences exist between the physiological profiles of current players based on playing position. There are also positional differences in the relative importance of anthropometric and fitness measures of off-ice hockey tests in relation to draft order. Physical fitness measures and anthropometric data are valuable in helping predict hockey playing potential. Emphasis on anthropometry should be used when comparing elite-level forwards, whereas peak anaerobic power and fatigue rate are more useful for differentiating between defense.

Validating the relationship between 3-dimensional body acceleration and oxygen consumption in trained Steller sea lions.

PubMed

Volpov, Beth L; Rosen, David A S; Trites, Andrew W; Arnould, John P Y

2015-08-01

We tested the ability of overall dynamic body acceleration (ODBA) to predict the rate of oxygen consumption ([Formula: see text]) in freely diving Steller sea lions (Eumetopias jubatus) while resting at the surface and diving. The trained sea lions executed three dive types-single dives, bouts of multiple long dives with 4-6 dives per bout, or bouts of multiple short dives with 10-12 dives per bout-to depths of 40 m, resulting in a range of activity and oxygen consumption levels. Average metabolic rate (AMR) over the dive cycle or dive bout calculated was calculated from [Formula: see text]. We found that ODBA could statistically predict AMR when data from all dive types were combined, but that dive type was a significant model factor. However, there were no significant linear relationships between AMR and ODBA when data for each dive type were analyzed separately. The potential relationships between AMR and ODBA were not improved by including dive duration, food consumed, proportion of dive cycle spent submerged, or number of dives per bout. It is not clear whether the lack of predictive power within dive type was due to low statistical power, or whether it reflected a true absence of a relationship between ODBA and AMR. The average percent error for predicting AMR from ODBA was 7-11 %, and standard error of the estimated AMR was 5-32 %. Overall, the extensive range of dive behaviors and physiological conditions we tested indicated that ODBA was not suitable for estimating AMR in the field due to considerable error and the inconclusive effects of dive type.

Projected electric power demands for the Potomac Electric Power Company

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

Wilson, J.W.

1975-07-01

Included are chapters on the background of the Potomac Electric Power Company, forecasting future power demand, demand modeling, accuracy of market predictions, and total power system requirements. (DG)

Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants

NASA Technical Reports Server (NTRS)

Bigger, J. T. Jr; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P.; Cohen, R. J.

1996-01-01

BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS. Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

A record-based case-control study of natural background radiation and the incidence of childhood leukaemia and other cancers in Great Britain during 1980-2006.

PubMed

Kendall, G M; Little, M P; Wakeford, R; Bunch, K J; Miles, J C H; Vincent, T J; Meara, J R; Murphy, M F G

2013-01-01

We conducted a large record-based case-control study testing associations between childhood cancer and natural background radiation. Cases (27,447) born and diagnosed in Great Britain during 1980-2006 and matched cancer-free controls (36,793) were from the National Registry of Childhood Tumours. Radiation exposures were estimated for mother's residence at the child's birth from national databases, using the County District mean for gamma rays, and a predictive map based on domestic measurements grouped by geological boundaries for radon. There was 12% excess relative risk (ERR) (95% CI 3, 22; two-sided P=0.01) of childhood leukaemia per millisievert of cumulative red bone marrow dose from gamma radiation; the analogous association for radon was not significant, ERR 3% (95% CI -4, 11; P=0.35). Associations for other childhood cancers were not significant for either exposure. Excess risk was insensitive to adjustment for measures of socio-economic status. The statistically significant leukaemia risk reported in this reasonably powered study (power ~50%) is consistent with high-dose rate predictions. Substantial bias is unlikely, and we cannot identify mechanisms by which confounding might plausibly account for the association, which we regard as likely to be causal. The study supports the extrapolation of high-dose rate risk models to protracted exposures at natural background exposure levels.

An optimization of the FPGA/NIOS adaptive FIR filter using linear prediction to reduce narrow band RFI for the next generation ground-based ultra-high energy cosmic-ray experiment

NASA Astrophysics Data System (ADS)

Szadkowski, Zbigniew; Fraenkel, E. D.; Glas, Dariusz; Legumina, Remigiusz

2013-12-01

The electromagnetic part of an extensive air shower developing in the atmosphere provides significant information complementary to that obtained by water Cherenkov detectors which are predominantly sensitive to the muonic content of an air shower at ground. The emissions can be observed in the frequency band between 10 and 100 MHz. However, this frequency range is significantly contaminated by narrow-band RFI and other human-made distortions. The Auger Engineering Radio Array currently suppresses the RFI by multiple time-to-frequency domain conversions using an FFT procedure as well as by a set of manually chosen IIR notch filters in the time-domain. An alternative approach developed in this paper is an adaptive FIR filter based on linear prediction (LP). The coefficients for the linear predictor are dynamically refreshed and calculated in the virtual NIOS processor. The radio detector is an autonomous system installed on the Argentinean pampas and supplied from a solar panel. Powerful calculation capacity inside the FPGA is a factor. Power consumption versus the degree of effectiveness of the calculation inside the FPGA is a figure of merit to be minimized. Results show that the RFI contamination can be significantly suppressed by the LP FIR filter for 64 or less stages.

Experimental validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, T. W.; Wu, X. F.

1994-01-01

This research report is presented in three parts. In the first part, acoustical analyses were performed on modes of vibration of the housing of a transmission of a gear test rig developed by NASA. The modes of vibration of the transmission housing were measured using experimental modal analysis. The boundary element method (BEM) was used to calculate the sound pressure and sound intensity on the surface of the housing and the radiation efficiency of each mode. The radiation efficiency of each of the transmission housing modes was then compared to theoretical results for a finite baffled plate. In the second part, analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise level radiated from the box. The FEM was used to predict the vibration, while the BEM was used to predict the sound intensity and total radiated sound power using surface vibration as the input data. Vibration predicted by the FEM model was validated by experimental modal analysis; noise predicted by the BEM was validated by measurements of sound intensity. Three types of results are presented for the total radiated sound power: sound power predicted by the BEM model using vibration data measured on the surface of the box; sound power predicted by the FEM/BEM model; and sound power measured by an acoustic intensity scan. In the third part, the structure used in part two was modified. A rib was attached to the top plate of the structure. The FEM and BEM were then used to predict structural vibration and radiated noise respectively. The predicted vibration and radiated noise were then validated through experimentation.

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

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

Defraene, Gilles, E-mail: gilles.defraene@uzleuven.be; Van den Bergh, Laura; Al-Mamgani, Abrahim

2012-03-01

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including themore » most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions: Comparable prediction models were obtained with LKB, RS, and logistic NTCP models. Including clinical factors improved the predictive power of all models significantly.« less

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

PubMed Central

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

2015-01-01

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

Age, weight, and the front abdominal power test as predictors of isokinetic trunk strength and work in young men and women.

