WorldWideScience

Sample records for significantly predicted performance

  1. The Real World Significance of Performance Prediction

    Science.gov (United States)

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  2. Parameter definition using vibration prediction software leads to significant drilling performance improvements

    Energy Technology Data Exchange (ETDEWEB)

    Amorim, Dalmo; Hanley, Chris Hanley; Fonseca, Isaac; Santos, Juliana [National Oilwell Varco, Houston TX (United States); Leite, Daltro J.; Borella, Augusto; Gozzi, Danilo [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil)

    2012-07-01

    The understanding and mitigation of downhole vibration has been a heavily researched subject in the oil industry as it results in more expensive drilling operations, as vibrations significantly diminish the amount of effective drilling energy available to the bit and generate forces that can push the bit or the Bottom Hole Assembly (BHA) off its concentric axis of rotation, producing high magnitude impacts with the borehole wall. In order to drill ahead, a sufficient amount of energy must be supplied by the rig to overcome the resistance of the drilling system, including the reactive torque of the system, drag forces, fluid pressure losses and energy dissipated by downhole vibrations, then providing the bit with the energy required to fail the rock. If the drill string enters resonant modes of vibration, not only does it decreases the amount of available energy to drill, but increases the potential for catastrophic downhole equipment and drilling bit failures. In this sense, the mitigation of downhole vibrations will result in faster, smoother, and cheaper drilling operations. A software tool using Finite Element Analysis (FEA) has been developed to provide better understanding of downhole vibration phenomena in drilling environments. The software tool calculates the response of the drilling system at various input conditions, based on the design of the wellbore along with the geometry of the Bottom Hole Assembly (BHA) and the drill string. It identifies where undesired levels of resonant vibration will be driven by certain combinations of specific drilling parameters, and also which combinations of drilling parameters will result in lower levels of vibration, so the least shocks, the highest penetration rate and the lowest cost per foot can be achieved. With the growing performance of personal computers, complex software systems modeling the drilling vibrations using FEA has been accessible to a wider audience of field users, further complimenting with real time

  3. Predicting significant torso trauma.

    Science.gov (United States)

    Nirula, Ram; Talmor, Daniel; Brasel, Karen

    2005-07-01

    Identification of motor vehicle crash (MVC) characteristics associated with thoracoabdominal injury would advance the development of automatic crash notification systems (ACNS) by improving triage and response times. Our objective was to determine the relationships between MVC characteristics and thoracoabdominal trauma to develop a torso injury probability model. Drivers involved in crashes from 1993 to 2001 within the National Automotive Sampling System were reviewed. Relationships between torso injury and MVC characteristics were assessed using multivariate logistic regression. Receiver operating characteristic curves were used to compare the model to current ACNS models. There were a total of 56,466 drivers. Age, ejection, braking, avoidance, velocity, restraints, passenger-side impact, rollover, and vehicle weight and type were associated with injury (p < 0.05). The area under the receiver operating characteristic curve (83.9) was significantly greater than current ACNS models. We have developed a thoracoabdominal injury probability model that may improve patient triage when used with ACNS.

  4. Significance of uncertainties derived from settling tank model structure and parameters on predicting WWTP performance - A global sensitivity analysis study

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2011-01-01

    Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... and from the last aerobic bioreactor upstream to the SST (Garrett/hydraulic method). For model structure uncertainty, two one-dimensional secondary settling tank (1-D SST) models are assessed, including a first-order model (the widely used Takács-model), in which the feasibility of using measured...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based...

  5. Gate valve performance prediction

    International Nuclear Information System (INIS)

    Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.

    1994-01-01

    The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

  6. Performance Prediction Toolkit

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-25

    The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. The PPT hardware model of a compute core (such as a Haswell core) consists of a set of parameters, such as clock speed, memory hierarchy levels, their respective sizes, cache-lines, access times for different cache levels, average cycle counts of ALU operations, etc. These parameters are ideally read off a spec sheet or are learned using regression models learned from hardware counters (PAPI) data. The compute core model offers an API to the software model, a function called time_compute(), which takes as input a tasklist. A tasklist is an unordered set of ALU, and other CPU-type operations (in particular virtual memory loads and stores). The PPT application model mimics the loop structure of the application and replaces the computational kernels with a call to the hardware model's time_compute() function giving tasklists as input that model the compute kernel. A PPT application model thus consists of tasklists representing kernels and the high-er level loop structure that we like to think of as pseudo code. The key challenge for the hardware model's time_compute-function is to translate virtual memory accesses into actual cache hierarchy level hits and misses.PPT also contains another CPU core level hardware model, Analytical Memory Model (AMM). The AMM solves this challenge soundly, where our previous alternatives explicitly include the L1,L2,L3 hit-rates as inputs to the tasklists. Explicit hit-rates inevitably only reflect the application modeler's best guess, perhaps informed by a few

  7. Predicting emergency diesel starting performance

    International Nuclear Information System (INIS)

    DeBey, T.M.

    1989-01-01

    The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

  8. EPRI MOV performance prediction program

    International Nuclear Information System (INIS)

    Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.

    1994-01-01

    An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

  9. The effect of ethnicity on the performance of protein-creatinine ratio in the prediction of significant proteinuria in pregnancies at risk of or with established hypertension: an implementation audit and cost implications.

    Science.gov (United States)

    Bhatti, Sadia; Cordina, Mark; Penna, Leonie; Sherwood, Roy; Dew, Tracy; Kametas, Nikos A

    2018-05-01

    The replacement of 24-h urine collection by protein-creatinine ratio (PCR) for the diagnosis of preeclampsia has been recently recommended. However, the literature is conflicting and there are concerns about the impact of demographic characteristics on the performance of PCR. This was an implementation audit of the introduction of PCR in a London Tertiary obstetric unit. The performance of PCR in the prediction of proteinuria ≥300 mg/day was assessed in 476 women with suspected preeclampsia who completed a 24-h urine collection and an untimed urine sample for PCR calculation. Multivariate logistic regression was used to assess the independent predictors of significant proteinuria. In a pregnant population, ethnicity and PCR are the main predictors of ≥300 mg proteinuria in a 24-h urine collection. A PCR cut-off of 30 mg/mmol would have incorrectly classified as non-proteinuric, 41.4% and 22.9% of black and non-black women, respectively. Sensitivity of 100% is achieved at cut-offs of 8.67 and 20.56 mg/mmol for black and non-black women, respectively. Applying these levels as a screening tool to inform the need to perform a 24-h urine collection in 1000 women, would lead to a financial saving of €2911 in non-black women and to an additional cost of €3269 in black women. Our data suggest that a move from screening for proteinuria with a 24-h urine collection to screening with urine PCR is not appropriate for black populations. However, the move may lead to cost-saving if used in the white population with a PCR cut-off of 20.5. © 2018 Nordic Federation of Societies of Obstetrics and Gynecology.

  10. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  11. Early signs that predict later haemodynamically significant patent ductus arteriosus.

    Science.gov (United States)

    Engür, Defne; Deveci, Murat; Türkmen, Münevver K

    2016-03-01

    Our aim was to determine the optimal cut-off values, sensitivity, specificity, and diagnostic power of 12 echocardiographic parameters on the second day of life to predict subsequent ductal patency. We evaluated preterm infants, born at ⩽32 weeks of gestation, starting on their second day of life, and they were evaluated every other day until ductal closure or until there were clinical signs of re-opening. We measured transductal diameter; pulmonary arterial diastolic flow; retrograde aortic diastolic flow; pulsatility index of the left pulmonary artery and descending aorta; left atrium and ventricle/aortic root ratio; left ventricular output; left ventricular flow velocity time integral; mitral early/late diastolic flow; and superior caval vein diameter and flow as well as performed receiver operating curve analysis. Transductal diameter (>1.5 mm); pulmonary arterial diastolic flow (>25.6 cm/second); presence of retrograde aortic diastolic flow; ductal diameter by body weight (>1.07 mm/kg); left pulmonary arterial pulsatility index (⩽0.71); and left ventricle to aortic root ratio (>2.2) displayed high sensitivity and specificity (p0.9). Parameters with moderate sensitivity and specificity were as follows: left atrial to aortic root ratio; left ventricular output; left ventricular flow velocity time integral; and mitral early/late diastolic flow ratio (p0.05) had low diagnostic value. Left pulmonary arterial pulsatility index, left ventricle/aortic root ratio, and ductal diameter by body weight are useful adjuncts offering a broader outlook for predicting ductal patency.

  12. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

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

    Science.gov (United States)

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

    2016-11-01

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

  14. Predictive Maintenance (PdM) Centralization for Significant Energy Savings

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Dale

    2010-09-15

    Cost effective predictive maintenance (PdM) technologies and basic energy calculations can mine energy savings form processes or maintenance activities. Centralizing and packaging this information correctly empowers facility maintenance and reliability professionals to build financial justification and support for strategies and personnel to weather global economic downturns and competition. Attendees will learn how to: Systematically build a 'pilot project' for applying PdM and tracking systems; Break down a typical electrical bill to calculate energy savings; Use return on investment (ROI) calculations to identify the best and highest value options, strategies and tips for substantiating your energy reduction maintenance strategies.

  15. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  16. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  17. Leukoaraiosis significantly worsens driving performance of ordinary older drivers.

    Directory of Open Access Journals (Sweden)

    Kimihiko Nakano

    Full Text Available BACKGROUND: Leukoaraiosis is defined as extracellular space caused mainly by atherosclerotic or demyelinated changes in the brain tissue and is commonly found in the brains of healthy older people. A significant association between leukoaraiosis and traffic crashes was reported in our previous study; however, the reason for this is still unclear. METHOD: This paper presents a comprehensive evaluation of driving performance in ordinary older drivers with leukoaraiosis. First, the degree of leukoaraiosis was examined in 33 participants, who underwent an actual-vehicle driving examination on a standard driving course, and a driver skill rating was also collected while the driver carried out a paced auditory serial addition test, which is a calculating task given verbally. At the same time, a steering entropy method was used to estimate steering operation performance. RESULTS: The experimental results indicated that a normal older driver with leukoaraiosis was readily affected by external disturbances and made more operation errors and steered less smoothly than one without leukoaraiosis during driving; at the same time, their steering skill significantly deteriorated. CONCLUSIONS: Leukoaraiosis worsens the driving performance of older drivers because of their increased vulnerability to distraction.

  18. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  19. Predicting Performance Ratings Using Motivational Antecedents

    National Research Council Canada - National Science Library

    Zazania, Michelle

    1998-01-01

    This research examined the role of motivation in predicting peer and trainer ratings of student performance and contrasted the relative importance of various antecedents for peer and trainer ratings...

  20. Complexity factors and prediction of performance

    International Nuclear Information System (INIS)

    Braarud, Per Oeyvind

    1998-03-01

    Understanding of what makes a control room situation difficult to handle is important when studying operator performance, both with respect to prediction as well as improvement of the human performance. A factor analytic approach identified eight factors from operators' answers to an 39 item questionnaire about complexity of the operator's task in the control room. A Complexity Profiling Questionnaire was developed, based on the factor analytic results from the operators' conception of complexity. The validity of the identified complexity factors was studied by prediction of crew performance and prediction of plant performance from ratings of the complexity of scenarios. The scenarios were rated by both process experts and the operators participating in the scenarios, using the Complexity Profiling Questionnaire. The process experts' complexity ratings predicted both crew performance and plant performance, while the operators' rating predicted plant performance only. The results reported are from initial studies of complexity, and imply a promising potential for further studies of the concept. The approach used in the study as well as the reported results are discussed. A chapter about the structure of the conception of complexity, and a chapter about further research conclude the report. (author)

  1. Using Machine Learning to Predict Student Performance

    OpenAIRE

    Pojon, Murat

    2017-01-01

    This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

  2. Genomic Prediction of Barley Hybrid Performance

    Directory of Open Access Journals (Sweden)

    Norman Philipp

    2016-07-01

    Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

  3. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  4. NREL Research Yields Significant Thermoelectric Performance | News | NREL

    Science.gov (United States)

    Chemical and Materials Science and Technology center, said the introduction of SWCNT into fabrics could from an exemplary SWNCT thin film improved thermoelectric properties. The newest paper revealed that that the same SWCNT thin film achieved identical performance when doped with either positive or

  5. Plant corrosion: prediction of materials performance

    International Nuclear Information System (INIS)

    Strutt, J.E.; Nicholls, J.R.

    1987-01-01

    Seventeen papers have been compiled forming a book on computer-based approaches to corrosion prediction in a wide range of industrial sectors, including the chemical, petrochemical and power generation industries. Two papers have been selected and indexed separately. The first describes a system operating within BNFL's Reprocessing Division to predict materials performance in corrosive conditions to aid future plant design. The second describes the truncation of the distribution function of pit depths during high temperature oxidation of a 20Cr austenitic steel in the fuel cladding in AGR systems. (U.K.)

  6. Hanford grout: predicting long-term performance

    International Nuclear Information System (INIS)

    Sewart, G.H.; Mitchell, D.H.; Treat, R.L.; McMakin, A.H.

    1987-01-01

    Grouted disposal is being planned for the low-level portion of liquid radioactive wastes at the Hanford site in Washington state. The performance of the disposal system must be such that it will protect people and the environment for thousands of years after disposal. To predict whether a specific grout disposal system will comply with existing and foreseen regulations, a performance assessment (PA) is performed. Long-term PAs are conducted for a range of performance conditions. Performance assessment is an inexact science. Quantifying projected impacts is especially difficult when only scant data exist on the behavior of certain components of the disposal system over thousands of years. To develop defensible results, we are honing the models and obtaining experimental data. The combination of engineered features and PA refinements is being used to ensure that Hanford grout will meet its principal goal: to protect people and the environment in the future

  7. What predicts performance during clinical psychology training?

    OpenAIRE

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

    2013-01-01

    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 r...

  8. Vegetation composition and structure significantly influence green roof performance

    Energy Technology Data Exchange (ETDEWEB)

    Dunnett, N.; Nagase, A.; Booth, R.; Grime, P. [Sheffield Univ., Sheffield (United Kingdom). Dept. of Landscape Architecture

    2005-07-01

    The majority of published literature on green roofs contains little specific information on the contribution of plants to the various functions and properties of green roofs. This paper reviewed previously published material in an attempt to shed light on the role of vegetation composition in green roof systems, with specific reference to hydrology and biodiversity support. Two ongoing experiments at the University of Sheffield were then considered: (1) a comparison of quality and quantity of runoff from different types of vegetation; and (2) a comparison of flowering seasons and biodiversity support of different vegetation. Results of the studies showed that there was no general pattern of variation in runoff that could be related to vegetation complexity or taxonomic composition of the communities. During the winter months, high precipitation quickly saturated the soil and percolate losses were similar for all treatments. In the summer, throughflow losses differed between treatments in relation to the structure of the plant canopy. Differing mechanisms resulted in variations in the volume of percolate that was collected. Lower volumes of percolate were observed in herb-only monocultures of Leontdon hispidus, a species with a high water content. Tap-rooted species were seen to more effectively absorb soil moisture. The biodiversity support study focused on the study of Sedum species and Labiatae species, which suggested that mixed vegetation containing these species had a far greater likelihood of attracting wild bees to support pollination. Results of the studies indicated that green roof vegetation with greater structural and species diversity may provide different benefits than sedum-dominated roots. Further studies are needed to investigate the trade-offs between vegetation types, and green roof functions and performance in order to justify calls for a wider diversity of green roof types. 8 refs., 2 tabs., 1 fig.

  9. Predicting Performance in Higher Education Using Proximal Predictors

    Science.gov (United States)

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

    2016-01-01

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

  10. Predicting sample size required for classification performance

    Directory of Open Access Journals (Sweden)

    Figueroa Rosa L

    2012-02-01

    Full Text Available Abstract Background Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p Conclusions This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.

  11. The prognostic significance of UCA1 for predicting clinical outcome in patients with digestive system malignancies.

    Science.gov (United States)

    Liu, Fang-Teng; Dong, Qing; Gao, Hui; Zhu, Zheng-Ming

    2017-06-20

    Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52-2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45-2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30-3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers.

  12. Performance evaluation recommendations of nuclear power plants outdoor significant civil structures earthquake resistance. Performance evaluation examples

    International Nuclear Information System (INIS)

    2005-06-01

    The Japan Society of Civil Engineers has updated performance evaluation recommendations of nuclear power plants outdoor significant civil structures earthquake resistance in June 2005. Based on experimental and analytical considerations, analytical seismic models of soils for underground structures, effects of vertical motions on time-history dynamic analysis and shear fracture of reinforced concretes by cyclic loadings have been incorporated in new recommendations. This document shows outdoor civil structures earthquake resistance and endurance performance evaluation examples based on revised recommendations. (T. Tanaka)

  13. Predicting Intentions of a Familiar Significant Other Beyond the Mirror Neuron System

    Directory of Open Access Journals (Sweden)

    Stephanie Cacioppo

    2017-08-01

    Full Text Available Inferring intentions of others is one of the most intriguing issues in interpersonal interaction. Theories of embodied cognition and simulation suggest that this mechanism takes place through a direct and automatic matching process that occurs between an observed action and past actions. This process occurs via the reactivation of past self-related sensorimotor experiences within the inferior frontoparietal network (including the mirror neuron system, MNS. The working model is that the anticipatory representations of others' behaviors require internal predictive models of actions formed from pre-established, shared representations between the observer and the actor. This model suggests that observers should be better at predicting intentions performed by a familiar actor, rather than a stranger. However, little is known about the modulations of the intention brain network as a function of the familiarity between the observer and the actor. Here, we combined functional magnetic resonance imaging (fMRI with a behavioral intention inference task, in which participants were asked to predict intentions from three types of actors: A familiar actor (their significant other, themselves (another familiar actor, and a non-familiar actor (a stranger. Our results showed that the participants were better at inferring intentions performed by familiar actors than non-familiar actors and that this better performance was associated with greater activation within and beyond the inferior frontoparietal network i.e., in brain areas related to familiarity (e.g., precuneus. In addition, and in line with Hebbian principles of neural modulations, the more the participants reported being cognitively close to their partner, the less the brain areas associated with action self-other comparison (e.g., inferior parietal lobule, attention (e.g., superior parietal lobule, recollection (hippocampus, and pair bond (ventral tegmental area, VTA were recruited, suggesting that the

  14. Bilirubin nomogram for prediction of significant hyperbilirubinemia in north Indian neonates.

    Science.gov (United States)

    Pathak, Umesh; Chawla, Deepak; Kaur, Saranjit; Jain, Suksham

    2013-04-01

    (i) To construct hour-specific serum total bilirubin (STB) nomogram in neonates born at =35 weeks of gestation; (ii)To evaluate efficacy of pre-discharge bilirubin measurement in predicting hyperbilirubinemia needing treatment. Diagnostic test performance in a prospective cohort study. Teaching hospital in Northern India. Healthy neonates with gestation =35 weeks or birth weight =2000 g. Serum total bilirubin was measured in all enrolled neonates at 24 ± 6, 72-96 and 96-144 h of postnatal age and when indicated clinically. Neonates were followed up during hospital stay and after discharge till completion of 7th postnatal day. Key outcome was significant hyperbilirubinemia (SHB) defined as need of phototherapy based on modified American Academy of Pediatrics (AAP) guidelines. In neonates born at 38 or more weeks of gestation middle line and in neonates born at 37 or less completed weeks of gestation, lower line of phototherapy thresholds were used to initiate phototherapy. For construction of nomogram, STB values were clubbed in six-hour epochs (age ± 3 hours) for postnatal age up to 48 h and twelve-hour epochs (age ± 6 hours) for age beyond 48 h. Predictive ability of the nomogram was assessed by calculating sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratio, by plotting receiver-operating characteristics (ROC) curve and calculating c-statistic. 997 neonates (birth weight: 2627 ± 536 g, gestation: 37.8 ± 1.5 weeks) were enrolled, of which 931 completed followup. Among enrolled neonates 344 (34.5%) were low birth weight. Rate of exclusive breastfeeding during hospital stay was more than 80%. Bilirubin nomogram was constructed using 40th, 75th and 95th percentile values of hour-specific bilirubin. Pre-discharge STB of =95th percentile was assigned to be in high-risk zone, between 75th and 94th centile in upper-intermediate risk zone, between 40th and 74th centile in lower-intermediate risk zone and below 40th

  15. Predicting the performance of fingerprint similarity searching.

    Science.gov (United States)

    Vogt, Martin; Bajorath, Jürgen

    2011-01-01

    Fingerprints are bit string representations of molecular structure that typically encode structural fragments, topological features, or pharmacophore patterns. Various fingerprint designs are utilized in virtual screening and their search performance essentially depends on three parameters: the nature of the fingerprint, the active compounds serving as reference molecules, and the composition of the screening database. It is of considerable interest and practical relevance to predict the performance of fingerprint similarity searching. A quantitative assessment of the potential that a fingerprint search might successfully retrieve active compounds, if available in the screening database, would substantially help to select the type of fingerprint most suitable for a given search problem. The method presented herein utilizes concepts from information theory to relate the fingerprint feature distributions of reference compounds to screening libraries. If these feature distributions do not sufficiently differ, active database compounds that are similar to reference molecules cannot be retrieved because they disappear in the "background." By quantifying the difference in feature distribution using the Kullback-Leibler divergence and relating the divergence to compound recovery rates obtained for different benchmark classes, fingerprint search performance can be quantitatively predicted.

  16. Image processing system performance prediction and product quality evaluation

    Science.gov (United States)

    Stein, E. K.; Hammill, H. B. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

  17. The baseline serum value of α-amylase is a significant predictor of distance running performance.

    Science.gov (United States)

    Lippi, Giuseppe; Salvagno, Gian Luca; Danese, Elisa; Tarperi, Cantor; La Torre, Antonio; Guidi, Gian Cesare; Schena, Federico

    2015-02-01

    This study was planned to investigate whether serum α-amylase concentration may be associated with running performance, physiological characteristics and other clinical chemistry analytes in a large sample of recreational athletes undergoing distance running. Forty-three amateur runners successfully concluded a 21.1 km half-marathon at 75%-85% of their maximal oxygen uptake (VO2max). Blood was drawn during warm up and 15 min after conclusion of the run. After correction for body weight change, significant post-run increases were observed for serum values of alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, bilirubin, creatine kinase (CK), iron, lactate dehydrogenase (LDH), triglycerides, urea and uric acid, whereas the values of body weight, glomerular filtration rate, total and low density lipoprotein-cholesterol were significantly decreased. The concentration of serum α-amylase was unchanged. In univariate analysis, significant associations with running performance were found for gender, VO2max, training regimen and pre-run serum values of α-amylase, CK, glucose, high density lipoprotein-cholesterol, LDH, urea and uric acid. In multivariate analysis, only VO2max (p=0.042) and baseline α-amylase (p=0.021) remained significant predictors of running performance. The combination of these two variables predicted 71% of variance in running performance. The baseline concentration of serum α-amylase was positively correlated with variation of serum glucose during the trial (r=0.345; p=0.025) and negatively with capillary blood lactate at the end of the run (r=-0.352; p=0.021). We showed that the baseline serum α-amylase concentration significantly and independently predicts distance running performance in recreational runners.

  18. Comparing theories' performance in predicting violence.

    Science.gov (United States)

    Haas, Henriette; Cusson, Maurice

    2015-01-01

    The stakes of choosing the best theory as a basis for violence prevention and offender rehabilitation are high. However, no single theory of violence has ever been universally accepted by a majority of established researchers. Psychiatry, psychology and sociology are each subdivided into different schools relying upon different premises. All theories can produce empirical evidence for their validity, some of them stating the opposite of each other. Calculating different models with multivariate logistic regression on a dataset of N = 21,312 observations and ninety-two influences allowed a direct comparison of the performance of operationalizations of some of the most important schools. The psychopathology model ranked as the best model in terms of predicting violence right after the comprehensive interdisciplinary model. Next came the rational choice and lifestyle model and third the differential association and learning theory model. Other models namely the control theory model, the childhood-trauma model and the social conflict and reaction model turned out to have low sensitivities for predicting violence. Nevertheless, all models produced acceptable results in predictions of a non-violent outcome. Copyright © 2015. Published by Elsevier Ltd.

  19. Axisymmetric thrust-vectoring nozzle performance prediction

    International Nuclear Information System (INIS)

    Wilson, E. A.; Adler, D.; Bar-Yoseph, P.Z

    1998-01-01

    Throat-hinged geometrically variable converging-diverging thrust-vectoring nozzles directly affect the jet flow geometry and rotation angle at the nozzle exit as a function of the nozzle geometry, the nozzle pressure ratio and flight velocity. The consideration of nozzle divergence in the effective-geometric nozzle relation is theoretically considered here for the first time. In this study, an explicit calculation procedure is presented as a function of nozzle geometry at constant nozzle pressure ratio, zero velocity and altitude, and compared with experimental results in a civil thrust-vectoring scenario. This procedure may be used in dynamic thrust-vectoring nozzle design performance predictions or analysis for civil and military nozzles as well as in the definition of initial jet flow conditions in future numerical VSTOL/TV jet performance studies

  20. Predicting Expressive Dynamics in Piano Performances using Neural Networks

    NARCIS (Netherlands)

    van Herwaarden, Sam; Grachten, Maarten; de Haas, W. Bas

    2014-01-01

    This paper presents a model for predicting expressive accentuation in piano performances with neural networks. Using Restricted Boltzmann Machines (RBMs), features are learned from performance data, after which these features are used to predict performed loudness. During feature learning, data

  1. Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

    Science.gov (United States)

    Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

    1999-01-01

    Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

  2. Predicting the Performance of Organic Corrosion Inhibitors

    Directory of Open Access Journals (Sweden)

    David A. Winkler

    2017-12-01

    Full Text Available The withdrawal of effective but toxic corrosion inhibitors has provided an impetus for the discovery of new, benign organic compounds to fill that role. Concurrently, developments in the high-throughput synthesis of organic compounds, the establishment of large libraries of available chemicals, accelerated corrosion inhibition testing technologies, and the increased capability of machine learning methods have made discovery of new corrosion inhibitors much faster and cheaper than it used to be. We summarize these technical developments in the corrosion inhibition field and describe how data-driven machine learning methods can generate models linking molecular properties to corrosion inhibition that can be used to predict the performance of materials not yet synthesized or tested. We briefly summarize the literature on quantitative structure–property relationships models of small organic molecule corrosion inhibitors. The success of these models provides a paradigm for rapid discovery of novel, effective corrosion inhibitors for a range of metals and alloys in diverse environments.

  3. Exploring the significance of human mobility patterns in social link prediction

    KAUST Repository

    Alharbi, Basma Mohammed

    2014-01-01

    Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper explores the effect of in-depth mobility patterns. Specifically, we study individuals\\' movement behavior, and quantify mobility on the basis of trip frequency, travel purpose and transportation mode. Our hybrid link prediction model is composed of two modules. The first module extracts mobility patterns, including travel purpose and mode, from raw trajectory data. The second module employs the extracted patterns for link prediction. We evaluate our method on two real data sets, GeoLife [15] and Reality Mining [5]. Experimental results show that our hybrid model significantly improves the accuracy of social link prediction, when comparing to primary topology-based solutions. Copyright 2014 ACM.

  4. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  5. Meta-Analysis of Predictive Significance of the Black Hole Sign for Hematoma Expansion in Intracerebral Hemorrhage.

    Science.gov (United States)

    Zheng, Jun; Yu, Zhiyuan; Guo, Rui; Li, Hao; You, Chao; Ma, Lu

    2018-04-27

    Hematoma expansion is related to unfavorable prognosis in intracerebral hemorrhage (ICH). The black hole sign is a novel marker on non-contrast computed tomography for predicting hematoma expansion. However, its predictive values are different in previous studies. Thus, this meta-analysis was conducted to evaluate the predictive significance of the black hole sign for hematoma expansion in ICH. A systematic literature search was performed. Original researches on the association between the black hole sign and hematoma expansion in ICH were included. Sensitivity and specificity were pooled to assess the predictive accuracy. Summary receiver operating characteristics curve (SROC) was developed. Deeks' funnel plot asymmetry test was used to assess the publication bias. Five studies with a total of 1495 patients were included in this study. The pooled sensitivity and specificity of the black hole sign for predicting hematoma expansion were 0.30 and 0.91, respectively. The area under the curve was 0.78 in SROC curve. There was no significant publication bias. This meta-analysis shows that the black hole sign is a helpful imaging marker for predicting hematoma expansion in ICH. Although the black hole sign has a relatively low sensitivity, its specificity is relatively high. Copyright © 2018 Elsevier Inc. All rights reserved.

  6. Artificial neural networks to predict presence of significant pathology in patients presenting to routine colorectal clinics.

    Science.gov (United States)

    Maslekar, S; Gardiner, A B; Monson, J R T; Duthie, G S

    2010-12-01

    Artificial neural networks (ANNs) are computer programs used to identify complex relations within data. Routine predictions of presence of colorectal pathology based on population statistics have little meaning for individual patient. This results in large number of unnecessary lower gastrointestinal endoscopies (LGEs - colonoscopies and flexible sigmoidoscopies). We aimed to develop a neural network algorithm that can accurately predict presence of significant pathology in patients attending routine outpatient clinics for gastrointestinal symptoms. Ethics approval was obtained and the study was monitored according to International Committee on Harmonisation - Good Clinical Practice (ICH-GCP) standards. Three-hundred patients undergoing LGE prospectively completed a specifically developed questionnaire, which included 40 variables based on clinical symptoms, signs, past- and family history. Complete data sets of 100 patients were used to train the ANN; the remaining data was used for internal validation. The primary output used was positive finding on LGE, including polyps, cancer, diverticular disease or colitis. For external validation, the ANN was applied to data from 50 patients in primary care and also compared with the predictions of four clinicians. Clear correlation between actual data value and ANN predictions were found (r = 0.931; P = 0.0001). The predictive accuracy of ANN was 95% in training group and 90% (95% CI 84-96) in the internal validation set and this was significantly higher than the clinical accuracy (75%). ANN also showed high accuracy in the external validation group (89%). Artificial neural networks offer the possibility of personal prediction of outcome for individual patients presenting in clinics with colorectal symptoms, making it possible to make more appropriate requests for lower gastrointestinal endoscopy. © 2010 The Authors. Colorectal Disease © 2010 The Association of Coloproctology of Great Britain and Ireland.

  7. The prognostic significance of HOTAIR for predicting clinical outcome in patients with digestive system tumors.

    Science.gov (United States)

    Ma, Gaoxiang; Wang, Qiaoyan; Lv, Chunye; Qiang, Fulin; Hua, Qiuhan; Chu, Haiyan; Du, Mulong; Tong, Na; Jiang, Yejuan; Wang, Meilin; Zhang, Zhengdong; Wang, Jian; Gong, Weida

    2015-12-01

    Although some studies have assessed the prognostic value of HOTAIR in patients with digestive system tumors, the relationship between the HOTAIR and outcome of digestive system tumors remains unknown. The PubMed was searched to identify the eligible studies. Here, we performed a meta-analysis with 11 studies, including a total of 903 cases. Pooled hazard ratios (HRs) and 95 % confidence interval (CI) of HOTAIR for cancer survival were calculated. We found that the pooled HR elevated HOTAIR expression in tumor tissues was 2.36 (95 % CI 1.88-2.97) compared with patients with low HOTAIR expression. Moreover, subgroup analysis revealed that HOTAIR overexpression was also markedly associated with short survival for esophageal squamous cell carcinoma (HR 2.19, 95 % CI 1.62-2.94) and gastric cancer (HR 1.66, 95 % CI 1.02-2.68). In addition, up-regulated HOTAIR was significantly related to survival of digestive system cancer among the studies with more follow-up time (follow time ≥ 5 years) (HR 2.51, 95 % CI 1.99-3.17). When stratified by HR resource and number of patients, the result indicated consistent results with the overall analysis. Subgroup analysis on ethnicities did not change the prognostic influence of elevated HOTAIR expression. Additionally, we conducted an independent validation cohort including 71 gastric cancer cases, in which patients with up-regulated HOTAIR expression had an unfavorable outcome with HR of 2.10 (95 % CI 1.10-4.03). The results suggest that aberrant HOTAIR expression may serve as a candidate positive marker to predict the prognosis of patients with carcinoma of digestive system.

  8. Clinical Significance of Hemostatic Parameters in the Prediction for Type 2 Diabetes Mellitus and Diabetic Nephropathy

    Directory of Open Access Journals (Sweden)

    Lianlian Pan

    2018-01-01

    Full Text Available It would be important to predict type 2 diabetes mellitus (T2DM and diabetic nephropathy (DN. This study was aimed at evaluating the predicting significance of hemostatic parameters for T2DM and DN. Plasma coagulation and hematologic parameters before treatment were measured in 297 T2DM patients. The risk factors and their predicting power were evaluated. T2DM patients without complications exhibited significantly different activated partial thromboplastin time (aPTT, platelet (PLT, and D-dimer (D-D levels compared with controls (P<0.01. Fibrinogen (FIB, PLT, and D-D increased in DN patients compared with those without complications (P<0.001. Both aPTT and PLT were the independent risk factors for T2DM (OR: 1.320 and 1.211, P<0.01, resp., and FIB and PLT were the independent risk factors for DN (OR: 1.611 and 1.194, P<0.01, resp.. The area under ROC curve (AUC of aPTT and PLT was 0.592 and 0.647, respectively, with low sensitivity in predicting T2DM. AUC of FIB was 0.874 with high sensitivity (85% and specificity (76% for DN, and that of PLT was 0.564, with sensitivity (60% and specificity (89% based on the cutoff values of 3.15 g/L and 245 × 109/L, respectively. This study suggests that hemostatic parameters have a low predicting value for T2DM, whereas fibrinogen is a powerful predictor for DN.

