Development and Evaluation of a Performance Modeling Flight Test Approach Based on Quasi Steady-State Maneuvers

NASA Technical Reports Server (NTRS)

Yechout, T. R.; Braman, K. B.

1984-01-01

The development, implementation and flight test evaluation of a performance modeling technique which required a limited amount of quasisteady state flight test data to predict the overall one g performance characteristics of an aircraft. The concept definition phase of the program include development of: (1) the relationship for defining aerodynamic characteristics from quasi steady state maneuvers; (2) a simplified in flight thrust and airflow prediction technique; (3) a flight test maneuvering sequence which efficiently provided definition of baseline aerodynamic and engine characteristics including power effects on lift and drag; and (4) the algorithms necessary for cruise and flight trajectory predictions. Implementation of the concept include design of the overall flight test data flow, definition of instrumentation system and ground test requirements, development and verification of all applicable software and consolidation of the overall requirements in a flight test plan.

Predicting Microbial Fuel Cell Biofilm Communities and Bioreactor Performance using Artificial Neural Networks.

PubMed

Lesnik, Keaton Larson; Liu, Hong

2017-09-19

The complex interactions that occur in mixed-species bioelectrochemical reactors, like microbial fuel cells (MFCs), make accurate predictions of performance outcomes under untested conditions difficult. While direct correlations between any individual waste stream characteristic or microbial community structure and reactor performance have not been able to be directly established, the increase in sequencing data and readily available computational power enables the development of alternate approaches. In the current study, 33 MFCs were evaluated under a range of conditions including eight separate substrates and three different wastewaters. Artificial Neural Networks (ANNs) were used to establish mathematical relationships between wastewater/solution characteristics, biofilm communities, and reactor performance. ANN models that incorporated biotic interactions predicted reactor performance outcomes more accurately than those that did not. The average percent error of power density predictions was 16.01 ± 4.35%, while the average percent error of Coulombic efficiency and COD removal rate predictions were 1.77 ± 0.57% and 4.07 ± 1.06%, respectively. Predictions of power density improved to within 5.76 ± 3.16% percent error through classifying taxonomic data at the family versus class level. Results suggest that the microbial communities and performance of bioelectrochemical systems can be accurately predicted using data-mining, machine-learning techniques.

Analysis of high vacuum systems using SINDA'85

NASA Technical Reports Server (NTRS)

Spivey, R. A.; Clanton, S. E.; Moore, J. D.

1993-01-01

The theory, algorithms, and test data correlation analysis of a math model developed to predict performance of the Space Station Freedom Vacuum Exhaust System are presented. The theory used to predict the flow characteristics of viscous, transition, and molecular flow is presented in detail. Development of user subroutines which predict the flow characteristics in conjunction with the SINDA'85/FLUINT analysis software are discussed. The resistance-capacitance network approach with application to vacuum system analysis is demonstrated and results from the model are correlated with test data. The model was developed to predict the performance of the Space Station Freedom Vacuum Exhaust System. However, the unique use of the user subroutines developed in this model and written into the SINDA'85/FLUINT thermal analysis model provides a powerful tool that can be used to predict the transient performance of vacuum systems and gas flow in tubes of virtually any geometry. This can be accomplished using a resistance-capacitance (R-C) method very similar to the methods used to perform thermal analyses.

A review of methodological factors in performance assessments of time-varying aircraft noise effects. [with annotated bibliography

NASA Technical Reports Server (NTRS)

Coates, G. D.; Alluisi, E. A.; Adkins, C. J., Jr.

1977-01-01

Literature on the effects of general noise on human performance is reviewed in an attempt to identify (1) those characteristics of noise that have been found to affect human performance; (2) those characteristics of performance most likely to be affected by the presence of noise, and (3) those characteristics of the performance situation typically associated with noise effects. Based on the characteristics identified, a theoretical framework is proposed that will permit predictions of possible effects of time-varying aircraft-type noise on complex human performance. An annotated bibliography of 50 articles is included.

Job Characteristics, Work Involvement, and Job Performance of Public Servants

ERIC Educational Resources Information Center

Johari, Johanim; Yahya, Khulida Kirana

2016-01-01

Purpose: The primary purpose of this study is to assess the predicting role of job characteristics on job performance. Dimensions in the job characteristics construct are skill variety, task identity, task significance, autonomy and feedback. Further, work involvement is tested as a mediator in the hypothesized link. Design/methodology/approach: A…

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

Wosnik, Martin; Bachant, Pete; Neary, Vincent Sinclair

CACTUS, developed by Sandia National Laboratories, is an open-source code for the design and analysis of wind and hydrokinetic turbines. While it has undergone extensive validation for both vertical axis and horizontal axis wind turbines, and it has been demonstrated to accurately predict the performance of horizontal (axial-flow) hydrokinetic turbines, its ability to predict the performance of crossflow hydrokinetic turbines has yet to be tested. The present study addresses this problem by comparing the predicted performance curves derived from CACTUS simulations of the U.S. Department of Energy’s 1:6 scale reference model crossflow turbine to those derived by experimental measurements inmore » a tow tank using the same model turbine at the University of New Hampshire. It shows that CACTUS cannot accurately predict the performance of this crossflow turbine, raising concerns on its application to crossflow hydrokinetic turbines generally. The lack of quality data on NACA 0021 foil aerodynamic (hydrodynamic) characteristics over the wide range of angles of attack (AoA) and Reynolds numbers is identified as the main cause for poor model prediction. A comparison of several different NACA 0021 foil data sources, derived using both physical and numerical modeling experiments, indicates significant discrepancies at the high AoA experienced by foils on crossflow turbines. Users of CACTUS for crossflow hydrokinetic turbines are, therefore, advised to limit its application to higher tip speed ratios (lower AoA), and to carefully verify the reliability and accuracy of their foil data. Accurate empirical data on the aerodynamic characteristics of the foil is the greatest limitation to predicting performance for crossflow turbines with semi-empirical models like CACTUS. Future improvements of CACTUS for crossflow turbine performance prediction will require the development of accurate foil aerodynamic characteristic data sets within the appropriate ranges of Reynolds numbers and AoA.« less

Closed loop models for analyzing the effects of simulator characteristics. [digital simulation of human operators

NASA Technical Reports Server (NTRS)

Baron, S.; Muralidharan, R.; Kleinman, D. L.

1978-01-01

The optimal control model of the human operator is used to develop closed loop models for analyzing the effects of (digital) simulator characteristics on predicted performance and/or workload. Two approaches are considered: the first utilizes a continuous approximation to the discrete simulation in conjunction with the standard optimal control model; the second involves a more exact discrete description of the simulator in a closed loop multirate simulation in which the optimal control model simulates the pilot. Both models predict that simulator characteristics can have significant effects on performance and workload.

Measurements and Predictions for a Distributed Exhaust Nozzle

NASA Technical Reports Server (NTRS)

Kinzie, Kevin W.; Brown, Martha C.; Schein, David B.; Solomon, W. David, Jr.

2001-01-01

The acoustic and aerodynamic performance characteristics of a distributed exhaust nozzle (DEN) design concept were evaluated experimentally and analytically with the purpose of developing a design methodology for developing future DEN technology. Aerodynamic and acoustic measurements were made to evaluate the DEN performance and the CFD design tool. While the CFD approach did provide an excellent prediction of the flowfield and aerodynamic performance characteristics of the DEN and 2D reference nozzle, the measured acoustic suppression potential of this particular DEN was low. The measurements and predictions indicated that the mini-exhaust jets comprising the distributed exhaust coalesced back into a single stream jet very shortly after leaving the nozzles. Even so, the database provided here will be useful for future distributed exhaust designs with greater noise reduction and aerodynamic performance potential.

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking

PubMed Central

Janssen, Christian P.; Brumby, Duncan P.

2015-01-01

We investigate how good people are at multitasking by comparing behavior to a prediction of the optimal strategy for dividing attention between two concurrent tasks. In our experiment, 24 participants had to interleave entering digits on a keyboard with controlling a randomly moving cursor with a joystick. The difficulty of the tracking task was systematically varied as a within-subjects factor. Participants were also exposed to different explicit reward functions that varied the relative importance of the tracking task relative to the typing task (between-subjects). Results demonstrate that these changes in task characteristics and monetary incentives, together with individual differences in typing ability, influenced how participants choose to interleave tasks. This change in strategy then affected their performance on each task. A computational cognitive model was used to predict performance for a wide set of alternative strategies for how participants might have possibly interleaved tasks. This allowed for predictions of optimal performance to be derived, given the constraints placed on performance by the task and cognition. A comparison of human behavior with the predicted optimal strategy shows that participants behaved near optimally. Our findings have implications for the design and evaluation of technology for multitasking situations, as consideration should be given to the characteristics of the task, but also to how different users might use technology depending on their individual characteristics and their priorities. PMID:26161851

Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models Volume II Reference Manual

DOT National Transportation Integrated Search

2007-08-01

The objective of this research study was to develop performance characteristics or variables (e.g., ride quality, rutting, : fatigue cracking, transverse cracking) of flexible pavements in Montana, and to use these characteristics in the : implementa...

The value of a non-sport-specific motor test battery in predicting performance in young female gymnasts.

PubMed

Vandorpe, Barbara; Vandendriessche, Joric B; Vaeyens, Roel; Pion, Johan; Lefevre, Johan; Philippaerts, Renaat M; Lenoir, Matthieu

2012-01-01

Gymnastics talent identification focuses on the identification of young gymnasts who display characteristics for potential success in the future. The aim of this study was to identify which current performance characteristics are related to performance in competition 2 years later. Twenty-three female gymnasts aged 7-8 years completed a multidimensional test battery measuring anthropometric, physical, and coordinative characteristics and were technically evaluated by expert coaches. Two years later, the all-around competition results of those gymnasts now participating in elite (n = 12) and sub-elite (n = 11) competition were obtained. None of the initial measurements significantly correlated with the results of the sub-elite gymnasts 2 years later. For the elite gymnasts, a non-sport-specific motor test battery correlated strongly with the competition result, with more than 40% of the variation in competition performance being explained by the result on that test 2 years earlier. Neither the coaches' judgement nor the anthropometric and physical characteristics were sensitive enough to predict performance. A motor coordination test might be valuable in the early identification of gymnasts, as its discriminative and predictive qualities might be sufficiently powerful for selection within a relatively homogeneous population of gymnasts exhibiting similar anthropometric and physical profiles.

Final Technical Report: Increasing Prediction Accuracy.

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

King, Bruce Hardison; Hansen, Clifford; Stein, Joshua

2015-12-01

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

A computationally efficient modelling of laminar separation bubbles

NASA Technical Reports Server (NTRS)

Dini, Paolo; Maughmer, Mark D.

1989-01-01

The goal is to accurately predict the characteristics of the laminar separation bubble and its effects on airfoil performance. Toward this end, a computational model of the separation bubble was developed and incorporated into the Eppler and Somers airfoil design and analysis program. Thus far, the focus of the research was limited to the development of a model which can accurately predict situations in which the interaction between the bubble and the inviscid velocity distribution is weak, the so-called short bubble. A summary of the research performed in the past nine months is presented. The bubble model in its present form is then described. Lastly, the performance of this model in predicting bubble characteristics is shown for a few cases.

Determining the Drivers of Student Performance in Online Business Courses

ERIC Educational Resources Information Center

Estelami, Hooman

2014-01-01

An emerging question in business education is whether all students would benefit from distance learning and if student performance can be predicted prior to enrollment in an online course based on student characteristics. In this paper, the role of student characteristics on academic performance is examined in the context two different online…

Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models Volume I Executive Research Summary

DOT National Transportation Integrated Search

2007-08-01

The objective of this research study was to develop performance characteristics or variables (e.g., ride quality, rutting, : fatigue cracking, transverse cracking) of flexible pavements in Montana, and to use these characteristics in the : implementa...

A prediction model for lift-fan simulator performance. M.S. Thesis - Cleveland State Univ.

NASA Technical Reports Server (NTRS)

Yuska, J. A.

1972-01-01

The performance characteristics of a model VTOL lift-fan simulator installed in a two-dimensional wing are presented. The lift-fan simulator consisted of a 15-inch diameter fan driven by a turbine contained in the fan hub. The performance of the lift-fan simulator was measured in two ways: (1) the calculated momentum thrust of the fan and turbine (total thrust loading), and (2) the axial-force measured on a load cell force balance (axial-force loading). Tests were conducted over a wide range of crossflow velocities, corrected tip speeds, and wing angle of attack. A prediction modeling technique was developed to help in analyzing the performance characteristics of lift-fan simulators. A multiple linear regression analysis technique is presented which calculates prediction model equations for the dependent variables.

Do Work Characteristics Predict Health Deterioration Among Employees with Chronic Diseases?

PubMed

de Wind, Astrid; Boot, Cécile R L; Sewdas, Ranu; Scharn, Micky; van den Heuvel, Swenne G; van der Beek, Allard J

2018-06-01

Purpose In our ageing workforce, the increasing numbers of employees with chronic diseases are encouraged to prolong their working lives. It is important to prevent health deterioration in this vulnerable group. This study aims to investigate whether work characteristics predict health deterioration over a 3-year period among employees with (1) chronic diseases, and, more specifically, (2) musculoskeletal and psychological disorders. Methods The study population consisted of 5600 employees aged 45-64 years with a chronic disease, who participated in the Dutch Study on Transitions in Employment, Ability and Motivation (STREAM). Information on work characteristics was derived from the baseline questionnaire. Health deterioration was defined as a decrease in general health (SF-12) between baseline and follow-up (1-3 years). Crude and adjusted logistic regression analyses were performed to investigate prediction of health deterioration by work characteristics. Subgroup analyses were performed for employees with musculoskeletal and psychological disorders. Results At follow-up, 19.2% of the employees reported health deterioration (N = 1075). Higher social support of colleagues or supervisor predicted health deterioration in the crude analyses in the total group, and the groups with either musculoskeletal or psychological disorders (ORs 1.11-1.42). This effect was not found anymore in the adjusted analyses. The other work characteristics did not predict health deterioration in any group. Conclusions This study did not support our hypothesis that work characteristics predict health deterioration among employees with chronic diseases. As our study population succeeded continuing employment to 45 years and beyond, it was probably a relatively healthy selection of employees.

Predicting in-treatment performance and post-treatment outcomes in methamphetamine users.

PubMed

Hillhouse, Maureen P; Marinelli-Casey, Patricia; Gonzales, Rachel; Ang, Alfonso; Rawson, Richard A

2007-04-01

This study examines the utility of individual drug use and treatment characteristics for predicting in-treatment performance and post-treatment outcomes over a 1-year period. Data were collected from 420 adults who participated in the Methamphetamine Treatment Project (MTP), a multi-site study of randomly assigned treatment for methamphetamine dependence. Interviews were conducted at baseline, during treatment and during three follow-up time-points: treatment discharge and at 6 and 12 months following admission. The Addiction Severity Index (ASI); the Craving, Frequency, Intensity and Duration Estimate (CFIDE); and laboratory urinalysis results were used in the current study. Analyses addressed both in-treatment performance and post-treatment outcomes. The most consistent finding is that pre-treatment methamphetamine use predicts in-treatment performance and post-treatment outcomes. No one variable predicted all in-treatment performance measures; however, gender, route of administration and pre-treatment methamphetamine use were significant predictors. Similarly, post-treatment outcomes were predicted by a range of variables, although pre-treatment methamphetamine use was significantly associated with each post-treatment outcome. These findings provide useful empirical information about treatment outcomes for methamphetamine abusers, and highlight the utility of assessing individual and in-treatment characteristics in the development of appropriate treatment plans.

Learner Characteristics Predict Performance and Confidence in E-Learning: An Analysis of User Behavior and Self-Evaluation

ERIC Educational Resources Information Center

Jeske, Debora; Roßnagell, Christian Stamov; Backhaus, Joy

2014-01-01

We examined the role of learner characteristics as predictors of four aspects of e-learning performance, including knowledge test performance, learning confidence, learning efficiency, and navigational effectiveness. We used both self reports and log file records to compute the relevant statistics. Regression analyses showed that both need for…

Predicting One Mile and Two Mile Run Performance from Physiological Measures.

ERIC Educational Resources Information Center

Sucec, A. A.

Twenty-three male distance runners between the ages of 16 and 23 who had achieved a ten-minute or better two-mile performance were tested to determine physical and physiological characteristics to be used in predictive research regarding running performance. Relative body fat ratio, metabolic data, and oxygen intake capability were among the…

Examining the relationships between span of control and manager job and unit performance outcomes.

PubMed

Wong, Carol A; Elliott-Miller, Pat; Laschinger, Heather; Cuddihy, Michael; Meyer, Raquel M; Keatings, Margaret; Burnett, Camille; Szudy, Natalie

2015-03-01

Our aim was to examine the combination of frontline manager (FLM) personal characteristics and span of control (SOC) on their job and unit performance outcomes. Healthcare downsizing and reform have contributed to larger spans for FLMs in Canadian hospitals and increased concerns about manager workload. Despite a heightened awareness of SOC issues among decision makers, there is limited empirical evidence related to the effects of SOC on outcomes. A non-experimental predictive survey design was used to examine FLM SOC in 14 Canadian academic hospitals. Managers (n = 121) completed an online survey of work characteristics and The Ottawa Hospital (TOH) SOC tool. Unit turnover data were collected from organisational databases. The combination of SOC and core self-evaluation significantly predicted role overload, work control and job satisfaction, but only SOC predicted unit adverse outcomes and neither significantly predicted unit turnover. The findings contribute to an understanding of connections between the combination of SOC and core self-evaluation and manager job and unit performance outcomes. Organisational strategies to create manageable FLM SOC are essential to ensure exemplary job and unit outcomes. Core self-evaluation is a personality characteristic that may enhance manager performance in the face of high spans of control. © 2013 John Wiley & Sons Ltd.

STGSTK: A computer code for predicting multistage axial flow compressor performance by a meanline stage stacking method

NASA Technical Reports Server (NTRS)

Steinke, R. J.

1982-01-01

A FORTRAN computer code is presented for off-design performance prediction of axial-flow compressors. Stage and compressor performance is obtained by a stage-stacking method that uses representative velocity diagrams at rotor inlet and outlet meanline radii. The code has options for: (1) direct user input or calculation of nondimensional stage characteristics; (2) adjustment of stage characteristics for off-design speed and blade setting angle; (3) adjustment of rotor deviation angle for off-design conditions; and (4) SI or U.S. customary units. Correlations from experimental data are used to model real flow conditions. Calculations are compared with experimental data.

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.

A neural network for the prediction of performance parameters of transformer cores

NASA Astrophysics Data System (ADS)

Nussbaum, C.; Booth, T.; Ilo, A.; Pfützner, H.

1996-07-01

The paper shows that Artificial Neural Networks (ANNs) may offer new possibilities for the prediction of transformer core performance parameters, i.e. no-load power losses and excitation. Basically this technique enables simulations with respect to different construction parameters most notably the characteristics of corner designs, i.e. the overlap length, the air gap length, and the number of steps. However, without additional physical knowledge incorporated into the ANN extrapolation beyond the training data limits restricts the predictive performance.

Small RNA-based prediction of hybrid performance in maize.

PubMed

Seifert, Felix; Thiemann, Alexander; Schrag, Tobias A; Rybka, Dominika; Melchinger, Albrecht E; Frisch, Matthias; Scholten, Stefan

2018-05-21

Small RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms. Their performance for the prediction of hybrid traits has not yet been analyzed. Our objective was to analyze the relation of parental sRNA expression with the performance of their hybrids, to develop a sRNA-based prediction approach, and to compare it to more common SNP and mRNA transcript based predictions using a factorial mating scheme of a maize hybrid breeding program. Correlation of genomic differences and messenger RNA (mRNA) or sRNA expression differences between parental lines with hybrid performance of their hybrids revealed that sRNAs showed an inverse relationship in contrast to the other two data types. We associated differences for SNPs, mRNA and sRNA expression between parental inbred lines with the performance of their hybrid combinations and developed two prediction approaches using distance measures based on associated markers. Cross-validations revealed parental differences in sRNA expression to be strong predictors for hybrid performance for grain yield in maize, comparable to genomic and mRNA data. The integration of both positively and negatively associated markers in the prediction approaches enhanced the prediction accurary. The associated sRNAs belong predominantly to the canonical size classes of 22- and 24-nt that show specific genomic mapping characteristics. Expression profiles of sRNA are a promising alternative to SNPs or mRNA expression profiles for hybrid prediction, especially for plant species without reference genome or transcriptome information. The characteristics of the sRNAs we identified suggest that association studies based on breeding populations facilitate the identification of sRNAs involved in hybrid performance.

What predicts performance in ultra-triathlon races? – a comparison between Ironman distance triathlon and ultra-triathlon

PubMed Central

Knechtle, Beat; Zingg, Matthias Alexander; Rosemann, Thomas; Stiefel, Michael; Rüst, Christoph Alexander

2015-01-01

Objective This narrative review summarizes recent intentions to find potential predictor variables for ultra-triathlon race performance (ie, triathlon races longer than the Ironman distance covering 3.8 km swimming, 180 km cycling, and 42.195 km running). Results from studies on ultra-triathletes were compared to results on studies on Ironman triathletes. Methods A literature search was performed in PubMed using the terms “ultra”, “triathlon”, and “performance” for the aspects of “ultra-triathlon”, and “Ironman”, “triathlon”, and “performance” for the aspects of “Ironman triathlon”. All resulting papers were searched for related citations. Results for ultra-triathlons were compared to results for Ironman-distance triathlons to find potential differences. Results Athletes competing in Ironman and ultra-triathlon differed in anthropometric and training characteristics, where both Ironmen and ultra-triathletes profited from low body fat, but ultra-triathletes relied more on training volume, whereas speed during training was related to Ironman race time. The most important predictive variables for a fast race time in an ultra-triathlon from Double Iron (ie, 7.6 km swimming, 360 km cycling, and 84.4 km running) and longer were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not in swimming, and origins in Central Europe. Conclusion Any athlete intending to compete in an ultra-triathlon should be aware that low body fat and high training volumes are highly predictive for overall race time. Little is known about the physiological characteristics of these athletes and about female ultra-triathletes. Future studies need to investigate anthropometric and training characteristics of female ultra-triathletes and what motivates women to compete in these races. Future studies need to correlate physiological characteristics such as maximum oxygen uptake (VO2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance. PMID:26056498

Source Listings for Computer Code SPIRALI Incompressible, Turbulent Spiral Grooved Cylindrical and Face Seals

NASA Technical Reports Server (NTRS)

Walowit, Jed A.; Shapiro, Wibur

2005-01-01

This is the source listing of the computer code SPIRALI which predicts the performance characteristics of incompressible cylindrical and face seals with or without the inclusion of spiral grooves. Performance characteristics include load capacity (for face seals), leakage flow, power requirements and dynamic characteristics in the form of stiffness, damping and apparent mass coefficients in 4 degrees of freedom for cylindrical seals and 3 degrees of freedom for face seals. These performance characteristics are computed as functions of seal and groove geometry, load or film thickness, running and disturbance speeds, fluid viscosity, and boundary pressures.

Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models Volume III Field Guide - Calibration and User's Guide for the Mechanistic-Empirical Pavement Design Guide

DOT National Transportation Integrated Search

2007-08-01

The objective of this research study was to develop performance characteristics or variables (e.g., ride quality, rutting, : fatigue cracking, transverse cracking) of flexible pavements in Montana, and to use these characteristics in the : implementa...

Development and evaluation of a predictive algorithm for telerobotic task complexity

NASA Technical Reports Server (NTRS)

Gernhardt, M. L.; Hunter, R. C.; Hedgecock, J. C.; Stephenson, A. G.

1993-01-01

There is a wide range of complexity in the various telerobotic servicing tasks performed in subsea, space, and hazardous material handling environments. Experience with telerobotic servicing has evolved into a knowledge base used to design tasks to be 'telerobot friendly.' This knowledge base generally resides in a small group of people. Written documentation and requirements are limited in conveying this knowledge base to serviceable equipment designers and are subject to misinterpretation. A mathematical model of task complexity based on measurable task parameters and telerobot performance characteristics would be a valuable tool to designers and operational planners. Oceaneering Space Systems and TRW have performed an independent research and development project to develop such a tool for telerobotic orbital replacement unit (ORU) exchange. This algorithm was developed to predict an ORU exchange degree of difficulty rating (based on the Cooper-Harper rating used to assess piloted operations). It is based on measurable parameters of the ORU, attachment receptacle and quantifiable telerobotic performance characteristics (e.g., link length, joint ranges, positional accuracy, tool lengths, number of cameras, and locations). The resulting algorithm can be used to predict task complexity as the ORU parameters, receptacle parameters, and telerobotic characteristics are varied.

Predicting the performance and innovativeness of scientists and engineers.

PubMed

Keller, Robert T

2012-01-01

A study of 644 scientists and engineers from 5 corporate research and development organizations investigated hypotheses generated from an interactionist framework of 4 individual characteristics as longitudinal predictors of performance and innovativeness. An innovative orientation predicted 1-year-later and 5-years-later supervisory job performance ratings and 5-years-later counts of patents and publications. An internal locus of control predicted 5-years-later patents and publications, and self-esteem predicted performance ratings for both times and patents. Team-level nonroutine tasks moderated the individual-level relationships between an innovative orientation and performance ratings and patents such that the relationships were stronger in a nonroutine task environment. Implications for an interactionist framework of performance and innovativeness for knowledge workers are discussed.

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

Harrison, T.D.

Sandia National Laboratories, Albuquerque (SNLA), is currently conducting a program to predict the performance and measure the characteristics of commercially available solar collectors that have the potential for use in industrial process heat and enhance oil recovery applications. The thermal performance predictions for the AAI solar line-focusing slat-type collector for five cities in the US are presented. (WHK)

Noise characteristics of upper surface blown configurations: Summary

NASA Technical Reports Server (NTRS)

Reddy, N. N.; Gibson, J. S.

1978-01-01

A systematic experimental program was conducted to develop a data base for the noise and related flow characteristics of upper surface blown configurations. The effect of various geometric and flow parameters was investigated experimentally. The dominant noise was identified from the measured flow and noise characteristics to be generated downstream of the trailing edge. The possibilities of noise reduction techniques were explored. An upper surface blown (USB) noise prediction program was developed to calculate noise levels at any point and noise contours (footprints). Using this noise prediction program and a cruise performance data base, aircraft design studies were conducted to integrate low noise and good performance characteristics. A theory was developed for the noise from the highly sheared layer of a trailing edge wake. Theoretical results compare favorably with the measured noise of the USB model.

Predicting the natural flow regime: Models for assessing hydrological alteration in streams

USGS Publications Warehouse

Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.

2009-01-01

Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also demonstrate how the models can be applied to predict expected natural flow characteristics at ungaged sites. ?? 2009 John Wiley & Sons, Ltd.

Association of Individual Characteristics with Teleoperation Performance.

PubMed

Pan, Dan; Zhang, Yijing; Li, Zhizhong; Tian, Zhiqiang

2016-09-01

A number of space activities (e.g., extravehicular astronaut rescue, cooperation in satellite services, space station supplies, and assembly) are implemented directly or assisted by remote robotic arms. Our study aimed to reveal those individual characteristics which could positively influence or even predict teleoperation performance of such a space robotic arm. There were 64 male volunteers without robot operation experience recruited for the study. Their individual characteristics were assessed, including spatial cognitive ability, cognitive style, and personality traits. The experimental tasks were three abstracted teleoperation tasks of a simulated space robotic arm: point aiming, line alignment, and obstacle avoidance. Teleoperation performance was measured from two aspects: task performance (completion time, extra distance moved, operation slips) and safety performance (collisions, joint limitations reached). The Pearson coefficients between individual characteristics and teleoperation performance were examined along with performance prediction models. It was found that the subjects with relatively high mental rotation ability or low neuroticism had both better task and safety performance (|r| = 0.212 ∼ 0.381). Subjects with relatively high perspective taking ability or high agreeableness had better task performance (r = -0.253; r = -0.249). Imagery subjects performed better than verbal subjects regarding both task and safety performance (|r| = 0.236 ∼ 0.290). Compared with analytic subjects, wholist subjects had better safety performance (r = 0.300). Additionally, extraverted subjects had better task performance (r = -0.259), but worse safety performance (r = 0.230). Those with high spatial cognitive ability, imagery and wholist cognitive style, low neuroticism, and high agreeableness were seen to have more advantages in working with the remote robotic arm. These results could be helpful to astronaut selection and training for space station missions. Pan D, Zhang Y, Li Z, Tian Z. Association of individual characteristics with teleoperation performance. Aerosp Med Hum Perform. 2016; 87(9):772-780.

Evaluation of CFD to Determine Two-Dimensional Airfoil Characteristics for Rotorcraft Applications

NASA Technical Reports Server (NTRS)

Smith, Marilyn J.; Wong, Tin-Chee; Potsdam, Mark; Baeder, James; Phanse, Sujeet

2004-01-01

The efficient prediction of helicopter rotor performance, vibratory loads, and aeroelastic properties still relies heavily on the use of comprehensive analysis codes by the rotorcraft industry. These comprehensive codes utilize look-up tables to provide two-dimensional aerodynamic characteristics. Typically these tables are comprised of a combination of wind tunnel data, empirical data and numerical analyses. The potential to rely more heavily on numerical computations based on Computational Fluid Dynamics (CFD) simulations has become more of a reality with the advent of faster computers and more sophisticated physical models. The ability of five different CFD codes applied independently to predict the lift, drag and pitching moments of rotor airfoils is examined for the SC1095 airfoil, which is utilized in the UH-60A main rotor. Extensive comparisons with the results of ten wind tunnel tests are performed. These CFD computations are found to be as good as experimental data in predicting many of the aerodynamic performance characteristics. Four turbulence models were examined (Baldwin-Lomax, Spalart-Allmaras, Menter SST, and k-omega).

Dissipation factor as a predictor of anodic coating performance

DOEpatents

Panitz, Janda K. G.

1995-01-01

A dissipation factor measurement is used to predict as-anodized fixture performance prior to actual use of the fixture in an etching environment. A dissipation factor measurement of the anodic coating determines its dielectric characteristics and correlates to the performance of the anodic coating in actual use. The ability to predict the performance of the fixture and its anodized coating permits the fixture to be repaired or replaced prior to complete failure.

Rotordynamic Instability Problems in High-Performance Turbomachinery, 1986

NASA Technical Reports Server (NTRS)

1987-01-01

The first rotordynamics workshop proceedings (NASA CP-2133, 1980) emphasized a feeling of uncertainty in predicting the stability of characteristics of high-performance turbomachinery. In the second workshop proceedings (NASA CP-2250, 1982) these uncertainities were reduced through programs established to systematically resolve problems, with emphasis on experimental validiation of the forces that influence rotordynamics. In third proceedings (NASA CP-2338, 1984) many programs for predicting or measuring forces and force coefficients in high-performance turbomachinery produced results. Data became available for designing new machines with enhanced stability characteristics or for upgrading existing machines. The present workshop proceedings illustrates a continued trend toward a more unified view of rotordynamic instability problems and several encouraging new analytical developments.

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

A mechanistic-empirical approach for evaluating the effect of diamond grinding and thin overlay on predicted pavement performance.

DOT National Transportation Integrated Search

2016-04-01

Advancements in pavement management practice require evaluating the performance of pavement preservation treatments using performance-related characteristics. However, state highway agencies face the challenge of developing performance-based relation...

A prediction model for cognitive performance in health ageing using diffusion tensor imaging with graph theory.

PubMed

Yun, Ruijuan; Lin, Chung-Chih; Wu, Shuicai; Huang, Chu-Chung; Lin, Ching-Po; Chao, Yi-Ping

2013-01-01

In this study, we employed diffusion tensor imaging (DTI) to construct brain structural network and then derive the connection matrices from 96 healthy elderly subjects. The correlation analysis between these topological properties of network based on graph theory and the Cognitive Abilities Screening Instrument (CASI) index were processed to extract the significant network characteristics. These characteristics were then integrated to estimate the models by various machine-learning algorithms to predict user's cognitive performance. From the results, linear regression model and Gaussian processes model showed presented better abilities with lower mean absolute errors of 5.8120 and 6.25 to predict the cognitive performance respectively. Moreover, these extracted topological properties of brain structural network derived from DTI also could be regarded as the bio-signatures for further evaluation of brain degeneration in healthy aged and early diagnosis of mild cognitive impairment (MCI).

Prediction of multi performance characteristics of wire EDM process using grey ANFIS

NASA Astrophysics Data System (ADS)

Kumanan, Somasundaram; Nair, Anish

2017-09-01

Super alloys are used to fabricate components in ultra-supercritical power plants. These hard to machine materials are processed using non-traditional machining methods like Wire cut electrical discharge machining and needs attention. This paper details about multi performance optimization of wire EDM process using Grey ANFIS. Experiments are designed to establish the performance characteristics of wire EDM such as surface roughness, material removal rate, wire wear rate and geometric tolerances. The control parameters are pulse on time, pulse off time, current, voltage, flushing pressure, wire tension, table feed and wire speed. Grey relational analysis is employed to optimise the multi objectives. Analysis of variance of the grey grades is used to identify the critical parameters. A regression model is developed and used to generate datasets for the training of proposed adaptive neuro fuzzy inference system. The developed prediction model is tested for its prediction ability.

The Ability of Psychological Flexibility and Job Control to Predict Learning, Job Performance, and Mental Health

ERIC Educational Resources Information Center

Bond, Frank W.; Flaxman, Paul E.

2006-01-01

This longitudinal study tested the degree to which an individual characteristic, psychological flexibility, and a work organization variable, job control, predicted ability to learn new skills at work, job performance, and mental health, amongst call center workers in the United Kingdom (N = 448). As hypothesized, results indicated that job…

Spherical roller bearing analysis. SKF computer program SPHERBEAN. Volume 3: Program correlation with full scale hardware tests

NASA Technical Reports Server (NTRS)

Kleckner, R. J.; Rosenlieb, J. W.; Dyba, G.

1980-01-01

The results of a series of full scale hardware tests comparing predictions of the SPHERBEAN computer program with measured data are presented. The SPHERBEAN program predicts the thermomechanical performance characteristics of high speed lubricated double row spherical roller bearings. The degree of correlation between performance predicted by SPHERBEAN and measured data is demonstrated. Experimental and calculated performance data is compared over a range in speed up to 19,400 rpm (0.8 MDN) under pure radial, pure axial, and combined loads.

Characterization of the space shuttle reaction control system engine

NASA Technical Reports Server (NTRS)

Wilson, M. S.; Stechman, R. C.; Edelman, R. B.; Fortune, O. F.; Economos, C.

1972-01-01

A computer program was developed and written in FORTRAN 5 which predicts the transient and steady state performance and heat transfer characteristics of a pulsing GO2/GH2 rocket engine. This program predicts the dynamic flow and ignition characteristics which, when combined in a quasi-steady state manner with the combustion and mixing analysis program, will provide the thrust and specific impulse of the engine as a function of time. The program also predicts the transient and steady state heat transfer characteristics of the engine using various cooling concepts. The computer program, test case, and documentation are presented. The program is applicable to any system capable of utilizing the FORTRAN 4 or FORTRAN 5 language.

Arid Zone Hydrology

USDA-ARS?s Scientific Manuscript database

Arid zone hydrology encompasses a wide range of topics and hydro-meteorological and ecological characteristics. Although arid and semi-arid watersheds perform the same functions as those in humid environments, their hydrology and sediment transport characteristics cannot be readily predicted by inf...

Timing of Occurrence Is the Most Important Characteristic of Spot Sign.

PubMed

Wang, Binli; Yan, Shenqiang; Xu, Mengjun; Zhang, Sheng; Liu, Keqin; Hu, Haitao; Selim, Magdy; Lou, Min

2016-05-01

Most previous studies have used single-phase computed tomographic angiography to detect the spot sign, a marker for hematoma expansion (HE) in spontaneous intracerebral hemorrhage. We investigated whether defining the spot sign based on timing on perfusion computed tomography (CTP) would improve its specificity for predicting HE. We prospectively enrolled supratentorial spontaneous intracerebral hemorrhage patients who underwent CTP within 6 hours of onset. Logistic regression was performed to assess the risk factors for HE and poor outcome. Predictive performance of individual CTP spot sign characteristics were examined with receiver operating characteristic analysis. Sixty-two men and 21 women with spontaneous intracerebral hemorrhage were included in this analysis. Spot sign was detected in 46% (38/83) of patients. Receiver operating characteristic analysis indicated that the timing of spot sign occurrence on CTP had the greatest area under receiver operating characteristic curve for HE (0.794; 95% confidence interval, 0.630-0.958; P=0.007); the cutoff time was 23.13 seconds. On multivariable analysis, the presence of early-occurring spot sign (ie, spot sign before 23.13 seconds) was an independent predictor not only of HE (odds ratio=28.835; 95% confidence interval, 6.960-119.458; P<0.001), but also of mortality at 3 months (odds ratio =22.377; 95% confidence interval, 1.773-282.334; P=0.016). Moreover, the predictive performance showed that the redefined early-occurring spot sign maintained a higher specificity for HE compared with spot sign (91% versus 74%). Redefining the spot sign based on timing of contrast leakage on CTP to determine early-occurring spot sign improves the specificity for predicting HE and 3-month mortality. The use of early-occurring spot sign could improve the selection of ICH patients for potential hemostatic therapy. © 2016 American Heart Association, Inc.

The development and testing of a skin tear risk assessment tool.

PubMed

Newall, Nelly; Lewin, Gill F; Bulsara, Max K; Carville, Keryln J; Leslie, Gavin D; Roberts, Pam A

2017-02-01

The aim of the present study is to develop a reliable and valid skin tear risk assessment tool. The six characteristics identified in a previous case control study as constituting the best risk model for skin tear development were used to construct a risk assessment tool. The ability of the tool to predict skin tear development was then tested in a prospective study. Between August 2012 and September 2013, 1466 tertiary hospital patients were assessed at admission and followed up for 10 days to see if they developed a skin tear. The predictive validity of the tool was assessed using receiver operating characteristic (ROC) analysis. When the tool was found not to have performed as well as hoped, secondary analyses were performed to determine whether a potentially better performing risk model could be identified. The tool was found to have high sensitivity but low specificity and therefore have inadequate predictive validity. Secondary analysis of the combined data from this and the previous case control study identified an alternative better performing risk model. The tool developed and tested in this study was found to have inadequate predictive validity. The predictive validity of an alternative, more parsimonious model now needs to be tested. © 2015 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Quiet High-Speed Fan

NASA Technical Reports Server (NTRS)

Lieber, Lysbeth; Repp, Russ; Weir, Donald S.

1996-01-01

A calibration of the acoustic and aerodynamic prediction methods was performed and a baseline fan definition was established and evaluated to support the quiet high speed fan program. A computational fluid dynamic analysis of the NASA QF-12 Fan rotor, using the DAWES flow simulation program was performed to demonstrate and verify the causes of the relatively poor aerodynamic performance observed during the fan test. In addition, the rotor flowfield characteristics were qualitatively compared to the acoustic measurements to identify the key acoustic characteristics of the flow. The V072 turbofan source noise prediction code was used to generate noise predictions for the TFE731-60 fan at three operating conditions and compared to experimental data. V072 results were also used in the Acoustic Radiation Code to generate far field noise for the TFE731-60 nacelle at three speed points for the blade passage tone. A full 3-D viscous flow simulation of the current production TFE731-60 fan rotor was performed with the DAWES flow analysis program. The DAWES analysis was used to estimate the onset of multiple pure tone noise, based on predictions of inlet shock position as a function of the rotor tip speed. Finally, the TFE731-60 fan rotor wake structure predicted by the DAWES program was used to define a redesigned stator with the leading edge configured to minimize the acoustic effects of rotor wake / stator interaction, without appreciably degrading performance.

How do task characteristics affect learning and performance? The roles of variably mapped and dynamic tasks.

PubMed

Macnamara, Brooke N; Frank, David J

2018-05-01

For well over a century, scientists have investigated individual differences in performance. The majority of studies have focused on either differences in practice, or differences in cognitive resources. However, the predictive ability of either practice or cognitive resources varies considerably across tasks. We are the first to examine task characteristics' impact on learning and performance in a complex task while controlling for other task characteristics. In 2 experiments we test key theoretical task characteristic thought to moderate the relationship between practice, cognitive resources, and performance. We devised a task where each of several key task characteristics can be manipulated independently. Participants played 5 rounds of a game similar to the popular tower defense videogame Plants vs. Zombies where both cognitive load and game characteristics were manipulated. In Experiment 1, participants either played a consistently mapped version-the stimuli and the associated meaning of their properties were constant across the 5 rounds-or played a variably mapped version-the stimuli and the associated meaning of their properties changed every few minutes. In Experiment 2, participants either played a static version-that is, turn taking with no time pressure-or played a dynamic version-that is, the stimuli moved regardless of participants' response rates. In Experiment 1, participants' accuracy and efficiency were substantially hindered in the variably mapped conditions. In Experiment 2, learning and performance accuracy were hindered in the dynamic conditions, especially when under cognitive load. Our results suggest that task characteristics impact the relative importance of cognitive resources and practice on predicting learning and performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Performance characteristics of plane-wall venturi-like reverse flow diverters

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

Smith, G.V.; Counce, R.M.

1984-02-01

The results of an analytical and experimental study of plane-wall venturi-like reverse flow diverters (RFD) are presented. In general, the flow characteristics of the RFD are reasonably well predicted by the mathematical model of the RFD, although a divergence between theory and data is observed for the output characteristics in the reverse flow mode as the output impedance is reduced. Overall, the performance of these devices indicates their usefulness in fluid control and fluid power systems, such as displacement pumping systems.

Performance characteristics of plane-wall venturi-like reverse flow diverters

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

Smith, G.V.; Counce, R.M.

1982-01-01

The results of an analytical and experimental study of plane-wall venturi-like reverse flow diverters (RFD) are presented. In general, the flow characteristics of the RFD are reasonably well predicted by the mathematical model of the RFD, although a divergence between theory and data is observed for the output characteristics in the reverse flow mode as the output impedance is reduced. Overall, the performance of these devices indicates their usefulness in fluid control and fluid power systems, such as displacement pumping systems.

Comparative Study on the Prediction of Aerodynamic Characteristics of Aircraft with Turbulence Models

NASA Astrophysics Data System (ADS)

Jang, Yujin; Huh, Jinbum; Lee, Namhun; Lee, Seungsoo; Park, Youngmin

2018-04-01

The RANS equations are widely used to analyze complex flows over aircraft. The equations require a turbulence model for turbulent flow analyses. A suitable turbulence must be selected for accurate predictions of aircraft aerodynamic characteristics. In this study, numerical analyses of three-dimensional aircraft are performed to compare the results of various turbulence models for the prediction of aircraft aerodynamic characteristics. A 3-D RANS solver, MSAPv, is used for the aerodynamic analysis. The four turbulence models compared are the Sparlart-Allmaras (SA) model, Coakley's q-ω model, Huang and Coakley's k-ɛ model, and Menter's k-ω SST model. Four aircrafts are considered: an ARA-M100, DLR-F6 wing-body, DLR-F6 wing-body-nacelle-pylon from the second drag prediction workshop, and a high wing aircraft with nacelles. The CFD results are compared with experimental data and other published computational results. The details of separation patterns, shock positions, and Cp distributions are discussed to find the characteristics of the turbulence models.

Prediction of Gas Lubricated Foil Journal Bearing Performance

NASA Technical Reports Server (NTRS)

Carpino, Marc; Talmage, Gita

2003-01-01

This report summarizes the progress in the first eight months of the project. The objectives of this research project are to theoretically predict the steady operating conditions and the rotor dynamic coefficients of gas foil journal bearings. The project is currently on or ahead of schedule with the development of a finite element code that predicts steady bearing performance characteristics such as film thickness, pressure, load, and drag. Graphical results for a typical bearing are presented in the report. Project plans for the next year are discussed.

Individual differences in children's innovative problem-solving are not predicted by divergent thinking or executive functions

PubMed Central

2016-01-01

Recent studies of children's tool innovation have revealed that there is variation in children's success in middle-childhood. In two individual differences studies, we sought to identify personal characteristics that might predict success on an innovation task. In Study 1, we found that although measures of divergent thinking were related to each other they did not predict innovation success. In Study 2, we measured executive functioning including: inhibition, working memory, attentional flexibility and ill-structured problem-solving. None of these measures predicted innovation, but, innovation was predicted by children's performance on a receptive vocabulary scale that may function as a proxy for general intelligence. We did not find evidence that children's innovation was predicted by specific personal characteristics. PMID:26926280

Estimation of hydraulic jump characteristics of channels with sudden diverging side walls via SVM.

PubMed

Roushangar, Kiyoumars; Valizadeh, Reyhaneh; Ghasempour, Roghayeh

2017-10-01

Sudden diverging channels are one of the energy dissipaters which can dissipate most of the kinetic energy of the flow through a hydraulic jump. An accurate prediction of hydraulic jump characteristics is an important step in designing hydraulic structures. This paper focuses on the capability of the support vector machine (SVM) as a meta-model approach for predicting hydraulic jump characteristics in different sudden diverging stilling basins (i.e. basins with and without appurtenances). In this regard, different models were developed and tested using 1,018 experimental data. The obtained results proved the capability of the SVM technique in predicting hydraulic jump characteristics and it was found that the developed models for a channel with a central block performed more successfully than models for channels without appurtenances or with a negative step. The superior performance for the length of hydraulic jump was obtained for the model with parameters F 1 (Froude number) and (h 2- h 1 )/h 1 (h 1 and h 2 are sequent depth of upstream and downstream respectively). Concerning the relative energy dissipation and sequent depth ratio, the model with parameters F 1 and h 1 /B (B is expansion ratio) led to the best results. According to the outcome of sensitivity analysis, Froude number had the most significant effect on the modeling. Also comparison between SVM and empirical equations indicated the great performance of the SVM.

Charge-coupled-device X-ray detector performance model

NASA Technical Reports Server (NTRS)

Bautz, M. W.; Berman, G. E.; Doty, J. P.; Ricker, G. R.

1987-01-01

A model that predicts the performance characteristics of CCD detectors being developed for use in X-ray imaging is presented. The model accounts for the interactions of both X-rays and charged particles with the CCD and simulates the transport and loss of charge in the detector. Predicted performance parameters include detective and net quantum efficiencies, split-event probability, and a parameter characterizing the effective thickness presented by the detector to cosmic-ray protons. The predicted performance of two CCDs of different epitaxial layer thicknesses is compared. The model predicts that in each device incomplete recovery of the charge liberated by a photon of energy between 0.1 and 10 keV is very likely to be accompanied by charge splitting between adjacent pixels. The implications of the model predictions for CCD data processing algorithms are briefly discussed.

Performance characteristics of five triage tools for major incidents involving traumatic injuries to children.

PubMed

Price, C L; Brace-McDonnell, S J; Stallard, N; Bleetman, A; Maconochie, I; Perkins, G D

2016-05-01

Context Triage tools are an essential component of the emergency response to a major incident. Although fortunately rare, mass casualty incidents involving children are possible which mandate reliable triage tools to determine the priority of treatment. To determine the performance characteristics of five major incident triage tools amongst paediatric casualties who have sustained traumatic injuries. Retrospective observational cohort study using data from 31,292 patients aged less than 16 years who sustained a traumatic injury. Data were obtained from the UK Trauma Audit and Research Network (TARN) database. Interventions Statistical evaluation of five triage tools (JumpSTART, START, CareFlight, Paediatric Triage Tape/Sieve and Triage Sort) to predict death or severe traumatic injury (injury severity score >15). Main outcome measures Performance characteristics of triage tools (sensitivity, specificity and level of agreement between triage tools) to identify patients at high risk of death or severe injury. Of the 31,292 cases, 1029 died (3.3%), 6842 (21.9%) had major trauma (defined by an injury severity score >15) and 14,711 (47%) were aged 8 years or younger. There was variation in the performance accuracy of the tools to predict major trauma or death (sensitivities ranging between 36.4 and 96.2%; specificities 66.0-89.8%). Performance characteristics varied with the age of the child. CareFlight had the best overall performance at predicting death, with the following sensitivity and specificity (95% CI) respectively: 95.3% (93.8-96.8) and 80.4% (80.0-80.9). JumpSTART was superior for the triaging of children under 8 years; sensitivity and specificity (95% CI) respectively: 86.3% (83.1-89.5) and 84.8% (84.2-85.5). The triage tools were generally better at identifying patients who would die than those with non-fatal severe injury. This statistical evaluation has demonstrated variability in the accuracy of triage tools at predicting outcomes for children who sustain traumatic injuries. No single tool performed consistently well across all evaluated scenarios. Copyright © 2015 Elsevier Ltd. All rights reserved.

First trimester prediction of maternal glycemic status.

PubMed

Gabbay-Benziv, Rinat; Doyle, Lauren E; Blitzer, Miriam; Baschat, Ahmet A

2015-05-01

To predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics. We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state. Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC - area under the curve 0.819, CI - confidence interval 0.769-0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668-0.746). GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

Internal performance predictions for Langley scramjet engine module

NASA Technical Reports Server (NTRS)

Pinckney, S. Z.

1978-01-01

A one dimensional theoretical method for the prediction of the internal performance of a scramjet engine is presented. The effects of changes in vehicle forebody flow parameters and characteristics on predicted thrust for the scramjet engine were evaluated using this method, and results are presented. A theoretical evaluation of the effects of changes in the scramjet engine's internal parameters is also presented. Theoretical internal performance predictions, in terms thrust coefficient and specific impulse, are provided for the scramjet engine for free stream Mach numbers of 5, 6, and 7 free stream dynamic pressure of 23,940 N/sq m forebody surface angles of 4.6 deg to 14.6 deg, and fuel equivalence ratio of 1.0.

Analysis and correlation of the test data from an advanced technology rotor system

NASA Technical Reports Server (NTRS)

Jepson, D.; Moffitt, R.; Hilzinger, K.; Bissell, J.

1983-01-01

Comparisons were made of the performance and blade vibratory loads characteristics for an advanced rotor system as predicted by analysis and as measured in a 1/5 scale model wind tunnel test, a full scale model wind tunnel test and flight test. The accuracy with which the various tools available at the various stages in the design/development process (analysis, model test etc.) could predict final characteristics as measured on the aircraft was determined. The accuracy of the analyses in predicting the effects of systematic tip planform variations investigated in the full scale wind tunnel test was evaluated.

What matters after sleeve gastrectomy: patient characteristics or surgical technique?

PubMed

Dhar, Vikrom K; Hanseman, Dennis J; Watkins, Brad M; Paquette, Ian M; Shah, Shimul A; Thompson, Jonathan R

2018-03-01

The impact of operative technique on outcomes in laparoscopic sleeve gastrectomy has been explored previously; however, the relative importance of patient characteristics remains unknown. Our aim was to characterize national variability in operative technique for laparoscopic sleeve gastrectomy and determine whether patient-specific factors are more critical to predicting outcomes. We queried the database of the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program for laparoscopic sleeve gastrostomies performed in 2015 (n = 88,845). Logistic regression models were used to determine predictors of postoperative outcomes. In 2015, >460 variations of laparoscopic sleeve gastrectomy were performed based on combinations of bougie size, distance from the pylorus, use of staple line reinforcement, and oversewing of the staple line. Despite such substantial variability, technique variants were not predictive of outcomes, including perioperative morbidity, leak, or bleeding (all P ≥ .05). Instead, preoperative patient characteristics were found to be more predictive of these outcomes after laparoscopic sleeve gastrectomy. Only history of gastroesophageal disease (odds ratio 1.44, 95% confidence interval 1.08-1.91, P < .01) was associated with leak. Considerable variability exists in technique among surgeons nationally, but patient characteristics are more predictive of adverse outcomes after laparoscopic sleeve gastrectomy. Bundled payments and reimbursement policies should account for patient-specific factors in addition to current accreditation and volume thresholds when deciding risk-adjustment strategies. Copyright © 2018 Elsevier Inc. All rights reserved.

Prediction of the birch pollen season characteristics in Cracow, Poland using an 18-year data series.

PubMed

Dorota, Myszkowska

2013-03-01

The aim of the study was to construct the model forecasting the birch pollen season characteristics in Cracow on the basis of an 18-year data series. The study was performed using the volumetric method (Lanzoni/Burkard trap). The 98/95 % method was used to calculate the pollen season. The Spearman's correlation test was applied to find the relationship between the meteorological parameters and pollen season characteristics. To construct the predictive model, the backward stepwise multiple regression analysis was used including the multi-collinearity of variables. The predictive models best fitted the pollen season start and end, especially models containing two independent variables. The peak concentration value was predicted with the higher prediction error. Also the accuracy of the models predicting the pollen season characteristics in 2009 was higher in comparison with 2010. Both, the multi-variable model and one-variable model for the beginning of the pollen season included air temperature during the last 10 days of February, while the multi-variable model also included humidity at the beginning of April. The models forecasting the end of the pollen season were based on temperature in March-April, while the peak day was predicted using the temperature during the last 10 days of March.

Performance Characteristics of the Cepheid Xpert vanA Assay for Rapid Identification of Patients at High Risk for Carriage of Vancomycin-Resistant Enterococci

PubMed Central

Gilhuley, Kathleen; Cianciminio-Bordelon, Diane; Tang, Yi-Wei

2012-01-01

We compared the performance characteristics of culture and the Cepheid Xpert vanA assay for routine surveillance of vancomycin-resistant enterococci (VRE) from rectal swabs in patients at high risk for VRE carriage. The Cepheid Xpert vanA assay had a limit of detection of 100 CFU/ml and correctly detected 101 well-characterized clinical VRE isolates with no cross-reactivity in 27 non-VRE and related culture isolates. The clinical sensitivity, specificity, positive predictive value, and negative predictive value of the Xpert vanA PCR assay were 100%, 96.9%, 91.3%, and 100%, respectively, when tested on 300 consecutively collected rectal swabs. This assay provides excellent predictive values for prompt identification of VRE-colonized patients in hospitals with relatively high rates of VRE carriage. PMID:22972822

Method and system for simulating heat and mass transfer in cooling towers

DOEpatents

Bharathan, Desikan; Hassani, A. Vahab

1997-01-01

The present invention is a system and method for simulating the performance of a cooling tower. More precisely, the simulator of the present invention predicts values related to the heat and mass transfer from a liquid (e.g., water) to a gas (e.g., air) when provided with input data related to a cooling tower design. In particular, the simulator accepts input data regarding: (a) cooling tower site environmental characteristics; (b) cooling tower operational characteristics; and (c) geometric characteristics of the packing used to increase the surface area within the cooling tower upon which the heat and mass transfer interactions occur. In providing such performance predictions, the simulator performs computations related to the physics of heat and mass transfer within the packing. Thus, instead of relying solely on trial and error wherein various packing geometries are tested during construction of the cooling tower, the packing geometries for a proposed cooling tower can be simulated for use in selecting a desired packing geometry for the cooling tower.

Predicting performance on the Columbia Card Task: effects of personality characteristics, mood, and executive functions.

PubMed

Buelow, Melissa T

2015-04-01

Behavioral measures of risky decision making are frequently used by researchers and clinicians; however, most of these measures are strongly associated with personality characteristics and state mood. The present study sought to examine personality, mood, and executive function predictors of performance on a newer measure of decision making, the Columbia Card Task (CCT). Participants were 489 undergraduate students who completed either the hot or cold version of the CCT as well as measures of state mood, impulsive sensation seeking, behavioral inhibition and activation systems, and executive functions (Wisconsin Card Sort Task; Digit Span). Results indicated that performance on the CCT-cold was predicted by Wisconsin Card Sort Task errors, and Digit Span predicted the CCT-hot. In addition, significant correlations were found between the CCT information use variables and the predictor variables. Implications for the utility of the CCT as a clinical instrument and its relationship with other measures of decision making are discussed. © The Author(s) 2014.

Predicting performance of junior doctors: Association of workplace based assessment with demographic characteristics, emotional intelligence, selection scores, and undergraduate academic performance.

PubMed

Carr, Sandra E; Celenza, Antonio; Mercer, Annette M; Lake, Fiona; Puddey, Ian B

2018-01-21

Predicting workplace performance of junior doctors from before entry or during medical school is difficult and has limited available evidence. This study explored the association between selected predictor variables and workplace based performance in junior doctors during their first postgraduate year. Two cohorts of medical students (n = 200) from one university in Western Australia participated in the longitudinal study. Pearson correlation coefficients and multivariate analyses utilizing linear regression were used to assess the relationships between performance on the Junior Doctor Assessment Tool (JDAT) and its sub-components with demographic characteristics, selection scores for medical school entry, emotional intelligence, and undergraduate academic performance. Grade Point Average (GPA) at the completion of undergraduate studies had the most significant association with better performance on the overall JDAT and each subscale. Increased age was a negative predictor for junior doctor performance on the Clinical management subscale and understanding emotion was a predictor for the JDAT Communication subscale. Secondary school performance measured by Tertiary Entry Rank on entry to medical school score predicted GPA but not junior doctor performance. The GPA as a composite measure of ability and performance in medical school is associated with junior doctor assessment scores. Using this variable to identify students at risk of difficulty could assist planning for appropriate supervision, support, and training for medical graduates transitioning to the workplace.

Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.

PubMed

Lee, Wen-Chung; Wu, Yun-Chun

2016-01-01

The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.

To transfer or not to transfer? Kinematics and laterality quotient predict interlimb transfer of motor learning

PubMed Central

Lefumat, Hannah Z.; Vercher, Jean-Louis; Miall, R. Chris; Cole, Jonathan; Buloup, Frank; Bringoux, Lionel; Bourdin, Christophe

2015-01-01

Humans can remarkably adapt their motor behavior to novel environmental conditions, yet it remains unclear which factors enable us to transfer what we have learned with one limb to the other. Here we tested the hypothesis that interlimb transfer of sensorimotor adaptation is determined by environmental conditions but also by individual characteristics. We specifically examined the adaptation of unconstrained reaching movements to a novel Coriolis, velocity-dependent force field. Right-handed subjects sat at the center of a rotating platform and performed forward reaching movements with the upper limb toward flashed visual targets in prerotation, per-rotation (i.e., adaptation), and postrotation tests. Here only the dominant arm was used during adaptation and interlimb transfer was assessed by comparing performance of the nondominant arm before and after dominant-arm adaptation. Vision and no-vision conditions did not significantly influence interlimb transfer of trajectory adaptation, which on average was significant but limited. We uncovered a substantial heterogeneity of interlimb transfer across subjects and found that interlimb transfer can be qualitatively and quantitatively predicted for each healthy young individual. A classifier showed that in our study, interlimb transfer could be predicted based on the subject's task performance, most notably motor variability during learning, and his or her laterality quotient. Positive correlations suggested that variability of motor performance and lateralization of arm movement control facilitate interlimb transfer. We further show that these individual characteristics can predict the presence and the magnitude of interlimb transfer of left-handers. Overall, this study suggests that individual characteristics shape the way the nervous system can generalize motor learning. PMID:26334018

Characterization of the Space Shuttle Ascent Debris using CFD Methods

NASA Technical Reports Server (NTRS)

Murman, Scott M.; Aftosmis, Michael J.; Rogers, Stuart E.

2005-01-01

After video analysis of space shuttle flight STS-107's ascent showed that an object shed from the bipod-ramp region impacted the left wing, a transport analysis was initiated to determine a credible flight path and impact velocity for the piece of debris. This debris transport analysis was performed both during orbit, and after the subsequent re-entry accident. The analysis provided an accurate prediction of the velocity a large piece of foam bipod ramp would have as it impacted the wing leading edge. This prediction was corroborated by video analysis and fully-coupled CFD/six degree of freedom (DOF) simulations. While the prediction of impact velocity was accurate enough to predict critical damage in this case, one of the recommendations of the Columbia Accident Investigation Board (CAIB) for return-to-flight (RTF) was to analyze the complete debris environment experienced by the shuttle stack on ascent. This includes categorizing all possible debris sources, their probable geometric and aerodynamic characteristics, and their potential for damage. This paper is chiefly concerned with predicting the aerodynamic characteristics of a variety of potential debris sources (insulating foam and cork, nose-cone ablator, ice, ...) for the shuttle ascent configuration using CFD methods. These aerodynamic characteristics are used in the debris transport analysis to predict flight path, impact velocity and angle, and provide statistical variation to perform risk analyses where appropriate. The debris aerodynamic characteristics are difficult to determine using traditional methods, such as static or dynamic test data, due to the scaling requirements of simulating a typical debris event. The use of CFD methods has been a critical element for building confidence in the accuracy of the debris transport code by bridging the gap between existing aerodynamic data and the dynamics of full-scale, in-flight events.

CASPer, an online pre-interview screen for personal/professional characteristics: prediction of national licensure scores.

PubMed

Dore, Kelly L; Reiter, Harold I; Kreuger, Sharyn; Norman, Geoffrey R

2017-05-01

Typically, only a minority of applicants to health professional training are invited to interview. However, pre-interview measures of cognitive skills predict for national licensure scores (Gauer et al. in Med Educ Online 21 2016) and subsequently licensure scores predict for performance in practice (Tamblyn et al. in JAMA 288(23): 3019-3026, 2002; Tamblyn et al. in JAMA 298(9):993-1001, 2007). Assessment of personal and professional characteristics, with the same psychometric rigour of measures of cognitive abilities, are needed upstream in the selection to health profession training programs. To fill that need, Computer-based Assessment for Sampling Personal characteristics (CASPer)-an on-line, video-based screening test-was created. In this paper, we examine the correlation between CASPer and Canadian national licensure examination outcomes in 109 doctors who took CASPer at the time of selection to medical school. Specifically, CASPer scores were correlated against performance on cognitive and 'non-cognitive' subsections of both the Medical Council of Canada Qualifying Examination (MCCQE) Parts I (end of medical school) and Part II (18 months into specialty training). Unlike most national licensure exams, MCCQE has specific subcomponents examining personal/professional qualities, providing a unique opportunity for comparison. The results demonstrated moderate predictive validity of CASPer to national licensure outcomes of personal/professional characteristics three to six years after admission to medical school. These types of disattenuated correlations (r = 0.3-0.5) are not otherwise predicted by traditional screening measures. These data support the ability of a computer-based strategy to screen applicants in a feasible, reliable test, which has now demonstrated predictive validity, lending evidence of its validation for medical school applicant selection.

Identifying crash-prone traffic conditions under different weather on freeways.

PubMed

Xu, Chengcheng; Wang, Wei; Liu, Pan

2013-09-01

Understanding the relationships between traffic flow characteristics and crash risk under adverse weather conditions will help highway agencies develop proactive safety management strategies to improve traffic safety in adverse weather conditions. The primary objective is to develop separate crash risk prediction models for different weather conditions. The crash data, weather data, and traffic data used in this study were collected on the I-880N freeway in California in 2008 and 2010. This study considered three different weather conditions: clear weather, rainy weather, and reduced visibility weather. The preliminary analysis showed that there was some heterogeneity in the risk estimates for traffic flow characteristics by weather conditions, and that the crash risk prediction model for all weather conditions cannot capture the impacts of the traffic flow variables on crash risk under adverse weather conditions. The Bayesian random intercept logistic regression models were applied to link the likelihood of crash occurrence with various traffic flow characteristics under different weather conditions. The crash risk prediction models were compared to their corresponding logistic regression model. It was found that the random intercept model improved the goodness-of-fit of the crash risk prediction models. The model estimation results showed that the traffic flow characteristics contributing to crash risk were different across different weather conditions. The speed difference between upstream and downstream stations was found to be significant in each crash risk prediction model. Speed difference between upstream and downstream stations had the largest impact on crash risk in reduced visibility weather, followed by that in rainy weather. The ROC curves were further developed to evaluate the predictive performance of the crash risk prediction models under different weather conditions. The predictive performance of the crash risk model for clear weather was better than those of the crash risk models for adverse weather conditions. The research results could promote a better understanding of the impacts of traffic flow characteristics on crash risk under adverse weather conditions, which will help transportation professionals to develop better crash prevention strategies in adverse weather. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Computer modeling of a two-junction, monolithic cascade solar cell

NASA Technical Reports Server (NTRS)

Lamorte, M. F.; Abbott, D.