PubMed

Cowley, Patrick M; Fitzgerald, Sharon; Sottung, Kyle; Swensen, Thomas

2009-05-01

First we tested the reliability of two new field tests of core stability (plank to fatigue test [PFT] and front abdominal power test [FAPT]), as well as established measures of core stability (isokinetic trunk extension and flexion strength [TES and TFS] and work [TEW and TFW]) over 3 days in 8 young men and women (24.0 +/- 3.1 years). The TES, TFS, TFW, and FAPT were highly reliable, TEW was moderately reliable, and PFT were unreliable for use during a single testing session. Next, we determined if age, weight, and the data from the reliable field test (FAPT) were predictive of TES, TEW, TFS, and TFW in 50 young men and women (19.0 +/- 1.2 years). The FAPT was the only significant predictor of TES and TEW in young women, explaining 16 and 15% of the variance in trunk performance, respectively. Weight was the only significant predictor of TFS and TFW in young women, explaining 28 and 14% of the variance in trunk performance, respectively. In young men, weight was the only significant predictor of TES, TEW, TFS, and TFW, and explained 27, 35, 42, and 33%, respectively, of the variance in trunk performance. In conclusion, the ability of weight and the FAPT to predict TES, TEW, TFS, and TFW was more frequent in young men than women. Additionally, because the FAPT requires few pieces of equipment, is fast to administer, and predicts isokinetic TES and TEW in young women, it can be used to provide a field-based estimate of isokinetic TES and TEW in women without history of back or lower-extremity injury.

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

PubMed

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

2015-12-01

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

Program Predicts Nonlinear Inverter Performance

NASA Technical Reports Server (NTRS)

Al-Ayoubi, R. R.; Oepomo, T. S.

1985-01-01

Program developed for ac power distribution system on Shuttle orbiter predicts total load on inverters and node voltages at each of line replaceable units (LRU's). Mathematical model simulates inverter performance at each change of state in power distribution system.

A novel method for predicting the power outputs of wave energy converters

NASA Astrophysics Data System (ADS)

Wang, Yingguang

2018-03-01

This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

Predictors of cultural capital on science academic achievement at the 8th grade level

NASA Astrophysics Data System (ADS)

Misner, Johnathan Scott

The purpose of the study was to determine if students' cultural capital is a significant predictor of 8th grade science achievement test scores in urban locales. Cultural capital refers to the knowledge used and gained by the dominant class, which allows social and economic mobility. Cultural capital variables include magazines at home and parental education level. Other variables analyzed include socioeconomic status (SES), gender, and English language learners (ELL). This non-experimental study analyzed the results of the 2011 Eighth Grade Science National Assessment of Educational Progress (NAEP). The researcher analyzed the data using a multivariate stepwise regression analysis. The researcher concluded that the addition of cultural capital factors significantly increased the predictive power of the model where magazines in home, gender, student classified as ELL, parental education level, and SES were the independent variables and science achievement was the dependent variable. For alpha=0.05, the overall test for the model produced a R2 value of 0.232; therefore the model predicted 23.2% of variance in science achievement results. Other major findings include: higher measures of home resources predicted higher 2011 NAEP eighth grade science achievement; males were predicted to have higher 2011 NAEP 8 th grade science achievement; classified ELL students were predicted to score lower on the NAEP eight grade science achievement; higher parent education predicted higher NAEP eighth grade science achievement; lower measures of SES predicted lower 2011 NAEP eighth grade science achievement. This study contributed to the research in this field by identifying cultural capital factors that have been found to have statistical significance on predicting eighth grade science achievement results, which can lead to strategies to help improve science academic achievement among underserved populations.

The complex contribution of sociodemographics to decision-making power in gay male couples

PubMed Central

Perry, Nicholas S.; Huebner, David M.; Baucom, Brian R. W.; Hoff, Colleen C.

2016-01-01

Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner’s individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N=566 couples), and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction, given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant’s HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power), as well as have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. PMID:27606937

Secondary traumatic stress among domestic violence advocates: workplace risk and protective factors.

PubMed

Slattery, Suzanne M; Goodman, Lisa A

2009-11-01

This study identified workplace factors associated with secondary traumatic stress (STS) in a sample of 148 domestic violence advocates working in diverse settings. Findings indicate that coworker support and quality clinical supervision are critical to emotional well-being and that an environment in which there is shared power-that is, respect for diversity, mutuality, and consensual decision making-provides better protection for advocates than more traditional, hierarchical organizational models. Furthermore, shared power emerged as the only workplace variable to significantly predict STS above and beyond individual factors. The discussion includes implications for practice and policy as well as directions for future research.

Study, selection, and preparation of solid cationic conductors. [characteristics of solid electrolytes for rechargeable high energy and high power density batteries

NASA Technical Reports Server (NTRS)

Roth, W. L.; Muller, O.

1974-01-01

Crystal chemical principles and transport theory have been used to predict structures and specific compounds which might find application as solid electrolytes in rechargeable high energy and high power density batteries operating at temperatures less than 200 C. Structures with 1-, 2-, and 3-dimensional channels were synthesized and screened by nuclear magnetic resonance, dielectric loss, and conductivity. There is significant conductivity at room temperature in some of the materials but none attain a level that is comparable to beta-alumina. Microwave and fast pulse methods were developed to measure conductivity in powders and in small crystals.

Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

ERIC Educational Resources Information Center

Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

2009-01-01

Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

The impact of three recent coal-fired power plant closings on Pittsburgh air quality: A natural experiment.

PubMed

Russell, Marie C; Belle, Jessica H; Liu, Yang

2017-01-01

Relative to the rest of the United States, the region of southwestern Pennsylvania, including metropolitan Pittsburgh, experiences high ambient concentrations of fine particulate matter (PM 2.5 ), which is known to be associated with adverse respiratory and cardiovascular health impacts. This study evaluates whether the closing of three coal-fired power plants within the southwestern Pennsylvania region resulted in a significant decrease in PM 2.5 concentration. Both PM 2.5 data obtained from EPA ground stations in the study region and aerosol optical depth (AOD) data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Terra and Aqua satellites were used to investigate regional air quality from January 2011 through December 2014. The impact of the plant closings on PM 2.5 concentration and AOD was evaluated using a series of generalized additive models. The model results show that monthly fuel consumption of the Elrama plant, which closed in October of 2012, and monthly fuel consumption of both the Mitchell and Hatfield's Ferry plants, which closed in October of 2013, were significant predictors of both PM 2.5 concentration and AOD at EPA ground stations in the study region, after controlling for multiple meteorological factors and long-term, region-wide air quality improvements. The model's power to predict PM 2.5 concentration increased from an adjusted R 2 of 0.61 to 0.68 after excluding data from ground stations with higher uncertainty due to recent increases in unconventional natural gas extraction activities. After preliminary analyses of mean PM 2.5 concentration and AOD showed a downward trend following each power plant shutdown, results from a series of generalized additive models confirmed that the activity of the three plants that closed, measured by monthly fuel consumption, was highly significant in predicting both AOD and PM 2.5 at 12 EPA ground stations; further research on PM 2.5 emissions from unconventional natural gas extraction is needed. With many coal-fired power plants scheduled to close across the United States in the coming years, there is interest in the potential impact on regional PM 2.5 concentrations. In southwestern Pennsylvania, recent coal-fired power plant closings were coupled with a boom in unconventional natural gas extraction. Natural gas is currently seen as an economically viable bridge fuel between coal and renewable energy. This study provides policymakers with more information on the potential ambient concentration changes associated with coal-fired power plant closings as the nation's energy reliance shifts toward natural gas.

Executive Functions as Predictors of School Performance and Social Relationships: Primary and Secondary School Students.