  9. Significance of High Resolution GHRSST on prediction of Indian Summer Monsoon

    KAUST Repository

    Jangid, Buddhi Prakash

    2017-02-24

    In this study, the Weather Research and Forecasting (WRF) model was used to assess the importance of very high resolution sea surface temperature (SST) on seasonal rainfall prediction. Two different SST datasets available from the National Centers for Environmental Prediction (NCEP) global model analysis and merged satellite product from Group for High Resolution SST (GHRSST) are used as a lower boundary condition in the WRF model for the Indian Summer Monsoon (ISM) 2010. Before using NCEP SST and GHRSST for model simulation, an initial verification of NCEP SST and GHRSST are performed with buoy measurements. It is found that approximately 0.4 K root mean square difference (RMSD) in GHRSST and NCEP SST when compared with buoy observations available over the Indian Ocean during 01 May to 30 September 2010. Our analyses suggest that use of GHRSST as lower boundary conditions in the WRF model improve the low level temperature, moisture, wind speed and rainfall prediction over ISM region. Moreover, temporal evolution of surface parameters such as temperature, moisture and wind speed forecasts associated with monsoon is also improved with GHRSST forcing as a lower boundary condition. Interestingly, rainfall prediction is improved with the use of GHRSST over the Western Ghats, which mostly not simulated in the NCEP SST based experiment.

  10. Significance of High Resolution GHRSST on prediction of Indian Summer Monsoon

    KAUST Repository

    Jangid, Buddhi Prakash; Kumar, Prashant; Attada, Raju; Kumar, Raj

    2017-01-01

    In this study, the Weather Research and Forecasting (WRF) model was used to assess the importance of very high resolution sea surface temperature (SST) on seasonal rainfall prediction. Two different SST datasets available from the National Centers for Environmental Prediction (NCEP) global model analysis and merged satellite product from Group for High Resolution SST (GHRSST) are used as a lower boundary condition in the WRF model for the Indian Summer Monsoon (ISM) 2010. Before using NCEP SST and GHRSST for model simulation, an initial verification of NCEP SST and GHRSST are performed with buoy measurements. It is found that approximately 0.4 K root mean square difference (RMSD) in GHRSST and NCEP SST when compared with buoy observations available over the Indian Ocean during 01 May to 30 September 2010. Our analyses suggest that use of GHRSST as lower boundary conditions in the WRF model improve the low level temperature, moisture, wind speed and rainfall prediction over ISM region. Moreover, temporal evolution of surface parameters such as temperature, moisture and wind speed forecasts associated with monsoon is also improved with GHRSST forcing as a lower boundary condition. Interestingly, rainfall prediction is improved with the use of GHRSST over the Western Ghats, which mostly not simulated in the NCEP SST based experiment.

  11. Pavement Performance : Approaches Using Predictive Analytics

    Science.gov (United States)

    2018-03-23

    Acceptable pavement condition is paramount to road safety. Using predictive analytics techniques, this project attempted to develop models that provide an assessment of pavement condition based on an array of indictors that include pavement distress,...

  12. Stochastic Prediction of Ventilation System Performance

    DEFF Research Database (Denmark)

    Haghighat, F.; Brohus, Henrik; Frier, Christian

    The paper briefly reviews the existing techniques for predicting the airflow rate due to the random nature of forcing functions, e.g. wind speed. The effort is to establish the relationship between the statistics of the output of a system and the statistics of the random input variables and param......The paper briefly reviews the existing techniques for predicting the airflow rate due to the random nature of forcing functions, e.g. wind speed. The effort is to establish the relationship between the statistics of the output of a system and the statistics of the random input variables...

  13. Six Significant Questions About Performance and Performance Courses in the Major.

    Science.gov (United States)

    Lawson, Hal A.; Pugh, D. Lionel

    James Bryant Conant's book, "The Education of America" (1963), triggered a major change in physical education curricula. Formerly a (sports) skills and applied techniques oriented discipline, physical education has expanded to areas such as kinesiology and sports sociology. However, performance and performance courses are still an important aspect…

  14. Use of data mining to predict significant factors and benefits of bilateral cochlear implantation.

    Science.gov (United States)

    Ramos-Miguel, Angel; Perez-Zaballos, Teresa; Perez, Daniel; Falconb, Juan Carlos; Ramosb, Angel

    2015-11-01

    Data mining (DM) is a technique used to discover pattern and knowledge from a big amount of data. It uses artificial intelligence, automatic learning, statistics, databases, etc. In this study, DM was successfully used as a predictive tool to assess disyllabic speech test performance in bilateral implanted patients with a success rate above 90%. 60 bilateral sequentially implanted adult patients were included in the study. The DM algorithms developed found correlations between unilateral medical records and Audiological test results and bilateral performance by establishing relevant variables based on two DM techniques: the classifier and the estimation. The nearest neighbor algorithm was implemented in the first case, and the linear regression in the second. The results showed that patients with unilateral disyllabic test results below 70% benefited the most from a bilateral implantation. Finally, it was observed that its benefits decrease as the inter-implant time increases.

  15. Statistical significance of theoretical predictions: A new dimension in nuclear structure theories (I)

    International Nuclear Information System (INIS)

    DUDEK, J; SZPAK, B; FORNAL, B; PORQUET, M-G

    2011-01-01

    In this and the follow-up article we briefly discuss what we believe represents one of the most serious problems in contemporary nuclear structure: the question of statistical significance of parametrizations of nuclear microscopic Hamiltonians and the implied predictive power of the underlying theories. In the present Part I, we introduce the main lines of reasoning of the so-called Inverse Problem Theory, an important sub-field in the contemporary Applied Mathematics, here illustrated on the example of the Nuclear Mean-Field Approach.

  16. Near peripheral motion contrast threshold predicts older drivers' simulator performance.

    Science.gov (United States)

    Henderson, Steven; Gagnon, Sylvain; Collin, Charles; Tabone, Ricardo; Stinchcombe, Arne

    2013-01-01

    Our group has previously demonstrated that peripheral motion contrast threshold (PMCT) is significantly associated with self-reported accident risk of older drivers (questionnaire assessment), and with Useful Field of View(®) subtest 2 (UFOV2). It has not been shown, however, that PMCT is significantly associated with driving performance. Using the method of descending limits (spatial two-alternative forced choice) we assessed motion contrast thresholds of 28 young participants (25-45), and 21 older drivers (63-86) for 0.4 cycle/degree drifting Gabor stimuli at 15° eccentricity and examined whether it was related to performance on a simulated on-road test and to a measure of visual attention (UFOV(®) subtests 2 and 3). Peripheral motion contrast thresholds (PMCT) of younger participants were significantly lower than older participants. PMCT and UFOV2 significantly predicted driving examiners' scores of older drivers' simulator performance, as well as number of crashes. Within the older group, PMCT correlated significantly with UFOV2, UFOV3, and age. Within the younger group, PMCT was not significantly related to either UFOV(®) scores or age. Partial correlations showed that: substantial association between PMCT and UFOV2 was not age-related (within the older driver group); PMCT and UFOV2 tapped a common visual function; and PMCT assessed a component not captured by UFOV2. PMCT is potentially a useful assessment tool for predicting accident risk of older drivers, and for informing efforts to develop effective countermeasures to remediate this functional deficit as much as possible. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. System Predicts Critical Runway Performance Parameters

    Science.gov (United States)

    Millen, Ernest W.; Person, Lee H., Jr.

    1990-01-01

    Runway-navigation-monitor (RNM) and critical-distances-process electronic equipment designed to provide pilot with timely and reliable predictive navigation information relating to takeoff, landing and runway-turnoff operations. Enables pilot to make critical decisions about runway maneuvers with high confidence during emergencies. Utilizes ground-referenced position data only to drive purely navigational monitor system independent of statuses of systems in aircraft.

  18. Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System.

    Science.gov (United States)

    Doyle, Andy; Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

    2014-12-01

    Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years.

  19. Performance samples on academic tasks : improving prediction of academic performance

    NARCIS (Netherlands)

    Tanilon, Jenny

    2011-01-01

    This thesis is about the development and validation of a performance-based test, labeled as Performance Samples on academic tasks in Education and Child Studies (PSEd). PSEd is designed to identify students who are most able to perform the academic tasks involved in an Education and Child Studies

  20. Performance analysis and prediction in triathlon.

    Science.gov (United States)

    Ofoghi, Bahadorreza; Zeleznikow, John; Macmahon, Clare; Rehula, Jan; Dwyer, Dan B

    2016-01-01

    Performance in triathlon is dependent upon factors that include somatotype, physiological capacity, technical proficiency and race strategy. Given the multidisciplinary nature of triathlon and the interaction between each of the three race components, the identification of target split times that can be used to inform the design of training plans and race pacing strategies is a complex task. The present study uses machine learning techniques to analyse a large database of performances in Olympic distance triathlons (2008-2012). The analysis reveals patterns of performance in five components of triathlon (three race "legs" and two transitions) and the complex relationships between performance in each component and overall performance in a race. The results provide three perspectives on the relationship between performance in each component of triathlon and the final placing in a race. These perspectives allow the identification of target split times that are required to achieve a certain final place in a race and the opportunity to make evidence-based decisions about race tactics in order to optimise performance.

  1. Predicting introductory programming performance: A multi-institutional multivariate study

    Science.gov (United States)

    Bergin, Susan; Reilly, Ronan

    2006-12-01

    A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

  2. Predicting Students' Performance in the Senior Secondary ...

    African Journals Online (AJOL)

    cce

    correlation design. ... the JSC examinations were a good predictor of performance at SSC ..... Table 12: Effects of the Independent Variables (JSCE 2000) on the .... JAMB Brochure, Abuja: Joint Admissions and Matriculation Examinations, 2-3.

  3. SYRUS: Understanding and Predicting Multitasking Performance

    National Research Council Canada - National Science Library

    Oswald, Frederick L; Hambrick, D. Z; Jones, L. A; Ghumman, Sonia S

    2007-01-01

    .... Fourth, related to the previous point, a summarization of our initial empirical work on multitasking, based on college-student participants who engaged in a computerized multitasking performance task...

  4. Significant interarm blood pressure difference predicts cardiovascular risk in hypertensive patients: CoCoNet study.

    Science.gov (United States)

    Kim, Su-A; Kim, Jang Young; Park, Jeong Bae

    2016-06-01

    There has been a rising interest in interarm blood pressure difference (IAD), due to its relationship with peripheral arterial disease and its possible relationship with cardiovascular disease. This study aimed to characterize hypertensive patients with a significant IAD in relation to cardiovascular risk. A total of 3699 patients (mean age, 61 ± 11 years) were prospectively enrolled in the study. Blood pressure (BP) was measured simultaneously in both arms 3 times using an automated cuff-oscillometric device. IAD was defined as the absolute difference in averaged BPs between the left and right arm, and an IAD ≥ 10 mm Hg was considered to be significant. The Framingham risk score was used to calculate the 10-year cardiovascular risk. The mean systolic IAD (sIAD) was 4.3 ± 4.1 mm Hg, and 285 (7.7%) patients showed significant sIAD. Patients with significant sIAD showed larger body mass index (P < 0.001), greater systolic BP (P = 0.050), more coronary artery disease (relative risk = 1.356, P = 0.034), and more cerebrovascular disease (relative risk = 1.521, P = 0.072). The mean 10-year cardiovascular risk was 9.3 ± 7.7%. By multiple regression, sIAD was significantly but weakly correlated with the 10-year cardiovascular risk (β = 0.135, P = 0.008). Patients with significant sIAD showed a higher prevalence of coronary artery disease, as well as an increase in 10-year cardiovascular risk. Therefore, accurate measurements of sIAD may serve as a simple and cost-effective tool for predicting cardiovascular risk in clinical settings.

  5. Significant interarm blood pressure difference predicts cardiovascular risk in hypertensive patients

    Science.gov (United States)

    Kim, Su-A; Kim, Jang Young; Park, Jeong Bae

    2016-01-01

    Abstract There has been a rising interest in interarm blood pressure difference (IAD), due to its relationship with peripheral arterial disease and its possible relationship with cardiovascular disease. This study aimed to characterize hypertensive patients with a significant IAD in relation to cardiovascular risk. A total of 3699 patients (mean age, 61 ± 11 years) were prospectively enrolled in the study. Blood pressure (BP) was measured simultaneously in both arms 3 times using an automated cuff-oscillometric device. IAD was defined as the absolute difference in averaged BPs between the left and right arm, and an IAD ≥ 10 mm Hg was considered to be significant. The Framingham risk score was used to calculate the 10-year cardiovascular risk. The mean systolic IAD (sIAD) was 4.3 ± 4.1 mm Hg, and 285 (7.7%) patients showed significant sIAD. Patients with significant sIAD showed larger body mass index (P < 0.001), greater systolic BP (P = 0.050), more coronary artery disease (relative risk = 1.356, P = 0.034), and more cerebrovascular disease (relative risk = 1.521, P = 0.072). The mean 10-year cardiovascular risk was 9.3 ± 7.7%. By multiple regression, sIAD was significantly but weakly correlated with the 10-year cardiovascular risk (β = 0.135, P = 0.008). Patients with significant sIAD showed a higher prevalence of coronary artery disease, as well as an increase in 10-year cardiovascular risk. Therefore, accurate measurements of sIAD may serve as a simple and cost-effective tool for predicting cardiovascular risk in clinical settings. PMID:27310982

  6. Surface tensions of multi-component mixed inorganic/organic aqueous systems of atmospheric significance: measurements, model predictions and importance for cloud activation predictions

    Directory of Open Access Journals (Sweden)

    D. O. Topping

    2007-01-01

    Full Text Available In order to predict the physical properties of aerosol particles, it is necessary to adequately capture the behaviour of the ubiquitous complex organic components. One of the key properties which may affect this behaviour is the contribution of the organic components to the surface tension of aqueous particles in the moist atmosphere. Whilst the qualitative effect of organic compounds on solution surface tensions has been widely reported, our quantitative understanding on mixed organic and mixed inorganic/organic systems is limited. Furthermore, it is unclear whether models that exist in the literature can reproduce the surface tension variability for binary and higher order multi-component organic and mixed inorganic/organic systems of atmospheric significance. The current study aims to resolve both issues to some extent. Surface tensions of single and multiple solute aqueous solutions were measured and compared with predictions from a number of model treatments. On comparison with binary organic systems, two predictive models found in the literature provided a range of values resulting from sensitivity to calculations of pure component surface tensions. Results indicate that a fitted model can capture the variability of the measured data very well, producing the lowest average percentage deviation for all compounds studied. The performance of the other models varies with compound and choice of model parameters. The behaviour of ternary mixed inorganic/organic systems was unreliably captured by using a predictive scheme and this was dependent on the composition of the solutes present. For more atmospherically representative higher order systems, entirely predictive schemes performed poorly. It was found that use of the binary data in a relatively simple mixing rule, or modification of an existing thermodynamic model with parameters derived from binary data, was able to accurately capture the surface tension variation with concentration. Thus

  7. Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions.

    Directory of Open Access Journals (Sweden)

    Tomislav Hengl

    Full Text Available 80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS project was established in 2008. Over the period 2008-2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management--organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na. We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15-75% in Root Mean Squared Error (RMSE across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring

  8. Cognitive load predicts point-of-care ultrasound simulator performance.

    Science.gov (United States)

    Aldekhyl, Sara; Cavalcanti, Rodrigo B; Naismith, Laura M

    2018-02-01

    The ability to maintain good performance with low cognitive load is an important marker of expertise. Incorporating cognitive load measurements in the context of simulation training may help to inform judgements of competence. This exploratory study investigated relationships between demographic markers of expertise, cognitive load measures, and simulator performance in the context of point-of-care ultrasonography. Twenty-nine medical trainees and clinicians at the University of Toronto with a range of clinical ultrasound experience were recruited. Participants answered a demographic questionnaire then used an ultrasound simulator to perform targeted scanning tasks based on clinical vignettes. Participants were scored on their ability to both acquire and interpret ultrasound images. Cognitive load measures included participant self-report, eye-based physiological indices, and behavioural measures. Data were analyzed using a multilevel linear modelling approach, wherein observations were clustered by participants. Experienced participants outperformed novice participants on ultrasound image acquisition. Ultrasound image interpretation was comparable between the two groups. Ultrasound image acquisition performance was predicted by level of training, prior ultrasound training, and cognitive load. There was significant convergence between cognitive load measurement techniques. A marginal model of ultrasound image acquisition performance including prior ultrasound training and cognitive load as fixed effects provided the best overall fit for the observed data. In this proof-of-principle study, the combination of demographic and cognitive load measures provided more sensitive metrics to predict ultrasound simulator performance. Performance assessments which include cognitive load can help differentiate between levels of expertise in simulation environments, and may serve as better predictors of skill transfer to clinical practice.

  9. The significance of collateral vessels, as seen on chest CT, in predicting SVC obstruction

    International Nuclear Information System (INIS)

    Yeouk, Young Soo; Kim, Sung Jin; Bae, Il Hun; Kim, Jae Youn; Hwang, Seung Min; Han, Gi Seok; Park, Kil Sun; Kim, Dae Young

    1998-01-01

    To evaluate the significance of collateral veins, as seen on chest CT, in the diagnosis of superior vena cava obstruction. We retrospectively the records of 81 patients in whom collateral veins were seen on chest CT. On spiral CT(n=49), contrast material was infused via power injector, and on conventional CT(n=32), 50 ml bolus infusion was followed by 50 ml drip infusion. Obstruction of the SVC was evaluated on chest CT; if, however, evaluation of the SVC of its major tributaries was difficult, as in five cases, the patient underwent SVC phlebography. Collateral vessels were assigned to one of ten categories. On conventional CT, the jugular venous arch in the only collateral vessel to predict SVC obstruction; on spiral CT, however, collateral vessels are not helpful in the diagnosis of SVC obstruction, but are a nonspecific finding. (author). 12 refs., 2 tab., 2 figs

  10. Dichotic listening performance predicts language comprehension.

    Science.gov (United States)

    Asbjørnsen, Arve E; Helland, Turid

    2006-05-01

    Dichotic listening performance is considered a reliable and valid procedure for the assessment of language lateralisation in the brain. However, the documentation of a relationship between language functions and dichotic listening performance is sparse, although it is accepted that dichotic listening measures language perception. In particular, language comprehension should show close correspondence to perception of language stimuli. In the present study, we tested samples of reading-impaired and normally achieving children between 10 and 13 years of age with tests of reading skills, language comprehension, and dichotic listening to consonant-vowel (CV) syllables. A high correlation between the language scores and the dichotic listening performance was expected. However, since the left ear score is believed to be an error when assessing language laterality, covariation was expected for the right ear scores only. In addition, directing attention to one ear input was believed to reduce the influence of random factors, and thus show a more concise estimate of left hemisphere language capacity. Thus, a stronger correlation between language comprehension skills and the dichotic listening performance when attending to the right ear was expected. The analyses yielded a positive correlation between the right ear score in DL and language comprehension, an effect that was stronger when attending to the right ear. The present results confirm the assumption that dichotic listening with CV syllables measures an aspect of language perception and language skills that is related to general language comprehension.

  11. Challenges of student selection: Predicting academic performance ...

    African Journals Online (AJOL)

    Finding accurate predictors of tertiary academic performance, specifically for disadvantaged students, is essential because of budget constraints and the need of the labour market to address employment equity. Increased retention, throughput and decreased dropout rates are vital. When making admission decisions, the

  12. Goal Setting and Expectancy Theory Predictions of Effort and Performance.

    Science.gov (United States)

    Dossett, Dennis L.; Luce, Helen E.

    Neither expectancy (VIE) theory nor goal setting alone are effective determinants of individual effort and task performance. To test the combined ability of VIE and goal setting to predict effort and performance, 44 real estate agents and their managers completed questionnaires. Quarterly income goals predicted managers' ratings of agents' effort,…

  13. Predicting sales performance: Strengthening the personality – job performance linkage

    NARCIS (Netherlands)

    T.B. Sitser (Thomas)

    2014-01-01

    markdownabstract__Abstract__ Many organizations worldwide use personality measures to select applicants for sales jobs or to assess incumbent sales employees. In the present dissertation, consisting of four independent studies, five approaches to strengthen the personality-sales performance

  14. Numerical simulation of a twin screw expander for performance prediction

    Science.gov (United States)

    Papes, Iva; Degroote, Joris; Vierendeels, Jan

    2015-08-01

    With the increasing use of twin screw expanders in waste heat recovery applications, the performance prediction of these machines plays an important role. This paper presents a mathematical model for calculating the performance of a twin screw expander. From the mass and energy conservation laws, differential equations are derived which are then solved together with the appropriate Equation of State in the instantaneous control volumes. Different flow processes that occur inside the screw expander such as filling (accompanied by a substantial pressure loss) and leakage flows through the clearances are accounted for in the model. The mathematical model employs all geometrical parameters such as chamber volume, suction and leakage areas. With R245fa as working fluid, the Aungier Redlich-Kwong Equation of State has been used in order to include real gas effects. To calculate the mass flow rates through the leakage paths formed inside the screw expander, flow coefficients are considered as constant and they are derived from 3D Computational Fluid Dynamic calculations at given working conditions and applied to all other working conditions. The outcome of the mathematical model is the P-V indicator diagram which is compared to CFD results of the same twin screw expander. Since CFD calculations require significant computational time, developed mathematical model can be used for the faster performance prediction.

  15. Wind Plant Performance Prediction (WP3) Project

    Energy Technology Data Exchange (ETDEWEB)

    Craig, Anna [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-26

    The methods for analysis of operational wind plant data are highly variable across the wind industry, leading to high uncertainties in the validation and bias-correction of preconstruction energy estimation methods. Lack of credibility in the preconstruction energy estimates leads to significant impacts on project financing and therefore the final levelized cost of energy for the plant. In this work, the variation in the evaluation of a wind plant's operational energy production as a result of variations in the processing methods applied to the operational data is examined. Preliminary results indicate that selection of the filters applied to the data and the filter parameters can have significant impacts in the final computed assessment metrics.

  16. Role of hyaluronic acid and laminin as serum markers for predicting significant fibrosis in patients with chronic hepatitis B

    Directory of Open Access Journals (Sweden)

    Feng Li

    Full Text Available OBJECTIVES: The aim of this study was to evaluate the diagnostic performance of serum HA and LN as serum markers for predicting significant fibrosis in CHB patients. METHODS: Serum HA and LN levels of 87 patients with chronic hepatitis B and 19 blood donors were assayed by RIA. Liver fibrosis stages were determined according to the Metavir scoring-system. The diagnostic performances of all indexes were evaluated by the receiver operating characteristic (ROC curves. RESULTS: Serum HA and LN concentrations increased significantly with the stage of hepatic fibrosis, which showed positive correlation with the stages of liver fibrosis (HA: r = 0.875, p < 0.001; LN: r = 0.610, p < 0.001. There were significant differences of serum HA and LN levels between F2-4 group in comparison with those in F0-F1 group (p < 0.001 and controls (p < 0.001, respectively. From ROC curves, 185.3 ng/mL as the optimal cut-off value of serum HA for diagnosis of significant fibrosis, giving its sensitivity, specificity, PPV, NPV, LR+, LR- and AC of 84.2%, 83.3%, 90.6%, 73.5%, 5.04, 0.19 and 83.9, respectively. While 132.7 ng/mL was the optimal cut-off value of serum LN, the sensitivity, specificity, PPV, NPV, LR+, LR- and AC were 71.9%, 80.0%, 87.2%, 60.0%, 3.59%, 0.35% and 74.7, respectively. Combinations of HA and LN by serial tests showed a perfect specificity and PPV of 100%, at the same time sensitivity declined to 63.2% and LR+ increased to 18.9, while parallel tests revealed a good sensitivity of 94.7%, NPV to 86.4%, and LR- declined to 0.08. CONCLUSIONS: Serum HA and LN concentrations showed positive correlation with the stages of liver fibrosis. Detection of serum HA and LN in predicting significant fibrosis showed good diagnostic performance, which would be further optimized by combination of the two indices. HA and LN would be clinically useful serum markers for predicting significant fibrosis in patients with chronic hepatitis B, when liver biopsy is

  17. Roles and significance of water conducting features for transport models in performance assessment

    International Nuclear Information System (INIS)

    Carrera, J.; Sanchez-Vila, X.; Medina, A.

    1999-01-01

    The term water conducting features (WCF) refers to zones of high hydraulic conductivity. In the context of waste disposal, it is further implied that they are narrow so that chances of sampling them are low. Yet, they may carry significant amounts of water. Moreover, their relatively small volumetric water content causes solutes to travel fast through them. Water-conducting features are a rather common feature of natural media. The fact that they have become a source of concern in recent years, reflects more the increased level of testing and monitoring than any intrinsic property of low permeability media. Accurate simulations of solute transport require a realistic accounting for water conducting features. Methods are presented to do so and examples are shown to illustrate these methods. Since detailed accounting of WCF's will not be possible in actual performance assessments, efforts should be directed towards typification, so as to identify the essential effects of WCF's on solute transport through different types of rocks. Field evidence suggests that, although individual WCF's may be difficult to characterize, their effects are quite predictable. (author)

  18. Significance of SYT8 For the Detection, Prediction, and Treatment of Peritoneal Metastasis From Gastric Cancer.

    Science.gov (United States)

    Kanda, Mitsuro; Shimizu, Dai; Tanaka, Haruyoshi; Tanaka, Chie; Kobayashi, Daisuke; Hayashi, Masamichi; Iwata, Naoki; Niwa, Yukiko; Yamada, Suguru; Fujii, Tsutomu; Sugimoto, Hiroyuki; Murotani, Kenta; Fujiwara, Michitaka; Kodera, Yasuhiro

    2018-03-01

    To develop novel diagnostic and therapeutic targets specific for peritoneal metastasis of gastric cancer (GC). Advanced GC frequently recurs because of undetected micrometastases even after curative resection. Peritoneal metastasis has been the most frequent recurrent pattern after gastrectomy and is incurable. We conducted a recurrence pattern-specific transcriptome analysis in an independent cohort of 16 patients with stage III GC who underwent curative gastrectomy and adjuvant S-1 for screening candidate molecules specific for peritoneal metastasis of GC. Next, another 340 patients were allocated to discovery and validation sets (1:2) to evaluate the diagnostic and predictive value of the candidate molecule. The results of quantitative reverse-transcription PCR and immunohistochemical analysis were correlated with clinical characteristics and survival. The effects of siRNA-mediated knockdown on phenotype and fluorouracil sensitivity of GC cells were evaluated in vitro, and the therapeutic effects of siRNAs were evaluated using a mouse xenograft model. Synaptotagmin VIII (SYT8) was identified as a candidate biomarker specific to peritoneal metastasis. In the discovery set, the optimal cut-off of SYT8 expression was established as 0.005. Expression levels of SYT8 mRNA in GC tissues were elevated in the validation set comprising patients with peritoneal recurrence or metastasis. SYT8 levels above the cut-off value were significantly and specifically associated with peritoneal metastasis, and served as an independent prognostic marker for peritoneal recurrence-free survival of patients with stage II/III GC. The survival difference between patients with SYT8 levels above and below the cut-off was associated with patients who received adjuvant chemotherapy. Inhibition of SYT8 expression by GC cells correlated with decreased invasion, migration, and fluorouracil resistance. Intraperitoneal administration of SYT8-siRNA inhibited the growth of peritoneal nodules and

  19. Does IQ Really Predict Job Performance?

    Science.gov (United States)

    Richardson, Ken; Norgate, Sarah H.

    2015-01-01

    IQ has played a prominent part in developmental and adult psychology for decades. In the absence of a clear theoretical model of internal cognitive functions, however, construct validity for IQ tests has always been difficult to establish. Test validity, therefore, has always been indirect, by correlating individual differences in test scores with what are assumed to be other criteria of intelligence. Job performance has, for several reasons, been one such criterion. Correlations of around 0.5 have been regularly cited as evidence of test validity, and as justification for the use of the tests in developmental studies, in educational and occupational selection and in research programs on sources of individual differences. Here, those correlations are examined together with the quality of the original data and the many corrections needed to arrive at them. It is concluded that considerable caution needs to be exercised in citing such correlations for test validation purposes. PMID:26405429

  20. Numerical modeling capabilities to predict repository performance

    International Nuclear Information System (INIS)

    1979-09-01

    This report presents a summary of current numerical modeling capabilities that are applicable to the design and performance evaluation of underground repositories for the storage of nuclear waste. The report includes codes that are available in-house, within Golder Associates and Lawrence Livermore Laboratories; as well as those that are generally available within the industry and universities. The first listing of programs are in-house codes in the subject areas of hydrology, solute transport, thermal and mechanical stress analysis, and structural geology. The second listing of programs are divided by subject into the following categories: site selection, structural geology, mine structural design, mine ventilation, hydrology, and mine design/construction/operation. These programs are not specifically designed for use in the design and evaluation of an underground repository for nuclear waste; but several or most of them may be so used

  1. Reliable predictions of waste performance in a geologic repository

    International Nuclear Information System (INIS)

    Pigford, T.H.; Chambre, P.L.

    1985-08-01

    Establishing reliable estimates of long-term performance of a waste repository requires emphasis upon valid theories to predict performance. Predicting rates that radionuclides are released from waste packages cannot rest upon empirical extrapolations of laboratory leach data. Reliable predictions can be based on simple bounding theoretical models, such as solubility-limited bulk-flow, if the assumed parameters are reliably known or defensibly conservative. Wherever possible, performance analysis should proceed beyond simple bounding calculations to obtain more realistic - and usually more favorable - estimates of expected performance. Desire for greater realism must be balanced against increasing uncertainties in prediction and loss of reliability. Theoretical predictions of release rate based on mass-transfer analysis are bounding and the theory can be verified. Postulated repository analogues to simulate laboratory leach experiments introduce arbitrary and fictitious repository parameters and are shown not to agree with well-established theory. 34 refs., 3 figs., 2 tabs

  2. Enhancing pavement performance prediction models for the Illinois Tollway System

    OpenAIRE

    Laxmikanth Premkumar; William R. Vavrik

    2016-01-01

    Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway) with over 2000 lane miles of pavement utilizes the condition rating survey (CRS) methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT) are used by th...

  3. Non-invasive prediction of hemodynamically significant coronary artery stenoses by contrast density difference in coronary CT angiography

    Energy Technology Data Exchange (ETDEWEB)

    Hell, Michaela M., E-mail: michaela.hell@uk-erlangen.de [Department of Cardiology, University of Erlangen (Germany); Dey, Damini [Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Taper Building, Room A238, 8700 Beverly Boulevard, Los Angeles, CA 90048 (United States); Marwan, Mohamed; Achenbach, Stephan; Schmid, Jasmin; Schuhbaeck, Annika [Department of Cardiology, University of Erlangen (Germany)

    2015-08-15

    Highlights: • Overestimation of coronary lesions by coronary computed tomography angiography and subsequent unnecessary invasive coronary angiography and revascularization is a concern. • Differences in plaque characteristics and contrast density difference between hemodynamically significant and non-significant stenoses, as defined by invasive fractional flow reserve, were assessed. • At a threshold of ≥24%, contrast density difference predicted hemodynamically significant lesions with a specificity of 75%, sensitivity of 33%, PPV of 35% and NPV of 73%. • The determination of contrast density difference required less time than transluminal attenuation gradient measurement. - Abstract: Objectives: Coronary computed tomography angiography (CTA) allows the detection of obstructive coronary artery disease. However, its ability to predict the hemodynamic significance of stenoses is limited. We assessed differences in plaque characteristics and contrast density difference between hemodynamically significant and non-significant stenoses, as defined by invasive fractional flow reserve (FFR). Methods: Lesion characteristics of 59 consecutive patients (72 lesions) in whom invasive FFR was performed in at least one coronary artery with moderate to high-grade stenoses in coronary CTA were evaluated by two experienced readers. Coronary CTA data sets were acquired on a second-generation dual-source CT scanner using retrospectively ECG-gated spiral acquisition or prospectively ECG-triggered axial acquisition mode. Plaque volume and composition (non-calcified, calcified), remodeling index as well as contrast density difference (defined as the percentage decline in luminal CT attenuation/cross-sectional area over the lesion) were assessed using a semi-automatic software tool (Autoplaq). Additionally, the transluminal attenuation gradient (defined as the linear regression coefficient between intraluminal CT attenuation and length from the ostium) was determined

  4. Spatially resolved flux measurements of NOx from London suggest significantly higher emissions than predicted by inventories.

    Science.gov (United States)

    Vaughan, Adam R; Lee, James D; Misztal, Pawel K; Metzger, Stefan; Shaw, Marvin D; Lewis, Alastair C; Purvis, Ruth M; Carslaw, David C; Goldstein, Allen H; Hewitt, C Nicholas; Davison, Brian; Beevers, Sean D; Karl, Thomas G

    2016-07-18

    To date, direct validation of city-wide emissions inventories for air pollutants has been difficult or impossible. However, recent technological innovations now allow direct measurement of pollutant fluxes from cities, for comparison with emissions inventories, which are themselves commonly used for prediction of current and future air quality and to help guide abatement strategies. Fluxes of NOx were measured using the eddy-covariance technique from an aircraft flying at low altitude over London. The highest fluxes were observed over central London, with lower fluxes measured in suburban areas. A footprint model was used to estimate the spatial area from which the measured emissions occurred. This allowed comparison of the flux measurements to the UK's National Atmospheric Emissions Inventory (NAEI) for NOx, with scaling factors used to account for the actual time of day, day of week and month of year of the measurement. The comparison suggests significant underestimation of NOx emissions in London by the NAEI, mainly due to its under-representation of real world road traffic emissions. A comparison was also carried out with an enhanced version of the inventory using real world driving emission factors and road measurement data taken from the London Atmospheric Emissions Inventory (LAEI). The measurement to inventory agreement was substantially improved using the enhanced version, showing the importance of fully accounting for road traffic, which is the dominant NOx emission source in London. In central London there was still an underestimation by the inventory of 30-40% compared with flux measurements, suggesting significant improvements are still required in the NOx emissions inventory.