1979-01-01

The theory and design criteria for monolithic, two-junction cascade solar cells are described. The departure from the conventional solar cell analytical method and the reasons for using the integral form of the continuity equations are briefly discussed. The results of design optimization are presented. The energy conversion efficiency that is predicted for the optimized structure is greater than 30% at 300 K, AMO and one sun. The analytical method predicts device performance characteristics as a function of temperature. The range is restricted to 300 to 600 K. While the analysis is capable of determining most of the physical processes occurring in each of the individual layers, only the more significant device performance characteristics are presented.

Variables that influence Ironman triathlon performance – what changed in the last 35 years?

PubMed Central

Knechtle, Beat; Knechtle, Raphael; Stiefel, Michael; Zingg, Matthias Alexander; Rosemann, Thomas; Rüst, Christoph Alexander

2015-01-01

Objective This narrative review summarizes findings for Ironman triathlon performance and intends to determine potential predictor variables for Ironman race performance in female and male triathletes. Methods A literature search was performed in PubMed using the terms “Ironman”, “triathlon”, and “performance”. All resulting articles were searched for related citations. Results Age, previous experience, sex, training, origin, anthropometric and physiological characteristics, pacing, and performance in split disciplines were predictive. Differences exist between the sexes for anthropometric characteristics. The most important predictive variables for a fast Ironman race time were age of 30–35 years (women and men), a fast personal best time in Olympic distance triathlon (women and men), a fast personal best time in marathon (women and men), high volume and high speed in training where high volume was more important than high speed (women and men), low body fat, low skin-fold thicknesses and low circumference of upper arm (only men), and origin from the United States of America (women and men). Conclusion These findings may help athletes and coaches to plan an Ironman triathlon career. Age and previous experience are important to find the right point in the life of a triathlete to switch from the shorter triathlon distances to the Ironman distance. Future studies need to correlate physiological characteristics such as maximum oxygen uptake with Ironman race time to investigate their potential predictive value and to investigate socio-economic aspects in Ironman triathlon. PMID:26346992

Absorption heat pump for space applications

NASA Technical Reports Server (NTRS)

Nguyen, Tuan; Simon, William E.; Warrier, Gopinath R.; Woramontri, Woranun

1993-01-01

In the first part, the performance of the Absorption Heat Pump (AHP) with water-sulfuric acid and water-magnesium chloride as two new refrigerant-absorbent fluid pairs was investigated. A model was proposed for the analysis of the new working pairs in a heat pump system, subject to different temperature lifts. Computer codes were developed to calculate the Coefficient of Performance (COP) of the system with the thermodynamic properties of the working fluids obtained from the literature. The study shows the potential of water-sulfuric acid as a satisfactory replacement for water-lithium bromide in the targeted temperature range. The performance of the AHP using water-magnesium chloride as refrigerant-absorbent pair does not compare well with those obtained using water-lithium bromide. The second part concentrated on the design and testing of a simple ElectroHydrodynamic (EHD) Pump. A theoretical design model based on continuum electromechanics was analyzed to predict the performance characteristics of the EHD pump to circulate the fluid in the absorption heat pump. A numerical method of solving the governing equations was established to predict the velocity profile, pressure - flow rate relationship and efficiency of the pump. The predicted operational characteristics of the EHD pump is comparable to that of turbomachinery hardware; however, the overall efficiency of the electromagnetic pump is much lower. An experimental investigation to verify the numerical results was conducted. The pressure - flow rate performance characteristics and overall efficiency of the pump obtained experimentally agree well with the theoretical model.

Study of Spray Disintegration in Accelerating Flow Fields

NASA Technical Reports Server (NTRS)

Nurick, W. H.

1972-01-01

An analytical and experimental investigation was conducted to perform "proof of principlem experiments to establish the effects of propellant combustion gas velocity on propella'nt atomization characteristics. The propellants were gaseous oxygen (GOX) and Shell Wax 270. The fuel was thus the same fluid used in earlier primary cold-flow atomization studies using the frozen wax method. Experiments were conducted over a range in L* (30 to 160 inches) at two contraction ratios (2 and 6). Characteristic exhaust velocity (c*) efficiencies varied from SO to 90 percent. The hot fire experimental performance characteristics at a contraction ratio of 6.0 in conjunction with analytical predictions from the drovlet heat-up version of the Distributed Energy Release (DER) combustion computer proDam showed that the apparent initial dropsize compared well with cold-flow predictions (if adjusted for the gas velocity effects). The results also compared very well with the trend in perfomnce as predicted with the model. significant propellant wall impingement at the contraction ratio of 2.0 precluded complete evaluation of the effect of gross changes in combustion gas velocity on spray dropsize.

Prediction of Performance of Diamond Wire Saw with Respect to Texture Characteristics of Rock / Prognozowanie Wydajności Pracy Strunowej Piły Diamentowej W Odniesieniu Do Charakterystyki Tekstury Skał

NASA Astrophysics Data System (ADS)

Ghaysari, N.; Ataei, M.; Sereshki, F.; Mikaiel, R.

2012-12-01

In this study, prediction of production rate in diamond wire saw has been investigated. Performance measurements of diamond wire saw carried out in 7 different quarries of carbonate rocks in Iran. For determination textural properties, rock samples were collected from these quarries. At first, a thin section was prepared for each rock and then 5 digital photographs were taken from each section. After this, all images were digitized using AutoCAD software. Then, area, perimeter, longest diameter and shortest diameter were assigned. According to these parameters, all of the other textural characteristics and texture coefficient were determined too. The correlation between sawing rate and textural characteristics were evaluated using multiple and simple regression analyses. Then developed model was validated by P-value test. It was concluded that area, perimeter, diameter equivalent and index of grain size homogeneity are very effective on production rate. Production rate using diamond wire saw can reliably be predicted using developed model.

Characteristics of Students at Risk for Mathematics Difficulties Predicting Arithmetic Word Problem Solving Performance: The Role of Attention, Behavior, and Reading

ERIC Educational Resources Information Center

Jitendra, Asha K.; Corroy, Kelly Cozine; Dupuis, Danielle N.

2013-01-01

The purposes of this study were (a) to evaluate differences in arithmetic word problem solving between high and low at-risk students for mathematics difficulties (MD) and (b) to assess the influence of attention, behavior, reading, and socio-economic status (SES) in predicting the word problem solving performance of third-grade students with MD.…

A New Navigation Satellite Clock Bias Prediction Method Based on Modified Clock-bias Quadratic Polynomial Model

NASA Astrophysics Data System (ADS)

Wang, Y. P.; Lu, Z. P.; Sun, D. S.; Wang, N.

2016-01-01

In order to better express the characteristics of satellite clock bias (SCB) and improve SCB prediction precision, this paper proposed a new SCB prediction model which can take physical characteristics of space-borne atomic clock, the cyclic variation, and random part of SCB into consideration. First, the new model employs a quadratic polynomial model with periodic items to fit and extract the trend term and cyclic term of SCB; then based on the characteristics of fitting residuals, a time series ARIMA ~(Auto-Regressive Integrated Moving Average) model is used to model the residuals; eventually, the results from the two models are combined to obtain final SCB prediction values. At last, this paper uses precise SCB data from IGS (International GNSS Service) to conduct prediction tests, and the results show that the proposed model is effective and has better prediction performance compared with the quadratic polynomial model, grey model, and ARIMA model. In addition, the new method can also overcome the insufficiency of the ARIMA model in model recognition and order determination.

Prediction of flow duration curves for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, Maya; Taylor, Graham; M. A. Sattar, Ahmed; Gharabaghi, Bahram

2017-02-01

This study presents novel models for prediction of flow Duration Curves (FDCs) at ungauged basins using artificial neural networks (ANN) and Gene Expression Programming (GEP) trained and tested using historical flow records from 171 unregulated and 89 regulated basins across North America. For the 89 regulated basins, FDCs were generated for both before and after flow regulation. Topographic, climatic, and land use characteristics are used to develop relationships between these basin characteristics and FDC statistical distribution parameters: mean (m) and variance (ν). The two main hypotheses that flow regulation has negligible effect on the mean (m) while it the variance (ν) were confirmed. The novel GEP model that predicts the mean (GEP-m) performed very well with high R2 (0.9) and D (0.95) values and low RAE value of 0.25. The simple regression model that predicts the variance (REG-v) was developed as a function of the mean (m) and a flow regulation index (R). The measured performance and uncertainty analysis indicated that the ANN-m was the best performing model with R2 (0.97), RAE (0.21), D (0.93) and the lowest 95% confidence prediction error interval (+0.22 to +3.49). Both GEP and ANN models were most sensitive to drainage area followed by mean annual precipitation, apportionment entropy disorder index, and shape factor.

A Short Report: Word-Level Phonological and Lexical Characteristics Interact to Influence Phoneme Awareness

PubMed Central

Hogan, Tiffany P.

2010-01-01

In this study, we examined the influence of word-level phonological and lexical characteristics on early phoneme awareness. Typically-developing children, ages 61–78 months, completed a phoneme-based, odd-one-out task that included consonant-vowel-consonant word sets (e.g., “chair-chain-ship”) that varied orthogonally by a phonological characteristic, sound-contrast similarity (similar vs. dissimilar), and a lexical characteristic, neighborhood density (dense vs. sparse). In a subsample of the participants – those with the highest vocabularies – results were in line with a predicted interactive effect of phonological and lexical characteristics on phoneme awareness performance: word sets contrasting similar sounds were less likely to yield correct responses in words from sparse neighborhoods than words from dense neighborhoods. Word sets contrasting dissimilar sounds were most likely to yield correct responses regardless of the words’ neighborhood density. Based on these findings, theories of early phoneme awareness development should consider both word-level (e.g., phonological and lexical characteristics) and child-level (e.g., vocabulary knowledge) influences on phoneme awareness performance. Attention to these word-level item influences is predicted to result in more sensitive and specific measures of reading risk. PMID:20574064

Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

NASA Technical Reports Server (NTRS)

Swanson, David J.

1990-01-01

The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

PM-1 NUCLEAR POWER PROGRAM. VOLUME II. PLANT PERFORMANCE STUDIES. Final Periodic Report, September 1, 1962 to December 31, 1962

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

None

1963-04-01

Data obtained during the performance testing of the PM-1 plant were compiled and evaluated. The plant powers an Air Defense Command radar station located at Sundance, Wyoming, and is required to supply extremely high-quality electrical power (minimum of frequency and voltage fluctuations) even during severe load transients. The data obtained were compiled into the following format: (1) operating requirements; (2) startup requirements; (3) plant as an energy source; (4) plant radiation levels and health physics; (5) plant instrumentation and control; (6) reactor characteristics; (7) primary system characteristics; (8) secondary system characteristics; and (9) malfunction reports. It was concluded from themore » data that the plant performance in general meets or exceeds specification. Transient and steady-state electrical fluctuations are well within specified limitations. Heat balance data for both the primary and secondary system agree reasonably well with design predictions. Radiation levels are below those anticipated. Coolant activity in the primary system is approximately at anticipated levels; secondary system coolant activity is negligible. The core life was re-estimated based on asbuilt core characteristics. A lifetime of 16.6 Mw-yr is predicted. (auth)« less

Performance evaluation of Space Shuttle SRB parachutes from air drop and scaled model wind tunnel tests. [Solid Rocket Booster recovery system

NASA Technical Reports Server (NTRS)

Moog, R. D.; Bacchus, D. L.; Utreja, L. R.

1979-01-01

The aerodynamic performance characteristics have been determined for the Space Shuttle Solid Rocket Booster drogue, main, and pilot parachutes. The performance evaluation on the 20-degree conical ribbon parachutes is based primarily on air drop tests of full scale prototype parachutes. In addition, parametric wind tunnel tests were performed and used in parachute configuration development and preliminary performance assessments. The wind tunnel test data are compared to the drop test results and both sets of data are used to determine the predicted performance of the Solid Rocket Booster flight parachutes. Data from other drop tests of large ribbon parachutes are also compared with the Solid Rocket Booster parachute performance characteristics. Parameters assessed include full open terminal drag coefficients, reefed drag area, opening characteristics, clustering effects, and forebody interference.

Predicting diagnostic error in Radiology via eye-tracking and image analytics: Application in mammography

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

Voisin, Sophie; Pinto, Frank M; Morin-Ducote, Garnetta

2013-01-01

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels. Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from 4 Radiology residents and 2 breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADsmore » images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated. Results: Diagnostic error can be predicted reliably by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model (AUC=0.79). Personalized user modeling was far more accurate for the more experienced readers (average AUC of 0.837 0.029) than for the less experienced ones (average AUC of 0.667 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features. Conclusions: Diagnostic errors in mammography can be predicted reliably by leveraging the radiologists gaze behavior and image content.« less

COMSAC: Computational Methods for Stability and Control. Part 2

NASA Technical Reports Server (NTRS)

Fremaux, C. Michael (Compiler); Hall, Robert M. (Compiler)

2004-01-01

The unprecedented advances being made in computational fluid dynamic (CFD) technology have demonstrated the powerful capabilities of codes in applications to civil and military aircraft. Used in conjunction with wind-tunnel and flight investigations, many codes are now routinely used by designers in diverse applications such as aerodynamic performance predictions and propulsion integration. Typically, these codes are most reliable for attached, steady, and predominantly turbulent flows. As a result of increasing reliability and confidence in CFD, wind-tunnel testing for some new configurations has been substantially reduced in key areas, such as wing trade studies for mission performance guarantees. Interest is now growing in the application of computational methods to other critical design challenges. One of the most important disciplinary elements for civil and military aircraft is prediction of stability and control characteristics. CFD offers the potential for significantly increasing the basic understanding, prediction, and control of flow phenomena associated with requirements for satisfactory aircraft handling characteristics.

Users' Manual for Computer Code SPIRALI Incompressible, Turbulent Spiral Grooved Cylindrical and Face Seals

NASA Technical Reports Server (NTRS)

Walowit, Jed A.; Shapiro, Wilbur

2005-01-01

The SPIRALI code predicts the performance characteristics of incompressible cylindrical and face seals with or without the inclusion of spiral grooves. Performance characteristics include load capacity (for face seals), leakage flow, power requirements and dynamic characteristics in the form of stiffness, damping and apparent mass coefficients in 4 degrees of freedom for cylindrical seals and 3 degrees of freedom for face seals. These performance characteristics are computed as functions of seal and groove geometry, load or film thickness, running and disturbance speeds, fluid viscosity, and boundary pressures. A derivation of the equations governing the performance of turbulent, incompressible, spiral groove cylindrical and face seals along with a description of their solution is given. The computer codes are described, including an input description, sample cases, and comparisons with results of other codes.

Predicting driving performance in older adults: we are not there yet!

PubMed

Bédard, Michel; Weaver, Bruce; Darzins, Peteris; Porter, Michelle M

2008-08-01

We set up this study to determine the predictive value of approaches for which a statistical association with driving performance has been documented. We determined the statistical association (magnitude of association and probability of occurrence by chance alone) between four different predictors (the Mini-Mental State Examination, Trails A test, Useful Field of View [UFOV], and a composite measure of past driving incidents) and driving performance. We then explored the predictive value of these measures with receiver operating characteristic (ROC) curves and various cutoff values. We identified associations between the predictors and driving performance well beyond the play of chance (p < .01). Nonetheless, the predictors had limited predictive value with areas under the curve ranging from .51 to .82. Statistical associations are not sufficient to infer adequate predictive value, especially when crucial decisions such as whether one can continue driving are at stake. The predictors we examined have limited predictive value if used as stand-alone screening tests.

Prediction of subcellular localization of eukaryotic proteins using position-specific profiles and neural network with weighted inputs.

PubMed

Zou, Lingyun; Wang, Zhengzhi; Huang, Jiaomin

2007-12-01

Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles (PSP) have been introduced as important characteristics of proteins in this article. In this study, to obtain position-specific profiles, the Position Specific Iterative-Basic Local Alignment Search Tool (PSI-BLAST) has been used to search for protein sequences in a database. Position-specific scoring matrices are extracted from the profiles as one class of characteristics. Four-part amino acid compositions and 1st-7th order dipeptide compositions have also been calculated as the other two classes of characteristics. Therefore, twelve characteristic vectors are extracted from each of the protein sequences. Next, the characteristic vectors are weighed by a simple weighing function and inputted into a BP neural network predictor named PSP-Weighted Neural Network (PSP-WNN). The Levenberg-Marquardt algorithm is employed to adjust the weight matrices and thresholds during the network training instead of the error back propagation algorithm. With a jackknife test on the RH2427 dataset, PSP-WNN has achieved a higher overall prediction accuracy of 88.4% rather than the prediction results by the general BP neural network, Markov model, and fuzzy k-nearest neighbors algorithm on this dataset. In addition, the prediction performance of PSP-WNN has been evaluated with a five-fold cross validation test on the PK7579 dataset and the prediction results have been consistently better than those of the previous method on the basis of several support vector machines, using compositions of both amino acids and amino acid pairs. These results indicate that PSP-WNN is a powerful tool for subcellular localization prediction. At the end of the article, influences on prediction accuracy using different weighting proportions among three characteristic vector categories have been discussed. An appropriate proportion is considered by increasing the prediction accuracy.

Assessing the sensitivity and robustness of prediction models for apple firmness using spectral scattering technique

USDA-ARS?s Scientific Manuscript database

Spectral scattering is useful for nondestructive sensing of fruit firmness. Prediction models, however, are typically built using multivariate statistical methods such as partial least squares regression (PLSR), whose performance generally depends on the characteristics of the data. The aim of this ...

Personal Self-Regulation and Regulatory Teaching to Predict Performance and Academic Confidence: New Evidence for the DEDEPRO Model™

ERIC Educational Resources Information Center

de la Fuente, Jesús; Justicia, Fernando; Sander, Paul; Cardelle-Elawar, Maria

2014-01-01

Introduction: The 3P and DEDEPRO Models predict interactive relationships among "presage," "process," and "product" variables through teaching and learning of self-regulation. The DEDEPRO Model has established different possibilities for interaction between student characteristics of self-regulation and external…

Comparison of Linear Induction Motor Theories for the LIMRV and TLRV Motors

DOT National Transportation Integrated Search

1978-01-01

The Oberretl, Yamamura, and Mosebach theories of the linear induction motor are described and also applied to predict performance characteristics of the TLRV & LIMRV linear induction motors. The effect of finite motor width and length on performance ...

Development of an analytical method to predict helicopter main rotor performance in icing conditions

NASA Technical Reports Server (NTRS)

Britton, Randall K.

1992-01-01

Historically, certification of a helicopter for flight into known icing conditions was a problem. This is because of the current emphasis on flight testing for verification of system performance. Flight testing in icing conditions is difficult because, in addition to being dangerous and expensive, many times conditions which are sought after cannot be readily found in nature. The problem is compounded for helicopters because of their small range in comparison to many fixed wing aircraft. Thus, helicopters are forced to wait for conditions to occur in a certain region rather than seeking them out. These and other drawbacks to flight testing prompted extreme interest in developing validated alternatives to flight testing. One such alternative is theoretical prediction. It is desirable to have the ability to predict how a helicopter will perform when subjected to icing conditions. Herein, calculations are restricted to the main rotor, and are illustrated. The computational tool used to obtain performance is the lifting line analysis of B65. B65 incorporates experimental data into data banks in order to determine the section lift, drag, and moment characteristics of various airfoils at different Mach numbers and angles of attack. The local flow angle is calculated at user specified radial locations. This flow angle, along with the local Mach number is then cross referenced with the airfoil tables to obtain the local section characteristics. The local characteristics are then integrated together to obtain the entire rotor attributes. Once the clean performance is known, characterization of the type and shape of ice which accretes on the rotor blades is obtained using the analysis of LEWICE. The Interactive Boundary Layer (IBL) method then calculates the 2-D characteristics of the iced airfoil for input into the airfoil data bank of B65. Calculations are restricted to natural ice shedding and it is assumed that no de-icing takes place. Once the new lift, drag, and moment characteristics are known for the entire blade radius, this information is fed into B65, where the iced performance is then calculated.

The National Football League (NFL) combine: does normalized data better predict performance in the NFL draft?

PubMed

Robbins, Daniel W

2010-11-01

The objective of this study was to investigate the predictive ability of National Football League (NFL) combine physical test data to predict draft order over the years 2005-2009. The NFL combine provides a setting in which NFL personnel can evaluate top draft prospects. The predictive ability of combine data in its raw form and when normalized in both a ratio and allometric manner was examined for 17 positions. Data from 8 combine physical performance tests were correlated with draft order to determine the direction and strength of relationship between the various combine measures and draft order. Players invited to the combine and subsequently drafted in the same year (n = 1,155) were included in the study. The primary finding was that performance in the combine physical test battery, whether normalized or not, has little association with draft success. In terms of predicting draft order from outcomes of the 8 tests making up the combine battery, normalized data provided no advantage over raw data. Of the 8 performance measures investigated, straight sprint time and jumping ability seem to hold the most weight with NFL personnel responsible for draft decisions. The NFL should consider revising the combine test battery to reflect the physical characteristics it deems important. It may be that NFL teams are more interested in attributes other than the purely physical traits reflected in the combine test battery. Players with aspirations of entering the NFL may be well advised to develop mental and technical skills in addition to developing the physical characteristics necessary to optimize performance.

Performance and combustion characteristics of direct-injection stratified-charge rotary engines

NASA Technical Reports Server (NTRS)

Nguyen, Hung Lee

1987-01-01

Computer simulations of the direct-injection stratified-charge (DISC) Wankel engine have been used to calculate heat release rates and performance and efficiency characteristics of the 1007R engine. Engine pressure data have been used in a heat release analysis to study the effects of heat transfer, leakage, and crevice flows. Predicted engine performance data are compared with experimental test data over a range of engine speeds and loads. An examination of methods to improve the performance of the Wankel engine with faster combustion, reduced leakage, higher compression ratio, and turbocharging is presented.

To transfer or not to transfer? Kinematics and laterality quotient predict interlimb transfer of motor learning.

PubMed

Lefumat, Hannah Z; Vercher, Jean-Louis; Miall, R Chris; Cole, Jonathan; Buloup, Frank; Bringoux, Lionel; Bourdin, Christophe; Sarlegna, Fabrice R

2015-11-01

Humans can remarkably adapt their motor behavior to novel environmental conditions, yet it remains unclear which factors enable us to transfer what we have learned with one limb to the other. Here we tested the hypothesis that interlimb transfer of sensorimotor adaptation is determined by environmental conditions but also by individual characteristics. We specifically examined the adaptation of unconstrained reaching movements to a novel Coriolis, velocity-dependent force field. Right-handed subjects sat at the center of a rotating platform and performed forward reaching movements with the upper limb toward flashed visual targets in prerotation, per-rotation (i.e., adaptation), and postrotation tests. Here only the dominant arm was used during adaptation and interlimb transfer was assessed by comparing performance of the nondominant arm before and after dominant-arm adaptation. Vision and no-vision conditions did not significantly influence interlimb transfer of trajectory adaptation, which on average was significant but limited. We uncovered a substantial heterogeneity of interlimb transfer across subjects and found that interlimb transfer can be qualitatively and quantitatively predicted for each healthy young individual. A classifier showed that in our study, interlimb transfer could be predicted based on the subject's task performance, most notably motor variability during learning, and his or her laterality quotient. Positive correlations suggested that variability of motor performance and lateralization of arm movement control facilitate interlimb transfer. We further show that these individual characteristics can predict the presence and the magnitude of interlimb transfer of left-handers. Overall, this study suggests that individual characteristics shape the way the nervous system can generalize motor learning. Copyright © 2015 the American Physiological Society.

Multi-modal imaging predicts memory performance in normal aging and cognitive decline.

PubMed

Walhovd, K B; Fjell, A M; Dale, A M; McEvoy, L K; Brewer, J; Karow, D S; Salmon, D P; Fennema-Notestine, C

2010-07-01

This study (n=161) related morphometric MR imaging, FDG-PET and APOE genotype to memory scores in normal controls (NC), mild cognitive impairment (MCI) and Alzheimer's disease (AD). Stepwise regression analyses focused on morphometric and metabolic characteristics of the episodic memory network: hippocampus, entorhinal, parahippocampal, retrosplenial, posterior cingulate, precuneus, inferior parietal, and lateral orbitofrontal cortices. In NC, hippocampal metabolism predicted learning; entorhinal metabolism predicted recognition; and hippocampal metabolism predicted recall. In MCI, thickness of the entorhinal and precuneus cortices predicted learning, while parahippocampal metabolism predicted recognition. In AD, posterior cingulate cortical thickness predicted learning, while APOE genotype predicted recognition. In the total sample, hippocampal volume and metabolism, cortical thickness of the precuneus, and inferior parietal metabolism predicted learning; hippocampal volume and metabolism, parahippocampal thickness and APOE genotype predicted recognition. Imaging methods appear complementary and differentially sensitive to memory in health and disease. Medial temporal and parietal metabolism and morphometry best explained memory variance. Medial temporal characteristics were related to learning, recall and recognition, while parietal structures only predicted learning. Copyright 2008. Published by Elsevier Inc.

Performance evaluation of 4 measuring methods of ground-glass opacities for predicting the 5-year relapse-free survival of patients with peripheral nonsmall cell lung cancer: a multicenter study.

PubMed

Kakinuma, Ryutaro; Kodama, Ken; Yamada, Kouzo; Yokoyama, Akira; Adachi, Shuji; Mori, Kiyoshi; Fukuyama, Yasuro; Fukuda, Yasuro; Kuriyama, Keiko; Oda, Junichi; Oda, Junji; Noguchi, Masayuki; Matsuno, Yoshihiro; Yokose, Tomoyuki; Ohmatsu, Hironobu; Nishiwaki, Yutaka

2008-01-01

To evaluate the performance of 4 methods of measuring the extent of ground-glass opacities as a means of predicting the 5-year relapse-free survival of patients with peripheral nonsmall cell lung cancer (NSLC). Ground-glass opacities on thin-section computed tomographic images of 120 peripheral NSLCs were measured at 7 medical institutions by the length, area, modified length, and vanishing ratio (VR) methods. The performance (Az) of each method in predicting the 5-year relapse-free survival was evaluated using receiver operating characteristic analysis. The mean Az value obtained by the length, area, modified length, and VR methods in the receiver operating characteristic analyses was 0.683, 0.702, 0.728, and 0.784, respectively. The differences between the mean Az value obtained by the VR method and by the other 3 methods were significant. Vanishing ratio method was the most accurate predictor of the 5-year relapse-free survival of patients with peripheral NSLC.

Predicting the educational performance of Isfahan University students of medical sciences based on their behaviour profile, mental health and demographic characteristic.

PubMed

Samouei, Rahele; Fooladvand, Maryam; Janghorban, Shahla; Khorvash, Fariba

2015-01-01

The issue of students' academic failure is one of the most important educational, economic, and social issues. Cognizance of the factors related to academic downfall is so efficient in its prevention and control and leads to protecting governmental assets and labor force. In order to achieve this goal, this study intends to determine the predictive factors of the students' academic performance in Isfahan University of Medical Sciences in terms of their personality profile, mental health, and their demographic characteristics. This study was a descriptive-correlation study on 771 students who entered Isfahan University of Medical Sciences between 2005 and 2007. The information was gathered through using the students' educational and clinical files (for measuring personality characteristics and mental health) and SAMA Software (To get the mean scores). Minnesota Multiphasic Personality Inventory short form and General Health Questionnaire were used for collecting clinical data. The data were analyzed using SPSS 15 (stepwise regression coefficient, variance analysis, Student's t-test, and Spearman correlation coefficient). The results showed that the aforementioned students obtained a normal average for their personality profile and mental health indicators. Of all the reviewed variables, education, age, gender, depression, and hypochondria were the predictive factors of the students' educational performance. It could be concluded that some of the personality features, mental health indicators, and personality profile play such a significant role in the students' educational life that the disorder in any of them affects the students' educational performance and academic failure.

[Research on fast detecting tomato seedlings nitrogen content based on NIR characteristic spectrum selection].

PubMed

Wu, Jing-zhu; Wang, Feng-zhu; Wang, Li-li; Zhang, Xiao-chao; Mao, Wen-hua

2015-01-01

In order to improve the accuracy and robustness of detecting tomato seedlings nitrogen content based on near-infrared spectroscopy (NIR), 4 kinds of characteristic spectrum selecting methods were studied in the present paper, i. e. competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variables elimination (MCUVE), backward interval partial least squares (BiPLS) and synergy interval partial least squares (SiPLS). There were totally 60 tomato seedlings cultivated at 10 different nitrogen-treatment levels (urea concentration from 0 to 120 mg . L-1), with 6 samples at each nitrogen-treatment level. They are in different degrees of over nitrogen, moderate nitrogen, lack of nitrogen and no nitrogen status. Each sample leaves were collected to scan near-infrared spectroscopy from 12 500 to 3 600 cm-1. The quantitative models based on the above 4 methods were established. According to the experimental result, the calibration model based on CARS and MCUVE selecting methods show better performance than those based on BiPLS and SiPLS selecting methods, but their prediction ability is much lower than that of the latter. Among them, the model built by BiPLS has the best prediction performance. The correlation coefficient (r), root mean square error of prediction (RMSEP) and ratio of performance to standard derivate (RPD) is 0. 952 7, 0. 118 3 and 3. 291, respectively. Therefore, NIR technology combined with characteristic spectrum selecting methods can improve the model performance. But the characteristic spectrum selecting methods are not universal. For the built model based or single wavelength variables selection is more sensitive, it is more suitable for the uniform object. While the anti-interference ability of the model built based on wavelength interval selection is much stronger, it is more suitable for the uneven and poor reproducibility object. Therefore, the characteristic spectrum selection will only play a better role in building model, combined with the consideration of sample state and the model indexes.

Method for Predicting the Energy Characteristics of Li-Ion Cells Designed for High Specific Energy

NASA Technical Reports Server (NTRS)

Bennett, William, R.

2012-01-01

Novel electrode materials with increased specific capacity and voltage performance are critical to the NASA goals for developing Li-ion batteries with increased specific energy and energy density. Although performance metrics of the individual electrodes are critically important, a fundamental understanding of the interactions of electrodes in a full cell is essential to achieving the desired performance, and for establishing meaningful goals for electrode performance in the first place. This paper presents design considerations for matching positive and negative electrodes in a viable design. Methods for predicting cell-level performance, based on laboratory data for individual electrodes, are presented and discussed.

The "surprise question" for predicting death in seriously ill patients: a systematic review and meta-analysis.

PubMed

Downar, James; Goldman, Russell; Pinto, Ruxandra; Englesakis, Marina; Adhikari, Neill K J

2017-04-03

The surprise question - "Would I be surprised if this patient died in the next 12 months?" - has been used to identify patients at high risk of death who might benefit from palliative care services. Our objective was to systematically review the performance characteristics of the surprise question in predicting death. We searched multiple electronic databases from inception to 2016 to identify studies that prospectively screened patients with the surprise question and reported on death at 6 to 18 months. We constructed models of hierarchical summary receiver operating characteristics (sROCs) to determine prognostic performance. Sixteen studies (17 cohorts, 11 621 patients) met the selection criteria. For the outcome of death at 6 to 18 months, the pooled prognostic characteristics were sensitivity 67.0% (95% confidence interval [CI] 55.7%-76.7%), specificity 80.2% (73.3%-85.6%), positive likelihood ratio 3.4 (95% CI 2.8-4.1), negative likelihood ratio 0.41 (95% CI 0.32-0.54), positive predictive value 37.1% (95% CI 30.2%-44.6%) and negative predictive value 93.1% (95% CI 91.0%-94.8%). The surprise question had worse discrimination in patients with noncancer illness (area under sROC curve 0.77 [95% CI 0.73-0.81]) than in patients with cancer (area under sROC curve 0.83 [95% CI 0.79-0.87; p = 0.02 for difference]). Most studies had a moderate to high risk of bias, often because they had a low or unknown participation rate or had missing data. The surprise question performs poorly to modestly as a predictive tool for death, with worse performance in noncancer illness. Further studies are needed to develop accurate tools to identify patients with palliative care needs and to assess the surprise question for this purpose. © 2017 Canadian Medical Association or its licensors.

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE PAGES

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.; ...

2017-11-21

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

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

Thomas, Edward V.; Lewis, John R.; Anderson-Cook, Christine M.

nverse prediction is important in a wide variety of scientific and engineering contexts. One might use inverse prediction to predict fundamental properties/characteristics of an object using measurements obtained from it. This can be accomplished by “inverting” parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are science based; but often, forward models are empirically based, using the results of experimentation. For empirically-based forward models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). While nature dictates the causal relationship between factorsmore » and responses, experimenters can influence control of the type, accuracy, and precision of forward models that can be constructed via selection of factors, factor levels, and the set of trials that are performed. Whether the forward models are based on science, experiments or both, researchers can influence the ability to perform inverse prediction by selecting informative response variables. By using an errors-in-variables framework for inverse prediction, this paper shows via simple analysis and examples how the capability of a multivariate response (with respect to being informative and discriminating) can vary depending on how well the various responses complement one another over the range of the factor-space of interest. Insights derived from this analysis could be useful for selecting a set of response variables among candidates in cases where the number of response variables that can be acquired is limited by difficulty, expense, and/or availability of material.« less

Prospective Cohort Study Evaluating the Prognostic Value of Simple EEG Parameters in Postanoxic Coma.

PubMed

Azabou, Eric; Fischer, Catherine; Mauguiere, François; Vaugier, Isabelle; Annane, Djillali; Sharshar, Tarek; Lofaso, Fréderic

2016-01-01

We prospectively studied early bedside standard EEG characteristics in 61 acute postanoxic coma patients. Five simple EEG features, namely, isoelectric, discontinuous, nonreactive to intense auditory and nociceptive stimuli, dominant delta frequency, and occurrence of paroxysms were classified yes or no. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) of each of these variables for predicting an unfavorable outcome, defined as death, persistent vegetative state, minimally conscious state, or severe neurological disability, as assessed 1 year after coma onset were computed as well as Synek's score. The outcome was unfavorable in 56 (91.8%) patients. Sensitivity, specificity, PPV, NPV, and AUC of nonreactive EEG for predicting an unfavorable outcome were 84%, 80%, 98%, 31%, and 0.82, respectively; and were all very close to the ones of Synek score>3, which were 82%, 80%, 98%, 29%, and 0.81, respectively. Specificities for predicting an unfavorable outcome were 100% for isoelectric, discontinuous, or dominant delta activity EEG. These 3 last features were constantly associated to unfavorable outcome. Absent EEG reactivity strongly predicted an unfavorable outcome in postanoxic coma, and performed as accurate as a Synek score>3. Analyzing characteristics of some simple EEG features may easily help nonneurophysiologist physicians to investigate prognostic issue of postanoxic coma patient. In this study (a) discontinuous, isoelectric, or delta-dominant EEG were constantly associated with unfavorable outcome and (b) nonreactive EEG performed prognostic as accurate as a Synek score>3. © EEG and Clinical Neuroscience Society (ECNS) 2015.

Forecasting electricity usage using univariate time series models

NASA Astrophysics Data System (ADS)

Hock-Eam, Lim; Chee-Yin, Yip

2014-12-01

Electricity is one of the important energy sources. A sufficient supply of electricity is vital to support a country's development and growth. Due to the changing of socio-economic characteristics, increasing competition and deregulation of electricity supply industry, the electricity demand forecasting is even more important than before. It is imperative to evaluate and compare the predictive performance of various forecasting methods. This will provide further insights on the weakness and strengths of each method. In literature, there are mixed evidences on the best forecasting methods of electricity demand. This paper aims to compare the predictive performance of univariate time series models for forecasting the electricity demand using a monthly data of maximum electricity load in Malaysia from January 2003 to December 2013. Results reveal that the Box-Jenkins method produces the best out-of-sample predictive performance. On the other hand, Holt-Winters exponential smoothing method is a good forecasting method for in-sample predictive performance.

Experimental and artificial neural network based prediction of performance and emission characteristics of DI diesel engine using Calophyllum inophyllum methyl ester at different nozzle opening pressure

NASA Astrophysics Data System (ADS)

Vairamuthu, G.; Thangagiri, B.; Sundarapandian, S.

2018-01-01

The present work investigates the effect of varying Nozzle Opening Pressures (NOP) from 220 bar to 250 bar on performance, emissions and combustion characteristics of Calophyllum inophyllum Methyl Ester (CIME) in a constant speed, Direct Injection (DI) diesel engine using Artificial Neural Network (ANN) approach. An ANN model has been developed to predict a correlation between specific fuel consumption (SFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), Unburnt hydrocarbon (UBHC), CO, CO2, NOx and smoke density using load, blend (B0 and B100) and NOP as input data. A standard Back-Propagation Algorithm (BPA) for the engine is used in this model. A Multi Layer Perceptron network (MLP) is used for nonlinear mapping between the input and the output parameters. An ANN model can predict the performance of diesel engine and the exhaust emissions with correlation coefficient (R2) in the range of 0.98-1. Mean Relative Errors (MRE) values are in the range of 0.46-5.8%, while the Mean Square Errors (MSE) are found to be very low. It is evident that the ANN models are reliable tools for the prediction of DI diesel engine performance and emissions. The test results show that the optimum NOP is 250 bar with B100.

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.

Determining a Model to Predict Hispanic Preservice Teachers' Success on the Texas Examination of Educator Standards

ERIC Educational Resources Information Center

Zhang, Zhidong; Telese, James

2012-01-01

In this article, we report the regression relations between preservice teachers' academic characteristics and their performance on the Texas Examination of Educator Standards. These academic characteristics include grade point average, reading ability, and critical thinking. The studies indicate that the critical thinking was the best predictor…

Pilot/vehicle model analysis of visual and motion cue requirements in flight simulation. [helicopter hovering

NASA Technical Reports Server (NTRS)

Baron, S.; Lancraft, R.; Zacharias, G.

1980-01-01

The optimal control model (OCM) of the human operator is used to predict the effect of simulator characteristics on pilot performance and workload. The piloting task studied is helicopter hover. Among the simulator characteristics considered were (computer generated) visual display resolution, field of view and time delay.

Characteristics of 15-Year-Old Students Predicting Scientific Literacy Skills in Turkey

ERIC Educational Resources Information Center

Demir, Ergül

2016-01-01

Since 2003, Turkey regularly participates in PISA. According to the PISA 2012 results, 15-year-old students in Turkey performed below both OECD countries and participating countries. Defining the relations between students' characteristics and their scientific literacy skills is thought to provide deeper understanding for the nature of this…

Spectral characteristics of mid-latitude continental convection from a global variable-resolution Voronoi-mesh atmospheric model

NASA Astrophysics Data System (ADS)

Wong, M.; Skamarock, W. C.

2015-12-01

Global numerical weather forecast tests were performed using the global nonhydrostatic atmospheric model, Model for Prediction Across Scales (MPAS), for the NOAA Storm Prediction Center 2015 Spring Forecast Experiment (May 2015) and the Plains Elevated Convection at Night (PECAN) field campaign (June to mid-July 2015). These two sets of forecasts were performed on 50-to-3 km and 15-to-3 km smoothly-varying horizontal meshes, respectively. Both variable-resolution meshes have nominal convection-permitting 3-km grid spacing over the entire continental US. Here we evaluate the limited-area (vs. global) spectra from these NWP simulations. We will show the simulated spectral characteristics of total kinetic energy, vertical velocity variance, and precipitation during these spring and summer periods when diurnal continental convection is most active over central US. Spectral characteristics of a high-resolution global 3-km simulation (essentially no nesting) from the 20 May 2013 Moore, OK tornado case are also shown. These characteristics include spectral scaling, shape, and anisotropy, as well as the effective resolution of continental convection representation in MPAS.

Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

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

Voisin, Sophie; Tourassi, Georgia D.; Pinto, Frank

2013-10-15

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS imagesmore » features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content.« less

Predicting Students' Academic Performance Based on School and Socio-Demographic Characteristics

ERIC Educational Resources Information Center

Thiele, Tamara; Singleton, Alexander; Pope, Daniel; Stanistreet, Debbi

2016-01-01

Students' trajectories into university are often uniquely dependent on school qualifications though these alone are limited as predictors of academic potential. This study endorses this, examining associations between school grades, school type, school performance, socio-economic deprivation, neighbourhood participation, sex and academic…

[Determinants of task preferences when performance is indicative of individual characteristics: self-assessment motivation and self-verification motivation].

PubMed

Numazaki, M; Kudo, E

1995-04-01

The present study was conducted to examine determinants of information-gathering behavior with regard to one's own characteristics. Four tasks with different self-congruent and incongruent diagnosticity were presented to subjects. As self-assessment theory predicted, high diagnostic tasks were preferred to low tasks. And as self-verification theory predicted, self-congruent diagnosticity had a stronger effect on task preference than self-incongruent diagnosticity. In addition, subjects who perceived the relevant characteristics important inclined to choose self-assessment behavior more than who did not. Also, subjects who were certain of their self-concept inclined to choose self-verification behavior more than who were not. These results suggest that both self-assessment and self-verification motivations play important roles in information-gathering behavior regarding one's characteristics, and strength of the motivations is determined by the importance of relevant characteristics or the certainty of self-concept.

Robust Prediction for Stationary Processes. 2D Enriched Version.

DTIC Science & Technology

1987-11-24

the absence of data outliers. Important performance characteristics studied include the breakdown point and the influence function . Included are numerical results, for some autoregressive nominal processes.

The correlation between fundamental characteristics and first-time performance in laparoscopic tasks.

PubMed

Harrington, Cuan M; Bresler, Richard; Ryan, Donncha; Dicker, Patrick; Traynor, Oscar; Kavanagh, Dara O

2018-04-01

The ability of characteristics to predict first time performance in laparoscopic tasks is not well described. Videogame experience predicts positive performance in laparoscopic experiences but its mechanism and confounding-association with aptitude remains to be elucidated. This study sought to evaluate for innate predictors of laparoscopic performance in surgically naive individuals with minimal videogame exposure. Participants with no prior laparoscopic exposure and minimal videogaming experience were recruited consecutively from preclinical years at a medical university. Participants completed four visuospatial, one psychomotor aptitude test and an electronic survey, followed by four laparoscopic tasks on a validated Virtual Reality simulator (LAP Mentor™). Twenty eligible individuals participated with a mean age of 20.8 (±3.8) years. Significant intra-aptitude performance correlations were present amongst 75% of the visuospatial tests. These visuospatial aptitudes correlated significantly with multiple laparoscopic task metrics: number of movements of a dominant instrument (r s  ≥ -0.46), accuracy rate of clip placement (r s  ≥ 0.50) and time taken (r s  ≥ -0.47) (p < 0.05). Musical Instrument experience predicted higher average speed of instruments (r s  ≥ 0.47) (p < 0.05). Participant's revised competitive index level predicted lower proficiency in laparoscopic metrics including: pathlength, economy and number of movements of dominant instrument (r s  ≥ 0.46) (p < 0.05). Multiple visuospatial aptitudes and innate competitive level influenced baseline laparoscopic performances across several tasks in surgically naïve individuals. Copyright © 2017 Elsevier Inc. All rights reserved.

Delirium prediction in the intensive care unit: comparison of two delirium prediction models.

PubMed

Wassenaar, Annelies; Schoonhoven, Lisette; Devlin, John W; van Haren, Frank M P; Slooter, Arjen J C; Jorens, Philippe G; van der Jagt, Mathieu; Simons, Koen S; Egerod, Ingrid; Burry, Lisa D; Beishuizen, Albertus; Matos, Joaquim; Donders, A Rogier T; Pickkers, Peter; van den Boogaard, Mark

2018-05-05

Accurate prediction of delirium in the intensive care unit (ICU) may facilitate efficient use of early preventive strategies and stratification of ICU patients by delirium risk in clinical research, but the optimal delirium prediction model to use is unclear. We compared the predictive performance and user convenience of the prediction  model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) in ICU patients and determined the value of a two-stage calculation. This 7-country, 11-hospital, prospective cohort study evaluated consecutive adults admitted to the ICU who could be reliably assessed for delirium using the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist. The predictive performance of the models was measured using the area under the receiver operating characteristic curve. Calibration was assessed graphically. A physician questionnaire evaluated user convenience. For the two-stage calculation we used E-PRE-DELIRIC immediately after ICU admission and updated the prediction using PRE-DELIRIC after 24 h. In total 2178 patients were included. The area under the receiver operating characteristic curve was significantly greater for PRE-DELIRIC (0.74 (95% confidence interval 0.71-0.76)) compared to E-PRE-DELIRIC (0.68 (95% confidence interval 0.66-0.71)) (z score of - 2.73 (p < 0.01)). Both models were well-calibrated. The sensitivity improved when using the two-stage calculation in low-risk patients. Compared to PRE-DELIRIC, ICU physicians (n = 68) rated the E-PRE-DELIRIC model more feasible. While both ICU delirium prediction models have moderate-to-good performance, the PRE-DELIRIC model predicts delirium better. However, ICU physicians rated the user convenience of E-PRE-DELIRIC superior to PRE-DELIRIC. In low-risk patients the delirium prediction further improves after an update with the PRE-DELIRIC model after 24 h. ClinicalTrials.gov, NCT02518646 . Registered on 21 July 2015.

Performance characteristics of broth-only cultures after revision total joint arthroplasty.

PubMed

Smith, Eric B; Cai, Jenny; Wynne, Rachael; Maltenfort, Mitchell; Good, Robert P

2014-11-01

Surgeons frequently obtain intraoperative cultures at the time of revision total joint arthroplasty. The use of broth or liquid medium before applying the sample to the agar medium may be associated with contamination and false-positive cultures; however, the degree to which this is the case is not known. We (1) calculated the performance characteristics of broth-only cultures (sensitivity, specificity, positive predictive value, and negative predictive value) and (2) characterized the organisms identified in broth to determine whether a specific organism showed increased proclivity for true-positive periprosthetic joint infection (PJI). A single-institution retrospective chart review was performed on 257 revision total joint arthroplasties from 2009 through 2010. One hundred ninety (74%) had cultures for review. All culture results, as well as treatment, if any, were documented and patients were followed for a minimum of 1 year for evidence of PJI. Cultures were measured as either positive from the broth only or broth negative. The true diagnosis of infection was determined by the Musculoskeletal Infection Society criteria during the preoperative workup or postoperatively at 1 year for purposes of calculating the performance characteristics of the broth-only culture. The sensitivity, specificity, positive predictive value, and negative predictive value were 19%, 88%, 13%, and 92%, respectively. The most common organism identified was coagulase-negative Staphylococcus (16 of 24 cases, 67%). Coagulase-negative Staphylococcus was present in all three true-positive cases; however, it was also found in 13 of the false-positive cases. The broth-only positive cultures showed poor sensitivity and positive predictive value but good specificity and negative predictive value. The good specificity indicates that it can help to rule in the presence of PJI; however, the poor sensitivity makes broth-only culture an unreliable screening test. We recommend that broth-only culture results be carefully scrutinized and decisions on the diagnosis and treatment of infection should be based specifically on the Musculoskeletal Infection Society criteria. Level IV, diagnostic study. See Instructions for Authors for a complete description of levels of evidence.

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

PubMed

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

2018-04-06

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

Student Buy-In Toward Formative Assessments: The Influence of Student Factors and Importance for Course Success †

PubMed Central

Brazeal, Kathleen R.; Couch, Brian A.

2017-01-01

Formative assessment (FA) techniques, such as pre-class assignments, in-class activities, and post-class homework, have been shown to improve student learning. While many students find these techniques beneficial, some students may not understand how they support learning or may resist their implementation. Improving our understanding of FA buy-in has important implications, since buy-in can potentially affect whether students fully engage with and learn from FAs. We investigated FAs in 12 undergraduate biology courses to understand which student characteristics influenced buy-in toward FAs and whether FA buy-in predicted course success. We administered a mid-semester survey that probed student perceptions toward several different FA types, including activities occurring before, during, and after class. The survey included closed-ended questions aligned with a theoretical framework outlining key FA objectives. We used factor analysis to calculate an overall buy-in score for each student and general linear models to determine whether certain characteristics were associated with buy-in and whether buy-in predicted exam scores and course grades. We found that unfixed student qualities, such as perceptions, behaviors, and beliefs, consistently predicted FA buy-in, while fixed characteristics, including demographics, previous experiences, and incoming performance metrics, had more limited effects. Importantly, we found that higher buy-in toward most FA types predicted higher exam scores and course grades, even when controlling for demographic characteristics and previous academic performance. We further discuss steps that instructors can take to maximize student buy-in toward FAs. PMID:28512523

Fusion of multiscale wavelet-based fractal analysis on retina image for stroke prediction.

PubMed

Che Azemin, M Z; Kumar, Dinesh K; Wong, T Y; Wang, J J; Kawasaki, R; Mitchell, P; Arjunan, Sridhar P

2010-01-01

In this paper, we present a novel method of analyzing retinal vasculature using Fourier Fractal Dimension to extract the complexity of the retinal vasculature enhanced at different wavelet scales. Logistic regression was used as a fusion method to model the classifier for 5-year stroke prediction. The efficacy of this technique has been tested using standard pattern recognition performance evaluation, Receivers Operating Characteristics (ROC) analysis and medical prediction statistics, odds ratio. Stroke prediction model was developed using the proposed system.

The CURB65 pneumonia severity score outperforms generic sepsis and early warning scores in predicting mortality in community‐acquired pneumonia

PubMed Central

Barlow, Gavin; Nathwani, Dilip; Davey, Peter

2007-01-01

Background The performance of CURB65 in predicting mortality in community‐acquired pneumonia (CAP) has been tested in two large observational studies. However, it has not been tested against generic sepsis and early warning scores, which are increasingly being advocated for identification of high‐risk patients in acute medical wards. Method A retrospective analysis was performed of data prospectively collected for a CAP quality improvement study. The ability to stratify mortality and performance characteristics (sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating curve) were calculated for stratifications of CURB65, CRB65, the systemic inflammatory response syndrome (SIRS) criteria and the standardised early warning score (SEWS). Results 419 patients were included in the main analysis with a median age of 74 years (men = 47%). CURB65 and CRB65 stratified mortality in a more clinically useful way and had more favourable operating characteristics than SIRS or SEWS; for example, mortality in low‐risk patients was 2% when defined by CURB65, but 9% when defined by SEWS and 11–17% when defined by variations of the SIRS criteria. The sensitivity, specificity, positive predictive value and negative predictive value of CURB65 was 71%, 69%, 35% and 91%, respectively, compared with 62%, 73%, 35% and 89% for the best performing version of SIRS and 52%, 67%, 27% and 86% for SEWS. CURB65 had the greatest area under the receiver operating curve (0.78 v 0.73 for CRB65, 0.68 for SIRS and 0.64 for SEWS). Conclusions CURB65 should not be supplanted by SIRS or SEWS for initial prognostic assessment in CAP. Further research to identify better generic prognostic tools is required. PMID:16928720

Dual nozzle aerodynamic and cooling analysis study

NASA Technical Reports Server (NTRS)

Meagher, G. M.

1981-01-01

Analytical models to predict performance and operating characteristics of dual nozzle concepts were developed and improved. Aerodynamic models are available to define flow characteristics and bleed requirements for both the dual throat and dual expander concepts. Advanced analytical techniques were utilized to provide quantitative estimates of the bleed flow, boundary layer, and shock effects within dual nozzle engines. Thermal analyses were performed to define cooling requirements for baseline configurations, and special studies of unique dual nozzle cooling problems defined feasible means of achieving adequate cooling.

Determination of tube-to-tube support interaction characteristics. [PWR

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

Haslinger, K.H.

Tube-to-tube support interaction characteristics were determined on a multi-span tube geometry representative of the hot-leg side of the C-E, System 80 steam generator design. Results will become input for an autoclave type wear test program on steam generator tubes, performed by Kraftwerk Union (KWU). Correlation of test data reported here with similar data obtained from the wear tests will be performed in an attempt to make predictions about the long-term fretting behavior of steam generator tubes.

Characterization, performance, and prediction of a lead-acid battery under simulated electric vehicle driving requirements

NASA Technical Reports Server (NTRS)

Ewashinka, J. G.; Bozek, J. M.

1981-01-01

A state-of-the-art 6-V battery module in current use by the electric vehicle industry was tested at the NASA Lewis Research Center to determine its performance characteristics under the SAE J227a driving schedules B, C, and D. The primary objective of the tests was to determine the effects of periods of recuperation and long and short periods of electrical regeneration in improving the performance of the battery module and hence extendng the vehicle range. A secondary objective was to formulate a computer program that would predict the performance of this battery module for the above driving schedules. The results show excellent correlation between the laboratory tests and predicted results. The predicted performance compared with laboratory tests was within +2.4 to -3.7 percent for the D schedule, +0.5 to -7.1 percent for the C schedule, and better than -11.4 percent for the B schedule.

Characterization, performance, and prediction of a lead-acid battery under simulated electric vehicle driving requirements

NASA Astrophysics Data System (ADS)

Ewashinka, J. G.; Bozek, J. M.

1981-05-01

A state-of-the-art 6-V battery module in current use by the electric vehicle industry was tested at the NASA Lewis Research Center to determine its performance characteristics under the SAE J227a driving schedules B, C, and D. The primary objective of the tests was to determine the effects of periods of recuperation and long and short periods of electrical regeneration in improving the performance of the battery module and hence extendng the vehicle range. A secondary objective was to formulate a computer program that would predict the performance of this battery module for the above driving schedules. The results show excellent correlation between the laboratory tests and predicted results. The predicted performance compared with laboratory tests was within +2.4 to -3.7 percent for the D schedule, +0.5 to -7.1 percent for the C schedule, and better than -11.4 percent for the B schedule.

Usefulness of cardiovascular magnetic resonance imaging to predict the need for intervention in patients with coarctation of the aorta.

PubMed

Muzzarelli, Stefano; Meadows, Alison Knauth; Ordovas, Karen Gomes; Higgins, Charles Bernard; Meadows, Jeffery Joshua

2012-03-15

Cardiovascular magnetic resonance (CMR) imaging can predict hemodynamically significant coarctation of the aorta (CoA) with a high degree of discrimination. However, the ability of CMR to predict important clinical outcomes in this patient population is unknown. Therefore, we sought to define the ability of CMR to predict the need for surgical or transcatheter intervention in patients with CoA. We retrospectively reviewed the data from 133 consecutive patients who had undergone CMR for the evaluation of known or suspected CoA. The characteristics of the CMR-derived variables predicting the need for surgical or transcatheter intervention for CoA within 1 year were determined through logistic regression analysis. Therapeutic aortic intervention was performed in 41 (31%) of the 133 patients during the study period. The indexed minimum aortic cross-sectional area was the strongest predictor of subsequent intervention (area under the receiver operating characteristic curve 0.975) followed by heart rate-corrected deceleration time in the descending aorta (area under the receiver operating characteristic curve 0.951), and the percentage of flow increase (area under the receiver operating characteristic curve 0.867). The combination of the indexed minimum aortic cross-sectional area and rate-corrected deceleration time in the descending aorta provided the best predictive model (area under the receiver operating characteristic curve 0.986). In conclusion, CMR findings can predict the need for subsequent intervention in CoA. These findings reinforce the "gate-keeper role" of CMR to cardiac catheterization by providing valuable diagnostic and powerful prognostic information and could guide additional treatment of patients with CoA with the final intent of reducing the number of diagnostic catheterizations in such patients. Copyright © 2012 Elsevier Inc. All rights reserved.

Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study.

PubMed

Wieske, Luuk; Witteveen, Esther; Verhamme, Camiel; Dettling-Ihnenfeldt, Daniela S; van der Schaaf, Marike; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2014-01-01

An early diagnosis of Intensive Care Unit-acquired weakness (ICU-AW) using muscle strength assessment is not possible in most critically ill patients. We hypothesized that development of ICU-AW can be predicted reliably two days after ICU admission, using patient characteristics, early available clinical parameters, laboratory results and use of medication as parameters. Newly admitted ICU patients mechanically ventilated ≥2 days were included in this prospective observational cohort study. Manual muscle strength was measured according to the Medical Research Council (MRC) scale, when patients were awake and attentive. ICU-AW was defined as an average MRC score <4. A prediction model was developed by selecting predictors from an a-priori defined set of candidate predictors, based on known risk factors. Discriminative performance of the prediction model was evaluated, validated internally and compared to the APACHE IV and SOFA score. Of 212 included patients, 103 developed ICU-AW. Highest lactate levels, treatment with any aminoglycoside in the first two days after admission and age were selected as predictors. The area under the receiver operating characteristic curve of the prediction model was 0.71 after internal validation. The new prediction model improved discrimination compared to the APACHE IV and the SOFA score. The new early prediction model for ICU-AW using a set of 3 easily available parameters has fair discriminative performance. This model needs external validation.

A Flight Prediction for Performance of the SWAS Solar Array Deployment Mechanism

NASA Technical Reports Server (NTRS)

Seniderman, Gary; Daniel, Walter K.

1999-01-01

The focus of this paper is a comparison of ground-based solar array deployment tests with the on-orbit deployment. The discussion includes a summary of the mechanisms involved and the correlation of a dynamics model with ground based test results. Some of the unique characteristics of the mechanisms are explained through the analysis of force and angle data acquired from the test deployments. The correlated dynamics model is then used to predict the performance of the system in its flight application.

"The cough game": are there characteristic urethrovesical movement patterns associated with stress incontinence?

PubMed

Lewicky-Gaupp, Christina; Blaivas, Jerry; Clark, Amanda; McGuire, Edward J; Schaer, Gabriel; Tumbarello, Julie; Tunn, Ralf; DeLancey, John O L

2009-02-01

This study was carried out to determine whether five experts in female stress urinary incontinence (SUI) could discover a pattern of urethrovesical movement characteristic of SUI on dynamic perineal ultrasound. A secondary analysis of data from a case-control study was performed. Ultrasounds from 31 cases (daily SUI) and 42 controls (continent volunteers) of similar age and parity were analyzed. Perineal ultrasound was performed during a single cough. The five experts, blinded to continence status and urodynamics, classified each woman as stress continent or incontinent. Correct responses ranged from 45.7% to 65.8% (mean 57.4 +/- 7.6). Sensitivity was 53.0 +/- 8.8% and specificity 61.2 +/- 12.4%. The positive predictive value was 48.8 +/- 8.2% and negative predictive value was 65.0 +/- 7.3%. Inter-rater reliability, evaluated by Cohen's kappa statistic, averaged 0.47 [95% CI 0.40-0.50]. Experts could not identify a pattern of urethrovesical movement characteristic of SUI on ultrasound.

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.

“The Cough Game”: Are there characteristic urethrovesical movement patterns associated with stress incontinence?

PubMed Central

LEWICKY-GAUPP, Christina; BLAIVAS, Jerry; CLARK, Amanda; McGUIRE, Edward J.; SCHAER, Gabriel; TUMBARELLO, Julie; TUNN, Ralf; DeLANCEY, John O.L.

2009-01-01

Introduction and Hypothesis To determine if 5 experts in female stress urinary incontinence (SUI) could discover a pattern of urethrovesical movement characteristic of SUI on dynamic perineal ultrasound. Methods A secondary analysis of data from a case-control study was performed. Ultrasounds from 31 cases (daily SUI) and 42 controls (continent volunteers) of similar age and parity were analyzed. Perineal ultrasound was performed during a single cough. The 5 experts, blinded to continence status and urodynamics, classified each woman as stress continent or incontinent. Results Correct responses ranged from 45.7% to 65.8% (mean 57.4 ± 7.6). Sensitivity was 53.0 ± 8.8% and specificity 61.2 ± 12.4%. The positive predictive value was 48.8 ± 8.2% and negative predictive value was 65.0 ± 7.3%. Inter-rater reliability, evaluated by Cohen's kappa statistic, averaged 0.47 [95% CI 0.40 – 0.50]. Conclusions Experts could not identify a pattern of urethrovesical movement characteristic of SUI on ultrasound. PMID:18850057

Parametric analysis of ATM solar array.

NASA Technical Reports Server (NTRS)

Singh, B. K.; Adkisson, W. B.

1973-01-01

The paper discusses the methods used for the calculation of ATM solar array performance characteristics and provides the parametric analysis of solar panels used in SKYLAB. To predict the solar array performance under conditions other than test conditions, a mathematical model has been developed. Four computer programs have been used to convert the solar simulator test data to the parametric curves. The first performs module summations, the second determines average solar cell characteristics which will cause a mathematical model to generate a curve matching the test data, the third is a polynomial fit program which determines the polynomial equations for the solar cell characteristics versus temperature, and the fourth program uses the polynomial coefficients generated by the polynomial curve fit program to generate the parametric data.

Experimental verification of propeller noise prediction

NASA Technical Reports Server (NTRS)

Succi, G. P.; Munro, D. H.; Zimmer, J. A.

1980-01-01

Results of experimental measurements of the sound fields of 1/4-scale general aviation propellers are presented and experimental wake surveys and pressure signatures obtained are compared with theoretical predictions. Experiments were performed primarily on a 1C160 propeller model mounted in front of a symmetric body in an anechoic wind tunnel, and measured the thrust and torque produced by propeller at different rotation speeds and tunnel velocities, wakes at three axial distances, and sound pressure at various azimuths and tip speeds with advance ratio or tunnel velocity constant. Aerodynamic calculations of blade loading were performed using airfoil section characteristics and a modified strip analysis procedure. The propeller was then modeled as an array of point sound sources with each point characterized by the force and volume of the corresponding propeller section in order to obtain the acoustic characteristics. Measurements are found to agree with predictions over a wide range of operating conditions, tip speeds and propeller nacelle combinations, without the use of adjustable constants.

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.

A comprehensive mechanistic model for upward two-phase flow in wellbores

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

Sylvester, N.D.; Sarica, C.; Shoham, O.

1994-05-01

A comprehensive model is formulated to predict the flow behavior for upward two-phase flow. This model is composed of a model for flow-pattern prediction and a set of independent mechanistic models for predicting such flow characteristics as holdup and pressure drop in bubble, slug, and annular flow. The comprehensive model is evaluated by using a well data bank made up of 1,712 well cases covering a wide variety of field data. Model performance is also compared with six commonly used empirical correlations and the Hasan-Kabir mechanistic model. Overall model performance is in good agreement with the data. In comparison withmore » other methods, the comprehensive model performed the best.« less

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

PubMed

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

2016-08-01

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

External validation of a prediction model for surgical site infection after thoracolumbar spine surgery in a Western European cohort.