PubMed

Zorza, Juan Pablo; Marino, Julián; Acosta Mesas, Alberto

2016-05-12

This study examined the relationship between executive functions (EFs) and school performance in primary and secondary school students aged 8 to 13 years (N = 146, M = 10.4, 45.8% girls). EFs were evaluated using the Trail Making Test (TMT), Verbal Fluency (VF), and the Stroop Test. Students' GPAs and teachers' assessment of academic skills were used to measure school performance. To evaluate the students' social behavior, participants were asked to rate all their classmates' prosocial behavior and nominate three students with whom they preferred to do school activities; teachers also provided evaluations of students' social skills. EF measures explained 41% (p = .003, f 2 = .694) of variability in school performance and 29% (p = .005, f 2 = .401) of variance in social behavior in primary school students. The predictive power of EFs was found to be lower for secondary school students, although the TMT showed significant prediction and explained 13% (p = .004, f 2 = .149) of variance in school performance and 15% (p = .008, f 2 = .176) in peer ratings of prosocial behavior. This paper discusses the relevance of EFs in the school environment and their different predictive power in primary and secondary school students.

Blade tip, finite aspect ratio, and dynamic stall effects on the Darrieus rotor

NASA Astrophysics Data System (ADS)

Paraschivoiu, I.; Desy, P.; Masson, C.

1988-02-01

The objective of the work described in this paper was to apply the Boeing-Vertol dynamic stall model in an asymmetric manner to account for the asymmetry of the flow between the left and right sides of the rotor. This phenomenon has been observed by the flow visualization of a two-straight-bladed Darrieus rotor in the IMST water tunnel. Also introduced into the aerodynamic model are the effects of the blade tip and finite aspect ratio on the aerodynamic performance of the Darrieus wind turbine. These improvements are compatible with the double-multiple-streamtube model and have been included in the CARDAAV computer code for predicting the aerodynamic performance. Very good agreement has been observed between the test data (Sandia 17 m) and theoretical predictions; a significant improvement over the previous dynamic stall model was obtained for the rotor power at low tip speed ratios, while the inclusion of the finite aspect ratio effects enhances the prediction of the rotor power for high tip speed ratios. The tip losses and finite aspect ratio effects were also calculated for a small-scale vertical-axis wind turbine, with a two-straight-bladed (NACA 0015) rotor.

Neuromechanical sensor fusion yields highest accuracies in predicting ambulation mode transitions for trans-tibial amputees.

PubMed

Tkach, D C; Hargrove, L J

2013-01-01

Advances in battery and actuator technology have enabled clinical use of powered lower limb prostheses such as the BiOM Powered Ankle. To allow ambulation over various types of terrains, such devices rely on built-in mechanical sensors or manual actuation by the amputee to transition into an operational mode that is suitable for a given terrain. It is unclear if mechanical sensors alone can accurately modulate operational modes while voluntary actuation prevents seamless, naturalistic gait. Ensuring that the prosthesis is ready to accommodate new terrain types at first step is critical for user safety. EMG signals from patient's residual leg muscles may provide additional information to accurately choose the proper mode of prosthesis operation. Using a pattern recognition classifier we compared the accuracy of predicting 8 different mode transitions based on (1) prosthesis mechanical sensor output (2) EMG recorded from residual limb and (3) fusion of EMG and mechanical sensor data. Our findings indicate that the neuromechanical sensor fusion significantly decreases errors in predicting 10 mode transitions as compared to using either mechanical sensors or EMG alone (2.3±0.7% vs. 7.8±0.9% and 20.2±2.0% respectively).

Robust face alignment under occlusion via regional predictive power estimation.

PubMed

Heng Yang; Xuming He; Xuhui Jia; Patras, Ioannis

2015-08-01

Face alignment has been well studied in recent years, however, when a face alignment model is applied on facial images with heavy partial occlusion, the performance deteriorates significantly. In this paper, instead of training an occlusion-aware model with visibility annotation, we address this issue via a model adaptation scheme that uses the result of a local regression forest (RF) voting method. In the proposed scheme, the consistency of the votes of the local RF in each of several oversegmented regions is used to determine the reliability of predicting the location of the facial landmarks. The latter is what we call regional predictive power (RPP). Subsequently, we adapt a holistic voting method (cascaded pose regression based on random ferns) by putting weights on the votes of each fern according to the RPP of the regions used in the fern tests. The proposed method shows superior performance over existing face alignment models in the most challenging data sets (COFW and 300-W). Moreover, it can also estimate with high accuracy (72.4% overlap ratio) which image areas belong to the face or nonface objects, on the heavily occluded images of the COFW data set, without explicit occlusion modeling.

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

DOE PAGES

Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine; ...

2017-12-15

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \\real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns,more » emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.« less

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

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

Volkova, Svitlana; Ayton, Ellyn; Porterfield, Katherine

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \\real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns,more » emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.« less

RECOVERY ACT: DYNAMIC ENERGY CONSUMPTION MANAGEMENT OF ROUTING TELECOM AND DATA CENTERS THROUGH REAL-TIME OPTIMAL CONTROL (RTOC): Final Scientific/Technical Report

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

Ron Moon

This final scientific report documents the Industrial Technology Program (ITP) Stage 2 Concept Development effort on Data Center Energy Reduction and Management Through Real-Time Optimal Control (RTOC). Society is becoming increasingly dependent on information technology systems, driving exponential growth in demand for data center processing and an insatiable appetite for energy. David Raths noted, 'A 50,000-square-foot data center uses approximately 4 megawatts of power, or the equivalent of 57 barrels of oil a day1.' The problem has become so severe that in some cases, users are giving up raw performance for a better balance between performance and energy efficiency. Historically,more » power systems for data centers were crudely sized to meet maximum demand. Since many servers operate at 60%-90% of maximum power while only utilizing an average of 5% to 15% of their capability, there are huge inefficiencies in the consumption and delivery of power in these data centers. The goal of the 'Recovery Act: Decreasing Data Center Energy Use through Network and Infrastructure Control' is to develop a state of the art approach for autonomously and intelligently reducing and managing data center power through real-time optimal control. Advances in microelectronics and software are enabling the opportunity to realize significant data center power savings through the implementation of autonomous power management control algorithms. The first step to realizing these savings was addressed in this study through the successful creation of a flexible and scalable mathematical model (equation) for data center behavior and the formulation of an acceptable low technical risk market introduction strategy leveraging commercial hardware and software familiar to the data center market. Follow-on Stage 3 Concept Development efforts include predictive modeling and simulation of algorithm performance, prototype demonstrations with representative data center equipment to verify requisite performance and continued commercial partnering agreement formation to ensure uninterrupted development, and deployment of the real-time optimal control algorithm. As a software implementable technique for reducing power consumption, the RTOC has two very desirable traits supporting rapid prototyping and ultimately widespread dissemination. First, very little capital is required for implementation. No major infrastructure modifications are required and there is no need to purchase expensive capital equipment. Second, the RTOC can be rolled out incrementally. Therefore, the effectiveness can be proven without a large scale initial roll out. Through the use of the Impact Projections Model provided by the DOE, monetary savings in excess of $100M in 2020 and billions by 2040 are predicted. In terms of energy savings, the model predicts a primary energy displacement of 260 trillion BTUs (33 trillion kWh), or a 50% reduction in server power consumption. The model also predicts a corresponding reduction of pollutants such as SO2 and NOx in excess of 100,000 metric tonnes assuming the RTOC is fully deployed. While additional development and prototyping is required to validate these predictions, the relative low cost and ease of implementation compared to large capital projects makes it an ideal candidate for further investigation.« less

Decreased endometrial vascularity and receptivity in unexplained recurrent miscarriage patients during midluteal and early pregnancy phases.