  5. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  6. Performance prediction method for a multi-stage Knudsen pump

    Science.gov (United States)

    Kugimoto, K.; Hirota, Y.; Kizaki, Y.; Yamaguchi, H.; Niimi, T.

    2017-12-01

    In this study, the novel method to predict the performance of a multi-stage Knudsen pump is proposed. The performance prediction method is carried out in two steps numerically with the assistance of a simple experimental result. In the first step, the performance of a single-stage Knudsen pump was measured experimentally under various pressure conditions, and the relationship of the mass flow rate was obtained with respect to the average pressure between the inlet and outlet of the pump and the pressure difference between them. In the second step, the performance of a multi-stage pump was analyzed by a one-dimensional model derived from the mass conservation law. The performances predicted by the 1D-model of 1-stage, 2-stage, 3-stage, and 4-stage pumps were validated by the experimental results for the corresponding number of stages. It was concluded that the proposed prediction method works properly.

  7. Predictive Performance Tuning of OpenACC Accelerated Applications

    KAUST Repository

    Siddiqui, Shahzeb

    2014-05-04

    Graphics Processing Units (GPUs) are gradually becoming mainstream in supercomputing as their capabilities to significantly accelerate a large spectrum of scientific applications have been clearly identified and proven. Moreover, with the introduction of high level programming models such as OpenACC [1] and OpenMP 4.0 [2], these devices are becoming more accessible and practical to use by a larger scientific community. However, performance optimization of OpenACC accelerated applications usually requires an in-depth knowledge of the hardware and software specifications. We suggest a prediction-based performance tuning mechanism [3] to quickly tune OpenACC parameters for a given application to dynamically adapt to the execution environment on a given system. This approach is applied to a finite difference kernel to tune the OpenACC gang and vector clauses for mapping the compute kernels into the underlying accelerator architecture. Our experiments show a significant performance improvement against the default compiler parameters and a faster tuning by an order of magnitude compared to the brute force search tuning.

  8. Do Maximal Roller Skiing Speed and Double Poling Performance Predict Youth Cross-Country Skiing Performance?

    Directory of Open Access Journals (Sweden)

    Roland Stöggl, Erich Müller, Thomas Stöggl

    2017-09-01

    Full Text Available The aims of the current study were to analyze whether specific roller skiing tests and cycle length are determinants of youth cross-country (XC skiing performance, and to evaluate sex specific differences by applying non-invasive diagnostics. Forty-nine young XC skiers (33 boys; 13.8 ± 0.6 yrs and 16 girls; 13.4 ± 0.9 yrs performed roller skiing tests consisting of both shorter (50 m and longer durations (575 m. Test results were correlated with on snow XC skiing performance (PXC based on 3 skating and 3 classical distance competitions (3 to 6 km. The main findings of the current study were: 1 Anthropometrics and maturity status were related to boys’, but not to girls’ PXC; 2 Significant moderate to acceptable correlations between girls’ and boys’ short duration maximal roller skiing speed (double poling, V2 skating, leg skating and PXC were found; 3 Boys’ PXC was best predicted by double poling test performance on flat and uphill, while girls’ performance was mainly predicted by uphill double poling test performance; 4 When controlling for maturity offset, boys’ PXC was still highly associated with the roller skiing tests. The use of simple non-invasive roller skiing tests for determination of PXC represents practicable support for ski clubs, schools or skiing federations in the guidance and evaluation of young talent.

  9. Hybrid Corporate Performance Prediction Model Considering Technical Capability

    Directory of Open Access Journals (Sweden)

    Joonhyuck Lee

    2016-07-01

    Full Text Available Many studies have tried to predict corporate performance and stock prices to enhance investment profitability using qualitative approaches such as the Delphi method. However, developments in data processing technology and machine-learning algorithms have resulted in efforts to develop quantitative prediction models in various managerial subject areas. We propose a quantitative corporate performance prediction model that applies the support vector regression (SVR algorithm to solve the problem of the overfitting of training data and can be applied to regression problems. The proposed model optimizes the SVR training parameters based on the training data, using the genetic algorithm to achieve sustainable predictability in changeable markets and managerial environments. Technology-intensive companies represent an increasing share of the total economy. The performance and stock prices of these companies are affected by their financial standing and their technological capabilities. Therefore, we apply both financial indicators and technical indicators to establish the proposed prediction model. Here, we use time series data, including financial, patent, and corporate performance information of 44 electronic and IT companies. Then, we predict the performance of these companies as an empirical verification of the prediction performance of the proposed model.

  10. Predicting Community College Outcomes: Does High School CTE Participation Have a Significant Effect?

    Science.gov (United States)

    Dietrich, Cecile; Lichtenberger, Eric; Kamalludeen, Rosemaliza

    2016-01-01

    This study explored the relative importance of participation in high school career and technical education (CTE) programs in predicting community college outcomes. A hierarchical generalized linear model (HGLM) was used to predict community college outcome attainment among a random sample of direct community college entrants. Results show that…

  11. Essays on predictability of emerging markets growth and financial performance

    OpenAIRE

    Banegas, Maria Ayelen

    2011-01-01

    This dissertation seeks to better understand the underlying factors driving financial performance and economic activity in international markets. The first chapter "Predictability of Growth in Emerging Markets: Information in Financial Aggregates" tests for predictability of output growth in a panel of twenty-two emerging market economies. I use pooled panel data methods that control for endogeneity and persistence in the predictor variables to test the predictive power of a large set of fina...

  12. Significant change of predictions related to the future of nuclear power

    International Nuclear Information System (INIS)

    Dumitrache, Ion

    2002-01-01

    During the last two decades of the 20th century, nuclear power contribution increased slowly in the world. This trend was mainly determined by the commissioning of new nuclear power plants, NPP, in the non-developed countries, except for Japan and South Korea. Almost all the forecasts offered the image of the stagnant nuclear power business. Sweden, Germany, Holland and Belgium Governments made clear the intention to stop the production of electricity based on fission. Recently, despite the negative effects on nuclear power of the terrorism events of September 11, 2001, the predictions related to the nuclear power future become much more optimistic. USA, Japan, South Korea and Canada made clear that new NPPs will offer their significant electricity contribution several decades, even after years 2020-2030. Moreover, several old NPP from USA obtained the license for an additional 20 years period of operation. The analysis indicated that most of the existing NPP in USA may increase the level of the maximum global power defined by the initial design. In the European Union the situation is much more complicated. About 35% of the electricity is based now on fission. Several countries, like Sweden and Germany, maintain the position of phasing out the NPPs, as soon as the licensed life-time is over. Finland decided to build a new power plant. France is very favorable to nuclear power, but does not need more energy. In the UK several very old NPP will be shut down, and companies like BNFL and British Energy intend to build new NPP, based on Westinghouse or AECL-Canada advanced reactors. Switzerland and Spain are favorable to the future use of nuclear power. In the eastern part of Europe, almost all the countries intend to base their electricity production on coal, fission, hydro and gas, nuclear contribution being significant. The most impressive increases of nuclear power output are related to Asia; in China, from 2.2 Gwe in 1999, to 18.7 Gwe in 2020, reference case, or 10

  13. Mastery and Performance Goals Predict Epistemic and Relational Conflict Regulation

    Science.gov (United States)

    Darnon, Celine; Muller, Dominique; Schrager, Sheree M.; Pannuzzo, Nelly; Butera, Fabrizio

    2006-01-01

    The present research examines whether mastery and performance goals predict different ways of reacting to a sociocognitive conflict with another person over materials to be learned, an issue not yet addressed by the achievement goal literature. Results from 2 studies showed that mastery goals predicted epistemic conflict regulation (a conflict…

  14. Comparison and Prediction of Preclinical Students' Performance in ...

    African Journals Online (AJOL)

    olayemitoyin

    The data support the hypothesis that students who performed well in one discipline were likely to .... predict success in the clinical curriculum (Baciewicz,. 1990). Similarly ... the International Association of Medical Science. Educators. 17-20.

  15. Determining Mean Predicted Performance for Army Job Families

    National Research Council Canada - National Science Library

    Zeidner, Joseph

    2003-01-01

    The present study is designed to obtain mean predicted performance (MPPs) for the 9- and 17-job families, using composites based on 7 ASVAB tests, using a triple cross validation design permitting completely unbiased estimates of MPP...

  16. Predictive factors for masticatory performance in Duchenne muscular dystrophy

    NARCIS (Netherlands)

    Bruggen, H.W. van; Engel-Hoek, L. van den; Steenks, M.H.; Bronkhorst, E.M.; Creugers, N.H.; Groot, I.J.M. de; Kalaykova, S.

    2014-01-01

    Patients with Duchenne muscular dystrophy (DMD) report masticatory and swallowing problems. Such problems may cause complications such as choking, and feeling of food sticking in the throat. We investigated whether masticatory performance in DMD is objectively impaired, and explored predictive

  17. Mining Behavior Based Safety Data to Predict Safety Performance

    Energy Technology Data Exchange (ETDEWEB)

    Jeffrey C. Joe

    2010-06-01

    The Idaho National Laboratory (INL) operates a behavior based safety program called Safety Observations Achieve Results (SOAR). This peer-to-peer observation program encourages employees to perform in-field observations of each other's work practices and habits (i.e., behaviors). The underlying premise of conducting these observations is that more serious accidents are prevented from occurring because lower level “at risk” behaviors are identified and corrected before they can propagate into culturally accepted “unsafe” behaviors that result in injuries or fatalities. Although the approach increases employee involvement in safety, the premise of the program has not been subject to sufficient empirical evaluation. The INL now has a significant amount of SOAR data on these lower level “at risk” behaviors. This paper describes the use of data mining techniques to analyze these data to determine whether they can predict if and when a more serious accident will occur.

  18. Predictive testing of performance of metals in HTR service environments

    International Nuclear Information System (INIS)

    Kondo, T.; Shindo, M.; Tamura, M.; Tsuji, H.; Kurata, Y.; Tsukada, T.

    1982-01-01

    Status of the material testing in simulated HTGR environment is reviewed with special attention focused on the methodology of the prediction of performance in long time. Importance of controlling effective chemical potentials relations in the material-environmental interface is stressed in regard of the complex inter-dependent kinetic relation between oxidation and carbon transport. Based on the recent experimental observations, proposals are made to establish some procedures for conservative prediction of the metal performance

  19. Prediction of Job Performance: Review of Military Studies

    Science.gov (United States)

    1982-03-01

    an assessment center to predict filed leadership performance of Army officers and NCOs. Proceedings of the 19th Annual Military Testing Association...C. Behaviors, results, and organizational effectiveness: The problem of criteria. In Dunnette, M. D. (Ed.), Handbook of Industrial and organizatin ...than for the Navy enlisted group. 30. Dyer, F. N., & Hlilligoss, R. Z. Using an assessment center to predict field leadership performance of Army

  20. Measuring and Predicting Sleep and Performance During Military Operations

    Science.gov (United States)

    2012-08-23

    strengths of this modeling approach is that accurate predictions of fatigue, performance, or alert- ness can be made from observed sleep timing...and, in which fatigue, performance, or alertness predictions are required prior to the task. Limitations of Current Models The strengths and...mean ± SD, 35.9 ± 1.2 hours), crews flew to Auckland , New Zealand, where another short layover was un- dertaken (23.6 ± 0.95 hours). A final flight

  1. Performance Prediction of Constrained Waveform Design for Adaptive Radar

    Science.gov (United States)

    2016-11-01

    the famous Woodward quote, having a ubiquitous feeling for all radar waveform design (and performance prediction) researchers , that is found at the end...discuss research that develops performance prediction models to quantify the impact on SINR when an amplitude constraint is placed on a radar waveform...optimize the radar perfor- mance for the particular scenario and tasks. There have also been several survey papers on various topics in waveform design for

  2. Exploring the significance of human mobility patterns in social link prediction

    KAUST Repository

    Alharbi, Basma Mohammed; Zhang, Xiangliang

    2014-01-01

    Link prediction is a fundamental task in social networks. Recently, emphasis has been placed on forecasting new social ties using user mobility patterns, e.g., investigating physical and semantic co-locations for new proximity measure. This paper

  3. On the significance of the noise model for the performance of a linear MPC in closed-loop operation

    DEFF Research Database (Denmark)

    Hagdrup, Morten; Boiroux, Dimitri; Mahmoudi, Zeinab

    2016-01-01

    This paper discusses the significance of the noise model for the performance of a Model Predictive Controller when operating in closed-loop. The process model is parametrized as a continuous-time (CT) model and the relevant sampled-data filtering and control algorithms are developed. Using CT...... models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation...

  4. Further developments in performance prediction techniques of adiabatic diesel engines

    Energy Technology Data Exchange (ETDEWEB)

    Rasihhan, Y

    1990-01-01

    The engine cycle simulation program 'SPICE', developed at Bath University, has been used extensively for insulated diesel engine research. The present study introduces more comprehensive engine heat transfer models thus enabling us to study the insulated engine heat transfer and performance characteristics in more detail. The new version of 'SPICE' separates the gas to wall heat transfer into two parts, convective and radiative. For this purpose, a detailed radiative heat transfer model which considers both the flame (gas and soot) and wall to wall radiative heat transfer is written. The previous engine resistance model is refined and replaced by a more detailed resistance model which considers piston-liner conduction heat transfer and 2-D heat flow in the liner. The wall surface temperature swing is also included in the engine heat transfer calculations which is quite significant in low conductivity ceramic insulated engines. A 1-D finite difference model is written for the transient heat transfer region of the wall and linked to the engine resistance model. This new version of 'SPICE' is used to predict the insulated engine heat transfer and performance for the experimental Petter PH1W engine for various insulation levels and schemes. An answer to the controversy of increase in engine heat loss with insulation is looked for. The effect of wall deposits on engine heat transfer and its significance for the insulated engine is highlighted. (Author).

  5. Multivariate performance reliability prediction in real-time

    International Nuclear Information System (INIS)

    Lu, S.; Lu, H.; Kolarik, W.J.

    2001-01-01

    This paper presents a technique for predicting system performance reliability in real-time considering multiple failure modes. The technique includes on-line multivariate monitoring and forecasting of selected performance measures and conditional performance reliability estimates. The performance measures across time are treated as a multivariate time series. A state-space approach is used to model the multivariate time series. Recursive forecasting is performed by adopting Kalman filtering. The predicted mean vectors and covariance matrix of performance measures are used for the assessment of system survival/reliability with respect to the conditional performance reliability. The technique and modeling protocol discussed in this paper provide a means to forecast and evaluate the performance of an individual system in a dynamic environment in real-time. The paper also presents an example to demonstrate the technique

  6. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  7. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  8. Music-related reward responses predict episodic memory performance.

    Science.gov (United States)

    Ferreri, Laura; Rodriguez-Fornells, Antoni

    2017-12-01

    Music represents a special type of reward involving the recruitment of the mesolimbic dopaminergic system. According to recent theories on episodic memory formation, as dopamine strengthens the synaptic potentiation produced by learning, stimuli triggering dopamine release could result in long-term memory improvements. Here, we behaviourally test whether music-related reward responses could modulate episodic memory performance. Thirty participants rated (in terms of arousal, familiarity, emotional valence, and reward) and encoded unfamiliar classical music excerpts. Twenty-four hours later, their episodic memory was tested (old/new recognition and remember/know paradigm). Results revealed an influence of music-related reward responses on memory: excerpts rated as more rewarding were significantly better recognized and remembered. Furthermore, inter-individual differences in the ability to experience musical reward, measured through the Barcelona Music Reward Questionnaire, positively predicted memory performance. Taken together, these findings shed new light on the relationship between music, reward and memory, showing for the first time that music-driven reward responses are directly implicated in higher cognitive functions and can account for individual differences in memory performance.

  9. Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

    Directory of Open Access Journals (Sweden)

    Sers Christine T

    2010-12-01

    Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.

  10. Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small cell lung carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Duan, X-Y.; Wang, W.; Li, M.; Li, Y.; Guo, Y-M. [PET-CT Center, The First Affiliated Hospital of Xi' an, Jiaotong University, Xi' an, Shaanxi (China)

    2015-02-03

    {sup 18}F-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is widely used to diagnose and stage non-small cell lung cancer (NSCLC). The aim of this retrospective study was to evaluate the predictive ability of different FDG standardized uptake values (SUVs) in 74 patients with newly diagnosed NSCLC. {sup 18}F-FDG PET/CT scans were performed and different SUV parameters (SUV{sub max}, SUV{sub avg}, SUV{sub T/L}, and SUV{sub T/A}) obtained, and their relationship with clinical characteristics were investigated. Meanwhile, correlation and multiple stepwise regression analyses were performed to determine the primary predictor of SUVs for NSCLC. Age, gender, and tumor size significantly affected SUV parameters. The mean SUVs of squamous cell carcinoma were higher than those of adenocarcinoma. Poorly differentiated tumors exhibited higher SUVs than well-differentiated ones. Further analyses based on the pathologic type revealed that the SUV{sub max}, SUV{sub avg}, and SUV{sub T/L} of poorly differentiated adenocarcinoma tumors were higher than those of moderately or well-differentiated tumors. Among these four SUV parameters, SUV{sub T/L} was the primary predictor for tumor differentiation. However, in adenocarcinoma, SUV{sub max} was the determining factor for tumor differentiation. Our results showed that these four SUV parameters had predictive significance related to NSCLC tumor differentiation; SUV{sub T/L} appeared to be most useful overall, but SUV{sub max} was the best index for adenocarcinoma tumor differentiation.

  11. Prevalence, significance and predictive value of antiphospholipid antibodies in Crohn’s disease

    Science.gov (United States)

    Sipeki, Nora; Davida, Laszlo; Palyu, Eszter; Altorjay, Istvan; Harsfalvi, Jolan; Antal Szalmas, Peter; Szabo, Zoltan; Veres, Gabor; Shums, Zakera; Norman, Gary L; Lakatos, Peter L; Papp, Maria

    2015-01-01

    AIM: To assess the prevalence and stability of different antiphospholipid antibodies (APLAs) and their association with disease phenotype and progression in inflammatory bowel diseases (IBD) patients. METHODS: About 458 consecutive patients [Crohn’s disease (CD): 271 and ulcerative colitis (UC): 187] were enrolled into a follow-up cohort study in a tertiary IBD referral center in Hungary. Detailed clinical phenotypes were determined at enrollment by reviewing the patients’ medical charts. Disease activity, medical treatment and data about evolvement of complications or surgical interventions were determined prospectively during the follow-up. Disease course (development f complicated disease phenotype and need for surgery), occurrence of thrombotic events, actual state of disease activity according to clinical, laboratory and endoscopic scores and accurate treatment regime were recorded during the follow-up, (median, 57.4 and 61.6 mo for CD and UC). Sera of IBD patients and 103 healthy controls (HC) were tested on individual anti-β2-Glycoprotein-I (anti-β2-GPI IgA/M/G), anti-cardiolipin (ACA IgA/M/G) and anti-phosphatidylserine/prothrombin (anti-PS/PT IgA/M/G) antibodies and also anti-Saccharomyces cerevisiae antibodies (ASCA IgA/G) by enzyme-linked immunosorbent assay (ELISA). In a subgroup of CD (n = 198) and UC patients (n = 103), obtaining consecutive samples over various arbitrary time-points during the disease course, we evaluated the intraindividual stability of the APLA status. Additionally, we provide an overview of studies, performed so far, in which significance of APLAs in IBD were assessed. RESULTS: Patients with CD had significantly higher prevalence of both ACA (23.4%) and anti-PS/PT (20.4%) antibodies than UC (4.8%, P < 0.0001 and 10.2%, P = 0.004) and HC (2.9%, P < 0.0001 and 15.5%, P = NS). No difference was found for the prevalence of anti-β2-GPI between different groups (7.2%-9.7%). In CD, no association was found between APLA and ASCA

  12. Predicting Document Retrieval System Performance: An Expected Precision Measure.

    Science.gov (United States)

    Losee, Robert M., Jr.

    1987-01-01

    Describes an expected precision (EP) measure designed to predict document retrieval performance. Highlights include decision theoretic models; precision and recall as measures of system performance; EP graphs; relevance feedback; and computing the retrieval status value of a document for two models, the Binary Independent Model and the Two Poisson…

  13. Predicting Academic Performance Based on Students' Blog and Microblog Posts

    NARCIS (Netherlands)

    Dascalu, Mihai; Popescu, Elvira; Becheru, Alexandru; Crossley, Scott; Trausan-Matu, Stefan

    2016-01-01

    This study investigates the degree to which textual complexity indices applied on students’ online contributions, corroborated with a longitudinal analysis performed on their weekly posts, predict academic performance. The source of student writing consists of blog and microblog posts, created in

  14. Significant increase of Echinococcus multilocularis prevalencein foxes, but no increased predicted risk for humans

    NARCIS (Netherlands)

    Maas, M.; Dam-Deisz, W.D.C.; Roon, van A.M.; Takumi, K.; Giessen, van der J.W.B.

    2014-01-01

    The emergence of the zoonotic tapeworm Echinococcus multilocularis, causative agent ofalveolar echinococcosis (AE), poses a public health risk. A previously designed risk mapmodel predicted a spread of E. multilocularis and increasing numbers of alveolar echinococ-cosis patients in the province of

  15. The significance of parenchymal changes of acute cellular rejection in predicting chronic liver graft rejection

    NARCIS (Netherlands)

    Gouw, ASH; van den Heuvel, MC; van den Berg, AP; Slooff, NJH; de Jong, KP; Poppema, S

    2002-01-01

    Background. Chronic rejection (CR) in liver allografts shows a rapid onset and progressive course, leading to graft failure within the first year after transplantation. Most cases are preceded by episodes of acute cellular rejection (AR), but histological features predictive for the transition

  16. PREDICTIVE SIGNIFICANCE OF ANTI-HLA AUTOANTIBODIES IN HEART TRANSPLANT RECIPIENTS

    Directory of Open Access Journals (Sweden)

    O. P. Shevchenko

    2013-01-01

    Full Text Available Aim. The aim of this study was to define the role of preformed anti-HLA antibodies (anti-HLA in antibody-mediated rejection (AMR and cardiac allograft vasculopathy (CAV after heart transplantation. Materials and Methods. 140 heart transplant recipients were followed after heart transplantation performed for 106 dilated and 34 – ischemic cardiomyopathy. Anti-HLA was determined before transplantation by ELISA. Results. Recipients were divided into 2 groups: anti-HLA positive (n = 45, 32,1% and anti-HLA negative (n = 95, 67,9%. The incidence of AMR in anti-HLA positive group was 12 (26,67% and 11 (11,58% in anti-HLA negative group. Risk of AMR was significantly higher in anti-HLA positive recipients (RR 2,3: 95% CI 1,02–4,81, р = 0,03. During first three years after transplantation CAV was diagnosed in 9 (20% of anti-HLA positive recipients and in 7 (6,8% of patients without anti-HLA. (RR 2,7: 95% CI 1,08–6,82, р = 0,03. Survival in freedom from CAV in anti-HLA negative recipients was much higher than in anti-HLA positive recipients (0,89 ± 0,07, 0,72 ± 0,06, resp. (p = 0,02.Conclusions. The presence of preformed anti-HLA antibodies in candidates for heart transplantation increase the risk of AMR and CAV post transplantation in 2,3 and 2,7 times, respectively. 

  17. Predicting Story Goodness Performance from Cognitive Measures Following Traumatic Brain Injury

    Science.gov (United States)

    Le, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

    2012-01-01

    Purpose: This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Le, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. Method: One hundred…

  18. Performance reliability prediction for thermal aging based on kalman filtering

    International Nuclear Information System (INIS)

    Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

    2015-01-01

    The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

  19. The prediction of swimming performance in competition from behavioral information.

    Science.gov (United States)

    Rushall, B S; Leet, D

    1979-06-01

    The swimming performances of the Canadian Team at the 1976 Olympic Games were categorized as being improved or worse than previous best times in the events contested. The two groups had been previously assessed on the Psychological Inventories for Competitive Swimmers. A stepwise multiple-discriminant analysis of the inventory responses revealed that 13 test questions produced a perfect discrimination of group membership. The resultant discriminant functions for predicting performance classification were applied to the test responses of 157 swimmers at the 1977 Canadian Winter National Swimming Championships. Using the same performance classification criteria the accuracy of prediction was not better than chance in three of four sex by performance classifications. This yielded a failure to locate a set of behavioral factors which determine swimming performance improvements in elite competitive circumstances. The possibility of sets of factors which do not discriminate between performances in similar environments or between similar groups of swimmers was raised.

  20. The presence, predictive utility, and clinical significance of body dysmorphic symptoms in women with eating disorders

    Science.gov (United States)

    2013-01-01

    Background Both eating disorders (EDs) and body dysmorphic disorder (BDD) are disorders of body image. This study aimed to assess the presence, predictive utility, and impact of clinical features commonly associated with BDD in women with EDs. Methods Participants recruited from two non-clinical cohorts of women, symptomatic and asymptomatic of EDs, completed a survey on ED (EDE-Q) and BDD (BDDE-SR) psychopathology, psychological distress (K-10), and quality of life (SF-12). Results A strong correlation was observed between the total BDDE-SR and the global EDE-Q scores (r = 0.79, p 0.05) measured appearance checking, reassurance-seeking, camouflaging, comparison-making, and social avoidance. In addition to these behaviors, inspection of sensitivity (Se) and specificity (Sp) revealed that BDDE-SR items measuring preoccupation and dissatisfaction with appearance were most predictive of ED cases (Se and Sp > 0.60). Higher total BDDE-SR scores were associated with greater distress on the K-10 and poorer quality of life on the SF-12 (all p < 0.01). Conclusions Clinical features central to the model of BDD are common in, predictive of, and associated with impairment in women with EDs. Practice implications are that these features be included in the assessment and treatment of EDs. PMID:24999401

  1. Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

    Science.gov (United States)

    Boone, Spencer

    2017-01-01

    This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

  2. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  3. Significance of satellite sign and spot sign in predicting hematoma expansion in spontaneous intracerebral hemorrhage.

    Science.gov (United States)

    Yu, Zhiyuan; Zheng, Jun; Ali, Hasan; Guo, Rui; Li, Mou; Wang, Xiaoze; Ma, Lu; Li, Hao; You, Chao

    2017-11-01

    Hematoma expansion is related to poor outcome in spontaneous intracerebral hemorrhage (ICH). Recently, a non-enhanced computed tomography (CT) based finding, termed the 'satellite sign', was reported to be a novel predictor for poor outcome in spontaneous ICH. However, it is still unclear whether the presence of the satellite sign is related to hematoma expansion. Initial computed tomography angiography (CTA) was conducted within 6h after ictus. Satellite sign on non-enhanced CT and spot sign on CTA were detected by two independent reviewers. The sensitivity and specificity of both satellite sign and spot sign were calculated. Receiver-operator analysis was conducted to evaluate their predictive accuracy for hematoma expansion. This study included 153 patients. Satellite sign was detected in 58 (37.91%) patients and spot sign was detected in 38 (24.84%) patients. Among 37 patients with hematoma expansion, 22 (59.46%) had satellite sign and 23 (62.16%) had spot sign. The sensitivity and specificity of satellite sign for prediction of hematoma expansion were 59.46% and 68.97%, respectively. The sensitivity and specificity of spot sign were 62.16% and 87.07%, respectively. The area under the curve (AUC) of satellite sign was 0.642 and the AUC of spot sign was 0.746. (P=0.157) CONCLUSION: Our results suggest that the satellite sign is an independent predictor for hematoma expansion in spontaneous ICH. Although spot sign has the higher predictive accuracy, satellite sign is still an acceptable predictor for hematoma expansion when CTA is unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Proactive Supply Chain Performance Management with Predictive Analytics

    Directory of Open Access Journals (Sweden)

    Nenad Stefanovic

    2014-01-01

    Full Text Available Today’s business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators. Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

  5. Proactive Supply Chain Performance Management with Predictive Analytics

    Science.gov (United States)

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment. PMID:25386605

  6. Proactive supply chain performance management with predictive analytics.

    Science.gov (United States)

    Stefanovic, Nenad

    2014-01-01

    Today's business climate requires supply chains to be proactive rather than reactive, which demands a new approach that incorporates data mining predictive analytics. This paper introduces a predictive supply chain performance management model which combines process modelling, performance measurement, data mining models, and web portal technologies into a unique model. It presents the supply chain modelling approach based on the specialized metamodel which allows modelling of any supply chain configuration and at different level of details. The paper also presents the supply chain semantic business intelligence (BI) model which encapsulates data sources and business rules and includes the data warehouse model with specific supply chain dimensions, measures, and KPIs (key performance indicators). Next, the paper describes two generic approaches for designing the KPI predictive data mining models based on the BI semantic model. KPI predictive models were trained and tested with a real-world data set. Finally, a specialized analytical web portal which offers collaborative performance monitoring and decision making is presented. The results show that these models give very accurate KPI projections and provide valuable insights into newly emerging trends, opportunities, and problems. This should lead to more intelligent, predictive, and responsive supply chains capable of adapting to future business environment.

  7. Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test.

    Science.gov (United States)

    Ring, Patrick; Neyse, Levent; David-Barett, Tamas; Schmidt, Ulrich

    2016-01-01

    This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT) and whether they differ by gender. After participants completed the CRT, they predicted their own (i), the other participants' (ii), men's (iii), and women's (iv) number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women's predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one's ability relative to same and opposite sex peers.

  8. Gender Differences in Performance Predictions: Evidence from the Cognitive Reflection Test

    Directory of Open Access Journals (Sweden)

    Patrick Ring

    2016-11-01

    Full Text Available This paper studies performance predictions in the 7-item Cognitive Reflection Test (CRT and whether they differ by gender. After participants completed the CRT, they predicted their own (i, the other participants’ (ii, men’s (iii, and women’s (iv number of correct answers. In keeping with existing literature, men scored higher on the CRT than women and both men and women were too optimistic about their own performance. When we compare gender-specific predictions, we observe that men think they perform significantly better than other men and do so significantly more than women. The equality between women’s predictions about their own performance and their female peers cannot be rejected. Our findings contribute to the growing literature on the underpinnings of behavior in economics and in psychology by uncovering gender differences in confidence about one’s ability relative to same and opposite sex peers.

  9. Enhancing pavement performance prediction models for the Illinois Tollway System

    Directory of Open Access Journals (Sweden)

    Laxmikanth Premkumar

    2016-01-01

    Full Text Available Accurate pavement performance prediction represents an important role in prioritizing future maintenance and rehabilitation needs, and predicting future pavement condition in a pavement management system. The Illinois State Toll Highway Authority (Tollway with over 2000 lane miles of pavement utilizes the condition rating survey (CRS methodology to rate pavement performance. Pavement performance models developed in the past for the Illinois Department of Transportation (IDOT are used by the Tollway to predict the future condition of its network. The model projects future CRS ratings based on pavement type, thickness, traffic, pavement age and current CRS rating. However, with time and inclusion of newer pavement types there was a need to calibrate the existing pavement performance models, as well as, develop models for newer pavement types.This study presents the results of calibrating the existing models, and developing new models for the various pavement types in the Illinois Tollway network. The predicted future condition of the pavements is used in estimating its remaining service life to failure, which is of immediate use in recommending future maintenance and rehabilitation requirements for the network. Keywords: Pavement performance models, Remaining life, Pavement management

  10. Predicting university performance in psychology: the role of previous performance and discipline-specific knowledge

    OpenAIRE

    Betts, LR; Elder, TJ; Hartley, J; Blurton, A

    2008-01-01

    Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry qualifications predicted: (1) their performance in years 1-3 of their Psychology degree, and (2) their overall degree performance. Students' overall...

  11. The Search Performance Evaluation and Prediction in Exploratory Search

    OpenAIRE

    LIU, FEI

    2016-01-01

    The exploratory search for complex search tasks requires an effective search behavior model to evaluate and predict user search performance. Few studies have investigated the relationship between user search behavior and search performance in exploratory search. This research adopts a mixed approach combining search system development, user search experiment, search query log analysis, and multivariate regression analysis to resolve the knowledge gap. Through this study, it is shown that expl...

  12. Predictive Bias and Sensitivity in NRC Fuel Performance Codes

    Energy Technology Data Exchange (ETDEWEB)

    Geelhood, Kenneth J.; Luscher, Walter G.; Senor, David J.; Cunningham, Mitchel E.; Lanning, Donald D.; Adkins, Harold E.

    2009-10-01

    The latest versions of the fuel performance codes, FRAPCON-3 and FRAPTRAN were examined to determine if the codes are intrinsically conservative. Each individual model and type of code prediction was examined and compared to the data that was used to develop the model. In addition, a brief literature search was performed to determine if more recent data have become available since the original model development for model comparison.

  13. STUDENT ACADEMIC PERFORMANCE PREDICTION USING SUPPORT VECTOR MACHINE

    OpenAIRE

    S.A. Oloruntoba1 ,J.L.Akinode2

    2017-01-01

    This paper investigates the relationship between students' preadmission academic profile and final academic performance. Data Sample of students in one of the Federal Polytechnic in south West part of Nigeria was used. The preadmission academic profile used for this study is the 'O' level grades(terminal high school results).The academic performance is defined using student's Grade Point Average(GPA). This research focused on using data mining technique to develop a model for predicting stude...