PubMed

Janssen, Daniël M C; van Kuijk, Sander M J; d'Aumerie, Boudewijn B; Willems, Paul C

2018-05-16

A prediction model for surgical site infection (SSI) after spine surgery was developed in 2014 by Lee et al. This model was developed to compute an individual estimate of the probability of SSI after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Before any prediction model can be validly implemented in daily medical practice, it should be externally validated to assess how the prediction model performs in patients sampled independently from the derivation cohort. We included 898 consecutive patients who underwent instrumented thoracolumbar spine surgery. To quantify overall performance using Nagelkerke's R 2 statistic, the discriminative ability was quantified as the area under the receiver operating characteristic curve (AUC). We computed the calibration slope of the calibration plot, to judge prediction accuracy. Sixty patients developed an SSI. The overall performance of the prediction model in our population was poor: Nagelkerke's R 2 was 0.01. The AUC was 0.61 (95% confidence interval (CI) 0.54-0.68). The estimated slope of the calibration plot was 0.52. The previously published prediction model showed poor performance in our academic external validation cohort. To predict SSI after instrumented thoracolumbar spine surgery for the present population, a better fitting prediction model should be developed.

Experimental and Numerical Analysis of Performance Discontinuity of a Pump-Turbine under Pumping Mode

NASA Astrophysics Data System (ADS)

Zhang, X.; Burgstaller, R.; Lai, X.; Gehrer, A.; Kefalas, A.; Pang, Y.

2016-11-01

The performance discontinuity of a pump-turbine under pumping mode is harmful to stable operation of units in hydropower station. In this paper, the performance discontinuity phenomenon of the pump-turbine was studied by means of experiment and numerical simulation. In the experiment, characteristics of the pump-turbine with different diffuser vane openings were tested in order to investigate the effect of pumping casing to the performance discontinuity. While other effects such as flow separation and rotating stall are known to have an effect on the discontinuity, the present studied test cases show that prerotation is the dominating effect for the instability, positions of the positive slope of characteristics are almost the same in different diffuser vane opening conditions. The impeller has principal effect to the performance discontinuity. In the numerical simulation, CFD analysis of tested pump-turbine has been done with k-ω and SST turbulence model. It is found that the position of performance curve discontinuity corresponds to flow recirculation at impeller inlet. Flow recirculation at impeller inlet is the cause of the discontinuity of characteristics curve. It is also found that the operating condition of occurrence of flow recirculation at impeller inlet is misestimated with k-ω and SST turbulence model. Furthermore, the original SST model has been modified. We predict the occurrence position of flow recirculation at impeller inlet correctly with the modified SST turbulence model, and it also can improve the prediction accuracy of the pump- turbine performance at the same time.

Benchmarking hydrological model predictive capability for UK River flows and flood peaks.

NASA Astrophysics Data System (ADS)

Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten

2017-04-01

Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results improve our understanding of the predictive capability of simple conceptual hydrological models across the UK and help us to identify where further effort is needed to develop modelling approaches to better represent different catchment and climate typologies.

The Satellite Clock Bias Prediction Method Based on Takagi-Sugeno Fuzzy Neural Network

NASA Astrophysics Data System (ADS)

Cai, C. L.; Yu, H. G.; Wei, Z. C.; Pan, J. D.

2017-05-01

The continuous improvement of the prediction accuracy of Satellite Clock Bias (SCB) is the key problem of precision navigation. In order to improve the precision of SCB prediction and better reflect the change characteristics of SCB, this paper proposes an SCB prediction method based on the Takagi-Sugeno fuzzy neural network. Firstly, the SCB values are pre-treated based on their characteristics. Then, an accurate Takagi-Sugeno fuzzy neural network model is established based on the preprocessed data to predict SCB. This paper uses the precise SCB data with different sampling intervals provided by IGS (International Global Navigation Satellite System Service) to realize the short-time prediction experiment, and the results are compared with the ARIMA (Auto-Regressive Integrated Moving Average) model, GM(1,1) model, and the quadratic polynomial model. The results show that the Takagi-Sugeno fuzzy neural network model is feasible and effective for the SCB short-time prediction experiment, and performs well for different types of clocks. The prediction results for the proposed method are better than the conventional methods obviously.

Set size influences the relationship between ANS acuity and math performance: a result of different strategies?

PubMed

Dietrich, Julia Felicitas; Nuerk, Hans-Christoph; Klein, Elise; Moeller, Korbinian; Huber, Stefan

2017-08-29

Previous research has proposed that the approximate number system (ANS) constitutes a building block for later mathematical abilities. Therefore, numerous studies investigated the relationship between ANS acuity and mathematical performance, but results are inconsistent. Properties of the experimental design have been discussed as a potential explanation of these inconsistencies. In the present study, we investigated the influence of set size and presentation duration on the association between non-symbolic magnitude comparison and math performance. Moreover, we focused on strategies reported as an explanation for these inconsistencies. In particular, we employed a non-symbolic magnitude comparison task and asked participants how they solved the task. We observed that set size was a significant moderator of the relationship between non-symbolic magnitude comparison and math performance, whereas presentation duration of the stimuli did not moderate this relationship. This supports the notion that specific design characteristics contribute to the inconsistent results. Moreover, participants reported different strategies including numerosity-based, visual, counting, calculation-based, and subitizing strategies. Frequencies of these strategies differed between different set sizes and presentation durations. However, we found no specific strategy, which alone predicted arithmetic performance, but when considering the frequency of all reported strategies, arithmetic performance could be predicted. Visual strategies made the largest contribution to this prediction. To conclude, the present findings suggest that different design characteristics contribute to the inconsistent findings regarding the relationship between non-symbolic magnitude comparison and mathematical performance by inducing different strategies and additional processes.

Associations of medical student personality and health/wellness characteristics with their medical school performance across the curriculum.

PubMed

Haight, Scott J; Chibnall, John T; Schindler, Debra L; Slavin, Stuart J

2012-04-01

To assess the relationships of cognitive and noncognitive performance predictors to medical student preclinical and clinical performance indicators across medical school years 1 to 3 and to evaluate the association of psychological health/wellness factors with performance. In 2010, the authors conducted a cross-sectional, correlational, retrospective study of all 175 students at the Saint Louis University School of Medicine who had just completed their third (first clinical) year. Students were asked to complete assessments of personality, stress, anxiety, depression, social support, and community cohesion. Performance measures included total Medical College Admission Test (MCAT) score, preclinical academic grades, National Board of Medical Examiners subject exam scores, United States Medical Licensing Examination Step 1 score, clinical evaluations, and Humanism in Medicine Honor Society nominations. A total of 152 students (87%) participated. MCAT scores predicted cognitive performance indicators (academic tests), whereas personality variables (conscientiousness, extraversion, empathy) predicted noncognitive indicators (clinical evaluations, humanism nominations). Conscientiousness predicted all clinical skills, extraversion predicted clinical skills reflecting interpersonal behavior, and empathy predicted motivation. Health/wellness variables had limited associations with performance. In multivariate analyses that included control for shelf exam scores, conscientiousness predicted clinical evaluations, and extraversion and empathy predicted humanism nominations. This study identified two sets of skills (cognitive, noncognitive) used during medical school, with minimal overlap across the types of performance (e.g., exam performance versus clinical interpersonal skills) they predict. Medical school admission and evaluation efforts may need to be modified to reflect the importance of personality and other noncognitive factors.

Simplified procedures for correlation of experimentally measured and predicted thrust chamber performance

NASA Technical Reports Server (NTRS)

Powell, W. B.

1973-01-01

Thrust chamber performance is evaluated in terms of an analytical model incorporating all the loss processes that occur in a real rocket motor. The important loss processes in the real thrust chamber were identified, and a methodology and recommended procedure for predicting real thrust chamber vacuum specific impulse were developed. Simplified equations for the calculation of vacuum specific impulse are developed to relate the delivered performance (both vacuum specific impulse and characteristic velocity) to the ideal performance as degraded by the losses corresponding to a specified list of loss processes. These simplified equations enable the various performance loss components, and the corresponding efficiencies, to be quantified separately (except that interaction effects are arbitrarily assigned in the process). The loss and efficiency expressions presented can be used to evaluate experimentally measured thrust chamber performance, to direct development effort into the areas most likely to yield improvements in performance, and as a basis to predict performance of related thrust chamber configurations.

Formulation of aerodynamic prediction techniques for hypersonic configuration design

NASA Technical Reports Server (NTRS)

1979-01-01

An investigation of approximate theoretical techniques for predicting aerodynamic characteristics and surface pressures for relatively slender vehicles at moderate hypersonic speeds was performed. Emphasis was placed on approaches that would be responsive to preliminary configuration design level of effort. Supersonic second order potential theory was examined in detail to meet this objective. Shock layer integral techniques were considered as an alternative means of predicting gross aerodynamic characteristics. Several numerical pilot codes were developed for simple three dimensional geometries to evaluate the capability of the approximate equations of motion considered. Results from the second order computations indicated good agreement with higher order solutions and experimental results for a variety of wing like shapes and values of the hypersonic similarity parameter M delta approaching one.

Application of physicochemical properties and process parameters in the development of a neural network model for prediction of tablet characteristics.

PubMed

Sovány, Tamás; Papós, Kitti; Kása, Péter; Ilič, Ilija; Srčič, Stane; Pintye-Hódi, Klára

2013-06-01

The importance of in silico modeling in the pharmaceutical industry is continuously increasing. The aim of the present study was the development of a neural network model for prediction of the postcompressional properties of scored tablets based on the application of existing data sets from our previous studies. Some important process parameters and physicochemical characteristics of the powder mixtures were used as training factors to achieve the best applicability in a wide range of possible compositions. The results demonstrated that, after some pre-processing of the factors, an appropriate prediction performance could be achieved. However, because of the poor extrapolation capacity, broadening of the training data range appears necessary.

Measures of accuracy and performance of diagnostic tests.

PubMed

Drobatz, Kenneth J

2009-05-01

Diagnostic tests are integral to the practice of veterinary cardiology, any other specialty, and general veterinary medicine. Developing and understanding diagnostic tests is one of the cornerstones of clinical research. This manuscript describes the diagnostic test properties including sensitivity, specificity, predictive value, likelihood ratio, receiver operating characteristic curve. Review of practical book chapters and standard statistics manuscripts. Diagnostics such as sensitivity, specificity, predictive value, likelihood ratio, and receiver operating characteristic curve are described and illustrated. Basic understanding of how diagnostic tests are developed and interpreted is essential in reviewing clinical scientific papers and understanding evidence based medicine.

Prediction of field emitter cathode lifetime based on measurement of I- V curves

NASA Astrophysics Data System (ADS)

Bormashov, V. S.; Nikolski, K. N.; Baturin, A. S.; Sheshin, E. P.

2003-06-01

A technique is presented, which allows the prediction of field emitter cathode lifetime without long-term direct measurements of cathode parameters stability. This technique is based on periodic measurements of cathode I- V characteristics. Moreover, it allows performing a post-experiment optimization for the appropriate choice of the feedback system to provide a stable operation during a long time. The proposed technique was applied to study the emission properties of reticulated vitreous carbon (RVC) and thermo-enlarged graphite (TEG). For the given cathodes, the characteristic time of the cathode destruction was estimated.

Managing the herbage utilisation and intake by cattle grazing rangelands

USDA-ARS?s Scientific Manuscript database

To be able to predict the performance of grazing cattle in extensive rangeland environments, herbage intake is paramount because it quantifies energy intake and performance. Nutrient demand of the animals is the major driver of herbage intake and characteristics of the sward dictate how this demand...

Principals' Perceptions of Barriers to Dismissal of Poor-Performing Teachers

ERIC Educational Resources Information Center

Dandoy, Jason R.

2012-01-01

The purpose of this study is to determine which factors influence items that school principals consider "barriers" to dismissal of "incompetent" or "poor performing" teachers. This study determines if specific characteristics of schools, principals, or a combination of the two can predict the specific barriers cited…

Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

ERIC Educational Resources Information Center

Ye, Qiang

2010-01-01

Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

Self-Efficacy, Self-Regulation, and Goal Orientation: Learner Motivational Characteristics That Influence Online Student Performance

ERIC Educational Resources Information Center

Wintling, Cheral Ann

2012-01-01

Learner motivational constructs of self-efficacy, self-regulation, and goal orientation in predicting successful student performance in online courses were explored. Thirty-three undergraduate students from the online courses Introduction to Educational Technology and Introduction to Education completed sections of the Motivated Strategies for…

The Overconfident Principles of Economics Student: An Examination of a Metacognitive Skill.

ERIC Educational Resources Information Center

Grimes, Paul W.

2002-01-01

Examined the effect of demographic characteristics, academic endowments, course preparation, and course performance variables on the accuracy of pretest expectations when asking students to predict their performance on a regularly scheduled macroeconomics midterm examination. Finds overconfidence and misjudgments about the scope of the midterm…

Evaluation and comparison of statistical methods for early temporal detection of outbreaks: A simulation-based study

PubMed Central

Le Strat, Yann

2017-01-01

The objective of this paper is to evaluate a panel of statistical algorithms for temporal outbreak detection. Based on a large dataset of simulated weekly surveillance time series, we performed a systematic assessment of 21 statistical algorithms, 19 implemented in the R package surveillance and two other methods. We estimated false positive rate (FPR), probability of detection (POD), probability of detection during the first week, sensitivity, specificity, negative and positive predictive values and F1-measure for each detection method. Then, to identify the factors associated with these performance measures, we ran multivariate Poisson regression models adjusted for the characteristics of the simulated time series (trend, seasonality, dispersion, outbreak sizes, etc.). The FPR ranged from 0.7% to 59.9% and the POD from 43.3% to 88.7%. Some methods had a very high specificity, up to 99.4%, but a low sensitivity. Methods with a high sensitivity (up to 79.5%) had a low specificity. All methods had a high negative predictive value, over 94%, while positive predictive values ranged from 6.5% to 68.4%. Multivariate Poisson regression models showed that performance measures were strongly influenced by the characteristics of time series. Past or current outbreak size and duration strongly influenced detection performances. PMID:28715489

Configuration and validation of a novel prostate disease nomogram predicting prostate biopsy outcome: A prospective study correlating clinical indicators among Filipino adult males with elevated PSA level.

PubMed

Chua, Michael E; Tanseco, Patrick P; Mendoza, Jonathan S; Castillo, Josefino C; Morales, Marcelino L; Luna, Saturnino L

2015-04-01

To configure and validate a novel prostate disease nomogram providing prostate biopsy outcome probabilities from a prospective study correlating clinical indicators and diagnostic parameters among Filipino adult male with elevated serum total prostate specific antigen (PSA) level. All men with an elevated serum total PSA underwent initial prostate biopsy at our institution from January 2011 to August 2014 were included. Clinical indicators, diagnostic parameters, which include PSA level and PSA-derivatives, were collected as predictive factors for biopsy outcome. Multiple logistic-regression analysis involving a backward elimination selection procedure was used to select independent predictors. A nomogram was developed to calculate the probability of the biopsy outcomes. External validation of the nomogram was performed using separate data set from another center for determination of sensitivity and specificity. A receiver-operating characteristic (ROC) curve was used to assess the accuracy in predicting differential biopsy outcome. Total of 552 patients was included. One hundred and ninety-one (34.6%) patients had benign prostatic hyperplasia, and 165 (29.9%) had chronic prostatitis. The remaining 196 (35.5%) patients had prostate adenocarcinoma. The significant independent variables used to predict biopsy outcome were age, family history of prostate cancer, prior antibiotic intake, PSA level, PSA-density, PSA-velocity, echogenic findings on ultrasound, and DRE status. The areas under the receiver-operating characteristic curve for prostate cancer using PSA alone and the nomogram were 0.688 and 0.804, respectively. The nomogram configured based on routinely available clinical parameters, provides high predictive accuracy with good performance characteristics in predicting the prostate biopsy outcome such as presence of prostate cancer, high Gleason prostate cancer, benign prostatic hyperplasia, and chronic prostatitis.

A Systematic Review of the Reliability and Validity of Behavioural Tests Used to Assess Behavioural Characteristics Important in Working Dogs.

PubMed

Brady, Karen; Cracknell, Nina; Zulch, Helen; Mills, Daniel Simon

2018-01-01

Working dogs are selected based on predictions from tests that they will be able to perform specific tasks in often challenging environments. However, withdrawal from service in working dogs is still a big problem, bringing into question the reliability of the selection tests used to make these predictions. A systematic review was undertaken aimed at bringing together available information on the reliability and predictive validity of the assessment of behavioural characteristics used with working dogs to establish the quality of selection tests currently available for use to predict success in working dogs. The search procedures resulted in 16 papers meeting the criteria for inclusion. A large range of behaviour tests and parameters were used in the identified papers, and so behaviour tests and their underpinning constructs were grouped on the basis of their relationship with positive core affect (willingness to work, human-directed social behaviour, object-directed play tendencies) and negative core affect (human-directed aggression, approach withdrawal tendencies, sensitivity to aversives). We then examined the papers for reports of inter-rater reliability, within-session intra-rater reliability, test-retest validity and predictive validity. The review revealed a widespread lack of information relating to the reliability and validity of measures to assess behaviour and inconsistencies in terminologies, study parameters and indices of success. There is a need to standardise the reporting of these aspects of behavioural tests in order to improve the knowledge base of what characteristics are predictive of optimal performance in working dog roles, improving selection processes and reducing working dog redundancy. We suggest the use of a framework based on explaining the direct or indirect relationship of the test with core affect.

A Free Wake Numerical Simulation for Darrieus Vertical Axis Wind Turbine Performance Prediction

NASA Astrophysics Data System (ADS)

Belu, Radian

2010-11-01

In the last four decades, several aerodynamic prediction models have been formulated for the Darrieus wind turbine performances and characteristics. We can identified two families: stream-tube and vortex. The paper presents a simplified numerical techniques for simulating vertical axis wind turbine flow, based on the lifting line theory and a free vortex wake model, including dynamic stall effects for predicting the performances of a 3-D vertical axis wind turbine. A vortex model is used in which the wake is composed of trailing stream-wise and shedding span-wise vortices, whose strengths are equal to the change in the bound vortex strength as required by the Helmholz and Kelvin theorems. Performance parameters are computed by application of the Biot-Savart law along with the Kutta-Jukowski theorem and a semi-empirical stall model. We tested the developed model with an adaptation of the earlier multiple stream-tube performance prediction model for the Darrieus turbines. Predictions by using our method are shown to compare favorably with existing experimental data and the outputs of other numerical models. The method can predict accurately the local and global performances of a vertical axis wind turbine, and can be used in the design and optimization of wind turbines for built environment applications.

Value of high-sensitivity C-reactive protein assays in predicting atrial fibrillation recurrence: a systematic review and meta-analysis.

PubMed

Yo, Chia-Hung; Lee, Si-Huei; Chang, Shy-Shin; Lee, Matthew Chien-Hung; Lee, Chien-Chang

2014-02-20

We performed a systematic review and meta-analysis of studies on high-sensitivity C-reactive protein (hs-CRP) assays to see whether these tests are predictive of atrial fibrillation (AF) recurrence after cardioversion. Systematic review and meta-analysis. PubMed, EMBASE and Cochrane databases as well as a hand search of the reference lists in the retrieved articles from inception to December 2013. This review selected observational studies in which the measurements of serum CRP were used to predict AF recurrence. An hs-CRP assay was defined as any CRP test capable of measuring serum CRP to below 0.6 mg/dL. We summarised test performance characteristics with the use of forest plots, hierarchical summary receiver operating characteristic curves and bivariate random effects models. Meta-regression analysis was performed to explore the source of heterogeneity. We included nine qualifying studies comprising a total of 347 patients with AF recurrence and 335 controls. A CRP level higher than the optimal cut-off point was an independent predictor of AF recurrence after cardioversion (summary adjusted OR: 3.33; 95% CI 2.10 to 5.28). The estimated pooled sensitivity and specificity for hs-CRP was 71.0% (95% CI 63% to 78%) and 72.0% (61% to 81%), respectively. Most studies used a CRP cut-off point of 1.9 mg/L to predict long-term AF recurrence (77% sensitivity, 65% specificity), and 3 mg/L to predict short-term AF recurrence (73% sensitivity, 71% specificity). hs-CRP assays are moderately accurate in predicting AF recurrence after successful cardioversion.

Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

PubMed

Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

2015-03-01

A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

Modelling invasion for a habitat generalist and a specialist plant species

USGS Publications Warehouse

Evangelista, P.H.; Kumar, S.; Stohlgren, T.J.; Jarnevich, C.S.; Crall, A.W.; Norman, J. B.; Barnett, D.T.

2008-01-01

Predicting suitable habitat and the potential distribution of invasive species is a high priority for resource managers and systems ecologists. Most models are designed to identify habitat characteristics that define the ecological niche of a species with little consideration to individual species' traits. We tested five commonly used modelling methods on two invasive plant species, the habitat generalist Bromus tectorum and habitat specialist Tamarix chinensis, to compare model performances, evaluate predictability, and relate results to distribution traits associated with each species. Most of the tested models performed similarly for each species; however, the generalist species proved to be more difficult to predict than the specialist species. The highest area under the receiver-operating characteristic curve values with independent validation data sets of B. tectorum and T. chinensis was 0.503 and 0.885, respectively. Similarly, a confusion matrix for B. tectorum had the highest overall accuracy of 55%, while the overall accuracy for T. chinensis was 85%. Models for the generalist species had varying performances, poor evaluations, and inconsistent results. This may be a result of a generalist's capability to persist in a wide range of environmental conditions that are not easily defined by the data, independent variables or model design. Models for the specialist species had consistently strong performances, high evaluations, and similar results among different model applications. This is likely a consequence of the specialist's requirement for explicit environmental resources and ecological barriers that are easily defined by predictive models. Although defining new invaders as generalist or specialist species can be challenging, model performances and evaluations may provide valuable information on a species' potential invasiveness.

Multi-factorial analysis of class prediction error: estimating optimal number of biomarkers for various classification rules.

PubMed

Khondoker, Mizanur R; Bachmann, Till T; Mewissen, Muriel; Dickinson, Paul; Dobrzelecki, Bartosz; Campbell, Colin J; Mount, Andrew R; Walton, Anthony J; Crain, Jason; Schulze, Holger; Giraud, Gerard; Ross, Alan J; Ciani, Ilenia; Ember, Stuart W J; Tlili, Chaker; Terry, Jonathan G; Grant, Eilidh; McDonnell, Nicola; Ghazal, Peter

2010-12-01

Machine learning and statistical model based classifiers have increasingly been used with more complex and high dimensional biological data obtained from high-throughput technologies. Understanding the impact of various factors associated with large and complex microarray datasets on the predictive performance of classifiers is computationally intensive, under investigated, yet vital in determining the optimal number of biomarkers for various classification purposes aimed towards improved detection, diagnosis, and therapeutic monitoring of diseases. We investigate the impact of microarray based data characteristics on the predictive performance for various classification rules using simulation studies. Our investigation using Random Forest, Support Vector Machines, Linear Discriminant Analysis and k-Nearest Neighbour shows that the predictive performance of classifiers is strongly influenced by training set size, biological and technical variability, replication, fold change and correlation between biomarkers. Optimal number of biomarkers for a classification problem should therefore be estimated taking account of the impact of all these factors. A database of average generalization errors is built for various combinations of these factors. The database of generalization errors can be used for estimating the optimal number of biomarkers for given levels of predictive accuracy as a function of these factors. Examples show that curves from actual biological data resemble that of simulated data with corresponding levels of data characteristics. An R package optBiomarker implementing the method is freely available for academic use from the Comprehensive R Archive Network (http://www.cran.r-project.org/web/packages/optBiomarker/).

Accuracy of SOFA score in prediction of 30-day outcome of critically ill patients.

PubMed

Safari, Saeed; Shojaee, Majid; Rahmati, Farhad; Barartloo, Alireza; Hahshemi, Behrooz; Forouzanfar, Mohammad Mehdi; Mohammadi, Elham

2016-12-01

Researchers have attempted to design various scoring systems to determine the severity and predict the outcome of critically ill patients. The present study aimed to evaluate the accuracy of SOFA score in predicting 1-month outcome of these patients in emergency department. The present study is a prospective cross-sectional study of >18 year old non-trauma critically ill patients presented to EDs of 3 hospitals, Tehran, Iran, during October 2014 to October 2015. Baseline characteristics, SOFA score variables, and 1-month outcome of patients were recorded and screening performance characteristics of the score were calculated using STATA 11 software. 140 patients with the mean age of 68.36 ± 18.62 years (18-95) were included (53.5% male). The most common complaints were decrease in level of consciousness (76.43%) and sepsis (60.0%), were the most frequent final diagnoses. Mean SOFA score of the patients was 7.13 ± 2.36 (minimum 2 and maximum 16). 72 (51.43%) patients died during the following 30 days and 16 (11.43%) patients were affected with multiple organ failure. Area under the ROC curve of SOFA score in predicting mortality of studied patients was 0.73 (95%CI: 0.65-0.81) (Fig. 2). Table 2 depicts screening performance characteristics of this scale in prediction of 1-month mortality in the best cut-off point of ≥7. At this cut-off point, sensitivity and specificity of SOFA in predicting 1-month mortality were 75% and 63.23%, respectively. Findings of the present study showed that SOFA scoring system has fair accuracy in predicting 1-month mortality of critically ill patients. However, until a more reliable scoring system is developed, SOFA might be useful for narrative prediction of patient outcome considering its acceptable likelihood ratios.

Determinants of success in Shared Savings Programs: An analysis of ACO and market characteristics.

PubMed

Ouayogodé, Mariétou H; Colla, Carrie H; Lewis, Valerie A

2017-03-01

Medicare's Accountable Care Organization (ACO) programs introduced shared savings to traditional Medicare, which allow providers who reduce health care costs for their patients to retain a percentage of the savings they generate. To examine ACO and market factors associated with superior financial performance in Medicare ACO programs. We obtained financial performance data from the Centers for Medicare and Medicaid Services (CMS); we derived market-level characteristics from Medicare claims; and we collected ACO characteristics from the National Survey of ACOs for 215 ACOs. We examined the association between ACO financial performance and ACO provider composition, leadership structure, beneficiary characteristics, risk bearing experience, quality and process improvement capabilities, physician performance management, market competition, CMS-assigned financial benchmark, and ACO contract start date. We examined two outcomes from Medicare ACOs' first performance year: savings per Medicare beneficiary and earning shared savings payments (a dichotomous variable). When modeling the ACO ability to save and earn shared savings payments, we estimated positive regression coefficients for a greater proportion of primary care providers in the ACO, more practicing physicians on the governing board, physician leadership, active engagement in reducing hospital re-admissions, a greater proportion of disabled Medicare beneficiaries assigned to the ACO, financial incentives offered to physicians, a larger financial benchmark, and greater ACO market penetration. No characteristic of organizational structure was significantly associated with both outcomes of savings per beneficiary and likelihood of achieving shared savings. ACO prior experience with risk-bearing contracts was positively correlated with savings and significantly increased the likelihood of receiving shared savings payments. In the first year, performance is quite heterogeneous, yet organizational structure does not consistently predict performance. Organizations with large financial benchmarks at baseline have greater opportunities to achieve savings. Findings on prior risk bearing suggest that ACOs learn over time under risk-bearing contracts. Given the lack of predictive power for organizational characteristics, CMS should continue to encourage diversity in organizational structures for ACO participants, and provide alternative funding and risk bearing mechanisms to continue to allow a diverse group of organizations to participate. III. Copyright © 2016 Elsevier Inc. All rights reserved.

Determinants of Success in Shared Savings Programs: An Analysis of ACO and Market Characteristics

PubMed Central

Colla, Carrie H.; Lewis, Valerie A.

2016-01-01

Background Medicare’s Accountable Care Organization (ACO) programs introduced shared savings to traditional Medicare, which allow providers who reduce health care costs for their patients to retain a percentage of the savings they generate. Objective To examine ACO and market factors associated with superior financial performance in Medicare ACO programs. Methods We obtained financial performance data from the Centers for Medicare and Medicaid Services (CMS); we derived market-level characteristics from Medicare claims; and we collected ACO characteristics from the National Survey of ACOs for 215 ACOs. We examined the association between ACO financial performance and ACO provider composition, leadership structure, beneficiary characteristics, risk bearing experience, quality and process improvement capabilities, physician performance management, market competition, CMS-assigned financial benchmark, and ACO contract start date. We examined two outcomes from Medicare ACOs’ first performance year: savings per Medicare beneficiary and earning shared savings payments (a dichotomous variable). Results When modeling the ACO ability to save and earn shared savings payments, we estimated positive regression coefficients for a greater proportion of primary care providers in the ACO, more practicing physicians on the governing board, physician leadership, active engagement in reducing hospital re-admissions, a greater proportion of disabled Medicare beneficiaries assigned to the ACO, financial incentives offered to physicians, a larger financial benchmark, and greater ACO market penetration. No characteristic of organizational structure was significantly associated with both outcomes of savings per beneficiary and likelihood of achieving shared savings. ACO prior experience with risk-bearing contracts was positively correlated with savings and significantly increased the likelihood of receiving shared savings payments. Conclusions In the first year performance is quite heterogeneous, yet organizational structure does not consistently predict performance. Organizations with large financial benchmarks at baseline have greater opportunities to achieve savings. Findings on prior risk bearing suggest that ACOs learn over time under risk-bearing contracts. Implications Given the lack of predictive power for organizational characteristics, CMS should continue to encourage diversity in organizational structures for ACO participants, and provide alternative funding and risk bearing mechanisms to continue to allow a diverse group of organizations to participate. Level of evidence III PMID:27687917

Performance characteristics of the Mayo/IBM PACS

NASA Astrophysics Data System (ADS)

Persons, Kenneth R.; Gehring, Dale G.; Pavicic, Mark J.; Ding, Yingjai

1991-07-01

The Mayo Clinic and IBM (at Rochester, Minnesota) have jointly developed a picture archiving system for use with Mayo's MRI and Neuro CT imaging modalities. The communications backbone of the PACS is a portion of the Mayo institutional network: a series of 4-Mbps token rings interconnected by bridges and fiber optic extensions. The performance characteristics of this system are important to understand because they affect the response time a PACS user can expect, and the response time for non-PACS users competing for resources on the institutional network. The performance characteristics of each component and the average load levels of the network were measured for various load distributions. These data were used to quantify the response characteristics of the existing system and to tune a model developed by North Dakota State University Department of Computer Science for predicting response times of more complex topologies.

Flight-Test-Determined Aerodynamic Force and Moment Characteristics of the X-43A at Mach 7.0

NASA Technical Reports Server (NTRS)

Davis. Marl C.; White, J. Terry

2006-01-01

The second flight of the Hyper-X program afforded a unique opportunity to determine the aerodynamic force and moment characteristics of an airframe-integrated scramjet-powered aircraft in hypersonic flight. These data were gathered via a repeated series of pitch, yaw, and roll doublets; frequency sweeps; and pushover-pullup maneuvers performed throughout the X-43A cowl-closed descent. Maneuvers were conducted at Mach numbers of 6.80 to 0.95 and altitudes from 92,000 ft msl to sea level. The dynamic pressure varied from 1300 psf to 400 psf with the angle of attack ranging from 0 deg to 14 deg. The flight-extracted aerodynamics were compared with preflight predictions based on wind-tunnel-test data. The X-43A flight-derived axial force was found to be 10 percent to 15 percent higher than prediction. Under-predictions of similar magnitude were observed for the normal force. For Mach numbers above 4.0, the flight-derived stability and control characteristics resulted in larger-than-predicted static margins, with the largest discrepancy approximately 5 in. forward along the x-axis center of gravity at Mach 6.0. This condition would result in less static margin in pitch. The predicted lateral-directional stability and control characteristics matched well with flight data when allowance was made for the high uncertainty in angle of sideslip.

Unstructured Grid Euler Method Assessment for Longitudinal and Lateral/Directional Aerodynamic Performance Analysis of the HSR Technology Concept Airplane at Supersonic Cruise Speed

NASA Technical Reports Server (NTRS)

Ghaffari, Farhad

1999-01-01

Unstructured grid Euler computations, performed at supersonic cruise speed, are presented for a High Speed Civil Transport (HSCT) configuration, designated as the Technology Concept Airplane (TCA) within the High Speed Research (HSR) Program. The numerical results are obtained for the complete TCA cruise configuration which includes the wing, fuselage, empennage, diverters, and flow through nacelles at M (sub infinity) = 2.4 for a range of angles-of-attack and sideslip. Although all the present computations are performed for the complete TCA configuration, appropriate assumptions derived from the fundamental supersonic aerodynamic principles have been made to extract aerodynamic predictions to complement the experimental data obtained from a 1.675%-scaled truncated (aft fuselage/empennage components removed) TCA model. The validity of the computational results, derived from the latter assumptions, are thoroughly addressed and discussed in detail. The computed surface and off-surface flow characteristics are analyzed and the pressure coefficient contours on the wing lower surface are shown to correlate reasonably well with the available pressure sensitive paint results, particularly, for the complex flow structures around the nacelles. The predicted longitudinal and lateral/directional performance characteristics for the truncated TCA configuration are shown to correlate very well with the corresponding wind-tunnel data across the examined range of angles-of-attack and sideslip. The complementary computational results for the longitudinal and lateral/directional performance characteristics for the complete TCA configuration are also presented along with the aerodynamic effects due to empennage components. Results are also presented to assess the computational method performance, solution sensitivity to grid refinement, and solution convergence characteristics.

Predicting Fluid Responsiveness by Passive Leg Raising: A Systematic Review and Meta-Analysis of 23 Clinical Trials.

PubMed

Cherpanath, Thomas G V; Hirsch, Alexander; Geerts, Bart F; Lagrand, Wim K; Leeflang, Mariska M; Schultz, Marcus J; Groeneveld, A B Johan

2016-05-01

Passive leg raising creates a reversible increase in venous return allowing for the prediction of fluid responsiveness. However, the amount of venous return may vary in various clinical settings potentially affecting the diagnostic performance of passive leg raising. Therefore we performed a systematic meta-analysis determining the diagnostic performance of passive leg raising in different clinical settings with exploration of patient characteristics, measurement techniques, and outcome variables. PubMed, EMBASE, the Cochrane Database of Systematic Reviews, and citation tracking of relevant articles. Clinical trials were selected when passive leg raising was performed in combination with a fluid challenge as gold standard to define fluid responders and non-responders. Trials were included if data were reported allowing the extraction of sensitivity, specificity, and area under the receiver operating characteristic curve. Twenty-three studies with a total of 1,013 patients and 1,034 fluid challenges were included. The analysis demonstrated a pooled sensitivity of 86% (95% CI, 79-92), pooled specificity of 92% (95% CI, 88-96), and a summary area under the receiver operating characteristic curve of 0.95 (95% CI, 0.92-0.98). Mode of ventilation, type of fluid used, passive leg raising starting position, and measurement technique did not affect the diagnostic performance of passive leg raising. The use of changes in pulse pressure on passive leg raising showed a lower diagnostic performance when compared with passive leg raising-induced changes in flow variables, such as cardiac output or its direct derivatives (sensitivity of 58% [95% CI, 44-70] and specificity of 83% [95% CI, 68-92] vs sensitivity of 85% [95% CI, 78-90] and specificity of 92% [95% CI, 87-94], respectively; p < 0.001). Passive leg raising retains a high diagnostic performance in various clinical settings and patient groups. The predictive value of a change in pulse pressure on passive leg raising is inferior to a passive leg raising-induced change in a flow variable.

Timing of occurrence is the most important characteristic of spot sign

PubMed Central

Xu, Mengjun; Zhang, Sheng; Liu, Keqin; Hu, Haitao; Selim, Magdy; Lou, Min

2016-01-01

Background and Purpose Most previous studies have used single-phase CT angiography (CTA) to detect the spot sign, a marker for hematoma expansion (HE) in spontaneous intracerebral hemorrhage (SICH). We investigated whether defining the spot sign based on timing on perfusion CT (CTP) would improve its specificity for predicting HE. Methods We prospectively enrolled supratentorial SICH patients, who underwent CTP within 6 h of onset. Logistic regression were performed to assess the risk factors for HE and poor outcome. Predictive performance of individual CTP spot sign characteristics were examined with receiver operating characteristic (ROC) analysis. Results Sixty-two men and 21 women with SICH were included in this analysis. Spot sign was detected in 46% (38/83) patients. ROC analysis indicated that the timing of spot sign occurrence on CTP had the greatest AUC for HE (0.794; 95% CI, 0.630-0.958; P=0.007); the cutoff time was 23.13 seconds. On multivariable analysis, the presence of early-occurring spot sign (EOSS; i.e. spot sign before 23.13 seconds) was an independent predictor, not only of HE (OR=28.835; 95% CI, 6.960-119.458; P<0.001), but also of mortality at 3 months (OR=22.377; 95% CI, 1.773-282.334; P=0.016). Moreover, the predictive performance showed that the redefined EOSS maintained a higher specificity for HE compared to spot sign (91% vs 74%). Conclusions Redefining the spot sign based on timing of contrast leakage on CTP to determine EOSS, improves the specificity for predicting HE and 3-month mortality. The use of EOSS could improve the selection of ICH patients for potential hemostatic therapy. PMID:27026627

Predicting BCI subject performance using probabilistic spatio-temporal filters.

PubMed

Suk, Heung-Il; Fazli, Siamac; Mehnert, Jan; Müller, Klaus-Robert; Lee, Seong-Whan

2014-01-01

Recently, spatio-temporal filtering to enhance decoding for Brain-Computer-Interfacing (BCI) has become increasingly popular. In this work, we discuss a novel, fully Bayesian-and thereby probabilistic-framework, called Bayesian Spatio-Spectral Filter Optimization (BSSFO) and apply it to a large data set of 80 non-invasive EEG-based BCI experiments. Across the full frequency range, the BSSFO framework allows to analyze which spatio-spectral parameters are common and which ones differ across the subject population. As expected, large variability of brain rhythms is observed between subjects. We have clustered subjects according to similarities in their corresponding spectral characteristics from the BSSFO model, which is found to reflect their BCI performances well. In BCI, a considerable percentage of subjects is unable to use a BCI for communication, due to their missing ability to modulate their brain rhythms-a phenomenon sometimes denoted as BCI-illiteracy or inability. Predicting individual subjects' performance preceding the actual, time-consuming BCI-experiment enhances the usage of BCIs, e.g., by detecting users with BCI inability. This work additionally contributes by using the novel BSSFO method to predict the BCI-performance using only 2 minutes and 3 channels of resting-state EEG data recorded before the actual BCI-experiment. Specifically, by grouping the individual frequency characteristics we have nicely classified them into the subject 'prototypes' (like μ - or β -rhythm type subjects) or users without ability to communicate with a BCI, and then by further building a linear regression model based on the grouping we could predict subjects' performance with the maximum correlation coefficient of 0.581 with the performance later seen in the actual BCI session.

Prediction of wastewater treatment plants performance based on artificial fish school neural network

NASA Astrophysics Data System (ADS)

Zhang, Ruicheng; Li, Chong

2011-10-01

A reliable model for wastewater treatment plant is essential in providing a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. For the multi-variable, uncertainty, non-linear characteristics of the wastewater treatment system, an artificial fish school neural network prediction model is established standing on actual operation data in the wastewater treatment system. The model overcomes several disadvantages of the conventional BP neural network. The results of model calculation show that the predicted value can better match measured value, played an effect on simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provides a simple and practical way for the operation and management in wastewater treatment plant, and has good research and engineering practical value.

Characterization of an active metasurface using terahertz ellipsometry

DOE PAGES

Karl, Nicholas; Heimbeck, Martin S.; Everitt, Henry O.; ...

2017-11-06

Switchable metasurfaces fabricated on a doped epi-layer have become an important platform for developing techniques to control terahertz (THz) radiation, as a DC bias can modulate the transmission characteristics of the metasurface. To model and understand this performance in new device configurations accurately, a quantitative understanding of the bias-dependent surface characteristics is required. In this work, we perform THz variable angle spectroscopic ellipsometry on a switchable metasurface as a function of DC bias. By comparing these data with numerical simulations, we extract a model for the response of the metasurface at any bias value. Using this model, we predict amore » giant bias-induced phase modulation in a guided wave configuration. Lastly, these predictions are in qualitative agreement with our measurements, offering a route to efficient modulation of THz signals.« less

Assessing the Classification Accuracy of Early Numeracy Curriculum-Based Measures Using Receiver Operating Characteristic Curve Analysis

ERIC Educational Resources Information Center

Laracy, Seth D.; Hojnoski, Robin L.; Dever, Bridget V.

2016-01-01

Receiver operating characteristic curve (ROC) analysis was used to investigate the ability of early numeracy curriculum-based measures (EN-CBM) administered in preschool to predict performance below the 25th and 40th percentiles on a quantity discrimination measure in kindergarten. Areas under the curve derived from a sample of 279 students ranged…

Selective attention deficits in obsessive-compulsive disorder: the role of metacognitive processes.

PubMed

Koch, Julia; Exner, Cornelia

2015-02-28

While initial studies supported the hypothesis that cognitive characteristics that capture cognitive resources act as underlying mechanisms in memory deficits in obsessive-compulsive disorder (OCD), the influence of those characteristics on selective attention has not been studied, yet. In this study, we examined the influence of cognitive self-consciousness (CSC), rumination and worrying on performance in selective attention in OCD and compared the results to a depressive and a healthy control group. We found that 36 OCD and 36 depressive participants were impaired in selective attention in comparison to 36 healthy controls. In all groups, hierarchical regression analyses demonstrated that age, intelligence and years in school significantly predicted performance in selective attention. But only in OCD, the predictive power of the regression model was improved when CSC, rumination and worrying were implemented as predictor variables. In contrast, in none of the three groups the predictive power improved when indicators of severity of obsessive-compulsive (OC) and depressive symptoms and trait anxiety were introduced as predictor variables. Thus, our results support the assumption that mental characteristics that bind cognitive resources play an important role in the understanding of selective attention deficits in OCD and that this mechanism is especially relevant for OCD. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Survival of the fittest: implications of self-reliance and coping for leaders and team performance.

PubMed

Daus, C S; Joplin, J R

1999-01-01

Using a laboratory methodology, the authors sought to establish an association between self-reliance (based on attachment theory) and team performance and satisfaction. Three hypotheses (direct effect, mediator, and moderator) were tested. With a sample of 187 students, the authors compared leader self-reliance characteristics with group member self-reliance characteristics (group n = 50) as predictors of group performance and satisfaction. Only group member counterdependence was predictive of decreased performance. Further, the authors examined the possible mediating and moderating effects of coping on the self-reliance-group effectiveness relationships. Coping did not mediate the relationship but did operate as a significant moderator in some instances.

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

A systematic review of the factors predicting the interest in cosmetic plastic surgery.

PubMed

Milothridis, Panagiotis; Pavlidis, Leonidas; Haidich, Anna-Bettina; Panagopoulou, Efharis

2016-01-01

A systematic review of the literature was performed to clarify the psychosocial characteristics of patients who have an interest in cosmetic plastic surgery. Medical literature was reviewed by two independent researchers, and a third reviewer evaluated their results. Twelve studies addressing the predictors of interest in cosmetic surgery were finally identified and analysed. Interest in cosmetic surgery was associated with epidemiological factors, their social networks, their psychological characteristics, such as body image, self-esteem and other personality traits and for specific psychopathology and found that these may either positively or negatively predict their motivation to seek and undergo a cosmetic procedure. The review examined the psychosocial characteristics associated with an interest in cosmetic surgery. Understanding cosmetic patients' characteristics, motivation and expectation for surgery is an important aspect of their clinical care to identify those patients more likely to benefit most from the procedure.

Geometric Image Biomarker Changes of the Parotid Gland Are Associated With Late Xerostomia.

PubMed

van Dijk, Lisanne V; Brouwer, Charlotte L; van der Laan, Hans Paul; Burgerhof, Johannes G M; Langendijk, Johannes A; Steenbakkers, Roel J H M; Sijtsema, Nanna M

2017-12-01

To identify a surrogate marker for late xerostomia 12 months after radiation therapy (Xer 12m ), according to information obtained shortly after treatment. Differences in parotid gland (PG) were quantified in image biomarkers (ΔIBMs) before and 6 weeks after radiation therapy in 107 patients. By performing stepwise forward selection, ΔIBMs that were associated with Xer 12m were selected. Subsequently other variables, such as PG dose and acute xerostomia scores, were added to improve the prediction performance. All models were internally validated. Prediction of Xer 12m based on PG surface reduction (ΔPG-surface) was good (area under the receiver operating characteristic curve, 0.82). Parotid gland dose was related to ΔPG-surface (P<.001, R 2  = 0.27). The addition of acute xerostomia scores to the ΔPG-surface improved the prediction of Xer 12m significantly, and vice versa. The final model including ΔPG-surface and acute xerostomia had outstanding performance in predicting Xer 12m early after radiation therapy (area under the receiver operating characteristic curve, 0.90). Parotid gland surface reduction was associated with late xerostomia. The early posttreatment model with ΔPG-surface and acute xerostomia scores can be considered as a surrogate marker for late xerostomia. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Numerical simulation of the cavitation characteristics of a mixed-flow pump

NASA Astrophysics Data System (ADS)

Chen, T.; Li, S. R.; Li, W. Z.; Liu, Y. L.; Wu, D. Z.; Wang, L. Q.

2013-12-01

As a kind of general equipment for fluid transportation, pumps were widely used in industry which includes many applications of high pressure, temperature and toxic fluids transportations. Performances of pumps affect the safety and reliability of the whole special equipment system. Cavitation in pumps cause the loss of performance and erosion of the blade, which could affect the running stability and reliability of the pump system. In this paper, a kind of numerical method for cavitaion performance prediction was presented. In order to investigate the accuracy of the method, CFD flow analysis and cavitation performance predictions of a mixed-flow pump were carried out. The numerical results were compared with the test results.

Performance characteristics of magnetic resonance imaging without contrast agents or sedation in pediatric appendicitis.

PubMed

Didier, Ryne A; Hopkins, Katharine L; Coakley, Fergus V; Krishnaswami, Sanjay; Spiro, David M; Foster, Bryan R

2017-09-01

Magnetic resonance imaging (MRI) has emerged as a promising modality for evaluating pediatric appendicitis. However optimal imaging protocols, including roles of contrast agents and sedation, have not been established and diagnostic criteria have not been fully evaluated. To investigate performance characteristics of rapid MRI without contrast agents or sedation in the diagnosis of pediatric appendicitis. We included patients ages 4-18 years with suspicion of appendicitis who underwent rapid MRI between October 2013 and March 2015 without contrast agent or sedation. After two-radiologist review, we determined performance characteristics of individual diagnostic criteria and aggregate diagnostic criteria by comparing MRI results to clinical outcomes. We used receiver operating characteristic (ROC) curves to determine cut-points for appendiceal diameter and wall thickness for optimization of predictive power, and we calculated area under the curve (AUC) as a measure of test accuracy. Ninety-eight MRI examinations were performed in 97 subjects. Overall, MRI had a 94% sensitivity, 95% specificity, 91% positive predictive value and 97% negative predictive value. Optimal cut-points for appendiceal diameter and wall thickness were ≥7 mm and ≥2 mm, respectively. Independently, those cut-points produced sensitivities of 91% and 84% and specificities of 84% and 43%. Presence of intraluminal fluid (30/33) or localized periappendiceal fluid (32/33) showed a significant association with acute appendicitis (P<0.01), with sensitivities of 91% and 97% and specificities of 60% and 50%. For examinations in which the appendix was not identified by one or both reviewers (23/98), the clinical outcome was negative. Rapid MRI without contrast agents or sedation is accurate for diagnosis of pediatric appendicitis when multiple diagnostic criteria are considered in aggregate. Individual diagnostic criteria including optimized cut-points of ≥7 mm for diameter and ≥2 mm for wall thickness demonstrate high sensitivities but relatively low specificities. Nonvisualization of the appendix favors a negative diagnosis.

Derivation and validation of different machine-learning models in mortality prediction of trauma in motorcycle riders: a cross-sectional retrospective study in southern Taiwan

PubMed Central

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Rau, Cheng-Shyuan; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-01-01

Objectives This study aimed to build and test the models of machine learning (ML) to predict the mortality of hospitalised motorcycle riders. Setting The study was conducted in a level-1 trauma centre in southern Taiwan. Participants Motorcycle riders who were hospitalised between January 2009 and December 2015 were classified into a training set (n=6306) and test set (n=946). Using the demographic information, injury characteristics and laboratory data of patients, logistic regression (LR), support vector machine (SVM) and decision tree (DT) analyses were performed to determine the mortality of individual motorcycle riders, under different conditions, using all samples or reduced samples, as well as all variables or selected features in the algorithm. Primary and secondary outcome measures The predictive performance of the model was evaluated based on accuracy, sensitivity, specificity and geometric mean, and an analysis of the area under the receiver operating characteristic curves of the two different models was carried out. Results In the training set, both LR and SVM had a significantly higher area under the receiver operating characteristic curve (AUC) than DT. No significant difference was observed in the AUC of LR and SVM, regardless of whether all samples or reduced samples and whether all variables or selected features were used. In the test set, the performance of the SVM model for all samples with selected features was better than that of all other models, with an accuracy of 98.73%, sensitivity of 86.96%, specificity of 99.02%, geometric mean of 92.79% and AUC of 0.9517, in mortality prediction. Conclusion ML can provide a feasible level of accuracy in predicting the mortality of motorcycle riders. Integration of the ML model, particularly the SVM algorithm in the trauma system, may help identify high-risk patients and, therefore, guide appropriate interventions by the clinical staff. PMID:29306885

A comparison of the Injury Severity Score and the Trauma Mortality Prediction Model.

PubMed

Cook, Alan; Weddle, Jo; Baker, Susan; Hosmer, David; Glance, Laurent; Friedman, Lee; Osler, Turner

2014-01-01

Performance benchmarking requires accurate measurement of injury severity. Despite its shortcomings, the Injury Severity Score (ISS) remains the industry standard 40 years after its creation. A new severity measure, the Trauma Mortality Prediction Model (TMPM), uses either the Abbreviated Injury Scale (AIS) or DRG International Classification of Diseases-9th Rev. (ICD-9) lexicons and may better quantify injury severity compared with ISS. We compared the performance of TMPM with ISS and other measures of injury severity in a single cohort of patients. We included 337,359 patient records with injuries reliably described in both the AIS and the ICD-9 lexicons from the National Trauma Data Bank. Five injury severity measures (ISS, maximum AIS score, New Injury Severity Score [NISS], ICD-9-Based Injury Severity Score [ICISS], TMPM) were computed using either the AIS or ICD-9 codes. These measures were compared for discrimination (area under the receiver operating characteristic curve), an estimate of proximity to a model that perfectly predicts the outcome (Akaike information criterion), and model calibration curves. TMPM demonstrated superior receiver operating characteristic curve, Akaike information criterion, and calibration using either the AIS or ICD-9 lexicons. Calibration plots demonstrate the monotonic characteristics of the TMPM models contrasted by the nonmonotonic features of the other prediction models. Severity measures were more accurate with the AIS lexicon rather than ICD-9. NISS proved superior to ISS in either lexicon. Since NISS is simpler to compute, it should replace ISS when a quick estimate of injury severity is required for AIS-coded injuries. Calibration curves suggest that the nonmonotonic nature of ISS may undermine its performance. TMPM demonstrated superior overall mortality prediction compared with all other models including ISS whether the AIS or ICD-9 lexicons were used. Because TMPM provides an absolute probability of death, it may allow clinicians to communicate more precisely with one another and with patients and families. Disagnostic study, level I; prognostic study, level II.

Evaluation of the Langley 4- by 7-meter tunnel for propeller noise measurements

NASA Technical Reports Server (NTRS)

Block, P. J. W.; Gentry, G. L., Jr.

1984-01-01

An experimental and theoretical evaluation of the Langley 4- by 7- Meter Tunnel was conducted to determine its suitability for obtaining propeller noise data. The tunnel circuit and open test section are described. An experimental evaluation is performed using microphones placed in and on the tunnel floor. The reflection characteristics and background noise are determined. The predicted source (propeller) near-field/far-field boundary is given using a first-principles method. The effect of the tunnel-floor boundry layer on the noise from the propeller is also predicted. A propeller test stand used for part of his evaluation is also described. The measured propeller performance characteristics are compared with those obtained at a larger scale, and the effect of the test-section configuration on the propeller performance is examined. Finally, propeller noise measurements were obtained on an eight-bladed SR-2 propeller operating at angles of attack -8 deg, 0 deg, and 4.6 deg to give an indication of attainable signal-to-noise ratios.

Integrated Aero-Propulsion CFD Methodology for the Hyper-X Flight Experiment

NASA Technical Reports Server (NTRS)

Cockrell, Charles E., Jr.; Engelund, Walter C.; Bittner, Robert D.; Dilley, Arthur D.; Jentink, Tom N.; Frendi, Abdelkader

2000-01-01

Computational fluid dynamics (CFD) tools have been used extensively in the analysis and development of the X-43A Hyper-X Research Vehicle (HXRV). A significant element of this analysis is the prediction of integrated vehicle aero-propulsive performance, which includes an integration of aerodynamic and propulsion flow fields. This paper describes analysis tools used and the methodology for obtaining pre-flight predictions of longitudinal performance increments. The use of higher-fidelity methods to examine flow-field characteristics and scramjet flowpath component performance is also discussed. Limited comparisons with available ground test data are shown to illustrate the approach used to calibrate methods and assess solution accuracy. Inviscid calculations to evaluate lateral-directional stability characteristics are discussed. The methodology behind 3D tip-to-tail calculations is described and the impact of 3D exhaust plume expansion in the afterbody region is illustrated. Finally, future technology development needs in the area of hypersonic propulsion-airframe integration analysis are discussed.

Prediction of Erectile Function Following Treatment for Prostate Cancer

PubMed Central

Alemozaffar, Mehrdad; Regan, Meredith M.; Cooperberg, Matthew R.; Wei, John T.; Michalski, Jeff M.; Sandler, Howard M.; Hembroff, Larry; Sadetsky, Natalia; Saigal, Christopher S.; Litwin, Mark S.; Klein, Eric; Kibel, Adam S.; Hamstra, Daniel A.; Pisters, Louis L.; Kuban, Deborah A.; Kaplan, Irving D.; Wood, David P.; Ciezki, Jay; Dunn, Rodney L.; Carroll, Peter R.; Sanda, Martin G.

2013-01-01

Context Sexual function is the health-related quality of life (HRQOL) domain most commonly impaired after prostate cancer treatment; however, validated tools to enable personalized prediction of erectile dysfunction after prostate cancer treatment are lacking. Objective To predict long-term erectile function following prostate cancer treatment based on individual patient and treatment characteristics. Design Pretreatment patient characteristics, sexual HRQOL, and treatment details measured in a longitudinal academic multicenter cohort (Prostate Cancer Outcomes and Satisfaction With Treatment Quality Assessment; enrolled from 2003 through 2006), were used to develop models predicting erectile function 2 years after treatment. A community-based cohort (community-based Cancer of the Prostate Strategic Urologic Research Endeavor [CaPSURE]; enrolled 1995 through 2007) externally validated model performance. Patients in US academic and community-based practices whose HRQOL was measured pretreatment (N = 1201) underwent follow-up after prostatectomy, external radiotherapy, or brachytherapy for prostate cancer. Sexual outcomes among men completing 2 years’ follow-up (n = 1027) were used to develop models predicting erectile function that were externally validated among 1913 patients in a community-based cohort. Main Outcome Measures Patient-reported functional erections suitable for intercourse 2 years following prostate cancer treatment. Results Two years after prostate cancer treatment, 368 (37% [95% CI, 34%–40%]) of all patients and 335 (48% [95% CI, 45%–52%]) of those with functional erections prior to treatment reported functional erections; 531 (53% [95% CI, 50%–56%]) of patients without penile prostheses reported use of medications or other devices for erectile dysfunction. Pretreatment sexual HRQOL score, age, serum prostate-specific antigen level, race/ethnicity, body mass index, and intended treatment details were associated with functional erections 2 years after treatment. Multivariable logistic regression models predicting erectile function estimated 2-year function probabilities from as low as 10% or less to as high as 70% or greater depending on the individual’s pretreatment patient characteristics and treatment details. The models performed well in predicting erections in external validation among CaPSURE cohort patients (areas under the receiver operating characteristic curve, 0.77 [95% CI, 0.74–0.80] for prostatectomy; 0.87 [95% CI, 0.80–0.94] for external radiotherapy; and 0.90 [95% CI, 0.85–0.95] for brachytherapy). Conclusion Stratification by pretreatment patient characteristics and treatment details enables prediction of erectile function 2 years after prostatectomy, external radiotherapy, or brachytherapy for prostate cancer. PMID:21934053

A face only an investor could love: CEOs' facial structure predicts their firms' financial performance.

PubMed

Wong, Elaine M; Ormiston, Margaret E; Haselhuhn, Michael P

2011-12-01

Researchers have theorized that innate personal traits are related to leadership success. Although links between psychological characteristics and leadership success have been well established, research has yet to identify any objective physical traits of leaders that predict organizational performance. In the research reported here, we identified leaders' facial structure as a specific physical trait that correlates with organizational performance. Specifically, we found that firms whose male CEOs have wider faces (relative to facial height) achieve superior financial performance. Decision-making dynamics within a firm's leadership team moderate this effect, such that the relationship between a given CEO's facial measurements and his firm's financial performance is stronger in firms with cognitively simple leadership teams.

Comparison of Different Scoring Systems Based on Both Donor and Recipient Characteristics for Predicting Outcome after Living Donor Liver Transplantation.

PubMed

Ma, Yucheng; Wang, Qing; Yang, Jiayin; Yan, Lunan

2015-01-01

In order to provide a good match between donor and recipient in liver transplantation, four scoring systems [the product of donor age and Model for End-stage Liver Disease score (D-MELD), the score to predict survival outcomes following liver transplantation (SOFT), the balance of risk score (BAR), and the transplant risk index (TRI)] based on both donor and recipient parameters were designed. This study was conducted to evaluate the performance of the four scores in living donor liver transplantation (LDLT) and compare them with the MELD score. The clinical data of 249 adult patients undergoing LDLT in our center were retrospectively evaluated. The area under the receiver operating characteristic curves (AUCs) of each score were calculated and compared at 1-, 3-, 6-month and 1-year after LDLT. The BAR at 1-, 3-, 6-month and 1-year after LDLT and the D-MELD and TRI at 1-, 3- and 6-month after LDLT showed acceptable performances in the prediction of survival (AUC>0.6), while the SOFT showed poor discrimination at 6-month after LDLT (AUC = 0.569). In addition, the D-MELD and BAR displayed positive correlations with the length of ICU stay (D-MELD, p = 0.025; BAR, p = 0.022). The SOFT was correlated with the time of mechanical ventilation (p = 0.022). The D-MELD, BAR and TRI provided acceptable performance in predicting survival after LDLT. However, even though these scoring systems were based on both donor and recipient parameters, only the BAR provided better performance than the MELD in predicting 1-year survival after LDLT.

Comparison of Different Scoring Systems Based on Both Donor and Recipient Characteristics for Predicting Outcome after Living Donor Liver Transplantation

PubMed Central

2015-01-01

Background and Objectives In order to provide a good match between donor and recipient in liver transplantation, four scoring systems [the product of donor age and Model for End-stage Liver Disease score (D-MELD), the score to predict survival outcomes following liver transplantation (SOFT), the balance of risk score (BAR), and the transplant risk index (TRI)] based on both donor and recipient parameters were designed. This study was conducted to evaluate the performance of the four scores in living donor liver transplantation (LDLT) and compare them with the MELD score. Patients and Methods The clinical data of 249 adult patients undergoing LDLT in our center were retrospectively evaluated. The area under the receiver operating characteristic curves (AUCs) of each score were calculated and compared at 1-, 3-, 6-month and 1-year after LDLT. Results The BAR at 1-, 3-, 6-month and 1-year after LDLT and the D-MELD and TRI at 1-, 3- and 6-month after LDLT showed acceptable performances in the prediction of survival (AUC>0.6), while the SOFT showed poor discrimination at 6-month after LDLT (AUC = 0.569). In addition, the D-MELD and BAR displayed positive correlations with the length of ICU stay (D-MELD, p = 0.025; BAR, p = 0.022). The SOFT was correlated with the time of mechanical ventilation (p = 0.022). Conclusion The D-MELD, BAR and TRI provided acceptable performance in predicting survival after LDLT. However, even though these scoring systems were based on both donor and recipient parameters, only the BAR provided better performance than the MELD in predicting 1-year survival after LDLT. PMID:26378786

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.

Systems, methods and computer-readable media to model kinetic performance of rechargeable electrochemical devices

DOEpatents

Gering, Kevin L.

2013-01-01

A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics. The computing system also analyzes the cell information of the electrochemical cell with a Butler-Volmer (BV) expression modified to determine exchange current density of the electrochemical cell by including kinetic performance information related to pulse-time dependence, electrode surface availability, or a combination thereof. A set of sigmoid-based expressions may be included with the modified-BV expression to determine kinetic performance as a function of pulse time. The determined exchange current density may be used with the modified-BV expression, with or without the sigmoid expressions, to analyze other characteristics of the electrochemical cell. Model parameters can be defined in terms of cell aging, making the overall kinetics model amenable to predictive estimates of cell kinetic performance along the aging timeline.

[Evaluation of performance of five bioinformatics software for the prediction of missense mutations].

PubMed

Chen, Qianting; Dai, Congling; Zhang, Qianjun; Du, Juan; Li, Wen

2016-10-01

To study the prediction performance evaluation with five kinds of bioinformatics software (SIFT, PolyPhen2, MutationTaster, Provean, MutationAssessor). From own database for genetic mutations collected over the past five years, Chinese literature database, Human Gene Mutation Database, and dbSNP, 121 missense mutations confirmed by functional studies, and 121 missense mutations suspected to be pathogenic by pedigree analysis were used as positive gold standard, while 242 missense mutations with minor allele frequency (MAF)>5% in dominant hereditary diseases were used as negative gold standard. The selected mutations were predicted with the five software. Based on the results, the performance of the five software was evaluated for their sensitivity, specificity, positive predict value, false positive rate, negative predict value, false negative rate, false discovery rate, accuracy, and receiver operating characteristic curve (ROC). In terms of sensitivity, negative predictive value and false negative rate, the rank was MutationTaster, PolyPhen2, Provean, SIFT, and MutationAssessor. For specificity and false positive rate, the rank was MutationTaster, Provean, MutationAssessor, SIFT, and PolyPhen2. For positive predict value and false discovery rate, the rank was MutationTaster, Provean, MutationAssessor, PolyPhen2, and SIFT. For area under the ROC curve (AUC) and accuracy, the rank was MutationTaster, Provean, PolyPhen2, MutationAssessor, and SIFT. The prediction performance of software may be different when using different parameters. Among the five software, MutationTaster has the best prediction performance.

Thrust and drag characteristics of a convergent-divergent nozzle with various exhaust jet temperatures

NASA Technical Reports Server (NTRS)

Hearth, Donald P; Wilcox, Fred A

1954-01-01

An investigation was conducted in the 8-by-6 foot supersonic wind tunnel on the effect of exhaust-gas temperatures on the external and internal characteristics of a convergent-divergent nozzle having an area expansion ratio of 1.83. Data were obtained over a pressure-ratio range from 1 to 20 at free-stream Mach numbers of 1.6 and 2.0 for exhaust temperatures of 860 degrees, 1650 degrees, and 2000 degrees R. Results of this investigation indicated that generally both the internal and external performance characteristics were only slightly affected by a large change in jet temperature. The small differences in performance which did occur were predicted satisfactorily from theoretical considerations.

The four spot time-of-flight laser anemometer

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

1985-01-01

The newly constructed, four-spot anemometer was shown to perform as predicted. The new anemometer's measurement region has the required characteristics: wide acceptance angle and high spatial selectivity to permit measurements in turbulent, hostile environments.