PubMed

Tan, Shu-Yin; Hang, Fu; Purvarshi, Gowreesunkur; Li, Min-Qing; Meng, Da-Hua; Huang, Ling-Ling

2015-10-01

To evaluate the predictive value of three-dimensional (3D)-power Doppler sonography on recurrent miscarriage. The study patients were divided into a recurrent miscarriage group (30 cases) and a normal pregnancy group (21 cases). Measurement of endometrial thickness was performed using two-dimensional transvaginal ultrasound in the midluteal phase. The endometrial volume, vascularization index (VI), flow index (FI), and vascularization-flow index (VFI) in midluteal and placenta volume, as well as the VI, FI, and VFI of early pregnancy were measured using Virtual Organ Computer-aided Analysis of 3D-power Doppler ultrasound. Endometrial thickness, endometrial volume, endometrial vascular data, VI, FI, and VFI of the midluteal phase were lower in the recurrent miscarriage group compared with the normal pregnancy group (p < 0.05). Placental volume, VI, and VFI during early pregnancy were lower in the miscarriage group compared with the normal pregnancy group (p < 0.05). There was no significant change in FI between the recurrent miscarriage and control groups during early pregnancy (p > 0.05). The predictive accuracy of endometrial thickness, endometrial volume, VI, FI, and VFI in the midluteal phase, and placenta volume, VI, FI, and VFI in early pregnancy as measured by the receiver operating characteristic curve to predict miscarriage before 12 gestational weeks in participants was 0.681, 0.876, 0.770, 0.720, 0.879, 0.771, 0.907, 0.592, respectively. The 3D-power Doppler ultrasound is a more comprehensive and sensitive method for evaluating endometrial receptivity. Endometrial volume, VI, FI, and VFI in the midluteal phase, as well as VI in early pregnancy, can be considered as predictive factors for recurrent miscarriage. Copyright © 2015. Published by Elsevier B.V.

Dispersal scaling from the world's rivers

USGS Publications Warehouse

Warrick, J.A.; Fong, D.A.

2004-01-01

Although rivers provide important biogeochemical inputs to oceans, there are currently no descriptive or predictive relationships of the spatial scales of these river influences. Our combined satellite, laboratory, field and modeling results show that the coastal dispersal areas of small, mountainous rivers exhibit remarkable self-similar scaling relationships over many orders of magnitude. River plume areas scale with source drainage area to a power significantly less than one (average = 0.65), and this power relationship decreases significantly with distance offshore of the river mouth. Observations of plumes from large rivers reveal that this scaling continues over six orders of magnitude of river drainage basin areas. This suggests that the cumulative area of coastal influence for many of the smallest rivers of the world is greater than that of single rivers of equal watershed size. Copyright 2004 by the American Geophysical Union.

Exposure damage mechanisms for KCl windows in high power laser systems

NASA Technical Reports Server (NTRS)

Blaszuk, P. R.; Woody, B. A.; Hulse, C. O.; Davis, J. W.; Waters, J. P.

1976-01-01

An experimental study of the 10.6 micrometer and 0.6328 micrometer optical properties of single crystal and europium doped polycrystal is described. Significant variations in the optical properties are observed over periods of exposure up to 100 hours. Models are proposed to predict the 10.6 micrometer absorptivity for long exposure periods. Mechanical creep has been detected in both materials at high temperature.

Agility performance in high-level junior basketball players: the predictive value of anthropometrics and power qualities.

PubMed

Sisic, Nedim; Jelicic, Mario; Pehar, Miran; Spasic, Miodrag; Sekulic, Damir

2016-01-01

In basketball, anthropometric status is an important factor when identifying and selecting talents, while agility is one of the most vital motor performances. The aim of this investigation was to evaluate the influence of anthropometric variables and power capacities on different preplanned agility performances. The participants were 92 high-level, junior-age basketball players (16-17 years of age; 187.6±8.72 cm in body height, 78.40±12.26 kg in body mass), randomly divided into a validation and cross-validation subsample. The predictors set consisted of 16 anthropometric variables, three tests of power-capacities (Sargent-jump, broad-jump and medicine-ball-throw) as predictors. The criteria were three tests of agility: a T-Shape-Test; a Zig-Zag-Test, and a test of running with a 180-degree turn (T180). Forward stepwise multiple regressions were calculated for validation subsamples and then cross-validated. Cross validation included correlations between observed and predicted scores, dependent samples t-test between predicted and observed scores; and Bland Altman graphics. Analysis of the variance identified centres being advanced in most of the anthropometric indices, and medicine-ball-throw (all at P<0.05); with no significant between-position-differences for other studied motor performances. Multiple regression models originally calculated for the validation subsample were then cross-validated, and confirmed for Zig-zag-Test (R of 0.71 and 0.72 for the validation and cross-validation subsample, respectively). Anthropometrics were not strongly related to agility performance, but leg length is found to be negatively associated with performance in basketball-specific agility. Power capacities are confirmed to be an important factor in agility. The results highlighted the importance of sport-specific tests when studying pre-planned agility performance in basketball. The improvement in power capacities will probably result in an improvement in agility in basketball athletes, while anthropometric indices should be used in order to identify those athletes who can achieve superior agility performance.

Testing the consistency of three-point halo clustering in Fourier and configuration space

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Gaztañaga, E.; Scoccimarro, R.; Crocce, M.

2018-05-01

We compare reduced three-point correlations Q of matter, haloes (as proxies for galaxies) and their cross-correlations, measured in a total simulated volume of ˜100 (h-1 Gpc)3, to predictions from leading order perturbation theory on a large range of scales in configuration space. Predictions for haloes are based on the non-local bias model, employing linear (b1) and non-linear (c2, g2) bias parameters, which have been constrained previously from the bispectrum in Fourier space. We also study predictions from two other bias models, one local (g2 = 0) and one in which c2 and g2 are determined by b1 via approximately universal relations. Overall, measurements and predictions agree when Q is derived for triangles with (r1r2r3)1/3 ≳60 h-1 Mpc, where r1 - 3 are the sizes of the triangle legs. Predictions for Qmatter, based on the linear power spectrum, show significant deviations from the measurements at the BAO scale (given our small measurement errors), which strongly decrease when adding a damping term or using the non-linear power spectrum, as expected. Predictions for Qhalo agree best with measurements at large scales when considering non-local contributions. The universal bias model works well for haloes and might therefore be also useful for tightening constraints on b1 from Q in galaxy surveys. Such constraints are independent of the amplitude of matter density fluctuation (σ8) and hence break the degeneracy between b1 and σ8, present in galaxy two-point correlations.