  14. Children's biological responsivity to acute stress predicts concurrent cognitive performance.

    Science.gov (United States)

    Roos, Leslie E; Beauchamp, Kathryn G; Giuliano, Ryan; Zalewski, Maureen; Kim, Hyoun K; Fisher, Philip A

    2018-04-10

    Although prior research has characterized stress system reactivity (i.e. hypothalamic-pituitary-adrenal axis, HPAA; autonomic nervous system, ANS) in children, it has yet to examine the extent to which biological reactivity predicts concurrent goal-directed behavior. Here, we employed a stressor paradigm that allowed concurrent assessment of both stress system reactivity and performance on a speeded-response task to investigate the links between biological reactivity and cognitive function under stress. We further investigated gender as a moderator given previous research suggesting that the ANS may be particularly predictive of behavior in males due to gender differences in socialization. In a sociodemographically diverse sample of young children (N = 58, M age = 5.38 yrs; 44% male), individual differences in sociodemographic covariates (age, household income), HPAA (i.e. cortisol), and ANS (i.e. respiratory sinus arrhythmia, RSA, indexing the parasympathetic branch; pre-ejection period, PEP, indexing the sympathetic branch) function were assessed as predictors of cognitive performance under stress. We hypothesized that higher income, older age, and greater cortisol reactivity would be associated with better performance overall, and flexible ANS responsivity (i.e. RSA withdrawal, PEP shortening) would be predictive of performance for males. Overall, females performed better than males. Two-group SEM analyses suggest that, for males, greater RSA withdrawal to the stressor was associated with better performance, while for females, older age, higher income, and greater cortisol reactivity were associated with better performance. Results highlight the relevance of stress system reactivity to cognitive performance under stress. Future research is needed to further elucidate for whom and in what situations biological reactivity predicts goal-directed behavior.

  15. Climbing fibers predict movement kinematics and performance errors.

    Science.gov (United States)

    Streng, Martha L; Popa, Laurentiu S; Ebner, Timothy J

    2017-09-01

    Requisite for understanding cerebellar function is a complete characterization of the signals provided by complex spike (CS) discharge of Purkinje cells, the output neurons of the cerebellar cortex. Numerous studies have provided insights into CS function, with the most predominant view being that they are evoked by error events. However, several reports suggest that CSs encode other aspects of movements and do not always respond to errors or unexpected perturbations. Here, we evaluated CS firing during a pseudo-random manual tracking task in the monkey ( Macaca mulatta ). This task provides extensive coverage of the work space and relative independence of movement parameters, delivering a robust data set to assess the signals that activate climbing fibers. Using reverse correlation, we determined feedforward and feedback CSs firing probability maps with position, velocity, and acceleration, as well as position error, a measure of tracking performance. The direction and magnitude of the CS modulation were quantified using linear regression analysis. The major findings are that CSs significantly encode all three kinematic parameters and position error, with acceleration modulation particularly common. The modulation is not related to "events," either for position error or kinematics. Instead, CSs are spatially tuned and provide a linear representation of each parameter evaluated. The CS modulation is largely predictive. Similar analyses show that the simple spike firing is modulated by the same parameters as the CSs. Therefore, CSs carry a broader array of signals than previously described and argue for climbing fiber input having a prominent role in online motor control. NEW & NOTEWORTHY This article demonstrates that complex spike (CS) discharge of cerebellar Purkinje cells encodes multiple parameters of movement, including motor errors and kinematics. The CS firing is not driven by error or kinematic events; instead it provides a linear representation of each

  16. Significance of collateral vessels on the prediction of superior vena cava syndrome on CT

    International Nuclear Information System (INIS)

    Kim, Hyun Sook; Kim, Hyung Jin; Lee, Hyeng Gon; Ahn, In Oak; Chung, Sung Hoon

    1993-01-01

    Although visible collateral vessels on computed tomography (CT) has been considered as an important finding in superior vena cava (SVC) syndrome, there is no systematical analysis concerning correlation between the CT evidence of collateral vessels and clinical evidence of SVC syndrome. The purpose of this study is to evaluate how accurately we predict the clinical presence of SVC syndrome by the collateral vessels in patients with apparent SVC obstruction in CT. Forty seven patients having a CT evidence of obstruction or compression of SVC and/or its major tributaries were included in this study. Lung cancer was the most common underlying disease (n=40). The enhanced CT scans were obtained through either arm vein using a combined bolus and drip-infusion technique. Analyzing the CT scans, we particularly paid attention to the site and pattern of venous compromise, presence of collateral vessels, and if present, their location, without knowing whether symptoms and sign were present or nor, and then compared them with clinical data by a thorough review of charts, To verify the frequency of visible collateral vessels in normal subjects, we also evaluated the CT scans of 50 patients without mediastinal disease and clinical SVC syndrome as a control group. On CT, collateral vessels were found in 24 patients, among whom three patient had a single collateral and 21 patients had two or more collateral channels. There were two false positive cases, in which clinically overt SVC syndrome appeared 10 days and three months after CT examination respectively, and one false negative case. The presence of collateral vessels on CT, respectively, and one false negative case. The presence of collateral vessels on CT, regardless of the number and location of collateral vessels and pattern of venous obstruction, was a good clue for predicting the presence of clinical SVC syndrome with the sensitivity and the specificity of 95.7% and 91.7%, respectively. In control group, collateral

  17. Analysis of Factors that Predict Clinical Performance in Medical School

    Science.gov (United States)

    White, Casey B.; Dey, Eric L.; Fantone, Joseph C.

    2009-01-01

    Academic achievement indices including GPAs and MCAT scores are used to predict the spectrum of medical student academic performance types. However, use of these measures ignores two changes influencing medical school admissions: student diversity and affirmative action, and an increased focus on communication skills. To determine if GPA and MCAT…

  18. Predicting Performance in Higher Education Using Proximal Predictors

    NARCIS (Netherlands)

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

    2016-01-01

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

  19. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...

  20. Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes.

    Science.gov (United States)

    Hung, Andrew J; Chen, Jian; Che, Zhengping; Nilanon, Tanachat; Jarc, Anthony; Titus, Micha; Oh, Paul J; Gill, Inderbir S; Liu, Yan

    2018-05-01

    Surgical performance is critical for clinical outcomes. We present a novel machine learning (ML) method of processing automated performance metrics (APMs) to evaluate surgical performance and predict clinical outcomes after robot-assisted radical prostatectomy (RARP). We trained three ML algorithms utilizing APMs directly from robot system data (training material) and hospital length of stay (LOS; training label) (≤2 days and >2 days) from 78 RARP cases, and selected the algorithm with the best performance. The selected algorithm categorized the cases as "Predicted as expected LOS (pExp-LOS)" and "Predicted as extended LOS (pExt-LOS)." We compared postoperative outcomes of the two groups (Kruskal-Wallis/Fisher's exact tests). The algorithm then predicted individual clinical outcomes, which we compared with actual outcomes (Spearman's correlation/Fisher's exact tests). Finally, we identified five most relevant APMs adopted by the algorithm during predicting. The "Random Forest-50" (RF-50) algorithm had the best performance, reaching 87.2% accuracy in predicting LOS (73 cases as "pExp-LOS" and 5 cases as "pExt-LOS"). The "pExp-LOS" cases outperformed the "pExt-LOS" cases in surgery time (3.7 hours vs 4.6 hours, p = 0.007), LOS (2 days vs 4 days, p = 0.02), and Foley duration (9 days vs 14 days, p = 0.02). Patient outcomes predicted by the algorithm had significant association with the "ground truth" in surgery time (p algorithm in predicting, were largely related to camera manipulation. To our knowledge, ours is the first study to show that APMs and ML algorithms may help assess surgical RARP performance and predict clinical outcomes. With further accrual of clinical data (oncologic and functional data), this process will become increasingly relevant and valuable in surgical assessment and training.

  1. Predicting High-Power Performance in Professional Cyclists.

    Science.gov (United States)

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

    2017-03-01

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

  2. Performance evaluation recommendations and manuals of nuclear power plants outdoor significant civil structures earthquake resistance

    International Nuclear Information System (INIS)

    2005-06-01

    Performance evaluation recommendations and manuals of nuclear power plants outdoor significant civil structures earthquake resistance have been updated in June 2005 by the Japan Society of Civil Engineers. Based on experimental and analytical considerations on the recommendations of May 2002, analytical seismic models of soils for underground structures, effects of vertical motions on time-history dynamic analysis and shear fracture of reinforced concretes by cyclic loadings have been evaluated and incorporated in new recommendations. (T. Tanaka)

  3. Performance evaluation recommendations of nuclear power plants outdoor significant civil structures earthquake resistance. Technical documentation

    International Nuclear Information System (INIS)

    2005-06-01

    The Japan Society of Civil Engineers has updated performance evaluation recommendations of nuclear power plants outdoor significant civil structures earthquake resistance in June 2005. Experimental and analytical considerations on the seismic effects evaluation criteria, such as analytical seismic models of soils for underground structures, effects of vertical motions on time-history dynamic analysis and shear fracture of reinforced concretes by cyclic loadings, were shown in this document and incorporated in new recommendations. (T. Tanaka)

  4. Prediction of mandibular rotation: an empirical test of clinician performance.

    Science.gov (United States)

    Baumrind, S; Korn, E L; West, E E

    1984-11-01

    An experiment was conducted in an attempt to determine empirically how effective a number of expert clinicians were at differentiating "backward rotators" from "forward rotators" on the basis of head-film information which might reasonably have been available to them prior to instituting treatment for the correction of Class II malocclusion. As a result of a previously reported ongoing study, pre- and posttreatment head films were available for 188 patients treated in the mixed dentition for the correction of Class II malocclusion and for 50 untreated Class II subjects. These subjects were divided into 14 groups (average size of group, 17; range, 6 to 23) solely on the basis of type of treatment and the clinician from whose clinic the records had originated. From within each group, we selected the two or three subjects who had exhibited the most extreme backward rotation and the two or three subjects who had exhibited the most extreme forward rotation of the mandible during the interval between films. The sole criterion for classification was magnitude of change in the mandibular plane angle of Downs between the pre- and posttreatment films of each patient. The resulting sample contained 32 backward-rotator subjects and 32 forward-rotator subjects. Five expert judges (mean clinical experience, 28 years) were asked to identify the backward-rotator subjects by examination of the pretreatment films. The findings may be summarized as follows: (1) No judge performed significantly better than chance. (2) There was strong evidence that the judges used a shared, though relatively ineffective, set of rules in making their discriminations between forward and backward rotators. (3) Statistical analysis of the predictive power of a set of standard cephalometric measurements which had previously been made for this set of subjects indicated that the numerical data also failed to identify potential backward rotators at a rate significantly better than chance. We infer from these

  5. Predictive validity of pre-admission assessments on medical student performance.

    Science.gov (United States)

    Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef; Mohamed, Ayman

    2017-11-24

    To examine the predictive validity of pre-admission variables on students' performance in a medical school in Saudi Arabia. In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students' progress test performance (p<0.001 and B=19.02). Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years.

  6. Entity versus incremental theories predict older adults' memory performance.

    Science.gov (United States)

    Plaks, Jason E; Chasteen, Alison L

    2013-12-01

    The authors examined whether older adults' implicit theories regarding the modifiability of memory in particular (Studies 1 and 3) and abilities in general (Study 2) would predict memory performance. In Study 1, individual differences in older adults' endorsement of the "entity theory" (a belief that one's ability is fixed) or "incremental theory" (a belief that one's ability is malleable) of memory were measured using a version of the Implicit Theories Measure (Dweck, 1999). Memory performance was assessed with a free-recall task. Results indicated that the higher the endorsement of the incremental theory, the better the free recall. In Study 2, older and younger adults' theories were measured using a more general version of the Implicit Theories Measure that focused on the modifiability of abilities in general. Again, for older adults, the higher the incremental endorsement, the better the free recall. Moreover, as predicted, implicit theories did not predict younger adults' memory performance. In Study 3, participants read mock news articles reporting evidence in favor of either the entity or incremental theory. Those in the incremental condition outperformed those in the entity condition on reading span and free-recall tasks. These effects were mediated by pretask worry such that, for those in the entity condition, higher worry was associated with lower performance. Taken together, these studies suggest that variation in entity versus incremental endorsement represents a key predictor of older adults' memory performance. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  7. Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

    Science.gov (United States)

    Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

    2018-02-01

    In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

  8. Calibration between Undergraduate Students' Prediction of and Actual Performance: The Role of Gender and Performance Attributions

    Science.gov (United States)

    Gutierrez, Antonio P.; Price, Addison F.

    2017-01-01

    This study investigated changes in male and female students' prediction and postdiction calibration accuracy and bias scores, and the predictive effects of explanatory styles on these variables beyond gender. Seventy undergraduate students rated their confidence in performance before and after a 40-item exam. There was an improvement in students'…

  9. A new model using routinely available clinical parameters to predict significant liver fibrosis in chronic hepatitis B.

    Directory of Open Access Journals (Sweden)

    Wai-Kay Seto

    Full Text Available OBJECTIVE: We developed a predictive model for significant fibrosis in chronic hepatitis B (CHB based on routinely available clinical parameters. METHODS: 237 treatment-naïve CHB patients [58.4% hepatitis B e antigen (HBeAg-positive] who had undergone liver biopsy were randomly divided into two cohorts: training group (n = 108 and validation group (n = 129. Liver histology was assessed for fibrosis. All common demographics, viral serology, viral load and liver biochemistry were analyzed. RESULTS: Based on 12 available clinical parameters (age, sex, HBeAg status, HBV DNA, platelet, albumin, bilirubin, ALT, AST, ALP, GGT and AFP, a model to predict significant liver fibrosis (Ishak fibrosis score ≥3 was derived using the five best parameters (age, ALP, AST, AFP and platelet. Using the formula log(index+1 = 0.025+0.0031(age+0.1483 log(ALP+0.004 log(AST+0.0908 log(AFP+1-0.028 log(platelet, the PAPAS (Platelet/Age/Phosphatase/AFP/AST index predicts significant fibrosis with an area under the receiving operating characteristics (AUROC curve of 0.776 [0.797 for patients with ALT <2×upper limit of normal (ULN] The negative predictive value to exclude significant fibrosis was 88.4%. This predictive power is superior to other non-invasive models using common parameters, including the AST/platelet/GGT/AFP (APGA index, AST/platelet ratio index (APRI, and the FIB-4 index (AUROC of 0.757, 0.708 and 0.723 respectively. Using the PAPAS index, 67.5% of liver biopsies for patients being considered for treatment with ALT <2×ULN could be avoided. CONCLUSION: The PAPAS index can predict and exclude significant fibrosis, and may reduce the need for liver biopsy in CHB patients.

  10. Predictive Measures of Locomotor Performance on an Unstable Walking Surface

    Science.gov (United States)

    Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Caldwell, E. E.; Batson, C. D.; De Dios, Y. E.; Gadd, N. E.; Goel, R.; Wood, S. J.; Cohen, H. S.; hide

    2016-01-01

    Locomotion requires integration of visual, vestibular, and somatosensory information to produce the appropriate motor output to control movement. The degree to which these sensory inputs are weighted and reorganized in discordant sensory environments varies by individual and may be predictive of the ability to adapt to novel environments. The goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to inform the design of training countermeasures designed to enhance the ability of astronauts to adapt to gravitational transitions improving balance and locomotor performance after a Mars landing and enhancing egress capability after a landing on Earth.

  11. Predicting Performance on MOOC Assessments using Multi-Regression Models

    OpenAIRE

    Ren, Zhiyun; Rangwala, Huzefa; Johri, Aditya

    2016-01-01

    The past few years has seen the rapid growth of data min- ing approaches for the analysis of data obtained from Mas- sive Open Online Courses (MOOCs). The objectives of this study are to develop approaches to predict the scores a stu- dent may achieve on a given grade-related assessment based on information, considered as prior performance or prior ac- tivity in the course. We develop a personalized linear mul- tiple regression (PLMR) model to predict the grade for a student, prior to attempt...

  12. Real-time Tsunami Inundation Prediction Using High Performance Computers

    Science.gov (United States)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

  13. A comparison of SAR ATR performance with information theoretic predictions

    Science.gov (United States)

    Blacknell, David

    2003-09-01

    Performance assessment of automatic target detection and recognition algorithms for SAR systems (or indeed any other sensors) is essential if the military utility of the system / algorithm mix is to be quantified. This is a relatively straightforward task if extensive trials data from an existing system is used. However, a crucial requirement is to assess the potential performance of novel systems as a guide to procurement decisions. This task is no longer straightforward since a hypothetical system cannot provide experimental trials data. QinetiQ has previously developed a theoretical technique for classification algorithm performance assessment based on information theory. The purpose of the study presented here has been to validate this approach. To this end, experimental SAR imagery of targets has been collected using the QinetiQ Enhanced Surveillance Radar to allow algorithm performance assessments as a number of parameters are varied. In particular, performance comparisons can be made for (i) resolutions up to 0.1m, (ii) single channel versus polarimetric (iii) targets in the open versus targets in scrubland and (iv) use versus non-use of camouflage. The change in performance as these parameters are varied has been quantified from the experimental imagery whilst the information theoretic approach has been used to predict the expected variation of performance with parameter value. A comparison of these measured and predicted assessments has revealed the strengths and weaknesses of the theoretical technique as will be discussed in the paper.

  14. Is the Bishop-score significant in predicting the success of labor induction in multiparous women?

    Science.gov (United States)

    Navve, D; Orenstein, N; Ribak, R; Daykan, Y; Shechter-Maor, G; Biron-Shental, T

    2017-05-01

    To determine whether the Bishop-score upon admission effects mode of delivery, maternal or neonatal outcomes of labor induction in multiparous women. A retrospective study including 600 multiparous women with a singleton pregnancy, 34 gestational weeks and above who underwent labor induction for maternal, fetal or combined indications. Induction was performed with one of three methods- oxytocin, a slow release vaginal prostaglandin E2 insert (10 mg dinoprostone) or a transcervical double balloon catheter. The women were divided into two groups-Bishop-score manual lysis, uterine revision, perineal tear grade 3-4, need for blood transfusions, relaparotomy, prolonged hospitalization) and neonatal outcomes (Apgar score, cord pH, hospitalization in the neonatal intensive care unit, prolonged hospitalization). Both groups had a high rate of vaginal deliveries-93.7% and 94.9%, respectively. There was no difference between the two groups in terms of maternal or neonatal outcomes. Labor induction in multiparous women is safe and successful regardless of the initial Bishop-score. In multiparous women the Bishop-score is not a good predictor for the success of labor induction, nor is it a predictor for maternal of neonatal adverse outcomes and complications.

  15. Prediction of Tennis Performance in Junior Elite Tennis Players

    Directory of Open Access Journals (Sweden)

    Tamara Kramer, Barbara C.H. Huijgen, Marije T. Elferink-Gemser, Chris Visscher

    2017-03-01

    Full Text Available Predicting current and future tennis performance can lead to improving the development of junior tennis players. The aim of this study is to investigate whether age, maturation, or physical fitness in junior elite tennis players in U13 can explain current and future tennis performance. The value of current tennis performance for future tennis performance is also investigated. A total of 86 junior elite tennis players (boys, n = 44; girls, n = 42 U13 (aged: 12.5 ± 0.3 years, and followed to U16, took part in this study. All players were top-30 ranked on the Dutch national ranking list at U13, and top-50 at U16. Age, maturation, and physical fitness, were measured at U13. A principal component analysis was used to extract four physical components from eight tests (medicine ball throwing overhead and reverse, ball throwing, SJ, CMJas, Sprint 5 and 10 meter, and the spider test. The possible relationship of age, maturation, and the physical components; “upper body power”, “lower body power”, “speed”, and “agility” with tennis performance at U13 and U16 was analyzed. Tennis performance was measured by using the ranking position on the Dutch national ranking list at U13 and U16. Regression analyses were conducted based on correlations between variables and tennis performance for boys and girls, separately. In boys U13, positive correlations were found between upper body power and tennis performance (R2 is 25%. In girls, positive correlations between maturation and lower body power with tennis performance were found at U13. Early maturing players were associated with a better tennis performance (R2 is 15%. In girls U16, only maturation correlated with tennis performance (R2 is 13%; later-maturing girls at U13 had better tennis performances at U16. Measuring junior elite tennis players at U13 is important for monitoring their development. These measurements did not predict future tennis performance of junior elite tennis players three

  16. Accurate prediction of the functional significance of single nucleotide polymorphisms and mutations in the ABCA1 gene.

    Directory of Open Access Journals (Sweden)

    Liam R Brunham

    2005-12-01

    Full Text Available The human genome contains an estimated 100,000 to 300,000 DNA variants that alter an amino acid in an encoded protein. However, our ability to predict which of these variants are functionally significant is limited. We used a bioinformatics approach to define the functional significance of genetic variation in the ABCA1 gene, a cholesterol transporter crucial for the metabolism of high density lipoprotein cholesterol. To predict the functional consequence of each coding single nucleotide polymorphism and mutation in this gene, we calculated a substitution position-specific evolutionary conservation score for each variant, which considers site-specific variation among evolutionarily related proteins. To test the bioinformatics predictions experimentally, we evaluated the biochemical consequence of these sequence variants by examining the ability of cell lines stably transfected with the ABCA1 alleles to elicit cholesterol efflux. Our bioinformatics approach correctly predicted the functional impact of greater than 94% of the naturally occurring variants we assessed. The bioinformatics predictions were significantly correlated with the degree of functional impairment of ABCA1 mutations (r2 = 0.62, p = 0.0008. These results have allowed us to define the impact of genetic variation on ABCA1 function and to suggest that the in silico evolutionary approach we used may be a useful tool in general for predicting the effects of DNA variation on gene function. In addition, our data suggest that considering patterns of positive selection, along with patterns of negative selection such as evolutionary conservation, may improve our ability to predict the functional effects of amino acid variation.

  17. Survival prediction algorithms miss significant opportunities for improvement if used for case selection in trauma quality improvement programs.

    Science.gov (United States)

    Heim, Catherine; Cole, Elaine; West, Anita; Tai, Nigel; Brohi, Karim

    2016-09-01

    Quality improvement (QI) programs have shown to reduce preventable mortality in trauma care. Detailed review of all trauma deaths is a time and resource consuming process and calculated probability of survival (Ps) has been proposed as audit filter. Review is limited on deaths that were 'expected to survive'. However no Ps-based algorithm has been validated and no study has examined elements of preventability associated with deaths classified as 'expected'. The objective of this study was to examine whether trauma performance review can be streamlined using existing mortality prediction tools without missing important areas for improvement. We conducted a retrospective study of all trauma deaths reviewed by our trauma QI program. Deaths were classified into non-preventable, possibly preventable, probably preventable or preventable. Opportunities for improvement (OPIs) involve failure in the process of care and were classified into clinical and system deviations from standards of care. TRISS and PS were used for calculation of probability of survival. Peer-review charts were reviewed by a single investigator. Over 8 years, 626 patients were included. One third showed elements of preventability and 4% were preventable. Preventability occurred across the entire range of the calculated Ps band. Limiting review to unexpected deaths would have missed over 50% of all preventability issues and a third of preventable deaths. 37% of patients showed opportunities for improvement (OPIs). Neither TRISS nor PS allowed for reliable identification of OPIs and limiting peer-review to patients with unexpected deaths would have missed close to 60% of all issues in care. TRISS and PS fail to identify a significant proportion of avoidable deaths and miss important opportunities for process and system improvement. Based on this, all trauma deaths should be subjected to expert panel review in order to aim at a maximal output of performance improvement programs. Copyright © 2016 Elsevier

  18. Performance monitoring and error significance in patients with obsessive-compulsive disorder.

    Science.gov (United States)

    Endrass, Tanja; Schuermann, Beate; Kaufmann, Christan; Spielberg, Rüdiger; Kniesche, Rainer; Kathmann, Norbert

    2010-05-01

    Performance monitoring has been consistently found to be overactive in obsessive-compulsive disorder (OCD). The present study examines whether performance monitoring in OCD is adjusted with error significance. Therefore, errors in a flanker task were followed by neutral (standard condition) or punishment feedbacks (punishment condition). In the standard condition patients had significantly larger error-related negativity (ERN) and correct-related negativity (CRN) ampliudes than controls. But, in the punishment condition groups did not differ in ERN and CRN amplitudes. While healthy controls showed an amplitude enhancement between standard and punishment condition, OCD patients showed no variation. In contrast, group differences were not found for the error positivity (Pe): both groups had larger Pe amplitudes in the punishment condition. Results confirm earlier findings of overactive error monitoring in OCD. The absence of a variation with error significance might indicate that OCD patients are unable to down-regulate their monitoring activity according to external requirements. Copyright 2010 Elsevier B.V. All rights reserved.

  19. Frontoparietal white matter integrity predicts haptic performance in chronic stroke

    Directory of Open Access Journals (Sweden)

    Alexandra L. Borstad

    2016-01-01

    Full Text Available Frontoparietal white matter supports information transfer between brain areas involved in complex haptic tasks such as somatosensory discrimination. The purpose of this study was to gain an understanding of the relationship between microstructural integrity of frontoparietal network white matter and haptic performance in persons with chronic stroke and to compare frontoparietal network integrity in participants with stroke and age matched control participants. Nineteen individuals with stroke and 16 controls participated. Haptic performance was quantified using the Hand Active Sensation Test (HASTe, an 18-item match-to-sample test of weight and texture discrimination. Three tesla MRI was used to obtain diffusion-weighted and high-resolution anatomical images of the whole brain. Probabilistic tractography was used to define 10 frontoparietal tracts total; Four intrahemispheric tracts measured bilaterally 1 thalamus to primary somatosensory cortex (T–S1, 2 thalamus to primary motor cortex (T–M1, 3 primary to secondary somatosensory cortex (S1 to SII and 4 primary somatosensory cortex to middle frontal gyrus (S1 to MFG and, 2 interhemispheric tracts; S1–S1 and precuneus interhemispheric. A control tract outside the network, the cuneus interhemispheric tract, was also examined. The diffusion metrics fractional anisotropy (FA, mean diffusivity (MD, axial (AD and radial diffusivity (RD were quantified for each tract. Diminished FA and elevated MD values are associated with poorer white matter integrity in chronic stroke. Nine of 10 tracts quantified in the frontoparietal network had diminished structural integrity poststroke compared to the controls. The precuneus interhemispheric tract was not significantly different between groups. Principle component analysis across all frontoparietal white matter tract MD values indicated a single factor explained 47% and 57% of the variance in tract mean diffusivity in stroke and control groups respectively

  20. Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

    Science.gov (United States)

    Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

    2016-01-01

    Frontoparietal white matter supports information transfer between brain areas involved in complex haptic tasks such as somatosensory discrimination. The purpose of this study was to gain an understanding of the relationship between microstructural integrity of frontoparietal network white matter and haptic performance in persons with chronic stroke and to compare frontoparietal network integrity in participants with stroke and age matched control participants. Nineteen individuals with stroke and 16 controls participated. Haptic performance was quantified using the Hand Active Sensation Test (HASTe), an 18-item match-to-sample test of weight and texture discrimination. Three tesla MRI was used to obtain diffusion-weighted and high-resolution anatomical images of the whole brain. Probabilistic tractography was used to define 10 frontoparietal tracts total; Four intrahemispheric tracts measured bilaterally 1) thalamus to primary somatosensory cortex (T-S1), 2) thalamus to primary motor cortex (T-M1), 3) primary to secondary somatosensory cortex (S1 to SII) and 4) primary somatosensory cortex to middle frontal gyrus (S1 to MFG) and, 2 interhemispheric tracts; S1-S1 and precuneus interhemispheric. A control tract outside the network, the cuneus interhemispheric tract, was also examined. The diffusion metrics fractional anisotropy (FA), mean diffusivity (MD), axial (AD) and radial diffusivity (RD) were quantified for each tract. Diminished FA and elevated MD values are associated with poorer white matter integrity in chronic stroke. Nine of 10 tracts quantified in the frontoparietal network had diminished structural integrity poststroke compared to the controls. The precuneus interhemispheric tract was not significantly different between groups. Principle component analysis across all frontoparietal white matter tract MD values indicated a single factor explained 47% and 57% of the variance in tract mean diffusivity in stroke and control groups respectively. Age

  1. Prediction of significant conduction disease through noninvasive assessment of cardiac calcification.

    Science.gov (United States)

    Mainigi, Sumeet K; Chebrolu, Lakshmi Hima Bindu; Romero-Corral, Abel; Mehta, Vinay; Machado, Rodolfo Rozindo; Konecny, Tomas; Pressman, Gregg S

    2012-10-01

    Cardiac calcification is associated with coronary artery disease, arrhythmias, conduction disease, and adverse cardiac events. Recently, we have described an echocardiographic-based global cardiac calcification scoring system. The objective of this study was to evaluate the severity of cardiac calcification in patients with permanent pacemakers as based on this scoring system. Patients with a pacemaker implanted within the 2-year study period with a previous echocardiogram were identified and underwent blinded global cardiac calcium scoring. These patients were compared to matched control patients without a pacemaker who also underwent calcium scoring. The study group consisted of 49 patients with pacemaker implantation who were compared to 100 matched control patients. The mean calcium score in the pacemaker group was 3.3 ± 2.9 versus 1.8 ± 2.0 (P = 0.006) in the control group. Univariate and multivariate analysis revealed glomerular filtration rate and calcium scoring to be significant predictors of the presence of a pacemaker. Echocardiographic-based calcium scoring correlates with the presence of severe conduction disease requiring a pacemaker. © 2012, Wiley Periodicals, Inc.

  2. Development of a Mobile Application for Building Energy Prediction Using Performance Prediction Model

    Directory of Open Access Journals (Sweden)

    Yu-Ri Kim

    2016-03-01

    Full Text Available Recently, the Korean government has enforced disclosure of building energy performance, so that such information can help owners and prospective buyers to make suitable investment plans. Such a building energy performance policy of the government makes it mandatory for the building owners to obtain engineering audits and thereby evaluate the energy performance levels of their buildings. However, to calculate energy performance levels (i.e., asset rating methodology, a qualified expert needs to have access to at least the full project documentation and/or conduct an on-site inspection of the buildings. Energy performance certification costs a lot of time and money. Moreover, the database of certified buildings is still actually quite small. A need, therefore, is increasing for a simplified and user-friendly energy performance prediction tool for non-specialists. Also, a database which allows building owners and users to compare best practices is required. In this regard, the current study developed a simplified performance prediction model through experimental design, energy simulations and ANOVA (analysis of variance. Furthermore, using the new prediction model, a related mobile application was also developed.

  3. When predictions take control: The effect of task predictions on task switching performance

    Directory of Open Access Journals (Sweden)

    Wout eDuthoo

    2012-08-01

    Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

  4. New pulmonary vein Doppler echocardiographic index predicts significant interatrial shunting in secundum atrial septal defect.

    Science.gov (United States)

    Lam, Yat-Yin; Fang, Fang; Yip, Gabriel Wai-Kwok; Li, Zhi-An; Yang, Ya; Yu, Cheuk-Man

    2012-09-20

    The relation between pulmonary venous flow (PVF) pattern and degree of left-to-right interatrial shunting (IAS) in patients with secundum atrial septal defect (ASD) is unknown. Fifty consecutive ASD patients (14 males, 36 ± 17 years) received transthoracic echocardiography (TTE) before and 1 day after transcatheter closure and their results were compared to 40 controls. The ratio of pulmonary-to-systemic flows (Qp/Qs) was assessed by TTE and invasive oximetry. Pre-closure PV systolic (PVs), diastolic (PVd) velocities and velocity-time integral (PV-VTI) increased, time from onset of ECG Q-wave to the peak PV diastolic wave (Q-PVd) shortened and atrial reversal (PVar) velocity significantly decreased as compared to normals. These findings normalized after closure. Patients with large IAS (defined as invasive Qp/Qs ≥ 2) had higher PVs, PVd and PV-VTI, shorter Q-PVd but lower PVar (all pIAS. Invasive Qp/Qs ratios correlated with PVs, PVd, PV-VTI, Q-PVd and TTE-derived Qp/Qs ratios, ASD sizes and RV end-diastolic dimensions (all pIAS after multivariate analysis. The corresponding sensitivity, specificity and AUC were 89%, 82% and 0.90 respectively for a PV-VTI of 30 cm (pIAS have distinguishable PVF features. Doppler evaluation of PV-VTI is a novel additional tool for assessing the magnitude of shunting in these patients non-invasively. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  5. Significantly enhanced robustness and electrochemical performance of flexible carbon nanotube-based supercapacitors by electrodepositing polypyrrole

    Science.gov (United States)

    Chen, Yanli; Du, Lianhuan; Yang, Peihua; Sun, Peng; Yu, Xiang; Mai, Wenjie

    2015-08-01

    Here, we report robust, flexible CNT-based supercapacitor (SC) electrodes fabricated by electrodepositing polypyrrole (PPy) on freestanding vacuum-filtered CNT film. These electrodes demonstrate significantly improved mechanical properties (with the ultimate tensile strength of 16 MPa), and greatly enhanced electrochemical performance (5.6 times larger areal capacitance). The major drawback of conductive polymer electrodes is the fast capacitance decay caused by structural breakdown, which decreases cycling stability but this is not observed in our case. All-solid-state SCs assembled with the robust CNT/PPy electrodes exhibit excellent flexibility, long lifetime (95% capacitance retention after 10,000 cycles) and high electrochemical performance (a total device volumetric capacitance of 4.9 F/cm3). Moreover, a flexible SC pack is demonstrated to light up 53 LEDs or drive a digital watch, indicating the broad potential application of our SCs for portable/wearable electronics.

  6. Genomic Prediction of Testcross Performance in Canola (Brassica napus)

    Science.gov (United States)

    Jan, Habib U.; Abbadi, Amine; Lücke, Sophie; Nichols, Richard A.; Snowdon, Rod J.

    2016-01-01

    Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable

  7. Field significance of performance measures in the context of regional climate model evaluation. Part 2: precipitation

    Science.gov (United States)

    Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2018-04-01

    A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as `field' or `global' significance. The block length for the local resampling tests is precisely determined to adequately account for the time series structure. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Daily precipitation climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. While the downscaled precipitation distributions are statistically indistinguishable from the observed ones in most regions in summer, the biases of some distribution characteristics are significant over large areas in winter. WRF-NOAH generates appropriate stationary fine-scale climate features in the daily precipitation field over regions of complex topography in both seasons and appropriate transient fine-scale features almost everywhere in summer. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the clear additional value of dynamical downscaling over global climate simulations. The evaluation methodology has a broad spectrum of applicability as it is

  8. Subjective Significance Shapes Arousal Effects on Modified Stroop Task Performance: A Duality of Activation Mechanisms Account.