An analytical technique for predicting the characteristics of a flexible wing equipped with an active flutter-suppression system and comparison with wind-tunnel data

NASA Technical Reports Server (NTRS)

Abel, I.

1979-01-01

An analytical technique for predicting the performance of an active flutter-suppression system is presented. This technique is based on the use of an interpolating function to approximate the unsteady aerodynamics. The resulting equations are formulated in terms of linear, ordinary differential equations with constant coefficients. This technique is then applied to an aeroelastic model wing equipped with an active flutter-suppression system. Comparisons between wind-tunnel data and analysis are presented for the wing both with and without active flutter suppression. Results indicate that the wing flutter characteristics without flutter suppression can be predicted very well but that a more adequate model of wind-tunnel turbulence is required when the active flutter-suppression system is used.

The role of visual attention in predicting driving impairment in older adults.

PubMed

Hoffman, Lesa; McDowd, Joan M; Atchley, Paul; Dubinsky, Richard

2005-12-01

This study evaluated the role of visual attention (as measured by the DriverScan change detection task and the Useful Field of View Test [UFOV]) in the prediction of driving impairment in 155 adults between the ages of 63 and 87. In contrast to previous research, participants were not oversampled for visual impairment or history of automobile accidents. Although a history of automobile accidents within the past 3 years could not be predicted using any variable, driving performance in a low-fidelity simulator could be significantly predicted by performance in the change detection task and by the divided and selection attention subtests of the UFOV in structural equation models. The sensitivity and specificity of each measure in identifying at-risk drivers were also evaluated with receiver operating characteristic curves.

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

PubMed

Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

2015-08-01

Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Iodine concentration: a new, important characteristic of the spot sign that predicts haematoma expansion.

PubMed

Fu, Fan; Sun, Shengjun; Liu, Liping; Li, Jianying; Su, Yaping; Li, Yingying

2018-04-19

The computed tomography angiography (CTA) spot sign is a validated predictor of haematoma expansion (HE) in spontaneous intracerebral haemorrhage (SICH). We investigated whether defining the iodine concentration (IC) inside the spot sign and the haematoma on Gemstone spectral imaging (GSI) would improve its sensitivity and specificity for predicting HE. From 2014 to 2016, we prospectively enrolled 65 SICH patients who underwent single-phase spectral CTA within 6 h. Logistic regression was performed to assess the risk factors for HE. The predictive performance of individual spot sign characteristics was examined via receiver operating characteristic (ROC) analysis. The spot sign was detected in 46.1% (30/65) of patients. ROC analysis indicated that IC inside the spot sign had the greatest area under the ROC curve for HE (0.858; 95% confidence interval, 0.727-0.989; p = 0.003). Multivariate analysis found that spot sign with higher IC (i.e. IC > 7.82 100 μg/ml) was an independent predictor of HE (odds ratio = 34.27; 95% confidence interval, 5.608-209.41; p < 0.001) with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 0.81, 0.75, 0.90 and 0.60, respectively; while the spot sign showed sensitivity, specificity, PPV and NPV of 0.81, 0.79, 0.73 and 0.86. Logistic regression analysis indicated that the IC in haematomas was independently associated with HE (odds ratio = 1.525; 95% confidence interval, 1.041-2.235; p = 0.030). ICs in haematoma and in spot sign were all independently associated with HE. IC analysis in spectral imaging may help to identify SICH patients for targeted haemostatic therapy. • Iodine concentration in spot sign and haematoma can predict haematoma expansion • Spectral imaging could measure the IC inside the spot sign and haematoma • IC in spot sign improved the positive predictive value (PPV) cf. CTA.

Abstracts of Presentations at Workshop on Unsteady and Two-Phase-Flows, Held in London, England on June 28-29, 1990

DTIC Science & Technology

1990-06-29

has been found to be a modification of the STAN’ program from Crawford and Kays2. An important characteristic of any boundary layer prediction program...function of freestream turbulence intensity, helped in predicting heat transfer rates between the hot gases and the b’arie surface. a Professor...be a modulator of transition to turbulence and the boundary layer prediction programs currently available have a poor performance in such flows

Genetic determinants of freckle occurrence in the Spanish population: Towards ephelides prediction from human DNA samples.

PubMed

Hernando, Barbara; Ibañez, Maria Victoria; Deserio-Cuesta, Julio Alberto; Soria-Navarro, Raquel; Vilar-Sastre, Inca; Martinez-Cadenas, Conrado

2018-03-01

Prediction of human pigmentation traits, one of the most differentiable externally visible characteristics among individuals, from biological samples represents a useful tool in the field of forensic DNA phenotyping. In spite of freckling being a relatively common pigmentation characteristic in Europeans, little is known about the genetic basis of this largely genetically determined phenotype in southern European populations. In this work, we explored the predictive capacity of eight freckle and sunlight sensitivity-related genes in 458 individuals (266 non-freckled controls and 192 freckled cases) from Spain. Four loci were associated with freckling (MC1R, IRF4, ASIP and BNC2), and female sex was also found to be a predictive factor for having a freckling phenotype in our population. After identifying the most informative genetic variants responsible for human ephelides occurrence in our sample set, we developed a DNA-based freckle prediction model using a multivariate regression approach. Once developed, the capabilities of the prediction model were tested by a repeated 10-fold cross-validation approach. The proportion of correctly predicted individuals using the DNA-based freckle prediction model was 74.13%. The implementation of sex into the DNA-based freckle prediction model slightly improved the overall prediction accuracy by 2.19% (76.32%). Further evaluation of the newly-generated prediction model was performed by assessing the model's performance in a new cohort of 212 Spanish individuals, reaching a classification success rate of 74.61%. Validation of this prediction model may be carried out in larger populations, including samples from different European populations. Further research to validate and improve this newly-generated freckle prediction model will be needed before its forensic application. Together with DNA tests already validated for eye and hair colour prediction, this freckle prediction model may lead to a substantially more detailed physical description of unknown individuals from DNA found at the crime scene. Copyright © 2017 Elsevier B.V. All rights reserved.

What children do on the Internet: domains visited and their relationship to socio-demographic characteristics and academic performance.

PubMed

Jackson, Linda A; Samona, Ricky; Moomaw, Jeff; Ramsay, Lauren; Murray, Christopher; Smith, Amy; Murray, Lindsay

2007-04-01

HomeNetToo is a longitudinal field study designed to examine the antecedents and consequences of home Internet use in low-income families. Participants included 140 children, mostly 13-year-old African American (83%) boys (58%), living in single-parent households (75%) where the median annual income was $15,000 (USD). This report focuses on children's Internet activities, socio-demographic characteristics related to their Internet activities, and the relationship between academic performance and Internet activities. Overall, findings indicate that low-income children initially use the Internet primarily for entertainment. As home Internet use loses its novelty children become more focused in their Internet activities, reducing the number of websites they visit and visiting more websites targeted to their specific interests. Pornography websites are popular initially, especially among boys, but their popularity decreases dramatically after 3 months. Age, race, and sex have little influence on which websites are most popular. Academic performance predicts subsequent Internet activities, and Internet activities predict subsequent academic performance. Directions for future research to identify mechanisms that mediate the relationship between Internet activities and academic performance and implications for the digital divide are discussed.

An Examination of Pre-Entry and Academic Performance Factors that Predict Persistence for Academically Underprepared Students at a Public Research University

ERIC Educational Resources Information Center

Stewart, Sheilynda F.

2010-01-01

The purpose of this study was to examine student demographic, family characteristics, pre-college, and college academic factors that predict persistence between freshmen students who were placed or not placed in remediation courses. The participants for this study were comprised of 3,213 first-time, full-time and part-time, degree-seeking freshmen…

Automated Cognitive Health Assessment From Smart Home-Based Behavior Data.

PubMed

Dawadi, Prafulla Nath; Cook, Diane Joyce; Schmitter-Edgecombe, Maureen

2016-07-01

Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and well-being assessment. In this paper, we examine the actual benefits of smart home-based analysis by monitoring daily behavior in the home and predicting clinical scores of the residents. To accomplish this goal, we propose a clinical assessment using activity behavior (CAAB) approach to model a smart home resident's daily behavior and predict the corresponding clinical scores. CAAB uses statistical features that describe characteristics of a resident's daily activity performance to train machine learning algorithms that predict the clinical scores. We evaluate the performance of CAAB utilizing smart home sensor data collected from 18 smart homes over two years. We obtain a statistically significant correlation ( r=0.72) between CAAB-predicted and clinician-provided cognitive scores and a statistically significant correlation ( r=0.45) between CAAB-predicted and clinician-provided mobility scores. These prediction results suggest that it is feasible to predict clinical scores using smart home sensor data and learning-based data analysis.

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

PubMed Central

Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

2011-01-01

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

Value of high-sensitivity C-reactive protein assays in predicting atrial fibrillation recurrence: a systematic review and meta-analysis

PubMed Central

Yo, Chia-Hung; Lee, Si-Huei; Chang, Shy-Shin; Lee, Matthew Chien-Hung; Lee, Chien-Chang

2014-01-01

Objectives We performed a systematic review and meta-analysis of studies on high-sensitivity C-reactive protein (hs-CRP) assays to see whether these tests are predictive of atrial fibrillation (AF) recurrence after cardioversion. Design Systematic review and meta-analysis. Data sources PubMed, EMBASE and Cochrane databases as well as a hand search of the reference lists in the retrieved articles from inception to December 2013. Study eligibility criteria This review selected observational studies in which the measurements of serum CRP were used to predict AF recurrence. An hs-CRP assay was defined as any CRP test capable of measuring serum CRP to below 0.6 mg/dL. Primary and secondary outcome measures We summarised test performance characteristics with the use of forest plots, hierarchical summary receiver operating characteristic curves and bivariate random effects models. Meta-regression analysis was performed to explore the source of heterogeneity. Results We included nine qualifying studies comprising a total of 347 patients with AF recurrence and 335 controls. A CRP level higher than the optimal cut-off point was an independent predictor of AF recurrence after cardioversion (summary adjusted OR: 3.33; 95% CI 2.10 to 5.28). The estimated pooled sensitivity and specificity for hs-CRP was 71.0% (95% CI 63% to 78%) and 72.0% (61% to 81%), respectively. Most studies used a CRP cut-off point of 1.9 mg/L to predict long-term AF recurrence (77% sensitivity, 65% specificity), and 3 mg/L to predict short-term AF recurrence (73% sensitivity, 71% specificity). Conclusions hs-CRP assays are moderately accurate in predicting AF recurrence after successful cardioversion. PMID:24556243

Catchments as non-linear filters: evaluating data-driven approaches for spatio-temporal predictions in ungauged basins

NASA Astrophysics Data System (ADS)

Bellugi, D. G.; Tennant, C.; Larsen, L.

2016-12-01

Catchment and climate heterogeneity complicate prediction of runoff across time and space, and resulting parameter uncertainty can lead to large accumulated errors in hydrologic models, particularly in ungauged basins. Recently, data-driven modeling approaches have been shown to avoid the accumulated uncertainty associated with many physically-based models, providing an appealing alternative for hydrologic prediction. However, the effectiveness of different methods in hydrologically and geomorphically distinct catchments, and the robustness of these methods to changing climate and changing hydrologic processes remain to be tested. Here, we evaluate the use of machine learning techniques to predict daily runoff across time and space using only essential climatic forcing (e.g. precipitation, temperature, and potential evapotranspiration) time series as model input. Model training and testing was done using a high quality dataset of daily runoff and climate forcing data for 25+ years for 600+ minimally-disturbed catchments (drainage area range 5-25,000 km2, median size 336 km2) that cover a wide range of climatic and physical characteristics. Preliminary results using Support Vector Regression (SVR) suggest that in some catchments this nonlinear-based regression technique can accurately predict daily runoff, while the same approach fails in other catchments, indicating that the representation of climate inputs and/or catchment filter characteristics in the model structure need further refinement to increase performance. We bolster this analysis by using Sparse Identification of Nonlinear Dynamics (a sparse symbolic regression technique) to uncover the governing equations that describe runoff processes in catchments where SVR performed well and for ones where it performed poorly, thereby enabling inference about governing processes. This provides a robust means of examining how catchment complexity influences runoff prediction skill, and represents a contribution towards the integration of data-driven inference and physically-based models.

Comparison of scoring systems for nonvariceal upper gastrointestinal bleeding: a multicenter prospective cohort study.

PubMed

Yang, Hae Min; Jeon, Seong Woo; Jung, Jin Tae; Lee, Dong Wook; Ha, Chang Yoon; Park, Kyung Sik; Lee, Si Hyung; Yang, Chang Heon; Park, Jun Hyung; Park, Youn Sun

2016-01-01

The Glasgow-Blatchford score (GBS) and Rockall score (RS) are widely used to assess risk in patients with upper gastrointestinal bleeding (UGIB). We compared both scoring systems and evaluated their clinical usefulness. Between February 2011 and December 2013, 1584 patients with nonvariceal UGIB were included in the study. A prospective study was conducted to compare the performance of the GBS, pre-RS, and full RS. We compared the performance of these scores using receiver operating characteristic curves. For prediction of the need for hospital-based intervention, the GBS was similar to the full RS (area under the receiver operating characteristic curves [AUROC] 0.705 vs 0.727; P = 0.282) and superior to the pre-RS (AUROC 0.705 vs 0.601; P < 0.0001). In predicting death, the full RS was superior to the GBS (AUROC 0.758 vs 0.644; P = 0.0006) and similar to the pre-RS (AUROC 0.758 vs 0.754; P = 0.869). In predicting rebleeding, the full RS was superior to both GBS (AUROC 0.642 vs 0.585; P = 0.031) and pre-RS (AUROC 0.642 vs 0.593; P = 0.0003). Of 1584 patients, 13 (0.8%) scored 0 on the GBS. Therapeutic intervention was not performed in any of these patients. The GBS is more useful than the pre-RS for predicting the need for hospital-based intervention. A cutoff value of 0 for low-risk patients who might be suitable for outpatient management is useful. The full RS is helpful in predicting death. None of the systems accurately predict rebleeding with a low AUROC. ( cris.nih.go.kr/KCT0000514). © 2015 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

Modern modeling techniques had limited external validity in predicting mortality from traumatic brain injury.

PubMed

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

2016-10-01

Prediction of medical outcomes may potentially benefit from using modern statistical modeling techniques. We aimed to externally validate modeling strategies for prediction of 6-month mortality of patients suffering from traumatic brain injury (TBI) with predictor sets of increasing complexity. We analyzed individual patient data from 15 different studies including 11,026 TBI patients. We consecutively considered a core set of predictors (age, motor score, and pupillary reactivity), an extended set with computed tomography scan characteristics, and a further extension with two laboratory measurements (glucose and hemoglobin). With each of these sets, we predicted 6-month mortality using default settings with five statistical modeling techniques: logistic regression (LR), classification and regression trees, random forests (RFs), support vector machines (SVM) and neural nets. For external validation, a model developed on one of the 15 data sets was applied to each of the 14 remaining sets. This process was repeated 15 times for a total of 630 validations. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative ability of the models. For the most complex predictor set, the LR models performed best (median validated AUC value, 0.757), followed by RF and support vector machine models (median validated AUC value, 0.735 and 0.732, respectively). With each predictor set, the classification and regression trees models showed poor performance (median validated AUC value, <0.7). The variability in performance across the studies was smallest for the RF- and LR-based models (inter quartile range for validated AUC values from 0.07 to 0.10). In the area of predicting mortality from TBI, nonlinear and nonadditive effects are not pronounced enough to make modern prediction methods beneficial. Copyright © 2016 Elsevier Inc. All rights reserved.

The influence of tyre characteristics on measures of rolling performance during cross-country mountain biking.

PubMed

Macdermid, Paul William; Fink, Philip W; Stannard, Stephen R

2015-01-01

This investigation sets out to assess the effect of five different models of mountain bike tyre on rolling performance over hard-pack mud. Independent characteristics included total weight, volume, tread surface area and tread depth. One male cyclist performed multiple (30) trials of a deceleration field test to assess reliability. Further tests performed on a separate occasion included multiple (15) trials of the deceleration test and six fixed power output hill climb tests for each tyre. The deceleration test proved to be reliable as a means of assessing rolling performance via differences in initial and final speed (coefficient of variation (CV) = 4.52%). Overall differences between tyre performance for both deceleration test (P = 0.014) and hill climb (P = 0.032) were found, enabling significant (P < 0.0001 and P = 0.049) models to be generated, allowing tyre performance prediction based on tyre characteristics. The ideal tyre for rolling and climbing performance on hard-pack surfaces would be to decrease tyre weight by way of reductions in tread surface area and tread depth while keeping volume high.

A numerical study on the thermal initiation of a confined explosive in 2-D geometry.

PubMed

Aydemir, Erdoğan; Ulas, Abdullah

2011-02-15

Insensitive munitions design against thermal stimuli like slow or fast cook-off has become a significant requirement for today's munitions. In order to achieve insensitive munitions characteristics, the response of the energetic material needs to be predicted against heating stimuli. In this study, a 2D numerical code was developed to simulate the slow and fast cook-off heating conditions of confined munitions and to obtain the response of the energetic materials. Computations were performed in order to predict the transient temperature distribution, the ignition time, and the location of ignition in the munitions. These predictions enable the designers to have an idea of when and at which location the energetic material ignites under certain adverse surrounding conditions. In the paper, the development of the code is explained and the numerical results are compared with available experimental and numerical data in the literature. Additionally, a parametric study was performed showing the effect of dimensional scaling of munitions and the heating rate on the ignition characteristics. Copyright © 2010 Elsevier B.V. All rights reserved.

Assessing a mini-application as a performance proxy for a finite element method engineering application

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

Lin, Paul T.; Heroux, Michael A.; Barrett, Richard F.

The performance of a large-scale, production-quality science and engineering application (‘app’) is often dominated by a small subset of the code. Even within that subset, computational and data access patterns are often repeated, so that an even smaller portion can represent the performance-impacting features. If application developers, parallel computing experts, and computer architects can together identify this representative subset and then develop a small mini-application (‘miniapp’) that can capture these primary performance characteristics, then this miniapp can be used to both improve the performance of the app as well as provide a tool for co-design for the high-performance computing community.more » However, a critical question is whether a miniapp can effectively capture key performance behavior of an app. This study provides a comparison of an implicit finite element semiconductor device modeling app on unstructured meshes with an implicit finite element miniapp on unstructured meshes. The goal is to assess whether the miniapp is predictive of the performance of the app. Finally, single compute node performance will be compared, as well as scaling up to 16,000 cores. Results indicate that the miniapp can be reasonably predictive of the performance characteristics of the app for a single iteration of the solver on a single compute node.« less

Assessing a mini-application as a performance proxy for a finite element method engineering application

DOE PAGES

Lin, Paul T.; Heroux, Michael A.; Barrett, Richard F.; ...

2015-07-30

The performance of a large-scale, production-quality science and engineering application (‘app’) is often dominated by a small subset of the code. Even within that subset, computational and data access patterns are often repeated, so that an even smaller portion can represent the performance-impacting features. If application developers, parallel computing experts, and computer architects can together identify this representative subset and then develop a small mini-application (‘miniapp’) that can capture these primary performance characteristics, then this miniapp can be used to both improve the performance of the app as well as provide a tool for co-design for the high-performance computing community.more » However, a critical question is whether a miniapp can effectively capture key performance behavior of an app. This study provides a comparison of an implicit finite element semiconductor device modeling app on unstructured meshes with an implicit finite element miniapp on unstructured meshes. The goal is to assess whether the miniapp is predictive of the performance of the app. Finally, single compute node performance will be compared, as well as scaling up to 16,000 cores. Results indicate that the miniapp can be reasonably predictive of the performance characteristics of the app for a single iteration of the solver on a single compute node.« less

A predictive model for diagnosing bipolar disorder based on the clinical characteristics of major depressive episodes in Chinese population.

PubMed

Gan, Zhaoyu; Diao, Feici; Wei, Qinling; Wu, Xiaoli; Cheng, Minfeng; Guan, Nianhong; Zhang, Ming; Zhang, Jinbei

2011-11-01

A correct timely diagnosis of bipolar depression remains a big challenge for clinicians. This study aimed to develop a clinical characteristic based model to predict the diagnosis of bipolar disorder among patients with current major depressive episodes. A prospective study was carried out on 344 patients with current major depressive episodes, with 268 completing 1-year follow-up. Data were collected through structured interviews. Univariate binary logistic regression was conducted to select potential predictive variables among 19 initial variables, and then multivariate binary logistic regression was performed to analyze the combination of risk factors and build a predictive model. Receiver operating characteristic (ROC) curve was plotted. Of 19 initial variables, 13 variables were preliminarily selected, and then forward stepwise exercise produced a final model consisting of 6 variables: age at first onset, maximum duration of depressive episodes, somatalgia, hypersomnia, diurnal variation of mood, irritability. The correct prediction rate of this model was 78% (95%CI: 75%-86%) and the area under the ROC curve was 0.85 (95%CI: 0.80-0.90). The cut-off point for age at first onset was 28.5 years old, while the cut-off point for maximum duration of depressive episode was 7.5 months. The limitations of this study include small sample size, relatively short follow-up period and lack of treatment information. Our predictive models based on six clinical characteristics of major depressive episodes prove to be robust and can help differentiate bipolar depression from unipolar depression. Copyright © 2011 Elsevier B.V. All rights reserved.

Performance of a block detector PET scanner in imaging non-pure positron emitters—modelling and experimental validation with 124I

NASA Astrophysics Data System (ADS)

Robinson, S.; Julyan, P. J.; Hastings, D. L.; Zweit, J.

2004-12-01

The key performance measures of resolution, count rate, sensitivity and scatter fraction are predicted for a dedicated BGO block detector patient PET scanner (GE Advance) in 2D mode for imaging with the non-pure positron-emitting radionuclides 124I, 55Co, 61Cu, 62Cu, 64Cu and 76Br. Model calculations including parameters of the scanner, decay characteristics of the radionuclides and measured parameters in imaging the pure positron-emitter 18F are used to predict performance according to the National Electrical Manufacturers Association (NEMA) NU 2-1994 criteria. Predictions are tested with measurements made using 124I and show that, in comparison with 18F, resolution degrades by 1.2 mm radially and tangentially throughout the field-of-view (prediction: 1.2 mm), count-rate performance reduces considerably and in close accordance with calculations, sensitivity decreases to 23.4% of that with 18F (prediction: 22.9%) and measured scatter fraction increases from 10.0% to 14.5% (prediction: 14.7%). Model predictions are expected to be equally accurate for other radionuclides and may be extended to similar scanners. Although performance is worse with 124I than 18F, imaging is not precluded in 2D mode. The viability of 124I imaging and performance in a clinical context compared with 18F is illustrated with images of a patient with recurrent thyroid cancer acquired using both [124I]-sodium iodide and [18F]-2-fluoro-2-deoxyglucose.

Performance of the European System for Cardiac Operative Risk Evaluation II: a meta-analysis of 22 studies involving 145,592 cardiac surgery procedures.

PubMed

Guida, Pietro; Mastro, Florinda; Scrascia, Giuseppe; Whitlock, Richard; Paparella, Domenico

2014-12-01

A systematic review of the European System for Cardiac Operative Risk Evaluation (euroSCORE) II performance for prediction of operative mortality after cardiac surgery has not been performed. We conducted a meta-analysis of studies based on the predictive accuracy of the euroSCORE II. We searched the Embase and PubMed databases for all English-only articles reporting performance characteristics of the euroSCORE II. The area under the receiver operating characteristic curve, the observed/expected mortality ratio, and observed-expected mortality difference with their 95% confidence intervals were analyzed. Twenty-two articles were selected, including 145,592 procedures. Operative mortality occurred in 4293 (2.95%), whereas the expected events according to euroSCORE II were 4802 (3.30%). Meta-analysis of these studies provided an area under the receiver operating characteristic curve of 0.792 (95% confidence interval, 0.773-0.811), an estimated observed/expected ratio of 1.019 (95% confidence interval, 0.899-1.139), and observed-expected difference of 0.125 (95% confidence interval, -0.269 to 0.519). Statistical heterogeneity was detected among retrospective studies including less recent procedures. Subgroups analysis confirmed the robustness of combined estimates for isolated valve procedures and those combined with revascularization surgery. A significant overestimation of the euroSCORE II with an observed/expected ratio of 0.829 (95% confidence interval, 0.677-0.982) was observed in isolated coronary artery bypass grafting and a slight underestimation of predictions in high-risk patients (observed/expected ratio 1.253 and observed-expected difference 1.859). Despite the heterogeneity, the results from this meta-analysis show a good overall performance of the euroSCORE II in terms of discrimination and accuracy of model predictions for operative mortality. Validation of the euroSCORE II in prospective populations needs to be further studied for a continuous improvement of patients' risk stratification before cardiac surgery. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Personal and environmental characteristics predicting burnout among certified athletic trainers at National Collegiate Athletic Association institutions.

PubMed

Kania, Michelle L; Meyer, Barbara B; Ebersole, Kyle T

2009-01-01

Recent research in the health care professions has shown that specific personal and environmental characteristics can predict burnout, which is a negative coping strategy related to stressful situations. Burnout has been shown to result in physiologic (eg, headaches, difficulty sleeping, poor appetite), psychological (eg, increased negative self-talk, depression, difficulty in interpersonal relationships), and behavioral (eg, diminished care, increased absenteeism, attrition) symptoms. To examine the relationship between selected personal and environmental characteristics and burnout among certified athletic trainers (ATs). Cross-sectional survey. A demographic survey that was designed for this study and the Maslach Burnout Inventory-Human Services Survey. A total of 206 ATs employed at National Collegiate Athletic Association (NCAA) institutions as clinical ATs volunteered. We assessed personal and environmental characteristics of ATs with the demographic survey and measured burnout using the Maslach Burnout Inventory-Human Services Survey. Multiple regression analyses were performed to examine relationships between specific personal and environmental characteristics and each of the 3 subscales of burnout (emotional exhaustion, depersonalization, personal accomplishment). Most ATs we surveyed experienced low to average levels of burnout. Personal characteristics predicted 45.5% of the variance in emotional exhaustion (P < .001), 21.5% of the variance in depersonalization (P < .001), and 24.8% of the variance in personal accomplishment (P < .001). Environmental characteristics predicted 16.7% of the variance in emotional exhaustion (P = .005), 14.4% of the variance in depersonalization (P = .024), and 10.4% of the variance in personal accomplishment (P = .209). Stress level and coaches' pressure to medically clear athletes predicted ratings on all 3 subscales of burnout. Our findings were similar to those of other studies of burnout among NCAA Division I ATs, coaches, and coach-teachers. The results also support the Cognitive-Affective Model of Athletic Burnout proposed by Smith. Finally, these results indicate new areas of concentration for burnout research and professional practice.

On-orbit experience with the HEAO attitude control subsystem

NASA Technical Reports Server (NTRS)

Hoffman, D. P.; Berkery, E. A.

1978-01-01

The first satellite (HEAO-1) in the High Energy Astronomy Observatory Program series was launched successfully on Aug. 12, 1977. To date it has completed over nine months of orbital operation in a science data gathering mode. During this period all attitude control modes have been exercised and all primary mission objectives have been achieved. This paper highlights the characteristics of the attitude control subsystem design and compares the predicted performance with the actual flight operations experience. Environmental disturbance modeling, component hardware/software characteristics, and overall attitude control performance are reviewed and are found to compare very well with the prelaunch analytical predictions. Brief comments are also included regarding the operations aspects of the attitude control subsystem. The experience in this regard demonstrates the effectiveness of the design flexibility afforded by the presence of a general purpose digital processor in the subsystem flight hardware implementation.

[Executive functions and stressful characteristics of children with attention-deficit hyperactivity disorder: influence on behavioral problems during adolescence].

PubMed

Colomer-Diago, Carla; Miranda-Casas, Ana; Herdoiza-Arroyo, Paulina; Presentación-Herrero, M Jesús

2012-02-29

The identification of possible factors that are influencing the course of attention-deficit hyperactivity disorder (ADHD) will allow the development of more effective early intervention strategies. AIMS. This research, which used a longitudinal and correlational design, set out to examine the temporal consistency of the primary symptoms and ADHD associated problems. In addition, the relationships and predictive power of working memory, inhibition and stressful characteristics of children with ADHD on the disorder symptoms and behavioral problems in adolescence was analyzed. This study included 65 families with children diagnosed with ADHD. In phase 1 children performed verbal working memory, visuo-spatial and inhibition tests, and information from parents about stressful characteristics of children was collected. In phase 1 and in the follow-up phase, which took place three years later, parents and teachers reported on the primary symptoms of ADHD and behavioral problems. Inattention symptoms as well as most behavioral problems were stable over time, while hyperactivity/impulsivity symptoms decreased. Moreover, neither working memory nor inhibition showed power to predict the central manifestations of ADHD or behavioral problems, while stressful characteristics of demandingness, low adaptability and negative mood had a moderate predictive capacity. These results confirm the role of stressful child characteristics as a risk factor in the course of ADHD.

Prediction of fetal growth restriction using estimated fetal weight vs a combined screening model in the third trimester.

PubMed

Miranda, J; Rodriguez-Lopez, M; Triunfo, S; Sairanen, M; Kouru, H; Parra-Saavedra, M; Crovetto, F; Figueras, F; Crispi, F; Gratacós, E

2017-11-01

To compare the performance of third-trimester screening, based on estimated fetal weight centile (EFWc) vs a combined model including maternal baseline characteristics, fetoplacental ultrasound and maternal biochemical markers, for the prediction of small-for-gestational-age (SGA) neonates and late-onset fetal growth restriction (FGR). This was a nested case-control study within a prospective cohort of 1590 singleton gestations undergoing third-trimester (32 + 0 to 36 + 6 weeks' gestation) evaluation. Maternal baseline characteristics, mean arterial pressure, fetoplacental ultrasound and circulating biochemical markers (placental growth factor (PlGF), lipocalin-2, unconjugated estriol and inhibin A) were assessed in all women who subsequently delivered a SGA neonate (n = 175), defined as birth weight < 10 th centile according to customized standards, and in a control group (n = 875). Among SGA cases, those with birth weight < 3 rd centile and/or abnormal uterine artery pulsatility index (UtA-PI) and/or abnormal cerebroplacental ratio (CPR) were classified as FGR. Logistic regression predictive models were developed for SGA and FGR, and their performance was compared with that obtained using EFWc alone. In SGA cases, EFWc, CPR Z-score and maternal serum concentrations of unconjugated estriol and PlGF were significantly lower, while mean UtA-PI Z-score and lipocalin-2 and inhibin A concentrations were significantly higher, compared with controls. Using EFWc alone, 52% (area under receiver-operating characteristics curve (AUC), 0.82 (95% CI, 0.77-0.85)) of SGA and 64% (AUC, 0.86 (95% CI, 0.81-0.91)) of FGR cases were predicted at a 10% false-positive rate. A combined screening model including a-priori risk (maternal characteristics), EFWc, UtA-PI, PlGF and estriol (with lipocalin-2 for SGA) achieved a detection rate of 61% (AUC, 0.86 (95% CI, 0.83-0.89)) for SGA cases and 77% (AUC, 0.92 (95% CI, 0.88-0.95)) for FGR. The combined model for the prediction of SGA and FGR performed significantly better than did using EFWc alone (P < 0.001 and P = 0.002, respectively). A multivariable integrative model of maternal characteristics, fetoplacental ultrasound and maternal biochemical markers modestly improved the detection of SGA and FGR cases at 32-36 weeks' gestation when compared with screening based on EFWc alone. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2016 ISUOG. Published by John Wiley & Sons Ltd.

Assessing the role of mini-applications in predicting key performance characteristics of scientific and engineering applications

DOE PAGES

Barrett, R. F.; Crozier, P. S.; Doerfler, D. W.; ...

2014-09-28

Computational science and engineering application programs are typically large, complex, and dynamic, and are often constrained by distribution limitations. As a means of making tractable rapid explorations of scientific and engineering application programs in the context of new, emerging, and future computing architectures, a suite of miniapps has been created to serve as proxies for full scale applications. Each miniapp is designed to represent a key performance characteristic that does or is expected to significantly impact the runtime performance of an application program. In this paper we introduce a methodology for assessing the ability of these miniapps to effectively representmore » these performance issues. We applied this methodology to four miniapps, examining the linkage between them and an application they are intended to represent. Herein we evaluate the fidelity of that linkage. This work represents the initial steps required to begin to answer the question, ''Under what conditions does a miniapp represent a key performance characteristic in a full app?''« less

How Do Task Characteristics Affect Learning and Performance? The Roles of Variably Mapped and Dynamic Tasks

ERIC Educational Resources Information Center

Macnamara, Brooke N.; Frank, David J.

2018-01-01

For well over a century, scientists have investigated individual differences in performance. The majority of studies have focused on either differences in practice, or differences in cognitive resources. However, the predictive ability of either practice or cognitive resources varies considerably across tasks. We are the first to examine task…

Cascade generalized predictive control strategy for boiler drum level.

PubMed

Xu, Min; Li, Shaoyuan; Cai, Wenjian

2005-07-01

This paper proposes a cascade model predictive control scheme for boiler drum level control. By employing generalized predictive control structures for both inner and outer loops, measured and unmeasured disturbances can be effectively rejected, and drum level at constant load is maintained. In addition, nonminimum phase characteristic and system constraints in both loops can be handled effectively by generalized predictive control algorithms. Simulation results are provided to show that cascade generalized predictive control results in better performance than that of well tuned cascade proportional integral differential controllers. The algorithm has also been implemented to control a 75-MW boiler plant, and the results show an improvement over conventional control schemes.

Fiber-optic epoxy composite cure sensor. II. Performance characteristics

NASA Astrophysics Data System (ADS)

Lam, Kai-Yuen; Afromowitz, Martin A.

1995-09-01

The performance of a fiber-optic epoxy composite cure sensor, as previously proposed, depends on the optical properties and the reaction kinetics of the epoxy. The reaction kinetics of a typical epoxy system are presented. It is a third-order autocatalytic reaction with a peak observed in each isothermal reaction-rate curve. A model is derived to describe the performance characteristics of the epoxy cure sensor. If a composite coupon is cured at an isothermal temperature, the sensor signal can be used to predict the time when the gel point occurs and to monitor the cure process. The sensor is also shown to perform well in nonstoichiometric epoxy matrices. In addition the sensor can detect the end of the cure without calibration.

Liquid Engine Design: Effect of Chamber Dimensions on Specific Impulse

NASA Technical Reports Server (NTRS)

Hoggard, Lindsay; Leahy, Joe

2009-01-01

Which assumption of combustion chemistry - frozen or equilibrium - should be used in the prediction of liquid rocket engine performance calculations? Can a correlation be developed for this? A literature search using the LaSSe tool, an online repository of old rocket data and reports, was completed. Test results of NTO/Aerozine-50 and Lox/LH2 subscale and full-scale injector and combustion chamber test results were found and studied for this task. NASA code, Chemical Equilibrium with Applications (CEA) was used to predict engine performance using both chemistry assumptions, defined here. Frozen- composition remains frozen during expansion through the nozzle. Equilibrium- instantaneous chemical equilibrium during nozzle expansion. Chamber parameters were varied to understand what dimensions drive chamber C* and Isp. Contraction Ratio is the ratio of the nozzle throat area to the area of the chamber. L is the length of the chamber. Characteristic chamber length, L*, is the length that the chamber would be if it were a straight tube and had no converging nozzle. Goal: Develop a qualitative and quantitative correlation for performance parameters - Specific Impulse (Isp) and Characteristic Velocity (C*) - as a function of one or more chamber dimensions - Contraction Ratio (CR), Chamber Length (L ) and/or Characteristic Chamber Length (L*). Determine if chamber dimensions can be correlated to frozen or equilibrium chemistry.

Shuttle STS-2 mission communication systems RF coverage and performance predictions. Volume 1: Ascent

NASA Technical Reports Server (NTRS)

Porter, J. A.; Gibson, J. S.; Kroll, Q. D.; Loh, Y. C.

1981-01-01

The RF communications capabilities and nominally expected performance for the ascent phase of the second orbital flight of the shuttle are provided. Predicted performance is given mainly in the form of plots of signal strength versus elapsed mission time for the STDN (downlink) and shuttle orbiter (uplink) receivers for the S-band PM and FM, and UHF systems. Performance of the NAV and landing RF systems is treated for RTLS abort, since in this case the spacecraft will loop around and return to the launch site. NAV and landing RF systems include TACAN, MSBLS, and C-band altimeter. Signal strength plots were produced by a computer program which combines the spacecraft trajectory, antenna patterns, transmit and receive performance characteristics, and system mathematical models. When available, measured spacecraft parameters were used in the predictions; otherwise, specified values were used. Specified ground station parameter values were also used. Thresholds and other criteria on the graphs are explained.

Vehicle integration effects on hypersonic waveriders. M.S. Thesis - George Washington Univ.

NASA Technical Reports Server (NTRS)

Cockrell, Charles Edward, Jr.

1994-01-01

The integration of a class of hypersonic high-lift configurations known as waveriders into hypersonic cruise vehicles was evaluated. Waveriders offer advantages in aerodynamic performance and propulsion/airframe integration (PAI) characteristics over conventional hypersonic shapes. A wind-tunnel model was developed which integrates realistic vehicle components with two waverider shapes, referred to as the 'straight-wing' and 'cranked-wing' shapes. Both shapes were conical-flow-derived waveriders at a design Mach number of 4.0. The cranked-wing shape was designed to provide advantages in subsonic performance and directional stability over conventional waveriders. Experimental data and limited computational fluid dynamics (CFD) predictions were obtained over a Mach number range of 2.3 to 4.63 at a Reynolds number of 2.0x10(exp 6) per foot. The CFD predictions and flow visualization data confirmed the shock attachment characteristics of the baseline waverider shapes and illustrated the waverider flow-field properties. Both CFD predictions and experimental data showed that no significant performance degradations occur at off-design Mach numbers for the waverider shapes and the integrated configurations. The experimental data showed that the effects of adding a realistic canopy were minimal. The effects of adding engine components were to increase the drag and thus degrade the aerodynamic performance of the configuration. A significant degradation in aerodynamic performance was observed when 0 degree control surfaces were added to close the blunt base of the waverider to a sharp trailing edge. A comparison of the fully-integrated waverider models to the baseline shapes showed that the performance was significantly degraded when all of the components were added to the waveriders. The fully-integrated configurations studied here do not offer significant performance advantages over conventional hypersonic vehicles, but still offer advantages in air-breathing propulsion integration. Additionally, areas are identified in this study where improvements could be made to enhance the performance. Both fully-integrated configurations are longitudinally unstable over the Mach number range studied for unpowered conditions. The cranked-wing fully-integrated configuration provided significantly better lateral-directional stability characteristics than the straight-wing configuration.

Examining the relationships between attention deficit/hyperactivity disorder and developmental coordination disorder symptoms, and writing performance in Japanese second grade students.

PubMed

Noda, Wataru; Ito, Hiroyuki; Fujita, Chikako; Ohnishi, Masafumi; Takayanagi, Nobuya; Someki, Fumio; Nakajima, Syunji; Ohtake, Satoko; Mochizuki, Naoto; Tsujii, Masatsugu

2013-09-01

The purpose of this study was to explore the relationships between attention deficit/hyperactivity disorder and developmental coordination disorder symptoms and writing performance in Japanese second grade students from regular classrooms. The second grade students (N=873) in Japanese public elementary schools participated in this study. We examined a variety of writing tasks, such as tracing, copying, handwriting (Hiragana and Katakana), and spelling (Hiragana, Katakana, and Kanji). We employed the Japanese version of the home form ADHD-rating scale (ADHD-RS) and the Japanese version of the Developmental Coordination Disorder Questionnaire (DCDQ-J) to assess the developmental characteristics of the participating children. Seven writing performance scores were submitted to a principal component analysis with a promax rotation, which yielded three composite scores (Spelling Accuracy, Tracing and Copying Accuracy, and Handwriting Fluency). A multiple regression analysis found that inattention predicted Spelling Accuracy and Handwriting Fluency and that hyperactive-impulsive predicted Handwriting Fluency. In addition, fine motor ability predicted Tracing and Copying Accuracy. The current study offered empirical evidence suggesting that developmental characteristics such as inattention and fine motor skill are related to writing difficulties in Japanese typical developing children. Copyright © 2013 Elsevier Ltd. All rights reserved.

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

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

Thomas, Edward V.; Lewis, John. R.; Anderson-Cook, Christine Michaela

The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictatesmore » the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.« less

Selecting an Informative/Discriminating Multivariate Response for Inverse Prediction

DOE PAGES

Thomas, Edward V.; Lewis, John. R.; Anderson-Cook, Christine Michaela; ...

2017-07-01

The inverse prediction is important in a variety of scientific and engineering applications, such as to predict properties/characteristics of an object by using multiple measurements obtained from it. Inverse prediction can be accomplished by inverting parameterized forward models that relate the measurements (responses) to the properties/characteristics of interest. Sometimes forward models are computational/science based; but often, forward models are empirically based response surface models, obtained by using the results of controlled experimentation. For empirical models, it is important that the experiments provide a sound basis to develop accurate forward models in terms of the properties/characteristics (factors). And while nature dictatesmore » the causal relationships between factors and responses, experimenters can control the complexity, accuracy, and precision of forward models constructed via selection of factors, factor levels, and the set of trials that are performed. Recognition of the uncertainty in the estimated forward models leads to an errors-in-variables approach for inverse prediction. The forward models (estimated by experiments or science based) can also be used to analyze how well candidate responses complement one another for inverse prediction over the range of the factor space of interest. Furthermore, one may find that some responses are complementary, redundant, or noninformative. Simple analysis and examples illustrate how an informative and discriminating subset of responses could be selected among candidates in cases where the number of responses that can be acquired during inverse prediction is limited by difficulty, expense, and/or availability of material.« less

Performance-based measures and behavioral ratings of executive function in diagnosing attention-deficit/hyperactivity disorder in children.

PubMed

Tan, Alexander; Delgaty, Lauren; Steward, Kayla; Bunner, Melissa

2018-04-16

Deficits in real-world executive functioning (EF) are a frequent characteristic of attention-deficit/hyperactivity disorder (ADHD). However, the predictive value of using performance-based and behavioral rating measures of EF when diagnosing ADHD remains unclear. The current study investigates the use of performance-based EF measures and a parent-report questionnaire with established ecological validity and clinical utility when diagnosing ADHD. Participants included 21 healthy controls, 21 ADHD-primary inattentive, and 21 ADHD-combined type subjects aged 6-15 years. A brief neuropsychological battery was administered to each subject including common EF assessment measures. Significant differences were not found between groups on most performance-based EF measures, whereas significant differences (p < 0.05) were found on most parent-report behavioral rating scales. Furthermore, performance-based measures did not predict group membership above chance levels. Results further support differences in predictive value of EF performance-based measures compared to parent-report questionnaires when diagnosing ADHD. Further research must investigate the relationship between performance-based and behavioral rating measures when assessing EF in ADHD.

Uncertainty estimates of purity measurements based on current information: toward a "live validation" of purity methods.

PubMed

Apostol, Izydor; Kelner, Drew; Jiang, Xinzhao Grace; Huang, Gang; Wypych, Jette; Zhang, Xin; Gastwirt, Jessica; Chen, Kenneth; Fodor, Szilan; Hapuarachchi, Suminda; Meriage, Dave; Ye, Frank; Poppe, Leszek; Szpankowski, Wojciech

2012-12-01

To predict precision and other performance characteristics of chromatographic purity methods, which represent the most widely used form of analysis in the biopharmaceutical industry. We have conducted a comprehensive survey of purity methods, and show that all performance characteristics fall within narrow measurement ranges. This observation was used to develop a model called Uncertainty Based on Current Information (UBCI), which expresses these performance characteristics as a function of the signal and noise levels, hardware specifications, and software settings. We applied the UCBI model to assess the uncertainty of purity measurements, and compared the results to those from conventional qualification. We demonstrated that the UBCI model is suitable to dynamically assess method performance characteristics, based on information extracted from individual chromatograms. The model provides an opportunity for streamlining qualification and validation studies by implementing a "live validation" of test results utilizing UBCI as a concurrent assessment of measurement uncertainty. Therefore, UBCI can potentially mitigate the challenges associated with laborious conventional method validation and facilitates the introduction of more advanced analytical technologies during the method lifecycle.

Personality characteristics and trait clusters in final stage astronaut selection.

PubMed

Musson, David M; Sandal, Gro M; Helmreich, Robert L

2004-04-01

This paper presents personality testing data from final stage applicants to the NASA astronaut program. Questions addressed include whether personality predicted final selection into the astronaut corps, whether women and men demonstrated typical gender differences in personality, and whether three characteristic clusters found in other high performance populations replicated in this group. Between 1989 and 1995, 259 final stage astronauts completed the Personal Characteristic Inventory (PCI) which assesses personality characteristics related to the broad traits of Instrumentality and Expressivity. In addition, 147 of these individuals also completed an abbreviated version of the NEO Five Factor Inventory (NEO-FFI) which assesses the "Big Five" traits of Neuroticism, Extraversion, Openness, Agreeableness, And Conscientiousness. Three previously identified trait clusters (Right, Wrong, and No Stuff) were found to replicate in this population. No differences were found on the PCI or on the modified NEO-FFI between applicants who were chosen to become astronauts (n = 63) and those who were not (n = 196). Men scored higher than women on competitiveness, but lower on expressivity and achievement strivings. These analyses suggest that the "Right Stuff," "Wrong Stuff" and "No Stuff" clusters originally described in airline pilots and other high performance groups also exist within this population. Consistent with findings from other high performance populations, men and women tend to differ to a lesser extent than found in the general population, particularly on traits related to achievement motivation. Personality trait testing did not predict which applicants were most likely to be accepted into the astronaut corps.

More than just the mean: moving to a dynamic view of performance-based compensation.

PubMed

Barnes, Christopher M; Reb, Jochen; Ang, Dionysius

2012-05-01

Compensation decisions have important consequences for employees and organizations and affect factors such as retention, motivation, and recruitment. Past research has primarily focused on mean performance as a predictor of compensation, promoting the implicit assumption that alternative aspects of dynamic performance are not relevant. To address this gap in the literature, we examined the influence of dynamic performance characteristics on compensation decisions in the National Basketball Association (NBA). We predicted that, in addition to performance mean, performance trend and variability would also affect compensation decisions. Results revealed that performance mean and trend, but not variability, were significantly and positively related to changes in compensation levels of NBA players. Moreover, trend (but not mean or variability) predicted compensation when controlling for future performance, suggesting that organizations overweighted trend in their compensation decisions. Theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Adaptation of a Biomarker-Based Sepsis Mortality Risk Stratification Tool for Pediatric Acute Respiratory Distress Syndrome.

PubMed

Yehya, Nadir; Wong, Hector R

2018-01-01

The original Pediatric Sepsis Biomarker Risk Model and revised (Pediatric Sepsis Biomarker Risk Model-II) biomarker-based risk prediction models have demonstrated utility for estimating baseline 28-day mortality risk in pediatric sepsis. Given the paucity of prediction tools in pediatric acute respiratory distress syndrome, and given the overlapping pathophysiology between sepsis and acute respiratory distress syndrome, we tested the utility of Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II for mortality prediction in a cohort of pediatric acute respiratory distress syndrome, with an a priori plan to revise the model if these existing models performed poorly. Prospective observational cohort study. University affiliated PICU. Mechanically ventilated children with acute respiratory distress syndrome. Blood collection within 24 hours of acute respiratory distress syndrome onset and biomarker measurements. In 152 children with acute respiratory distress syndrome, Pediatric Sepsis Biomarker Risk Model performed poorly and Pediatric Sepsis Biomarker Risk Model-II performed modestly (areas under receiver operating characteristic curve of 0.61 and 0.76, respectively). Therefore, we randomly selected 80% of the cohort (n = 122) to rederive a risk prediction model for pediatric acute respiratory distress syndrome. We used classification and regression tree methodology, considering the Pediatric Sepsis Biomarker Risk Model biomarkers in addition to variables relevant to acute respiratory distress syndrome. The final model was comprised of three biomarkers and age, and more accurately estimated baseline mortality risk (area under receiver operating characteristic curve 0.85, p < 0.001 and p = 0.053 compared with Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II, respectively). The model was tested in the remaining 20% of subjects (n = 30) and demonstrated similar test characteristics. A validated, biomarker-based risk stratification tool designed for pediatric sepsis was adapted for use in pediatric acute respiratory distress syndrome. The newly derived Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model demonstrates good test characteristics internally and requires external validation in a larger cohort. Tools such as Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model have the potential to provide improved risk stratification and prognostic enrichment for future trials in pediatric acute respiratory distress syndrome.

A new neuro-fuzzy training algorithm for identifying dynamic characteristics of smart dampers

NASA Astrophysics Data System (ADS)

Dzung Nguyen, Sy; Choi, Seung-Bok

2012-08-01

This paper proposes a new algorithm, named establishing neuro-fuzzy system (ENFS), to identify dynamic characteristics of smart dampers such as magnetorheological (MR) and electrorheological (ER) dampers. In the ENFS, data clustering is performed based on the proposed algorithm named partitioning data space (PDS). Firstly, the PDS builds data clusters in joint input-output data space with appropriate constraints. The role of these constraints is to create reasonable data distribution in clusters. The ENFS then uses these clusters to perform the following tasks. Firstly, the fuzzy sets expressing characteristics of data clusters are established. The structure of the fuzzy sets is adjusted to be suitable for features of the data set. Secondly, an appropriate structure of neuro-fuzzy (NF) expressed by an optimal number of labeled data clusters and the fuzzy-set groups is determined. After the ENFS is introduced, its effectiveness is evaluated by a prediction-error-comparative work between the proposed method and some other methods in identifying numerical data sets such as ‘daily data of stock A’, or in identifying a function. The ENFS is then applied to identify damping force characteristics of the smart dampers. In order to evaluate the effectiveness of the ENFS in identifying the damping forces of the smart dampers, the prediction errors are presented by comparing with experimental results.

JT8D and JT9D jet engine performance improvement program. Task 1: Feasibility analysis

NASA Technical Reports Server (NTRS)

Gaffin, W. O.; Webb, D. E.

1979-01-01

JT8D and JT9D component performance improvement concepts which have a high probability of incorporation into production engines were identified and ranked. An evaluation method based on airline payback period was developed for the purpose of identifying the most promising concepts. The method used available test data and analytical models along with conceptual/preliminary designs to predict the performance improvements, weight, installation characteristics, cost for new production and retrofit, maintenance cost, and qualitative characteristics of candidate concepts. These results were used to arrive at the concept payback period, which is the time required for an airline to recover the investment cost of concept implementation.

Development of a computer technique for the prediction of transport aircraft flight profile sonic boom signatures. M.S. Thesis

NASA Technical Reports Server (NTRS)

Coen, Peter G.

1991-01-01

A new computer technique for the analysis of transport aircraft sonic boom signature characteristics was developed. This new technique, based on linear theory methods, combines the previously separate equivalent area and F function development with a signature propagation method using a single geometry description. The new technique was implemented in a stand-alone computer program and was incorporated into an aircraft performance analysis program. Through these implementations, both configuration designers and performance analysts are given new capabilities to rapidly analyze an aircraft's sonic boom characteristics throughout the flight envelope.

Computer modeling of heat pipe performance

NASA Technical Reports Server (NTRS)

Peterson, G. P.

1983-01-01

A parametric study of the defining equations which govern the steady state operational characteristics of the Grumman monogroove dual passage heat pipe is presented. These defining equations are combined to develop a mathematical model which describes and predicts the operational and performance capabilities of a specific heat pipe given the necessary physical characteristics and working fluid. Included is a brief review of the current literature, a discussion of the governing equations, and a description of both the mathematical and computer model. Final results of preliminary test runs of the model are presented and compared with experimental tests on actual prototypes.

Development of advanced fuel cell system

NASA Technical Reports Server (NTRS)

Grevstad, P. E.

1972-01-01

Weight, life and performance characteristics optimization of hydrogen-oxygen fuel cell power systems were considered. A promising gold alloy cathode catalyst was identified and tested in a cell for 5,000 hours. The compatibility characteristics of candidate polymer structural materials were measured after exposure to electrolyte and water vapor for 8,000 hours. Lightweight cell designs were prepared and fabrication techniques to produce them were developed. Testing demonstrated that predicted performance was achieved. Lightweight components for passive product water removal and evaporative cooling of cells were demonstrated. Systems studies identified fuel cell powerplant concepts for meeting the requirements of advanced spacecraft.

Prediction of Balance Compensation After Vestibular Schwannoma Surgery.

PubMed

Parietti-Winkler, Cécile; Lion, Alexis; Frère, Julien; Perrin, Philippe P; Beurton, Renaud; Gauchard, Gérome C

2016-06-01

Background Balance compensation after vestibular schwannoma (VS) surgery is under the influence of specific preoperative patient and tumor characteristics. Objective To prospectively identify potential prognostic factors for balance recovery, we compared the respective influence of these preoperative characteristics on balance compensation after VS surgery. Methods In 50 patients scheduled for VS surgical ablation, we measured postural control before surgery (BS), 8 (AS8) days after, and 90 (AS90) days after surgery. Based on factors found previously in the literature, we evaluated age, body mass index and preoperative physical activity (PA), tumor grade, vestibular status, and preference for visual cues to control balance as potential prognostic factors using stepwise multiple regression models. Results An asymmetric vestibular function was the sole significant explanatory factor for impaired balance performance BS, whereas the preoperative PA alone significantly contributed to higher performance at AS8. An evaluation of patients' balance recovery over time showed that PA and vestibular status were the 2 significant predictive factors for short-term postural compensation (BS to AS8), whereas none of these preoperative factors was significantly predictive for medium-term postoperative postural recovery (AS8 to AS90). Conclusions We identified specific preoperative patient and vestibular function characteristics that may predict postoperative balance recovery after VS surgery. Better preoperative characterization of these factors in each patient could inform more personalized presurgical and postsurgical management, leading to a better, more rapid balance recovery, earlier return to normal daily activities and work, improved quality of life, and reduced medical and societal costs. © The Author(s) 2015.

Logistic Regression Analyses for Predicting Clinically Important Differences in Motor Capacity, Motor Performance, and Functional Independence after Constraint-Induced Therapy in Children with Cerebral Palsy

ERIC Educational Resources Information Center

Wang, Tien-ni; Wu, Ching-yi; Chen, Chia-ling; Shieh, Jeng-yi; Lu, Lu; Lin, Keh-chung

2013-01-01

Given the growing evidence for the effects of constraint-induced therapy (CIT) in children with cerebral palsy (CP), there is a need for investigating the characteristics of potential participants who may benefit most from this intervention. This study aimed to establish predictive models for the effects of pediatric CIT on motor and functional…

Performance characteristics of prostate-specific antigen density and biopsy core details to predict oncological outcome in patients with intermediate to high-risk prostate cancer underwent robot-assisted radical prostatectomy.

PubMed

Yashi, Masahiro; Nukui, Akinori; Tokura, Yuumi; Takei, Kohei; Suzuki, Issei; Sakamoto, Kazumasa; Yuki, Hideo; Kambara, Tsunehito; Betsunoh, Hironori; Abe, Hideyuki; Fukabori, Yoshitatsu; Nakazato, Yoshimasa; Kaji, Yasushi; Kamai, Takao

2017-06-23

Many urologic surgeons refer to biopsy core details for decision making in cases of localized prostate cancer (PCa) to determine whether an extended resection and/or lymph node dissection should be performed. Furthermore, recent reports emphasize the predictive value of prostate-specific antigen density (PSAD) for further risk stratification, not only for low-risk PCa, but also for intermediate- and high-risk PCa. This study focused on these parameters and compared respective predictive impact on oncologic outcomes in Japanese PCa patients. Two-hundred and fifty patients with intermediate- and high-risk PCa according to the National Comprehensive Cancer Network (NCCN) classification, that underwent robot-assisted radical prostatectomy at a single institution, and with observation periods of longer than 6 months were enrolled. None of the patients received hormonal treatments including antiandrogens, luteinizing hormone-releasing hormone analogues, or 5-alpha reductase inhibitors preoperatively. PSAD and biopsy core details, including the percentage of positive cores and the maximum percentage of cancer extent in each positive core, were analyzed in association with unfavorable pathologic results of prostatectomy specimens, and further with biochemical recurrence. The cut-off values of potential predictive factors were set through receiver-operating characteristic curve analyses. In the entire cohort, a higher PSAD, the percentage of positive cores, and maximum percentage of cancer extent in each positive core were independently associated with advanced tumor stage ≥ pT3 and an increased index tumor volume > 0.718 ml. NCCN classification showed an association with a tumor stage ≥ pT3 and a Gleason score ≥8, and the attribution of biochemical recurrence was also sustained. In each NCCN risk group, these preoperative factors showed various associations with unfavorable pathological results. In the intermediate-risk group, the percentage of positive cores showed an independent predictive value for biochemical recurrence. In the high-risk group, PSAD showed an independent predictive value. PSAD and biopsy core details have different performance characteristics for the prediction of oncologic outcomes in each NCCN risk group. Despite the need for further confirmation of the results with a larger cohort and longer observation, these factors are important as preoperative predictors in addition to the NCCN classification for a urologic surgeon to choose a surgical strategy.

X-43A Flight-Test-Determined Aerodynamic Force and Moment Characteristics at Mach 7.0

NASA Technical Reports Server (NTRS)

Davis, Mark C.; White, J. Terry

2008-01-01

The second flight of the Hyper-X program afforded a unique opportunity to determine the aerodynamic force and moment characteristics of an airframe-integrated scramjet-powered aircraft in hypersonic flight. These data were gathered via a repeated series of pitch, yaw, and roll doublets, frequency sweeps, and pushover-pullup maneuvers performed throughout the X-43A cowl-closed descent. Maneuvers were conducted at Mach numbers of 6.80-0.95 and at altitudes from 92,000 ft mean sea level to sea level. The dynamic pressure varied from 1300 to 400 psf with the angle of attack ranging from 0 to 14 deg. The flight-extracted aerodynamics were compared with preflight predictions based on wind-tunnel test data. The X-43A flight-derived axial force was found to be 10-15%higher than prediction. Underpredictions of similar magnitude were observed for the normal force. For Mach numbers above 4.0, the flight-derived stability and control characteristics resulted in larger-than-predicted static margins, with the largest discrepancy approximately 5 in. forward along the x-axis center of gravity at Mach 6.0. This condition would result in less static margin in pitch. The predicted lateral-directional stability and control characteristics matched well with flight data when allowance was made for the high uncertainty in angle of sideslip.

Numerical and Qualitative Contrasts of Two Statistical Models ...

EPA Pesticide Factsheets

Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and products. This study provided an empirical and qualitative comparison of both models using 29 years of data for two discrete time series of chlorophyll-a (chl-a) in the Patuxent River estuary. Empirical descriptions of each model were based on predictive performance against the observed data, ability to reproduce flow-normalized trends with simulated data, and comparisons of performance with validation datasets. Between-model differences were apparent but minor and both models had comparable abilities to remove flow effects from simulated time series. Both models similarly predicted observations for missing data with different characteristics. Trends from each model revealed distinct mainstem influences of the Chesapeake Bay with both models predicting a roughly 65% increase in chl-a over time in the lower estuary, whereas flow-normalized predictions for the upper estuary showed a more dynamic pattern, with a nearly 100% increase in chl-a in the last 10 years. Qualitative comparisons highlighted important differences in the statistical structure, available products, and characteristics of the data and desired analysis. This manuscript describes a quantitative comparison of two recently-

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.

Predicting ICU mortality: a comparison of stationary and nonstationary temporal models.

PubMed Central

Kayaalp, M.; Cooper, G. F.; Clermont, G.

2000-01-01

OBJECTIVE: This study evaluates the effectiveness of the stationarity assumption in predicting the mortality of intensive care unit (ICU) patients at the ICU discharge. DESIGN: This is a comparative study. A stationary temporal Bayesian network learned from data was compared to a set of (33) nonstationary temporal Bayesian networks learned from data. A process observed as a sequence of events is stationary if its stochastic properties stay the same when the sequence is shifted in a positive or negative direction by a constant time parameter. The temporal Bayesian networks forecast mortalities of patients, where each patient has one record per day. The predictive performance of the stationary model is compared with nonstationary models using the area under the receiver operating characteristics (ROC) curves. RESULTS: The stationary model usually performed best. However, one nonstationary model using large data sets performed significantly better than the stationary model. CONCLUSION: Results suggest that using a combination of stationary and nonstationary models may predict better than using either alone. PMID:11079917

Predicting dementia using socio-demographic characteristics and the Free and Cued Selective Reminding Test in the general population.

PubMed

Mura, Thibault; Baramova, Marieta; Gabelle, Audrey; Artero, Sylvaine; Dartigues, Jean-François; Amieva, Hélène; Berr, Claudine

2017-03-23

Our study aimed to determine whether the consideration of socio-demographic features improves the prediction of Alzheimer's dementia (AD) at 5 years when using the Free and Cued Selective Reminding Test (FCSRT) in the general older population. Our analyses focused on 2558 subjects from the prospective Three-City Study, a cohort of community-dwelling individuals aged 65 years and over, with FCSRT scores. Four "residual scores" and "risk scores" were built that included the FCSRT scores and socio-demographic variables. The predictive performance of crude, residual and risk scores was analyzed by comparing the areas under the ROC curve (AUC). In total, 1750 subjects were seen 5 years after completing the FCSRT. AD was diagnosed in 116 of them. Compared with the crude free-recall score, the predictive performances of the residual score and of the risk score were not significantly improved (AUC: 0.83 vs 0.82 and 0.88 vs 0.89 respectively). Using socio-demographic features in addition to the FCSRT does not improve its predictive performance for dementia or AD.

Comparison of Two Predictive Models for Short-Term Mortality in Patients after Severe Traumatic Brain Injury.

PubMed

Kesmarky, Klara; Delhumeau, Cecile; Zenobi, Marie; Walder, Bernhard

2017-07-15

The Glasgow Coma Scale (GCS) and the Abbreviated Injury Score of the head region (HAIS) are validated prognostic factors in traumatic brain injury (TBI). The aim of this study was to compare the prognostic performance of an alternative predictive model including motor GCS, pupillary reactivity, age, HAIS, and presence of multi-trauma for short-term mortality with a reference predictive model including motor GCS, pupil reaction, and age (IMPACT core model). A secondary analysis of a prospective epidemiological cohort study in Switzerland including patients after severe TBI (HAIS >3) with the outcome death at 14 days was performed. Performance of prediction, accuracy of discrimination (area under the receiver operating characteristic curve [AUROC]), calibration, and validity of the two predictive models were investigated. The cohort included 808 patients (median age, 56; interquartile range, 33-71), median GCS at hospital admission 3 (3-14), abnormal pupil reaction 29%, with a death rate of 29.7% at 14 days. The alternative predictive model had a higher accuracy of discrimination to predict death at 14 days than the reference predictive model (AUROC 0.852, 95% confidence interval [CI] 0.824-0.880 vs. AUROC 0.826, 95% CI 0.795-0.857; p < 0.0001). The alternative predictive model had an equivalent calibration, compared with the reference predictive model Hosmer-Lemeshow p values (Chi2 8.52, Hosmer-Lemeshow p = 0.345 vs. Chi2 8.66, Hosmer-Lemeshow p = 0.372). The optimism-corrected value of AUROC for the alternative predictive model was 0.845. After severe TBI, a higher performance of prediction for short-term mortality was observed with the alternative predictive model, compared with the reference predictive model.