On the impact of power corrections in the prediction of B → K *μ+μ- observables

NASA Astrophysics Data System (ADS)

Descotes-Genon, Sébastien; Hofer, Lars; Matias, Joaquim; Virto, Javier

2014-12-01

The recent LHCb angular analysis of the exclusive decay B → K * μ + μ - has indicated significant deviations from the Standard Model expectations. Accurate predictions can be achieved at large K *-meson recoil for an optimised set of observables designed to have no sensitivity to hadronic input in the heavy-quark limit at leading order in α s . However, hadronic uncertainties reappear through non-perturbative ΛQCD /m b power corrections, which must be assessed precisely. In the framework of QCD factorisation we present a systematic method to include factorisable power corrections and point out that their impact on angular observables depends on the scheme chosen to define the soft form factors. Associated uncertainties are found to be under control, contrary to earlier claims in the literature. We also discuss the impact of possible non-factorisable power corrections, including an estimate of charm-loop effects. We provide results for angular observables at large recoil for two different sets of inputs for the form factors, spelling out the different sources of theoretical uncertainties. Finally, we comment on a recent proposal to explain the anomaly in B → K * μ + μ - observables through charm-resonance effects, and we propose strategies to test this proposal identifying observables and kinematic regions where either the charm-loop model can be disentangled from New Physics effects or the two options leave different imprints.

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer

PubMed Central

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Chang, Shu-Shya; Rau, Cheng-Shyuan; Tai, Hsueh-Ling; Peng, Shu-Hui; Lin, Yi-Chun; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-01-01

Background The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR). Materials and methods There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score. Results ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P<0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance. Conclusion The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer. PMID:29568393

Risk Prediction for Epithelial Ovarian Cancer in 11 United States–Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci

PubMed Central

Clyde, Merlise A.; Palmieri Weber, Rachel; Iversen, Edwin S.; Poole, Elizabeth M.; Doherty, Jennifer A.; Goodman, Marc T.; Ness, Roberta B.; Risch, Harvey A.; Rossing, Mary Anne; Terry, Kathryn L.; Wentzensen, Nicolas; Whittemore, Alice S.; Anton-Culver, Hoda; Bandera, Elisa V.; Berchuck, Andrew; Carney, Michael E.; Cramer, Daniel W.; Cunningham, Julie M.; Cushing-Haugen, Kara L.; Edwards, Robert P.; Fridley, Brooke L.; Goode, Ellen L.; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B.; Olson, Sara H.; Pearce, Celeste Leigh; Pike, Malcolm C.; Rothstein, Joseph H.; Sellers, Thomas A.; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J.; Vierkant, Robert A.; Wicklund, Kristine G.; Wu, Anna H.; Ziogas, Argyrios; Tworoger, Shelley S.; Schildkraut, Joellen M.

2016-01-01

Previously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted. PMID:27698005

Frequency weighting derived from power absorption of fingers-hand-arm system under z(h)-axis vibration.

PubMed

Dong, Ren G; Welcome, Daniel E; McDowell, Thomas W; Wu, John Z; Schopper, Aaron W

2006-01-01

The objectives of this study are to derive the frequency weighting from three vibration power absorption (VPA) methods (finger VPA, palm VPA, and total or hand VPA), and to explore whether these energy methods are better than the currently accepted acceleration method. To calculate the VPA weightings, the mechanical impedance of eight subjects exposed to a broadband random vibration spectrum in the z(h)-axis using 18 combinations of hand couplings and applied forces was measured. The VPA weightings were compared with the frequency weighting specified in ISO 5349-1 [2001. Mechanical Vibration--Measurement and Evaluation of Human Exposure to Hand--Transmitted Vibration--Part 1: General Requirements. International Organization for Standardization, Geneva, Switzerland]. This study found that the hand and palm VPA weightings are very similar to the ISO weighting but the finger VPA weighting for the combined grip and push action is much higher than the ISO weighting at frequencies higher than 25 Hz. Therefore, this study predicted that the total power absorption of the entire hand-arm system is likely to be correlated with psychophysical response or subjective sensation. However, if the ISO weighting method cannot yield good predictions of the vibration-induced disorders in the fingers and hand, the hand and palm energy methods are unlikely to yield significantly better predictions. The finger VPA is a vibration measure between unweighted and ISO weighted accelerations. The palm VPA method may have some value for studying the disorders in the wrist-arm system.

Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach.

PubMed

Ali, Mehreen; Khan, Suleiman A; Wennerberg, Krister; Aittokallio, Tero

2018-04-15

Proteomics profiling is increasingly being used for molecular stratification of cancer patients and cell-line panels. However, systematic assessment of the predictive power of large-scale proteomic technologies across various drug classes and cancer types is currently lacking. To that end, we carried out the first pan-cancer, multi-omics comparative analysis of the relative performance of two proteomic technologies, targeted reverse phase protein array (RPPA) and global mass spectrometry (MS), in terms of their accuracy for predicting the sensitivity of cancer cells to both cytotoxic chemotherapeutics and molecularly targeted anticancer compounds. Our results in two cell-line panels demonstrate how MS profiling improves drug response predictions beyond that of the RPPA or the other omics profiles when used alone. However, frequent missing MS data values complicate its use in predictive modeling and required additional filtering, such as focusing on completely measured or known oncoproteins, to obtain maximal predictive performance. Rather strikingly, the two proteomics profiles provided complementary predictive signal both for the cytotoxic and targeted compounds. Further, information about the cellular-abundance of primary target proteins was found critical for predicting the response of targeted compounds, although the non-target features also contributed significantly to the predictive power. The clinical relevance of the selected protein markers was confirmed in cancer patient data. These results provide novel insights into the relative performance and optimal use of the widely applied proteomic technologies, MS and RPPA, which should prove useful in translational applications, such as defining the best combination of omics technologies and marker panels for understanding and predicting drug sensitivities in cancer patients. Processed datasets, R as well as Matlab implementations of the methods are available at https://github.com/mehr-een/bemkl-rbps. mehreen.ali@helsinki.fi or tero.aittokallio@fimm.fi. Supplementary data are available at Bioinformatics online.

Postoperative air leak grading is useful to predict prolonged air leak after pulmonary lobectomy.

PubMed

Oh, Sang Gi; Jung, Yochun; Jheon, Sanghoon; Choi, Yunhee; Yun, Ju Sik; Na, Kook Joo; Ahn, Byoung Hee

2017-01-23

Results of studies to predict prolonged air leak (PAL; air leak longer than 5 days) after pulmonary lobectomy have been inconsistent and are of limited use. We developed a new scale representing the amount of early postoperative air leak and determined its correlation with air leak duration and its potential as a predictor of PAL. We grade postoperative air leak using a 5-grade scale. All 779 lobectomies from January 2005 to December 2009 with available medical records were reviewed retrospectively. We devised six 'SUM' variables using air leak grades in the initial 72 h postoperatively. Excluding unrecorded cases and postoperative broncho-pleural fistulas, there were 720 lobectomies. PAL occurred in 135 cases (18.8%). Correlation analyses showed each SUM variable highly correlated with air leak duration, and the SUM 4to9 , which was the sum of six consecutive values of air leak grades for every 8 h record on postoperative days 2 and 3, was proved to be the most powerful predictor of PAL; PAL could be predicted with 75.7% and 77.7% positive and negative predictive value, respectively, when SUM 4to9  ≥ 16. When 4 predictors derived from multivariable logistic regression of perioperative variables were combined with SUM 4to9 , there was no significant increase in predictability compared with SUM 4to9 alone. This simple new method to predict PAL using SUM 4to9 showed that the amount of early postoperative air leak is the most powerful predictor of PAL, therefore, grading air leak after pulmonary lobectomy is a useful method to predict PAL.