    Science.gov (United States)

    Imbir, Kamil K

    2016-01-01

    Activation mechanisms such as arousal are known to be responsible for slowdown observed in the Emotional Stroop and modified Stroop tasks. Using the duality of mind perspective, we may conclude that both ways of processing information (automatic or controlled) should have their own mechanisms of activation, namely, arousal for an experiential mind, and subjective significance for a rational mind. To investigate the consequences of both, factorial manipulation was prepared. Other factors that influence Stroop task processing such as valence, concreteness, frequency, and word length were controlled. Subjective significance was expected to influence arousal effects. In the first study, the task was to name the color of font for activation charged words. In the second study, activation charged words were, at the same time, combined with an incongruent condition of the classical Stroop task around a fixation point. The task was to indicate the font color for color-meaning words. In both studies, subjective significance was found to shape the arousal impact on performance in terms of the slowdown reduction for words charged with subjective significance.

  9. Subjective Significance Shapes Arousal Effects on Modified Stroop Task Performance: a Duality of Activation Mechanisms Account

    Directory of Open Access Journals (Sweden)

    Kamil Konrad Imbir

    2016-02-01

    Full Text Available Activation mechanisms such as arousal are known to be responsible for slowdown observed in the Emotional Stroop (EST and modified Stroop tasks. Using the duality of mind perspective, we may conclude that both ways of processing information (automatic or controlled should have their own mechanisms of activation, namely, arousal for an experiential mind, and subjective significance for a rational mind. To investigate the consequences of both, factorial manipulation was prepared. Other factors that influence Stroop task processing such as valence, concreteness, frequency and word length were controlled. Subjective significance was expected to influence arousal effects. In the first study, the task was to name the color of font for activation charged words. In the second study, activation charged words were, at the same time, combined with an incongruent condition of the classical Stroop task around a fixation point. The task was to indicate the font color for color-meaning words. In both studies, subjective significance was found to shape the arousal impact on performance in terms of the slowdown reduction for words charged with subjective significance.

  10. Faculty Decisions on Serials Subscriptions Differ Significantly from Decisions Predicted by a Bibliometric Tool.

    Directory of Open Access Journals (Sweden)

    Sue F. Phelps

    2016-03-01

    of the faculty choices. The p-value for this relationship was less than 0.0001, also indicating that the result was not by chance. A quadratic model plotted alongside the previous linear model follows a similar pattern. The p-value of the comparison is 0.0002, which indicates the quadratic model’s fit cannot be explained by random chance. Main Results – The authors point out three outstanding findings. First, the match rate between faculty valuations and bibliometric scores for serials is 65%. This exceeds the 50% rate that would indicate random association, but also indicates a statistically significant difference between faculty and bibliometric valuations. Secondly, the match rate with the bibliometric scores for titles that faculty chose to keep (73% was higher than those they chose to cancel (54%. Thirdly, the match rate increased with higher bibliometric scores. Conclusions – Though the authors identify only a modest degree of similarity between faculty and bibliometric valuations of serials, it is noted that there is more agreement in the higher valued serials than the lower valued serials. With that in mind, librarians might focus faculty review on the lower scoring titles in the future, taking into consideration that unique faculty interests may drive selection at that level and would need to be balanced with the mission of the library.

  11. Modeling and prediction of flotation performance using support vector regression

    Directory of Open Access Journals (Sweden)

    Despotović Vladimir

    2017-01-01

    Full Text Available Continuous efforts have been made in recent year to improve the process of paper recycling, as it is of critical importance for saving the wood, water and energy resources. Flotation deinking is considered to be one of the key methods for separation of ink particles from the cellulose fibres. Attempts to model the flotation deinking process have often resulted in complex models that are difficult to implement and use. In this paper a model for prediction of flotation performance based on Support Vector Regression (SVR, is presented. Representative data samples were created in laboratory, under a variety of practical control variables for the flotation deinking process, including different reagents, pH values and flotation residence time. Predictive model was created that was trained on these data samples, and the flotation performance was assessed showing that Support Vector Regression is a promising method even when dataset used for training the model is limited.

  12. Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files.

    Science.gov (United States)

    Sun, Xiaobo; Gao, Jingjing; Jin, Peng; Eng, Celeste; Burchard, Esteban G; Beaty, Terri H; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen; Wang, Fusheng; Qin, Zhaohui S

    2018-06-01

    Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)-based high-performance computing (HPC) implementation, and the popular VCFTools. Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems.

  13. Focused R&D For Electrochromic Smart Windowsa: Significant Performance and Yield Enhancements

    Energy Technology Data Exchange (ETDEWEB)

    Mark Burdis; Neil Sbar

    2003-01-31

    There is a need to improve the energy efficiency of building envelopes as they are the primary factor governing the heating, cooling, lighting and ventilation requirements of buildings--influencing 53% of building energy use. In particular, windows contribute significantly to the overall energy performance of building envelopes, thus there is a need to develop advanced energy efficient window and glazing systems. Electrochromic (EC) windows represent the next generation of advanced glazing technology that will (1) reduce the energy consumed in buildings, (2) improve the overall comfort of the building occupants, and (3) improve the thermal performance of the building envelope. ''Switchable'' EC windows provide, on demand, dynamic control of visible light, solar heat gain, and glare without blocking the view. As exterior light levels change, the window's performance can be electronically adjusted to suit conditions. A schematic illustrating how SageGlass{reg_sign} electrochromic windows work is shown in Figure I.1. SageGlass{reg_sign} EC glazings offer the potential to save cooling and lighting costs, with the added benefit of improving thermal and visual comfort. Control over solar heat gain will also result in the use of smaller HVAC equipment. If a step change in the energy efficiency and performance of buildings is to be achieved, there is a clear need to bring EC technology to the marketplace. This project addresses accelerating the widespread introduction of EC windows in buildings and thus maximizing total energy savings in the U.S. and worldwide. We report on R&D activities to improve the optical performance needed to broadly penetrate the full range of architectural markets. Also, processing enhancements have been implemented to reduce manufacturing costs. Finally, tests are being conducted to demonstrate the durability of the EC device and the dual pane insulating glass unit (IGU) to be at least equal to that of conventional

  14. Locomotion With Loads: Practical Techniques for Predicting Performance Outcomes

    Science.gov (United States)

    2015-05-01

    Metabolic energy consumption as a function of speed and body size in birds and mammals. J Exp Biol. 97, 1-21. Weyand, P., Smith, B., Puyau, M. and...height, weight (including load), speed, and grade algorithms proposed will allow walking metabolic rates to be predicted to within 6.0 and 12.0% in...gait, metabolism , performance, load carriage 16. SECURITY CLASSIFICATION OF: Unclassified 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME

  15. Decline Curve Based Models for Predicting Natural Gas Well Performance

    OpenAIRE

    Kamari, Arash; Mohammadi, Amir H.; Lee, Moonyong; Mahmood, Tariq; Bahadori, Alireza

    2016-01-01

    The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN) modelling strategy, least square support vector machine (LSSVM) approach, adaptive neuro-fuzzy ...

  16. Sexual victimization history predicts academic performance in college women.

    Science.gov (United States)

    Baker, Majel R; Frazier, Patricia A; Greer, Christiaan; Paulsen, Jacob A; Howard, Kelli; Meredith, Liza N; Anders, Samantha L; Shallcross, Sandra L

    2016-11-01

    College women frequently report having experienced sexual victimization (SV) in their lifetime, including child sexual abuse and adolescent/adult sexual assault. Although the harmful mental health sequelae of SV have been extensively studied, recent research suggests that SV is also a risk factor for poorer college academic performance. The current studies examined whether exposure to SV uniquely predicted poorer college academic performance, even beyond contributions from three well-established predictors of academic performance: high school rank, composite standardized test scores (i.e., American College Testing [ACT]), and conscientiousness. Study 1 analyzed longitudinal data from a sample of female college students (N = 192) who were assessed at the beginning and end of one semester. SV predicted poorer cumulative end-of-semester grade point average (GPA) while controlling for well-established predictors of academic performance. Study 2 replicated these findings in a second longitudinal study of female college students (N = 390) and extended the analyses to include follow-up data on the freshmen and sophomore students (n = 206) 4 years later. SV predicted students' GPA in their final term at the university above the contributions of well-established academic predictors, and it was the only factor related to leaving college. These findings highlight the importance of expanding the scope of outcomes of SV to include academic performance, and they underscore the need to assess SV and other adverse experiences on college campuses to target students who may be at risk of poor performance or leaving college. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  17. A Meta-analysis for the Diagnostic Performance of Transient Elastography for Clinically Significant Portal Hypertension.

    Science.gov (United States)

    You, Myung-Won; Kim, Kyung Won; Pyo, Junhee; Huh, Jimi; Kim, Hyoung Jung; Lee, So Jung; Park, Seong Ho

    2017-01-01

    We aimed to evaluate the correlation between liver stiffness measurement using transient elastography (TE-LSM) and hepatic venous pressure gradient and the diagnostic performance of TE-LSM in assessing clinically significant portal hypertension through meta-analysis. Eleven studies were included from thorough literature research and selection processes. The summary correlation coefficient was 0.783 (95% confidence interval [CI], 0.737-0.823). Summary sensitivity, specificity and area under the hierarchical summary receiver operating characteristic curve (AUC) were 87.5% (95% CI, 75.8-93.9%), 85.3 % (95% CI, 76.9-90.9%) and 0.9, respectively. The subgroup with low cut-off values of 13.6-18 kPa had better summary estimates (sensitivity 91.2%, specificity 81.3% and partial AUC 0.921) than the subgroup with high cut-off values of 21-25 kPa (sensitivity 71.2%, specificity 90.9% and partial AUC 0.769). In summary, TE-LSM correlated well with hepatic venous pressure gradient and represented good diagnostic performance in diagnosing clinically significant portal hypertension. For use as a sensitive screening tool, we propose using low cut-off values of 13.6-18 kPa in TE-LSM. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

  18. Behavioral Change and Building Performance: Strategies for Significant, Persistent, and Measurable Institutional Change

    Energy Technology Data Exchange (ETDEWEB)

    Wolfe, Amy K.; Malone, Elizabeth L.; Heerwagen, Judith H.; Dion, Jerome P.

    2014-04-01

    The people who use Federal buildings — Federal employees, operations and maintenance staff, and the general public — can significantly impact a building’s environmental performance and the consumption of energy, water, and materials. Many factors influence building occupants’ use of resources (use behaviors) including work process requirements, ability to fulfill agency missions, new and possibly unfamiliar high-efficiency/high-performance building technologies; a lack of understanding, education, and training; inaccessible information or ineffective feedback mechanisms; and cultural norms and institutional rules and requirements, among others. While many strategies have been used to introduce new occupant use behaviors that promote sustainability and reduced resource consumption, few have been verified in the scientific literature or have properly documented case study results. This paper documents validated strategies that have been shown to encourage new use behaviors that can result in significant, persistent, and measureable reductions in resource consumption. From the peer-reviewed literature, the paper identifies relevant strategies for Federal facilities and commercial buildings that focus on the individual, groups of individuals (e.g., work groups), and institutions — their policies, requirements, and culture. The paper documents methods with evidence of success in changing use behaviors and enabling occupants to effectively interact with new technologies/designs. It also provides a case study of the strategies used at a Federal facility — Fort Carson, Colorado. The paper documents gaps in the current literature and approaches, and provides topics for future research.

  19. A critical review of predictive models for the onset of significant void in forced-convection subcooled boiling

    International Nuclear Information System (INIS)

    Dorra, H.; Lee, S.C.; Bankoff, S.G.

    1993-06-01

    This predictive models for the onset of significant void (OSV) in forced-convection subcooled boiling are reviewed and compared with extensive data. Three analytical models and seven empirical correlations are considered in this review. These models and correlations are put onto a common basis and are compared, again on a common basis, with a variety of data. The evaluation of their range of validity and applicability under various operating conditions are discussed. The results show that the correlations of Saha-Zuber seems to be the best model to predict OSV in vertical subcooled boiling flow

  20. Performance characteristics of SCC radioimmunoassay and clinical significance serum SCC Ag assay in patients with malignancy

    International Nuclear Information System (INIS)

    Kim, Dong Youn

    1986-01-01

    To evaluate the performance characteristics of SCC RIV and the clinical significance of serum SCC Ag assay in patients with malignancy, serum SCC Ag levels were measured by SCC RIV kit in 40 normal controls and 35 percents with various untreated malignancy, who visited Chonju Presbyterian Medical Center. The results were as follows; 1. The SCC RIA was simple to perform and can be completed in two workday. And the standard curve and reproducibility were both good. 2. The mean serum SCC Ag level in normal controls was 1.64 ± 0.93 ng/mL and normal upper limit of serum SCC Ag was defined as 2.6 ng/mL. 3 out of 40 (7.5%) normal controls showed elevated SCC Ag levels above the normal upper limit. 3. In 35 patients with various untreated malignancy, 18 patients (51.4%) showed elevated serum SCC Ag levels, 59.1% of 22 patients with cervical cancer, 80% of 5 patients with lung cancer, 33% of 3 patients with esophageal cancer, 0% of 2 patients with rectal cancer and 0% of 3 patients with breast cancer showed elevated serum SCC Ag levels. Above results represent that SCC RIV is simple method to perform followed by good standard curve and reproducibility, and may be a useful indicator reflecting diagnostic data of patients with cervical cancer and lung cancer

  1. Predicting work Performance through selection interview ratings and Psychological assessment

    Directory of Open Access Journals (Sweden)

    Liziwe Nzama

    2008-11-01

    Full Text Available The aim of the study was to establish whether selection interviews used in conjunction with psychological assessments of personality traits and cognitive functioning contribute to predicting work performance. The sample consisted of 102 managers who were appointed recently in a retail organisation. The independent variables were selection interview ratings obtained on the basis of structured competency-based interview schedules by interviewing panels, fve broad dimensions of personality defned by the Five Factor Model as measured by the 15 Factor Questionnaire (15FQ+, and cognitive processing variables (current level of work, potential level of work, and 12 processing competencies measured by the Cognitive Process Profle (CPP. Work performance was measured through annual performance ratings that focused on measurable outputs of performance objectives. Only two predictor variables correlated statistically signifcantly with the criterion variable, namely interview ratings (r = 0.31 and CPP Verbal Abstraction (r = 0.34. Following multiple regression, only these variables contributed signifcantly to predicting work performance, but only 17.8% of the variance of the criterion was accounted for.

  2. Comparative values of medical school assessments in the prediction of internship performance.

    Science.gov (United States)

    Lee, Ming; Vermillion, Michelle

    2018-02-01

    Multiple undergraduate achievements have been used for graduate admission consideration. Their relative values in the prediction of residency performance are not clear. This study compared the contributions of major undergraduate assessments to the prediction of internship performance. Internship performance ratings of the graduates of a medical school were collected from 2012 to 2015. Hierarchical multiple regression analyses were used to examine the predictive values of undergraduate measures assessing basic and clinical sciences knowledge and clinical performances, after controlling for differences in the Medical College Admission Test (MCAT). Four hundred eighty (75%) graduates' archived data were used in the study. Analyses revealed that clinical competencies, assessed by the USMLE Step 2 CK, NBME medicine exam, and an eight-station objective structured clinical examination (OSCE), were strong predictors of internship performance. Neither the USMLE Step 1 nor the inpatient internal medicine clerkship evaluation predicted internship performance. The undergraduate assessments as a whole showed a significant collective relationship with internship performance (ΔR 2  = 0.12, p < 0.001). The study supports the use of clinical competency assessments, instead of pre-clinical measures, in graduate admission consideration. It also provides validity evidence for OSCE scores in the prediction of workplace performance.

  3. Predicting BCI subject performance using probabilistic spatio-temporal filters.

    Directory of Open Access Journals (Sweden)

    Heung-Il Suk

    Full Text Available 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.

  4. Predicting space telerobotic operator training performance from human spatial ability assessment

    Science.gov (United States)

    Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

    2013-11-01

    Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

  5. Field significance of performance measures in the context of regional climate model evaluation. Part 1: temperature

    Science.gov (United States)

    Ivanov, Martin; Warrach-Sagi, Kirsten; Wulfmeyer, Volker

    2018-04-01

    A new approach for rigorous spatial analysis of the downscaling performance of regional climate model (RCM) simulations is introduced. It is based on a multiple comparison of the local tests at the grid cells and is also known as "field" or "global" significance. New performance measures for estimating the added value of downscaled data relative to the large-scale forcing fields are developed. The methodology is exemplarily applied to a standard EURO-CORDEX hindcast simulation with the Weather Research and Forecasting (WRF) model coupled with the land surface model NOAH at 0.11 ∘ grid resolution. Monthly temperature climatology for the 1990-2009 period is analysed for Germany for winter and summer in comparison with high-resolution gridded observations from the German Weather Service. The field significance test controls the proportion of falsely rejected local tests in a meaningful way and is robust to spatial dependence. Hence, the spatial patterns of the statistically significant local tests are also meaningful. We interpret them from a process-oriented perspective. In winter and in most regions in summer, the downscaled distributions are statistically indistinguishable from the observed ones. A systematic cold summer bias occurs in deep river valleys due to overestimated elevations, in coastal areas due probably to enhanced sea breeze circulation, and over large lakes due to the interpolation of water temperatures. Urban areas in concave topography forms have a warm summer bias due to the strong heat islands, not reflected in the observations. WRF-NOAH generates appropriate fine-scale features in the monthly temperature field over regions of complex topography, but over spatially homogeneous areas even small biases can lead to significant deteriorations relative to the driving reanalysis. As the added value of global climate model (GCM)-driven simulations cannot be smaller than this perfect-boundary estimate, this work demonstrates in a rigorous manner the

  6. Significant enhancement in thermoelectric performance of nanostructured higher manganese silicides synthesized employing a melt spinning technique.

    Science.gov (United States)

    Muthiah, Saravanan; Singh, R C; Pathak, B D; Avasthi, Piyush Kumar; Kumar, Rishikesh; Kumar, Anil; Srivastava, A K; Dhar, Ajay

    2018-01-25

    The limited thermoelectric performance of p-type Higher Manganese Silicides (HMS) in terms of their low figure-of-merit (ZT), which is far below unity, is the main bottle-neck for realising an efficient HMS based thermoelectric generator, which has been recognized as the most promising material for harnessing waste-heat in the mid-temperature range, owing to its thermal stability, earth-abundant and environmentally friendly nature of its constituent elements. We report a significant enhancement in the thermoelectric performance of nanostructured HMS synthesized using rapid solidification by optimizing the cooling rates during melt-spinning followed by spark plasma sintering of the resulting melt-spun ribbons. By employing this experimental strategy, an unprecedented ZT ∼ 0.82 at 800 K was realized in spark plasma sintered 5 at% Al-doped MnSi 1.73 HMS, melt spun at an optimized high cooling rate of ∼2 × 10 7 K s -1 . This enhancement in ZT represents a ∼25% increase over the best reported values thus far for HMS and primarily originates from a nano-crystalline microstructure consisting of a HMS matrix (20-40 nm) with excess Si (3-9 nm) uniformly distributed in it. This nanostructure, resulting from the high cooling rates employed during the melt-spinning of HMS, introduces a high density of nano-crystallite boundaries in a wide spectrum of nano-scale dimensions, which scatter the low-to-mid-wavelength heat-carrying phonons. This abundant phonon scattering results in a significantly reduced thermal conductivity of ∼1.5 W m -1 K -1 at 800 K, which primarily contributes to the enhancement in ZT.

  7. Decline curve based models for predicting natural gas well performance

    Directory of Open Access Journals (Sweden)

    Arash Kamari

    2017-06-01

    Full Text Available The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN modelling strategy, least square support vector machine (LSSVM approach, adaptive neuro-fuzzy inference system (ANFIS, and decision tree (DT method for the prediction of cumulative gas production as well as initial decline rate multiplied by time as a function of the Arps' decline curve exponent and ratio of initial gas flow rate over total gas flow rate. It was concluded that the results obtained based on the models developed in current study are in satisfactory agreement with the actual gas well production data. Furthermore, the results of comparative study performed demonstrates that the LSSVM strategy is superior to the other models investigated for the prediction of both cumulative gas production, and initial decline rate multiplied by time.

  8. Performance and wake predictions of HAWTs in wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Leclerc, C.; Masson, C.; Paraschivoiu, I. [Ecole Polytechnique, Montreal (Canada)

    1997-12-31

    The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.

  9. Examining significant factors in micro and small enterprises performance: case study in Amhara region, Ethiopia

    Science.gov (United States)

    Cherkos, Tomas; Zegeye, Muluken; Tilahun, Shimelis; Avvari, Muralidhar

    2017-07-01

    Furniture manufacturing micro and small enterprises are confronted with several factors that affect their performance. Some enterprises fail to sustain, some others remain for long period of time without transforming, and most are producing similar and non-standard products. The main aim of this manuscript is on improving the performance and contribution of MSEs by analyzing impact of significant internal and external factors. Data was collected via a questionnaire, group discussion with experts and interviewing process. Randomly selected eight representative main cities of Amhara region with 120 furniture manufacturing enterprises are considered. Data analysis and presentation was made using SPSS tools (correlation, proximity, and T test) and impact-effort analysis matrix tool. The correlation analysis shows that politico-legal with infrastructure, leadership with entrepreneurship skills and finance and credit with marketing factors are those factors, which result in high correlation with Pearson correlation values of r = 0.988, 0.983, and 0.939, respectively. The study investigates that the most critical factors faced by MSEs are work premises, access to finance, infrastructure, entrepreneurship and business managerial problems. The impact of these factors is found to be high and is confirmed by the 50% drop-out rate in 2014/2015. Furthermore, more than 25% work time losses due to power interruption daily and around 65% work premises problems challenged MSEs. Further, an impact-effort matrix was developed to help the MSEs to prioritize the affecting factors.

  10. Predictive models for PEM-electrolyzer performance using adaptive neuro-fuzzy inference systems

    Energy Technology Data Exchange (ETDEWEB)

    Becker, Steffen [University of Tasmania, Hobart 7001, Tasmania (Australia); Karri, Vishy [Australian College of Kuwait (Kuwait)

    2010-09-15

    Predictive models were built using neural network based Adaptive Neuro-Fuzzy Inference Systems for hydrogen flow rate, electrolyzer system-efficiency and stack-efficiency respectively. A comprehensive experimental database forms the foundation for the predictive models. It is argued that, due to the high costs associated with the hydrogen measuring equipment; these reliable predictive models can be implemented as virtual sensors. These models can also be used on-line for monitoring and safety of hydrogen equipment. The quantitative accuracy of the predictive models is appraised using statistical techniques. These mathematical models are found to be reliable predictive tools with an excellent accuracy of {+-}3% compared with experimental values. The predictive nature of these models did not show any significant bias to either over prediction or under prediction. These predictive models, built on a sound mathematical and quantitative basis, can be seen as a step towards establishing hydrogen performance prediction models as generic virtual sensors for wider safety and monitoring applications. (author)

  11. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

    Directory of Open Access Journals (Sweden)

    Amber Watts PhD

    2015-08-01

    Full Text Available Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD, we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status adjusting for age, sex, education, and self-reported walking. Results : Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion : Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function.

  12. Performance of immunological response in predicting virological failure.

    Science.gov (United States)

    Ingole, Nayana; Mehta, Preeti; Pazare, Amar; Paranjpe, Supriya; Sarkate, Purva

    2013-03-01

    In HIV-infected individuals on antiretroviral therapy (ART), the decision on when to switch from first-line to second-line therapy is dictated by treatment failure, and this can be measured in three ways: clinically, immunologically, and virologically. While viral load (VL) decreases and CD4 cell increases typically occur together after starting ART, discordant responses may be seen. Hence the current study was designed to determine the immunological and virological response to ART and to evaluate the utility of immunological response to predict virological failure. All treatment-naive HIV-positive individuals aged >18 years who were eligible for ART were enrolled and assessed at baseline, 6 months, and 12 months clinically and by CD4 cell count and viral load estimations. The patients were categorized as showing concordant favorable (CF), immunological only (IO), virological only (VO), and concordant unfavorable responses (CU). The efficiency of immunological failure to predict virological failure was analyzed across various levels of virological failure (VL>50, >500, and >5,000 copies/ml). At 6 months, 87(79.81%), 7(5.5%), 13 (11.92%), and 2 (1.83%) patients and at 12 months 61(69.3%), 9(10.2%), 16 (18.2%), and 2 (2.3%) patients had CF, IO, VO, and CU responses, respectively. Immunological failure criteria had a very low sensitivity (11.1-40%) and positive predictive value (8.3-25%) to predict virological failure. Immunological criteria do not accurately predict virological failure resulting in significant misclassification of therapeutic responses. There is an urgent need for inclusion of viral load testing in the initiation and monitoring of ART.

  13. Prediction of performance and evaluation of flexible pavement rehabilitation strategies

    Directory of Open Access Journals (Sweden)

    Kang-Won Wayne Lee

    2017-04-01

    Full Text Available Five test sections with different additives and strategies were established to rehabilitate a State-maintained highway more effectively in Rhode Island (RI: control, calcium chloride, asphalt emulsion, Portland cement and geogrid. Resilient moduli of subgrade soils and subbase materials before and after full depth rehabilitation were employed as input parameters to predict the performance of pavement structures using AASHTOWare Pavement ME Design (Pavement ME software in terms of rutting, cracking and roughness. It was attempted to use Level 1 input (which includes traffic full spectrum data, climate data and structural layer properties for Pavement ME. Traffic data was obtained from a Weigh-in-Motion (WIM instrument and Providence station was used for collecting climatic data. Volumetric properties, dynamic modulus and creep compliance were used as input parameters for 19 mm (0.75 in. warm mix asphalt (WMA base and 12.5 mm (0.5 in. WMA surface layer. The results indicated that all test sections observed AC top-down (longitudinal cracking except Portland cement section which passed for all criteria. The order in terms of performance (best to worst for all test sections by Pavement ME was Portland cement, calcium chloride, control, geogrid, and asphalt emulsion. It was also observed that all test sections passed for both bottom up and top down fatigue cracking by increasing thickness of either of the two top asphalt layers. Test sections with five different base/subbase materials were evaluated in last two years through visual condition survey and measurements of deflection and roughness to confirm the prediction, but there was no serious distress and roughness. Thus these experiments allowed selecting the best rehabilitation/reconstruction techniques for the particular and/or similar highway, and a framework was formulated to select an optimal technique and/or strategy for future rehabilitation/reconstruction projects. Finally, guidelines for

  14. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

  15. Bayesian calibration of power plant models for accurate performance prediction

    International Nuclear Information System (INIS)

    Boksteen, Sowande Z.; Buijtenen, Jos P. van; Pecnik, Rene; Vecht, Dick van der

    2014-01-01

    Highlights: • Bayesian calibration is applied to power plant performance prediction. • Measurements from a plant in operation are used for model calibration. • A gas turbine performance model and steam cycle model are calibrated. • An integrated plant model is derived. • Part load efficiency is accurately predicted as a function of ambient conditions. - Abstract: Gas turbine combined cycles are expected to play an increasingly important role in the balancing of supply and demand in future energy markets. Thermodynamic modeling of these energy systems is frequently applied to assist in decision making processes related to the management of plant operation and maintenance. In most cases, model inputs, parameters and outputs are treated as deterministic quantities and plant operators make decisions with limited or no regard of uncertainties. As the steady integration of wind and solar energy into the energy market induces extra uncertainties, part load operation and reliability are becoming increasingly important. In the current study, methods are proposed to not only quantify various types of uncertainties in measurements and plant model parameters using measured data, but to also assess their effect on various aspects of performance prediction. The authors aim to account for model parameter and measurement uncertainty, and for systematic discrepancy of models with respect to reality. For this purpose, the Bayesian calibration framework of Kennedy and O’Hagan is used, which is especially suitable for high-dimensional industrial problems. The article derives a calibrated model of the plant efficiency as a function of ambient conditions and operational parameters, which is also accurate in part load. The article shows that complete statistical modeling of power plants not only enhances process models, but can also increases confidence in operational decisions

  16. Variability, Predictability, and Race Factors Affecting Performance in Elite Biathlon.

    Science.gov (United States)

    Skattebo, Øyvind; Losnegard, Thomas

    2018-03-01

    To investigate variability, predictability, and smallest worthwhile performance enhancement in elite biathlon sprint events. In addition, the effects of race factors on performance were assessed. Data from 2005 to 2015 including >10,000 and >1000 observations for each sex for all athletes and annual top-10 athletes, respectively, were included. Generalized linear mixed models were constructed based on total race time, skiing time, shooting time, and proportions of targets hit. Within-athlete race-to-race variability was expressed as coefficient of variation of performance times and standard deviation (SD) in proportion units (%) of targets hit. The models were adjusted for random and fixed effects of subject identity, season, event identity, and race factors. The within-athlete variability was independent of sex and performance standard of athletes: 2.5-3.2% for total race time, 1.5-1.8% for skiing time, and 11-15% for shooting times. The SD of the proportion of hits was ∼10% in both shootings combined (meaning ±1 hit in 10 shots). The predictability in total race time was very high to extremely high for all athletes (ICC .78-.84) but trivial for top-10 athletes (ICC .05). Race times during World Championships and Olympics were ∼2-3% faster than in World Cups. Moreover, race time increased by ∼2% per 1000 m of altitude, by ∼5% per 1% of gradient, by 1-2% per 1 m/s of wind speed, and by ∼2-4% on soft vs hard tracks. Researchers and practitioners should focus on strategies that improve biathletes' performance by at least 0.8-0.9%, corresponding to the smallest worthwhile enhancement (0.3 × within-athlete variability).

  17. Predictive neuromechanical simulations indicate why walking performance declines with ageing.

    Science.gov (United States)

    Song, Seungmoon; Geyer, Hartmut

    2018-04-01

    Although the natural decline in walking performance with ageing affects the quality of life of a growing elderly population, its physiological origins remain unknown. By using predictive neuromechanical simulations of human walking with age-related neuro-musculo-skeletal changes, we find evidence that the loss of muscle strength and muscle contraction speed dominantly contribute to the reduced walking economy and speed. The findings imply that focusing on recovering these muscular changes may be the only effective way to improve performance in elderly walking. More generally, the work is of interest for investigating the physiological causes of altered gait due to age, injury and disorders. Healthy elderly people walk slower and energetically less efficiently than young adults. This decline in walking performance lowers the quality of life for a growing ageing population, and understanding its physiological origin is critical for devising interventions that can delay or revert it. However, the origin of the decline in walking performance remains unknown, as ageing produces a range of physiological changes whose individual effects on gait are difficult to separate in experiments with human subjects. Here we use a predictive neuromechanical model to separately address the effects of common age-related changes to the skeletal, muscular and nervous systems. We find in computer simulations of this model that the combined changes produce gait consistent with elderly walking and that mainly the loss of muscle strength and mass reduces energy efficiency. In addition, we find that the slower preferred walking speed of elderly people emerges in the simulations when adapting to muscle fatigue, again mainly caused by muscle-related changes. The results suggest that a focus on recovering these muscular changes may be the only effective way to improve performance in elderly walking. © 2018 The Authors. The Journal of Physiology © 2018 The Physiological Society.

  18. Performance Prediction and Validation: Data, Frameworks, and Considerations

    Energy Technology Data Exchange (ETDEWEB)

    Tinnesand, Heidi

    2017-05-19

    Improving the predictability and reliability of wind power generation and operations will reduce costs and potentially establish a framework to attract new capital into the distributed wind sector, a key cost reduction requirement highlighted in results from the distributed wind future market assessment conducted with dWind. Quantifying and refining the accuracy of project performance estimates will also directly address several of the key challenges identified by industry stakeholders in 2015 as part of the distributed wind resource assessment workshop and be cross-cutting for several other facets of the distributed wind portfolio. This presentation covers the efforts undertaken in 2016 to address these topics.

  19. Numerical analysis of the performance prediction for a thermoelectric generator

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang Nyung [Kyung Hee University, Yongin (Korea, Republic of)

    2015-09-15

    The present study develops a two-dimensional numerical code that can predict the performance of a thermoelectric generator module including a p-leg/n-leg pair and top and bottom electrodes. The present code can simulate the detailed thermoelectric phenomena including the heat flow, electric current, Joule heating, Peltier heating, and Thomson heating, together with the efficiency of the modules whose properties depend on the temperature. The present numerical code can be used for the design optimization of a thermoelectric power generator.

  20. Predicting Students’ Performance using Modified ID3 Algorithm

    OpenAIRE

    Ramanathan L; Saksham Dhanda; Suresh Kumar D

    2013-01-01

    The ability to predict performance of students is very crucial in our present education system. We can use data mining concepts for this purpose. ID3 algorithm is one of the famous algorithms present today to generate decision trees. But this algorithm has a shortcoming that it is inclined to attributes with many values. So , this research aims to overcome this shortcoming of the algorithm by using gain ratio(instead of information gain) as well as by giving weights to each attribute at every...

  1. Performance prediction of a multi-basin solar still

    International Nuclear Information System (INIS)

    Mahdi, N.Al.