Space Shuttle Main Engine performance analysis

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1993-01-01

For a number of years, NASA has relied primarily upon periodically updated versions of Rocketdyne's power balance model (PBM) to provide space shuttle main engine (SSME) steady-state performance prediction. A recent computational study indicated that PBM predictions do not satisfy fundamental energy conservation principles. More recently, SSME test results provided by the Technology Test Bed (TTB) program have indicated significant discrepancies between PBM flow and temperature predictions and TTB observations. Results of these investigations have diminished confidence in the predictions provided by PBM, and motivated the development of new computational tools for supporting SSME performance analysis. A multivariate least squares regression algorithm was developed and implemented during this effort in order to efficiently characterize TTB data. This procedure, called the 'gains model,' was used to approximate the variation of SSME performance parameters such as flow rate, pressure, temperature, speed, and assorted hardware characteristics in terms of six assumed independent influences. These six influences were engine power level, mixture ratio, fuel inlet pressure and temperature, and oxidizer inlet pressure and temperature. A BFGS optimization algorithm provided the base procedure for determining regression coefficients for both linear and full quadratic approximations of parameter variation. Statistical information relative to data deviation from regression derived relations was also computed. A new strategy for integrating test data with theoretical performance prediction was also investigated. The current integration procedure employed by PBM treats test data as pristine and adjusts hardware characteristics in a heuristic manner to achieve engine balance. Within PBM, this integration procedure is called 'data reduction.' By contrast, the new data integration procedure, termed 'reconciliation,' uses mathematical optimization techniques, and requires both measurement and balance uncertainty estimates. The reconciler attempts to select operational parameters that minimize the difference between theoretical prediction and observation. Selected values are further constrained to fall within measurement uncertainty limits and to satisfy fundamental physical relations (mass conservation, energy conservation, pressure drop relations, etc.) within uncertainty estimates for all SSME subsystems. The parameter selection problem described above is a traditional nonlinear programming problem. The reconciler employs a mixed penalty method to determine optimum values of SSME operating parameters associated with this problem formulation.

Basic corrections to predictions of solar cell performance required by nonlinearities

NASA Technical Reports Server (NTRS)

Lindholm, F. A.; Fossum, J. G.; Burgess, E. L.

1976-01-01

The superposition principle is used to derive the approximation that the current-voltage characteristic of an illuminated solar cell is the dark current-voltage characteristic shifted by the short-circuit photocurrent. The derivation requires the linearity of the boundary value problems that underlie the electrical characteristics. The shifting approximation is invalid if considerable photocurrent and considerable dark current both occur within the junction space-charge region; it is invalid also if sizable series resistance is present or if high-injection concentrations of holes and electrons exist within the quasi-neutral regions.

STGSTK- PREDICTING MULTISTAGE AXIAL-FLOW COMPRESSOR PERFORMANCE BY A MEANLINE STAGE-STACKING METHOD

NASA Technical Reports Server (NTRS)

Steinke, R. J.

1994-01-01

The STGSTK computer program was developed for predicting the off-design performance of multistage axial-flow compressors. The axial-flow compressor is widely used in aircraft engines. In addition to its inherent advantage of high mass flow per frontal area, it can exhibit very good aerodynamic performance. However, good aerodynamic performance over an acceptable range of operating conditions is not easily attained. STGSTK provides an analytical tool for the development of new compressor designs. The simplicity of a one-dimensional compressible flow model enables the stage-stacking method used in STGSTK to have excellent convergence properties and short computer run times. Also, the simplicity of the model makes STGSTK a manageable code that eases the incorporation, or modification, of empirical correlations directly linked to test data. Thus, the user can adapt the code to meet varying design needs. STGSTK uses a meanline stage-stacking method to predict off-design performance. Stage and cumulative compressor performance is calculated from representative meanline velocity diagrams located at rotor inlet and outlet meanline radii. STGSTK includes options for the following: 1) non-dimensional stage characteristics may be input directly or calculated from stage design performance input, 2) stage characteristics may be modified for off-design speed and blade reset, and 3) rotor design deviation angle may be modified for off-design flow, speed, and blade setting angle. Many of the code's options use correlations that are normally obtained from experimental data. The STGSTK user may modify these correlations as needed. This program is written in FORTRAN IV for batch execution and has been implemented on an IBM 370 series computer with a central memory requirement of approximately 85K of 8 bit bytes. STGSTK was developed in 1982.

Application of linear regression analysis in accuracy assessment of rolling force calculations

NASA Astrophysics Data System (ADS)

Poliak, E. I.; Shim, M. K.; Kim, G. S.; Choo, W. Y.

1998-10-01

Efficient operation of the computational models employed in process control systems require periodical assessment of the accuracy of their predictions. Linear regression is proposed as a tool which allows separate systematic and random prediction errors from those related to measurements. A quantitative characteristic of the model predictive ability is introduced in addition to standard statistical tests for model adequacy. Rolling force calculations are considered as an example for the application. However, the outlined approach can be used to assess the performance of any computational model.

Diatomic gasdynamic lasers.

NASA Technical Reports Server (NTRS)

Mckenzie, R. L.

1972-01-01

Predictions from a numerical model of the vibrational relaxation of anharmonic diatomic oscillators in supersonic expansions are used to show the extent to which the small anharmonicity of gases like CO can cause significant overpopulations of upper vibrational states. When mixtures of CO and N2 are considered, radiative gain on many of the vibration-rotation transitions of CO is predicted. Experiments are described that qualitatively verify the predictions by demonstrating laser oscillation in CO-N2 expansions. The resulting CO-N2 gasdynamic laser displays performance characteristics that equal or exceed those of similar CO2 lasers.

Diatomic gasdynamic lasers

NASA Technical Reports Server (NTRS)

Mckenzie, R. L.

1971-01-01

Predictions from a numerical model of the vibrational relaxation of anharmonic diatomic oscillators in supersonic expansions are used to show the extent to which the small anharmonicity of gases like CO can cause significant overpopulations of upper vibrational states. When mixtures of CO and N2 are considered, radiative gain on many of the vibration-rotation transitions of CO is predicted. Experiments are described that qualitatively verify the predictions by demonstrating laser oscillation in CO-N2 expansions. The resulting CO-N2 gasdynamic laser displays performance characteristics that equal or exceed those of similar CO2 lasers.

Noise characteristics of upper surface blown configurations: Analytical Studies

NASA Technical Reports Server (NTRS)

Reddy, N. N.; Tibbetts, J. G.; Pennock, A. P.; Tam, C. K. W.

1978-01-01

Noise and flow results of upper surface blown configurations were analyzed. The dominant noise source mechanisms were identified from experimental data. From far-field noise data for various geometric and operational parameters, an empirical noise prediction program was developed and evaluated by comparing predicted results with experimental data from other tests. USB aircraft compatibility studies were conducted using the described noise prediction and a cruise performance data base. A final design aircraft was selected and theory was developed for the noise from the trailing edge wake assuming it as a highly sheared layer.

Age differences in recall and predicting recall of action events and words.

PubMed

McDonald-Miszczak, L; Hubley, A M; Hultsch, D F

1996-03-01

Age differences in recall and prediction of recall were examined with different memory tasks. We asked 36 younger (19-28 yrs) and 36 older (60-81 yrs) women to provide both global and item-by-item predictions of their recall, and then to recall either (a) Subject Performance Tasks (SPTs), (b) verb-noun word-pairs memorized in list-like fashion (Word-Pairs), or (c) nonsense verb-noun word-pairs (Nonsense-Pairs) over three experimental trials. Based on previous research, we hypothesized that these tasks would vary in relative difficulty and flexibility of encoding. The results indicated that (a) age differences in global predictions (task specific self-efficacy) and recall performance across trials were minimized with SPT as compared with verbal materials, (b) global predictions were higher and more accurate for SPT as compared to verbal materials, and (c) item-by-item predictions were most accurate for materials encoded with the most flexibility (Nonsense Pairs). The results suggest that SPTs may provide some level of environmental support to reduce age differences in performance and task-specific self-efficacy, but that memory monitoring may depend on specific characteristics of the stimuli (i.e., flexibility of encoding) rather than their verbal or nonverbal nature.

Evaluation of an urban land surface scheme over a tropical suburban neighborhood

NASA Astrophysics Data System (ADS)

Harshan, Suraj; Roth, Matthias; Velasco, Erik; Demuzere, Matthias

2017-07-01

The present study evaluates the performance of the SURFEX (TEB/ISBA) urban land surface parametrization scheme in offline mode over a suburban area of Singapore. Model performance (diurnal and seasonal characteristics) is investigated using measurements of energy balance fluxes, surface temperatures of individual urban facets, and canyon air temperature collected during an 11-month period. Model performance is best for predicting net radiation and sensible heat fluxes (both are slightly overpredicted during daytime), but weaker for latent heat (underpredicted during daytime) and storage heat fluxes (significantly underpredicted daytime peaks and nighttime storage). Daytime surface temperatures are generally overpredicted, particularly those containing horizontal surfaces such as roofs and roads. This result, together with those for the storage heat flux, point to the need for a better characterization of the thermal and radiative characteristics of individual urban surface facets in the model. Significant variation exists in model behavior between dry and wet seasons, the latter generally being better predicted. The simple vegetation parametrization used is inadequate to represent seasonal moisture dynamics, sometimes producing unrealistically dry conditions.

Can We Predict Technical Aptitude?: A Systematic Review.

PubMed

Louridas, Marisa; Szasz, Peter; de Montbrun, Sandra; Harris, Kenneth A; Grantcharov, Teodor P

2016-04-01

To identify background characteristics and cognitive tests that may predict surgical trainees' future technical performance, and therefore be used to supplement existing surgical residency selection criteria. Assessment of technical skills is not commonly incorporated as part of the selection process for surgical trainees in North America. Emerging evidence, however, suggests that not all trainees are capable of reaching technical competence. Therefore, incorporating technical aptitude into selection processes may prove useful. A systematic search was carried out of the MEDLINE, PsycINFO, and Embase online databases to identify all studies that assessed associations between surrogate markers of innate technical abilities in surgical trainees, and whether these abilities correlate with technical performance. The quality of each study was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation system. A total of 8035 records were identified. After screening by title, abstract, and full text, 52 studies were included. Very few surrogate markers were found to predict technical performance. Significant associations with technical performance were seen for 1 of 23 participant-reported surrogate markers, 2 of 25 visual spatial tests, and 2 of 19 dexterity tests. The assessment of trainee Basic Performance Resources predicted technical performance in 62% and 75% of participants. To date, no single test has been shown to reliably predict the technical performance of surgical trainees. Strategies that rely on assessing multiple innate abilities, their interaction, and their relationship with technical skill may ultimately be more likely to serve as reliable predictors of future surgical performance.

Impact of metal ionic characteristics on adsorption potential of Ficus carica leaves using QSPR modeling.

PubMed

Batool, Fozia; Iqbal, Shahid; Akbar, Jamshed

2018-04-03

The present study describes Quantitative Structure Property Relationship (QSPR) modeling to relate metal ions characteristics with adsorption potential of Ficus carica leaves for 13 selected metal ions (Ca +2 , Cr +3 , Co +2 , Cu +2 , Cd +2 , K +1 , Mg +2 , Mn +2 , Na +1 , Ni +2 , Pb +2 , Zn +2 , and Fe +2 ) to generate QSPR model. A set of 21 characteristic descriptors were selected and relationship of these metal characteristics with adsorptive behavior of metal ions was investigated. Stepwise Multiple Linear Regression (SMLR) analysis and Artificial Neural Network (ANN) were applied for descriptors selection and model generation. Langmuir and Freundlich isotherms were also applied on adsorption data to generate proper correlation for experimental findings. Model generated indicated covalent index as the most significant descriptor, which is responsible for more than 90% predictive adsorption (α = 0.05). Internal validation of model was performed by measuring [Formula: see text] (0.98). The results indicate that present model is a useful tool for prediction of adsorptive behavior of different metal ions based on their ionic characteristics.

Gait Rather Than Cognition Predicts Decline in Specific Cognitive Domains in Early Parkinson's Disease.

PubMed

Morris, Rosie; Lord, Sue; Lawson, Rachael A; Coleman, Shirley; Galna, Brook; Duncan, Gordon W; Khoo, Tien K; Yarnall, Alison J; Burn, David J; Rochester, Lynn

2017-11-09

Dementia is significant in Parkinson's disease (PD) with personal and socioeconomic impact. Early identification of risk is of upmost importance to optimize management. Gait precedes and predicts cognitive decline and dementia in older adults. We aimed to evaluate gait characteristics as predictors of cognitive decline in newly diagnosed PD. One hundred and nineteen participants recruited at diagnosis were assessed at baseline, 18 and 36 months. Baseline gait was characterized by variables that mapped to five domains: pace, rhythm, variability, asymmetry, and postural control. Cognitive assessment included attention, fluctuating attention, executive function, visual memory, and visuospatial function. Mixed-effects models tested independent gait predictors of cognitive decline. Gait characteristics of pace, variability, and postural control predicted decline in fluctuating attention and visual memory, whereas baseline neuropsychological assessment performance did not predict decline. This provides novel evidence for gait as a clinical biomarker for PD cognitive decline in early disease. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.

Housing price prediction: parametric versus semi-parametric spatial hedonic models

NASA Astrophysics Data System (ADS)

Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema

2018-01-01

House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

Energy prediction using spatiotemporal pattern networks

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

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated bymore » the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.« less

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

PubMed

Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

2015-01-01

Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

Effects of Data Anonymization by Cell Suppression on Descriptive Statistics and Predictive Modeling Performance

PubMed Central

Ohno-Machado, Lucila; Vinterbo, Staal; Dreiseitl, Stephan

2002-01-01

Protecting individual data in disclosed databases is essential. Data anonymization strategies can produce table ambiguation by suppression of selected cells. Using table ambiguation, different degrees of anonymization can be achieved, depending on the number of individuals that a particular case must become indistinguishable from. This number defines the level of anonymization. Anonymization by cell suppression does not necessarily prevent inferences from being made from the disclosed data. Preventing inferences may be important to preserve confidentiality. We show that anonymized data sets can preserve descriptive characteristics of the data, but might also be used for making inferences on particular individuals, which is a feature that may not be desirable. The degradation of predictive performance is directly proportional to the degree of anonymity. As an example, we report the effect of anonymization on the predictive performance of a model constructed to estimate the probability of disease given clinical findings.

Effects of data anonymization by cell suppression on descriptive statistics and predictive modeling performance.

PubMed Central

Ohno-Machado, L.; Vinterbo, S. A.; Dreiseitl, S.

2001-01-01

Protecting individual data in disclosed databases is essential. Data anonymization strategies can produce table ambiguation by suppression of selected cells. Using table ambiguation, different degrees of anonymization can be achieved, depending on the number of individuals that a particular case must become indistinguishable from. This number defines the level of anonymization. Anonymization by cell suppression does not necessarily prevent inferences from being made from the disclosed data. Preventing inferences may be important to preserve confidentiality. We show that anonymized data sets can preserve descriptive characteristics of the data, but might also be used for making inferences on particular individuals, which is a feature that may not be desirable. The degradation of predictive performance is directly proportional to the degree of anonymity. As an example, we report the effect of anonymization on the predictive performance of a model constructed to estimate the probability of disease given clinical findings. PMID:11825239

Novel biomarkers for predicting intrauterine growth restriction: a systematic review and meta-analysis.

PubMed

Conde-Agudelo, A; Papageorghiou, A T; Kennedy, S H; Villar, J

2013-05-01

Several biomarkers for predicting intrauterine growth restriction (IUGR) have been proposed in recent years. However, the predictive performance of these biomarkers has not been systematically evaluated. To determine the predictive accuracy of novel biomarkers for IUGR in women with singleton gestations. Electronic databases, reference list checking and conference proceedings. Observational studies that evaluated the accuracy of novel biomarkers proposed for predicting IUGR. Data were extracted on characteristics, quality and predictive accuracy from each study to construct 2×2 tables. Summary receiver operating characteristic curves, sensitivities, specificities and likelihood ratios (LRs) were generated. A total of 53 studies, including 39,974 women and evaluating 37 novel biomarkers, fulfilled the inclusion criteria. Overall, the predictive accuracy of angiogenic factors for IUGR was minimal (median pooled positive and negative LRs of 1.7, range 1.0-19.8; and 0.8, range 0.0-1.0, respectively). Two small case-control studies reported high predictive values for placental growth factor and angiopoietin-2 only when IUGR was defined as birthweight centile with clinical or pathological evidence of fetal growth restriction. Biomarkers related to endothelial function/oxidative stress, placental protein/hormone, and others such as serum levels of vitamin D, urinary albumin:creatinine ratio, thyroid function tests and metabolomic profile had low predictive accuracy. None of the novel biomarkers evaluated in this review are sufficiently accurate to recommend their use as predictors of IUGR in routine clinical practice. However, the use of biomarkers in combination with biophysical parameters and maternal characteristics could be more useful and merits further research. © 2013 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2013 RCOG.

Effects of training and anthropometric factors on marathon and 100 km ultramarathon race performance

PubMed Central

Tanda, Giovanni; Knechtle, Beat

2015-01-01

Background Marathon (42 km) and 100 km ultramarathon races are increasing in popularity. The aim of the present study was to investigate the potential associations of anthropometric and training variables with performance in these long-distance running competitions. Methods Training and anthropometric data from a large cohort of marathoners and 100 km ultramarathoners provided the basis of this work. Correlations between training and anthropometric indices of subjects and race performance were assessed using bivariate and multiple regression analyses. Results A combination of volume and intensity in training was found to be suitable for prediction of marathon and 100 km ultramarathon race pace. The relative role played by these two variables was different, in that training volume was more important than training pace for the prediction of 100 km ultramarathon performance, while the opposite was found for marathon performance. Anthropometric characteristics in terms of body fat percentage negatively affected 42 km and 100 km race performance. However, when this factor was relatively low (ie, less than 15% body fat), the performance of 42 km and 100 km races could be predicted solely on the basis of training indices. Conclusion Mean weekly training distance run and mean training pace were key predictor variables for both marathon and 100 km ultramarathon race performance. Predictive correlations for race performance are provided for runners with a relatively low body fat percentage. PMID:25995653

An investigation of the performance of an electronic in-line pump system for diesel engines

NASA Astrophysics Data System (ADS)

Fan, Li-Yun; Zhu, Yuan-Xian; Long, Wu-Qiang; Ma, Xiu-Zhen; Xue, Ying-Ying

2008-12-01

WIT Electronic Fuel System Co., Ltd. has developed a new fuel injector, the Electronic In-line Pump (EIP) system, designed to meet China’s diesel engine emission and fuel economy regulations. It can be used on marine diesel engines and commercial vehicle engines through different EIP systems. A numerical model of the EIP system was built in the AMESim environment for the purpose of creating a design tool for engine application and system optimization. The model was used to predict key injection characteristics under different operating conditions, such as injection pressure, injection rate, and injection duration. To validate these predictions, experimental tests were conducted under the conditions that were modeled. The results were quite encouraging and in agreement with model predictions. Additional experiments were conducted to study the injection characteristics of the EIP system. These results show that injection pressure and injection quantity are insensitive to injection timing variations, this is due to the design of the constant velocity cam profile. Finally, injection quantity and pressure vs. pulse width at different cam speeds are presented, an important injection characteristic for EIP system calibration.

A computational approach to compare regression modelling strategies in prediction research.

PubMed

Pajouheshnia, Romin; Pestman, Wiebe R; Teerenstra, Steven; Groenwold, Rolf H H

2016-08-25

It is often unclear which approach to fit, assess and adjust a model will yield the most accurate prediction model. We present an extension of an approach for comparing modelling strategies in linear regression to the setting of logistic regression and demonstrate its application in clinical prediction research. A framework for comparing logistic regression modelling strategies by their likelihoods was formulated using a wrapper approach. Five different strategies for modelling, including simple shrinkage methods, were compared in four empirical data sets to illustrate the concept of a priori strategy comparison. Simulations were performed in both randomly generated data and empirical data to investigate the influence of data characteristics on strategy performance. We applied the comparison framework in a case study setting. Optimal strategies were selected based on the results of a priori comparisons in a clinical data set and the performance of models built according to each strategy was assessed using the Brier score and calibration plots. The performance of modelling strategies was highly dependent on the characteristics of the development data in both linear and logistic regression settings. A priori comparisons in four empirical data sets found that no strategy consistently outperformed the others. The percentage of times that a model adjustment strategy outperformed a logistic model ranged from 3.9 to 94.9 %, depending on the strategy and data set. However, in our case study setting the a priori selection of optimal methods did not result in detectable improvement in model performance when assessed in an external data set. The performance of prediction modelling strategies is a data-dependent process and can be highly variable between data sets within the same clinical domain. A priori strategy comparison can be used to determine an optimal logistic regression modelling strategy for a given data set before selecting a final modelling approach.

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

PubMed

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

2018-03-01

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

Quantity and location of aortic valve complex calcification predicts severity and location of paravalvular regurgitation and frequency of post-dilation after balloon-expandable transcatheter aortic valve replacement.

PubMed

Khalique, Omar K; Hahn, Rebecca T; Gada, Hemal; Nazif, Tamim M; Vahl, Torsten P; George, Isaac; Kalesan, Bindu; Forster, Molly; Williams, Mathew B; Leon, Martin B; Einstein, Andrew J; Pulerwitz, Todd C; Pearson, Gregory D N; Kodali, Susheel K

2014-08-01

This study sought to determine the impact of quantity and location of aortic valve calcification (AVC) on paravalvular regurgitation (PVR) and rates of post-dilation (PD) immediately after transcatheter aortic valve replacement (TAVR). The impact of AVC in different locations within the aortic valve complex is incompletely understood. This study analyzed 150 patients with severe, symptomatic aortic stenosis who underwent TAVR. Total AVC volume scores were calculated from contrast-enhanced multidetector row computed tomography imaging. AVC was divided by leaflet sector and region (Leaflet, Annulus, left ventricular outflow tract [LVOT]), and a combination of LVOT and Annulus (AnnulusLVOT). Asymmetry was assessed. Receiver-operating characteristic analysis was performed with greater than or equal to mild PVR and PD as classification variables. Logistic regression was performed. Quantity of and asymmetry of AVC for all regions of the aortic valve complex predicted greater than or equal to mild PVR by receiver-operating characteristic analysis (area under the curve = 0.635 to 0.689), except Leaflet asymmetry. Receiver-operating characteristic analysis for PD was significant for quantity and asymmetry of AVC in all regions, with higher area under the curve values than for PVR (area under the curve = 0.648 to 0.741). On multivariable analysis, Leaflet and AnnulusLVOT calcification were independent predictors of both PVR and PD regardless of multidetector row computed tomography area cover index. Quantity and asymmetry of AVC in all regions of the aortic valve complex predict greater than or equal to mild PVR and performance of PD, with the exception of Leaflet asymmetry. Quantity of AnnulusLVOT and Leaflet calcification independently predict PVR and PD when taking into account multidetector row computed tomography area cover index. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Psychosocial work characteristics and long-term sickness absence due to mental disorders.

PubMed

van Hoffen, Marieke F A; Roelen, Corné A M; van Rhenen, Willem; Schaufeli, Wilmar B; Heymans, Martijn W; Twisk, Jos W R

2018-02-09

Psychosocial work characteristics are associated with all-cause long-term sickness absence (LTSA). This study investigated whether psychosocial work characteristics such as higher workload, faster pace of work, less variety in work, lack of performance feedback, and lack of supervisor support are prospectively associated with higher LTSA due to mental disorders. Cohort study including 4877 workers employed in the distribution and transport sector in The Netherlands. Psychosocial work characteristics were included in a logistic regression model estimating the odds ratios (OR) and 95% confidence intervals (CI) of mental LTSA during 2-year follow-up. The ability of the regression model to discriminate between workers with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC). Tow thousand seven hundred and eighty-two (57%) workers were included in the analysis; 73 (3%) had mental LTSA. Feedback about one's performance (OR = 0.82; 95% CI 0.70-0.96) was associated with mental LTSA. A prediction model including psychosocial work characteristics poorly discriminated (AUC = 0.65; 95% CI 0.56-0.74) between workers with and without mental LTSA. Feedback about one's performance is associated with lower rates of mental LTSA, but it is not useful to measure psychosocial work characteristics to identify workers at risk of mental LTSA.

Using regression analysis to predict emergency patient volume at the Indianapolis 500 mile race.

PubMed

Bowdish, G E; Cordell, W H; Bock, H C; Vukov, L F

1992-10-01

Emergency physicians often plan and provide on-site medical care for mass gatherings. Most of the mass gathering literature is descriptive. Only a few studies have looked at factors such as crowd size, event characteristics, or weather in predicting numbers and types of patients at mass gatherings. We used regression analysis to relate patient volume on Race Day at the Indianapolis Motor Speedway to weather conditions and race characteristics. Race Day weather data for the years 1983 to 1989 were obtained from the National Oceanic and Atmospheric Administration. Data regarding patients treated on 1983 to 1989 Race Days were obtained from the facility hospital (Hannah Emergency Medical Center) data base. Regression analysis was performed using weather factors and race characteristics as independent variables and number of patients seen as the dependent variable. Data from 1990 were used to test the validity of the model. There was a significant relationship between dew point (which is calculated from temperature and humidity) and patient load (P less than .01). Dew point, however, failed to predict patient load during the 1990 race. No relationships could be established between humidity, sunshine, wind, or race characteristics and number of patients. Although higher dew point was associated with higher patient load during the 1983 to 1989 races, dew point was a poor predictor of patient load during the 1990 race. Regression analysis may be useful in identifying relationships between event characteristics and patient load but is probably inadequate to explain the complexities of crowd behavior and too simplified to use as a prediction tool.

Experimental Aerodynamic Characteristics of the Pegasus Air-Launched Booster and Comparisons with Predicted and Flight Results

NASA Technical Reports Server (NTRS)

Rhode, M. N.; Engelund, Walter C.; Mendenhall, Michael R.

1995-01-01

Experimental longitudinal and lateral-directional aerodynamic characteristics were obtained for the Pegasus and Pegasus XL configurations over a Mach number range from 1.6 to 6 and angles of attack from -4 to +24 degrees. Angle of sideslip was varied from -6 to +6 degrees, and control surfaces were deflected to obtain elevon, aileron, and rudder effectiveness. Experimental data for the Pegasus configuration are compared with engineering code predictions performed by Nielsen Engineering & Research, Inc. (NEAR) in the aerodynamic design of the Pegasus vehicle, and with results from the Aerodynamic Preliminary Analysis System (APAS) code. Comparisons of experimental results are also made with longitudinal flight data from Flight #2 of the Pegasus vehicle. Results show that the longitudinal aerodynamic characteristics of the Pegasus and Pegasus XL configurations are similar, having the same lift-curve slope and drag levels across the Mach number range. Both configurations are longitudinally stable, with stability decreasing towards neutral levels as Mach number increases. Directional stability is negative at moderate to high angles of attack due to separated flow over the vertical tail. Dihedral effect is positive for both configurations, but is reduced 30-50 percent for the Pegasus XL configuration because of the horizontal tail anhedral. Predicted longitudinal characteristics and both longitudinal and lateral-directional control effectiveness are generally in good agreement with experiment. Due to the complex leeside flowfield, lateral-directional characteristics are not as well predicted by the engineering codes. Experiment and flight data are in good agreement across the Mach number range.

Aeroacoustics of Flight Vehicles: Theory and Practice. Volume 2: Noise Control

NASA Technical Reports Server (NTRS)

Hubbard, Harvey H. (Editor)

1991-01-01

Flight vehicles and the underlying concepts of noise generation, noise propagation, noise prediction, and noise control are studied. This volume includes those chapters that relate to flight vehicle noise control and operations: human response to aircraft noise; atmospheric propagation; theoretical models for duct acoustic propagation and radiation; design and performance of duct acoustic treatment; jet noise suppression; interior noise; flyover noise measurement and prediction; and quiet aircraft design and operational characteristics.

Validating models of target acquisition performance in the dismounted soldier context

NASA Astrophysics Data System (ADS)

Glaholt, Mackenzie G.; Wong, Rachel K.; Hollands, Justin G.

2018-04-01

The problem of predicting real-world operator performance with digital imaging devices is of great interest within the military and commercial domains. There are several approaches to this problem, including: field trials with imaging devices, laboratory experiments using imagery captured from these devices, and models that predict human performance based on imaging device parameters. The modeling approach is desirable, as both field trials and laboratory experiments are costly and time-consuming. However, the data from these experiments is required for model validation. Here we considered this problem in the context of dismounted soldiering, for which detection and identification of human targets are essential tasks. Human performance data were obtained for two-alternative detection and identification decisions in a laboratory experiment in which photographs of human targets were presented on a computer monitor and the images were digitally magnified to simulate range-to-target. We then compared the predictions of different performance models within the NV-IPM software package: Targeting Task Performance (TTP) metric model and the Johnson model. We also introduced a modification to the TTP metric computation that incorporates an additional correction for target angular size. We examined model predictions using NV-IPM default values for a critical model constant, V50, and we also considered predictions when this value was optimized to fit the behavioral data. When using default values, certain model versions produced a reasonably close fit to the human performance data in the detection task, while for the identification task all models substantially overestimated performance. When using fitted V50 values the models produced improved predictions, though the slopes of the performance functions were still shallow compared to the behavioral data. These findings are discussed in relation to the models' designs and parameters, and the characteristics of the behavioral paradigm.

Modeling and Performance Simulation of the Mass Storage Network Environment

NASA Technical Reports Server (NTRS)

Kim, Chan M.; Sang, Janche

2000-01-01

This paper describes the application of modeling and simulation in evaluating and predicting the performance of the mass storage network environment. Network traffic is generated to mimic the realistic pattern of file transfer, electronic mail, and web browsing. The behavior and performance of the mass storage network and a typical client-server Local Area Network (LAN) are investigated by modeling and simulation. Performance characteristics in throughput and delay demonstrate the important role of modeling and simulation in network engineering and capacity planning.

Use of the Interview in Resident Candidate Selection: A Review of the Literature.

PubMed

Stephenson-Famy, Alyssa; Houmard, Brenda S; Oberoi, Sidharth; Manyak, Anton; Chiang, Seine; Kim, Sara

2015-12-01

Although the resident candidate interview is costly and time-consuming for both applicants and programs, it is considered critically important for resident selection. Noncognitive attributes, including communication skills and professionalism, can be assessed by the personal interview. We conducted a review of the literature on the residency interview to identify the interview characteristics used for resident selection and to ascertain to what extent the interview yields information that predicts future performance. We searched PubMed and Scopus using the following search terms: residency, internship, interview, selection, and performance. We extracted information on characteristics of the interview process, including type of interview format, measures taken to minimize bias by interviewers, and testing of other clinical/surgical skills. We identified 104 studies that pertained to the resident selection interview, with highly varied interview formats and assessment tools. A positive correlation was demonstrated between a medical school academic record and the interview, especially for unblinded interview formats. A total of 34 studies attempted to correlate interview score with performance in residency, with mixed results. We also identified a number of studies that included personality testing, clinical skills testing, or surgical skills testing. Our review identified a wide variety of approaches to the selection interview and a range of factors that have been studied to assess its effectiveness. More research needs to be done not only to address and ascertain appropriate interview formats that predict positive performance in residency, but also to determine interview factors that can predict both residents' "success" and program attrition.

Experimental study on rotating instability mode characteristics of axial compressor tip flow

NASA Astrophysics Data System (ADS)

Tian, Jie; Yao, Dan; Wu, Yadong; Ouyang, Hua

2018-04-01

This paper investigates the rotating instabilities that occurred on the single-stage axial compressor designed for aerodynamic performance validation, which was tested with two sets of circumferential measuring points in combination. Circumferential mode characteristics of compressors are usually too high to be captured experimentally, and aliasing of the circumferential mode order occurs when not enough sensors are used. A calibration and prediction method to capture the higher circumferential mode of unsteady flow in a compressor was proposed. Unsteady pressure fluctuations near the tip region in an axial compressor were studied, and high circumferential mode characteristics were captured on both the blade passing frequency (BPF) and the rotational instability frequency (RIF) under different flow rate conditions based on this novel method. The characteristic RI spectrum with a broadband hump was present in a large range of flow conditions. Both the frequency range and the dominant circumferential mode order decreased as the flow rate decreased. Based on the calibrated mode characteristics, a rotating aerodynamic source model is used to explain the side-by-side peak of RIF spectrum and rotating characteristics of RI. The calibration and prediction method of the high circumferential mode is beneficial for the research of unsteady flow in an axial compressor.

Prediction of circulation control performance characteristics for Super STOL and STOL applications

NASA Astrophysics Data System (ADS)

Naqvi, Messam Abbas

The rapid air travel growth during the last three decades, has resulted in runway congestion at major airports. The current airports infrastructure will not be able to support the rapid growth trends expected in the next decade. Changes or upgrades in infrastructure alone would not be able to satisfy the growth requirements, and new airplane concepts such as the NASA proposed Super Short Takeoff and Landing and Extremely Short Takeoff & Landing (ESTOL) are being vigorously pursued. Aircraft noise pollution during Takeoff & Landing is another serious concern and efforts are aimed to reduce the airframe noise produced by Conventional High Lift Devices during Takeoff & Landing. Circulation control technology has the prospect of being a good alternative to resolve both the aforesaid issues. Circulation control airfoils are not only capable of producing very high values of lift (Cl values in excess of 8.0) at zero degree angle of attack, but also eliminate the noise generated by the conventional high lift devices and their associated weight penalty as well as their complex operation and storage. This will ensure not only satisfying the small takeoff and landing distances, but minimal acoustic signature in accordance with FAA requirements. The Circulation Control relies on the tendency of an emanating wall jet to independently control the circulation and lift on an airfoil. Unlike, conventional airfoil where rear stagnation point is located at the sharp trailing edge, circulation control airfoils possess a round trailing edge, therefore the rear stagnation point is free to move. The location of rear stagnation point is controlled by the blown jet momentum. This provides a secondary control in the form of jet momentum with which the lift generated can be controlled rather the only available control of incidence (angle of attack) in case of conventional airfoils. The use of Circulation control despite its promising potential has been limited only to research applications due to the lack of a simple prediction capability. This research effort was focused on the creation of a rapid prediction capability of Circulation Control Aerodynamic Characteristics which could help designers with rapid performance estimates for design space exploration. A morphological matrix was created with the available set of options which could be chosen to create this prediction capability starting with purely analytical physics based modeling to high fidelity CFD codes. Based on the available constraints, and desired accuracy meta-models have been created around the two dimensional circulation control performance results computed using Navier Stokes Equations (Computational Fluid Dynamics). DSS2, a two dimensional RANS code written by Professor Lakshmi Sankar was utilized for circulation control airfoil characteristics. The CFD code was first applied to the NCCR 1510-7607N airfoil to validate the model with available experimental results. It was then applied to compute the results of a fractional factorial design of experiments array. Metamodels were formulated using the neural networks to the results obtained from the Design of Experiments. Additional validation runs were performed to validate the model predictions. Metamodels are not only capable of rapid performance prediction, but also help generate the relation trends of response matrices with control variables and capture the complex interactions between control variables. Quantitative as well as qualitative assessments of results were performed by computation of aerodynamic forces & moments and flow field visualizations. Wing characteristics in three dimensions were obtained by integration over the whole wing using Prandtl's Wing Theory. The baseline Super STOL configuration [3] was then analyzed with the application of circulation control technology. The desired values of lift and drag to achieve the target values of Takeoff & Landing performance were compared with the optimal configurations obtained by the model. The same optimal configurations were then subjected to Super STOL cruise conditions to perform a trade off analysis between Takeoff and Cruise Performance. Supercritical airfoils modified for circulation control were also thoroughly analyzed for Takeoff and Cruise performance and may constitute a viable option for Super STOL & STOL Designs. The prediction capability produced by this research effort can be integrated with the current conceptual aircraft modeling & simulation framework. The prediction tool is applicable within the selected ranges of each variable, but methodology and formulation scheme adopted can be applied to any other design space exploration.

Performance of non-invasive models of fibrosis in predicting mild to moderate fibrosis in patients with non-alcoholic fatty liver disease.

PubMed

Siddiqui, Mohammad S; Patidar, Kavish R; Boyett, Sherry; Luketic, Velimir A; Puri, Puneet; Sanyal, Arun J

2016-04-01

In non-alcoholic fatty liver disease, presence of fibrosis is predictive of long-term liver-related complications. Currently, there are no reliable and non-invasive means of quantifying fibrosis in those with non-alcoholic fatty liver disease. Therefore, we aimed to evaluate the performance of a panel of non-invasive models in predicting fibrosis in non-alcoholic fatty liver disease. The accuracy of FibroMeter non-alcoholic fatty liver disease, fibrosis 4 and four other non-invasive models in predicting fibrosis in those with biopsy proven non-alcoholic fatty liver disease was compared. These models were constructed post hoc in patients who had necessary clinical information collected within 2 months of a liver biopsy. The areas under receiver operating characteristics curves were compared for each model using Delong analysis. Optimum cut-off for each model and fibrosis stage were calculated using the Youden index. The area under receiver operating characteristics curves for F ≥ 1 fibrosis for fibrosis 4 and FibroMeter non-alcoholic fatty liver disease was 0.821 and 0.801 respectively. For F ≥ 3, the area under receiver operating characteristics curves was 0.866 for fibrosis 4 and 0.862 for FibroMeter non-alcoholic fatty liver disease. Delong analysis showed the area under receiver operating characteristics curves was statistically different for fibrosis 4 and FibroMeter non-alcoholic fatty liver disease compared with BARD, BAAT and aspartate aminotransferase:alanine aminotransferase ratio for F ≥ 1 and F ≥ 3. Area under receiver operating characteristics curves were significantly different for fibrosis 4 and FibroMeter non-alcoholic fatty liver disease for F ≥ 3 compared with non-alcoholic fatty liver disease fibrosis score. At a fixed sensitivity of 90%, FibroMeter non-alcoholic fatty liver disease had the highest specificity for F ≥ 1 (52.4%) and F ≥ 3 (63.8%). In contrast, at a fixed specificity of 90%, fibrosis 4 outperformed other models with a sensitivity of 60.2% for F ≥ 1 and 70.6% for F ≥ 3 fibrosis. These non-invasive models of fibrosis can predict varying degrees of fibrosis from routinely collected clinical information in non-alcoholic fatty liver disease. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Conjunction of wavelet transform and SOM-mutual information data pre-processing approach for AI-based Multi-Station nitrate modeling of watersheds

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Andalib, Gholamreza; Dąbrowska, Dominika

2017-05-01

Accurate nitrate load predictions can elevate decision management of water quality of watersheds which affects to environment and drinking water. In this paper, two scenarios were considered for Multi-Station (MS) nitrate load modeling of the Little River watershed. In the first scenario, Markovian characteristics of streamflow-nitrate time series were proposed for the MS modeling. For this purpose, feature extraction criterion of Mutual Information (MI) was employed for input selection of artificial intelligence models (Feed Forward Neural Network, FFNN and least square support vector machine). In the second scenario for considering seasonality-based characteristics of the time series, wavelet transform was used to extract multi-scale features of streamflow-nitrate time series of the watershed's sub-basins to model MS nitrate loads. Self-Organizing Map (SOM) clustering technique which finds homogeneous sub-series clusters was also linked to MI for proper cluster agent choice to be imposed into the models for predicting the nitrate loads of the watershed's sub-basins. The proposed MS method not only considers the prediction of the outlet nitrate but also covers predictions of interior sub-basins nitrate load values. The results indicated that the proposed FFNN model coupled with the SOM-MI improved the performance of MS nitrate predictions compared to the Markovian-based models up to 39%. Overall, accurate selection of dominant inputs which consider seasonality-based characteristics of streamflow-nitrate process could enhance the efficiency of nitrate load predictions.

Team Teaching.

ERIC Educational Resources Information Center

Cunningham, David C.

1963-01-01

A study was designed to evaluate the effectiveness of principals in structuring teaching teams; to assess background and personality characteristics appearing essential to successful individual and team performance; and to select personality factor scores which would predict individual and team success. Subjects were 31 teaching teams (99…

Factors Influencing College Persistence for First-Time Students

ERIC Educational Resources Information Center

Stewart, Sheilynda; Lim, Doo Hun; Kim, JoHyun

2015-01-01

Using Tinto's (1993) longitudinal model of institutional departure, this study examined demographic variables, family characteristics, precollege and college academic performance factors, and extent to which mandatory placement in remedial courses predict persistence at a public research institution. This study also examined the relationship…

Video Games as Psychological Tests.

ERIC Educational Resources Information Center

Jones, Marshall B.

1984-01-01

Briefly describes the characteristics of video games and discusses some advantages and disadvantages of their use to measure individual abilities. Relevant research is cited in the areas of stabilization with practice, predictive testing, performance testing, testing under extreme conditions, testing brain-injured persons, and differential…

A PRIM approach to predictive-signature development for patient stratification

PubMed Central

Chen, Gong; Zhong, Hua; Belousov, Anton; Devanarayan, Viswanath

2015-01-01

Patients often respond differently to a treatment because of individual heterogeneity. Failures of clinical trials can be substantially reduced if, prior to an investigational treatment, patients are stratified into responders and nonresponders based on biological or demographic characteristics. These characteristics are captured by a predictive signature. In this paper, we propose a procedure to search for predictive signatures based on the approach of patient rule induction method. Specifically, we discuss selection of a proper objective function for the search, present its algorithm, and describe a resampling scheme that can enhance search performance. Through simulations, we characterize conditions under which the procedure works well. To demonstrate practical uses of the procedure, we apply it to two real-world data sets. We also compare the results with those obtained from a recent regression-based approach, Adaptive Index Models, and discuss their respective advantages. In this study, we focus on oncology applications with survival responses. PMID:25345685

On use of characteristic wavelengths of track irregularities to predict track portions with deteriorated wheel/rail forces

NASA Astrophysics Data System (ADS)

Xu, Lei; Zhai, Wanming; Chen, Zhaowei

2018-05-01

The dynamic performance of the railway vehicles and the guiding tracks is mainly governed by the wheel-rail interactions, particularly in cases of track irregularities. In this work, a united model was developed to investigate the track portions subject to violent wheel/rail forces triggered by track irregularities at middle-low frequencies. In the modeling procedures, a time-frequency unification method combining wavelet transform and Wigner-Ville distribution for characterizing time-frequency characteristics of track irregularities and a three-dimensional nonlinear model for describing vehicle-track interaction signatures were developed and coupled, based on which the method for predicting track portions subject to deteriorated wheel/rail forces was proposed. The theoretical models developed in this paper were comprehensively validated by numerical investigations. The significance of this present study mainly lies on offering a new path to establish correlation and realize mutual prediction between track irregularity and railway system dynamics.

Flight evaluation of the transonic stability and control characteristics of an airplane incorporating a supercritical wing

NASA Technical Reports Server (NTRS)

Matheny, N. W.; Gatlin, D. H.

1978-01-01

A TF-8A airplane was equipped with a transport type supercritical wing and fuselage fairings to evaluate predicted performance improvements for cruise at transonic speeds. A comparison of aerodynamic derivatives extracted from flight and wind tunnel data showed that static longitudinal stability, effective dihedral, and aileron effectiveness, were higher than predicted. The static directional stability derivative was slower than predicted. The airplane's handling qualities were acceptable with the stability augmentation system on. The unaugmented airplane exhibited some adverse lateral directional characteristics that involved low Dutch roll damping and low roll control power at high angles of attack and roll control power that was greater than satisfactory for transport aircraft at cruise conditions. Longitudinally, the aircraft exhibited a mild pitchup tendency. Leading edge vortex generators delayed the onset of flow separation, moving the pitchup point to a higher lift coefficient and reducing its severity.

Evaluation of the synoptic and mesoscale predictive capabilities of a mesoscale atmospheric simulation system

NASA Technical Reports Server (NTRS)

Koch, S. E.; Skillman, W. C.; Kocin, P. J.; Wetzel, P. J.; Brill, K.; Keyser, D. A.; Mccumber, M. C.

1983-01-01

The overall performance characteristics of a limited area, hydrostatic, fine (52 km) mesh, primitive equation, numerical weather prediction model are determined in anticipation of satellite data assimilations with the model. The synoptic and mesoscale predictive capabilities of version 2.0 of this model, the Mesoscale Atmospheric Simulation System (MASS 2.0), were evaluated. The two part study is based on a sample of approximately thirty 12h and 24h forecasts of atmospheric flow patterns during spring and early summer. The synoptic scale evaluation results benchmark the performance of MASS 2.0 against that of an operational, synoptic scale weather prediction model, the Limited area Fine Mesh (LFM). The large sample allows for the calculation of statistically significant measures of forecast accuracy and the determination of systematic model errors. The synoptic scale benchmark is required before unsmoothed mesoscale forecast fields can be seriously considered.

Interpretable Deep Models for ICU Outcome Prediction

PubMed Central

Che, Zhengping; Purushotham, Sanjay; Khemani, Robinder; Liu, Yan

2016-01-01

Exponential surge in health care data, such as longitudinal data from electronic health records (EHR), sensor data from intensive care unit (ICU), etc., is providing new opportunities to discover meaningful data-driven characteristics and patterns ofdiseases. Recently, deep learning models have been employedfor many computational phenotyping and healthcare prediction tasks to achieve state-of-the-art performance. However, deep models lack interpretability which is crucial for wide adoption in medical research and clinical decision-making. In this paper, we introduce a simple yet powerful knowledge-distillation approach called interpretable mimic learning, which uses gradient boosting trees to learn interpretable models and at the same time achieves strong prediction performance as deep learning models. Experiment results on Pediatric ICU dataset for acute lung injury (ALI) show that our proposed method not only outperforms state-of-the-art approaches for morality and ventilator free days prediction tasks but can also provide interpretable models to clinicians. PMID:28269832

Does probability guided hysteroscopy reduce costs in women investigated for postmenopausal bleeding?

PubMed

Breijer, M C; van Hanegem, N; Visser, N C M; Verheijen, R H M; Mol, B W J; Pijnenborg, J M A; Opmeer, B C; Timmermans, A

2015-01-01

To evaluate whether a model to predict a failed endometrial biopsy in women with postmenopausal bleeding (PMB) and a thickened endometrium can reduce costs without compromising diagnostic accuracy. Model based cost-minimization analysis. A decision analytic model was designed to compare two diagnostic strategies for women with PMB: (I) attempting office endometrial biopsy and performing outpatient hysteroscopy after failed biopsy and (II) predicted probability of a failed endometrial biopsy based on patient characteristics to guide the decision for endometrial biopsy or immediate hysteroscopy. Robustness of assumptions regarding costs was evaluated in sensitivity analyses. Costs for the different strategies. At different cut-offs for the predicted probability of failure of an endometrial biopsy, strategy I was generally less expensive than strategy II. The costs for strategy I were always € 460; the costs for strategy II varied between € 457 and € 475. At a 65% cut-off, a possible saving of € 3 per woman could be achieved. Individualizing the decision to perform an endometrial biopsy or immediate hysteroscopy in women presenting with postmenopausal bleeding based on patient characteristics does not increase the efficiency of the diagnostic work-up.

Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function

PubMed Central

Tian, Weidong; Zhang, Lan V; Taşan, Murat; Gibbons, Francis D; King, Oliver D; Park, Julie; Wunderlich, Zeba; Cherry, J Michael; Roth, Frederick P

2008-01-01

Background: Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships. Results: We have developed a strategy ('Funckenstein') that performs guilt-by-profiling and guilt-by-association and combines the results. Using a benchmark set of functional categories and input data for protein-coding genes in Saccharomyces cerevisiae, Funckenstein was compared with a previous combined strategy. Subsequently, we applied Funckenstein to 2,455 Gene Ontology terms. In the process, we developed 2,455 guilt-by-profiling classifiers based on 8,848 gene characteristics and 12 functional linkage graphs based on 23 biological relationships. Conclusion: Funckenstein outperforms a previous combined strategy using a common benchmark dataset. The combination of 'guilt-by-profiling' and 'guilt-by-association' gave significant improvement over the component classifiers, showing the greatest synergy for the most specific functions. Performance was evaluated by cross-validation and by literature examination of the top-scoring novel predictions. These quantitative predictions should help prioritize experimental study of yeast gene functions. PMID:18613951

Propellant vaporization as a criterion for rocket-engine design : experimental effect of fuel temperature on liquid-oxygen - heptane performance

NASA Technical Reports Server (NTRS)

Heidmann, M F

1957-01-01

Characteristic exhaust velocity of a 200-pound-thrust rocket engine was evaluated for fuel temperatures of -90 degrees, and 200 degrees f with a spray formed by two impinging heptane jets reacting in a highly atomized oxygen atmosphere. Tests covered a range of mixture ratios and chamber lengths. The characteristic exhaust-velocity efficiency increased 2 percent for a 290 degree f increase in fuel temperature. This increase in performance can be compared with that obtained by increasing chamber length by about 1/2 inch. The result agrees with the fuel-temperature effect predicted from an analysis based on droplet evaporation theory. Mixture ratio markedly affected characteristic exhaust velocity efficiency, but total flow rate and fuel temperature did not.

Flow Characteristics Near to Stent Strut Configurations on Femoropopliteal Artery

NASA Astrophysics Data System (ADS)

Paisal, Muhammad Sufyan Amir; Fadhil Syed Adnan, Syed; Taib, Ishkrizat; Ismail, Al Emran; Kamil Abdullah, Mohammad; Nordin, Normayati; Seri, Suzairin Md; Darlis, Nofrizalidris

2017-08-01

Femoropopiteal artery stenting is a common procedure suggested by medical expert especially for patient who is diagnosed with severe stenosis. Many researchers reported that the growth of stenosis is significantly related to the geometry of stent strut configuration. The different shapes of stent geometry are presenting the different flow pattern and re-circulation in stented femoropopliteal artery. The blood flow characteristics near to the stent geometry are predicted for the possibility of thrombosis and atherosclerosis to be formed as well as increase the growth of stenosis. Thus, this study aims to determine the flow characteristic near to stent strut configuration based on different hemodynamic parameters. Three dimensional models of stent and simplified femoropopliteal artery are modelled using computer aided design (CAD) software. Three different models of stent shapes; hexagon, circle and rectangle are simulated using computational fluid dynamic (CFD) method. Then, parametric study is implemented to predict the performance of stent due to hemodynamic differences. The hemodynamic parameters considered are pressure, velocity, low wall shear stress (WSSlow) and wall shear stress (WSS). From the observation, flow re-circulation has been formed for all simulated stent models which the proximal region shown the severe vortices. However, rectangular shape of stent strut (Type P3) shows the lowest WSSlow and the highest WSS between the range of 4 dyne/cm2 and 70 dyne/cm2. Stent Type P3 also shows the best hemodynamic stent performance as compare to others. In conclusion, Type P3 has a favourable result in hemodynamic stent performance that predicted less probability of thrombosis and atherosclerosis to be formed as well as reduces the growth of restenosis.

Challenges of developing a cardiovascular risk calculator for patients with rheumatoid arthritis.

PubMed

Crowson, Cynthia S; Rollefstad, Silvia; Kitas, George D; van Riel, Piet L C M; Gabriel, Sherine E; Semb, Anne Grete

2017-01-01

Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

In silico modeling to predict drug-induced phospholipidosis

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

Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov

2013-06-01

Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the constructionmore » and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.« less

Performance analysis of the ascent propulsion system of the Apollo spacecraft

NASA Technical Reports Server (NTRS)

Hooper, J. C., III

1973-01-01

Activities involved in the performance analysis of the Apollo lunar module ascent propulsion system are discussed. A description of the ascent propulsion system, including hardware, instrumentation, and system characteristics, is included. The methods used to predict the inflight performance and to establish performance uncertainties of the ascent propulsion system are discussed. The techniques of processing the telemetered flight data and performing postflight performance reconstruction to determine actual inflight performance are discussed. Problems that have been encountered and results from the analysis of the ascent propulsion system performance during the Apollo 9, 10, and 11 missions are presented.

International Low-Earth-Orbit Spacecraft Materials Test Program Initiated for Better Prediction of Durability and Performance

NASA Technical Reports Server (NTRS)

Rutledge, Sharon K.

1999-01-01

Spacecraft in low Earth orbit (LEO) are subjected to many components of the environment, which can cause them to degrade much more rapidly than intended and greatly shorten their functional life. The atomic oxygen, ultraviolet radiation, and cross contamination present in LEO can affect sensitive surfaces such as thermal control paints, multilayer insulation, solar array surfaces, and optical surfaces. The LEO Spacecraft Materials Test (LEO-SMT) program is being conducted to assess the effects of simulated LEO exposure on current spacecraft materials to increase understanding of LEO degradation processes as well as to enable the prediction of in-space performance and durability. Using ground-based simulation facilities to test the durability of materials currently flying in LEO will allow researchers to compare the degradation evidenced in the ground-based facilities with that evidenced on orbit. This will allow refinement of ground laboratory test systems and the development of algorithms to predict the durability and performance of new materials in LEO from ground test results. Accurate predictions based on ground tests could reduce development costs and increase reliability. The wide variety of national and international materials being tested represent materials being functionally used on spacecraft in LEO. The more varied the types of materials tested, the greater the probability that researchers will develop and validate predictive models for spacecraft long-term performance and durability. Organizations that are currently participating in the program are ITT Research Institute (USA), Lockheed Martin (USA), MAP (France), SOREQ Nuclear Research Center (Israel), TNO Institute of Applied Physics (The Netherlands), and UBE Industries, Ltd. (Japan). These represent some of the major suppliers of thermal control and sensor materials currently flying in LEO. The participants provide materials that are exposed to selected levels of atomic oxygen, vacuum ultraviolet radiation, contamination, or synergistic combined environments at the NASA Lewis Research Center. Changes in characteristics that could affect mission performance or lifetime are then measured. These characteristics include changes in mass, solar absorptance, and thermal emittance. The durability of spacecraft materials from U.S. suppliers is then compared with those of materials from other participating countries. Lewis will develop and validate performance and durability prediction models using this ground data and available space data. NASA welcomes the opportunity to consider additional international participants in this program, which should greatly aid future spacecraft designers as they select materials for LEO missions.

What predicts performance during clinical psychology training?

PubMed Central

Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

2014-01-01

Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Results Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Conclusions Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. Practitioner points While referee and selection interview ratings did not predict performance during training, they may be useful in screening out unsuitable candidates at the application stage High school final academic performance was the best predictor of good performance during clinical psychology training The findings are derived from seven cohorts of one training course, the UK's largest; they cannot be assumed to generalize to all training courses PMID:24206117

EEG potentials predict upcoming emergency brakings during simulated driving

NASA Astrophysics Data System (ADS)

Haufe, Stefan; Treder, Matthias S.; Gugler, Manfred F.; Sagebaum, Max; Curio, Gabriel; Blankertz, Benjamin

2011-10-01

Emergency braking assistance has the potential to prevent a large number of car crashes. State-of-the-art systems operate in two stages. Basic safety measures are adopted once external sensors indicate a potential upcoming crash. If further activity at the brake pedal is detected, the system automatically performs emergency braking. Here, we present the results of a driving simulator study indicating that the driver's intention to perform emergency braking can be detected based on muscle activation and cerebral activity prior to the behavioural response. Identical levels of predictive accuracy were attained using electroencephalography (EEG), which worked more quickly than electromyography (EMG), and using EMG, which worked more quickly than pedal dynamics. A simulated assistance system using EEG and EMG was found to detect emergency brakings 130 ms earlier than a system relying only on pedal responses. At 100 km h-1 driving speed, this amounts to reducing the braking distance by 3.66 m. This result motivates a neuroergonomic approach to driving assistance. Our EEG analysis yielded a characteristic event-related potential signature that comprised components related to the sensory registration of a critical traffic situation, mental evaluation of the sensory percept and motor preparation. While all these components should occur often during normal driving, we conjecture that it is their characteristic spatio-temporal superposition in emergency braking situations that leads to the considerable prediction performance we observed.

EEG potentials predict upcoming emergency brakings during simulated driving.

PubMed

Haufe, Stefan; Treder, Matthias S; Gugler, Manfred F; Sagebaum, Max; Curio, Gabriel; Blankertz, Benjamin

2011-10-01

Emergency braking assistance has the potential to prevent a large number of car crashes. State-of-the-art systems operate in two stages. Basic safety measures are adopted once external sensors indicate a potential upcoming crash. If further activity at the brake pedal is detected, the system automatically performs emergency braking. Here, we present the results of a driving simulator study indicating that the driver's intention to perform emergency braking can be detected based on muscle activation and cerebral activity prior to the behavioural response. Identical levels of predictive accuracy were attained using electroencephalography (EEG), which worked more quickly than electromyography (EMG), and using EMG, which worked more quickly than pedal dynamics. A simulated assistance system using EEG and EMG was found to detect emergency brakings 130 ms earlier than a system relying only on pedal responses. At 100 km h(-1) driving speed, this amounts to reducing the braking distance by 3.66 m. This result motivates a neuroergonomic approach to driving assistance. Our EEG analysis yielded a characteristic event-related potential signature that comprised components related to the sensory registration of a critical traffic situation, mental evaluation of the sensory percept and motor preparation. While all these components should occur often during normal driving, we conjecture that it is their characteristic spatio-temporal superposition in emergency braking situations that leads to the considerable prediction performance we observed.

ELF Sferics Produced by Rocket-Triggered Lightning and Observed at Great Distances

NASA Astrophysics Data System (ADS)

Dupree, N. A.; Moore, R. C.; Fraser-Smith, A. C.

2013-12-01

Experimental observations of ELF radio atmospherics produced by rocket-triggered lightning flashes are used to analyze Earth-ionosphere waveguide excitation and propagation characteristics as a function of return stroke. Rocket-triggered lightning experiments are performed at the International Center for Lightning Research and Testing (ICLRT) located at Camp Blanding, Florida. Long-distance ELF observations are performed in California, Greenland, and Antarctica, although this work focuses on observations performed in Greenland. The lightning current waveforms directly measured at the base of the lightning channel (at the ICLRT) are used together with the Long Wavelength Propagation Capability (LWPC) code to predict the sferic waveform observed at the receiver locations under various ionospheric conditions. LWPC was developed by the Naval Ocean Systems Center over a period of many years. It is an inherently narrowband propagation code that has been modified to predict the broadband response of the Earth-ionosphere waveguide to an impulsive lightning flash while preserving the ability of LWPC to account for an inhomogeneous waveguide. This paper critically compares observations with model predictions, and in particular analyzes Earth-ionosphere waveguide excitation as a function of return stroke. The ability to infer source characteristics using observations at great distances may prove to greatly enhance the understanding of lightning processes that are associated with the production of transient luminous events (TLEs) as well as other ionospheric effects associated with lightning.

Slug sizing/slug volume prediction, state of the art review and simulation

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

Burke, N.E.; Kashou, S.F.

1995-12-01

Slug flow is a flow pattern commonly encountered in offshore multiphase flowlines. It is characterized by an alternate flow of liquid slugs and gas pockets, resulting in an unsteady hydrodynamic behavior. All important design variables, such as slug length and slug frequency, liquid holdup, and pressure drop, vary with time and this makes the prediction of slug flow characteristics both difficult and challenging. This paper reviews the state of the art methods in slug catcher sizing and slug volume predictions. In addition, history matching of measured slug flow data is performed using the OLGA transient simulator. This paper reviews themore » design factors that impact slug catcher sizing during steady state, during transient, during pigging, and during operations under a process control system. The slug tracking option of the OLGA simulator is applied to predict the slug length and the slug volume during a field operation. This paper will also comment on the performance of common empirical slug prediction correlations.« less

Slug-sizing/slug-volume prediction: State of the art review and simulation

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

Burke, N.E.; Kashou, S.F.

1996-08-01

Slug flow is a flow pattern commonly encountered in offshore multiphase flowlines. It is characterized by an alternate flow of liquid slugs and gas pockets, resulting in an unsteady hydrodynamic behavior. All important design variables, such as slug length and slug frequency, liquid holdup, and pressure drop, vary with time and this makes the prediction of slug flow characteristics both difficult and challenging. This paper reviews the state of the art methods in slug-catcher sizing and slug-volume predictions. In addition, history matching of measured slug flow data is performed using the OLGA transient simulator. This paper reviews the design factorsmore » that impact slug-catcher sizing during steady state, during transient, during pigging, and during operations under a process-control system. The slug-tracking option of the simulator is applied to predict the slug length and the slug volume during a field operation. This paper will also comment on the performance of common empirical slug-prediction correlations.« less

Comparison of Models for Spacer Grid Pressure Loss in Nuclear Fuel Bundles for One and Two-Phase Flows

NASA Astrophysics Data System (ADS)

Maskal, Alan B.

Spacer grids maintain the structural integrity of the fuel rods within fuel bundles of nuclear power plants. They can also improve flow characteristics within the nuclear reactor core. However, spacer grids add reactor coolant pressure losses, which require estimation and engineering into the design. Several mathematical models and computer codes were developed over decades to predict spacer grid pressure loss. Most models use generalized characteristics, measured by older, less precise equipment. The study of OECD/US-NRC BWR Full-Size Fine Mesh Bundle Tests (BFBT) provides updated and detailed experimental single and two-phase results, using technically advanced flow measurements for a wide range of boundary conditions. This thesis compares the predictions from the mathematical models to the BFBT experimental data by utilizing statistical formulae for accuracy and precision. This thesis also analyzes the effects of BFBT flow characteristics on spacer grids. No single model has been identified as valid for all flow conditions. However, some models' predictions perform better than others within a range of flow conditions, based on the accuracy and precision of the models' predictions. This study also demonstrates that pressure and flow quality have a significant effect on two-phase flow spacer grid models' biases.

Predictors and Effects of Knowledge Management in U.S. Colleges and Schools of Pharmacy

NASA Astrophysics Data System (ADS)

Watcharadamrongkun, Suntaree

Public demands for accountability in higher education have placed increasing pressure on institutions to document their achievement of critical outcomes. These demands also have had wide-reaching implications for the development and enforcement of accreditation standards, including those governing pharmacy education. The knowledge management (KM) framework provides perspective for understanding how organizations evaluate themselves and guidance for how to improve their performance. In this study, we explore knowledge management processes, how these processes are affected by organizational structure and by information technology resources, and how these processes affect organizational performance. This is done in the context of Accreditation Standards and Guidelines for the Professional Program in Pharmacy Leading to the Doctor of Pharmacy Degree (Standards 2007). Data were collected using an online census survey of 121 U.S. Colleges and Schools of Pharmacy and supplemented with archival data. A key informant method was used with CEO Deans and Assessment leaders serving as respondents. The survey yielded a 76.0% (92/121) response rate. Exploratory factor analysis was used to construct scales (and scales) describing core KM processes: Knowledge Acquisition, Knowledge Integration, and Institutionalization; all scale reliabilities were found to be acceptable. Analysis showed that, as expected, greater Knowledge Acquisition predicts greater Knowledge Integration and greater Knowledge Integration predicts greater Institutionalization. Predictive models were constructed using hierarchical multiple regression and path analysis. Overall, information technology resources had stronger effects on KM processes than did characteristics of organizational structure. Greater Institutionalization predicted better outcomes related to direct measures of performance (i.e., NAPLEX pass rates, Accreditation actions) but Institutionalization was unrelated to an indirect measure of performance (i.e., USNWR ratings). Several organizational structure characteristics (i.e., size, age, and being part of an academic health center) were significant predictors of organizational performance; in contrast, IT resources had no direct effects on performance. Findings suggest that knowledge management processes, organizational structures and IT resources are related to better performance for Colleges and Schools of Pharmacy. Further research is needed to understand mechanisms through which specific knowledge management processes translate into better performance and, relatedly, to establish how enhancing KM processes can be used to improve institutional quality.