A large-eddy simulation based power estimation capability for wind farms over complex terrain

NASA Astrophysics Data System (ADS)

Senocak, I.; Sandusky, M.; Deleon, R.

2017-12-01

There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.

Physics-based model for predicting the performance of a miniature wind turbine

NASA Astrophysics Data System (ADS)

Xu, F. J.; Hu, J. Z.; Qiu, Y. P.; Yuan, F. G.

2011-04-01

A comprehensive physics-based model for predicting the performance of the miniature wind turbine (MWT) for power wireless sensor systems was proposed in this paper. An approximation of the power coefficient of the turbine rotor was made after the turbine rotor performance was measured. Incorporation of the approximation with the equivalent circuit model which was proposed according to the principles of the MWT, the overall system performance of the MWT was predicted. To demonstrate the prediction, the MWT system comprised of a 7.6 cm thorgren plastic propeller as turbine rotor and a DC motor as generator was designed and its performance was tested experimentally. The predicted output voltage, power and system efficiency are matched well with the tested results, which imply that this study holds promise in estimating and optimizing the performance of the MWT.

Using Bayes to get the most out of non-significant results

PubMed Central

Dienes, Zoltan

2014-01-01

No scientific conclusion follows automatically from a statistically non-significant result, yet people routinely use non-significant results to guide conclusions about the status of theories (or the effectiveness of practices). To know whether a non-significant result counts against a theory, or if it just indicates data insensitivity, researchers must use one of: power, intervals (such as confidence or credibility intervals), or else an indicator of the relative evidence for one theory over another, such as a Bayes factor. I argue Bayes factors allow theory to be linked to data in a way that overcomes the weaknesses of the other approaches. Specifically, Bayes factors use the data themselves to determine their sensitivity in distinguishing theories (unlike power), and they make use of those aspects of a theory’s predictions that are often easiest to specify (unlike power and intervals, which require specifying the minimal interesting value in order to address theory). Bayes factors provide a coherent approach to determining whether non-significant results support a null hypothesis over a theory, or whether the data are just insensitive. They allow accepting and rejecting the null hypothesis to be put on an equal footing. Concrete examples are provided to indicate the range of application of a simple online Bayes calculator, which reveal both the strengths and weaknesses of Bayes factors. PMID:25120503

Common polygenic variation enhances risk prediction for Alzheimer's disease.

PubMed

Escott-Price, Valentina; Sims, Rebecca; Bannister, Christian; Harold, Denise; Vronskaya, Maria; Majounie, Elisa; Badarinarayan, Nandini; Morgan, Kevin; Passmore, Peter; Holmes, Clive; Powell, John; Brayne, Carol; Gill, Michael; Mead, Simon; Goate, Alison; Cruchaga, Carlos; Lambert, Jean-Charles; van Duijn, Cornelia; Maier, Wolfgang; Ramirez, Alfredo; Holmans, Peter; Jones, Lesley; Hardy, John; Seshadri, Sudha; Schellenberg, Gerard D; Amouyel, Philippe; Williams, Julie

2015-12-01

The identification of subjects at high risk for Alzheimer's disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer's disease and the accuracy of Alzheimer's disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer's Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer's disease (P = 4.9 × 10(-26)). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10(-19)). The best prediction accuracy AUC = 78.2% (95% confidence interval 77-80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer's disease has a significant polygenic component, which has predictive utility for Alzheimer's disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Comparison of Different Risk Perception Measures in Predicting Seasonal Influenza Vaccination among Healthy Chinese Adults in Hong Kong: A Prospective Longitudinal Study

PubMed Central

Liao, Qiuyan; Wong, Wing Sze; Fielding, Richard

2013-01-01

Background Risk perception is a reported predictor of vaccination uptake, but which measures of risk perception best predict influenza vaccination uptake remain unclear. Methodology During the main influenza seasons (between January and March) of 2009 (Wave 1) and 2010 (Wave 2),505 Chinese students and employees from a Hong Kong university completed an online survey. Multivariate logistic regression models were conducted to assess how well different risk perceptions measures in Wave 1 predicted vaccination uptake against seasonal influenza in Wave 2. Principal Findings The results of the multivariate logistic regression models showed that feeling at risk (β = 0.25, p = 0.021) was the better predictor compared with probability judgment while probability judgment (β = 0.25, p = 0.029 ) was better than beliefs about risk in predicting subsequent influenza vaccination uptake. Beliefs about risk and feeling at risk seemed to predict the same aspect of subsequent vaccination uptake because their associations with vaccination uptake became insignificant when paired into the logistic regression model. Similarly, to compare the four scales for assessing probability judgment in predicting vaccination uptake, the 7-point verbal scale remained a significant and stronger predictor for vaccination uptake when paired with other three scales; the 6-point verbal scale was a significant and stronger predictor when paired with the percentage scale or the 2-point verbal scale; and the percentage scale was a significant and stronger predictor only when paired with the 2-point verbal scale. Conclusions/Significance Beliefs about risk and feeling at risk are not well differentiated by Hong Kong Chinese people. Feeling at risk, an affective-cognitive dimension of risk perception predicts subsequent vaccination uptake better than do probability judgments. Among the four scales for assessing risk probability judgment, the 7-point verbal scale offered the best predictive power for subsequent vaccination uptake. PMID:23894292

Measurements and predictions of flyover and static noise of a TF30 afterburning turbofan engine

NASA Technical Reports Server (NTRS)

Burcham, F. W., Jr.; Lasagna, P. L.; Oas, S. C.

1978-01-01

The noise of the TF30 afterburning turbofan engine in an F-111 airplane was determined from static (ground) and flyover tests. A survey was made to measure the exhaust temperature and velocity profiles for a range of power settings. Comparisons were made between predicted and measured jet mixing, internal, and shock noise. It was found that the noise produced at static conditions was dominated by jet mixing noise, and was adequately predicted by current methods. The noise produced during flyovers exhibited large contributions from internally generated noise in the forward arc. For flyovers with the engine at nonafterburning power, the internal noise, shock noise, and jet mixing noise were accurately predicted. During flyovers with afterburning power settings, however, additional internal noise believed to be due to the afterburning process was evident; its level was as much as 8 decibels above the nonafterburning internal noise. Power settings that produced exhausts with inverted velocity profiles appeared to be slightly less noisy than power settings of equal thrust that produced uniform exhaust velocity profiles both in flight and in static testing.