    1992-01-01

    A transient analysis for the prediction of the performance of a multi-basin solar still is presented. The energy-balance equations for the glass covers, the water masses and the absorber plate are manipulated to obtain a set of ordinary differential equations which are solved numerically. The analysis is applied to investigate the effect of the number of basins on the daily productivity of the still. Meteorological data corresponding to a June day in Bahrain have been used for the computation. The results indicate that the daily distillate output is increased by increasing the number of basins in the still. (author)

  2. Validity of the Optometry Admission Test in Predicting Performance in Schools and Colleges of Optometry.

    Science.gov (United States)

    Kramer, Gene A.; Johnston, JoElle

    1997-01-01

    A study examined the relationship between Optometry Admission Test scores and pre-optometry or undergraduate grade point average (GPA) with first and second year performance in optometry schools. The test's predictive validity was limited but significant, and comparable to those reported for other admission tests. In addition, the scores…

  3. Mean platelet volume (MPV) predicts middle distance running performance.

    Science.gov (United States)

    Lippi, Giuseppe; Salvagno, Gian Luca; Danese, Elisa; Skafidas, Spyros; Tarperi, Cantor; Guidi, Gian Cesare; Schena, Federico

    2014-01-01

    Running economy and performance in middle distance running depend on several physiological factors, which include anthropometric variables, functional characteristics, training volume and intensity. Since little information is available about hematological predictors of middle distance running time, we investigated whether some hematological parameters may be associated with middle distance running performance in a large sample of recreational runners. The study population consisted in 43 amateur runners (15 females, 28 males; median age 47 years), who successfully concluded a 21.1 km half-marathon at 75-85% of their maximal aerobic power (VO2max). Whole blood was collected 10 min before the run started and immediately thereafter, and hematological testing was completed within 2 hours after sample collection. The values of lymphocytes and eosinophils exhibited a significant decrease compared to pre-run values, whereas those of mean corpuscular volume (MCV), platelets, mean platelet volume (MPV), white blood cells (WBCs), neutrophils and monocytes were significantly increased after the run. In univariate analysis, significant associations with running time were found for pre-run values of hematocrit, hemoglobin, mean corpuscular hemoglobin (MCH), red blood cell distribution width (RDW), MPV, reticulocyte hemoglobin concentration (RetCHR), and post-run values of MCH, RDW, MPV, monocytes and RetCHR. In multivariate analysis, in which running time was entered as dependent variable whereas age, sex, blood lactate, body mass index, VO2max, mean training regimen and the hematological parameters significantly associated with running performance in univariate analysis were entered as independent variables, only MPV values before and after the trial remained significantly associated with running time. After adjustment for platelet count, the MPV value before the run (p = 0.042), but not thereafter (p = 0.247), remained significantly associated with running

  4. Mean platelet volume (MPV predicts middle distance running performance.

    Directory of Open Access Journals (Sweden)

    Giuseppe Lippi

    Full Text Available Running economy and performance in middle distance running depend on several physiological factors, which include anthropometric variables, functional characteristics, training volume and intensity. Since little information is available about hematological predictors of middle distance running time, we investigated whether some hematological parameters may be associated with middle distance running performance in a large sample of recreational runners.The study population consisted in 43 amateur runners (15 females, 28 males; median age 47 years, who successfully concluded a 21.1 km half-marathon at 75-85% of their maximal aerobic power (VO2max. Whole blood was collected 10 min before the run started and immediately thereafter, and hematological testing was completed within 2 hours after sample collection.The values of lymphocytes and eosinophils exhibited a significant decrease compared to pre-run values, whereas those of mean corpuscular volume (MCV, platelets, mean platelet volume (MPV, white blood cells (WBCs, neutrophils and monocytes were significantly increased after the run. In univariate analysis, significant associations with running time were found for pre-run values of hematocrit, hemoglobin, mean corpuscular hemoglobin (MCH, red blood cell distribution width (RDW, MPV, reticulocyte hemoglobin concentration (RetCHR, and post-run values of MCH, RDW, MPV, monocytes and RetCHR. In multivariate analysis, in which running time was entered as dependent variable whereas age, sex, blood lactate, body mass index, VO2max, mean training regimen and the hematological parameters significantly associated with running performance in univariate analysis were entered as independent variables, only MPV values before and after the trial remained significantly associated with running time. After adjustment for platelet count, the MPV value before the run (p = 0.042, but not thereafter (p = 0.247, remained significantly associated with running

  5. Working memory in children predicts performance on a gambling task.

    Science.gov (United States)

    Audusseau, Jean; Juhel, Jacques

    2015-01-01

    The authors investigated whether working memory (WM) plays a significant role in the development of decision making in children, operationalized by the Children's Gambling Task (CGT). A total of 105 children aged 6-7, 8-9, and 10-11 years old carried out the CGT. Children aged 6-7 years old were found to have a lower performance than older children, which shows that the CGT is sensitive to participant's age. The hypothesis that WM plays a significant role in decision making was then tested following two approaches: (a) an experimental approach, comparing between groups the performance on the CGT in a control condition (the CGT only was administered) to that in a double task condition (participants had to carry out a recall task in addition to the CGT); (b) an interindividual approach, probing the relationship between CGT performance and performance on tasks measuring WM efficiency. The between-groups approach evidenced a better performance in the control group. Moreover, the interindividual approach showed that the higher the participants' WM efficiency was, the higher their performance in the CGT was. Taken together, these two approaches yield converging results that support the hypothesis that WM plays a significant role in decision making in children.

  6. Evacuation of performance and significant chemical constituents and by products in drinking water treatment

    International Nuclear Information System (INIS)

    Jamrah, I. A.

    1999-01-01

    Drinking water treatment is a task that comprises of several processes that eventually lead to the addition of chemicals to achieve the objectives of treatment. This study was conducted to assess treatment performance, explain the presence of significant chemical species in water, and investigate the interactions and chemical by-products that are formed during the course of treatment. Grab water samples were collected on a regular basis from the influent and effluent of Zai water treatment plant. Chemical analysis were conducted to determine the concentrations of various chemical species of interest. Turbidity, temperature, and pH of the samples were also measured. The study concluded that Zai Water Treatment Plant produces potable drinking water in accordance with Jordanian Standards. The use of treatment chemical resulted in an increase in the concentrations of certain materials, such as manganese, aluminum, and sulfate. The turbidity of the raw water and the TOC of the samples were positively correlated, and the treatment results in approximately 20% TOC reduction, which demonstrates that the measures used for the control of TOC (carbon adsorption and permanganate pre-oxidation), are not very effective. The study also showed that the TOC content of our raw water samples and the concentration of tribalomethanes resulting after disinfection were positively correlated, and that bromoform was the dominant component. Also chloroform was the minor component of tribalomethanes formed during treatment. Positive correlation between the total concentration of tribalomethanes in water and the chlorine dose used for disinfection was also observed, and the total concentration of tribalomethanes increased with temperature. The formation of tribalomethanes was enhanced as the pH of water increased and as the concentration of bromide ion in raw water became significant. (author). 25 refs., 14 figs.1 table

  7. Cold-Blooded Attention: Finger Temperature Predicts Attentional Performance.

    Science.gov (United States)

    Vergara, Rodrigo C; Moënne-Loccoz, Cristóbal; Maldonado, Pedro E

    2017-01-01

    Thermal stress has been shown to increase the chances of unsafe behavior during industrial and driving performances due to reductions in mental and attentional resources. Nonetheless, establishing appropriate safety standards regarding environmental temperature has been a major problem, as modulations are also be affected by the task type, complexity, workload, duration, and previous experience with the task. To bypass this attentional and thermoregulatory problem, we focused on the body rather than environmental temperature. Specifically, we measured tympanic, forehead, finger and environmental temperatures accompanied by a battery of attentional tasks. We considered a 10 min baseline period wherein subjects were instructed to sit and relax, followed by three attentional tasks: a continuous performance task (CPT), a flanker task (FT) and a counting task (CT). Using multiple linear regression models, we evaluated which variable(s) were the best predictors of performance. The results showed a decrement in finger temperature due to instruction and task engagement that was absent when the subject was instructed to relax. No changes were observed in tympanic or forehead temperatures, while the environmental temperature remained almost constant for each subject. Specifically, the magnitude of the change in finger temperature was the best predictor of performance in all three attentional tasks. The results presented here suggest that finger temperature can be used as a predictor of alertness, as it predicted performance in attentional tasks better than environmental temperature. These findings strongly support that peripheral temperature can be used as a tool to prevent unsafe behaviors and accidents.

  8. Cold-Blooded Attention: Finger Temperature Predicts Attentional Performance

    Directory of Open Access Journals (Sweden)

    Rodrigo C. Vergara

    2017-09-01

    Full Text Available Thermal stress has been shown to increase the chances of unsafe behavior during industrial and driving performances due to reductions in mental and attentional resources. Nonetheless, establishing appropriate safety standards regarding environmental temperature has been a major problem, as modulations are also be affected by the task type, complexity, workload, duration, and previous experience with the task. To bypass this attentional and thermoregulatory problem, we focused on the body rather than environmental temperature. Specifically, we measured tympanic, forehead, finger and environmental temperatures accompanied by a battery of attentional tasks. We considered a 10 min baseline period wherein subjects were instructed to sit and relax, followed by three attentional tasks: a continuous performance task (CPT, a flanker task (FT and a counting task (CT. Using multiple linear regression models, we evaluated which variable(s were the best predictors of performance. The results showed a decrement in finger temperature due to instruction and task engagement that was absent when the subject was instructed to relax. No changes were observed in tympanic or forehead temperatures, while the environmental temperature remained almost constant for each subject. Specifically, the magnitude of the change in finger temperature was the best predictor of performance in all three attentional tasks. The results presented here suggest that finger temperature can be used as a predictor of alertness, as it predicted performance in attentional tasks better than environmental temperature. These findings strongly support that peripheral temperature can be used as a tool to prevent unsafe behaviors and accidents.

  9. Does teacher evaluation based on student performance predict motivation, well-being, and ill-being?

    Science.gov (United States)

    Cuevas, Ricardo; Ntoumanis, Nikos; Fernandez-Bustos, Juan G; Bartholomew, Kimberley

    2018-06-01

    This study tests an explanatory model based on self-determination theory, which posits that pressure experienced by teachers when they are evaluated based on their students' academic performance will differentially predict teacher adaptive and maladaptive motivation, well-being, and ill-being. A total of 360 Spanish physical education teachers completed a multi-scale inventory. We found support for a structural equation model that showed that perceived pressure predicted teacher autonomous motivation negatively, predicted amotivation positively, and was unrelated to controlled motivation. In addition, autonomous motivation predicted vitality positively and exhaustion negatively, whereas controlled motivation and amotivation predicted vitality negatively and exhaustion positively. Amotivation significantly mediated the relation between pressure and vitality and between pressure and exhaustion. The results underline the potential negative impact of pressure felt by teachers due to this type of evaluation on teacher motivation and psychological health. Copyright © 2018 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  10. No significant effect of prefrontal tDCS on working memory performance in older adults

    Directory of Open Access Journals (Sweden)

    Jonna eNilsson

    2015-12-01

    Full Text Available Transcranial direct current stimulation (tDCS has been put forward as a non-pharmacological alternative for alleviating cognitive decline in old age. Although results have shown some promise, little is known about the optimal stimulation parameters for modulation in the cognitive domain. In this study, the effects of tDCS over the dorsolateral prefrontal cortex (dlPFC on working memory performance were investigated in thirty older adults. An N-back task assessed working memory before, during and after anodal tDCS at a current strength of 1mA and 2mA, in addition to sham stimulation. The study used a single-blind, cross-over design. The results revealed no significant effect of tDCS on accuracy or response times during or after stimulation, for any of the current strengths. These results suggest that a single session of tDCS over the dlPFC is unlikely to improve working memory, as assessed by an N-back task, in old age.

  11. Aerodynamic performance prediction of Darrieus-type wind turbines

    Directory of Open Access Journals (Sweden)

    Ion NILĂ

    2010-06-01

    Full Text Available The prediction of Darrieus wind turbine aerodynamic performances provides the necessarydesign and operational data base related to the wind potential. In this sense it provides the type ofturbine suitable to the area where it is to be installed. Two calculation methods are analyzed for arotor with straight blades. The first one is a global method that allows an assessment of the turbinenominal power by a brief calculation. This method leads to an overestimation of performances. Thesecond is the calculation method of the gust factor and momentum which deals with the pale as beingcomposed of different elements that don’t influence each other. This method, developed based on thetheory of the turbine blades, leads to values close to the statistical data obtained experimentally. Thevalues obtained by the calculation method of gust factor - momentum led to the concept of a Darrieusturbine, which will be tested for different wind values in the INCAS subsonic wind tunnel.

  12. Performance prediction of rotary compressor with hydrocarbon refrigerant mixtures

    Energy Technology Data Exchange (ETDEWEB)

    Park, M.W.; Chung, Y.G. [Hanyang University Graduate School, Seoul (Korea); Park, K.W. [LG Industrial System Corporation Limited (Korea); Park, H.Y. [Hanyang University, Seoul (Korea)

    1999-04-01

    This paper presents the modeling approach that can be predicted transient behavior of rotary compressor. Mass and energy conservation laws are applied to the control volume, and real gas state equation is used to obtain thermodynamic properties of refrigerant. The valve equation is solved to analyze discharge process also. Dynamic analysis of vane and roller is carried out to gain friction work. From above modeling, the performance of rotary compressor with radial clearance and friction loss is investigated numerically. The performance of each refrigerant and the possibility of using the hydrocarbon refrigerant mixtures in an existing rotary compressor are estimated by applying R12, R134a, R290/R600a mixture also. (author). 6 refs., 13 figs., 1 tab.

  13. Tracking Neuronal Connectivity from Electric Brain Signals to Predict Performance.

    Science.gov (United States)

    Vecchio, Fabrizio; Miraglia, Francesca; Rossini, Paolo Maria

    2018-05-01

    The human brain is a complex container of interconnected networks. Network neuroscience is a recent venture aiming to explore the connection matrix built from the human brain or human "Connectome." Network-based algorithms provide parameters that define global organization of the brain; when they are applied to electroencephalographic (EEG) signals network, configuration and excitability can be monitored in millisecond time frames, providing remarkable information on their instantaneous efficacy also for a given task's performance via online evaluation of the underlying instantaneous networks before, during, and after the task. Here we provide an updated summary on the connectome analysis for the prediction of performance via the study of task-related dynamics of brain network organization from EEG signals.

  14. Planetary Suit Hip Bearing Model for Predicting Design vs. Performance

    Science.gov (United States)

    Cowley, Matthew S.; Margerum, Sarah; Harvil, Lauren; Rajulu, Sudhakar

    2011-01-01

    , the suited performance trends were comparable between the model and the suited subjects. With the three off-nominal bearing configurations compared to the nominal bearing configurations, human subjects showed decreases in hip flexion of 64%, 6%, and 13% and in hip abduction of 59%, 2%, and 20%. Likewise the solid model showed decreases in hip flexion of 58%, 1%, and 25% and in hip abduction of 56%, 0%, and 30%, under the same condition changes from the nominal configuration. Differences seen between the model predictions and the human subject performance data could be attributed to the model lacking dynamic elements and performing kinematic analysis only, the level of fit of the subjects with the suit, the levels of the subject s suit experience.

  15. Clinical significance and predictive factors of early massive recurrence after radiofrequency ablation in patients with a single small hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Ju-Yeon Cho

    2016-12-01

    Full Text Available Background/Aims Radiofrequency ablation (RFA is one of the most frequently applied curative treatments in patients with a single small hepatocellular carcinoma (HCC. However, the clinical significance of and risk factors for early massive recurrence after RFA—a dreadful event limiting further curative treatment—have not been fully evaluated. Methods In total, 438 patients with a single HCC of size ≤3 cm who underwent percutaneous RFA as an initial treatment between 2006 and 2009 were included. Baseline patient characteristics, overall survival, predictive factors, and recurrence after RFA were evaluated. In addition, the incidence, impact on survival, and predictive factors of early massive recurrence, and initial recurrence beyond the Milan criteria within 2 years were also investigated. Results During the median follow-up of 68.4 months, recurrent HCC was confirmed in 302 (68.9% patients, with early massive recurrence in 27 patients (6.2%. The 1-, 3-, and 5-year overall survival rates were 95.4%, 84.7%, and 81.8%, respectively, in patients with no recurrence, 99.6%, 86.4%, and 70.1% in patients with recurrence within the Milan criteria or late recurrence, and 92.6%, 46.5%, and 0.05% in patients with early massive recurrence. Multivariable analysis identified older age, Child-Pugh score B or C, and early massive recurrence as predictive of poor overall survival. A tumor size of ≥2 cm and tumor location adjacent to the colon were independent risk factors predictive of early massive recurrence. Conclusions Early massive recurrence is independently predictive of poor overall survival after RFA in patients with a single small HCC. Tumors sized ≥2 cm and located adjacent to the colon appear to be independent risk factors for early massive recurrence.

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

    Science.gov (United States)

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

    2017-04-01

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

  17. The prediction of the hydrodynamic performance of tidal current turbines

    International Nuclear Information System (INIS)

    Xiao, B Y; Zhou, L J; Xiao, Y X; Wang, Z W

    2013-01-01

    Nowadays tidal current energy is considered to be one of the most promising alternative green energy resources and tidal current turbines are used for power generation. Prediction of the open water performance around tidal turbines is important for the reason that it can give some advice on installation and array of tidal current turbines. This paper presents numerical computations of tidal current turbines by using a numerical model which is constructed to simulate an isolated turbine. This paper aims at studying the installation of marine current turbine of which the hydro-environmental impacts influence by means of numerical simulation. Such impacts include free-stream velocity magnitude, seabed and inflow direction of velocity. The results of the open water performance prediction show that the power output and efficiency of marine current turbine varies from different marine environments. The velocity distribution should be clearly and the suitable unit installation depth and direction be clearly chosen, which can ensure the most effective strategy for energy capture before installing the marine current turbine. The findings of this paper are expected to be beneficial in developing tidal current turbines and array in the future

  18. Determination of Constructs and Dimensions of Employability Skills Based Work Performance Prediction: A Triangular Approach

    OpenAIRE

    Rahmat, Normala; Buntat, Yahya; Ayub, Abdul Rahman

    2015-01-01

    The level of the employability skills of the graduates as determined by job role and mapped to the employability skills, which correspond to the requirement of employers, will have significant impact on the graduates’ job performance. The main objective of this study was to identify the constructs and dimensions of employability skills, which can predict the work performance of electronic polytechnic graduate in electrical and electronics industry. A triangular qualitative approach was used i...

  19. Predicting the Impacts of Intravehicular Displays on Driving Performance with Human Performance Modeling

    Science.gov (United States)

    Mitchell, Diane Kuhl; Wojciechowski, Josephine; Samms, Charneta

    2012-01-01

    A challenge facing the U.S. National Highway Traffic Safety Administration (NHTSA), as well as international safety experts, is the need to educate car drivers about the dangers associated with performing distraction tasks while driving. Researchers working for the U.S. Army Research Laboratory have developed a technique for predicting the increase in mental workload that results when distraction tasks are combined with driving. They implement this technique using human performance modeling. They have predicted workload associated with driving combined with cell phone use. In addition, they have predicted the workload associated with driving military vehicles combined with threat detection. Their technique can be used by safety personnel internationally to demonstrate the dangers of combining distracter tasks with driving and to mitigate the safety risks.

  20. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna's hummingbirds.

    Science.gov (United States)

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-11-19

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability.

  1. ROLE AND SIGNIFICANCE OF STATEMENT OF OTHER COMPREHENSIVE INCOME– IN RESPECT OF REPORTING COMPANIES’ PERFORMANCE

    Directory of Open Access Journals (Sweden)

    Ildiko Orban

    2014-07-01

    Full Text Available A commonly accepted rule-system, which name was International Financial Reporting Standards (IFRS created the framework for represent the financial performace, and other facts related to the company’s health. In the system of IFRS profit is not equal to income less expenses, this deviation led to the other comprehensive income, OCI term. IFRS have created the term of other comprehensive income, but knowledge and using of it is not widespread. In this paper I tend to present the meaning and essence of this income category, and to reveal how it is work in corporate practice. As basis of the research, definitions and formats related to the statement of comprehensive income will be presented in the paper first. In order to get a clear picture about the differences between the income statements, I make a comparison of the IFRS and the Hungarian Accounting Act in the field of performance’s representation. As a result of my comparison I’ve stated that the EU accepted the international financial reporting standards to present the financial performance of publicly traded companies, and as EU member state it is obligatory for the Hungarian companies as well. This is the reason why Hungary’s present task is taking over the IFRS mentality. After the comparative analysis I’ve examined the Statement of other comprehensive income in the practice of 11 listed companies in the Budapest Stock Exchange. The Premium category includes those companies’ series of liquid shares, which has got broader investor base. The aim of this examination was to reveal if the most significant listed companies calculate other comprehensive income and what kind of items do they present in the statement of OCI. As a result of the research we can state that statement of other comprehensive income is part of the statement of total comprehensive income in general, and not an individual statement. Main items of the other comprehensive income of the examined companies are the

  2. Predicting students' intention to use stimulants for academic performance enhancement.

    Science.gov (United States)

    Ponnet, Koen; Wouters, Edwin; Walrave, Michel; Heirman, Wannes; Van Hal, Guido

    2015-02-01

    The non-medical use of stimulants for academic performance enhancement is becoming a more common practice among college and university students. The objective of this study is to gain a better understanding of students' intention to use stimulant medication for the purpose of enhancing their academic performance. Based on an extended model of Ajzen's theory of planned behavior, we examined the predictive value of attitude, subjective norm, perceived behavioral control, psychological distress, procrastination, substance use, and alcohol use on students' intention to use stimulants to improve their academic performance. The sample consisted of 3,589 Flemish university and college students (mean age: 21.59, SD: 4.09), who participated anonymously in an online survey conducted in March and April 2013. Structural equation modeling was used to investigate the relationships among the study variables. Our results indicate that subjective norm is the strongest predictor of students' intention to use stimulant medication, followed by attitude and perceived behavioral control. To a lesser extent, procrastinating tendencies, psychological distress, and substance abuse contribute to students' intention. Conclusions/ Importance: Based on these findings, we provide several recommendations on how to curtail students' intention to use stimulant medication for the purpose of improving their academic performance. In addition, we urge researchers to identify other psychological variables that might be related to students' intention.

  3. Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years.

    Science.gov (United States)

    Selzam, Saskia; Dale, Philip S; Wagner, Richard K; DeFries, John C; Cederlöf, Martin; O'Reilly, Paul F; Krapohl, Eva; Plomin, Robert

    2017-07-04

    It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ( EduYears ) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

  4. Identifying the most significant indicators of the total road safety performance index.

    Science.gov (United States)

    Tešić, Milan; Hermans, Elke; Lipovac, Krsto; Pešić, Dalibor

    2018-04-01

    The review of the national and international literature dealing with the assessment of the road safety level has shown great efforts of the authors who tried to define the methodology for calculating the composite road safety index on a territory (region, state, etc.). The procedure for obtaining a road safety composite index of an area has been largely harmonized. The question that has not been fully resolved yet concerns the selection of indicators. There is a wide range of road safety indicators used to show a road safety situation on a territory. Road safety performance index (RSPI) obtained on the basis of a larger number of safety performance indicators (SPIs) enable decision makers to more precisely define the earlier goal- oriented actions. However, recording a broader comprehensive set of SPIs helps identify the strengths and weaknesses of a country's road safety system. Providing high quality national and international databases that would include comparable SPIs seems to be difficult since a larger number of countries dispose of a small number of identical indicators available for use. Therefore, there is a need for calculating a road safety performance index with a limited number of indicators (RSPI ln n ) which will provide a comparison of a sufficient quality, of as many countries as possible. The application of the Data Envelopment Analysis (DEA) method and correlative analysis has helped to check if the RSPI ln n is likely to be of sufficient quality. A strong correlation between the RSPI ln n and the RSPI has been identified using the proposed methodology. Based on this, the most contributing indicators and methodologies for gradual monitoring of SPIs, have been defined for each country analyzed. The indicator monitoring phases in the analyzed countries have been defined in the following way: Phase 1- the indicators relating to alcohol, speed and protective systems; Phase 2- the indicators relating to roads and Phase 3- the indicators relating to

  5. The role of sleep in predicting college academic performance: is it a unique predictor?

    Science.gov (United States)

    Taylor, Daniel J; Vatthauer, Karlyn E; Bramoweth, Adam D; Ruggero, Camilo; Roane, Brandy

    2013-01-01

    Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. This project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Participants (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset latency, later bedtimes, later wake times, and TST inconsistency would predict decreased academic performance. The most significant predictors of academic performance were high school GPA, standardized test scores (i.e., SAT/ACT), TST, time awake before arising (TWAK), TST inconsistency, and the quadratic terms of perceived stress (PSS) and TST.

  6. Compression stockings significantly improve hemodynamic performance in post-thrombotic syndrome irrespective of class or length.

    Science.gov (United States)

    Lattimer, Christopher R; Azzam, Mustapha; Kalodiki, Evi; Makris, Gregory C; Geroulakos, George

    2013-07-01

    Graduated elastic compression (GEC) stockings have been demonstrated to reduce the morbidity associated with post-thrombotic syndrome. The ideal length or compression strength required to achieve this is speculative and related to physician preference and patient compliance. The aim of this study was to evaluate the hemodynamic performance of four different stockings and determine the patient's preference. Thirty-four consecutive patients (40 legs, 34 male) with post-thrombotic syndrome were tested with four different stockings (Mediven plus open toe, Bayreuth, Germany) of their size in random order: class 1 (18-21 mm Hg) and class II (23-32 mm Hg), below-knee (BK) and above-knee thigh-length (AK). The median age, Venous Clinical Severity Score, Venous Segmental Disease Score, and Villalta scale were 62 years (range, 31-81 years), 8 (range, 1-21), 5 (range, 2-10), and 10 (range, 2-22), respectively. The C of C0-6EsAs,d,pPr,o was C0 = 2, C2 = 1, C3 = 3, C4a = 12, C4b = 7, C5 = 12, C6 = 3. Obstruction and reflux was observed on duplex in 47.5% legs, with deep venous reflux alone in 45%. Air plethysmography was used to measure the venous filling index (VFI), venous volume, and time to fill 90% of the venous volume. Direct pressure measurements were obtained while lying and standing using the PicoPress device (Microlab Elettronica, Nicolò, Italy). The pressure sensor was placed underneath the test stocking 5 cm above and 2 cm posterior to the medial malleolus. At the end of the study session, patients stated their preferred stocking based on comfort. The VFI, venous volume, and time to fill 90% of the venous volume improved significantly with all types of stocking versus no compression. In class I, the VFI (mL/s) improved from a median of 4.9 (range, 1.7-16.3) without compression to 3.7 (range, 0-14) BK (24.5%) and 3.6 (range, 0.6-14.5) AK (26.5%). With class II, the corresponding improvement was to 4.0 (range, 0.3-16.2) BK (18.8%) and 3.7 (range, 0.5-14.2) AK (24

  7. Evaluation of Design & Analysis Code, CACTUS, for Predicting Crossflow Hydrokinetic Turbine Performance

    Energy Technology Data Exchange (ETDEWEB)

    Wosnik, Martin [Univ. of New Hampshire, Durham, NH (United States). Center for Ocean Renewable Energy; Bachant, Pete [Univ. of New Hampshire, Durham, NH (United States). Center for Ocean Renewable Energy; Neary, Vincent Sinclair [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Murphy, Andrew W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-09-01

    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 in 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.

  8. 40 CFR 141.723 - Requirements to respond to significant deficiencies identified in sanitary surveys performed by EPA.

    Science.gov (United States)

    2010-07-01

    ... deficiencies identified in sanitary surveys performed by EPA. 141.723 Section 141.723 Protection of Environment... performed by EPA, systems must respond in writing to significant deficiencies identified in sanitary survey... will address significant deficiencies noted in the survey. (d) Systems must correct significant...

  9. Performance analysis of tracked panel according to predicted global radiation

    International Nuclear Information System (INIS)

    Chang, T.P.

    2009-01-01

    In this paper, the performance of a south facing single-axis tracked panel was analyzed according to global radiation predicted by empirical model. Mathematic expressions appropriate for single-axis tracking system were derived to calculate the radiation on it. Instantaneous increments of solar energy collected by the tracked panel relative to fixed panel are illustrated. The validity of the empirical model to Taiwan area will also be examined with the actual irradiation data observed in Taipei. The results are summarized as follows: the gains made by the tracked panel relative to a fixed panel are between 20.0% and 33.9% for four specified days of year, between 20.9% and 33.2% for the four seasons and 27.6% over the entire year. For latitudes below 65 deg., the yearly optimal tilt angle of a fixed panel is close to 0.8 times latitude, the irradiation ratio of the tracked panel to the fixed panel is about 1.3, which are smaller than the corresponding values calculated from extraterrestrial radiation, suggesting us that the installation angle should be adjusted toward a flatter angle and that the gain of the tracked panel will reduce while it works in cloudy climate or in air pollution environment. Although the captured radiation increases with the maximal rotation angle of panel, but the benefit on the global radiation case is still not so good as that on extraterrestrial radiation case. The irradiation data observed is much less than the data predicted by the empirical model, however the trend of fitting curve to the observed data is somewhat in agreement with that to the predicted one; the yearly gain is 14.3% when a tracked panel is employed throughout the year.

  10. Estimating the Performance of Random Forest versus Multiple Regression for Predicting Prices of the Apartments

    Directory of Open Access Journals (Sweden)

    Marjan Čeh

    2018-05-01

    Full Text Available The goal of this study is to analyse the predictive performance of the random forest machine learning technique in comparison to commonly used hedonic models based on multiple regression for the prediction of apartment prices. A data set that includes 7407 records of apartment transactions referring to real estate sales from 2008–2013 in the city of Ljubljana, the capital of Slovenia, was used in order to test and compare the predictive performances of both models. Apparent challenges faced during modelling included (1 the non-linear nature of the prediction assignment task; (2 input data being based on transactions occurring over a period of great price changes in Ljubljana whereby a 28% decline was noted in six consecutive testing years; and (3 the complex urban form of the case study area. Available explanatory variables, organised as a Geographic Information Systems (GIS ready dataset, including the structural and age characteristics of the apartments as well as environmental and neighbourhood information were considered in the modelling procedure. All performance measures (R2 values, sales ratios, mean average percentage error (MAPE, coefficient of dispersion (COD revealed significantly better results for predictions obtained by the random forest method, which confirms the prospective of this machine learning technique on apartment price prediction.

  11. Individualized performance prediction during total sleep deprivation: accounting for trait vulnerability to sleep loss.

    Science.gov (United States)

    Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Thorsley, David; Wesensten, Nancy J; Balkin, Thomas J; Reifman, Jaques

    2012-01-01

    Individual differences in vulnerability to sleep loss can be considerable, and thus, recent efforts have focused on developing individualized models for predicting the effects of sleep loss on performance. Individualized models constructed using a Bayesian formulation, which combines an individual's available performance data with a priori performance predictions from a group-average model, typically need at least 40 h of individual data before showing significant improvement over the group-average model predictions. Here, we improve upon the basic Bayesian formulation for developing individualized models by observing that individuals may be classified into three sleep-loss phenotypes: resilient, average, and vulnerable. For each phenotype, we developed a phenotype-specific group-average model and used these models to identify each individual's phenotype. We then used the phenotype-specific models within the Bayesian formulation to make individualized predictions. Results on psychomotor vigilance test data from 48 individuals indicated that, on average, ∼85% of individual phenotypes were accurately identified within 30 h of wakefulness. The percentage improvement of the proposed approach in 10-h-ahead predictions was 16% for resilient subjects and 6% for vulnerable subjects. The trade-off for these improvements was a slight decrease in prediction accuracy for average subjects.

  12. Study of prognostic significance of antenatal ultrasonography and renin angiotensin system activation in predicting disease severity in posterior urethral valves

    Directory of Open Access Journals (Sweden)

    Divya Bhadoo

    2015-01-01

    Full Text Available Aims: Study on prognostic significance of antenatal ultrasonography and renin angiotensin system activation in predicting disease severity in posterior urethral valves. Materials and Methods: Antenatally diagnosed hydronephrosis patients were included. Postnatally, they were divided into two groups, posterior urethral valve (PUV and non-PUV. The studied parameters were: Gestational age at detection, surgical intervention, ultrasound findings, cord blood and follow up plasma renin activity (PRA values, vesico-ureteric reflux (VUR, renal scars, and glomerular filtration rate (GFR. Results: A total of 25 patients were included, 10 PUV and 15 non-PUV. All infants with PUV underwent primary valve incision. GFR was less than 60 ml/min/1.73 m 2 body surface area in 4 patients at last follow-up. Keyhole sign, oligoamnios, absent bladder cycling, and cortical cysts were not consistent findings on antenatal ultrasound in PUV. Cord blood PRA was significantly higher (P < 0.0001 in PUV compared to non-PUV patients. Gestational age at detection of hydronephrosis, cortical cysts, bladder wall thickness, and amniotic fluid index were not significantly correlated with GFR while PRA could differentiate between poor and better prognosis cases with PUV. Conclusions: Ultrasound was neither uniformly useful in diagnosing PUV antenatally, nor differentiating it from cases with non-PUV hydronephrosis. In congenital hydronephrosis, cord blood PRA was significantly higher in cases with PUV compared to non-PUV cases and fell significantly after valve ablation. Cord blood PRA could distinguish between poor and better prognosis cases with PUV.

  13. Application of Machine Learning Algorithms for the Query Performance Prediction

    Directory of Open Access Journals (Sweden)

    MILICEVIC, M.

    2015-08-01

    Full Text Available This paper analyzes the relationship between the system load/throughput and the query response time in a real Online transaction processing (OLTP system environment. Although OLTP systems are characterized by short transactions, which normally entail high availability and consistent short response times, the need for operational reporting may jeopardize these objectives. We suggest a new approach to performance prediction for concurrent database workloads, based on the system state vector which consists of 36 attributes. There is no bias to the importance of certain attributes, but the machine learning methods are used to determine which attributes better describe the behavior of the particular database server and how to model that system. During the learning phase, the system's profile is created using multiple reference queries, which are selected to represent frequent business processes. The possibility of the accurate response time prediction may be a foundation for automated decision-making for database (DB query scheduling. Possible applications of the proposed method include adaptive resource allocation, quality of service (QoS management or real-time dynamic query scheduling (e.g. estimation of the optimal moment for a complex query execution.