Grindability measurements on low-rank fuels. [Prediction of large pulverizer performance from small scale test equipment

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

Peipho, R.R.; Dougan, D.R.

1981-01-01

Experience has shown that the grinding characteristics of low rank coals are best determined by testing them in a pulverizer. Test results from a small MPS-32 Babcock and Wilcox pulverizer to predict large, full-scale pulverizer performance are presented. The MPS-32 apparatus, test procedure and evaluation of test results is described. The test data show that the Hardgrove apparatus and the ASTM test method must be used with great caution when considering low-rank fuels. The MPS-32 meets the needs for real-machine simulation but with some disadvantages. A smaller pulverizer is desirable. 1 ref.

Development of a screening tool using electronic health records for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose detection in the Slovenian population.

PubMed

Štiglic, G; Kocbek, P; Cilar, L; Fijačko, N; Stožer, A; Zaletel, J; Sheikh, A; Povalej Bržan, P

2018-05-01

To develop and validate a simplified screening test for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose for the Slovenian population (SloRisk) to be used in the general population. Data on 11 391 people were collected from the electronic health records of comprehensive medical examinations in five Slovenian healthcare centres. Fasting plasma glucose as well as information related to the Finnish Diabetes Risk Score questionnaire, FINDRISC, were collected for 2073 people to build predictive models. Bootstrapping-based evaluation was used to estimate the area under the receiver-operating characteristic curve performance metric of two proposed logistic regression models as well as the Finnish Diabetes Risk Score model both at recommended and at alternative cut-off values. The final model contained five questions for undiagnosed Type 2 diabetes prediction and achieved an area under the receiver-operating characteristic curve of 0.851 (95% CI 0.850-0.853). The impaired fasting glucose prediction model included six questions and achieved an area under the receiver-operating characteristic curve of 0.840 (95% CI 0.839-0.840). There were four questions that were included in both models (age, sex, waist circumference and blood sugar history), with physical activity selected only for undiagnosed Type 2 diabetes and questions on family history and hypertension drug use selected only for the impaired fasting glucose prediction model. This study proposes two simplified models based on FINDRISC questions for screening of undiagnosed Type 2 diabetes and impaired fasting glucose in the Slovenian population. A significant improvement in performance was achieved compared with the original FINDRISC questionnaire. Both models include waist circumference instead of BMI. © 2018 Diabetes UK.

Personal and Environmental Characteristics Predicting Burnout Among Certified Athletic Trainers at National Collegiate Athletic Association Institutions

PubMed Central

Kania, Michelle L; Meyer, Barbara B; Ebersole, Kyle T

2009-01-01

Context: Recent research in the health care professions has shown that specific personal and environmental characteristics can predict burnout, which is a negative coping strategy related to stressful situations. Burnout has been shown to result in physiologic (eg, headaches, difficulty sleeping, poor appetite), psychological (eg, increased negative self-talk, depression, difficulty in interpersonal relationships), and behavioral (eg, diminished care, increased absenteeism, attrition) symptoms. Objective: To examine the relationship between selected personal and environmental characteristics and burnout among certified athletic trainers (ATs). Design: Cross-sectional survey. Setting: A demographic survey that was designed for this study and the Maslach Burnout Inventory–Human Services Survey. Patients or Other Participants: A total of 206 ATs employed at National Collegiate Athletic Association (NCAA) institutions as clinical ATs volunteered. Main Outcome Measure(s): We assessed personal and environmental characteristics of ATs with the demographic survey and measured burnout using the Maslach Burnout Inventory–Human Services Survey. Multiple regression analyses were performed to examine relationships between specific personal and environmental characteristics and each of the 3 subscales of burnout (emotional exhaustion, depersonalization, personal accomplishment). Results: Most ATs we surveyed experienced low to average levels of burnout. Personal characteristics predicted 45.5% of the variance in emotional exhaustion (P < .001), 21.5% of the variance in depersonalization (P < .001), and 24.8% of the variance in personal accomplishment (P < .001). Environmental characteristics predicted 16.7% of the variance in emotional exhaustion (P  =  .005), 14.4% of the variance in depersonalization (P  =  .024), and 10.4% of the variance in personal accomplishment (P  =  .209). Stress level and coaches' pressure to medically clear athletes predicted ratings on all 3 subscales of burnout. Conclusions: Our findings were similar to those of other studies of burnout among NCAA Division I ATs, coaches, and coach-teachers. The results also support the Cognitive-Affective Model of Athletic Burnout proposed by Smith. Finally, these results indicate new areas of concentration for burnout research and professional practice. PMID:19180220

Fast-response free-running frequency-stabilized dc-to-dc converter employing a state plane-trajectory control law

NASA Technical Reports Server (NTRS)

Huffman, S. D.; Burns, W. W., III; Wilson, T. G.; Owen, H. A., Jr.

1976-01-01

Implementations of a state-plane-trajectory control law for energy storage dc-to-dc converters are presented. Performance characteristics of experimental voltage step-up converter systems employing these implementations are reported and compared to theoretical predictions.

DECISION-SUPPORT TOOLS FOR PREDICTING THE PERFORMANCE OF WATER DISTRIBUTION AND WASTEWATER COLLECTION SYSTEMS

EPA Science Inventory

Water and wastewater infrastructure systems represent a major capital investment; utilities must ensure they are getting the highest yield possible on their investment, both in terms of dollars and water quality. Accurate information related to equipment, pipe characteristics, l...

DECISION-SUPPORT TOOLS FOR PREDICTING THE PERFORMANCE OF WATER DISTRIBUTION AND WASTEWATER COLLECTION SYSTEMS

EPA Science Inventory

Water and wastewater infrastructure systems represent a major capital investment; utilities must ensure they are getting the highest yield possible on their investment, both in terms of dollars and water quality. Accurate information related to equipment, pipe characteristics, lo...

Evaluation of the Shuttle GN&C during powered ascent flight phase. [Guidance Navigation and Control equipment system design and flight tests

NASA Technical Reports Server (NTRS)

Olson, L.; Sunkel, J. W.

1982-01-01

An overview of the ascent trajectory and GN&C (guidance, navigation, and control) system design is followed by a summary of flight test results for the ascent phase of STS-1. The most notable variance from nominal pre-flight predictions was the lofted trajectory observed in first stage due to an unanticipated shift in pitch aerodynamic characteristics from those predicted by wind tunnel tests. The GN&C systems performed as expected on STS-1 throughout powered flight. Following a discussion of the software constants changed for Flight 2 to provide adequate performance margin, a summary of test results from STS-2 and STS-3 is presented. Vehicle trajectory response and GN&C system behavior were very similar to STS-1. Ascent aerodynamic characteristics extracted from the first two test flights were included in the data base used to design the first stage steering and pitch trim profiles for STS-3.

Current Testing Capabilities at the NASA Ames Ballistic Ranges

NASA Technical Reports Server (NTRS)

Ramsey, Alvin; Tam, Tim; Bogdanoff, David; Gage, Peter

1999-01-01

Capabilities for designing and performing ballistic range tests at the NASA Ames Research Center are presented. Computational tools to assist in designing and developing ballistic range models and to predict the flight characteristics of these models are described. A CFD code modeling two-stage gun performance is available, allowing muzzle velocity, maximum projectile base pressure, and gun erosion to be predicted. Aerodynamic characteristics such as drag and stability can be obtained at speeds ranging from 0.2 km/s to 8 km/s. The composition and density of the test gas can be controlled, which allows for an assessment of Reynolds number and specific heat ratio effects under conditions that closely match those encountered during planetary entry. Pressure transducers have been installed in the gun breech to record the time history of the pressure during launch, and pressure transducers have also been installed in the walls of the range to measure sonic boom effects. To illustrate the testing capabilities of the Ames ballistic ranges, an overview of some of the recent tests is given.

Preliminary noise tradeoff study of a Mach 2.7 cruise aircraft

NASA Technical Reports Server (NTRS)

Mascitti, V. R.; Maglieri, D. J. (Editor); Raney, J. P. (Editor)

1979-01-01

NASA computer codes in the areas of preliminary sizing and enroute performance, takeoff and landing performance, aircraft noise prediction, and economics were used in a preliminary noise tradeoff study for a Mach 2.7 design supersonic cruise concept. Aerodynamic configuration data were based on wind-tunnel model tests and related analyses. Aircraft structural characteristics and weight were based on advanced structural design methodologies, assuming conventional titanium technology. The most advanced noise prediction techniques available were used, and aircraft operating costs were estimated using accepted industry methods. The 4-engines cycles included in the study were based on assumed 1985 technology levels. Propulsion data was provided by aircraft manufacturers. Additional empirical data is needed to define both noise reduction features and other operating characteristics of all engine cycles under study. Data on VCE design parameters, coannular nozzle inverted flow noise reduction and advanced mechanical suppressors are urgently needed to reduce the present uncertainties in studies of this type.

Decision making for pancreatic resection in patients with intraductal papillary mucinous neoplasms.

PubMed

Xu, Bin; Ding, Wei-Xing; Jin, Da-Yong; Wang, Dan-Song; Lou, Wen-Hui

2013-03-07

To identify a practical approach for preoperative decision-making in patients with intraductal papillary mucinous neoplasms (IPMNs) of the pancreas. Between March 1999 and November 2006, the clinical characteristics, pathological data and computed tomography/magnetic resonance imaging (CT/MRI) of 54 IPMNs cases were retrieved and analyzed. The relationships between the above data and decision-making for pancreatic resection were analyzed using SPSS 13.0 software. Univariate analysis of risk factors for malignant or invasive IPMNs was performed with regard to the following variables: carcinoembryonic antigen, carbohydrate antigen 19-9 (CA19-9) and the characteristics from CT/MRI images. Receiver operating characteristic (ROC) curve analysis for pancreatic resection was performed using significant factors from the univariate analysis. CT/MRI images, including main and mixed duct IPMNs, tumor size > 30 mm or a solid component appearance in the lesion, and preoperative serum CA19-9 > 37 U/mL had good predictive value for determining pancreatic resection (P < 0.05), but with limitations. Combining the above factors (CT/MRI images and CA19-9) improved the accuracy and sensitivity for determining pancreatic resection in IPMNs. Using ROC analysis, the area under the curve reached 0.893 (P < 0.01, 95%CI: 0.763-1.023), with a sensitivity, specificity, positive predictive value and negative predictive value of 95.2%, 83.3%, 95.2% and 83.3%, respectively. Combining preoperative CT/MRI images and CA19-9 level may provide useful information for surgical decision-making in IPMNs.

Integrated Vehicle Ground Vibration Testing in Support of Launch Vehicle Loads and Controls Analysis

NASA Technical Reports Server (NTRS)

Askins, Bruce R.; Davis, Susan R.; Salyer, Blaine H.; Tuma, Margaret L.

2008-01-01

All structural systems possess a basic set of physical characteristics unique to that system. These unique physical characteristics include items such as mass distribution and damping. When specified, they allow engineers to understand and predict how a structural system behaves under given loading conditions and different methods of control. These physical properties of launch vehicles may be predicted by analysis or measured by certain types of tests. Generally, these properties are predicted by analysis during the design phase of a launch vehicle and then verified by testing before the vehicle becomes operational. A ground vibration test (GVT) is intended to measure by test the fundamental dynamic characteristics of launch vehicles during various phases of flight. During the series of tests, properties such as natural frequencies, mode shapes, and transfer functions are measured directly. These data will then be used to calibrate loads and control systems analysis models for verifying analyses of the launch vehicle. NASA manned launch vehicles have undergone ground vibration testing leading to the development of successful launch vehicles. A GVT was not performed on the inaugural launch of the unmanned Delta III which was lost during launch. Subsequent analyses indicated had a GVT been performed, it would have identified instability issues avoiding loss of the vehicle. This discussion will address GVT planning, set-up, execution and analyses, for the Saturn and Shuttle programs, and will also focus on the current and on-going planning for the Ares I and V Integrated Vehicle Ground Vibration Test (IVGVT).

Development of design and analysis methodology for composite bolted joints

NASA Astrophysics Data System (ADS)

Grant, Peter; Sawicki, Adam

1991-05-01

This paper summarizes work performed to develop composite joint design methodology for use on rotorcraft primary structure, determine joint characteristics which affect joint bearing and bypass strength, and develop analytical methods for predicting the effects of such characteristics in structural joints. Experimental results have shown that bearing-bypass interaction allowables cannot be defined using a single continuous function due to variance of failure modes for different bearing-bypass ratios. Hole wear effects can be significant at moderate stress levels and should be considered in the development of bearing allowables. A computer program has been developed and has successfully predicted bearing-bypass interaction effects for the (0/+/-45/90) family of laminates using filled hole and unnotched test data.

Single-pass memory system evaluation for multiprogramming workloads

NASA Technical Reports Server (NTRS)

Conte, Thomas M.; Hwu, Wen-Mei W.

1990-01-01

Modern memory systems are composed of levels of cache memories, a virtual memory system, and a backing store. Varying more than a few design parameters and measuring the performance of such systems has traditionally be constrained by the high cost of simulation. Models of cache performance recently introduced reduce the cost simulation but at the expense of accuracy of performance prediction. Stack-based methods predict performance accurately using one pass over the trace for all cache sizes, but these techniques have been limited to fully-associative organizations. This paper presents a stack-based method of evaluating the performance of cache memories using a recurrence/conflict model for the miss ratio. Unlike previous work, the performance of realistic cache designs, such as direct-mapped caches, are predicted by the method. The method also includes a new approach to the problem of the effects of multiprogramming. This new technique separates the characteristics of the individual program from that of the workload. The recurrence/conflict method is shown to be practical, general, and powerful by comparing its performance to that of a popular traditional cache simulator. The authors expect that the availability of such a tool will have a large impact on future architectural studies of memory systems.

Prediction future asset price which is non-concordant with the historical distribution

NASA Astrophysics Data System (ADS)

Seong, Ng Yew; Hin, Pooi Ah

2015-12-01

This paper attempts to predict the major characteristics of the future asset price which is non-concordant with the distribution estimated from the price today and the prices on a large number of previous days. The three major characteristics of the i-th non-concordant asset price are the length of the interval between the occurrence time of the previous non-concordant asset price and that of the present non-concordant asset price, the indicator which denotes that the non-concordant price is extremely small or large by its values -1 and 1 respectively, and the degree of non-concordance given by the negative logarithm of the probability of the left tail or right tail of which one of the end points is given by the observed future price. The vector of three major characteristics of the next non-concordant price is modelled to be dependent on the vectors corresponding to the present and l - 1 previous non-concordant prices via a 3-dimensional conditional distribution which is derived from a 3(l + 1)-dimensional power-normal mixture distribution. The marginal distribution for each of the three major characteristics can then be derived from the conditional distribution. The mean of the j-th marginal distribution is an estimate of the value of the j-th characteristics of the next non-concordant price. Meanwhile, the 100(α/2) % and 100(1 - α/2) % points of the j-th marginal distribution can be used to form a prediction interval for the j-th characteristic of the next non-concordant price. The performance measures of the above estimates and prediction intervals indicate that the fitted conditional distribution is satisfactory. Thus the incorporation of the distribution of the characteristics of the next non-concordant price in the model for asset price has a good potential of yielding a more realistic model.

Development and Preliminary Performance of a Risk Factor Screen to Predict Posttraumatic Psychological Disorder After Trauma Exposure

PubMed Central

Carlson, Eve B.; Palmieri, Patrick A.; Spain, David A.

2017-01-01

Objective We examined data from a prospective study of risk factors that increase vulnerability or resilience, exacerbate distress, or foster recovery to determine whether risk factors accurately predict which individuals will later have high posttraumatic (PT) symptom levels and whether brief measures of risk factors also accurately predict later symptom elevations. Method Using data from 129 adults exposed to traumatic injury of self or a loved one, we conducted receiver operating characteristic (ROC) analyses of 14 risk factors assessed by full-length measures, determined optimal cutoff scores and calculated predictive performance for the nine that were most predictive. For five risk factors, we identified sets of items that accounted for 90% of variance in total scores and calculated predictive performance for sets of brief risk measures. Results A set of nine risk factors assessed by full measures identified 89% of those who later had elevated PT symptoms (sensitivity) and 78% of those who did not (specificity). A set of four brief risk factor measures assessed soon after injury identified 86% of those who later had elevated PT symptoms and 72% of those who did not. Conclusions Use of sets of brief risk factor measures shows promise of accurate prediction of PT psychological disorder and probable PTSD or depression. Replication of predictive accuracy is needed in a new and larger sample. PMID:28622811

The injury severity score or the new injury severity score for predicting mortality, intensive care unit admission and length of hospital stay: experience from a university hospital in a developing country.

PubMed

Tamim, Hala; Al Hazzouri, Adina Zeki; Mahfoud, Ziad; Atoui, Maria; El-Chemaly, Souheil

2008-01-01

Limited research has been performed to compare the predictive abilities of the injury severity score (ISS) and the new ISS (NISS) in the developing world. From January 2001 until January 2003 all trauma patients admitted to the American University of Beirut Medical Centre were enrolled. The statistical performance of the ISS/NISS in predicting mortality, admission to the intensive care unit (ICU) and length of hospital stay (LOS dichotomised as <10 or > or =10 days) was evaluated using receiver operating characteristic and the Hosmer-Lemeshow calibration statistic. A total of 891 consecutive patients were enrolled. The ISS and NISS were equivalent in predicting survival, and both performed better in patients younger than 65 years of age. However, the ISS predicted ICU admission and LOS better than the NISS. However, these predictive abilities were lower for the geriatric trauma patients aged 65 years and above compared to the other age groups. There are conflicting results in the literature about the abilities of ISS and NISS to predict mortality. However, this is the first study to report that ISS has a superior ability in predicting both LOS and ICU admission. The scoring of trauma severity may need to be individualised to different countries and trauma systems.

Characterizing smoking topography of cannabis in heavy users

PubMed Central

Stitzer, Maxine L.; Vandrey, Ryan

2013-01-01

Rationale Little is known about the smoking topography characteristics of heavy cannabis users. Such measures may be able to predict cannabis use-related outcomes and could be used to validate self-reported measures of cannabis use. Objectives The current study was conducted to measure cannabis smoking topography characteristics during periods of ad libitum use and to correlate topography assessments with measures of self-reported cannabis use, withdrawal and craving during abstinence, and cognitive task performance. Methods Participants (N=20) completed an inpatient study in which they alternated between periods of ad libitum cannabis use and abstinence. Measures of self-reported cannabis use, smoking topography, craving, withdrawal, and sleep measures were collected. Results Participants smoked with greater intensity (e.g., greater volume, longer duration) on initial cigarette puffs with a steady decline on subsequent puffs. Smoking characteristics were significantly correlated with severity of withdrawal, notably sleep quality and architecture, and craving during abstinence, suggesting dose-related effects of cannabis use on these outcomes. Smoking characteristics generally were not significantly associated with cognitive performance. Smoking topography measures were significantly correlated with self-reported measures of cannabis use, indicating validity of these assessments, but topography measures were more sensitive than self-report in predicting cannabis-related outcomes. Conclusions A dose–effect relationship between cannabis consumption and outcomes believed to be clinically important was observed. With additional research, smoking topography assessments may become a useful clinical tool. PMID:21922170

James Webb Space Telescope Deployment Brushless DC Motor Characteristics Analysis

NASA Technical Reports Server (NTRS)

Tran, Ahn N.

2016-01-01

A DC motor's performance is usually characterized by a series of tests, which are conducted by pass/fail criteria. In most cases, these tests are adequate to address the performance characteristics under environmental and loading effects with some uncertainties and decent power/torque margins. However, if the motor performance requirement is very stringent, a better understanding of the motor characteristics is required. The purpose of this paper is to establish a standard way to extract the torque components of the brushless motor and gear box characteristics of a high gear ratio geared motor from the composite geared motor testing and motor parameter measurement. These torque components include motor magnetic detent torque, Coulomb torque, viscous torque, windage torque, and gear tooth sliding torque. The Aerospace Corp bearing torque model and MPB torque models are used to predict the Coulomb torque of the motor rotor bearings and to model the viscous components. Gear tooth sliding friction torque is derived from the dynamo geared motor test data. With these torque data, the geared motor mechanical efficiency can be estimated and provide the overall performance of the geared motor versus several motor operating parameters such as speed, temperature, applied current, and transmitted power.

Job Demands-Control-Support model and employee safety performance.

PubMed

Turner, Nick; Stride, Chris B; Carter, Angela J; McCaughey, Deirdre; Carroll, Anthony E

2012-03-01

The aim of this study was to explore whether work characteristics (job demands, job control, social support) comprising Karasek and Theorell's (1990) Job Demands-Control-Support framework predict employee safety performance (safety compliance and safety participation; Neal and Griffin, 2006). We used cross-sectional data of self-reported work characteristics and employee safety performance from 280 healthcare staff (doctors, nurses, and administrative staff) from Emergency Departments of seven hospitals in the United Kingdom. We analyzed these data using a structural equation model that simultaneously regressed safety compliance and safety participation on the main effects of each of the aforementioned work characteristics, their two-way interactions, and the three-way interaction among them, while controlling for demographic, occupational, and organizational characteristics. Social support was positively related to safety compliance, and both job control and the two-way interaction between job control and social support were positively related to safety participation. How work design is related to employee safety performance remains an important area for research and provides insight into how organizations can improve workplace safety. The current findings emphasize the importance of the co-worker in promoting both safety compliance and safety participation. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

1995-04-01

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

Electromagnetic Modelling of MMIC CPWs for High Frequency Applications

NASA Astrophysics Data System (ADS)

Sinulingga, E. P.; Kyabaggu, P. B. K.; Rezazadeh, A. A.

2018-02-01

Realising the theoretical electrical characteristics of components through modelling can be carried out using computer-aided design (CAD) simulation tools. If the simulation model provides the expected characteristics, the fabrication process of Monolithic Microwave Integrated Circuit (MMIC) can be performed for experimental verification purposes. Therefore improvements can be suggested before mass fabrication takes place. This research concentrates on development of MMIC technology by providing accurate predictions of the characteristics of MMIC components using an improved Electromagnetic (EM) modelling technique. The knowledge acquired from the modelling and characterisation process in this work can be adopted by circuit designers for various high frequency applications.

Performance and Operational Characteristics of a Python Turbine-propeller Engine at Simulated Altitude Conditions / Carl L. Meyer and Lavern A. Johnson

NASA Technical Reports Server (NTRS)

Meyer, Carl L; Johnson, Lavern A

1952-01-01

The performance and operational characteristics of a Python turbine-propeller engine were investigated at simulated altitude conditions in the NACA Lewis altitude wind tunnel. In the performance phase, data were obtained over a range of engine speeds and exhaust nozzle areas at altitudes from 10,000 to 40,000 feet at a single cowl-inlet ram pressure ratio; independent control of engine speed and fuel flow was used to obtain a range of powers at each engine speed. Engine performance data obtained at a given altitude could not be used to predict performance accurately at other altitudes by use of the standard air pressure and temperature generalizing factors. At a given engine speed and turbine-inlet total temperature, a greater portion of the total available energy was converted to propulsive power as the altitude increased.

What Performance Characteristics Determine Elite Versus Nonelite Athletes in the Same Sport?

PubMed Central

Lorenz, Daniel S.; Reiman, Michael P.; Lehecka, B.J.; Naylor, Andrew

2013-01-01

Context: There are significant data comparing elite and nonelite athletes in anaerobic field and court sports as well as endurance sports. This review delineates specific performance characteristics in the elite athlete and may help guide rehabilitation. Evidence Acquisition: A Medline search from April 1982 to April 2012 was undertaken for articles written in English. Additional references were accrued from reference lists of research articles. Results: In the anaerobic athlete, maximal power production was consistently correlated to elite performance. Elite performance in the endurance athlete is more ambiguous, however, and appears to be related to the dependent variable investigated in each individual study. Conclusion: In anaerobic field and court sport athletes, maximal power output is most predictive of elite performance. In the endurance athlete, however, it is not as clear. Elite endurance athletes consistently test higher than nonelite athletes in running economy, anaerobic threshold, and VO2max. PMID:24427430

Numerical predictions of EML (electromagnetic launcher) system performance

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

Schnurr, N.M.; Kerrisk, J.F.; Davidson, R.F.

1987-01-01

The performance of an electromagnetic launcher (EML) depends on a large number of parameters, including the characteristics of the power supply, rail geometry, rail and insulator material properties, injection velocity, and projectile mass. EML system performance is frequently limited by structural or thermal effects in the launcher (railgun). A series of computer codes has been developed at the Los Alamos National Laboratory to predict EML system performance and to determine the structural and thermal constraints on barrel design. These codes include FLD, a two-dimensional electrostatic code used to calculate the high-frequency inductance gradient and surface current density distribution for themore » rails; TOPAZRG, a two-dimensional finite-element code that simultaneously analyzes thermal and electromagnetic diffusion in the rails; and LARGE, a code that predicts the performance of the entire EML system. Trhe NIKE2D code, developed at the Lawrence Livermore National Laboratory, is used to perform structural analyses of the rails. These codes have been instrumental in the design of the Lethality Test System (LTS) at Los Alamos, which has an ultimate goal of accelerating a 30-g projectile to a velocity of 15 km/s. The capabilities of the individual codes and the coupling of these codes to perform a comprehensive analysis is discussed in relation to the LTS design. Numerical predictions are compared with experimental data and presented for the LTS prototype tests.« less

Development of in vitro-in vivo correlation of parenteral naltrexone loaded polymeric microspheres.

PubMed

Andhariya, Janki V; Shen, Jie; Choi, Stephanie; Wang, Yan; Zou, Yuan; Burgess, Diane J

2017-06-10

Establishment of in vitro-in vivo correlations (IVIVCs) for parenteral polymeric microspheres has been very challenging, due to their complex multiphase release characteristics (which is affected by the nature of the drug) as well as the lack of compendial in vitro release testing methods. Previously, a Level A correlation has been established and validated for polymeric microspheres containing risperidone (a practically water insoluble small molecule drug). The objectives of the present study were: 1) to investigate whether a Level A IVIVC can be established for polymeric microspheres containing another small molecule drug with different solubility profiles compared to risperidone; and 2) to determine whether release characteristic differences (bi-phasic vs tri-phasic) between microspheres can affect the development and predictability of IVIVCs. Naltrexone was chosen as the model drug. Three compositionally equivalent formulations of naltrexone microspheres with different release characteristics were prepared using different manufacturing processes. The critical physicochemical properties (such as drug loading, particle size, porosity, and morphology) as well as the in vitro release characteristics of the prepared naltrexone microspheres and the reference-listed drug (Vivitrol®) were determined. The pharmacokinetics of the naltrexone microspheres were investigated using a rabbit model. The obtained pharmacokinetic profiles were deconvoluted using the Loo-Riegelman method, and compared with the in vitro release profiles of the naltrexone microspheres obtained using USP apparatus 4. Level A IVIVCs were established and validated for predictability. The results demonstrated that the developed USP 4 method was capable of detecting manufacturing process related performance changes, and most importantly, predicting the in vivo performance of naltrexone microspheres in the investigated animal model. A critical difference between naltrexone and risperidone loaded microspheres is their respective bi-phasic and tri-phasic release profiles with varying burst release and lag phase. These variations in release profiles affect the development of IVIVCs. Nevertheless, IVIVCs have been established and validated for polymeric microspheres with different release characteristics. Copyright © 2017. Published by Elsevier B.V.

Velocity measurements in a turbulent trailing vortex and their application to BWI noise prediction

NASA Technical Reports Server (NTRS)

Devenport, William J.; Glegg, Stewart A. L.

1991-01-01

The objectives were to observe the turbulence structure and spectral characteristics of the trailing vortex shed by a rectangular NACA 0012 wing over a range of conditions and to incorporate these observations into the blade-wake interaction (BWI) noise-prediction method of Glegg (1989). The following sections are presented: (1) measurements performed during the first year of this two year investigation; (2) presentation and discussion of a representative sample of the results; (3) implications for the BWI noise prediction method; and (4) re-evaluation of work planned for the second year.

Flight evaluation of an advanced technology light twin-engine airplane (ATLIT)

NASA Technical Reports Server (NTRS)

Holmes, B. J.

1977-01-01

Project organization and execution, airplane description and performance predictions, and the results of the flight evaluation of an advanced technology light twin engine airplane (ATLIT) are presented. The ATLIT is a Piper PA-34-200 Seneca I modified by the installation of new wings incorporating the GA(W)-1 (Whitcomb) airfoil, reduced wing area, roll control spoilers, and full span Fowler flaps. The conclusions for the ATLIT evaluation are based on complete stall and roll flight test results and partial performance test results. The Stalling and rolling characteristics met design expectations. Climb performance was penalized by extensive flow separation in the region of the wing body juncture. Cruise performance was found to be penalized by a large value of zero lift drag. Calculations showed that, with proper attention to construction details, the improvements in span efficiency and zero lift drag would permit the realization of the predicted increases in cruising and maximum rate of climb performance.

Anthropometric, physiological and performance characteristics of elite team-handball players.

PubMed

Chaouachi, Anis; Brughelli, Matt; Levin, Gregory; Boudhina, Nahla Ben Brahim; Cronin, John; Chamari, Karim

2009-01-15

The objective of this study was to provide anthropometric, physiological, and performance characteristics of an elite international handball team. Twenty-one elite handball players were tested and categorized according to their playing positions (goalkeepers, backs, pivots, and wings). Testing consisted of anthropometric and physiological measures of height, body mass, percentage body fat and endurance (VO(2max)), performance measures of speed (5, 10, and 30 m), strength (bench press and squat), unilateral and bilateral horizontal jumping ability, and a 5-jump horizontal test. Significant differences were found between player positions for some anthropometric characteristics (height and percentage body fat) but not for the physiological or performance characteristics. Strong correlations were noted between single leg horizontal jumping distances with 5-, 10-, and 30-m sprint times (r = 0.51-0.80; P < 0.01). The best predictors of sprint times were single leg horizontal jumping with the dominant leg and the distance measured for the 5-jump test, which when combined accounted for 72% of the common variance associated with sprint ability. In conclusion, performance abilities between positions in elite team-handball players appear to be very similar. Single leg horizontal jumping distance could be a specific standardized test for predicting sprinting ability in elite handball players.

Parameter transferability within homogeneous regions and comparisons with predictions from a priori parameters in the eastern United States

NASA Astrophysics Data System (ADS)

Chouaib, Wafa; Alila, Younes; Caldwell, Peter V.

2018-05-01

The need for predictions of flow time-series persists at ungauged catchments, motivating the research goals of our study. By means of the Sacramento model, this paper explores the use of parameter transfer within homogeneous regions of similar climate and flow characteristics and makes comparisons with predictions from a priori parameters. We assessed the performance using the Nash-Sutcliffe (NS), bias, mean monthly hydrograph and flow duration curve (FDC). The study was conducted on a large dataset of 73 catchments within the eastern US. Two approaches to the parameter transferability were developed and evaluated; (i) the within homogeneous region parameter transfer using one donor catchment specific to each region, (ii) the parameter transfer disregarding the geographical limits of homogeneous regions, where one donor catchment was common to all regions. Comparisons between both parameter transfers enabled to assess the gain in performance from the parameter regionalization and its respective constraints and limitations. The parameter transfer within homogeneous regions outperformed the a priori parameters and led to a decrease in bias and increase in efficiency reaching a median NS of 0.77 and a NS of 0.85 at individual catchments. The use of FDC revealed the effect of bias on the inaccuracy of prediction from parameter transfer. In one specific region, of mountainous and forested catchments, the prediction accuracy of the parameter transfer was less satisfactory and equivalent to a priori parameters. In this region, the parameter transfer from the outsider catchment provided the best performance; less-biased with smaller uncertainty in medium flow percentiles (40%-60%). The large disparity of energy conditions explained the lack of performance from parameter transfer in this region. Besides, the subsurface stormflow is predominant and there is a likelihood of lateral preferential flow, which according to its specific properties further explained the reduced efficiency. Testing the parameter transferability using criteria of similar climate and flow characteristics at ungauged catchments and comparisons with predictions from a priori parameters are a novelty. The ultimate limitations of both approaches are recognized and recommendations are made for future research.

Rotary engine performance computer program (RCEMAP and RCEMAPPC): User's guide

NASA Technical Reports Server (NTRS)

Bartrand, Timothy A.; Willis, Edward A.

1993-01-01

This report is a user's guide for a computer code that simulates the performance of several rotary combustion engine configurations. It is intended to assist prospective users in getting started with RCEMAP and/or RCEMAPPC. RCEMAP (Rotary Combustion Engine performance MAP generating code) is the mainframe version, while RCEMAPPC is a simplified subset designed for the personal computer, or PC, environment. Both versions are based on an open, zero-dimensional combustion system model for the prediction of instantaneous pressures, temperature, chemical composition and other in-chamber thermodynamic properties. Both versions predict overall engine performance and thermal characteristics, including bmep, bsfc, exhaust gas temperature, average material temperatures, and turbocharger operating conditions. Required inputs include engine geometry, materials, constants for use in the combustion heat release model, and turbomachinery maps. Illustrative examples and sample input files for both versions are included.

Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels.

PubMed

Baseer, Abdul; Weddell, Stephen J; Jones, Richard D

2017-07-01

Microsleeps are involuntary and brief instances of complete loss of responsiveness, typically of 0.5-15 s duration. They adversely affect performance in extended attention-driven jobs and can be fatal. Our aim was to predict microsleeps from 16 channel EEG signals. Two information theoretic concepts - pairwise joint entropy and mutual information - were independently used to continuously extract features from EEG signals. k-nearest neighbor (kNN) with k = 3 was used to calculate both joint entropy and mutual information. Highly correlated features were discarded and the rest were ranked using Fisher score followed by an average of 3-fold cross-validation area under the curve of the receiver operating characteristic (AUC ROC ). Leave-one-out method (LOOM) was performed to test the performance of microsleep prediction system on independent data. The best prediction for 0.25 s ahead was AUCROC, sensitivity, precision, geometric mean (GM), and φ of 0.93, 0.68, 0.33, 0.75, and 0.38 respectively with joint entropy using single linear discriminant analysis (LDA) classifier.

10 CFR 431.17 - Determination of efficiency.

Code of Federal Regulations, 2014 CFR

2014-01-01

... characteristics of that basic model, and (ii) Based on engineering or statistical analysis, computer simulation or... simulation or modeling, and other analytic evaluation of performance data on which the AEDM is based... applied. (iii) If requested by the Department, the manufacturer shall conduct simulations to predict the...

10 CFR 431.17 - Determination of efficiency.

Code of Federal Regulations, 2012 CFR

2012-01-01

... characteristics of that basic model, and (ii) Based on engineering or statistical analysis, computer simulation or... simulation or modeling, and other analytic evaluation of performance data on which the AEDM is based... applied. (iii) If requested by the Department, the manufacturer shall conduct simulations to predict the...

Radioisotopes: Today's Applications.

ERIC Educational Resources Information Center

Department of Energy, Washington, DC. Nuclear Energy Office.

Radioisotopes are useful because of their three unique characteristics: (1) radiation emission; (2) predictable radioactive lives; and (3) the same chemical properties as the nonradioactive atoms of that element. Researchers are able to "order" a radioisotope with the right radiation, half-life, and chemical property to perform a given task with…

Factors That Predict Pre-Service Teachers' Teaching Performance

ERIC Educational Resources Information Center

Corcoran, Roisin P.; O'Flaherty, Joanne

2018-01-01

Understanding the factors that contribute to an effective teacher has the potential to influence selection and preparation of pre-service teachers and may influence student outcomes. Prior research suggests a relationship between teacher characteristics (academic achievement, verbal ability, gender) and teacher effectiveness, however, these…

NIR technique in the classification of cotton leaf grade

USDA-ARS?s Scientific Manuscript database

Near infrared (NIR) spectroscopy, a useful technique due to the speed, ease of use, and adaptability to on-line or off-line implementation, has been applied to perform the qualitative classification and quantitative prediction of cotton quality characteristics, including trash index. One term to as...

Characteristics and determinants of endurance cycle ergometry and six-minute walk distance in patients with COPD.

PubMed

Andrianopoulos, Vasileios; Wagers, Scott S; Groenen, Miriam T J; Vanfleteren, Lowie E; Franssen, Frits M E; Smeenk, Frank W J M; Vogiatzis, Ioannis; Wouters, Emiel F M; Spruit, Martijn A

2014-05-31

Exercise tolerance can be assessed by the cycle endurance test (CET) and six-minute walk test (6MWT) in patients with Chronic Obstructive Pulmonary Disease (COPD). We sought to investigate the characteristics of functional exercise performance and determinants of the CET and 6MWT in a large clinical cohort of COPD patients. A dataset of 2053 COPD patients (43% female, age: 66.9 ± 9.5 years, FEV1% predicted: 48.2 ± 23.2) was analyzed retrospectively. Patients underwent, amongst others, respiratory function evaluation; medical tests and questionnaires, one maximal incremental cycle test where peak work rate was determined and two functional exercise tests: a CET at 75% of peak work rate and 6MWT. A stepwise multiple linear regression was used to assess determinants. On average, patients had impaired exercise tolerance (peak work rate: 56 ± 27% predicted, 6MWT: 69 ± 17% predicted). A total of 2002 patients had CET time of duration (CET-Tend) less than 20 min while only 51 (2.5%) of the patients achieved 20 min of CET-Tend . In former patients, the percent of predicted peak work rate achieved differed significantly between men (48 ± 21% predicted) and women (67 ± 31% predicted). In contrast, CET-Tend was longer in men (286 ± 174 s vs 250 ± 153 s, p < 0.001). Also, six minute walking distance (6MWD) was higher in men compared to women, both in absolute terms as in percent of predicted (443 m, 67%predicted vs 431 m, 72%predicted, p < 0.05). Gender was associated with the CET-Tend but BMI, FEV1 and FRC were related to the 6MWD highlighting the different determinants of exercise performance between CET and 6MWT. CET-Tend is a valuable outcome of CET as it is related to multiple clinical aspects of disease severity in COPD. Gender difference should temper the interpretation of CET.

Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL

PubMed Central

Li, Wen; Arasu, Vignesh; Newitt, David C.; Jones, Ella F.; Wilmes, Lisa; Gibbs, Jessica; Kornak, John; Joe, Bonnie N.; Esserman, Laura J.; Hylton, Nola M.

2016-01-01

Functional tumor volume (FTV) measurements by dynamic contrast-enhanced magnetic resonance imaging can predict treatment outcomes for women receiving neoadjuvant chemotherapy for breast cancer. Here, we explore whether the contrast thresholds used to define FTV could be adjusted by breast cancer subtype to improve predictive performance. Absolute FTV and percent change in FTV (ΔFTV) at sequential time-points during treatment were calculated and investigated as predictors of pathologic complete response at surgery. Early percent enhancement threshold (PEt) and signal enhancement ratio threshold (SERt) were varied. The predictive performance of resulting FTV predictors was evaluated using the area under the receiver operating characteristic curve. A total number of 116 patients were studied both as a full cohort and in the following groups defined by hormone receptor (HR) and HER2 receptor subtype: 45 HR+/HER2−, 39 HER2+, and 30 triple negatives. High AUCs were found at different ranges of PEt and SERt levels in different subtypes. Findings from this study suggest that the predictive performance to treatment response by MRI varies by contrast thresholds, and that pathologic complete response prediction may be improved through subtype-specific contrast enhancement thresholds. A validation study is underway with a larger patient population. PMID:28066808

What predicts performance during clinical psychology training?

PubMed

Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

2014-06-01

While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Longitudinal cross-sectional study using prospective and retrospective data. Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. © 2013 The Authors. British Journal of Clinical Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.

Player's success prediction in rugby union: From youth performance to senior level placing.

PubMed

Fontana, Federico Y; Colosio, Alessandro L; Da Lozzo, Giorgio; Pogliaghi, Silvia

2017-04-01

The study questioned if and to what extent specific anthropometric and functional characteristics measured in youth draft camps, can accurately predict subsequent career progression in rugby union. Original research. Anthropometric and functional characteristics of 531 male players (U16) were retrospectively analysed in relation to senior level team representation at age 21-24. Players were classified as International (Int: National team and international clubs) or National (Nat: 1st, 2nd and other divisions and dropout). Multivariate analysis of variance (one-way MANOVA) tested differences between Int and Nat, along a combination of anthropometric (body mass, height, body fat, fat-free mass) and functional variables (SJ, CMJ, t 15m , t 30m , VO 2max ). A discriminant function (DF) was determined to predict group assignment based on the linear combination of variables that best discriminate groups. Correct level assignment was expressed as % hit rate. A combination of anthropometric and functional characteristics reflects future level assignment (Int vs. Nat). Players' success can be accurately predicted (hit rate=81% and 77% for Int and Nat respectively) by a DF that combines anthropometric and functional variables as measured at ∼15 years of age, percent body fat and speed being the most influential predictors of group stratification. Within a group of 15 year-olds with exceptional physical characteristics, future players' success can be predicted using a linear combination of anthropometric and functional variables, among which a lower percent body fat and higher speed over a 15m sprint provide the most important predictors of the highest career success. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Biomarker-based risk prediction in the community.

PubMed

AbouEzzeddine, Omar F; McKie, Paul M; Scott, Christopher G; Rodeheffer, Richard J; Chen, Horng H; Michael Felker, G; Jaffe, Allan S; Burnett, John C; Redfield, Margaret M

2016-11-01

Guided by predictive characteristics of cardiovascular biomarkers, we explored the clinical implications of a simulated biomarker-guided heart failure (HF) and major adverse cardiovascular events (MACE) prevention strategy in the community. In a community cohort (n = 1824), the predictive characteristics for HF and MACE of galectin-3 (Gal-3), ST2, high-sensitivity cardiac troponin I (hscTnI), high-sensitivity C-reactive protein (hsCRP), N-terminal pro-brain natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP) were established. We performed number needed to screen (NNS) and treat (NNT) with the intervention analyses according to biomarker screening strategy and intervention efficacy in persons with at least one cardiovascular risk factor. In the entire cohort, for both HF and MACE, the predictive characteristics of NT-proBNP and hscTnI were superior to other biomarkers; alone, in a multimarker model, and adjusting for clinical risk factors. An NT-proBNP-guided preventative intervention with an intervention effect size (4-year hazard ratio for intervention in biomarker positive cohort) of ≤0.7 would reduce the global burden of HF by ≥20% and MACE by ≥15%. From this simulation, the NNS to prevent one HF event or MACE in 4 years would be ≤100 with a NNT to prevent one HF event of ≤20 and one MACE of ≤10. The predictive characteristics of NT-proBNP and hscTnI for HF or MACE in the community are superior to other biomarkers. Biomarker-guided preventative interventions with reasonable efficacy would compare favourably to established preventative interventions. This data provides a framework for biomarker selection which may inform design of biomarker-guided preventative intervention trials. © 2016 The Authors. European Journal of Heart Failure © 2016 European Society of Cardiology.

Change in organizational justice and job performance in Japanese employees: A prospective cohort study.

PubMed

Nakagawa, Yuko; Inoue, Akiomi; Kawakami, Norito; Tsuno, Kanami; Tomioka, Kimiko; Nakanishi, Mayuko; Mafune, Kosuke; Hiro, Hisanori

2015-01-01

The aim of the present study was to investigate the association of one-year change in organizational justice (i.e., procedural justice and interactional justice) with job performance in Japanese employees. This study surveyed 425 men and 683 women from a manufacturing company in Japan. Self-administered questionnaires, including the Organizational Justice Questionnaire (OJQ), the World Health Organization Health and Work Performance Questionnaire (WHO-HPQ) and the scales on demographic characteristics, were administered at baseline (August 2009). At one-year follow-up (August 2010), the OJQ and WHO-HPQ were used again to assess organizational justice and job performance. The change in organizational justice was measured by dichotomizing each OJQ subscale score by median at baseline and follow-up, and the participants were classified into four groups (i.e., stable low, adverse change, favorable change and stable high). Analysis of covariance (ANCOVA) was employed. After adjusting for demographic and occupational characteristics and job performance at baseline, the groups classified based on the change in procedural justice differed significantly in job performance at follow-up (ANCOVA: F [3, 1097]=4.35, p<0.01). Multiple comparisons revealed that the stable high procedural justice group had significantly higher job performance at follow-up compared with the stable low procedural justice group. The groups classified based on change in interactional justice did not differ significantly in job performance at follow-up (p>0.05). The present findings suggest that keeping the level of procedural justice high predicts higher levels of job performance, whereas the psychosocial factor of interactional justice is not so important for predicting job performance.

Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer.

PubMed

Hoogendoorn, Mark; Szolovits, Peter; Moons, Leon M G; Numans, Mattijs E

2016-05-01

Machine learning techniques can be used to extract predictive models for diseases from electronic medical records (EMRs). However, the nature of EMRs makes it difficult to apply off-the-shelf machine learning techniques while still exploiting the rich content of the EMRs. In this paper, we explore the usage of a range of natural language processing (NLP) techniques to extract valuable predictors from uncoded consultation notes and study whether they can help to improve predictive performance. We study a number of existing techniques for the extraction of predictors from the consultation notes, namely a bag of words based approach and topic modeling. In addition, we develop a dedicated technique to match the uncoded consultation notes with a medical ontology. We apply these techniques as an extension to an existing pipeline to extract predictors from EMRs. We evaluate them in the context of predictive modeling for colorectal cancer (CRC), a disease known to be difficult to diagnose before performing an endoscopy. Our results show that we are able to extract useful information from the consultation notes. The predictive performance of the ontology-based extraction method moves significantly beyond the benchmark of age and gender alone (area under the receiver operating characteristic curve (AUC) of 0.870 versus 0.831). We also observe more accurate predictive models by adding features derived from processing the consultation notes compared to solely using coded data (AUC of 0.896 versus 0.882) although the difference is not significant. The extracted features from the notes are shown be equally predictive (i.e. there is no significant difference in performance) compared to the coded data of the consultations. It is possible to extract useful predictors from uncoded consultation notes that improve predictive performance. Techniques linking text to concepts in medical ontologies to derive these predictors are shown to perform best for predicting CRC in our EMR dataset. Copyright © 2016 Elsevier B.V. All rights reserved.

User’s Guide for the VTRPE (Variable Terrain Radio Parabolic Equation) Computer Model

DTIC Science & Technology

1991-10-01

propagation effects and antenna characteristics in radar system performance calculations. the radar transmission equation is oiten employed. Fol- lowing Kerr.2...electromagnetic wave equations for the complex electric and magnetic radiation fields. The model accounts for the effects of nonuniform atmospheric refractivity...mission equation, that is used in the performance prediction and analysis of radar and communication systems. Optimized fast Fourier transform (FFT

Task Performance in Small Group Settings: The Role of Group Members' Self-Efficacy And Collective Efficacy and Group's Characteristics

ERIC Educational Resources Information Center

Khong, Jerrine Z. N.; Liem, Gregory Arief D.; Klassen, Robert M.

2017-01-01

The present study extends the literature by investigating the relative salience of self- and collective efficacy in predicting group performance among early adolescents in Indonesia. A total of 435 early adolescents (mean age 11.70 years, 53% female) were randomly assigned to groups of three to four and completed three group tasks (task 1:…

Experimental Study on the Seismic Performance of Recycled Concrete Brick Walls Embedded with Vertical Reinforcement.

PubMed

Cao, Wanlin; Zhang, Yongbo; Dong, Hongying; Zhou, Zhongyi; Qiao, Qiyun

2014-08-19

Recycled concrete brick (RCB) is manufactured by recycled aggregate processed from discarded concrete blocks arising from the demolishing of existing buildings. This paper presents research on the seismic performance of RCB masonry walls to assess the applicability of RCB for use in rural low-rise constructions. The seismic performance of a masonry wall is closely related to the vertical load applied to the wall. Thus, the compressive performance of RCB masonry was investigated firstly by constructing and testing eighteen RCB masonry compressive specimens with different mortar strengths. The load-bearing capacity, deformation and failure characteristic were analyzed, as well. Then, a quasi-static test was carried out to study the seismic behavior of RCB walls by eight RCB masonry walls subjected to an axial compressive load and a reversed cyclic lateral load. Based on the test results, equations for predicting the compressive strength of RCB masonry and the lateral ultimate strength of an RCB masonry wall were proposed. Experimental values were found to be in good agreement with the predicted values. Meanwhile, finite element analysis (FEA) and parametric analysis of the RCB walls were carried out using ABAQUS software. The elastic-plastic deformation characteristics and the lateral load-displacement relations were studied.

Experimental Study on the Seismic Performance of Recycled Concrete Brick Walls Embedded with Vertical Reinforcement

PubMed Central

Cao, Wanlin; Zhang, Yongbo; Dong, Hongying; Zhou, Zhongyi; Qiao, Qiyun

2014-01-01

Recycled concrete brick (RCB) is manufactured by recycled aggregate processed from discarded concrete blocks arising from the demolishing of existing buildings. This paper presents research on the seismic performance of RCB masonry walls to assess the applicability of RCB for use in rural low-rise constructions. The seismic performance of a masonry wall is closely related to the vertical load applied to the wall. Thus, the compressive performance of RCB masonry was investigated firstly by constructing and testing eighteen RCB masonry compressive specimens with different mortar strengths. The load-bearing capacity, deformation and failure characteristic were analyzed, as well. Then, a quasi-static test was carried out to study the seismic behavior of RCB walls by eight RCB masonry walls subjected to an axial compressive load and a reversed cyclic lateral load. Based on the test results, equations for predicting the compressive strength of RCB masonry and the lateral ultimate strength of an RCB masonry wall were proposed. Experimental values were found to be in good agreement with the predicted values. Meanwhile, finite element analysis (FEA) and parametric analysis of the RCB walls were carried out using ABAQUS software. The elastic-plastic deformation characteristics and the lateral load-displacement relations were studied. PMID:28788170

The porcupine caribou herd

USGS Publications Warehouse

Griffith, Brad; Douglas, David C.; Walsh, Noreen E.; Young, Donald D.; McCabe, Thomas R.; Russell, Donald E.; White, Robert G.; Cameron, Raymond D.; Whitten, Kenneth R.; Douglas, David C.; Reynolds, Patricia E.; Rhode, E.B.

2002-01-01

Documentation of the natural range of variation in ecological, life history, and physiological characteristics of caribou (Rangifer tarandus) of the Porcupine caribou herd is a necessary base for detecting or predicting any potential effects of industrial development on the performance (e.g., distribution, demography, weight-gain of individuals) of the herd. To demonstrate an effect of development, post-development performance must differ from pre-development performance while accounting for any natural environmental trends.We had 2 working hypotheses for our investigations: 1) performance of the Porcupine caribou herd was associated with environmental patterns and habitat quality, and 2) access to important habitats was a key influence on demography.We sought to document the range of natural variation in habitat conditions, herd size, demography (defined here as survival and reproduction), sources and magnitude of mortality, distribution, habitat use, and weight gain and loss, and to develop an understanding of the interactions among these characteristics of the herd.In addition, we investigated ways that we could use this background information, combined with auxiliary information from the adjacent Central Arctic caribou herd, to predict the direction and magnitude of any potential effects of industrial oil development in the 1002 Area of the Arctic National Wildlife Refuge on Porcupine caribou herd calf survival on the herd's calving grounds during June.

Prediction models for the risk of spontaneous preterm birth based on maternal characteristics: a systematic review and independent external validation.

PubMed

Meertens, Linda J E; van Montfort, Pim; Scheepers, Hubertina C J; van Kuijk, Sander M J; Aardenburg, Robert; Langenveld, Josje; van Dooren, Ivo M A; Zwaan, Iris M; Spaanderman, Marc E A; Smits, Luc J M

2018-04-17

Prediction models may contribute to personalized risk-based management of women at high risk of spontaneous preterm delivery. Although prediction models are published frequently, often with promising results, external validation generally is lacking. We performed a systematic review of prediction models for the risk of spontaneous preterm birth based on routine clinical parameters. Additionally, we externally validated and evaluated the clinical potential of the models. Prediction models based on routinely collected maternal parameters obtainable during first 16 weeks of gestation were eligible for selection. Risk of bias was assessed according to the CHARMS guidelines. We validated the selected models in a Dutch multicenter prospective cohort study comprising 2614 unselected pregnant women. Information on predictors was obtained by a web-based questionnaire. Predictive performance of the models was quantified by the area under the receiver operating characteristic curve (AUC) and calibration plots for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation. Clinical value was evaluated by means of decision curve analysis and calculating classification accuracy for different risk thresholds. Four studies describing five prediction models fulfilled the eligibility criteria. Risk of bias assessment revealed a moderate to high risk of bias in three studies. The AUC of the models ranged from 0.54 to 0.67 and from 0.56 to 0.70 for the outcomes spontaneous preterm birth <37 weeks and <34 weeks of gestation, respectively. A subanalysis showed that the models discriminated poorly (AUC 0.51-0.56) for nulliparous women. Although we recalibrated the models, two models retained evidence of overfitting. The decision curve analysis showed low clinical benefit for the best performing models. This review revealed several reporting and methodological shortcomings of published prediction models for spontaneous preterm birth. Our external validation study indicated that none of the models had the ability to predict spontaneous preterm birth adequately in our population. Further improvement of prediction models, using recent knowledge about both model development and potential risk factors, is necessary to provide an added value in personalized risk assessment of spontaneous preterm birth. © 2018 The Authors Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

Thermodynamic Analysis of Dual-Mode Scramjet Engine Operation and Performance

NASA Technical Reports Server (NTRS)

Riggins, David; Tacket, Regan; Taylor, Trent; Auslender, Aaron

2006-01-01

Recent analytical advances in understanding the performance continuum (the thermodynamic spectrum) for air-breathing engines based on fundamental second-law considerations have clarified scramjet and ramjet operation, performance, and characteristics. Second-law based analysis is extended specifically in this work to clarify and describe the performance characteristics for dual-mode scramjet operation in the mid-speed range of flight Mach 4 to 7. This is done by a fundamental investigation of the complex but predictable interplay between heat release and irreversibilities in such an engine; results demonstrate the flow and performance character of the dual mode regime and of dual mode transition behavior. Both analytical and computational (multi-dimensional CFD) studies of sample dual-mode flow-fields are performed in order to demonstrate the second-law capability and performance and operability issues. The impact of the dual-mode regime is found to be characterized by decreasing overall irreversibility with increasing heat release, within the operability limits of the system.

A Flight Investigation of the STOL Characteristics of an Augmented Jet Flap STOL Research Aircraft

NASA Technical Reports Server (NTRS)

Quigley, H. C.; Innis, R. C.; Grossmith, S.

1974-01-01

The flight test program objectives are: (1) To determine the in-flight aerodynamic, performance, and handling qualities of a jet STOL aircraft incorporating the augmented jet flap concept; (2) to compare the results obtained in flight with characteristics predicted from wind tunnel and simulator test results; (3) to contribute to the development of criteria for design and operation of jet STOL transport aircraft; and (4) to provide a jet STOL transport aircraft for STOL systems research and development. Results obtained during the first 8 months of proof-of-concept flight testing of the aircraft in STOL configurations are reported. Included are a brief description of the aircraft, fan-jet engines, and systems; a discussion of the aerodynamic, stability and control, and STOL performance; and pilot opinion of the handling qualities and operational characteristics.

Class modality, student characteristics, and performance in a community college introductory STEM course

NASA Astrophysics Data System (ADS)

Fogle, Thomas Ty

Research on introductory STEM course performance has indicated that student characteristics (age, ethnicity and gender) and Grade Point Average (G.P.A.) can be predictive of student performance, and by implication, a correlation among these factors can help determine course design interventions to help certain types of students perform well in introductory STEM courses. The basis of this study was a community college Visual Basic programming course taught in both online and hybrid format. Beginning students in this course represented a diverse population residing in a large, mid-western, city and surrounding communities. Many of these students were defined as "at-Risk" or "non-traditional, which generally means any combination of socio-economic, cultural, family and employment factors that indicate a student is non-traditional. Research has shown these students struggle academically in technologically dense STEM courses, and may require student services and support to achieve their individual performance goals. The overall number in the study range was 392 distance students and 287 blended course students. The main question of this research was to determine to what extent student characteristics in a community college context, and previous success, as measured in overall G.P.A., were related to course performance in an introductory Visual Basic programming (STEM) course; and, whether or not a combination of these factors and course modality was predictive of success. The study employed a quantitative, quasi-experimental design to assess whether students' course performance was linked to course modality, student characteristics and overall G.P.A. The results indicated that the only predictor of student performance was overall G.P.A. Despite the research analyzed in Chapter 2, there was no statistically significant relationship to modality, age, ethnicity, or gender to performance in the course. Cognitive load is significant in a computer programming course and it was theorized that would be expanded in an online context. However, the results of the analysis showed that course modality did not affect the chances of students performing well. Internal validity constraints may have contributed to the results, as the course is highly controlled and modularized in both online and hybrid format, and taught by few instructors, all of whom are available for face to face problem solving for both online and hybrid students.

Use of the Interview in Resident Candidate Selection: A Review of the Literature

PubMed Central

Stephenson-Famy, Alyssa; Houmard, Brenda S.; Oberoi, Sidharth; Manyak, Anton; Chiang, Seine; Kim, Sara

2015-01-01

Background Although the resident candidate interview is costly and time-consuming for both applicants and programs, it is considered critically important for resident selection. Noncognitive attributes, including communication skills and professionalism, can be assessed by the personal interview. Objective We conducted a review of the literature on the residency interview to identify the interview characteristics used for resident selection and to ascertain to what extent the interview yields information that predicts future performance. Methods We searched PubMed and Scopus using the following search terms: residency, internship, interview, selection, and performance. We extracted information on characteristics of the interview process, including type of interview format, measures taken to minimize bias by interviewers, and testing of other clinical/surgical skills. Results We identified 104 studies that pertained to the resident selection interview, with highly varied interview formats and assessment tools. A positive correlation was demonstrated between a medical school academic record and the interview, especially for unblinded interview formats. A total of 34 studies attempted to correlate interview score with performance in residency, with mixed results. We also identified a number of studies that included personality testing, clinical skills testing, or surgical skills testing. Conclusions Our review identified a wide variety of approaches to the selection interview and a range of factors that have been studied to assess its effectiveness. More research needs to be done not only to address and ascertain appropriate interview formats that predict positive performance in residency, but also to determine interview factors that can predict both residents' “success” and program attrition. PMID:26692964

[Predictors of fighting spirit or helplessness/hopelessness in people with cancer].

PubMed

Oh, Pok-Ja; Lee, Yeon-Joo

2008-04-01

This study was done to identify predictors of the fighting spirit or helplessness/hopelessness in the patients' mental adjustment to cancer. Cancer patients' characteristics like performance status, metastasis and duration of diagnosis with demographic factors, spiritual support and social support were used as predictors of a fighting spirit or helplessness/hopelessness. A total of 124 ambulatory cancer patients completed the Mental Adjustment to Cancer (MAC) scale and responded in a structured instrument about their characteristics, spiritual and social support. The results of multiple regression analysis revealed that confidence in the supporter (R(2)=.114, p=.000), duration of cancer diagnosis (R(2)=.041, p=.000) and faith (R(2)=.030, p=.000) were predictive of a fighting spirit (R(2)=.185, p=.000); whereas, education (R(2)=.074, p=.001), performance status (R(2)=.055, p=.000), satisfaction with social support (R(2)=.046, p=.000), and metastasis (R(2)=.037, p=.000) were predictive of helplessness/hopelessness (R(2)=.202, p=.000). Social support, spiritual support and disease related factors like metastasis, performance status, and duration of cancer diagnosis need to be considered in a psychosocial nursing intervention for a fighting spirit or helplessness/hopelessness.

Robust PLS approach for KPI-related prediction and diagnosis against outliers and missing data

NASA Astrophysics Data System (ADS)

Yin, Shen; Wang, Guang; Yang, Xu

2014-07-01

In practical industrial applications, the key performance indicator (KPI)-related prediction and diagnosis are quite important for the product quality and economic benefits. To meet these requirements, many advanced prediction and monitoring approaches have been developed which can be classified into model-based or data-driven techniques. Among these approaches, partial least squares (PLS) is one of the most popular data-driven methods due to its simplicity and easy implementation in large-scale industrial process. As PLS is totally based on the measured process data, the characteristics of the process data are critical for the success of PLS. Outliers and missing values are two common characteristics of the measured data which can severely affect the effectiveness of PLS. To ensure the applicability of PLS in practical industrial applications, this paper introduces a robust version of PLS to deal with outliers and missing values, simultaneously. The effectiveness of the proposed method is finally demonstrated by the application results of the KPI-related prediction and diagnosis on an industrial benchmark of Tennessee Eastman process.

A Proposed Method to Predict Preterm Birth Using Clinical Data, Standard Maternal Serum Screening, and Cholesterol

PubMed Central

ALLEMAN, Brandon W.; SMITH, Amanda R.; BYERS, Heather M.; BEDELL, Bruce; RYCKMAN, Kelli K.; MURRAY, Jeffrey C.; BOROWSKI, Kristi S.

2013-01-01

Objective To create a predictive model for preterm birth (PTB) from available clinical data and serum analytes. Study Design Serum analytes, routine pregnancy screening plus cholesterol and corresponding health information were linked to birth certificate data for a cohort of 2699 Iowa women with serum sampled in the first and second trimester. Stepwise logistic regression was used to select the best predictive model for PTB. Results Serum screening markers remained significant predictors of PTB even after controlling for maternal characteristics. The best predictive model included maternal characteristics, first trimester total cholesterol (TC), TC change between trimesters and second trimester alpha-fetoprotein and inhibin A. The model showed better discriminatory ability than PTB history alone and performed similarly in subgroups of women without past PTB. Conclusions Using clinical and serum screening data a potentially useful predictor of PTB was constructed. Validation and replication in other populations, and incorporation of other measures that identify PTB risk, like cervical length, can be a step towards identifying additional women who may benefit from new or currently available interventions. PMID:23500456

Orbiter Landing Loads Math Model Description and Correlation with ALT Flight Data

NASA Technical Reports Server (NTRS)

Hamilton, D. A.; Schliesing, J. A.; Zupp, G. A., Jr.

1980-01-01

Results of the space shuttle approach and landing test are examined in order to assess landing gear characteristics and performance and verify landing dynamic analyses. The landing gears were instrumented with load-calibrated strain gages, a wheel-speed sensor, and strut stroke measurement devices. The mathematical procedure used in predicting the shuttle touchdown loads and dynamics is presented together with the comparisons between measured flight data and the analytical predictions. Conclusions from these data are also presented.

Suitability Screening Test for Marine Corps Air Traffic Controllers Phase 3: Non-cognitive Test Validation and Cognitive Test Prototype

DTIC Science & Technology

2014-06-01

Individuals possess a variety of abilities, preferences , interests, and personal characteristics that should be useful in predicting who will be best suited... traits . Through both concurrent and predictive validity designs, scores on the NCAPS were correlated with measures of schoolhouse academic performance and...other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a

Prediction of overall and blade-element performance for axial-flow pump configurations

NASA Technical Reports Server (NTRS)

Serovy, G. K.; Kavanagh, P.; Okiishi, T. H.; Miller, M. J.

1973-01-01

A method and a digital computer program for prediction of the distributions of fluid velocity and properties in axial flow pump configurations are described and evaluated. The method uses the blade-element flow model and an iterative numerical solution of the radial equilbrium and continuity conditions. Correlated experimental results are used to generate alternative methods for estimating blade-element turning and loss characteristics. Detailed descriptions of the computer program are included, with example input and typical computed results.