Predicting mortality with biomarkers: a population-based prospective cohort study for elderly Costa Ricans

PubMed Central

2012-01-01

Background Little is known about adult health and mortality relationships outside high-income nations, partly because few datasets have contained biomarker data in representative populations. Our objective is to determine the prognostic value of biomarkers with respect to total and cardiovascular mortality in an elderly population of a middle-income country, as well as the extent to which they mediate the effects of age and sex on mortality. Methods This is a prospective population-based study in a nationally representative sample of elderly Costa Ricans. Baseline interviews occurred mostly in 2005 and mortality follow-up went through December 2010. Sample size after excluding observations with missing values: 2,313 individuals and 564 deaths. Main outcome: prospective death rate ratios for 22 baseline biomarkers, which were estimated with hazard regression models. Results Biomarkers significantly predict future death above and beyond demographic and self-reported health conditions. The studied biomarkers account for almost half of the effect of age on mortality. However, the sex gap in mortality became several times wider after controlling for biomarkers. The most powerful predictors were simple physical tests: handgrip strength, pulmonary peak flow, and walking speed. Three blood tests also predicted prospective mortality: C-reactive protein (CRP), glycated hemoglobin (HbA1c), and dehydroepiandrosterone sulfate (DHEAS). Strikingly, high blood pressure (BP) and high total cholesterol showed little or no predictive power. Anthropometric measures also failed to show significant mortality effects. Conclusions This study adds to the growing evidence that blood markers for CRP, HbA1c, and DHEAS, along with organ-specific functional reserve indicators (handgrip, walking speed, and pulmonary peak flow), are valuable tools for identifying vulnerable elderly. The results also highlight the need to better understand an anomaly noted previously in other settings: despite the continued medical focus on drugs for BP and cholesterol, high levels of BP and cholesterol have little predictive value of mortality in this elderly population. PMID:22694922

Prediction of Radioactive Material Proliferation in Abukuma Basin using USLE

NASA Astrophysics Data System (ADS)

Yi, C. J.

2014-12-01

Due to the nuclear-power plant accident after the 2011 Great East Japan Earthquake and Tsunami, the residents who had resided within 20 km from the Daiichi Fukushima Nuclear Power Plant had forced to leave their hometown. The impacts by the radioactive contamination extended to numerous social elements, such as food, economy, civil engineering, community rebuilding, etc. Japanese government agencies have measured the level of radioactive contamination in urban, agricultural area, forest, riverine and ocean. The research found that the concentration level of cesium-137 (137Cs) is higher in the forest than an open area such as paddy field or rural town. Litter layers and surface layers, especially, are found to be significantly contaminated. The study calculated the estimation of contaminated soil erosion using the USLE which the idea is based on scenario that addresses a question, what if 137Cs would carry out from the forest after intensive rainfall. Predicting radioactively contaminated areas after intense rainfall is a critical matter for the future watershed risk management.

Operator performance and localized muscle fatigue in a simulated space vehicle control task

NASA Technical Reports Server (NTRS)

Lewis, J. L., Jr.

1979-01-01

Fourier transforms in a special purpose computer were utilized to obtain power spectral density functions from electromyograms of the biceps brachii, triceps brachii, brachioradialis, flexor carpi ulnaris, brachialis, and pronator teres in eight subjects performing isometric tracking tasks in two directions utilizing a prototype spacecraft rotational hand controller. Analysis of these spectra in general purpose computers aided in defining muscles involved in performing the task, and yielded a derived measure potentially useful in predicting task termination. The triceps was the only muscle to show significant differences in all possible tests for simple effects in both tasks and, overall, was the most consistently involved of the six muscles. The total power monitored for triceps, biceps, and brachialis dropped to minimal levels across all subjects earlier than for other muscles. However, smaller variances existed for the biceps, brachioradialis, brachialis, and flexor carpi ulnaris muscles and could provide longer predictive times due to smaller standard deviations for a greater population range.

Slow Crack Growth of Brittle Materials With Exponential Crack-Velocity Formulation. Part 3; Constant Stress and Cyclic Stress Experiments

NASA Technical Reports Server (NTRS)

Choi, Sung R.; Nemeth, Noel N.; Gyekenyesi, John P.

2002-01-01

The previously determined life prediction analysis based on an exponential crack-velocity formulation was examined using a variety of experimental data on advanced structural ceramics tested under constant stress and cyclic stress loading at ambient and elevated temperatures. The data fit to the relation between the time to failure and applied stress (or maximum applied stress in cyclic loading) was very reasonable for most of the materials studied. It was also found that life prediction for cyclic stress loading from data of constant stress loading in the exponential formulation was in good agreement with the experimental data, resulting in a similar degree of accuracy as compared with the power-law formulation. The major limitation in the exponential crack-velocity formulation, however, was that the inert strength of a material must be known a priori to evaluate the important slow-crack-growth (SCG) parameter n, a significant drawback as compared with the conventional power-law crack-velocity formulation.

Financial technical indicator based on chaotic bagging predictors for adaptive stock selection in Japanese and American markets

NASA Astrophysics Data System (ADS)

Suzuki, Tomoya; Ohkura, Yuushi

2016-01-01

In order to examine the predictability and profitability of financial markets, we introduce three ideas to improve the traditional technical analysis to detect investment timings more quickly. Firstly, a nonlinear prediction model is considered as an effective way to enhance this detection power by learning complex behavioral patterns hidden in financial markets. Secondly, the bagging algorithm can be applied to quantify the confidence in predictions and compose new technical indicators. Thirdly, we also introduce how to select more profitable stocks to improve investment performance by the two-step selection: the first step selects more predictable stocks during the learning period, and then the second step adaptively and dynamically selects the most confident stock showing the most significant technical signal in each investment. Finally, some investment simulations based on real financial data show that these ideas are successful in overcoming complex financial markets.

On the Predictability of Future Impact in Science

PubMed Central

Penner, Orion; Pan, Raj K.; Petersen, Alexander M.; Kaski, Kimmo; Fortunato, Santo

2013-01-01

Correctly assessing a scientist's past research impact and potential for future impact is key in recruitment decisions and other evaluation processes. While a candidate's future impact is the main concern for these decisions, most measures only quantify the impact of previous work. Recently, it has been argued that linear regression models are capable of predicting a scientist's future impact. By applying that future impact model to 762 careers drawn from three disciplines: physics, biology, and mathematics, we identify a number of subtle, but critical, flaws in current models. Specifically, cumulative non-decreasing measures like the h-index contain intrinsic autocorrelation, resulting in significant overestimation of their “predictive power”. Moreover, the predictive power of these models depend heavily upon scientists' career age, producing least accurate estimates for young researchers. Our results place in doubt the suitability of such models, and indicate further investigation is required before they can be used in recruiting decisions. PMID:24165898

Forecasting ozone concentrations in the east of Croatia using nonparametric Neural Network Models

NASA Astrophysics Data System (ADS)

Kovač-Andrić, Elvira; Sheta, Alaa; Faris, Hossam; Gajdošik, Martina Šrajer

2016-07-01

Ozone is one of the most significant secondary pollutants with numerous negative effects on human health and environment including plants and vegetation. Therefore, more effort is made recently by governments and associations to predict ozone concentrations which could help in establishing better plans and regulation for environment protection. In this study, we use two Artificial Neural Network based approaches (MPL and RBF) to develop, for the first time, accurate ozone prediction models, one for urban and another one for rural area in the eastern part of Croatia. The evaluation of actual against the predicted ozone concentrations revealed that MLP and RBF models are very competitive for the training and testing data in the case of Kopački Rit area whereas in the case of Osijek city, MLP shows better evaluation results with 9% improvement in the correlation coefficient. Furthermore, subsequent feature selection process has improved the prediction power of RBF network.