  14. Mental Strategies Predict Performance and Satisfaction with Performance among Soccer Players.

    Science.gov (United States)

    Kruk, Magdalena; Blecharz, Jan; Boberska, Monika; Zarychta, Karolina; Luszczynska, Aleksandra

    2017-10-01

    This study investigated the changes in mental strategies across the season and their effects on performance and satisfaction with individual performance. Data were collected three times: at the pre-season at Time 1 (T1; baseline), in the mid-season at Time 2 (T2; two-month follow-up), and at the end-of-season at Time 3 (T3; nine-month follow-up) among male soccer players (N = 97) aged 16-27. Athletes completed the questionnaires assessing the use of nine psychological strategies in competition and the level of satisfaction with individual performance. Endurance performance was measured objectively with a 300 m run. A high level of relaxation (T1) explained better 300 m run performance (T3) and a high level of self-talk explained a higher satisfaction with individual performance (T3). A rare use of distractibility and emotional control (T1) predicted a higher level of satisfaction with individual performance (T3). No predictive role of other psychological strategies was found. The use of emotional control, relaxation, and distractibility increased over the season, whereas the use of imagery and negative thinking declined. Besides the roles of self-talk, imagery, relaxation and goal-setting, the effects of distractibility and emotional control should be taken into account when considering athletes' mental training programs.

  15. Predictive Validity of National Basketball Association Draft Combine on Future Performance.

    Science.gov (United States)

    Teramoto, Masaru; Cross, Chad L; Rieger, Randall H; Maak, Travis G; Willick, Stuart E

    2018-02-01

    Teramoto, M, Cross, CL, Rieger, RH, Maak, TG, and Willick, SE. Predictive validity of national basketball association draft combine on future performance. J Strength Cond Res 32(2): 396-408, 2018-The National Basketball Association (NBA) Draft Combine is an annual event where prospective players are evaluated in terms of their athletic abilities and basketball skills. Data collected at the Combine should help NBA teams select right the players for the upcoming NBA draft; however, its value for predicting future performance of players has not been examined. This study investigated predictive validity of the NBA Draft Combine on future performance of basketball players. We performed a principal component analysis (PCA) on the 2010-2015 Combine data to reduce correlated variables (N = 234), a correlation analysis on the Combine data and future on-court performance to examine relationships (maximum pairwise N = 217), and a robust principal component regression (PCR) analysis to predict first-year and 3-year on-court performance from the Combine measures (N = 148 and 127, respectively). Three components were identified within the Combine data through PCA (= Combine subscales): length-size, power-quickness, and upper-body strength. As per the correlation analysis, the individual Combine items for anthropometrics, including height without shoes, standing reach, weight, wingspan, and hand length, as well as the Combine subscale of length-size, had positive, medium-to-large-sized correlations (r = 0.313-0.545) with defensive performance quantified by Defensive Box Plus/Minus. The robust PCR analysis showed that the Combine subscale of length-size was a predictor most significantly associated with future on-court performance (p ≤ 0.05), including Win Shares, Box Plus/Minus, and Value Over Replacement Player, followed by upper-body strength. In conclusion, the NBA Draft Combine has value for predicting future performance of players.

  16. Functional relationships between plasmids and their significance for metabolism and symbiotic performance of Rhizobium leguminosarum bv. trifolii.

    Science.gov (United States)

    Stasiak, Grażyna; Mazur, Andrzej; Wielbo, Jerzy; Marczak, Małgorzata; Zebracki, Kamil; Koper, Piotr; Skorupska, Anna

    2014-11-01

    Rhizobium leguminosarum bv. trifolii TA1 (RtTA1) is a soil bacterium establishing a highly specific symbiotic relationship with clover, which is based on the exchange of molecular signals between the host plant and the microsymbiont. The RtTA1 genome is large and multipartite, composed of a chromosome and four plasmids, which comprise approximately 65 % and 35 % of the total genome, respectively. Extrachromosomal replicons were previously shown to confer significant metabolic versatility to bacteria, which is important for their adaptation in the soil and nodulation competitiveness. To investigate the contribution of individual RtTA1 plasmids to the overall cell phenotype, metabolic properties and symbiotic performance, a transposon-based elimination strategy was employed. RtTA1 derivatives cured of pRleTA1b or pRleTA1d and deleted in pRleTA1a were obtained. In contrast to the in silico predictions of pRleTA1b and pRleTA1d, which were described as chromid-like replicons, both appeared to be completely curable. On the other hand, for pRleTA1a (symbiotic plasmid) and pRleTA1c, which were proposed to be unessential for RtTA1 viability, it was not possible to eliminate them at all (pRleTA1c) or entirely (pRleTA1a). Analyses of the phenotypic traits of the RtTA1 derivatives obtained revealed the functional significance of individual plasmids and their indispensability for growth, certain metabolic pathways, production of surface polysaccharides, autoaggregation, biofilm formation, motility and symbiotic performance. Moreover, the results allow us to suggest broad functional cooperation among the plasmids in shaping the phenotypic properties and symbiotic capabilities of rhizobia.

  17. Sensorimotor abilities predict on-field performance in professional baseball.

    Science.gov (United States)

    Burris, Kyle; Vittetoe, Kelly; Ramger, Benjamin; Suresh, Sunith; Tokdar, Surya T; Reiter, Jerome P; Appelbaum, L Gregory

    2018-01-08

    Baseball players must be able to see and react in an instant, yet it is hotly debated whether superior performance is associated with superior sensorimotor abilities. In this study, we compare sensorimotor abilities, measured through 8 psychomotor tasks comprising the Nike Sensory Station assessment battery, and game statistics in a sample of 252 professional baseball players to evaluate the links between sensorimotor skills and on-field performance. For this purpose, we develop a series of Bayesian hierarchical latent variable models enabling us to compare statistics across professional baseball leagues. Within this framework, we find that sensorimotor abilities are significant predictors of on-base percentage, walk rate and strikeout rate, accounting for age, position, and league. We find no such relationship for either slugging percentage or fielder-independent pitching. The pattern of results suggests performance contributions from both visual-sensory and visual-motor abilities and indicates that sensorimotor screenings may be useful for player scouting.

  18. Significant correlation between spleen volume and thrombocytopenia in liver transplant patients: a concept for predicting persistent thrombocytopenia.

    Science.gov (United States)

    Ohira, Masahiro; Ishifuro, Minoru; Ide, Kentaro; Irei, Toshimitsu; Tashiro, Hirotaka; Itamoto, Toshiyuki; Ito, Katsuhide; Chayama, Kazuaki; Asahara, Toshimasa; Ohdan, Hideki

    2009-02-01

    Interferon (IFN) therapy with or without ribavirin treatment is well established as a standard antiviral treatment for hepatitis C virus (HCV)-infected patients. However, susceptibility to thrombocytopenia is a major obstacle for initiating or continuing this therapy, particularly in liver transplant (LTx) recipients with HCV. Studies have reported that splenectomy performed concurrently with LTx is a feasible strategy for conditioning patients for anti-HCV IFN therapy. However, the relationship between the severity of splenomegaly and alterations in the blood cytopenia in LTx recipients remains to be clarified. Here, we analyzed the relationship between spleen volume (SV) and thrombocytopenia in 45 patients who underwent LTx at Hiroshima University Hospital. The extent of pre-LTx splenomegaly [the SV to body surface area (BSA) ratio in an individual] was inversely correlated with both the post-LTx white blood cell count and platelet (PLT) count (P or= 400), persistent thrombocytopenia is predictable after LTx. (c) 2009 AASLD.

  19. Performance prediction of hot mix asphalt from asphalt binders

    International Nuclear Information System (INIS)

    Hafeez, I.; Kamal, M.A.; Shahzad, Q.; Bashir, N.; Ahadi, M.R.

    2012-01-01

    Asphalt binder being a high weight hydrocarbon contains asphaltene and maltene and is widely used as cementing materials in the construction of flexible pavements. Its performance in hot mix asphalt also depends on combining with different proportions of aggregates. The main objective of this study was to characterize asphalt cement rheological behavior and to investigate the influence of asphalt on asphalt-aggregate mixtures prepared with virgin binders and using polymers. Binder rheology and mixtures stiffness were determined under a range of cyclic loadings and temperature conditions. Master curves were developed for the evaluation of relationship between parameters like complex modulus and phase angle at different frequencies. Horizontal shift factors were also computed to determine time and temperature response of binders and mixes. The results showed that the stiffness of both the binder and the mixes depends on temperature and frequency of load. Polymer modified binder is least susceptible to temperature variations as compared to other virgin asphalt cement. Performance of asphalt mixtures can be predicted from those of asphalt binders using the master curve technique. (author)

  20. Prediction of Gas Injection Performance for Heterogeneous Reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Blunt, Martin J.; Orr, Franklin M.

    1999-05-17

    This report describes research carried out in the Department of Petroleum Engineering at Stanford University from September 1997 - September 1998 under the second year of a three-year grant from the Department of Energy on the "Prediction of Gas Injection Performance for Heterogeneous Reservoirs." The research effort is an integrated study of the factors affecting gas injection, from the pore scale to the field scale, and involves theoretical analysis, laboratory experiments, and numerical simulation. The original proposal described research in four areas: (1) Pore scale modeling of three phase flow in porous media; (2) Laboratory experiments and analysis of factors influencing gas injection performance at the core scale with an emphasis on the fundamentals of three phase flow; (3) Benchmark simulations of gas injection at the field scale; and (4) Development of streamline-based reservoir simulator. Each state of the research is planned to provide input and insight into the next stage, such that at the end we should have an integrated understanding of the key factors affecting field scale displacements.

  1. Preparatory neural activity predicts performance on a conflict task.

    Science.gov (United States)

    Stern, Emily R; Wager, Tor D; Egner, Tobias; Hirsch, Joy; Mangels, Jennifer A

    2007-10-24

    Advance preparation has been shown to improve the efficiency of conflict resolution. Yet, with little empirical work directly linking preparatory neural activity to the performance benefits of advance cueing, it is not clear whether this relationship results from preparatory activation of task-specific networks, or from activity associated with general alerting processes. Here, fMRI data were acquired during a spatial Stroop task in which advance cues either informed subjects of the upcoming relevant feature of conflict stimuli (spatial or semantic) or were neutral. Informative cues decreased reaction time (RT) relative to neutral cues, and cues indicating that spatial information would be task-relevant elicited greater activity than neutral cues in multiple areas, including right anterior prefrontal and bilateral parietal cortex. Additionally, preparatory activation in bilateral parietal cortex and right dorsolateral prefrontal cortex predicted faster RT when subjects responded to spatial location. No regions were found to be specific to semantic cues at conventional thresholds, and lowering the threshold further revealed little overlap between activity associated with spatial and semantic cueing effects, thereby demonstrating a single dissociation between activations related to preparing a spatial versus semantic task-set. This relationship between preparatory activation of spatial processing networks and efficient conflict resolution suggests that advance information can benefit performance by leading to domain-specific biasing of task-relevant information.

  2. PREDICTING THERMAL PERFORMANCE OF ROOFING SYSTEMS IN SURABAYA

    Directory of Open Access Journals (Sweden)

    MINTOROGO Danny Santoso

    2015-07-01

    Full Text Available Traditional roofing systems in the developing country likes Indonesia are still be dominated by the 30o, 45o, and more pitched angle roofs; the roofing cover materials are widely used to traditional clay roof tiles, then modern concrete roof tiles, and ceramic roof tiles. In the 90’s decay, shop houses are prosperous built with flat concrete roofs dominant. Green roofs and roof ponds are almost rarely built to meet the sustainable environmental issues. Some tested various roof systems in Surabaya were carried out to observe the roof thermal performances. Mathematical equation model from three references are also performed in order to compare with the real project tested. Calculated with equation (Kabre et al., the 30o pitched concrete-roof-tile, 30o clay-roof-tile, 45o pitched concrete-roof-tile are the worst thermal heat flux coming to room respectively. In contrast, the bare soil concrete roof and roof pond system are the least heat flux streamed onto room. Based on predicted calculation without insulation and cross-ventilation attic space, the roof pond and bare soil concrete roof (greenery roof are the appropriate roof systems for the Surabaya’s climate; meanwhile the most un-recommended roof is pitched 30o or 45o angle with concrete-roof tiles roofing systems.

  3. Millisecond photo-thermal process on significant improvement of supercapacitor’s performance

    International Nuclear Information System (INIS)

    Wang, Kui; Wang, Jixiao; Wu, Ying; Zhao, Song; Wang, Zhi; Wang, Shichang

    2016-01-01

    Graphical abstract: A high way for charge transfer is created by a millisecond photo-thermal process which could decrease contact resistance among nanomaterials and improve the electrochemical performances. - Highlights: • Improve conductivity among nanomaterials with a millisecond photo-thermal process. • The specific capacitance can increase about 25% with an photo-thermal process. • The circle stability and rate capability can be improved above 10% with photo-thermal process. • Provide a new way that create electron path to improve electrochemical performance. - Abstract: Supercapacitors fabricated with nanomaterials usually have high specific capacitance and excellent performance. However, the small size of nanomaterials renders a considerable limitation of the contact area among nanomaterials, which is harmful to charge carrier transfer. This fact may hinder the development and application of nanomaterials in electrochemical storage systems. Here, a millisecond photo-thermal process was introduced to create a charge carries transfer path to decrease the contact resistance among nanomaterials, and enhance the electrochemical performance of supercapacitors. Polyaniline (PANI) nanowire, as a model nanomaterial, was used to modify electrodes under different photo-thermal process conditions. The modified electrodes were characterized by scanning electronic microscopy (SEM), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and the results were analysed by equivalent circuit simulation. These results demonstrate that the photo-thermal process can alter the morphology of PANI nanowires, lower the charge transfer resistances and thus improve the performance of electrodes. The specific capacitance increase of the modified electrodes is about 25%. The improvement of the circle stability and rate capability are above 10%. To the best of our knowledge, this is the first attempt on research the effect of photo-thermal process on the conductivity

  4. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    International Nuclear Information System (INIS)

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development

  5. Evidence That Bimanual Motor Timing Performance Is Not a Significant Factor in Developmental Stuttering

    Science.gov (United States)

    Hilger, Allison I.; Zelaznik, Howard; Smith, Anne

    2016-01-01

    Purpose: Stuttering involves a breakdown in the speech motor system. We address whether stuttering in its early stage is specific to the speech motor system or whether its impact is observable across motor systems. Method: As an extension of Olander, Smith, and Zelaznik (2010), we measured bimanual motor timing performance in 115 children: 70…

  6. Student-Led Project Teams: Significance of Regulation Strategies in High- and Low-Performing Teams

    Science.gov (United States)

    Ainsworth, Judith

    2016-01-01

    We studied group and individual co-regulatory and self-regulatory strategies of self-managed student project teams using data from intragroup peer evaluations and a postproject survey. We found that high team performers shared their research and knowledge with others, collaborated to advise and give constructive criticism, and demonstrated moral…

  7. Labour Mobility and Plant Performance in Denmark: The Significance of Related Inflows

    DEFF Research Database (Denmark)

    Timmermans, Bram; Boschma, Ron

    This paper investigates the impact of different types of labour mobility on plant performance, making use of the IDA-database that provides detailed information on all individuals and plants for the whole of Denmark. Our study shows that the effect of labour mobility can only be assessed when one...... performance. Moreover, intra-regional skilled labour mobility had a negative effect on plant performance in general, while the effect of inter-regional labour mobility depends on the type of skills that flow into the plant. We used a sophisticated indicator of revealed relatedness that measures the degree...... accounts for the type of skills that flow into the plant, and the degree to which these match the existing set of skills at the plant level. We found that the inflow of related skills has a positive impact on plant performance, while inflows of similar and unrelated skills have a negative effect on plant...

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

    Science.gov (United States)

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

    1986-01-01

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

  9. Exploration of Machine Learning Approaches to Predict Pavement Performance

    Science.gov (United States)

    2018-03-23

    Machine learning (ML) techniques were used to model and predict pavement condition index (PCI) for various pavement types using a variety of input variables. The primary objective of this research was to develop and assess PCI predictive models for t...

  10. Predicting story goodness performance from cognitive measures following traumatic brain injury.

    Science.gov (United States)

    Lê, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

    2012-05-01

    This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Lê, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. One hundred sixty-seven individuals with TBI participated in the study. Story retellings were analyzed using the SGI protocol. Three cognitive measures--Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001) Sorting Test, Wechsler Memory Scale--Third Edition (WMS-III; Wechsler, 1997) Working Memory Primary Index (WMI), and WMS-III Immediate Memory Primary Index (IMI)--were entered into a multiple linear regression model for each discourse measure. Two sets of regression analyses were performed, the first with the Sorting Test as the first predictor and the second with it as the last. The first set of regression analyses identified the Sorting Test and IMI as the only significant predictors of performance on measures of the SGI. The second set identified all measures as significant predictors when evaluating each step of the regression function. The cognitive variables predicted performance on the SGI measures, although there were differences in the amount of explained variance. The results (a) suggest that storytelling ability draws on a number of underlying skills and (b) underscore the importance of using discrete cognitive tasks rather than broad cognitive indices to investigate the cognitive substrates of discourse.

  11. Towards an improved prediction of the free radical scavenging potency of flavonoids: the significance of double PCET mechanisms.

    Science.gov (United States)

    Amić, Ana; Marković, Zoran; Dimitrić Marković, Jasmina M; Stepanić, Višnja; Lučić, Bono; Amić, Dragan

    2014-01-01

    The 1H(+)/1e(-) and 2H(+)/2e(-) proton-coupled electron transfer (PCET) processes of free radical scavenging by flavonoids were theoretically studied for aqueous and lipid environments using the PM6 and PM7 methods. The results reported here indicate that the significant contribution of the second PCET mechanism, resulting in the formation of a quinone/quinone methide, effectively discriminates the active from inactive flavonoids. The predictive potency of descriptors related to the energetics of second PCET mechanisms (the second O-H bond dissociation enthalpy (BDE2) related to hydrogen atom transfer (HAT) mechanism, and the second electron transfer enthalpy (ETE2) related to sequential proton loss electron transfer (SPLET) mechanism) are superior to the currently used indices, which are related to the first 1H(+)/1e(-) processes, and could serve as primary descriptors in development of the QSAR (quantitative structure-activity relationships) of flavonoids. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Gaussian Process Regression for WDM System Performance Prediction

    DEFF Research Database (Denmark)

    Wass, Jesper; Thrane, Jakob; Piels, Molly

    2017-01-01

    Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data.......Gaussian process regression is numerically and experimentally investigated to predict the bit error rate of a 24 x 28 CiBd QPSK WDM system. The proposed method produces accurate predictions from multi-dimensional and sparse measurement data....

  13. Does Residency Selection Criteria Predict Performance in Orthopaedic Surgery Residency?

    Science.gov (United States)

    Raman, Tina; Alrabaa, Rami George; Sood, Amit; Maloof, Paul; Benevenia, Joseph; Berberian, Wayne

    2016-04-01

    More than 1000 candidates applied for orthopaedic residency positions in 2014, and the competition is intense; approximately one-third of the candidates failed to secure a position in the match. However, the criteria used in the selection process often are subjective and studies have differed in terms of which criteria predict either objective measures or subjective ratings of resident performance by faculty. Do preresidency selection factors serve as predictors of success in residency? Specifically, we asked which preresidency selection factors are associated or correlated with (1) objective measures of resident knowledge and performance; and (2) subjective ratings by faculty. Charts of 60 orthopaedic residents from our institution were reviewed. Preresidency selection criteria examined included United States Medical Licensing Examination (USMLE) Step 1 and Step 2 scores, Medical College Admission Test (MCAT) scores, number of clinical clerkship honors, number of letters of recommendation, number of away rotations, Alpha Omega Alpha (AOA) honor medical society membership, fourth-year subinternship at our institution, and number of publications. Resident performance was assessed using objective measures including American Board of Orthopaedic Surgery (ABOS) Part I scores and Orthopaedics In-Training Exam (OITE) scores and subjective ratings by faculty including global evaluation scores and faculty rankings of residents. We tested associations between preresidency criteria and the subsequent objective and subjective metrics using linear correlation analysis and Mann-Whitney tests when appropriate. Objective measures of resident performance namely, ABOS Part I scores, had a moderate linear correlation with the USMLE Step 2 scores (r = 0.55, p communication skills" subsection of the global evaluations. We found that USMLE Step 2, number of honors in medical school clerkships, and AOA membership demonstrated the strongest correlations with resident performance. Our

  14. Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2017-01-01

    Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure presents computing conditions in which contention for resources among high-priority data analysis happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system’s state itself caused to focus on design of the built-in situational awareness analytic tools.

  15. Significant Returns in Engagement and Performance with a Free Teaching App

    Science.gov (United States)

    Green, Alan

    2016-01-01

    Pedagogical research shows that teaching methods other than traditional lectures may result in better outcomes. However, lecture remains the dominant method in economics, likely due to high implementation costs of methods shown to be effective in the literature. In this article, the author shows significant benefits of using a teaching app for…

  16. The Proposal of Key Performance Indicators in Facility Management and Determination the Weights of Significance

    Science.gov (United States)

    Rimbalová, Jarmila; Vilčeková, Silvia

    2013-11-01

    The practice of facilities management is rapidly evolving with the increasing interest in the discourse of sustainable development. The industry and its market are forecasted to develop to include non-core functions, activities traditionally not associated with this profession, but which are increasingly being addressed by facilities managers. The scale of growth in the built environment and the consequential growth of the facility management sector is anticipated to be enormous. Key Performance Indicators (KPI) are measure that provides essential information about performance of facility services delivery. In selecting KPI, it is critical to limit them to those factors that are essential to the organization reaching its goals. It is also important to keep the number of KPI small just to keep everyone's attention focused on achieving the same KPIs. This paper deals with the determination of weights of KPI of FM in terms of the design and use of sustainable buildings.

  17. Predicting performance at medical school: can we identify at-risk students?

    Directory of Open Access Journals (Sweden)

    Shaban S

    2011-05-01

    Full Text Available Sami Shaban, Michelle McLeanDepartment of Medical Education, Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab EmiratesBackground: The purpose of this study was to examine the predictive potential of multiple indicators (eg, preadmission scores, unit, module and clerkship grades, course and examination scores on academic performance at medical school, with a view to identifying students at risk.Methods: An analysis was undertaken of medical student grades in a 6-year medical school program at the Faculty of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates, over the past 14 years.Results: While high school scores were significantly (P < 0.001 correlated with the final integrated examination, predictability was only 6.8%. Scores for the United Arab Emirates university placement assessment (Common Educational Proficiency Assessment were only slightly more promising as predictors with 14.9% predictability for the final integrated examination. Each unit or module in the first four years was highly correlated with the next unit or module, with 25%–60% predictability. Course examination scores (end of years 2, 4, and 6 were significantly correlated (P < 0.001 with the average scores in that 2-year period (59.3%, 64.8%, and 55.8% predictability, respectively. Final integrated examination scores were significantly correlated (P < 0.001 with National Board of Medical Examiners scores (35% predictability. Multivariate linear regression identified key grades with the greatest predictability of the final integrated examination score at three stages in the program.Conclusion: This study has demonstrated that it may be possible to identify “at-risk” students relatively early in their studies through continuous data archiving and regular analysis. The data analysis techniques used in this study are not unique to this institution.Keywords: at-risk students, grade

  18. Validation of three noninvasive laboratory variables to predict significant fibrosis and cirrhosis in patients with chronic hepatitis C in Saudi Arabia

    International Nuclear Information System (INIS)

    Ado, Ayman A.; Al-Swat, Khalid; Azzam, N.; Al-Faleh, Faleh; Ahmed, S.

    2007-01-01

    We tested the clinical utility of the platelet count, aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio, and the AST to platelet ratio index (APRI) score in predicting the presence or absence of advanced fibrosis and cirrhosis in patients with chronic hepatitis C in Saudi Arabia. Liver biopsy procedures performed on chronic hepatitis C patients in our gastroenterology unit at King Khalid University Hospital were traced form records between 1998 to 2003. The hospital computer database was then accessed and detailed laboratory parameters obtained. By plotting receiver operating characteristic curves (ROC), three selected models (platelet count, AST/ALT ratio and the APRI score) were compared in terms of the best variable to predict significant fibrosis. Two hundred and forty-six patients with hepatitis C were included in this analysis. Overall, 26% of patients had advanced fibrosis. When comparing the three above mentioned prediction models, APRI score was the one associated with the highest area under the curve (AUC) = 0.812 (95%Cl, 0.756-0.868) on the ROC curves, compared to the platelet count and AST/ALT ratio, which yielded an AUC of 0.783 (0.711-0.855) and 0.716 (0.642-0.789), respectively. The APRI score seemed to be the best predictive variable for the presence or absence of advanced fibrosis in Saudi hepatitis C patients. (author)

  19. Identifying significant uncertainties in thermally dependent processes for repository performance analysis

    International Nuclear Information System (INIS)

    Gansemer, J.D.; Lamont, A.

    1994-01-01

    In order to study the performance of the potential Yucca Mountain Nuclear Waste Repository, scientific investigations are being conducted to reduce the uncertainty about process models and system parameters. This paper is intended to demonstrate a method for determining a strategy for the cost effective management of these investigations. It is not meant to be a complete study of all processes and interactions, but does outline a method which can be applied to more in-depth investigations

  20. Predictive validity of the comprehensive basic science examination mean score for assessment of medical students' performance

    Directory of Open Access Journals (Sweden)

    Firouz Behboudi

    2002-04-01

    Full Text Available Background Medical education curriculum improvements can be achieved bye valuating students performance. Medical students have to pass two undergraduate comprehensive examinations, basic science and preinternship, in Iran. Purpose To measure validity of the students' mean score in comprehensive basic science exam (CBSE for predicting their performance in later curriculum phases. Methods This descriptive cross-sectional study was conducted on 95 (38 women and 55 men Guilan medical university students. Their admission to the university was 81% by regional quota and 12% by shaheed and other organizations' share. They first enrolled in 1994 and were able to pass CBS£ at first try. Data on gender, regional quota, and average grades of CBS£, PC, and CPIE were collected by a questionnaire. The calculations were done by SPSS package. Results The correlation coefficient between CBS£ and CPIE mean scores (0.65 was higher than correlation coefficient between CBS£ and PC mean scores (0.49. The predictive validity of CBS£ average grade was significant for students' performance in CPIE; however, the predictive validity of CBSE mean scores for students I pe1jormance in PC was lower. Conclusion he students' mean score in CBSE can be a good denominator for their further admission. We recommend further research to assess the predictive validity for each one of the basic courses. Keywords predictive validity, comprehensive basic exam

  1. Combined use of serum MCP-1/IL-10 ratio and uterine artery Doppler index significantly improves the prediction of preeclampsia.

    Science.gov (United States)

    Cui, Shihong; Gao, Yanan; Zhang, Linlin; Wang, Yuan; Zhang, Lindong; Liu, Pingping; Liu, Ling; Chen, Juan

    2017-10-01

    Monocyte chemotactic protein-1 (MCP-1, or CCL2) is a member of the chemokine subfamily involved in recruitment of monocytes in inflammatory tissues. IL-10 is a key regulator for maintaining the balance of anti-inflammatory and pro-inflammatory milieu at the feto-maternal interface. Doppler examination has been routinely performed for the monitoring and management of preeclampsia patients. This study evaluates the efficiency of these factors alone, or in combination, for the predication of preeclampsia. The serum levels of MCP-1 and IL-10 in 78 preeclampsia patients and 143 age-matched normal controls were measured. The Doppler ultrasonography was performed and Artery Pulsatility Index (PI) and Resistance Index (RI) were calculated for the same subjects. It was found that while the second-trimester serum MCP-1, IL-10, MCP-1/IL-10 ratio, PI, and RI showed some power in predicting preeclampsia, the combination of MCP-1/IL-10 and PI and RI accomplishes the highest efficiency, achieving an AUC of 0.973 (95% CI, 0.000-1.000, Ppreeclampsia. Future studies using a larger sample can be conducted to construct an algorithm capable of quantitative assessment on the risk of preeclampsia. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. In surgeons performing cardiothoracic surgery is sleep deprivation significant in its impact on morbidity or mortality?

    Science.gov (United States)

    Asfour, Leila; Asfour, Victoria; McCormack, David; Attia, Rizwan

    2014-09-01

    A best evidence topic in cardiac surgery was written according to a structured protocol. The question addressed was: is there a difference in cardiothoracic surgery outcomes in terms of morbidity or mortality of patients operated on by a sleep-deprived surgeon compared with those operated by a non-sleep-deprived surgeon? Reported search criteria yielded 77 papers, of which 15 were deemed to represent the best evidence on the topic. Three studies directly related to cardiothoracic surgery and 12 studies related to non-cardiothoracic surgery. Recommendations are based on 18 121 cardiothoracic patients and 214 666 non-cardiothoracic surgical patients. Different definitions of sleep deprivation were used in the studies, either reviewing surgeon's sleeping hours or out-of-hours operating. Surgical outcomes reviewed included: mortality rate, neurological, renal, pulmonary, infectious complications, length of stay, length of intensive care stay, cardiopulmonary bypass times and aortic-cross-clamp times. There were no significant differences in mortality or intraoperative complications in the groups of patients operated on by sleep-deprived versus non-sleep-deprived surgeons in cardiothoracic studies. One study showed a significant increase in the rate of septicaemia in patients operated on by severely sleep-deprived surgeons (3.6%) compared with the moderately sleep-deprived (0.9%) and non-sleep-deprived groups (0.8%) (P = 0.03). In the non-cardiothoracic studies, 7 of the 12 studies demonstrated statistically significant higher reoperation rate in trauma cases (P sleep deprivation in cardiothoracic surgeons on morbidity or mortality. However, overall the non-cardiothoracic studies have demonstrated that operative time and sleep deprivation can have a significant impact on overall morbidity and mortality. It is likely that other confounding factors concomitantly affect outcomes in out-of-hours surgery. © The Author 2014. Published by Oxford University Press on behalf of

  3. Online physician ratings fail to predict actual performance on measures of quality, value, and peer review.

    Science.gov (United States)

    Daskivich, Timothy J; Houman, Justin; Fuller, Garth; Black, Jeanne T; Kim, Hyung L; Spiegel, Brennan

    2018-04-01

    Patients use online consumer ratings to identify high-performing physicians, but it is unclear if ratings are valid measures of clinical performance. We sought to determine whether online ratings of specialist physicians from 5 platforms predict quality of care, value of care, and peer-assessed physician performance. We conducted an observational study of 78 physicians representing 8 medical and surgical specialties. We assessed the association of consumer ratings with specialty-specific performance scores (metrics including adherence to Choosing Wisely measures, 30-day readmissions, length of stay, and adjusted cost of care), primary care physician peer-review scores, and administrator peer-review scores. Across ratings platforms, multivariable models showed no significant association between mean consumer ratings and specialty-specific performance scores (β-coefficient range, -0.04, 0.04), primary care physician scores (β-coefficient range, -0.01, 0.3), and administrator scores (β-coefficient range, -0.2, 0.1). There was no association between ratings and score subdomains addressing quality or value-based care. Among physicians in the lowest quartile of specialty-specific performance scores, only 5%-32% had consumer ratings in the lowest quartile across platforms. Ratings were consistent across platforms; a physician's score on one platform significantly predicted his/her score on another in 5 of 10 comparisons. Online ratings of specialist physicians do not predict objective measures of quality of care or peer assessment of clinical performance. Scores are consistent across platforms, suggesting that they jointly measure a latent construct that is unrelated to performance. Online consumer ratings should not be used in isolation to select physicians, given their poor association with clinical performance.

  4. Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

    Science.gov (United States)

    Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J.; Dong, Bing; Huang, Yufei

    2018-01-01

    Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R2 (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures. PMID:29690601

  5. Burst muscle performance predicts the speed, acceleration, and turning performance of Anna’s hummingbirds

    Science.gov (United States)

    Segre, Paolo S; Dakin, Roslyn; Zordan, Victor B; Dickinson, Michael H; Straw, Andrew D; Altshuler, Douglas L

    2015-01-01

    Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability. DOI: http://dx.doi.org/10.7554/eLife.11159.001 PMID:26583753

  6. Postexercise Glycogen Recovery and Exercise Performance is Not Significantly Different Between Fast Food and Sport Supplements.

    Science.gov (United States)

    Cramer, Michael J; Dumke, Charles L; Hailes, Walter S; Cuddy, John S; Ruby, Brent C

    2015-10-01

    A variety of dietary choices are marketed to enhance glycogen recovery after physical activity. Past research informs recommendations regarding the timing, dose, and nutrient compositions to facilitate glycogen recovery. This study examined the effects of isoenergetic sport supplements (SS) vs. fast food (FF) on glycogen recovery and exercise performance. Eleven males completed two experimental trials in a randomized, counterbalanced order. Each trial included a 90-min glycogen depletion ride followed by a 4-hr recovery period. Absolute amounts of macronutrients (1.54 ± 0.27 g·kg-1 carbohydrate, 0.24 ± 0.04 g·kg fat-1, and 0.18 ±0.03g·kg protein-1) as either SS or FF were provided at 0 and 2 hr. Muscle biopsies were collected from the vastus lateralis at 0 and 4 hr post exercise. Blood samples were analyzed at 0, 30, 60, 120, 150, 180, and 240 min post exercise for insulin and glucose, with blood lipids analyzed at 0 and 240 min. A 20k time-trial (TT) was completed following the final muscle biopsy. There were no differences in the blood glucose and insulin responses. Similarly, rates of glycogen recovery were not different across the diets (6.9 ± 1.7 and 7.9 ± 2.4 mmol·kg wet weight- 1·hr-1 for SS and FF, respectively). There was also no difference across the diets for TT performance (34.1 ± 1.8 and 34.3 ± 1.7 min for SS and FF, respectively. These data indicate that short-term food options to initiate glycogen resynthesis can include dietary options not typically marketed as sports nutrition products such as fast food menu items.