Web-based thyroid imaging reporting and data system: Malignancy risk of atypia of undetermined significance or follicular lesion of undetermined significance thyroid nodules calculated by a combination of ultrasonography features and biopsy results.

PubMed

Choi, Young Jun; Baek, Jung Hwan; Shin, Jung Hee; Shim, Woo Hyun; Kim, Seon-Ok; Lee, Won-Hong; Song, Dong Eun; Kim, Tae Yong; Chung, Ki-Wook; Lee, Jeong Hyun

2018-05-13

The purpose of this study was to construct a web-based predictive model using ultrasound characteristics and subcategorized biopsy results for thyroid nodules of atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) to stratify the risk of malignancy. Data included 672 thyroid nodules from 656 patients from a historical cohort. We analyzed ultrasound images of thyroid nodules and biopsy results according to nuclear atypia and architectural atypia. Multivariate logistic regression analysis was performed to predict whether nodules were diagnosed as malignant or benign. The ultrasound features, including spiculated margin, marked hypoechogenicity, calcifications, biopsy results, and cytologic atypia, showed significant differences between groups. A 13-point risk scoring system was developed, and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the development and validation sets were 0.837 and 0.830, respectively (http://www.gap.kr/thyroidnodule_b3.php). We devised a web-based predictive model using the combined information of ultrasound characteristics and biopsy results for AUS/FLUS thyroid nodules to stratify the malignant risk. © 2018 Wiley Periodicals, Inc.

Political Alienation in Adolescence: Associations with Parental Role Models, Parenting Styles, and Classroom Climate

ERIC Educational Resources Information Center

Gniewosz, Burkhard; Noack, Peter; Buhl, Monika

2009-01-01

The present study examined how parental political attitudes, parenting styles, and classroom characteristics predict adolescents' political alienation, as feelings about the individual's ability to affect the political system's performance at the individual level. Participants were 463 families that included mothers, fathers, and their adolescent…

Prediction of Child Performance on a Parent-Child Behavioral Approach Test with Animal Phobic Children

ERIC Educational Resources Information Center

Ollendick, Thomas H.; Lewis, Krystal M.; Cowart, Maria J. W.; Davis, Thompson, III

2012-01-01

A host of factors including genetic influences, temperament characteristics, learning experiences, information processing biases, parental psychopathology, and specific parenting practices have been hypothesized to contribute to the development and expression of children's phobias. In the present study, the authors focused on parental…

Problems and Methods of Teaching and Assessment of Students on Day Release in Higher Education.

ERIC Educational Resources Information Center

Trotman-Dickenson, Danusia

1980-01-01

Part-time students' characteristics and teaching and testing preferences were correlated with performance on a standardized economics exam. Learning modules are described. Methods of pinpointing student weaknesses and predicting students' final results are discussed as they relate to other subjects. (MSE)

Assessing Readiness for Online Education--Research Models for Identifying Students at Risk

ERIC Educational Resources Information Center

Wladis, Claire; Conway, Katherine M.; Hachey, Alyse C.

2016-01-01

This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed…

Trajectories of sleep disturbance and daytime sleepiness in women before and after surgery for breast cancer.

PubMed

Van Onselen, Christina; Paul, Steven M; Lee, Kathryn; Dunn, Laura; Aouizerat, Bradley E; West, Claudia; Dodd, Marylin; Cooper, Bruce; Miaskowski, Christine

2013-02-01

Sleep disturbance is a problem for oncology patients. To evaluate how sleep disturbance and daytime sleepiness (DS) changed from before to six months following surgery and whether certain characteristics predicted initial levels and/or the trajectories of these parameters. Patients (n=396) were enrolled prior to surgery and completed monthly assessments for six months following surgery. The General Sleep Disturbance Scale was used to assess sleep disturbance and DS. Using hierarchical linear modeling, demographic, clinical, symptom, and psychosocial adjustment characteristics were evaluated as predictors of initial levels and trajectories of sleep disturbance and DS. All seven General Sleep Disturbance Scale scores were above the cutoff for clinically meaningful levels of sleep disturbance. Lower performance status; higher comorbidity, attentional fatigue, and physical fatigue; and more severe hot flashes predicted higher preoperative levels of sleep disturbance. Higher levels of education predicted higher sleep disturbance scores over time. Higher levels of depressive symptoms predicted higher preoperative levels of sleep disturbance, which declined over time. Lower performance status; higher body mass index; higher fear of future diagnostic tests; not having had sentinel lymph node biopsy; having had an axillary lymph node dissection; and higher depression, physical fatigue, and attentional fatigue predicted higher DS prior to surgery. Higher levels of education, not working for pay, and not having undergone neo-adjuvant chemotherapy predicted higher DS scores over time. Sleep disturbance is a persistent problem for patients with breast cancer. The effects of interventions that can address modifiable risk factors need to be evaluated. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

Assessing the performance of quantitative image features on early stage prediction of treatment effectiveness for ovary cancer patients: a preliminary investigation

NASA Astrophysics Data System (ADS)

Zargari, Abolfazl; Du, Yue; Thai, Theresa C.; Gunderson, Camille C.; Moore, Kathleen; Mannel, Robert S.; Liu, Hong; Zheng, Bin; Qiu, Yuchen

2018-02-01

The objective of this study is to investigate the performance of global and local features to better estimate the characteristics of highly heterogeneous metastatic tumours, for accurately predicting the treatment effectiveness of the advanced stage ovarian cancer patients. In order to achieve this , a quantitative image analysis scheme was developed to estimate a total of 103 features from three different groups including shape and density, Wavelet, and Gray Level Difference Method (GLDM) features. Shape and density features are global features, which are directly applied on the entire target image; wavelet and GLDM features are local features, which are applied on the divided blocks of the target image. To assess the performance, the new scheme was applied on a retrospective dataset containing 120 recurrent and high grade ovary cancer patients. The results indicate that the three best performed features are skewness, root-mean-square (rms) and mean of local GLDM texture, indicating the importance of integrating local features. In addition, the averaged predicting performance are comparable among the three different categories. This investigation concluded that the local features contains at least as copious tumour heterogeneity information as the global features, which may be meaningful on improving the predicting performance of the quantitative image markers for the diagnosis and prognosis of ovary cancer patients.

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.

Evaluation of MELD score and Maddrey discriminant function for mortality prediction in patients with alcoholic hepatitis.

PubMed

Monsanto, Pedro; Almeida, Nuno; Lrias, Clotilde; Pina, Jos Eduardo; Sofia, Carlos

2013-01-01

Maddrey discriminant function (DF) is the traditional model for evaluating the severity and prognosis in alcoholic hepatitis (AH). However, MELD has also been used for this purpose. We aimed to determine the predictive parameters and compare the ability of Maddrey DF and MELD to predict short-term mortality in patients with AH. Retrospective study of 45 patients admitted in our department with AH between 2000 and 2010. Demographic, clinical and laboratory parameters were collected. MELD and Maddrey DF were calculated on admission. Short-term mortality was assessed at 30 and 90 days. Student t-test, χ2 test, univariate analysis, logistic regression and receiver operating characteristic curves were performed. Thirty-day and 90-day mortality was 27% and 42%, respectively. In multivariate analysis, Maddrey DF was the only independent predictor of mortality for these two periods. Receiver operating characteristic curves for Maddrey DF revealed an excellent discriminatory ability to predict 30-day and 90-day mortality for a Maddrey DF greater than 65 and 60, respectively. Discriminatory ability to predict 30-day and 90-day mortality for MELD was low. AH remains associated with a high short-term mortality. Maddrey DF is a more valuable model than MELD to predict short-term mortality in patients with AH.

Exercise-induced oxygen desaturation in COPD patients without resting hypoxemia.

PubMed

Andrianopoulos, Vasileios; Franssen, Frits M E; Peeters, Jos P I; Ubachs, Tim J A; Bukari, Halah; Groenen, Miriam; Burtin, Chris; Vogiatzis, Ioannis; Wouters, Emiel F M; Spruit, Martijn A

2014-01-01

Exercise-induced oxygen desaturation (EID) is associated with increased risk of mortality in chronic obstructive pulmonary disease (COPD). Several screening tests have been proposed to predict EID, including FEV1, DLCO and baseline-SpO2. We aimed to validate a proposed cut-off of baseline-SpO2 ≤95% as simple screening procedure to predict EID during six-minute walk test (6MWT). In addition, we studied the prevalence and characteristics of patients exhibited EID to SpO2nadir ≤88%. 402 non-hypoxemic COPD patients performed 6MWT. Sensitivity and specificity of baseline SpO2 ≤95% as a cut-off to predict EID and determinants of EID were investigated. 158 patients (39%) exhibited EID. The sensitivity of baseline-SpO2 ≤95% to predict EID was 81.0%, specificity 49.2%, positive and negative predictive values were 50.8% and 80.0%, respectively. In a multivariate model, DLCO <50%, FEV1 <45%, PaO2 <10kPa, baseline-SpO2 <95%, and female sex were the strongest determinants of EID. Baseline oxygen saturation solely is inaccurate to predict EID. A combination of clinical characteristics (DLCO, FEV1, PaO2, baseline-SpO2, sex) increases the odds for EID in COPD. Copyright © 2013 Elsevier B.V. All rights reserved.

Forensic DNA Phenotyping: Predicting human appearance from crime scene material for investigative purposes.

PubMed

Kayser, Manfred

2015-09-01

Forensic DNA Phenotyping refers to the prediction of appearance traits of unknown sample donors, or unknown deceased (missing) persons, directly from biological materials found at the scene. "Biological witness" outcomes of Forensic DNA Phenotyping can provide investigative leads to trace unknown persons, who are unidentifiable with current comparative DNA profiling. This intelligence application of DNA marks a substantially different forensic use of genetic material rather than that of current DNA profiling presented in the courtroom. Currently, group-specific pigmentation traits are already predictable from DNA with reasonably high accuracies, while several other externally visible characteristics are under genetic investigation. Until individual-specific appearance becomes accurately predictable from DNA, conventional DNA profiling needs to be performed subsequent to appearance DNA prediction. Notably, and where Forensic DNA Phenotyping shows great promise, this is on a (much) smaller group of potential suspects, who match the appearance characteristics DNA-predicted from the crime scene stain or from the deceased person's remains. Provided sufficient funding being made available, future research to better understand the genetic basis of human appearance will expectedly lead to a substantially more detailed description of an unknown person's appearance from DNA, delivering increased value for police investigations in criminal and missing person cases involving unknowns. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Characterizing ceramics and the interfacial adhesion to resin: I - The relationship of microstructure, composition, properties and fractography.

PubMed

Della Bona, Alvaro

2005-03-01

The appeal of ceramics as structural dental materials is based on their light weight, high hardness values, chemical inertness, and anticipated unique tribological characteristics. A major goal of current ceramic research and development is to produce tough, strong ceramics that can provide reliable performance in dental applications. Quantifying microstructural parameters is important to develop structure/property relationships. Quantitative microstructural analysis provides an association among the constitution, physical properties, and structural characteristics of materials. Structural reliability of dental ceramics is a major factor in the clinical success of ceramic restorations. Complex stress distributions are present in most practical conditions and strength data alone cannot be directly extrapolated to predict structural performance.

Automated Clinical Assessment from Smart home-based Behavior Data

PubMed Central

Dawadi, Prafulla Nath; Cook, Diane Joyce; Schmitter-Edgecombe, Maureen

2016-01-01

Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and well-being assessment. In this paper, we examine the actual benefits of smart home-based analysis by monitoring daily behaviour in the home and predicting standard clinical assessment scores of the residents. To accomplish this goal, we propose a Clinical Assessment using Activity Behavior (CAAB) approach to model a smart home resident’s daily behavior and predict the corresponding standard clinical assessment scores. CAAB uses statistical features that describe characteristics of a resident’s daily activity performance to train machine learning algorithms that predict the clinical assessment scores. We evaluate the performance of CAAB utilizing smart home sensor data collected from 18 smart homes over two years using prediction and classification-based experiments. In the prediction-based experiments, we obtain a statistically significant correlation (r = 0.72) between CAAB-predicted and clinician-provided cognitive assessment scores and a statistically significant correlation (r = 0.45) between CAAB-predicted and clinician-provided mobility scores. Similarly, for the classification-based experiments, we find CAAB has a classification accuracy of 72% while classifying cognitive assessment scores and 76% while classifying mobility scores. These prediction and classification results suggest that it is feasible to predict standard clinical scores using smart home sensor data and learning-based data analysis. PMID:26292348

Successful prediction and performance in waterflooding Wesson Hogg Sand Unit, Ouachita County, Arkansas

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

Clanton, H.W.

1966-01-01

By unitization and waterflooding, the Hogg Sand reservoir will increase ultimate recovery by 21,500,000 bbl. The predicted ultimate recovery of 1,103 bbl per acre-ft is considered well above average for waterflood projects. Predicted reservoir performance has closely paralleled actual performance in many areas of investigation, viz., recovery in bbl per acre-ft, flood pattern, water percent at depletion, and attaining a reservoir pressure which would sustain production by natural flow. A departure from the generally accepted practices utilized in waterflooding has not been a detriment in successfully flooding the Hogg Sand reservoir. The major factors contributing to the high degree ofmore » success can be found in the excellent reservoir characteristics. Operating costs of $0.2429 per bbl, including amortization, is approximately 1/4 of that normally expected in waterfloods. Remaining oil after flooding is indicated to be 49% of the oil in place and clearly indicates a need for concentrated efforts in the field of tertiary recovery.« less

Comparison of two procedures for predicting rocket engine nozzle performance

NASA Technical Reports Server (NTRS)

Davidian, Kenneth J.

1987-01-01

Two nozzle performance prediction procedures which are based on the standardized JANNAF methodology are presented and compared for four rocket engine nozzles. The first procedure required operator intercedence to transfer data between the individual performance programs. The second procedure is more automated in that all necessary programs are collected into a single computer code, thereby eliminating the need for data reformatting. Results from both procedures show similar trends but quantitative differences. Agreement was best in the predictions of specific impulse and local skin friction coefficient. Other compared quantities include characteristic velocity, thrust coefficient, thrust decrement, boundary layer displacement thickness, momentum thickness, and heat loss rate to the wall. Effects of wall temperature profile used as an input to the programs was investigated by running three wall temperature profiles. It was found that this change greatly affected the boundary layer displacement thickness and heat loss to the wall. The other quantities, however, were not drastically affected by the wall temperature profile change.

Fire danger index efficiency as a function of fuel moisture and fire behavior.

PubMed

Torres, Fillipe Tamiozzo Pereira; Romeiro, Joyce Machado Nunes; Santos, Ana Carolina de Albuquerque; de Oliveira Neto, Ricardo Rodrigues; Lima, Gumercindo Souza; Zanuncio, José Cola

2018-08-01

Assessment of the performance of forest fire hazard indices is important for prevention and management strategies, such as planning prescribed burnings, public notifications and firefighting resource allocation. The objective of this study was to evaluate the performance of fire hazard indices considering fire behavior variables and susceptibility expressed by the moisture of combustible material. Controlled burns were carried out at different times and information related to meteorological conditions, characteristics of combustible material and fire behavior variables were recorded. All variables analyzed (fire behavior and fuel moisture content) can be explained by the prediction indices. The Brazilian EVAP/P showed the best performance, both at predicting moisture content of the fuel material and fire behavior variables, and the Canadian system showed the best performance to predicting the rate of spread. The coherence of the correlations between the indices and the variables analyzed makes the methodology, which can be applied anywhere, important for decision-making in regions with no records or with only unreliable forest fire data. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling of rolling element bearing mechanics

NASA Technical Reports Server (NTRS)

Greenhill, L. M.

1991-01-01

Roller element bearings provide the primary mechanical interface between rotating and nonrotating components in the high performance turbomachinery of the Space Shuttle Main Engine (SSME). Knowledge of bearing behavior under various loading and environmental conditions is essential to predicting and understanding the overall behavior of turbopumps, including rotordynamic stability, critical speeds and bearing life. The objective is to develop mathematical models and computer programs to describe the mechanical behavior of ball and cylinder roller bearings under the loading and environmental conditions encountered in the SSME and future high performance rocket engines. This includes characteristics such as nonlinear load/motion relationships, stiffness and damping, rolling element loads for life prediction, and roller and cage stability.

Methods for utilizing maximum power from a solar array

NASA Technical Reports Server (NTRS)

Decker, D. K.

1972-01-01

A preliminary study of maximum power utilization methods was performed for an outer planet spacecraft using an ion thruster propulsion system and a solar array as the primary energy source. The problems which arise from operating the array at or near the maximum power point of its 1-V characteristic are discussed. Two closed loop system configurations which use extremum regulators to track the array's maximum power point are presented. Three open loop systems are presented that either: (1) measure the maximum power of each array section and compute the total array power, (2) utilize a reference array to predict the characteristics of the solar array, or (3) utilize impedance measurements to predict the maximum power utilization. The advantages and disadvantages of each system are discussed and recommendations for further development are made.

Validation of a Predictive Scoring System for Deep Sternal Wound Infection after Bilateral Internal Thoracic Artery Grafting in a Cohort of French Patients.

PubMed

Perrotti, Andrea; Gatti, Giuseppe; Dorigo, Enrica; Sinagra, Gianfranco; Pappalardo, Aniello; Chocron, Sidney

The Gatti score is a weighted scoring system based on risk factors for deep sternal wound infection (DSWI) that was created in an Italian center to predict DSWI risk after bilateral internal thoracic artery (BITA) grafting. No external evaluation based on validation samples derived from other surgical centers has been performed. The aim of this study is to perform this validation. During 2015, BITA grafts were used as skeletonized conduits in all 255 consecutive patients with multi-vessel coronary disease who underwent isolated coronary bypass surgery at the Department of Thoracic and Cardio-Vascular Surgery, University Hospital Jean Minjoz, Besançon, France. Baseline characteristics, operative data, and immediate outcomes of every patient were collected prospectively. A DSWI risk score was assigned to each patient pre-operatively. The discrimination power of both models, pre-operative and combined, of the Gatti score was assessed with the calculation of the area under the receiver operating characteristic curve. Fourteen (5.5%) patients had DSWI. Major differences both as the baseline characteristics of patients and surgical techniques were found between this series and the original series from which the Gatti score was derived. The area under the receiver operating characteristic curve was 0.78 (95% confidence interval: 0.64-0.92) for the pre-operative model and 0.84 (95% confidence interval: 0.69-0.98) for the combined model. The Gatti score has proven to be effective even in a cohort of French patients despite major differences from the original Italian series. Multi-center validation studies must be performed before introducing the score into clinical practice.

Clinical usefulness of the clock drawing test applying rasch analysis in predicting of cognitive impairment.

PubMed

Yoo, Doo Han; Lee, Jae Shin

2016-07-01

[Purpose] This study examined the clinical usefulness of the clock drawing test applying Rasch analysis for predicting the level of cognitive impairment. [Subjects and Methods] A total of 187 stroke patients with cognitive impairment were enrolled in this study. The 187 patients were evaluated by the clock drawing test developed through Rasch analysis along with the mini-mental state examination of cognitive evaluation tool. An analysis of the variance was performed to examine the significance of the mini-mental state examination and the clock drawing test according to the general characteristics of the subjects. Receiver operating characteristic analysis was performed to determine the cutoff point for cognitive impairment and to calculate the sensitivity and specificity values. [Results] The results of comparison of the clock drawing test with the mini-mental state showed significant differences in according to gender, age, education, and affected side. A total CDT of 10.5, which was selected as the cutoff point to identify cognitive impairement, showed a sensitivity, specificity, Youden index, positive predictive, and negative predicive values of 86.4%, 91.5%, 0.8, 95%, and 88.2%. [Conclusion] The clock drawing test is believed to be useful in assessments and interventions based on its excellent ability to identify cognitive disorders.

Empirically Optimized Flow Cytometric Immunoassay Validates Ambient Analyte Theory

PubMed Central

Parpia, Zaheer A.; Kelso, David M.

2010-01-01

Ekins’ ambient analyte theory predicts, counter intuitively, that an immunoassay’s limit of detection can be improved by reducing the amount of capture antibody. In addition, it also anticipates that results should be insensitive to the volume of sample as well as the amount of capture antibody added. The objective of this study is to empirically validate all of the performance characteristics predicted by Ekins’ theory. Flow cytometric analysis was used to detect binding between a fluorescent ligand and capture microparticles since it can directly measure fractional occupancy, the primary response variable in ambient analyte theory. After experimentally determining ambient analyte conditions, comparisons were carried out between ambient and non-ambient assays in terms of their signal strengths, limits of detection, and their sensitivity to variations in reaction volume and number of particles. The critical number of binding sites required for an assay to be in the ambient analyte region was estimated to be 0.1VKd. As predicted, such assays exhibited superior signal/noise levels and limits of detection; and were not affected by variations in sample volume and number of binding sites. When the signal detected measures fractional occupancy, ambient analyte theory is an excellent guide to developing assays with superior performance characteristics. PMID:20152793

Funnel plot control limits to identify poorly performing healthcare providers when there is uncertainty in the value of the benchmark.

PubMed

Manktelow, Bradley N; Seaton, Sarah E; Evans, T Alun

2016-12-01

There is an increasing use of statistical methods, such as funnel plots, to identify poorly performing healthcare providers. Funnel plots comprise the construction of control limits around a benchmark and providers with outcomes falling outside the limits are investigated as potential outliers. The benchmark is usually estimated from observed data but uncertainty in this estimate is usually ignored when constructing control limits. In this paper, the use of funnel plots in the presence of uncertainty in the value of the benchmark is reviewed for outcomes from a Binomial distribution. Two methods to derive the control limits are shown: (i) prediction intervals; (ii) tolerance intervals Tolerance intervals formally include the uncertainty in the value of the benchmark while prediction intervals do not. The probability properties of 95% control limits derived using each method were investigated through hypothesised scenarios. Neither prediction intervals nor tolerance intervals produce funnel plot control limits that satisfy the nominal probability characteristics when there is uncertainty in the value of the benchmark. This is not necessarily to say that funnel plots have no role to play in healthcare, but that without the development of intervals satisfying the nominal probability characteristics they must be interpreted with care. © The Author(s) 2014.

Abdominal Circumference Versus Body Mass Index as Predictors of Lower Extremity Overuse Injury Risk.

PubMed

Nye, Nathaniel S; Kafer, Drew S; Olsen, Cara; Carnahan, David H; Crawford, Paul F

2018-02-01

Abdominal circumference (AC) is superior to body mass index (BMI) as a measure of risk for various health outcomes. Our objective was to compare AC and BMI as predictors of lower extremity overuse injury (LEOI) risk. Retrospective review of electronic medical records of 79,868 US Air Force personnel over a 7-year period (2005-2011) for incidence of new LEOI. Subjects were stratified by BMI and AC. Injury risk for BMI/AC subgroups was calculated using Kaplan-Meier curves and Cox proportional-hazards regression. Receiver operating characteristic curves with area under the curve were used to compare each model's predictive value. Cox proportional-hazards regression showed significant risk association between elevated BMI, AC, and all injury types, with hazard ratios ranging 1.230-3.415 for obese versus normal BMI and 1.665-3.893 for high-risk versus low-risk AC (P < .05 for all measures). Receiver operating characteristic curves with area under the curve showed equivalent performance between BMI and AC for predicting all injury types. However, the combined model (AC and BMI) showed improved predictive ability over either model alone for joint injury, overall LEOI, and most strongly for osteoarthritis. Although AC and BMI alone performed similarly well, a combined approach using BMI and AC together improved risk estimation for LEOI.

Impact of experimental design on PET radiomics in predicting somatic mutation status.

PubMed

Yip, Stephen S F; Parmar, Chintan; Kim, John; Huynh, Elizabeth; Mak, Raymond H; Aerts, Hugo J W L

2017-12-01

PET-based radiomic features have demonstrated great promises in predicting genetic data. However, various experimental parameters can influence the feature extraction pipeline, and hence, Here, we investigated how experimental settings affect the performance of radiomic features in predicting somatic mutation status in non-small cell lung cancer (NSCLC) patients. 348 NSCLC patients with somatic mutation testing and diagnostic PET images were included in our analysis. Radiomic feature extractions were analyzed for varying voxel sizes, filters and bin widths. 66 radiomic features were evaluated. The performance of features in predicting mutations status was assessed using the area under the receiver-operating-characteristic curve (AUC). The influence of experimental parameters on feature predictability was quantified as the relative difference between the minimum and maximum AUC (δ). The large majority of features (n=56, 85%) were significantly predictive for EGFR mutation status (AUC≥0.61). 29 radiomic features significantly predicted EGFR mutations and were robust to experimental settings with δ Overall <5%. The overall influence (δ Overall ) of the voxel size, filter and bin width for all features ranged from 5% to 15%, respectively. For all features, none of the experimental designs was predictive of KRAS+ from KRAS- (AUC≤0.56). The predictability of 29 radiomic features was robust to the choice of experimental settings; however, these settings need to be carefully chosen for all other features. The combined effect of the investigated processing methods could be substantial and must be considered. Optimized settings that will maximize the predictive performance of individual radiomic features should be investigated in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

PubMed Central

Zhu, Qing; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614

Day-ahead crude oil price forecasting using a novel morphological component analysis based model.

PubMed

Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung

2014-01-01

As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PubMed

Baquero, Oswaldo Santos; Santana, Lidia Maria Reis; Chiaravalloti-Neto, Francisco

2018-01-01

Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in turn, timely and efficient interventions to reduce the burden of the disease. We conducted a comparative study of dengue predictions in São Paulo city to test the performance of trained seasonal autoregressive integrated moving average models, generalized additive models and artificial neural networks. We also used a naïve model as a benchmark. A generalized additive model with lags of the number of cases and meteorological variables had the best performance, predicted epidemics of unprecedented magnitude and its performance was 3.16 times higher than the benchmark and 1.47 higher that the next best performing model. The predictive models captured the seasonal patterns but differed in their capacity to anticipate large epidemics and all outperformed the benchmark. In addition to be able to predict epidemics of unprecedented magnitude, the best model had computational advantages, since its training and tuning was straightforward and required seconds or at most few minutes. These are desired characteristics to provide timely results for decision makers. However, it should be noted that predictions are made just one month ahead and this is a limitation that future studies could try to reduce.

Relating landscape characteristics to non-point source pollution in mine waste-located watersheds using geospatial techniques.

PubMed

Xiao, Huaguo; Ji, Wei

2007-01-01

Landscape characteristics of a watershed are important variables that influence surface water quality. Understanding the relationship between these variables and surface water quality is critical in predicting pollution potential and developing watershed management practices to eliminate or reduce pollution risk. To understand the impacts of landscape characteristics on water quality in mine waste-located watersheds, we conducted a case study in the Tri-State Mining District which is located in the conjunction of three states (Missouri, Kansas and Oklahoma). Severe heavy metal pollution exists in that area resulting from historical mining activities. We characterized land use/land cover over the last three decades by classifying historical multi-temporal Landsat imagery. Landscape metrics such as proportion, edge density and contagion were calculated based on the classified imagery. In-stream water quality data over three decades were collected, including lead, zinc, iron, cadmium, aluminum and conductivity which were used as key water quality indicators. Statistical analyses were performed to quantify the relationship between landscape metrics and surface water quality. Results showed that landscape characteristics in mine waste-located watersheds could account for as much as 77% of the variation of water quality indicators. A single landscape metric alone, such as proportion of mine waste area, could be used to predict surface water quality; but its predicting power is limited, usually accounting for less than 60% of the variance of water quality indicators.

Paradigm of pretest risk stratification before coronary computed tomography.

PubMed

Jensen, Jesper Møller; Ovrehus, Kristian A; Nielsen, Lene H; Jensen, Jesper K; Larsen, Henrik M; Nørgaard, Bjarne L

2009-01-01

The optimal method of determining the pretest risk of coronary artery disease as a patient selection tool before coronary multidetector computed tomography (MDCT) is unknown. We investigated the ability of 3 different clinical risk scores to predict the outcome of coronary MDCT. This was a retrospective study of 551 patients consecutively referred for coronary MDCT on a suspicion of coronary artery disease. Diamond-Forrester, Duke, and Morise risk models were used to predict coronary artery stenosis (>50%) as assessed by coronary MDCT. The models were compared by receiver operating characteristic analysis. The distribution of low-, intermediate-, and high-risk persons, respectively, was established and compared for each of the 3 risk models. Overall, all risk prediction models performed equally well. However, the Duke risk model classified the low-risk patients more correctly than did the other models (P < 0.01). In patients without coronary artery calcification (CAC), the predictive value of the Duke risk model was superior to the other risk models (P < 0.05). Currently available risk prediction models seem to perform better in patients without CAC. Between the risk prediction models, there was a significant discrepancy in the distribution of patients at low, intermediate, or high risk (P < 0.01). The 3 risk prediction models perform equally well, although the Duke risk score may have advantages in subsets of patients. The choice of risk prediction model affects the referral pattern to MDCT. Copyright (c) 2009 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Self-rated health and mortality: could clinical and performance-based measures of health and functioning explain the association?

PubMed

Lyyra, Tiina-Mari; Heikkinen, Eino; Lyyra, Anna-Liisa; Jylhä, Marja

2006-01-01

It is well established that self-rated health (SRH) predicts mortality even when other indicators of health status are taken into account. It has been suggested that SRH measures a wide array of mortality-related physiological and pathological characteristics not captured by the covariates included in the analyses. Our aim was to test this hypothesis by examining the predictive value of SRH on mortality controlling for different measurements of body structure, performance-based functioning and diagnosed diseases with a population-based, prospective study over an 18-year follow-up. Subjects consisted of 257 male residents of the city of Jyväskylä, central Finland, aged 51-55 and 71-75 years. Among the 71-75-year-olds the association between SRH and mortality was weaker over the longer compared to shorter follow-up period. In the multivariate Cox regression models with an 18-year follow-up time for middle-aged and a10-year follow-up time for older men, SRH predicted mortality even when the anthropometrics, clinical chemistry and performance-based measures of functioning were controlled for, but not when the number of chronic diseases was included. Although our results confirm the hypothesis that the predictive value of SRH can be explained by diagnosed diseases, its predictive power remained, when the clinical and performance-based measures of health and functioning were controlled.

Temperature-Dependent Characterization, Modeling, and Switching Speed-Limitation Analysis of Third-Generation 10-kV SiC MOSFET

DOE PAGES

Ji, Shiqi; Zheng, Sheng; Wang, Fei; ...

2017-07-06

The temperature-dependent characteristics of the third-generation 10-kV/20-A SiC MOSFET including the static characteristics and switching performance are carried out in this paper. The steady-state characteristics, including saturation current, output characteristics, antiparallel diode, and parasitic capacitance, are tested. Here, a double pulse test platform is constructed including a circuit breaker and gate drive with >10-kV insulation and also a hotplate under the device under test for temperature-dependent characterization during switching transients. The switching performance is tested under various load currents and gate resistances at a 7-kV dc-link voltage from 25 to 125 C and compared with previous 10-kV MOSFETs. A simplemore » behavioral model with its parameter extraction method is proposed to predict the temperature-dependent characteristics of the 10-kV SiC MOSFET. The switching speed limitations, including the reverse recovery of SiC MOSFET's body diode, overvoltage caused by stray inductance, crosstalk, heat sink, and electromagnetic interference to the control are discussed based on simulations and experimental results.« less

Temperature-Dependent Characterization, Modeling, and Switching Speed-Limitation Analysis of Third-Generation 10-kV SiC MOSFET

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

Ji, Shiqi; Zheng, Sheng; Wang, Fei

The temperature-dependent characteristics of the third-generation 10-kV/20-A SiC MOSFET including the static characteristics and switching performance are carried out in this paper. The steady-state characteristics, including saturation current, output characteristics, antiparallel diode, and parasitic capacitance, are tested. Here, a double pulse test platform is constructed including a circuit breaker and gate drive with >10-kV insulation and also a hotplate under the device under test for temperature-dependent characterization during switching transients. The switching performance is tested under various load currents and gate resistances at a 7-kV dc-link voltage from 25 to 125 C and compared with previous 10-kV MOSFETs. A simplemore » behavioral model with its parameter extraction method is proposed to predict the temperature-dependent characteristics of the 10-kV SiC MOSFET. The switching speed limitations, including the reverse recovery of SiC MOSFET's body diode, overvoltage caused by stray inductance, crosstalk, heat sink, and electromagnetic interference to the control are discussed based on simulations and experimental results.« less

Domains of cognitive function in early old age: which ones are predicted by pre-retirement psychosocial work characteristics?

PubMed Central

Sabbath, Erika; Andel, Ross; Zins, Marie; Goldberg, Marcel; Berr, Claudine

2016-01-01

Background Psychosocial work characteristics may predict cognitive functioning after retirement. However, little research has explored specific cognitive domains associated with psychosocial work environments. Our study tested whether exposure to job demands, job control, and their combination during working life predicted post-retirement performance on eight cognitive tests. Methods We used data from French GAZEL cohort members who had undergone post-retirement cognitive testing (n=2,149). Psychosocial job characteristics were measured on average four years before retirement using Karasek’s Job Content Questionnaire (job demands, job control, demand-control combinations). We tested associations between these exposures and post-retirement performance on tests of executive function, visual-motor speed, psycho-motor speed, verbal memory, and verbal fluency using OLS regression. Results Low job control during working life was negatively associated with executive function, psychomotor speed, phonemic fluency, and semantic fluency after retirement (p’s<.05) even after adjustment for demographics, socioeconomic status, health and social behaviours, and vascular risk factors. Both passive (low-demand, low-control) and high-strain (high-demand, low-control) jobs were associated with lower scores on phonemic and semantic fluency when compared to low-strain (low-demand, high-control) jobs. Conclusions Low job control, in combination with both high and low job demands, is associated with post-retirement deficits in some, but not all, cognitive domains. In addition to work stress, associations between passive work and subsequent cognitive function may implicate lack of cognitive engagement at work as a risk factor for future cognitive difficulties. PMID:27188277

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo

NASA Astrophysics Data System (ADS)

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-01

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo.

PubMed

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-28

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

Soft sensor modelling by time difference, recursive partial least squares and adaptive model updating

NASA Astrophysics Data System (ADS)

Fu, Y.; Yang, W.; Xu, O.; Zhou, L.; Wang, J.

2017-04-01

To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference, moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-carboxy-benz-aldehyde (CBA) content in the purified terephthalic acid (PTA) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflect the process characteristics accurately.

Stability of Cell Wall Composition and Saccharification Efficiency in Miscanthus across Diverse Environments

PubMed Central

van der Weijde, Tim; Dolstra, Oene; Visser, Richard G. F.; Trindade, Luisa M.

2017-01-01

To investigate the potential effects of differences between growth locations on the cell wall composition and saccharification efficiency of the bioenergy crop miscanthus, a diverse set of 15 accessions were evaluated in six locations across Europe for the first 3 years following establishment. High-throughput quantification of cellulose, hemicellulose and lignin contents, as well as cellulose and hemicellulose conversion rates was achieved by combining near-infrared reflectance spectroscopy (NIRS) and biochemical analysis. Prediction models were developed and found to predict biomass quality characteristics with high accuracy. Location significantly affected biomass quality characteristics in all three cultivation years, but location-based differences decreased toward the third year as the plants reached maturity and the effect of location-dependent differences in the rate of establishment reduced. In all locations extensive variation in accession performance was observed for quality traits. The performance of the different accessions in the second and third cultivation year was strongly correlated, while accession performance in the first cultivation year did not correlate well with performance in later years. Significant genotype-by-environment (G × E) interactions were observed for most traits, revealing differences between accessions in environmental sensitivity. Stability analysis of accession performance for calculated ethanol yields suggested that selection for good and stable performance is a viable approach. Environmental influence on biomass quality is substantial and should be taken into account in order to match genotype, location and end-use of miscanthus as a lignocellulose feedstock. PMID:28111583

Stability of Cell Wall Composition and Saccharification Efficiency in Miscanthus across Diverse Environments.

PubMed

van der Weijde, Tim; Dolstra, Oene; Visser, Richard G F; Trindade, Luisa M

2016-01-01

To investigate the potential effects of differences between growth locations on the cell wall composition and saccharification efficiency of the bioenergy crop miscanthus, a diverse set of 15 accessions were evaluated in six locations across Europe for the first 3 years following establishment. High-throughput quantification of cellulose, hemicellulose and lignin contents, as well as cellulose and hemicellulose conversion rates was achieved by combining near-infrared reflectance spectroscopy (NIRS) and biochemical analysis. Prediction models were developed and found to predict biomass quality characteristics with high accuracy. Location significantly affected biomass quality characteristics in all three cultivation years, but location-based differences decreased toward the third year as the plants reached maturity and the effect of location-dependent differences in the rate of establishment reduced. In all locations extensive variation in accession performance was observed for quality traits. The performance of the different accessions in the second and third cultivation year was strongly correlated, while accession performance in the first cultivation year did not correlate well with performance in later years. Significant genotype-by-environment (G × E) interactions were observed for most traits, revealing differences between accessions in environmental sensitivity. Stability analysis of accession performance for calculated ethanol yields suggested that selection for good and stable performance is a viable approach. Environmental influence on biomass quality is substantial and should be taken into account in order to match genotype, location and end-use of miscanthus as a lignocellulose feedstock.

MSG test report-steady-state heat transfer. [LMFBR

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

Harty, R.B.

This report documents the results of the Steady-State Heat Transfer Tests conducted on the AI Modular Steam Generator (MSG), at the Sodium Component Test Installation (SCTI) of the Liquid Metal Engineering Center. Heat transfer and pressure drop performance data are given along with current predictions of performance. Departure from nucleate boiling characteristics is given. A dispersed flow film boiling model, employing thermal nonequilibrium, was used to analyze data in the film boiling region.

Predicting the risk for colorectal cancer with personal characteristics and fecal immunochemical test.

PubMed

Li, Wen; Zhao, Li-Zhong; Ma, Dong-Wang; Wang, De-Zheng; Shi, Lei; Wang, Hong-Lei; Dong, Mo; Zhang, Shu-Yi; Cao, Lei; Zhang, Wei-Hua; Zhang, Xi-Peng; Zhang, Qing-Huai; Yu, Lin; Qin, Hai; Wang, Xi-Mo; Chen, Sam Li-Sheng

2018-05-01

We aimed to predict colorectal cancer (CRC) based on the demographic features and clinical correlates of personal symptoms and signs from Tianjin community-based CRC screening data.A total of 891,199 residents who were aged 60 to 74 and were screened in 2012 were enrolled. The Lasso logistic regression model was used to identify the predictors for CRC. Predictive validity was assessed by the receiver operating characteristic (ROC) curve. Bootstrapping method was also performed to validate this prediction model.CRC was best predicted by a model that included age, sex, education level, occupations, diarrhea, constipation, colon mucosa and bleeding, gallbladder disease, a stressful life event, family history of CRC, and a positive fecal immunochemical test (FIT). The area under curve (AUC) for the questionnaire with a FIT was 84% (95% CI: 82%-86%), followed by 76% (95% CI: 74%-79%) for a FIT alone, and 73% (95% CI: 71%-76%) for the questionnaire alone. With 500 bootstrap replications, the estimated optimism (<0.005) shows good discrimination in validation of prediction model.A risk prediction model for CRC based on a series of symptoms and signs related to enteric diseases in combination with a FIT was developed from first round of screening. The results of the current study are useful for increasing the awareness of high-risk subjects and for individual-risk-guided invitations or strategies to achieve mass screening for CRC.

Preschoolers' precision of the approximate number system predicts later school mathematics performance.

PubMed

Mazzocco, Michèle M M; Feigenson, Lisa; Halberda, Justin

2011-01-01

The Approximate Number System (ANS) is a primitive mental system of nonverbal representations that supports an intuitive sense of number in human adults, children, infants, and other animal species. The numerical approximations produced by the ANS are characteristically imprecise and, in humans, this precision gradually improves from infancy to adulthood. Throughout development, wide ranging individual differences in ANS precision are evident within age groups. These individual differences have been linked to formal mathematics outcomes, based on concurrent, retrospective, or short-term longitudinal correlations observed during the school age years. However, it remains unknown whether this approximate number sense actually serves as a foundation for these school mathematics abilities. Here we show that ANS precision measured at preschool, prior to formal instruction in mathematics, selectively predicts performance on school mathematics at 6 years of age. In contrast, ANS precision does not predict non-numerical cognitive abilities. To our knowledge, these results provide the first evidence for early ANS precision, measured before the onset of formal education, predicting later mathematical abilities.

Preschoolers' Precision of the Approximate Number System Predicts Later School Mathematics Performance

PubMed Central

Mazzocco, Michèle M. M.; Feigenson, Lisa; Halberda, Justin

2011-01-01

The Approximate Number System (ANS) is a primitive mental system of nonverbal representations that supports an intuitive sense of number in human adults, children, infants, and other animal species. The numerical approximations produced by the ANS are characteristically imprecise and, in humans, this precision gradually improves from infancy to adulthood. Throughout development, wide ranging individual differences in ANS precision are evident within age groups. These individual differences have been linked to formal mathematics outcomes, based on concurrent, retrospective, or short-term longitudinal correlations observed during the school age years. However, it remains unknown whether this approximate number sense actually serves as a foundation for these school mathematics abilities. Here we show that ANS precision measured at preschool, prior to formal instruction in mathematics, selectively predicts performance on school mathematics at 6 years of age. In contrast, ANS precision does not predict non-numerical cognitive abilities. To our knowledge, these results provide the first evidence for early ANS precision, measured before the onset of formal education, predicting later mathematical abilities. PMID:21935362

A PRIM approach to predictive-signature development for patient stratification.

PubMed

Chen, Gong; Zhong, Hua; Belousov, Anton; Devanarayan, Viswanath

2015-01-30

Patients often respond differently to a treatment because of individual heterogeneity. Failures of clinical trials can be substantially reduced if, prior to an investigational treatment, patients are stratified into responders and nonresponders based on biological or demographic characteristics. These characteristics are captured by a predictive signature. In this paper, we propose a procedure to search for predictive signatures based on the approach of patient rule induction method. Specifically, we discuss selection of a proper objective function for the search, present its algorithm, and describe a resampling scheme that can enhance search performance. Through simulations, we characterize conditions under which the procedure works well. To demonstrate practical uses of the procedure, we apply it to two real-world data sets. We also compare the results with those obtained from a recent regression-based approach, Adaptive Index Models, and discuss their respective advantages. In this study, we focus on oncology applications with survival responses. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Two Different Maintenance Strategies in the Hospital Environment: Preventive Maintenance for Older Technology Devices and Predictive Maintenance for Newer High-Tech Devices.

PubMed

Sezdi, Mana

2016-01-01

A maintenance program generated through the consideration of characteristics and failures of medical equipment is an important component of technology management. However, older technology devices and newer high-tech devices cannot be efficiently managed using the same strategies because of their different characteristics. This study aimed to generate a maintenance program comprising two different strategies to increase the efficiency of device management: preventive maintenance for older technology devices and predictive maintenance for newer high-tech devices. For preventive maintenance development, 589 older technology devices were subjected to performance verification and safety testing (PVST). For predictive maintenance development, the manufacturers' recommendations were used for 134 high-tech devices. These strategies were evaluated in terms of device reliability. This study recommends the use of two different maintenance strategies for old and new devices at hospitals in developing countries. Thus, older technology devices that applied only corrective maintenance will be included in maintenance like high-tech devices.

Two Different Maintenance Strategies in the Hospital Environment: Preventive Maintenance for Older Technology Devices and Predictive Maintenance for Newer High-Tech Devices

PubMed Central

Sezdi, Mana

2016-01-01

A maintenance program generated through the consideration of characteristics and failures of medical equipment is an important component of technology management. However, older technology devices and newer high-tech devices cannot be efficiently managed using the same strategies because of their different characteristics. This study aimed to generate a maintenance program comprising two different strategies to increase the efficiency of device management: preventive maintenance for older technology devices and predictive maintenance for newer high-tech devices. For preventive maintenance development, 589 older technology devices were subjected to performance verification and safety testing (PVST). For predictive maintenance development, the manufacturers' recommendations were used for 134 high-tech devices. These strategies were evaluated in terms of device reliability. This study recommends the use of two different maintenance strategies for old and new devices at hospitals in developing countries. Thus, older technology devices that applied only corrective maintenance will be included in maintenance like high-tech devices. PMID:27195666

Prediction and Factor Extraction of Drug Function by Analyzing Medical Records in Developing Countries.

PubMed

Hu, Min; Nohara, Yasunobu; Nakamura, Masafumi; Nakashima, Naoki

2017-01-01

The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict pharmaceutical prescriptions may solve HRH crises. In this study, we investigate a predictive model by analyzing prescription data of 4,543 subjects in Bangladesh. We predict the function of prescribed drugs, comparing three machine-learning approaches. The approaches compare whether a subject shall be prescribed medicine from the 21 most frequently prescribed drug functions. Receiver Operating Characteristics (ROC) were selected as a way to evaluate and assess prediction models. The results show the drug function with the best prediction performance was oral hypoglycemic drugs, which has an average AUC of 0.962. To understand how the variables affect prediction, we conducted factor analysis based on tree-based algorithms and natural language processing techniques.

Specialized CFD Grid Generation Methods for Near-Field Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Park, Michael A.; Campbell, Richard L.; Elmiligui, Alaa; Cliff, Susan E.; Nayani, Sudheer N.

2014-01-01

Ongoing interest in analysis and design of low sonic boom supersonic transports re- quires accurate and ecient Computational Fluid Dynamics (CFD) tools. Specialized grid generation techniques are employed to predict near- eld acoustic signatures of these con- gurations. A fundamental examination of grid properties is performed including grid alignment with ow characteristics and element type. The issues a ecting the robustness of cylindrical surface extrusion are illustrated. This study will compare three methods in the extrusion family of grid generation methods that produce grids aligned with the freestream Mach angle. These methods are applied to con gurations from the First AIAA Sonic Boom Prediction Workshop.

Pulmonary and Critical Care In-Service Training Examination Score as a Predictor of Board Certification Examination Performance.

PubMed

Kempainen, Robert R; Hess, Brian J; Addrizzo-Harris, Doreen J; Schaad, Douglas C; Scott, Craig S; Carlin, Brian W; Shaw, Robert C; Duhigg, Lauren; Lipner, Rebecca S

2016-04-01

Most trainees in combined pulmonary and critical care medicine fellowship programs complete in-service training examinations (ITEs) that test knowledge in both disciplines. Whether ITE scores predict performance on the American Board of Internal Medicine Pulmonary Disease Certification Examination and Critical Care Medicine Certification Examination is unknown. To determine whether pulmonary and critical care medicine ITE scores predict performance on subspecialty board certification examinations independently of trainee demographics, program director competency ratings, fellowship program characteristics, and prior medical knowledge assessments. First- and second-year fellows who were enrolled in the study between 2008 and 2012 completed a questionnaire encompassing demographics and fellowship training characteristics. These data and ITE scores were matched to fellows' subsequent scores on subspecialty certification examinations, program director ratings, and previous scores on their American Board of Internal Medicine Internal Medicine Certification Examination. Multiple linear regression and logistic regression were used to identify independent predictors of subspecialty certification examination scores and likelihood of passing the examinations, respectively. Of eligible fellows, 82.4% enrolled in the study. The ITE score for second-year fellows was matched to their certification examination scores, which yielded 1,484 physicians for pulmonary disease and 1,331 for critical care medicine. Second-year fellows' ITE scores (β = 0.24, P < 0.001) and Internal Medicine Certification Examination scores (β = 0.49, P < 0.001) were the strongest predictors of Pulmonary Disease Certification Examination scores, and were the only significant predictors of passing the examination (ITE odds ratio, 1.12 [95% confidence interval, 1.07-1.16]; Internal Medicine Certification Examination odds ratio, 1.01 [95% confidence interval, 1.01-1.02]). Similar results were obtained for predicting Critical Care Medicine Certification Examination scores and for passing the examination. The predictive value of ITE scores among first-year fellows on the subspecialty certification examinations was comparable to second-year fellows' ITE scores. The Pulmonary and Critical Care Medicine ITE score is an independent, and stronger, predictor of subspecialty certification examination performance than fellow demographics, program director competency ratings, and fellowship characteristics. These findings support the use of the ITE to identify the learning needs of fellows as they work toward subspecialty board certification.

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

DEEP: a general computational framework for predicting enhancers

PubMed Central

Kleftogiannis, Dimitrios; Kalnis, Panos; Bajic, Vladimir B.

2015-01-01

Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/. PMID:25378307

Weak characteristic information extraction from early fault of wind turbine generator gearbox

NASA Astrophysics Data System (ADS)

Xu, Xiaoli; Liu, Xiuli

2017-09-01

Given the weak early degradation characteristic information during early fault evolution in gearbox of wind turbine generator, traditional singular value decomposition (SVD)-based denoising may result in loss of useful information. A weak characteristic information extraction based on μ-SVD and local mean decomposition (LMD) is developed to address this problem. The basic principle of the method is as follows: Determine the denoising order based on cumulative contribution rate, perform signal reconstruction, extract and subject the noisy part of signal to LMD and μ-SVD denoising, and obtain denoised signal through superposition. Experimental results show that this method can significantly weaken signal noise, effectively extract the weak characteristic information of early fault, and facilitate the early fault warning and dynamic predictive maintenance.

Evidence-based occupational hearing screening II: validation of a screening methodology using measures of functional hearing ability.

PubMed

Soli, Sigfrid D; Amano-Kusumoto, Akiko; Clavier, Odile; Wilbur, Jed; Casto, Kristen; Freed, Daniel; Laroche, Chantal; Vaillancourt, Véronique; Giguère, Christian; Dreschler, Wouter A; Rhebergen, Koenraad S

2018-05-01

Validate use of the Extended Speech Intelligibility Index (ESII) for prediction of speech intelligibility in non-stationary real-world noise environments. Define a means of using these predictions for objective occupational hearing screening for hearing-critical public safety and law enforcement jobs. Analyses of predicted and measured speech intelligibility in recordings of real-world noise environments were performed in two studies using speech recognition thresholds (SRTs) and intelligibility measures. ESII analyses of the recordings were used to predict intelligibility. Noise recordings were made in prison environments and at US Army facilities for training ground and airborne forces. Speech materials included full bandwidth sentences and bandpass filtered sentences that simulated radio transmissions. A total of 22 adults with normal hearing (NH) and 15 with mild-moderate hearing impairment (HI) participated in the two studies. Average intelligibility predictions for individual NH and HI subjects were accurate in both studies (r 2  ≥ 0.94). Pooled predictions were slightly less accurate (0.78 ≤ r 2  ≤ 0.92). An individual's SRT and audiogram can accurately predict the likelihood of effective speech communication in noise environments with known ESII characteristics, where essential hearing-critical tasks are performed. These predictions provide an objective means of occupational hearing screening.

SGC Tests for Influence of Material Composition on Compaction Characteristic of Asphalt Mixtures

PubMed Central

Chen, Qun

2013-01-01

Compaction characteristic of the surface layer asphalt mixture (13-type gradation mixture) was studied using Superpave gyratory compactor (SGC) simulative compaction tests. Based on analysis of densification curve of gyratory compaction, influence rules of the contents of mineral aggregates of all sizes and asphalt on compaction characteristic of asphalt mixtures were obtained. SGC Tests show that, for the mixture with a bigger content of asphalt, its density increases faster, that there is an optimal amount of fine aggregates for optimal compaction and that an appropriate amount of mineral powder will improve workability of mixtures, but overmuch mineral powder will make mixtures dry and hard. Conclusions based on SGC tests can provide basis for how to adjust material composition for improving compaction performance of asphalt mixtures, and for the designed asphalt mixture, its compaction performance can be predicted through these conclusions, which also contributes to the choice of compaction schemes. PMID:23818830

SGC tests for influence of material composition on compaction characteristic of asphalt mixtures.

PubMed

Chen, Qun; Li, Yuzhi

2013-01-01

Compaction characteristic of the surface layer asphalt mixture (13-type gradation mixture) was studied using Superpave gyratory compactor (SGC) simulative compaction tests. Based on analysis of densification curve of gyratory compaction, influence rules of the contents of mineral aggregates of all sizes and asphalt on compaction characteristic of asphalt mixtures were obtained. SGC Tests show that, for the mixture with a bigger content of asphalt, its density increases faster, that there is an optimal amount of fine aggregates for optimal compaction and that an appropriate amount of mineral powder will improve workability of mixtures, but overmuch mineral powder will make mixtures dry and hard. Conclusions based on SGC tests can provide basis for how to adjust material composition for improving compaction performance of asphalt mixtures, and for the designed asphalt mixture, its compaction performance can be predicted through these conclusions, which also contributes to the choice of compaction schemes.

The gender gap reloaded: are school characteristics linked to labor market performance?

PubMed

Konstantopoulos, Spyros; Constant, Amelie

2008-06-01

This study examines the wage gender gap of young adults in the 1970s, 1980s, and 2000 in the US. Using quantile regression we estimate the gender gap across the entire wage distribution. We also study the importance of high school characteristics in predicting future labor market performance. We conduct analyses for three major racial/ethnic groups in the US: Whites, Blacks, and Hispanics, employing data from two rich longitudinal studies: NLS and NELS. Our results indicate that while some school characteristics are positive and significant predictors of future wages for Whites, they are less so for the two minority groups. We find significant wage gender disparities favoring men across all three surveys in the 1970s, 1980s, and 2000. The wage gender gap is more pronounced in higher paid jobs (90th quantile) for all groups, indicating the presence of a persistent and alarming "glass ceiling."

Application of a baseflow filter for evaluating model structure suitability of the IHACRES CMD

NASA Astrophysics Data System (ADS)

Kim, H. S.

2015-02-01

The main objective of this study was to assess the predictive uncertainty from the rainfall-runoff model structure coupling a conceptual module (non-linear module) with a metric transfer function module (linear module). The methodology was primarily based on the comparison between the outputs of the rainfall-runoff model and those from an alternative model approach. An alternative model approach was used to minimise uncertainties arising from data and the model structure. A baseflow filter was adopted to better understand deficiencies in the forms of the rainfall-runoff model by avoiding the uncertainties related to data and the model structure. The predictive uncertainty from the model structure was investigated for representative groups of catchments having similar hydrological response characteristics in the upper Murrumbidgee Catchment. In the assessment of model structure suitability, the consistency (or variability) of catchment response over time and space in model performance and parameter values has been investigated to detect problems related to the temporal and spatial variability of the model accuracy. The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters. A graphical comparison of model residuals, effective rainfall estimates and hydrographs was used to determine a model's ability related to systematic model deviation between simulated and observed behaviours and general behavioural differences in the timing and magnitude of peak flows. The model's predictability was very sensitive to catchment response characteristics. The linear module performs reasonably well in the wetter catchments but has considerable difficulties when applied to the drier catchments where a hydrologic response is dominated by quick flow. The non-linear module has a potential limitation in its capacity to capture non-linear processes for converting observed rainfall into effective rainfall in both the wetter and drier catchments. The comparative study based on a better quantification of the accuracy and precision of hydrological modelling predictions yields a better understanding for the potential improvement of model deficiencies.

Assessing personal talent determinants in young racquet sport players: a systematic review.

PubMed

Faber, Irene R; Bustin, Paul M J; Oosterveld, Frits G J; Elferink-Gemser, Marije T; Nijhuis-Van der Sanden, Maria W G

2016-01-01

Since junior performances have little predictive value for future success, other solutions are sought to assess a young player's potential. The objectives of this systematic review are (1) to provide an overview of instruments measuring personal talent determinants of young players in racquet sports, and (2) to evaluate these instruments regarding their validity for talent development. Electronic searches were conducted in PubMed, PsychINFO, Web of Knowledge, ScienceDirect and SPORTDiscus (1990 to 31 March 2014). Search terms represented tennis, table tennis, badminton and squash, the concept of talent, methods of testing and children. Thirty articles with information regarding over 100 instruments were included. Validity evaluation showed that instruments focusing on intellectual and perceptual abilities, and coordinative skills discriminate elite from non-elite players and/or are related to current performance, but their predictive validity is not confirmed. There is moderate evidence that the assessments of mental and goal management skills predict future performance. Data on instruments measuring physical characteristics prohibit a conclusion due to conflicting findings. This systematic review yielded an ambiguous end point. The lack of longitudinal studies precludes verification of the instrument's capacity to forecast future performance. Future research should focus on instruments assessing multidimensional talent determinants and their predictive value in longitudinal designs.

Short Physical Performance Battery for cardiovascular disease inpatients: implications for critical factors and sarcopenia.

PubMed

Yasuda, Tomohiro; Nakajima, Toshiaki; Sawaguchi, Tatsuya; Nozawa, Naohiro; Arakawa, Tomoe; Takahashi, Reiko; Mizushima, Yuta; Katayanagi, Satoshi; Matsumoto, Kazuhisa; Toyoda, Shigeru; Inoue, Teruo

2017-12-12

We examined the relationship between Short Physical Performance Battery (SPPB) and clinical and laboratory factors and the effect of sarcopenia and sarcopenic obesity (SO) on clinical and laboratory factors for cardiovascular disease (CVD) inpatients. CVD male (n = 318) and female (n = 172) inpatients were recruited. A stepwise multiple-regression analysis was performed to predict total SPPB scores and assess clinical and laboratory factors (physical characteristics, functional and morphological assessments, etc.). Each test outcome were compared among sarcopenia, SO and non-sarcopenic groups. To predict total SPPB scores, the predicted handgrip, Controlling Nutritional Status score, % body fat, anterior mid-thigh muscle thickness, standing height and systolic blood pressure were calculated for males and anterior mid-thigh MTH, BMI, knee extension and fat mass were calculated for females. There were no differences in blood pressure, total SPPB scores and functional assessments between sarcopenia and SO groups for CVD male and female inpatients. In conclusion, the physical performance of CVD inpatients can be predicted by nutritional, functional, clinical and anthropometric variables, regardless the gender and the presence of sarcopenia. Furthermore, the presence of sarcopenia has a negative effect on the clinical and laboratory factors, but there is a difference in impact between sarcopenia and SO regardless the gender.

Projectile Combustion Effects on Ram Accelerator Performance

NASA Astrophysics Data System (ADS)

Chitale, Saarth Anjali

University of Washington Abstract Projectile Combustion Effects on Ram Accelerator Performance Saarth Anjali Chitale Chair of the Supervisory Committee: Prof. Carl Knowlen William E. Boeing Department of Aeronautics and Astronautics The ram accelerator facility at the University of Washington is used to propel projectiles at supersonic velocities. This concept is similar to an air-breathing ramjet engine in that sub-caliber projectiles, shaped like the ramjet engine center-body, are shot through smooth-bore steel-walled tubes having an internal diameter of 38 mm. The ram accelerator propulsive cycles operate between Mach 2 to 10 and have the potential to accelerate projectile to velocities greater than 8 km/s. The theoretical thrust versus Mach number characteristics can be obtained using knowledge of gas dynamics and thermodynamics that goes into the design of the ram accelerator. The corresponding velocity versus distance profiles obtained from the test runs at the University of Washington, however, are often not consistent with the theoretical predictions after the projectiles reach in-tube Mach numbers greater than 4. The experimental velocities are typically greater than the expected theoretical predictions; which has led to the proposition that the combustion process may be moving up onto the projectile. An alternative explanation for higher than predicted thrust, which is explored here, is that the performance differences can be attributed to the ablation of the projectile body which results in molten metal being added to the flow of the gaseous combustible mixture around the projectile. This molten metal is assumed to mix uniformly and react with the gaseous propellant; thereby enhancing the propellant energy release and altering the predicted thrust-Mach characteristics. This theory predicts at what Mach number the projectile will first experience enhanced thrust and the corresponding velocity-distance profile. Preliminary results are in good agreement with projectiles operating in methane/oxygen/nitrogen propellants. Effects of projectile surface to volume ratio are also explored by applying the model to experimental results from smaller (Tohoku University, 25-mm-bore) and larger (Institute of Saint-Louis 90-mm-bore) bore ram accelerators. Due to lower surface-to-volume ratio, large diameter projectiles are predicted to need to reach higher Mach numbers than smaller diameter projectiles before thrust enhancement due to metal ablation and burning would be experienced. This proposition was supported by published experimental data. The theoretical modeling of projectile ablation, metal combustion, and subsequent ram accelerator thrust characteristics are presented along comparisons to experiments from three different sized ram accelerator facilities.

A Job Analysis for K-8 Principals in a Nationwide Charter School System

ERIC Educational Resources Information Center

Cumings, Laura; Coryn, Chris L. S.

2009-01-01

Background: Although no single technique on its own can predict job performance, a job analysis is a customary approach for identifying the relevant knowledge, skills, abilities, and other characteristics (KSAO) necessary to successfully complete the job tasks of a position. Once the position requirements are identified, the hiring process is…

Predicting Stereotype Threat, Test Anxiety, and Cognitive Ability Test Performance: An Examination of Three Models

ERIC Educational Resources Information Center

Sawyer, Jr., Thomas P.; Hollis-Sawyer, Lisa A.

2005-01-01

As the classroom and workplace, among other contexts, become more diverse in their population characteristics, the need to be aware of specific factors impacting testing outcome issues correspondingly increases. The focus in this study, among other purposes, was to identify possible interactions between examinee's individual-difference…

Deployment and Performance Characteristics of 5-Foot Diameter (1.5m) Attached Inflatable Decelerators from Mach Numbers 2.2-4.4

NASA Technical Reports Server (NTRS)

Bohon, Herman L.; Miserentino, Robert

1970-01-01

Deployment characteristics and steady-state performance data were obtained over the Mach number range from 2.2 to 4.4 and at angles of attack from 0 degrees to l0 degrees. All attached inflatable decelerator (AID) models deployed successfully and exhibited flutter-free performance after deployment. Shock loads commonly associated with inflation of parachutes during deployment were not experienced. Force and moment data and ram-air pressure data were obtained throughout the Mach number range and at angles of attack from 0 degrees to l0 degrees. The high drag coefficient of 1.14 was in good agreement with the value predicted by the theory used in the design and indicated other AID shapes may be designed on a rational basis with a high degree of confidence.

Research on digital system design of nuclear power valve

NASA Astrophysics Data System (ADS)

Zhang, Xiaolong; Li, Yuan; Wang, Tao; Dai, Ye

2018-04-01

With the progress of China's nuclear power industry, nuclear power plant valve products is in a period of rapid development, high performance, low cost, short cycle of design requirements for nuclear power valve is proposed, so there is an urgent need for advanced digital design method and integrated design platform to provide technical support. Especially in the background of the nuclear power plant leakage in Japan, it is more practical to improve the design capability and product performance of the nuclear power valve. The finite element numerical analysis is a common and effective method for the development of nuclear power valves. Nuclear power valve has high safety, complexity of valve chamber and nonlinearity of seal joint surface. Therefore, it is urgent to establish accurate prediction models for earthquake prediction and seal failure to meet engineering accuracy and calculation conditions. In this paper, a general method of finite element modeling for nuclear power valve assembly and key components is presented, aiming at revealing the characteristics and rules of finite element modeling of nuclear power valves, and putting forward aprecision control strategy for finite element models for nuclear power valve characteristics analysis.

Seroma in ventral incisional herniorrhaphy: incidence, predictors and outcome.