Prestimulus EEG Power Predicts Conscious Awareness But Not Objective Visual Performance

PubMed Central

Veniero, Domenica

2017-01-01

Abstract Prestimulus oscillatory neural activity has been linked to perceptual outcomes during performance of psychophysical detection and discrimination tasks. Specifically, the power and phase of low frequency oscillations have been found to predict whether an upcoming weak visual target will be detected or not. However, the mechanisms by which baseline oscillatory activity influences perception remain unclear. Recent studies suggest that the frequently reported negative relationship between α power and stimulus detection may be explained by changes in detection criterion (i.e., increased target present responses regardless of whether the target was present/absent) driven by the state of neural excitability, rather than changes in visual sensitivity (i.e., more veridical percepts). Here, we recorded EEG while human participants performed a luminance discrimination task on perithreshold stimuli in combination with single-trial ratings of perceptual awareness. Our aim was to investigate whether the power and/or phase of prestimulus oscillatory activity predict discrimination accuracy and/or perceptual awareness on a trial-by-trial basis. Prestimulus power (3–28 Hz) was inversely related to perceptual awareness ratings (i.e., higher ratings in states of low prestimulus power/high excitability) but did not predict discrimination accuracy. In contrast, prestimulus oscillatory phase did not predict awareness ratings or accuracy in any frequency band. These results provide evidence that prestimulus α power influences the level of subjective awareness of threshold visual stimuli but does not influence visual sensitivity when a decision has to be made regarding stimulus features. Hence, we find a clear dissociation between the influence of ongoing neural activity on conscious awareness and objective performance. PMID:29255794

Prediction and characterization of application power use in a high-performance computing environment

DOE PAGES

Bugbee, Bruce; Phillips, Caleb; Egan, Hilary; ...

2017-02-27

Power use in data centers and high-performance computing (HPC) facilities has grown in tandem with increases in the size and number of these facilities. Substantial innovation is needed to enable meaningful reduction in energy footprints in leadership-class HPC systems. In this paper, we focus on characterizing and investigating application-level power usage. We demonstrate potential methods for predicting power usage based on a priori and in situ characteristics. Lastly, we highlight a potential use case of this method through a simulated power-aware scheduler using historical jobs from a real scientific HPC system.

Storm surge and tidal range energy

NASA Astrophysics Data System (ADS)

Lewis, Matthew; Angeloudis, Athanasios; Robins, Peter; Evans, Paul; Neill, Simon

2017-04-01

The need to reduce carbon-based energy sources whilst increasing renewable energy forms has led to concerns of intermittency within a national electricity supply strategy. The regular rise and fall of the tide makes prediction almost entirely deterministic compared to other stochastic renewable energy forms; therefore, tidal range energy is often stated as a predictable and firm renewable energy source. Storm surge is the term used for the non-astronomical forcing of tidal elevation, and is synonymous with coastal flooding because positive storm surges can elevate water-levels above the height of coastal flood defences. We hypothesis storm surges will affect the reliability of the tidal range energy resource; with negative surge events reducing the tidal range, and conversely, positive surge events increasing the available resource. Moreover, tide-surge interaction, which results in positive storm surges more likely to occur on a flooding tide, will reduce the annual tidal range energy resource estimate. Water-level data (2000-2012) at nine UK tide gauges, where the mean tidal amplitude is above 2.5m and thus suitable for tidal-range energy development (e.g. Bristol Channel), were used to predict tidal range power with a 0D modelling approach. Storm surge affected the annual resource estimate by between -5% to +3%, due to inter-annual variability. Instantaneous power output were significantly affected (Normalised Root Mean Squared Error: 3%-8%, Scatter Index: 15%-41%) with spatial variability and variability due to operational strategy. We therefore find a storm surge affects the theoretical reliability of tidal range power, such that a prediction system may be required for any future electricity generation scenario that includes large amounts of tidal-range energy; however, annual resource estimation from astronomical tides alone appears sufficient for resource estimation. Future work should investigate water-level uncertainties on the reliability and predictability of tidal range energy with 2D hydrodynamic models.

Effects of 31 FDA approved small-molecule kinase inhibitors on isolated rat liver mitochondria.

PubMed

Zhang, Jun; Salminen, Alec; Yang, Xi; Luo, Yong; Wu, Qiangen; White, Matthew; Greenhaw, James; Ren, Lijun; Bryant, Matthew; Salminen, William; Papoian, Thomas; Mattes, William; Shi, Qiang

2017-08-01

The FDA has approved 31 small-molecule kinase inhibitors (KIs) for human use as of November 2016, with six having black box warnings for hepatotoxicity (BBW-H) in product labeling. The precise mechanisms and risk factors for KI-induced hepatotoxicity are poorly understood. Here, the 31 KIs were tested in isolated rat liver mitochondria, an in vitro system recently proposed to be a useful tool to predict drug-induced hepatotoxicity in humans. The KIs were incubated with mitochondria or submitochondrial particles at concentrations ranging from therapeutic maximal blood concentrations (Cmax) levels to 100-fold Cmax levels. Ten endpoints were measured, including oxygen consumption rate, inner membrane potential, cytochrome c release, swelling, reactive oxygen species, and individual respiratory chain complex (I-V) activities. Of the 31 KIs examined only three including sorafenib, regorafenib and pazopanib, all of which are hepatotoxic, caused significant mitochondrial toxicity at concentrations equal to the Cmax, indicating that mitochondrial toxicity likely contributes to the pathogenesis of hepatotoxicity associated with these KIs. At concentrations equal to 100-fold Cmax, 18 KIs were found to be toxic to mitochondria, and among six KIs with BBW-H, mitochondrial injury was induced by regorafenib, lapatinib, idelalisib, and pazopanib, but not ponatinib, or sunitinib. Mitochondrial liability at 100-fold Cmax had a positive predictive power (PPV) of 72% and negative predictive power (NPV) of 33% in predicting human KI hepatotoxicity as defined by product labeling, with the sensitivity and specificity being 62% and 44%, respectively. Similar predictive power was obtained using the criterion of Cmax ≥1.1 µM or daily dose ≥100 mg. Mitochondrial liability at 1-2.5-fold Cmax showed a 100% PPV and specificity, though the NPV and sensitivity were 32% and 14%, respectively. These data provide novel mechanistic insights into KI hepatotoxicity and indicate that mitochondrial toxicity at therapeutic levels can help identify hepatotoxic KIs.

NREL Projects Awarded More Than $3 Million to Advance Novel Solar

Science.gov Websites

in Grid Operations," evaluating a research solution to better integrate solar power generation funding program, which advances state-of-the-art techniques for predicting solar power generation to Office to advance predictive modeling of solar power as part of its Solar Forecasting 2 funding program

Predictive Ability of the Medicine Ball Chest Throw and Vertical Jump Tests for Determining Muscular Strength and Power in Adolescents

ERIC Educational Resources Information Center

Hackett, Daniel A.; Davies, Timothy B.; Ibel, Denis; Cobley, Stephen; Sanders, Ross

2018-01-01

This study examined the predictive ability of the medicine ball chest throw and vertical jump for muscular strength and power in adolescents. One hundred and ninety adolescents participated in this study. Participants performed trials of the medicine ball chest throw and vertical jump, with vertical jump peak power calculated via an estimation…