PubMed

Kaafarani, Haytham M A; Hur, Kwan; Hirter, Angie; Kim, Lawrence T; Thomas, Anthony; Berger, David H; Reda, Domenic; Itani, Kamal M F

2009-11-01

Factors leading to seroma following ventral incisional herniorrhaphy (VIH) are poorly understood. Between 2004 and 2006, patients were prospectively randomized at 4 Veterans Affairs hospitals to undergo laparoscopic or open VIH. Patients who developed seromas within 8 weeks postoperatively were compared with those who did not. Multivariate analyses were performed to identify predictors of seroma. Of 145 patients who underwent VIH, 24 (16.6%) developed seromas. Patients who underwent open VIH had more seromas than those who underwent laparoscopic VIH (23.3% vs 6.8%, P = .011). Seroma patients had hernias that were never spontaneously reducible (0% vs 21%, P = .015), had more abdominal incisions preoperatively (mean, 2.4 vs 1.8; P = .037), and were less likely to have drain catheters placed than those without seromas (30.0% vs 63.1%, P = .011). In multivariate analyses, open VIH predicted seroma (odds ratio, 5.5; 95% confidence interval, 1.6-18.8), as well as the specific hospital at which the procedure was performed. Spontaneous resolution occurred in 71% of seromas; 29% required aspiration. Procedural characteristics and hernia characteristics rather than patient comorbidities predicted seroma in VIH.

A High-Granularity Approach to Modeling Energy Consumption and Savings Potential in the U.S. Residential Building Stock

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

None

Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper willmore » describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.« less

Prediction of HDR quality by combining perceptually transformed display measurements with machine learning

NASA Astrophysics Data System (ADS)

Choudhury, Anustup; Farrell, Suzanne; Atkins, Robin; Daly, Scott

2017-09-01

We present an approach to predict overall HDR display quality as a function of key HDR display parameters. We first performed subjective experiments on a high quality HDR display that explored five key HDR display parameters: maximum luminance, minimum luminance, color gamut, bit-depth and local contrast. Subjects rated overall quality for different combinations of these display parameters. We explored two models | a physical model solely based on physically measured display characteristics and a perceptual model that transforms physical parameters using human vision system models. For the perceptual model, we use a family of metrics based on a recently published color volume model (ICT-CP), which consists of the PQ luminance non-linearity (ST2084) and LMS-based opponent color, as well as an estimate of the display point spread function. To predict overall visual quality, we apply linear regression and machine learning techniques such as Multilayer Perceptron, RBF and SVM networks. We use RMSE and Pearson/Spearman correlation coefficients to quantify performance. We found that the perceptual model is better at predicting subjective quality than the physical model and that SVM is better at prediction than linear regression. The significance and contribution of each display parameter was investigated. In addition, we found that combined parameters such as contrast do not improve prediction. Traditional perceptual models were also evaluated and we found that models based on the PQ non-linearity performed better.

Network-based prediction and knowledge mining of disease genes.

PubMed

Carson, Matthew B; Lu, Hui

2015-01-01

In recent years, high-throughput protein interaction identification methods have generated a large amount of data. When combined with the results from other in vivo and in vitro experiments, a complex set of relationships between biological molecules emerges. The growing popularity of network analysis and data mining has allowed researchers to recognize indirect connections between these molecules. Due to the interdependent nature of network entities, evaluating proteins in this context can reveal relationships that may not otherwise be evident. We examined the human protein interaction network as it relates to human illness using the Disease Ontology. After calculating several topological metrics, we trained an alternating decision tree (ADTree) classifier to identify disease-associated proteins. Using a bootstrapping method, we created a tree to highlight conserved characteristics shared by many of these proteins. Subsequently, we reviewed a set of non-disease-associated proteins that were misclassified by the algorithm with high confidence and searched for evidence of a disease relationship. Our classifier was able to predict disease-related genes with 79% area under the receiver operating characteristic (ROC) curve (AUC), which indicates the tradeoff between sensitivity and specificity and is a good predictor of how a classifier will perform on future data sets. We found that a combination of several network characteristics including degree centrality, disease neighbor ratio, eccentricity, and neighborhood connectivity help to distinguish between disease- and non-disease-related proteins. Furthermore, the ADTree allowed us to understand which combinations of strongly predictive attributes contributed most to protein-disease classification. In our post-processing evaluation, we found several examples of potential novel disease-related proteins and corresponding literature evidence. In addition, we showed that first- and second-order neighbors in the PPI network could be used to identify likely disease associations. We analyzed the human protein interaction network and its relationship to disease and found that both the number of interactions with other proteins and the disease relationship of neighboring proteins helped to determine whether a protein had a relationship to disease. Our classifier predicted many proteins with no annotated disease association to be disease-related, which indicated that these proteins have network characteristics that are similar to disease-related proteins and may therefore have disease associations not previously identified. By performing a post-processing step after the prediction, we were able to identify evidence in literature supporting this possibility. This method could provide a useful filter for experimentalists searching for new candidate protein targets for drug repositioning and could also be extended to include other network and data types in order to refine these predictions.

Using CV-GLUE procedure in analysis of wetland model predictive uncertainty.

PubMed

Huang, Chun-Wei; Lin, Yu-Pin; Chiang, Li-Chi; Wang, Yung-Chieh

2014-07-01

This study develops a procedure that is related to Generalized Likelihood Uncertainty Estimation (GLUE), called the CV-GLUE procedure, for assessing the predictive uncertainty that is associated with different model structures with varying degrees of complexity. The proposed procedure comprises model calibration, validation, and predictive uncertainty estimation in terms of a characteristic coefficient of variation (characteristic CV). The procedure first performed two-stage Monte-Carlo simulations to ensure predictive accuracy by obtaining behavior parameter sets, and then the estimation of CV-values of the model outcomes, which represent the predictive uncertainties for a model structure of interest with its associated behavior parameter sets. Three commonly used wetland models (the first-order K-C model, the plug flow with dispersion model, and the Wetland Water Quality Model; WWQM) were compared based on data that were collected from a free water surface constructed wetland with paddy cultivation in Taipei, Taiwan. The results show that the first-order K-C model, which is simpler than the other two models, has greater predictive uncertainty. This finding shows that predictive uncertainty does not necessarily increase with the complexity of the model structure because in this case, the more simplistic representation (first-order K-C model) of reality results in a higher uncertainty in the prediction made by the model. The CV-GLUE procedure is suggested to be a useful tool not only for designing constructed wetlands but also for other aspects of environmental management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of three statistical prediction models for forensic age prediction based on DNA methylation.

PubMed

Smeers, Inge; Decorte, Ronny; Van de Voorde, Wim; Bekaert, Bram

2018-05-01

DNA methylation is a promising biomarker for forensic age prediction. A challenge that has emerged in recent studies is the fact that prediction errors become larger with increasing age due to interindividual differences in epigenetic ageing rates. This phenomenon of non-constant variance or heteroscedasticity violates an assumption of the often used method of ordinary least squares (OLS) regression. The aim of this study was to evaluate alternative statistical methods that do take heteroscedasticity into account in order to provide more accurate, age-dependent prediction intervals. A weighted least squares (WLS) regression is proposed as well as a quantile regression model. Their performances were compared against an OLS regression model based on the same dataset. Both models provided age-dependent prediction intervals which account for the increasing variance with age, but WLS regression performed better in terms of success rate in the current dataset. However, quantile regression might be a preferred method when dealing with a variance that is not only non-constant, but also not normally distributed. Ultimately the choice of which model to use should depend on the observed characteristics of the data. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction modeling of physiological responses and human performance in the heat with application to space operations

NASA Technical Reports Server (NTRS)

Pandolf, Kent B.; Stroschein, Leander A.; Gonzalez, Richard R.; Sawka, Michael N.

1994-01-01

This institute has developed a comprehensive USARIEM heat strain model for predicting physiological responses and soldier performance in the heat which has been programmed for use by hand-held calculators, personal computers, and incorporated into the development of a heat strain decision aid. This model deals directly with five major inputs: the clothing worn, the physical work intensity, the state of heat acclimation, the ambient environment (air temperature, relative humidity, wind speed, and solar load), and the accepted heat casualty level. In addition to predicting rectal temperature, heart rate, and sweat loss given the above inputs, our model predicts the expected physical work/rest cycle, the maximum safe physical work time, the estimated recovery time from maximal physical work, and the drinking water requirements associated with each of these situations. This model provides heat injury risk management guidance based on thermal strain predictions from the user specified environmental conditions, soldier characteristics, clothing worn, and the physical work intensity. If heat transfer values for space operations' clothing are known, NASA can use this prediction model to help avoid undue heat strain in astronauts during space flight.

Success-factors in transition to university mathematics

NASA Astrophysics Data System (ADS)

Bengmark, S.; Thunberg, H.; Winberg, T. M.

2017-11-01

This study examines different factors' relative importance for students' performance in the transition to university mathematics. Students' characteristics (motivation, actions and beliefs) were measured when entering the university and at the end of the first year. Principal component analysis revealed four important constructs: Self-efficacy, Motivation type, Study habits and Views of mathematics. Subsequently, orthogonal partial least squares (OPLS) analysis was used for measuring the constructs' ability to predict students' university mathematics grades. No individual constructs measured at the time of entrance predicted more than 5% of the variation. On the other hand, jointly they predicted 14%, which is almost in pair with upper secondary grades predicting 17%. Constructs measured at the end of the first year were stronger predictors, jointly predicting 37% of the variation in university grades, with Self-efficacy (21%) and Motivation (12%) being the two strongest individual predictors. In general, Study habits were not important for predicting university achievement. However, for students with low upper secondary grades, the textbook and interaction with peers, rather than internet-based resources, contributed positively to achievement. The association between Views of mathematics and performance was weak for all groups and non-existing for students with low grades.

Review and evaluation of performance measures for survival prediction models in external validation settings.

PubMed

Rahman, M Shafiqur; Ambler, Gareth; Choodari-Oskooei, Babak; Omar, Rumana Z

2017-04-18

When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell's concordance measure which tended to increase as censoring increased. We recommend that Uno's concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller's measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston's D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive accuracy curves. In addition, we recommend to investigate the characteristics of the validation data such as the level of censoring and the distribution of the prognostic index derived in the validation setting before choosing the performance measures.

Thermo-physical performance prediction of the KSC Ground Operation Demonstration Unit for liquid hydrogen

NASA Astrophysics Data System (ADS)

Baik, J. H.; Notardonato, W. U.; Karng, S. W.; Oh, I.

2015-12-01

NASA Kennedy Space Center (KSC) researchers have been working on enhanced and modernized cryogenic liquid propellant handling techniques to reduce life cycle costs of propellant management system for the unique KSC application. The KSC Ground Operation Demonstration Unit (GODU) for liquid hydrogen (LH2) plans to demonstrate integrated refrigeration, zero-loss flexible term storage of LH2, and densified hydrogen handling techniques. The Florida Solar Energy Center (FSEC) has partnered with the KSC researchers to develop thermal performance prediction model of the GODU for LH2. The model includes integrated refrigeration cooling performance, thermal losses in the tank and distribution lines, transient system characteristics during chilling and loading, and long term steady-state propellant storage. This paper will discuss recent experimental data of the GODU for LH2 system and modeling results.

Theoretical performance of cross-wind axis turbines with results for a catenary vertical axis configuration

NASA Technical Reports Server (NTRS)

Muraca, R. J.; Stephens, M. V.; Dagenhart, J. R.

1975-01-01

A general analysis capable of predicting performance characteristics of cross-wind axis turbines was developed, including the effects of airfoil geometry, support struts, blade aspect ratio, windmill solidity, blade interference and curved flow. The results were compared with available wind tunnel results for a catenary blade shape. A theoretical performance curve for an aerodynamically efficient straight blade configuration was also presented. In addition, a linearized analytical solution applicable for straight configurations was developed. A listing of the computer program developed for numerical solutions of the general performance equations is included in the appendix.

Sediment delivery modeling in practice: Comparing the effects of watershed characteristics and data resolution across hydroclimatic regions.

PubMed

Hamel, Perrine; Falinski, Kim; Sharp, Richard; Auerbach, Daniel A; Sánchez-Canales, María; Dennedy-Frank, P James

2017-02-15

Geospatial models are commonly used to quantify sediment contributions at the watershed scale. However, the sensitivity of these models to variation in hydrological and geomorphological features, in particular to land use and topography data, remains uncertain. Here, we assessed the performance of one such model, the InVEST sediment delivery model, for six sites comprising a total of 28 watersheds varying in area (6-13,500km 2 ), climate (tropical, subtropical, mediterranean), topography, and land use/land cover. For each site, we compared uncalibrated and calibrated model predictions with observations and alternative models. We then performed correlation analyses between model outputs and watershed characteristics, followed by sensitivity analyses on the digital elevation model (DEM) resolution. Model performance varied across sites (overall r 2 =0.47), but estimates of the magnitude of specific sediment export were as or more accurate than global models. We found significant correlations between metrics of sediment delivery and watershed characteristics, including erosivity, suggesting that empirical relationships may ultimately be developed for ungauged watersheds. Model sensitivity to DEM resolution varied across and within sites, but did not correlate with other observed watershed variables. These results were corroborated by sensitivity analyses performed on synthetic watersheds ranging in mean slope and DEM resolution. Our study provides modelers using InVEST or similar geospatial sediment models with practical insights into model behavior and structural uncertainty: first, comparison of model predictions across regions is possible when environmental conditions differ significantly; second, local knowledge on the sediment budget is needed for calibration; and third, model outputs often show significant sensitivity to DEM resolution. Copyright © 2016 Elsevier B.V. All rights reserved.

Measuring the performance of telephone-based disease surveillance systems in local health departments.

PubMed

Dausey, David J; Chandra, Anita; Schaefer, Agnes G; Bahney, Ben; Haviland, Amelia; Zakowski, Sarah; Lurie, Nicole

2008-09-01

We tested telephone-based disease surveillance systems in local health departments to identify system characteristics associated with consistent and timely responses to urgent case reports. We identified a stratified random sample of 74 health departments and conducted a series of unannounced tests of their telephone-based surveillance systems. We used regression analyses to identify system characteristics that predicted fast connection with an action officer (an appropriate public health professional). Optimal performance in consistently connecting callers with an action officer in 30 minutes or less was achieved by 31% of participating health departments. Reaching a live person upon dialing, regardless of who that person was, was the strongest predictor of optimal performance both in being connected with an action officer and in consistency of connection times. Health departments can achieve optimal performance in consistently connecting a caller with an action officer in 30 minutes or less and may improve performance by using a telephone-based disease surveillance system in which the phone is answered by a live person at all times.

Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology.

PubMed

Min, Hua; Mobahi, Hedyeh; Irvin, Katherine; Avramovic, Sanja; Wojtusiak, Janusz

2017-09-16

Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to the SEER-MHOS dataset to discover patterns of patient characteristics that impact the ability to perform activities of daily living (ADLs). Bio-ontologies are used to provide computable knowledge for ML methods to "understand" biomedical data. This retrospective study included 723 cancer patients from the SEER-MHOS dataset. Two ML methods were applied to create predictive models for ADL disabilities for the first year after a patient's cancer diagnosis. The first method is a standard rule learning algorithm; the second is that same algorithm additionally equipped with methods for reasoning with ontologies. The models showed that a patient's race, ethnicity, smoking preference, treatment plan and tumor characteristics including histology, staging, cancer site, and morphology were predictors for ADL performance levels one year after cancer diagnosis. The ontology-guided ML method was more accurate at predicting ADL performance levels (P < 0.1) than methods without ontologies. This study demonstrated that bio-ontologies can be harnessed to provide medical knowledge for ML algorithms. The presented method demonstrates that encoding specific types of hierarchical relationships to guide rule learning is possible, and can be extended to other types of semantic relationships present in biomedical ontologies. The ontology-guided ML method achieved better performance than the method without ontologies. The presented method can also be used to promote the effectiveness and efficiency of ML in healthcare, in which use of background knowledge and consistency with existing clinical expertise is critical.

Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ Using Deep Learning Features.

PubMed

Shi, Bibo; Grimm, Lars J; Mazurowski, Maciej A; Baker, Jay A; Marks, Jeffrey R; King, Lorraine M; Maley, Carlo C; Hwang, E Shelley; Lo, Joseph Y

2018-03-01

The aim of this study was to determine whether deep features extracted from digital mammograms using a pretrained deep convolutional neural network are prognostic of occult invasive disease for patients with ductal carcinoma in situ (DCIS) on core needle biopsy. In this retrospective study, digital mammographic magnification views were collected for 99 subjects with DCIS at biopsy, 25 of which were subsequently upstaged to invasive cancer. A deep convolutional neural network model that was pretrained on nonmedical images (eg, animals, plants, instruments) was used as the feature extractor. Through a statistical pooling strategy, deep features were extracted at different levels of convolutional layers from the lesion areas, without sacrificing the original resolution or distorting the underlying topology. A multivariate classifier was then trained to predict which tumors contain occult invasive disease. This was compared with the performance of traditional "handcrafted" computer vision (CV) features previously developed specifically to assess mammographic calcifications. The generalization performance was assessed using Monte Carlo cross-validation and receiver operating characteristic curve analysis. Deep features were able to distinguish DCIS with occult invasion from pure DCIS, with an area under the receiver operating characteristic curve of 0.70 (95% confidence interval, 0.68-0.73). This performance was comparable with the handcrafted CV features (area under the curve = 0.68; 95% confidence interval, 0.66-0.71) that were designed with prior domain knowledge. Despite being pretrained on only nonmedical images, the deep features extracted from digital mammograms demonstrated comparable performance with handcrafted CV features for the challenging task of predicting DCIS upstaging. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

The Effects of Compensatory Scanning Training on Mobility in Patients with Homonymous Visual Field Defects: Further Support, Predictive Variables and Follow-Up

PubMed Central

Melis-Dankers, Bart J. M.; Brouwer, Wiebo H.; Tucha, Oliver; Heutink, Joost

2016-01-01

Introduction People with homonymous visual field defects (HVFD) often report difficulty detecting obstacles in the periphery on their blind side in time when moving around. Recently, a randomized controlled trial showed that the InSight-Hemianopia Compensatory Scanning Training (IH-CST) specifically improved detection of peripheral stimuli and avoiding obstacles when moving around, especially in dual task situations. Method The within-group training effects of the previously reported IH-CST are examined in an extended patient group. Performance of patients with HVFD on a pre-assessment, post-assessment and follow-up assessment and performance of a healthy control group are compared. Furthermore, it is examined whether training effects can be predicted by demographic characteristics, variables related to the visual disorder, and neuropsychological test results. Results Performance on both subjective and objective measures of mobility-related scanning was improved after training, while no evidence was found for improvement in visual functions (including visual fields), reading, visual search and dot counting. Self-reported improvement did not correlate with improvement in objective mobility performance. According to the participants, the positive effects were still present six to ten months after training. No demographic characteristics, variables related to the visual disorder, and neuropsychological test results were found to predict the size of training effect, although some inconclusive evidence was found for more improvement in patients with left-sided HVFD than in patients with right-sided HFVD. Conclusion Further support was found for a positive effect of IH-CST on detection of visual stimuli during mobility-related activities specifically. Based on the reports given by patients, these effects appear to be long-term effects. However, no conclusions can be drawn on the objective long-term training effects. PMID:27935973

Prediction and optimization of CI engine performance fuelled with Calophyllum inophyllum diesel blend using response surface methodology (RSM).

PubMed

Venugopal, Paramaguru; Kasimani, Ramesh; Chinnasamy, Suresh

2018-06-21

The transportation demand in India is increasing tremendously, which arouses the energy consumption by 4.1 to 6.1% increases each year from 2010 to 2050. In addition, the private vehicle ownership keeps on increasing almost 10% per year during the last decade and reaches 213 million tons of oil consumption in 2016. Thus, this makes India the third largest importer of crude oil in the world. Because of this problem, there is a need of promoting the alternative fuels (biodiesel) which are from different feedstocks for the transportation. This alternative fuel has better emission characteristics compared to neat diesel, hence the biodiesel can be used as direct alternative for diesel and it can also be blended with diesel to get better performance. However, the effect of compression ratio, injection timing, injection pressure, composition-blend ratio and air-fuel ratio, and the shape of the cylinder may affect the performance and emission characteristics of the diesel engine. This article deals with the effect of compression ratio in the performance of the engine while using Honne oil diesel blend and also to find out the optimum compression ratio. So the experimentations are conducted using Honne oil diesel blend-fueled CI engine at variable load conditions and at constant speed operations. In order to find out the optimum compression ratio, experiments are carried out on a single-cylinder, four-stroke variable compression ratio diesel engine, and it is found that 18:1 compression ratio gives better performance than the lower compression ratios. Engine performance tests were carried out at different compression ratio values. Using experimental data, regression model was developed and the values were predicted using response surface methodology. Then the predicted values were validated with the experimental results and a maximum error percentage of 6.057 with an average percentage of error as 3.57 were obtained. The optimum numeric factors for different responses were also selected using RSM.

Early detection of poor adherers to statins: applying individualized surveillance to pay for performance.

PubMed

Zimolzak, Andrew J; Spettell, Claire M; Fernandes, Joaquim; Fusaro, Vincent A; Palmer, Nathan P; Saria, Suchi; Kohane, Isaac S; Jonikas, Magdalena A; Mandl, Kenneth D

2013-01-01

Medication nonadherence costs $300 billion annually in the US. Medicare Advantage plans have a financial incentive to increase medication adherence among members because the Centers for Medicare and Medicaid Services (CMS) now awards substantive bonus payments to such plans, based in part on population adherence to chronic medications. We sought to build an individualized surveillance model that detects early which beneficiaries will fall below the CMS adherence threshold. This was a retrospective study of over 210,000 beneficiaries initiating statins, in a database of private insurance claims, from 2008-2011. A logistic regression model was constructed to use statin adherence from initiation to day 90 to predict beneficiaries who would not meet the CMS measure of proportion of days covered 0.8 or above, from day 91 to 365. The model controlled for 15 additional characteristics. In a sensitivity analysis, we varied the number of days of adherence data used for prediction. Lower adherence in the first 90 days was the strongest predictor of one-year nonadherence, with an odds ratio of 25.0 (95% confidence interval 23.7-26.5) for poor adherence at one year. The model had an area under the receiver operating characteristic curve of 0.80. Sensitivity analysis revealed that predictions of comparable accuracy could be made only 40 days after statin initiation. When members with 30-day supplies for their first statin fill had predictions made at 40 days, and members with 90-day supplies for their first fill had predictions made at 100 days, poor adherence could be predicted with 86% positive predictive value. To preserve their Medicare Star ratings, plan managers should identify or develop effective programs to improve adherence. An individualized surveillance approach can be used to target members who would most benefit, recognizing the tradeoff between improved model performance over time and the advantage of earlier detection.

Predicting medical students' intentions to take up rural practice after graduation.

PubMed

Jones, Michael; Humphreys, John; Prideaux, David

2009-10-01

Using a novel longitudinal tracking project, this study develops and evaluates the performance of a predictive model and index of rural medical practice intention based on the characteristics of incoming medical students. Medical school entry survey data were obtained from the Medical Schools Outcome Database (MSOD) project implemented in all Australian and New Zealand medical schools and coordinated through Medical Deans Australia and New Zealand, the representative body for the Deans of 18 Australian and two New Zealand medical schools and faculties. The medical school commencement survey collects data on students' education and family background, including rural upbringing, personal circumstances and scholarships, and on their practice intentions in terms of location and specialty. The MSOD will also allow tracking of medical graduates after graduation. Logistic regression modelling was used to develop a predictive model of rural practice intention. Split-sample validation was used to gain some insight into the stability of performance of the model. Response rates to the MSOD survey exceeded 90% on average. The model findings confirm and extend previous research examining the association of medical student characteristics with intention to take up rural medical practice. The statistically significant independent factors in the model included students' rural backgrounds, financial arrangements and intentions regarding specialist versus generalist practice upon graduation. Model performance was good, with an area under the receiver-operator characteristics curve of 0.86, and reproducible, with an area in a validation sample of 0.83. The model and related index provide important insights into individual factors associated with rural practice intention among students commencing medical studies. The model can also provide a means for optimising the use of scarce medical programme resources, thereby helping to improve the supply of rural medical practitioners. This study illustrates the power and potential of a robust, consistent, systematic longitudinal tracking project.

Advanced planning activity. [for interplanetary flight and space exploration

NASA Technical Reports Server (NTRS)

1974-01-01

Selected mission concepts for interplanetary exploration through 1985 were examined, including: (1) Jupiter orbiter performance characteristics; (2) solar electric propulsion missions to Mercury, Venus, Neptune, and Uranus; (3) space shuttle planetary missions; (4) Pioneer entry probes to Saturn and Uranus; (5) rendezvous with Comet Kohoutek and Comet Encke; (6) space tug capabilities; and (7) a Pioneer mission to Mars in 1979. Mission options, limitations, and performance predictions are assessed, along with probable configurational, boost, and propulsion requirements.

The importance of job autonomy, cognitive ability, and job-related skill for predicting role breadth and job performance.

PubMed

Morgeson, Frederick P; Delaney-Klinger, Kelly; Hemingway, Monica A

2005-03-01

Role theory suggests and empirical research has found that there is considerable variation in how broadly individuals define their jobs. We investigated the theoretically meaningful yet infrequently studied relationships between incumbent job autonomy, cognitive ability, job-related skill, role breadth, and job performance. Using multiple data sources and multiple measurement occasions in a field setting, we found that job autonomy, cognitive ability, and job-related skill were positively related to role breadth, accounting for 23% of the variance in role breadth. In addition, role breadth was positively related to job performance and was found to mediate the relationship between job autonomy, cognitive ability, job-related skill, and job performance. These results add to our understanding of the factors that predict role breadth, as well as having implications for how job aspects and individual characteristics are translated into performance outcomes and the treatment of variability in incumbent reports of job tasks.

Personal best marathon time and longest training run, not anthropometry, predict performance in recreational 24-hour ultrarunners.

PubMed

Knechtle, Beat; Knechtle, Patrizia; Rosemann, Thomas; Lepers, Romuald

2011-08-01

In recent studies, a relationship between both low body fat and low thicknesses of selected skinfolds has been demonstrated for running performance of distances from 100 m to the marathon but not in ultramarathon. We investigated the association of anthropometric and training characteristics with race performance in 63 male recreational ultrarunners in a 24-hour run using bi and multivariate analysis. The athletes achieved an average distance of 146.1 (43.1) km. In the bivariate analysis, body mass (r = -0.25), the sum of 9 skinfolds (r = -0.32), the sum of upper body skinfolds (r = -0.34), body fat percentage (r = -0.32), weekly kilometers ran (r = 0.31), longest training session before the 24-hour run (r = 0.56), and personal best marathon time (r = -0.58) were related to race performance. Stepwise multiple regression showed that both the longest training session before the 24-hour run (p = 0.0013) and the personal best marathon time (p = 0.0015) had the best correlation with race performance. Performance in these 24-hour runners may be predicted (r2 = 0.46) by the following equation: Performance in a 24-hour run, km) = 234.7 + 0.481 (longest training session before the 24-hour run, km) - 0.594 (personal best marathon time, minutes). For practical applications, training variables such as volume and intensity were associated with performance but not anthropometric variables. To achieve maximum kilometers in a 24-hour run, recreational ultrarunners should have a personal best marathon time of ∼3 hours 20 minutes and complete a long training run of ∼60 km before the race, whereas anthropometric characteristics such as low body fat or low skinfold thicknesses showed no association with performance.

Interaction between personality traits and cerebrospinal fluid biomarkers of Alzheimer's disease pathology modulates cognitive performance.

PubMed

Tautvydaitė, Domilė; Kukreja, Deepti; Antonietti, Jean-Philippe; Henry, Hugues; von Gunten, Armin; Popp, Julius

2017-02-02

During adulthood, personality characteristics may contribute to the individual capacity to compensate the impact of developing cerebral Alzheimer's disease (AD) pathology on cognitive impairment in later life. In this study we aimed to investigate whether and how premorbid personality traits interact with cerebrospinal fluid (CSF) markers of AD pathology to predict cognitive performance in subjects with mild cognitive impairment or mild AD dementia and in participants with normal cognition. One hundred and ten subjects, of whom 66 were patients with mild cognitive impairment or mild AD dementia and 44 were healthy controls, had a comprehensive medical and neuropsychological examination as well as lumbar puncture to measure CSF biomarkers of AD pathology (amyloid beta 1-42 , phosphorylated tau and total-tau). Participants' proxies completed the Revised NEO Personality Inventory, Form R to retrospectively assess subjects' premorbid personality. In hierarchical multivariate regression analyses, including age, gender, education, APOEε4 status and cognitive level, premorbid neuroticism, conscientiousness and agreeableness modulated the effect of CSF biomarkers on cognitive performance. Low premorbid openness independently predicted lower levels of cognitive functioning after controlling for biomarker concentrations. Our findings suggest that specific premorbid personality traits are associated with cerebral AD pathology and modulate its impact on cognitive performance. Considering personality characteristics may help to appraise a person's cognitive reserve and the risk of cognitive decline in later life.

Analysis and test of a 16-foot radial rib reflector developmental model

NASA Technical Reports Server (NTRS)

Birchenough, Shawn A.

1989-01-01

Analytical and experimental modal tests were performed to determine the vibrational characteristics of a 16-foot diameter radial rib reflector model. Single rib analyses and experimental tests provided preliminary information relating to the reflector. A finite element model predicted mode shapes and frequencies of the reflector. The analyses correlated well with the experimental tests, verifying the modeling method used. The results indicate that five related, characteristic mode shapes form a group. The frequencies of the modes are determined by the relative phase of the radial ribs.

Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements.

PubMed

Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2015-08-01

Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology.

Computing Operating Characteristics Of Bearing/Shaft Systems

NASA Technical Reports Server (NTRS)

Moore, James D.

1996-01-01

SHABERTH computer program predicts operating characteristics of bearings in multibearing load-support system. Lubricated and nonlubricated bearings modeled. Calculates loads, torques, temperatures, and fatigue lives of ball and/or roller bearings on single shaft. Provides for analysis of reaction of system to termination of supply of lubricant to bearings and other lubricated mechanical elements. Valuable in design and analysis of shaft/bearing systems. Two versions of SHABERTH available. Cray version (LEW-14860), "Computing Thermal Performances Of Shafts and Bearings". IBM PC version (MFS-28818), written for IBM PC-series and compatible computers running MS-DOS.

F-15/nonaxisymmetric nozzle system integration study support program

NASA Technical Reports Server (NTRS)

Stevens, H. L.

1978-01-01

Nozzle and cooling methods were defined and analyzed to provide a viable system for demonstration 2-D nozzle technology on the F-15 aircraft. Two candidate cooling systems applied to each nozzle were evaluated. The F-100 engine mount and case modifications requirements were analyzed and the actuation and control system requirements for two dimensional nozzles were defined. Nozzle performance changes relative to the axisymmetric baseline nozzle were evaluated and performance and weight characteristics for axisymmetric reference configurations were estimated. The infrared radiation characteristics of these nozzles installed on the F-100 engine were predicted. A full scale development plan with associated costs to carry the F100 engine/two-dimensional (2-D) nozzle through flight tests was defined.

Unsteady aerodynamic analysis of space shuttle vehicles. Part 2: Steady and unsteady aerodynamics of sharp-edged delta wings

NASA Technical Reports Server (NTRS)

Ericsson, L. E.; Reding, J. P.

1973-01-01

An analysis of the steady and unsteady aerodynamics of sharp-edged slender wings has been performed. The results show that slender wing theory can be modified to give the potential flow static and dynamic characteristics in incompressible flow. A semiempirical approximation is developed for the vortex-induced loads, and it is shown that the analytic approximation for sharp-edged slender wings gives good prediction of experimentally determined steady and unsteady aerodynamics at M = 0 and M = 1. The predictions are good not only for delta wings but also for so-called arrow and diamond wings. The results indicate that the effects of delta planform lifting surfaces can be included in a simple manner when determining elastic launch vehicle dynamic characteristics. For Part 1 see (N73-32763).

Validation of the Combined Comorbidity Index of Charlson and Elixhauser to Predict 30-Day Mortality Across ICD-9 and ICD-10.

PubMed

Simard, Marc; Sirois, Caroline; Candas, Bernard

2018-05-01

To validate and compare performance of an International Classification of Diseases, tenth revision (ICD-10) version of a combined comorbidity index merging conditions of Charlson and Elixhauser measures against individual measures in the prediction of 30-day mortality. To select a weight derivation method providing optimal performance across ICD-9 and ICD-10 coding systems. Using 2 adult population-based cohorts of patients with hospital admissions in ICD-9 (2005, n=337,367) and ICD-10 (2011, n=348,820), we validated a combined comorbidity index by predicting 30-day mortality with logistic regression. To appreciate performance of the Combined index and both individual measures, factors impacting indices performance such as population characteristics and weight derivation methods were accounted for. We applied 3 scoring methods (Van Walraven, Schneeweiss, and Charlson) and determined which provides best predictive values. Combined index [c-statistics: 0.853 (95% confidence interval: CI, 0.848-0.856)] performed better than original Charlson [0.841 (95% CI, 0.835-0.844)] or Elixhauser [0.841 (95% CI, 0.837-0.844)] measures on ICD-10 cohort. All weight derivation methods provided close high discrimination results for the Combined index (Van Walraven: 0.852, Schneeweiss: 0.851, Charlson: 0.849). Results were consistent across both coding systems. The Combined index remains valid with both ICD-9 and ICD-10 coding systems and the 3 weight derivation methods evaluated provided consistent high performance across those coding systems.

Does trait affectivity predict work-to-family conflict and enrichment beyond job characteristics?

PubMed

Tement, Sara; Korunka, Christian

2013-01-01

The present study examines whether negative and positive affectivity (NA and PA, respectively) predict different forms of work-to-family conflict (WFC-time, WFC-strain, WFC-behavior) and enrichment (WFE-development, WFE-affect, WFE-capital) beyond job characteristics (workload, autonomy, variety, workplace support). Furthermore, interactions between job characteristics and trait affectivity while predicting WFC and WFE were examined. Using a large sample of Slovenian employees (N = 738), NA and PA were found to explain variance in WFC as well as in WFE above and beyond job characteristics. More precisely, NA significantly predicted WFC, whereas PA significantly predicted WFE. In addition, several interactive effects were found to predict forms of WFC and WFE. These results highlight the importance of trait affectivity in work-family research. They provide further support for the crucial impact of job characteristics as well.

Computer modeling of fan-exit-splitter spacing effects on F100 response to distortion

NASA Technical Reports Server (NTRS)

Shaw, M.; Murdoch, R. W.

1982-01-01

The distortion response of the F100(3) engine was effected by the fan exit splitter configuration. The sensitivity for a proximate splitter fan is calculated to be slightly greater than a remote splitter configuration with identical airfoils. Predicted response was based upon a multiple segment parallel compressor Model modified to include a bypass ratio representation that effects the performance characteristics of the last rotor and intermediate case struts. The predicted distortion response required an accurate definition of row pre- and post-stall undistorted operation.

A predictive model of human performance.

NASA Technical Reports Server (NTRS)

Walters, R. F.; Carlson, L. D.

1971-01-01

An attempt is made to develop a model describing the overall responses of humans to exercise and environmental stresses for prediction of exhaustion vs an individual's physical characteristics. The principal components of the model are a steady state description of circulation and a dynamic description of thermal regulation. The circulatory portion of the system accepts changes in work load and oxygen pressure, while the thermal portion is influenced by external factors of ambient temperature, humidity and air movement, affecting skin blood flow. The operation of the model is discussed and its structural details are given.

Loads and aeroelasticity division research and technology accomplishments for FY 1983 and plans for FY 1984

NASA Technical Reports Server (NTRS)

Gardner, J. E.; Dixon, S. C.

1984-01-01

Research was done in the following areas: development and validation of solution algorithms, modeling techniques, integrated finite elements for flow-thermal-structural analysis and design, optimization of aircraft and spacecraft for the best performance, reduction of loads and increase in the dynamic structural stability of flexible airframes by the use of active control, methods for predicting steady and unsteady aerodynamic loads and aeroelastic characteristics of flight vehicles with emphasis on the transonic range, and methods for predicting and reducing helicoper vibrations.

Relationship among performance, carcass, and feed efficiency characteristics, and their ability to predict economic value in the feedlot.

PubMed

Retallick, K M; Faulkner, D B; Rodriguez-Zas, S L; Nkrumah, J D; Shike, D W

2013-12-01

A 4-yr study was conducted using 736 steers of known Angus, Simmental, or Simmental × Angus genetics to determine performance, carcass, and feed efficiency factors that explained variation in economic performance. Steers were pen fed and individual DMI was recorded using a GrowSafe automated feeding system (GrowSafe Systems Ltd., Airdrie, Alberta, Canada). Steers consumed a similar diet and received similar management each year. The objectives of this study were to: 1) determine current economic value of feed efficiency and 2) identify performance, carcass, and feed efficiency characteristics that predict: carcass value, profit, cost of gain, and feed costs. Economic data used were from 2011 values. Feed efficiency values investigated were: feed conversion ratio (FCR; feed to gain), residual feed intake (RFI), residual BW gain (RG), and residual intake and BW gain (RIG). Dependent variables were carcass value ($/steer), profit ($/steer), feed costs ($/steer • d(-1)), and cost of gain ($/kg). Independent variables were year, DMI, ADG, HCW, LM area, marbling, yield grade, dam breed, and sire breed. A 10% improvement in RG (P < 0.05) yielded the lowest cost of gain at $0.09/kg and highest carcass value at $17.92/steer. Carcass value increased (P < 0.05) as feed efficiency improved for FCR, RG, and RIG. Profit increased with a 10% improvement in feed efficiency (P < 0.05) with FCR at $34.65/steer, RG at $31.21/steer, RIG at $21.66/steer, and RFI at $11.47/steer. The carcass value prediction model explained 96% of the variation among carcasses and included HCW, marbling score, and yield grade. Average daily gain, marbling score, yield grade, DMI, HCW, and year born constituted 81% of the variation for prediction of profit. Eighty-five percent of the variation in cost of gain was explained by ADG, DMI, HCW, and year. Prediction equations were developed that excluded ADG and DMI, and included feed efficiency values. Using these equations, cost of gain was explained primarily by FCR (R(2) = 0.71). Seventy-three percent of profitability was explained, with 55% being accounted for by RG and marbling. These prediction equations represent the relative importance of factors contributing to economic success in feedlot cattle based on current prices.

Development of a Multicomponent Prediction Model for Acute Esophagitis in Lung Cancer Patients Receiving Chemoradiotherapy

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

De Ruyck, Kim, E-mail: kim.deruyck@UGent.be; Sabbe, Nick; Oberije, Cary

2011-10-01

Purpose: To construct a model for the prediction of acute esophagitis in lung cancer patients receiving chemoradiotherapy by combining clinical data, treatment parameters, and genotyping profile. Patients and Methods: Data were available for 273 lung cancer patients treated with curative chemoradiotherapy. Clinical data included gender, age, World Health Organization performance score, nicotine use, diabetes, chronic disease, tumor type, tumor stage, lymph node stage, tumor location, and medical center. Treatment parameters included chemotherapy, surgery, radiotherapy technique, tumor dose, mean fractionation size, mean and maximal esophageal dose, and overall treatment time. A total of 332 genetic polymorphisms were considered in 112 candidatemore » genes. The predicting model was achieved by lasso logistic regression for predictor selection, followed by classic logistic regression for unbiased estimation of the coefficients. Performance of the model was expressed as the area under the curve of the receiver operating characteristic and as the false-negative rate in the optimal point on the receiver operating characteristic curve. Results: A total of 110 patients (40%) developed acute esophagitis Grade {>=}2 (Common Terminology Criteria for Adverse Events v3.0). The final model contained chemotherapy treatment, lymph node stage, mean esophageal dose, gender, overall treatment time, radiotherapy technique, rs2302535 (EGFR), rs16930129 (ENG), rs1131877 (TRAF3), and rs2230528 (ITGB2). The area under the curve was 0.87, and the false-negative rate was 16%. Conclusion: Prediction of acute esophagitis can be improved by combining clinical, treatment, and genetic factors. A multicomponent prediction model for acute esophagitis with a sensitivity of 84% was constructed with two clinical parameters, four treatment parameters, and four genetic polymorphisms.« less

The role of imaging based prostate biopsy morphology in a data fusion paradigm for transducing prognostic predictions

NASA Astrophysics Data System (ADS)

Khan, Faisal M.; Kulikowski, Casimir A.

2016-03-01

A major focus area for precision medicine is in managing the treatment of newly diagnosed prostate cancer patients. For patients with a positive biopsy, clinicians aim to develop an individualized treatment plan based on a mechanistic understanding of the disease factors unique to each patient. Recently, there has been a movement towards a multi-modal view of the cancer through the fusion of quantitative information from multiple sources, imaging and otherwise. Simultaneously, there have been significant advances in machine learning methods for medical prognostics which integrate a multitude of predictive factors to develop an individualized risk assessment and prognosis for patients. An emerging area of research is in semi-supervised approaches which transduce the appropriate survival time for censored patients. In this work, we apply a novel semi-supervised approach for support vector regression to predict the prognosis for newly diagnosed prostate cancer patients. We integrate clinical characteristics of a patient's disease with imaging derived metrics for biomarker expression as well as glandular and nuclear morphology. In particular, our goal was to explore the performance of nuclear and glandular architecture within the transduction algorithm and assess their predictive power when compared with the Gleason score manually assigned by a pathologist. Our analysis in a multi-institutional cohort of 1027 patients indicates that not only do glandular and morphometric characteristics improve the predictive power of the semi-supervised transduction algorithm; they perform better when the pathological Gleason is absent. This work represents one of the first assessments of quantitative prostate biopsy architecture versus the Gleason grade in the context of a data fusion paradigm which leverages a semi-supervised approach for risk prognosis.

Simple Scoring System to Predict In-Hospital Mortality After Surgery for Infective Endocarditis.

PubMed

Gatti, Giuseppe; Perrotti, Andrea; Obadia, Jean-François; Duval, Xavier; Iung, Bernard; Alla, François; Chirouze, Catherine; Selton-Suty, Christine; Hoen, Bruno; Sinagra, Gianfranco; Delahaye, François; Tattevin, Pierre; Le Moing, Vincent; Pappalardo, Aniello; Chocron, Sidney

2017-07-20

Aspecific scoring systems are used to predict the risk of death postsurgery in patients with infective endocarditis (IE). The purpose of the present study was both to analyze the risk factors for in-hospital death, which complicates surgery for IE, and to create a mortality risk score based on the results of this analysis. Outcomes of 361 consecutive patients (mean age, 59.1±15.4 years) who had undergone surgery for IE in 8 European centers of cardiac surgery were recorded prospectively, and a risk factor analysis (multivariable logistic regression) for in-hospital death was performed. The discriminatory power of a new predictive scoring system was assessed with the receiver operating characteristic curve analysis. Score validation procedures were carried out. Fifty-six (15.5%) patients died postsurgery. BMI >27 kg/m 2 (odds ratio [OR], 1.79; P =0.049), estimated glomerular filtration rate <50 mL/min (OR, 3.52; P <0.0001), New York Heart Association class IV (OR, 2.11; P =0.024), systolic pulmonary artery pressure >55 mm Hg (OR, 1.78; P =0.032), and critical state (OR, 2.37; P =0.017) were independent predictors of in-hospital death. A scoring system was devised to predict in-hospital death postsurgery for IE (area under the receiver operating characteristic curve, 0.780; 95% CI, 0.734-0.822). The score performed better than 5 of 6 scoring systems for in-hospital death after cardiac surgery that were considered. A simple scoring system based on risk factors for in-hospital death was specifically created to predict mortality risk postsurgery in patients with IE. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Value of lower respiratory tract surveillance cultures to predict bacterial pathogens in ventilator-associated pneumonia: systematic review and diagnostic test accuracy meta-analysis.

PubMed

Brusselaers, Nele; Labeau, Sonia; Vogelaers, Dirk; Blot, Stijn

2013-03-01

In ventilator-associated pneumonia (VAP), early appropriate antimicrobial therapy may be hampered by involvement of multidrug-resistant (MDR) pathogens. A systematic review and diagnostic test accuracy meta-analysis were performed to analyse whether lower respiratory tract surveillance cultures accurately predict the causative pathogens of subsequent VAP in adult patients. Selection and assessment of eligibility were performed by three investigators by mutual consideration. Of the 525 studies retrieved, 14 were eligible for inclusion (all in English; published since 1994), accounting for 791 VAP episodes. The following data were collected: study and population characteristics; in- and exclusion criteria; diagnostic criteria for VAP; microbiological workup of surveillance and diagnostic VAP cultures. Sub-analyses were conducted for VAP caused by Staphylococcus aureus, Pseudomonas spp., and Acinetobacter spp., MDR microorganisms, frequency of sampling, and consideration of all versus the most recent surveillance cultures. The meta-analysis showed a high accuracy of surveillance cultures, with pooled sensitivities up to 0.75 and specificities up to 0.92 in culture-positive VAP. The area under the curve (AUC) of the hierarchical summary receiver-operating characteristic curve demonstrates moderate accuracy (AUC: 0.90) in predicting multidrug resistance. A sampling frequency of >2/week (sensitivity 0.79; specificity 0.96) and consideration of only the most recent surveillance culture (sensitivity 0.78; specificity 0.96) are associated with a higher accuracy of prediction. This study provides evidence for the benefit of surveillance cultures in predicting MDR bacterial pathogens in VAP. However, clinical and statistical heterogeneity, limited samples sizes, and bias remain important limitations of this meta-analysis.

Predicting distant failure in early stage NSCLC treated with SBRT using clinical parameters.

PubMed

Zhou, Zhiguo; Folkert, Michael; Cannon, Nathan; Iyengar, Puneeth; Westover, Kenneth; Zhang, Yuanyuan; Choy, Hak; Timmerman, Robert; Yan, Jingsheng; Xie, Xian-J; Jiang, Steve; Wang, Jing

2016-06-01

The aim of this study is to predict early distant failure in early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT) using clinical parameters by machine learning algorithms. The dataset used in this work includes 81 early stage NSCLC patients with at least 6months of follow-up who underwent SBRT between 2006 and 2012 at a single institution. The clinical parameters (n=18) for each patient include demographic parameters, tumor characteristics, treatment fraction schemes, and pretreatment medications. Three predictive models were constructed based on different machine learning algorithms: (1) artificial neural network (ANN), (2) logistic regression (LR) and (3) support vector machine (SVM). Furthermore, to select an optimal clinical parameter set for the model construction, three strategies were adopted: (1) clonal selection algorithm (CSA) based selection strategy; (2) sequential forward selection (SFS) method; and (3) statistical analysis (SA) based strategy. 5-cross-validation is used to validate the performance of each predictive model. The accuracy was assessed by area under the receiver operating characteristic (ROC) curve (AUC), sensitivity and specificity of the system was also evaluated. The AUCs for ANN, LR and SVM were 0.75, 0.73, and 0.80, respectively. The sensitivity values for ANN, LR and SVM were 71.2%, 72.9% and 83.1%, while the specificity values for ANN, LR and SVM were 59.1%, 63.6% and 63.6%, respectively. Meanwhile, the CSA based strategy outperformed SFS and SA in terms of AUC, sensitivity and specificity. Based on clinical parameters, the SVM with the CSA optimal parameter set selection strategy achieves better performance than other strategies for predicting distant failure in lung SBRT patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Pretransplantation soluble CD30 level as a predictor of acute rejection in kidney transplantation: a meta-analysis.

PubMed

Chen, Yile; Tai, Qiang; Hong, Shaodong; Kong, Yuan; Shang, Yushu; Liang, Wenhua; Guo, Zhiyong; He, Xiaoshun

2012-11-15

The question of whether high pretransplantation soluble CD30 (sCD30) level can be a predictor of kidney transplant acute rejection (AR) is under debate. Herein, we performed a meta-analysis on the predictive efficacy of sCD30 for AR in renal transplantation. PubMed (1966-2012), EMBASE (1988-2012), and Web of Science (1986-2012) databases were searched for studies concerning the predictive efficacy of sCD30 for AR after kidney transplantation. After a careful review of eligible studies, sensitivity, specificity, and other measures of the accuracy of sCD30 were pooled. A summary receiver operating characteristic curve was used to represent the overall test performance. Twelve studies enrolling 2507 patients met the inclusion criteria. The pooled estimates for pretransplantation sCD30 in prediction of allograft rejection risk were poor, with a sensitivity of 0.70 (95% confidence interval (CI), 0.66-0.74), a specificity of 0.48 (95% CI, 0.46-0.50), a positive likelihood ratio of 1.35 (95% CI, 1.20-1.53), a negative likelihood ratio of 0.68 (95% CI, 0.55-0.84), and a diagnostic odds ratio of 2.07 (95% CI, 1.54-2.80). The area under curve of the summary receiver operating characteristic curve was 0.60, indicating poor overall accuracy of the serum sCD30 level in the prediction of patients at risk for AR. The results of the meta-analysis show that the accuracy of pretransplantation sCD30 for predicting posttransplantation AR was poor. Prospective studies are needed to clarify the usefulness of this test for identifying risks of AR in transplant recipients.

Experimental validation of a numerical model for subway induced vibrations

NASA Astrophysics Data System (ADS)

Gupta, S.; Degrande, G.; Lombaert, G.

2009-04-01

This paper presents the experimental validation of a coupled periodic finite element-boundary element model for the prediction of subway induced vibrations. The model fully accounts for the dynamic interaction between the train, the track, the tunnel and the soil. The periodicity or invariance of the tunnel and the soil in the longitudinal direction is exploited using the Floquet transformation, which allows for an efficient formulation in the frequency-wavenumber domain. A general analytical formulation is used to compute the response of three-dimensional invariant or periodic media that are excited by moving loads. The numerical model is validated by means of several experiments that have been performed at a site in Regent's Park on the Bakerloo line of London Underground. Vibration measurements have been performed on the axle boxes of the train, on the rail, the tunnel invert and the tunnel wall, and in the free field, both at the surface and at a depth of 15 m. Prior to these vibration measurements, the dynamic soil characteristics and the track characteristics have been determined. The Bakerloo line tunnel of London Underground has been modelled using the coupled periodic finite element-boundary element approach and free field vibrations due to the passage of a train at different speeds have been predicted and compared to the measurements. The correspondence between the predicted and measured response in the tunnel is reasonably good, although some differences are observed in the free field. The discrepancies are explained on the basis of various uncertainties involved in the problem. The variation in the response with train speed is similar for the measurements as well as the predictions. This study demonstrates the applicability of the coupled periodic finite element-boundary element model to make realistic predictions of the vibrations from underground railways.

Personalized mortality prediction driven by electronic medical data and a patient similarity metric.

PubMed

Lee, Joon; Maslove, David M; Dubin, Joel A

2015-01-01

Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our novel medical data analytics contributes to meaningful use of EMR data.

Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric

PubMed Central

Lee, Joon; Maslove, David M.; Dubin, Joel A.

2015-01-01

Background Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. Methods and Findings We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. Conclusions The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our novel medical data analytics contributes to meaningful use of EMR data. PMID:25978419

Validated Risk Score for Predicting 6-Month Mortality in Infective Endocarditis.

PubMed

Park, Lawrence P; Chu, Vivian H; Peterson, Gail; Skoutelis, Athanasios; Lejko-Zupa, Tatjana; Bouza, Emilio; Tattevin, Pierre; Habib, Gilbert; Tan, Ren; Gonzalez, Javier; Altclas, Javier; Edathodu, Jameela; Fortes, Claudio Querido; Siciliano, Rinaldo Focaccia; Pachirat, Orathai; Kanj, Souha; Wang, Andrew

2016-04-18

Host factors and complications have been associated with higher mortality in infective endocarditis (IE). We sought to develop and validate a model of clinical characteristics to predict 6-month mortality in IE. Using a large multinational prospective registry of definite IE (International Collaboration on Endocarditis [ICE]-Prospective Cohort Study [PCS], 2000-2006, n=4049), a model to predict 6-month survival was developed by Cox proportional hazards modeling with inverse probability weighting for surgery treatment and was internally validated by the bootstrapping method. This model was externally validated in an independent prospective registry (ICE-PLUS, 2008-2012, n=1197). The 6-month mortality was 971 of 4049 (24.0%) in the ICE-PCS cohort and 342 of 1197 (28.6%) in the ICE-PLUS cohort. Surgery during the index hospitalization was performed in 48.1% and 54.0% of the cohorts, respectively. In the derivation model, variables related to host factors (age, dialysis), IE characteristics (prosthetic or nosocomial IE, causative organism, left-sided valve vegetation), and IE complications (severe heart failure, stroke, paravalvular complication, and persistent bacteremia) were independently associated with 6-month mortality, and surgery was associated with a lower risk of mortality (Harrell's C statistic 0.715). In the validation model, these variables had similar hazard ratios (Harrell's C statistic 0.682), with a similar, independent benefit of surgery (hazard ratio 0.74, 95% CI 0.62-0.89). A simplified risk model was developed by weight adjustment of these variables. Six-month mortality after IE is ≈25% and is predicted by host factors, IE characteristics, and IE complications. Surgery during the index hospitalization is associated with lower mortality but is performed less frequently in the highest risk patients. A simplified risk model may be used to identify specific risk subgroups in IE. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Improving predictions of protein-protein interfaces by combining amino acid-specific classifiers based on structural and physicochemical descriptors with their weighted neighbor averages.

PubMed

de Moraes, Fábio R; Neshich, Izabella A P; Mazoni, Ivan; Yano, Inácio H; Pereira, José G C; Salim, José A; Jardine, José G; Neshich, Goran

2014-01-01

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html).

Improving Predictions of Protein-Protein Interfaces by Combining Amino Acid-Specific Classifiers Based on Structural and Physicochemical Descriptors with Their Weighted Neighbor Averages

PubMed Central

de Moraes, Fábio R.; Neshich, Izabella A. P.; Mazoni, Ivan; Yano, Inácio H.; Pereira, José G. C.; Salim, José A.; Jardine, José G.; Neshich, Goran

2014-01-01

Protein-protein interactions are involved in nearly all regulatory processes in the cell and are considered one of the most important issues in molecular biology and pharmaceutical sciences but are still not fully understood. Structural and computational biology contributed greatly to the elucidation of the mechanism of protein interactions. In this paper, we present a collection of the physicochemical and structural characteristics that distinguish interface-forming residues (IFR) from free surface residues (FSR). We formulated a linear discriminative analysis (LDA) classifier to assess whether chosen descriptors from the BlueStar STING database (http://www.cbi.cnptia.embrapa.br/SMS/) are suitable for such a task. Receiver operating characteristic (ROC) analysis indicates that the particular physicochemical and structural descriptors used for building the linear classifier perform much better than a random classifier and in fact, successfully outperform some of the previously published procedures, whose performance indicators were recently compared by other research groups. The results presented here show that the selected set of descriptors can be utilized to predict IFRs, even when homologue proteins are missing (particularly important for orphan proteins where no homologue is available for comparative analysis/indication) or, when certain conformational changes accompany interface formation. The development of amino acid type specific classifiers is shown to increase IFR classification performance. Also, we found that the addition of an amino acid conservation attribute did not improve the classification prediction. This result indicates that the increase in predictive power associated with amino acid conservation is exhausted by adequate use of an extensive list of independent physicochemical and structural parameters that, by themselves, fully describe the nano-environment at protein-protein interfaces. The IFR classifier developed in this study is now integrated into the BlueStar STING suite of programs. Consequently, the prediction of protein-protein interfaces for all proteins available in the PDB is possible through STING_interfaces module, accessible at the following website: (http://www.cbi.cnptia.embrapa.br/SMS/predictions/index.html). PMID:24489849

Prediction of Moisture Content for Congou Black Tea Withering Leaves Using Image Features and Nonlinear Method.

PubMed

Liang, Gaozhen; Dong, Chunwang; Hu, Bin; Zhu, Hongkai; Yuan, Haibo; Jiang, Yongwen; Hao, Guoshuang

2018-05-18

Withering is the first step in the processing of congou black tea. With respect to the deficiency of traditional water content detection methods, a machine vision based NDT (Non Destructive Testing) method was established to detect the moisture content of withered leaves. First, according to the time sequences using computer visual system collected visible light images of tea leaf surfaces, and color and texture characteristics are extracted through the spatial changes of colors. Then quantitative prediction models for moisture content detection of withered tea leaves was established through linear PLS (Partial Least Squares) and non-linear SVM (Support Vector Machine). The results showed correlation coefficients higher than 0.8 between the water contents and green component mean value (G), lightness component mean value (L * ) and uniformity (U), which means that the extracted characteristics have great potential to predict the water contents. The performance parameters as correlation coefficient of prediction set (Rp), root-mean-square error of prediction (RMSEP), and relative standard deviation (RPD) of the SVM prediction model are 0.9314, 0.0411 and 1.8004, respectively. The non-linear modeling method can better describe the quantitative analytical relations between the image and water content. With superior generalization and robustness, the method would provide a new train of thought and theoretical basis for the online water content monitoring technology of automated production of black tea.

Predicting protein function and other biomedical characteristics with heterogeneous ensembles

PubMed Central

Whalen, Sean; Pandey, Om Prakash

2015-01-01

Prediction problems in biomedical sciences, including protein function prediction (PFP), are generally quite difficult. This is due in part to incomplete knowledge of the cellular phenomenon of interest, the appropriateness and data quality of the variables and measurements used for prediction, as well as a lack of consensus regarding the ideal predictor for specific problems. In such scenarios, a powerful approach to improving prediction performance is to construct heterogeneous ensemble predictors that combine the output of diverse individual predictors that capture complementary aspects of the problems and/or datasets. In this paper, we demonstrate the potential of such heterogeneous ensembles, derived from stacking and ensemble selection methods, for addressing PFP and other similar biomedical prediction problems. Deeper analysis of these results shows that the superior predictive ability of these methods, especially stacking, can be attributed to their attention to the following aspects of the ensemble learning process: (i) better balance of diversity and performance, (ii) more effective calibration of outputs and (iii) more robust incorporation of additional base predictors. Finally, to make the effective application of heterogeneous ensembles to large complex datasets (big data) feasible, we present DataSink, a distributed ensemble learning framework, and demonstrate its sound scalability using the examined datasets. DataSink is publicly available from https://github.com/shwhalen/datasink. PMID:26342255

Effects of transionospheric signal decorrelation on Global Navigation Satellite Systems (GNSS) performance studied from irregularity dynamics around the northern crest of the EIA

NASA Astrophysics Data System (ADS)

Das, T.; Roy, B.; Paul, A.

2014-10-01

Transionospheric satellite navigation links operate primarily at L band and are frequently subject to severe degradation of performances arising out of ionospheric irregularities. Various characteristic features of equatorial ionospheric irregularity bubbles like the drift velocity, characteristic velocity, decorrelation time, and decorrelation distance can be determined using spaced aerial measurements at VHF. These parameters measured at VHF from a station Calcutta situated near the northern crest of the Equatorial Ionization Anomaly (EIA) in the geophysically sensitive Indian longitude sector have been correlated with L band scintillation indices and GPS position accuracy parameters for identifying possible proxies to L band scintillations. Good correspondences have been observed between decorrelation times and distances at VHF with GPS S4 and Position Dilution of Precision during periods of GPS scintillations (S4 > 0.3) for February-April 2011, August-October 2011, and February-April 2012. A functional relation has been developed between irregularity drift velocity measured at VHF and S4 at L band during February-April 2011, and validation of measured S4 and predicted values performed during August-October 2011 and February-April 2012. Significant improvement in L band scintillation prediction and consequent navigational accuracy will result using such relations derived from VHF irregularity measurements which are much simpler and inexpensive.

When they listen and when they watch: Pianists’ use of nonverbal audio and visual cues during duet performance

PubMed Central

Goebl, Werner

2015-01-01

Nonverbal auditory and visual communication helps ensemble musicians predict each other’s intentions and coordinate their actions. When structural characteristics of the music make predicting co-performers’ intentions difficult (e.g., following long pauses or during ritardandi), reliance on incoming auditory and visual signals may change. This study tested whether attention to visual cues during piano–piano and piano–violin duet performance increases in such situations. Pianists performed the secondo part to three duets, synchronizing with recordings of violinists or pianists playing the primo parts. Secondos’ access to incoming audio and visual signals and to their own auditory feedback was manipulated. Synchronization was most successful when primo audio was available, deteriorating when primo audio was removed and only cues from primo visual signals were available. Visual cues were used effectively following long pauses in the music, however, even in the absence of primo audio. Synchronization was unaffected by the removal of secondos’ own auditory feedback. Differences were observed in how successfully piano–piano and piano–violin duos synchronized, but these effects of instrument pairing were not consistent across pieces. Pianists’ success at synchronizing with violinists and other pianists is likely moderated by piece characteristics and individual differences in the clarity of cueing gestures used. PMID:26279610

Preliminary dynamic tests of a flight-type ejector

NASA Technical Reports Server (NTRS)

Drummond, Colin K.

1992-01-01

A thrust augmenting ejector was tested to provide experimental data to assist in the assessment of theoretical models to predict duct and ejector fluid-dynamic characteristics. Eleven full-scale thrust augmenting ejector tests were conducted in which a rapid increase in the ejector nozzle pressure ratio was effected through a unique facility, bypass/burst-disk subsystem. The present work examines two cases representative of the test performance window. In the first case, the primary nozzle pressure ration (NPR) increased 36 percent from one unchoked (NPR = 1.29) primary flow condition to another (NPR = 1.75) over a 0.15 second interval. The second case involves choked primary flow conditions, where a 17 percent increase in primary nozzle flowrate (from NPR = 2.35 to NPR = 2.77) occurred over approximately 0.1 seconds. Although the real-time signal measurements support qualitative remarks on ejector performance, extracting quantitative ejector dynamic response was impeded by excessive aerodynamic noise and thrust stand dynamic (resonance) characteristics. It does appear, however, that a quasi-steady performance assumption is valid for this model with primary nozzle pressure increased on the order of 50 lb(sub f)/s. Transient signal treatment of the present dataset is discussed and initial interpretations of the results are compared with theoretical predictions for a similar Short Takeoff and Vertical Landing (STOVL) ejector model.

Tests for predicting complications of pre-eclampsia: A protocol for systematic reviews

PubMed Central

Thangaratinam, Shakila; Coomarasamy, Arri; Sharp, Steve; O'Mahony, Fidelma; O'Brien, Shaughn; Ismail, Khaled MK; Khan, Khalid S

2008-01-01

Background Pre-eclampsia is associated with several complications. Early prediction of complications and timely management is needed for clinical care of these patients to avert fetal and maternal mortality and morbidity. There is a need to identify best testing strategies in pre eclampsia to identify the women at increased risk of complications. We aim to determine the accuracy of various tests to predict complications of pre-eclampsia by systematic quantitative reviews. Method We performed extensive search in MEDLINE (1951–2004), EMBASE (1974–2004) and also will also include manual searches of bibliographies of primary and review articles. An initial search has revealed 19500 citations. Two reviewers will independently select studies and extract data on study characteristics, quality and accuracy. Accuracy data will be used to construct 2 × 2 tables. Data synthesis will involve assessment for heterogeneity and appropriately pooling of results to produce summary Receiver Operating Characteristics (ROC) curve and summary likelihood ratios. Discussion This review will generate predictive information and integrate that with therapeutic effectiveness to determine the absolute benefit and harm of available therapy in reducing complications in women with pre-eclampsia. PMID:18694494

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

PubMed Central

Tang, Haijing; Liang, Yu; Huang, Zhongnan; Wang, Taoyi; He, Lin; Du, Yicong; Ding, Gangyi

2016-01-01

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction. PMID:27872637