  7. Research of performance prediction to energy on hydraulic turbine

    International Nuclear Information System (INIS)

    Quan, H; Li, R N; Li, Q F; Han, W; Su, Q M

    2012-01-01

    Refer to the low specific speed Francis turbine blade design principle and double-suction pump structure. Then, design a horizontal double-channel hydraulic turbine Francis. Through adding different guide vane airfoil and and no guide vane airfoil on the hydraulic conductivity components to predict hydraulic turbine energy and using Fluent software to numerical simulation that the operating conditions and point. The results show that the blade pressure surface and suction surface pressure is low when the hydraulic turbine installation is added standard positive curvature of the guide vane and modified positive curvature of guide vane. Therefore, the efficiency of energy recovery is low. However, the pressure of negative curvature guide vane and symmetric guide vane added on hydraulic turbine installations is larger than that of the former ones, and it is conducive to working of runner. With the decreasing of guide vane opening, increasing of inlet angle, flow state gets significantly worse. Then, others obvious phenomena are that the reflux and horizontal flow appeared in blade pressure surface. At the same time, the vortex was formed in Leaf Road, leading to the loss of energy. Through analyzing the distribution of pressure, velocity, flow lines of over-current flow in the the back hydraulic conductivity components in above programs we can known that the hydraulic turbine installation added guide vane is more reasonable than without guide vanes, it is conducive to improve efficiency of energy conversion.

  8. Authoring experience: the significance and performance of storytelling in Socratic dialogue with rehabilitating cancer patients.

    Science.gov (United States)

    Knox, Jeanette Bresson Ladegaard; Svendsen, Mette Nordahl

    2015-08-01

    This article examines the storytelling aspect in philosophizing with rehabilitating cancer patients in small Socratic dialogue groups (SDG). Recounting an experience to illustrate a philosophical question chosen by the participants is the traditional point of departure for the dialogical exchange. However, narrating is much more than a beginning point or the skeletal framework of events and it deserves more scholarly attention than hitherto given. Storytelling pervades the whole Socratic process and impacts the conceptual analysis in a SDG. In this article we show how the narrative aspect became a rich resource for the compassionate bond between participants and how their stories cultivated the abstract reflection in the group. In addition, the aim of the article is to reveal the different layers in the performance of storytelling, or of authoring experience. By picking, poking and dissecting an experience through a collaborative effort, most participants had their initial experience existentially refined and the chosen concept of which the experience served as an illustration transformed into a moral compass to be used in self-orientation post cancer.

  9. Significant Performance Enhancement in Asymmetric Supercapacitors based on Metal Oxides, Carbon nanotubes and Neutral Aqueous Electrolyte

    Science.gov (United States)

    Singh, Arvinder; Chandra, Amreesh

    2015-10-01

    Amongst the materials being investigated for supercapacitor electrodes, carbon based materials are most investigated. However, pure carbon materials suffer from inherent physical processes which limit the maximum specific energy and power that can be achieved in an energy storage device. Therefore, use of carbon-based composites with suitable nano-materials is attaining prominence. The synergistic effect between the pseudocapacitive nanomaterials (high specific energy) and carbon (high specific power) is expected to deliver the desired improvements. We report the fabrication of high capacitance asymmetric supercapacitor based on electrodes of composites of SnO2 and V2O5 with multiwall carbon nanotubes and neutral 0.5 M Li2SO4 aqueous electrolyte. The advantages of the fabricated asymmetric supercapacitors are compared with the results published in the literature. The widened operating voltage window is due to the higher over-potential of electrolyte decomposition and a large difference in the work functions of the used metal oxides. The charge balanced device returns the specific capacitance of ~198 F g-1 with corresponding specific energy of ~89 Wh kg-1 at 1 A g-1. The proposed composite systems have shown great potential in fabricating high performance supercapacitors.

  10. Integrated genomic and immunophenotypic classification of pancreatic cancer reveals three distinct subtypes with prognostic/predictive significance.

    Science.gov (United States)

    Wartenberg, Martin; Cibin, Silvia; Zlobec, Inti; Vassella, Erik; Eppenberger-Castori, Serenella M M; Terracciano, Luigi; Eichmann, Micha; Worni, Mathias; Gloor, Beat; Perren, Aurel; Karamitopoulou, Eva

    2018-04-16

    Current clinical classification of pancreatic ductal adenocarcinoma (PDAC) is unable to predict prognosis or response to chemo- or immunotherapy and does not take into account the host reaction to PDAC-cells. Our aim is to classify PDAC according to host- and tumor-related factors into clinically/biologically relevant subtypes by integrating molecular and microenvironmental findings. A well-characterized PDAC-cohort (n=110) underwent next-generation sequencing with a hotspot cancer panel, while Next-generation Tissue-Microarrays were immunostained for CD3, CD4, CD8, CD20, PD-L1, p63, hyaluronan-mediated motility receptor (RHAMM) and DNA mismatch-repair proteins. Previous data on FOXP3 were integrated. Immune-cell counts and protein expression were correlated with tumor-derived driver mutations, clinicopathologic features (TNM 8. 2017), survival and epithelial-mesenchymal-transition (EMT)-like tumor budding.  Results: Three PDAC-subtypes were identified: the "immune-escape" (54%), poor in T- and B-cells and enriched in FOXP3+Tregs, with high-grade budding, frequent CDKN2A- , SMAD4- and PIK3CA-mutations and poor outcome; the "immune-rich" (35%), rich in T- and B-cells and poorer in FOXP3+Tregs, with infrequent budding, lower CDKN2A- and PIK3CA-mutation rate and better outcome and a subpopulation with tertiary lymphoid tissue (TLT), mutations in DNA damage response genes (STK11, ATM) and the best outcome; and the "immune-exhausted" (11%) with immunogenic microenvironment and two subpopulations: one with PD-L1-expression and high PIK3CA-mutation rate and a microsatellite-unstable subpopulation with high prevalence of JAK3-mutations. The combination of low budding, low stromal FOXP3-counts, presence of TLTs and absence of CDKN2A-mutations confers significant survival advantage in PDAC-patients. Immune host responses correlate with tumor characteristics leading to morphologically recognizable PDAC-subtypes with prognostic/predictive significance. Copyright ©2018

  11. Preoperative Metabolic Syndrome Is Predictive of Significant Gastric Cancer Mortality after Gastrectomy: The Fujian Prospective Investigation of Cancer (FIESTA Study

    Directory of Open Access Journals (Sweden)

    Dan Hu

    2017-02-01

    Full Text Available Metabolic syndrome (MetS has been shown to be associated with an increased risk of gastric cancer. However, the impact of MetS on gastric cancer mortality remains largely unknown. Here, we prospectively examined the prediction of preoperative MetS for gastric cancer mortality by analyzing a subset of data from the ongoing Fujian prospective investigation of cancer (FIESTA study. This study was conducted among 3012 patients with gastric cancer who received radical gastrectomy between 2000 and 2010. The latest follow-up was completed in 2015. Blood/tissue specimens, demographic and clinicopathologic characteristics were collected at baseline. During 15-year follow-up, 1331 of 3012 patients died of gastric cancer. The median survival time (MST of patients with MetS was 31.3 months, which was significantly shorter than that of MetS-free patients (157.1 months. The coexistence of MetS before surgery was associated with a 2.3-fold increased risk for gastric cancer mortality (P < 0.001. The multivariate-adjusted hazard ratios (HRs were increased with invasion depth T1/T2 (HR = 2.78, P < 0.001, regional lymph node metastasis N0 (HR = 2.65, P < 0.001, positive distant metastasis (HR = 2.53, P < 0.001, TNM stage I/II (HR = 3.00, P < 0.001, intestinal type (HR = 2.96, P < 0.001, negative tumor embolus (HR = 2.34, P < 0.001, and tumor size ≤4.5 cm (HR = 2.49, P < 0.001. Further survival tree analysis confirmed the top splitting role of TNM stage, followed by MetS or hyperglycemia with remarkable discrimination ability. In this large cohort study, preoperative MetS, especially hyperglycemia, was predictive of significant gastric cancer mortality in patients with radical gastrectomy, especially for early stage of gastric cancer.

  12. MHA admission criteria and program performance: do they predict career performance?

    Science.gov (United States)

    Porter, J; Galfano, V J

    1987-01-01

    The purpose of this study was to determine to what extent admission criteria predict graduate school and career performance. The study also analyzed which objective and subjective criteria served as the best predictors. MHA graduates of the University of Minnesota from 1974 to 1977 were surveyed to assess career performance. Student files served as the data base on admission criteria and program performance. Career performance was measured by four variables: total compensation, satisfaction, fiscal responsibility, and level of authority. High levels of MHA program performance were associated with women who had high undergraduate GPAs from highly selective undergraduate colleges, were undergraduate business majors, and participated in extracurricular activities. High levels of compensation were associated with relatively low undergraduate GPAs, high levels of participation in undergraduate extracurricular activities, and being single at admission to graduate school. Admission to MHA programs should be based upon both objective and subjective criteria. Emphasis should be placed upon the selection process for MHA students since admission criteria are shown to explain 30 percent of the variability in graduate program performance, and as much as 65 percent of the variance in level of position authority.

  13. Simplified Predictive Models for CO2 Sequestration Performance Assessment

    Science.gov (United States)

    Mishra, Srikanta; RaviGanesh, Priya; Schuetter, Jared; Mooney, Douglas; He, Jincong; Durlofsky, Louis

    2014-05-01

    simulations, the LHS-based meta-model yields a more robust predictive model, as verified by a k-fold cross-validation approach. In the third category (RMM), we use a reduced-order modeling procedure that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) for extrapolating system response at new control points from a limited number of trial runs ("snapshots"). We observe significant savings in computational time with very good accuracy from the POD-TPWL reduced order model - which could be important in the context of history matching, uncertainty quantification and optimization problems. The paper will present results from our ongoing investigations, and also discuss future research directions and likely outcomes. This work was supported by U.S. Department of Energy National Energy Technology Laboratory award DE-FE0009051 and Ohio Department of Development grant D-13-02.

  14. Predictive tool of energy performance of cold storage in agrifood industries: The Portuguese case study

    International Nuclear Information System (INIS)

    Nunes, José; Neves, Diogo; Gaspar, Pedro D.; Silva, Pedro D.; Andrade, Luís P.

    2014-01-01

    Highlights: • A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed. • The correlations used by the predictive tool result from the greatest number of data sets collected to date in Portugal. • Strong relationships between raw material, energy consumption and volume of cold stores were established. • Case studies were analyzed that demonstrate the applicability of the tool. • The tool results are useful in the decision-making process of practice measures for the improvement of energy efficiency. - Abstract: Food processing and conservation represent decisive factors for the sustainability of the planet given the significant growth of the world population in the last decades. Therefore, the cooling process during the manufacture and/or storage of food products has been subject of study and improvement in order to ensure the food supply with good quality and safety. A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed in order to contribute to the improvement of the energy efficiency of this industry. The predictive tool is based on a set of characteristic correlated parameters: amount of raw material annually processed, annual energy consumption and volume of cold rooms. Case studies of application of the predictive tool consider industries in the meat sector, specifically slaughterhouses. The results obtained help on the decision-making of practice measures for improvement of the energy efficiency in this industry

  15. AREVA - 2012 annual results: significant turnaround in performance one year after launching the Action 2016 plan

    International Nuclear Information System (INIS)

    Duperray, Julien; Berezowskyj, Katherine; Kempkes, Vincent; Rosso, Jerome; Thebault, Alexandre; Scorbiac, Marie de; Repaire, Philippine du

    2013-01-01

    One year after launching Areva's Action 2016 strategic plan, the first results are in. AREVA is ahead of schedule in executing its recovery plan. While pursuing its efforts in the management of a few difficult projects (such as OL3), Areva group was able to return to a virtuous performance cycle rooted in strong growth in nuclear order intake and good progress on its cost reduction program. Commercially, despite the difficult economic environment, AREVA was able to capitalize on its leadership in the installed base and on its long-term partnerships with strategic customers, beginning with EDF, with which AREVA renewed a confident and constructive working relationship. Areva has secured 80% of its objective of one billion euros of savings by the end of 2015 to improve its competitiveness. The group also continued efforts to optimize working capital requirement and control the capital expenditure trajectory. Together, these results enabled AREVA to exceed the objectives set for 2012 for two key indicators of its strategic plan: EBITDA and free operating cash flow. Nearly 60% of the 2.1 billion euros devoted to capital expenditures for future growth in 2012 were funded by operations, a quasi-doubled share compared to 2011. Areva's floor target for asset disposals was achieved one year ahead of schedule, also helping the Group to control its net debt, which remained below 4 billion euros. In 2013, Areva is continuing to implement the Action 2016 plan to keep its turnaround on track. In summary: - Backlog renewed over the year 2012 to euro 45.4 bn thanks to the increase in nuclear order intake; - Sales revenue growth: euro 9.342 bn (+5.3% vs. 2011), led by nuclear and renewables operations; - Very sharp upturn in EBITDA: euro 1.007 bn (+euro 586 m vs. 2011) - Very net improvement in free operating cash flow: -euro 854 m (+euro 512 m vs. 2011); - Back to positive reported operating income: euro 118 m (+euro 1.984 bn vs. 2011); - 2012-2013 floor target for asset disposals

  16. Predicting the outcomes of performance error indicators on accreditation status in the nuclear power industry

    International Nuclear Information System (INIS)

    Wilson, P.A.

    1986-01-01

    The null hypothesis for this study suggested that there was no significant difference in the types of performance error indicators between accredited and non-accredited programs on the following types of indicators: (1) number of significant event reports per unit, (2) number of forced outages per unit, (3) number of unplanned automatic scrams per unit, and (4) amount of equivalent availability per unit. A sample of 90 nuclear power plants was selected for this study. Data were summarized from two data bases maintained by the Institute of Nuclear Power Operations. Results of this study did not support the research hypothesis. There was no significant difference between the accredited and non-accredited programs on any of the four performance error indicators. The primary conclusions of this include the following: (1) The four selected performance error indicators cannot be used individually or collectively to predict accreditation status in the nuclear power industry. (2) Annual performance error indicator ratings cannot be used to determine the effects of performance-based training on plant performance. (3) The four selected performance error indicators cannot be used to measure the effect of operator job performance on plant effectiveness

  17. Predicting memory performance in normal ageing using different measures of hippocampal size

    International Nuclear Information System (INIS)

    Lye, T.C.; Creasey, H.; Kril, J.J.; Grayson, D.A.; Piguet, O.; Bennett, H.P.; Ridley, L.J.; Broe, G.A.

    2006-01-01

    A number of different methods have been employed to correct hippocampal volumes for individual variation in head size. Researchers have previously used qualitative visual inspection to gauge hippocampal atrophy. The purpose of this study was to determine the best measure(s) of hippocampal size for predicting memory functioning in 102 community-dwelling individuals over 80 years of age. Hippocampal size was estimated using magnetic resonance imaging (MRI) volumetry and qualitative visual assessment. Right and left hippocampal volumes were adjusted by three different estimates of head size: total intracranial volume (TICV), whole-brain volume including ventricles (WB+V) and a more refined measure of whole-brain volume with ventricles extracted (WB). We compared the relative efficacy of these three volumetric adjustment methods and visual ratings of hippocampal size in predicting memory performance using linear regression. All four measures of hippocampal size were significant predictors of memory performance. TICV-adjusted volumes performed most poorly in accounting for variance in memory scores. Hippocampal volumes adjusted by either measure of whole-brain volume performed equally well, although qualitative visual ratings of the hippocampus were at least as effective as the volumetric measures in predicting memory performance in community-dwelling individuals in the ninth or tenth decade of life. (orig.)

  18. Predicting neuropsychological test performance on the basis of temporal orientation.

    Science.gov (United States)

    Ryan, Joseph J; Glass, Laura A; Bartels, Jared M; Bergner, CariAnn M; Paolo, Anthony M

    2009-05-01

    Temporal orientation is often disrupted in the context of psychiatric or neurological disease; tests assessing this function are included in most mental status examinations. The present study examined the relationship between scores on the Temporal Orientation Scale (TOS) and performance on a battery of tests that assess memory, language, and cognitive functioning in a sample of patients with Alzheimer's disease (N = 55). Pearson-product moment correlations showed that, in all but two instances, the TOS was significantly correlated with each neuropsychological measure, p values < or = .05. Also, severely disoriented (i.e., TOS score < or = -8) patients were consistently 'impaired' on memory tests but not on tests of language and general cognitive functioning.

  19. Validation of DAB2IP methylation and its relative significance in predicting outcome in renal cell carcinoma

    Science.gov (United States)

    Zhao, Liang-Yun; Kapur, Payal; Wu, Kai-Jie; Wang, Bin; Yu, Yan-Hong; Liao, Bing; He, Da-Lin; Chen, Wei; Margulis, Vitaly; Hsieh, Jer-Tsong; Luo, Jun-Hang

    2016-01-01

    We have recently reported tumor suppressive role of DAB2IP in RCC development. In this study, We identified one CpG methylation biomarker (DAB2IP CpG1) located UTSS of DAB2IP that was associated with poor overall survival in a cohort of 318 ccRCC patients from the Cancer Genome Atlas (TCGA). We further validated the prognostic accuracy of DAB2IP CpG methylation by pyrosequencing quantitative methylation assay in 224 ccRCC patients from multiple Chinese centers (MCHC set), and 239 patients from University of Texas Southwestern Medical Center at Dallas (UTSW set) by using FFPE samples. DAB2IP CpG1 can predict the overall survival of patients in TCGA, MCHC, and UTSW sets independent of patient age, Fuhrman grade and TNM stage (all p<0.05). DAB2IP CpG1 successfully categorized patients into high-risk and low-risk groups with significant differences of clinical outcome in respective clinical subsets, regardless of age, sex, grade, stage, or race (HR: 1.63-7.83; all p<0.05). The detection of DAB2IP CpG1 methylation was minimally affected by ITH in ccRCC. DAB2IP mRNA expression was regulated by DNA methylation in vitro. DAB2IP CpG1 methylation is a practical and repeatable biomarker for ccRCC, which can provide prognostic value that complements the current staging system. PMID:27129174

  20. Predicting energy performance of a net-zero energy building: A statistical approach

    International Nuclear Information System (INIS)

    Kneifel, Joshua; Webb, David

    2016-01-01

    Highlights: • A regression model is applied to actual energy data from a net-zero energy building. • The model is validated through a rigorous statistical analysis. • Comparisons are made between model predictions and those of a physics-based model. • The model is a viable baseline for evaluating future models from the energy data. - Abstract: Performance-based building requirements have become more prevalent because it gives freedom in building design while still maintaining or exceeding the energy performance required by prescriptive-based requirements. In order to determine if building designs reach target energy efficiency improvements, it is necessary to estimate the energy performance of a building using predictive models and different weather conditions. Physics-based whole building energy simulation modeling is the most common approach. However, these physics-based models include underlying assumptions and require significant amounts of information in order to specify the input parameter values. An alternative approach to test the performance of a building is to develop a statistically derived predictive regression model using post-occupancy data that can accurately predict energy consumption and production based on a few common weather-based factors, thus requiring less information than simulation models. A regression model based on measured data should be able to predict energy performance of a building for a given day as long as the weather conditions are similar to those during the data collection time frame. This article uses data from the National Institute of Standards and Technology (NIST) Net-Zero Energy Residential Test Facility (NZERTF) to develop and validate a regression model to predict the energy performance of the NZERTF using two weather variables aggregated to the daily level, applies the model to estimate the energy performance of hypothetical NZERTFs located in different cities in the Mixed-Humid Climate Zone, and compares these

  1. Cognition and procedure representational requirements for predictive human performance models

    Science.gov (United States)

    Corker, K.

    1992-01-01

    Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods

  2. The Role of Family Functioning, Peer Attachment and Academic Performance in predicting of Happiness in Adolescent Girls

    Directory of Open Access Journals (Sweden)

    Maryam Salehzadeh

    2017-02-01

    Full Text Available The purpose of this research was to determine the role of family functioning (FF, academic performance (EP and peer attachment (PA in predicting of happiness adolescent girls. Therefore, 344 high school female students in Yazd were selected through multi-stage random sampling and were asked to complete the Oxford Happiness Questionnaire, Family Assessment Device (FAD, and Inventory of Parent and Peer Attachment. Students' grade point average was considered as the measure of academic performance.  The results of analysis of regression showed that all the subscales of family functioning and peers attachment and also academic performance have significant correlation with happiness yet only "the roles and relationships" of family performance and peers attachment could predict happiness. Attachment to peers was the strongest factor. However, academic performance did not have a significant role in prediction of student's happiness. In accordance with the findings of developmental psychology, peers and family are the two most important psychological constructs that have the most significant roles in predicting the happiness of adolescent girls. But academic performance did not have a significant role in predicting student's happiness, thereby it can challenge the social common belief in educational systems regarding the strong association between academic performance and well-being and happiness.

  3. Thermodynamic simulation model for predicting the performance of spark ignition engines using biogas as fuel

    International Nuclear Information System (INIS)

    Nunes de Faria, Mário M.; Vargas Machuca Bueno, Juan P.; Ayad, Sami M.M. Elmassalami; Belchior, Carlos R. Pereira

    2017-01-01

    Highlights: • A 0-D model for performance prediction of SI ICE fueled with biogas is proposed. • Relative difference between simulated and experimental values was under 5%. • Can be adapted for different biogas compositions and operating ranges. • Could be a valuable tool for predicting trends and guiding experimentation. • Is suitable for use with biogas supplies in developing regions. - Abstract: Biogas found its way from developing countries and is now an alternative to fossil fuels in internal combustion engines and with the advantage of lower greenhouse gas emissions. However, its use in gas engines requires engine modifications or adaptations that may be costly. This paper reports the results of experimental performance and emissions tests of an engine-generator unit fueled with biogas produced in a sewage plant in Brazil, operating under different loads, and with suitable engine modifications. These emissions and performance results were in agreement with the literature and it was confirmed that the penalties to engine performance were more significant than emission reduction in the operating range tested. Furthermore, a zero dimensional simulation model was employed to predict performance characteristics. Moreover, a differential thermodynamic equation system was solved, obtaining the pressure inside the cylinder as a function of the crank angle for different engine conditions. Mean effective pressure and indicated power were also obtained. The results of simulation and experimental tests of the engine in similar conditions were compared and the model validated. Although several simplifying assumptions were adopted and empirical correlations were used for Wiebe function, the model was adequate in predicting engine performance as the relative difference between simulated and experimental values was lower than 5%. The model can be adapted for use with different raw or enriched biogas compositions and could prove to be a valuable tool to guide

  4. Significance of cardiac sympathetic nervous system abnormality for predicting vascular events in patients with idiopathic paroxysmal atrial fibrillation

    International Nuclear Information System (INIS)

    Akutsu, Yasushi; Kaneko, Kyouichi; Kodama, Yusuke; Li, Hui-Ling; Kawamura, Mitsuharu; Asano, Taku; Hamazaki, Yuji; Tanno, Kaoru; Kobayashi, Youichi; Suyama, Jumpei; Shinozuka, Akira; Gokan, Takehiko

    2010-01-01

    Neuronal system activity plays an important role for the prognosis of patients with atrial fibrillation (AF). Using 123 I metaiodobenzylguanidine ( 123 I-MIBG) scintigraphy, we investigated whether a cardiac sympathetic nervous system (SNS) abnormality would be associated with an increased risk of vascular events in patients with paroxysmal AF. 123 I-MIBG scintigraphy was performed in 69 consecutive patients (67 ± 13 years, 62% men) with paroxysmal AF who did not have structural heart disease. SNS integrity was assessed from the heart to mediastinum (H/M) ratio on delayed imaging. Serum concentration of C-reactive protein (CRP) was measured before 123 I-MIBG study. During a mean of 4.5 ± 3.6 years follow-up, 19 patients had myocardial infarction, stroke or heart failure (range: 0.2-11.5 years). SNS abnormality (H/M ratio <2.7) and high CRP (≥0.3 mg/dl) were associated with the vascular events (58.3% in 14 of 24 patients with SNS abnormality vs 11.1% in 5 of 45 patients without SNS abnormality, p < 0.0001, 52.4% in 11 of 21 patients with high CRP vs 16.7% in 8 of 48 patients without high CRP, p < 0.0001). After adjustment for potential confounding variables such as age, left atrial dimension and left ventricular function, SNS abnormality was an independent predictor of vascular events with a hazard ratio of 4.1 [95% confidence interval (CI): 1.3-12.6, p = 0.014]. Further, SNS abnormality had an incremental and additive prognostic power in combination with high CRP with an adjusted hazard ratio of 4.1 (95% CI: 1.5-10.9, p = 0.006). SNS abnormality is predictive of vascular events in patients with idiopathic paroxysmal AF. (orig.)

  5. Significance of cardiac sympathetic nervous system abnormality for predicting vascular events in patients with idiopathic paroxysmal atrial fibrillation

    Energy Technology Data Exchange (ETDEWEB)

    Akutsu, Yasushi; Kaneko, Kyouichi; Kodama, Yusuke; Li, Hui-Ling; Kawamura, Mitsuharu; Asano, Taku; Hamazaki, Yuji; Tanno, Kaoru; Kobayashi, Youichi [Showa University School of Medicine, Division of Cardiology, Department of Medicine, Tokyo (Japan); Suyama, Jumpei; Shinozuka, Akira; Gokan, Takehiko [Showa University School of Medicine, Department of Radiology, Tokyo (Japan)

    2010-04-15

    Neuronal system activity plays an important role for the prognosis of patients with atrial fibrillation (AF). Using {sup 123}I metaiodobenzylguanidine ({sup 123}I-MIBG) scintigraphy, we investigated whether a cardiac sympathetic nervous system (SNS) abnormality would be associated with an increased risk of vascular events in patients with paroxysmal AF. {sup 123}I-MIBG scintigraphy was performed in 69 consecutive patients (67 {+-} 13 years, 62% men) with paroxysmal AF who did not have structural heart disease. SNS integrity was assessed from the heart to mediastinum (H/M) ratio on delayed imaging. Serum concentration of C-reactive protein (CRP) was measured before {sup 123}I-MIBG study. During a mean of 4.5 {+-} 3.6 years follow-up, 19 patients had myocardial infarction, stroke or heart failure (range: 0.2-11.5 years). SNS abnormality (H/M ratio <2.7) and high CRP ({>=}0.3 mg/dl) were associated with the vascular events (58.3% in 14 of 24 patients with SNS abnormality vs 11.1% in 5 of 45 patients without SNS abnormality, p < 0.0001, 52.4% in 11 of 21 patients with high CRP vs 16.7% in 8 of 48 patients without high CRP, p < 0.0001). After adjustment for potential confounding variables such as age, left atrial dimension and left ventricular function, SNS abnormality was an independent predictor of vascular events with a hazard ratio of 4.1 [95% confidence interval (CI): 1.3-12.6, p = 0.014]. Further, SNS abnormality had an incremental and additive prognostic power in combination with high CRP with an adjusted hazard ratio of 4.1 (95% CI: 1.5-10.9, p = 0.006). SNS abnormality is predictive of vascular events in patients with idiopathic paroxysmal AF. (orig.)

  6. Assessing Prediction Performance of Neoadjuvant Chemotherapy Response in Bladder Cancer

    OpenAIRE

    Cremer, Chris

    2016-01-01

    Neoadjuvant chemotherapy is a treatment routinely prescribed to patients diagnosed with muscle-invasive bladder cancer. Unfortunately, not all patients are responsive to this treatment and would greatly benefit from an accurate prediction of their expected response to chemotherapy. In this project, I attempt to develop a model that will predict response using tumour microarray data. I show that using my dataset, every method is insufficient at accurately classifying responders and non-respond...

  7. Retrospective lifetime dietary patterns predict cognitive performance in community-dwelling older Australians.

    Science.gov (United States)

    Hosking, Diane E; Nettelbeck, Ted; Wilson, Carlene; Danthiir, Vanessa

    2014-07-28

    Dietary intake is a modifiable exposure that may have an impact on cognitive outcomes in older age. The long-term aetiology of cognitive decline and dementia, however, suggests that the relevance of dietary intake extends across the lifetime. In the present study, we tested whether retrospective dietary patterns from the life periods of childhood, early adulthood, adulthood and middle age predicted cognitive performance in a cognitively healthy sample of 352 older Australian adults >65 years. Participants completed the Lifetime Diet Questionnaire and a battery of cognitive tests designed to comprehensively assess multiple cognitive domains. In separate regression models, lifetime dietary patterns were the predictors of cognitive factor scores representing ten constructs derived by confirmatory factor analysis of the cognitive test battery. All regression models were progressively adjusted for the potential confounders of current diet, age, sex, years of education, English as native language, smoking history, income level, apoE ɛ4 status, physical activity, other past dietary patterns and health-related variables. In the adjusted models, lifetime dietary patterns predicted cognitive performance in this sample of older adults. In models additionally adjusted for intake from the other life periods and mechanistic health-related variables, dietary patterns from the childhood period alone reached significance. Higher consumption of the 'coffee and high-sugar, high-fat extras' pattern predicted poorer performance on simple/choice reaction time, working memory, retrieval fluency, short-term memory and reasoning. The 'vegetable and non-processed' pattern negatively predicted simple/choice reaction time, and the 'traditional Australian' pattern positively predicted perceptual speed and retrieval fluency. Identifying early-life dietary antecedents of older-age cognitive performance contributes to formulating strategies for delaying or preventing cognitive decline.

  8. Do physiological measures predict selected CrossFit(®) benchmark performance?

    Science.gov (United States)

    Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

    2015-01-01

    CrossFit(®) is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit "Workouts of the Day" (WODs). Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs "Grace" (30 clean and jerks for time), "Fran" (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and "Cindy" (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the "CrossFit Total" (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=-0.88 and -0.65, respectively) and anaerobic threshold (r=-0.61 and -0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R (2)=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs.

  9. Triaging TIA/minor stroke patients using the ABCD2 score does not predict those with significant carotid disease.

    Science.gov (United States)

    Walker, J; Isherwood, J; Eveson, D; Naylor, A R

    2012-05-01

    'Rapid Access' TIA Clinics use the ABCD(2) score to triage patients as it is not possible to see everyone with a suspected TIA TIA/minor stroke or 'carotid territory' TIA/minor stroke. Between 1.10.2008 and 31.04.2011, 2452 patients were referred to the Leicester Rapid Access TIA Service. After Stroke Physician review, 1273 (52%) were thought to have suffered a minor stroke/TIA. Of these, both FD/ED referrer and Specialist Stroke Consultant ABCD(2) scores and carotid Duplex ultrasound studies were available for 843 (66%). The yield for identifying a ≥50% stenosis or carotid occlusion was 109/843 (12.9%) in patients with 'any territory' TIA/minor stroke and 101/740 (13.6%) in those with a clinical diagnosis of 'carotid territory' TIA/minor stroke. There was no association between ABCD(2) score and the likelihood of encountering significant carotid disease and analyses of the area under the receiver operating characteristic curve (AUC) for FD/ED referrer and stroke specialist ABCD(2) scores showed no prediction of carotid stenosis (FD/ED: AUC 0.50 (95%CI 0.44-0.55, p = 0.9), Specialist: AUC 0.51 (95%CI 0.45-0.57, p = 0.78). The ABCD(2) score was unable to identify TIA/minor stroke patients with a higher prevalence of clinically important ipsilateral carotid disease. Copyright © 2012 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

  10. Patient-specific metrics of invasiveness reveal significant prognostic benefit of resection in a predictable subset of gliomas.

    Directory of Open Access Journals (Sweden)

    Anne L Baldock

    Full Text Available Malignant gliomas are incurable, primary brain neoplasms noted for their potential to extensively invade brain parenchyma. Current methods of clinical imaging do not elucidate the full extent of brain invasion, making it difficult to predict which, if any, patients are likely to benefit from gross total resection. Our goal was to apply a mathematical modeling approach to estimate the overall tumor invasiveness on a patient-by-patient basis and determine whether gross total resection would improve survival in patients with relatively less invasive gliomas.In 243 patients presenting with contrast-enhancing gliomas, estimates of the relative invasiveness of each patient's tumor, in terms of the ratio of net proliferation rate of the glioma cells to their net dispersal rate, were derived by applying a patient-specific mathematical model to routine pretreatment MR imaging. The effect of varying degrees of extent of resection on overall survival was assessed for cohorts of patients grouped by tumor invasiveness.We demonstrate that patients with more diffuse tumors showed no survival benefit (P = 0.532 from gross total resection over subtotal/biopsy, while those with nodular (less diffuse tumors showed a significant benefit (P = 0.00142 with a striking median survival benefit of over eight months compared to sub-totally resected tumors in the same cohort (an 80% improvement in survival time for GTR only seen for nodular tumors.These results suggest that our patient-specific, model-based estimates of tumor invasiveness have clinical utility in surgical decision making. Quantification of relative invasiveness assessed from routinely obtained pre-operative imaging provides a practical predictor of the benefit of gross total resection.

  11. Mid-Treatment Sleep Duration Predicts Clinically Significant Knee Osteoarthritis Pain reduction at 6 months: Effects From a Behavioral Sleep Medicine Clinical Trial.

    Science.gov (United States)

    Salwen, Jessica K; Smith, Michael T; Finan, Patrick H

    2017-02-01

    To determine the relative influence of sleep continuity (sleep efficiency, sleep onset latency, total sleep time [TST], and wake after sleep onset) on clinical pain outcomes within a trial of cognitive behavioral therapy for insomnia (CBT-I) for patients with comorbid knee osteoarthritis and insomnia. Secondary analyses were performed on data from 74 patients with comorbid insomnia and knee osteoarthritis who completed a randomized clinical trial of 8-session multicomponent CBT-I versus an active behavioral desensitization control condition (BD), including a 6-month follow-up assessment. Data used herein include daily diaries of sleep parameters, actigraphy data, and self-report questionnaires administered at specific time points. Patients who reported at least 30% improvement in self-reported pain from baseline to 6-month follow-up were considered responders (N = 31). Pain responders and nonresponders did not differ significantly at baseline across any sleep continuity measures. At mid-treatment, only TST predicted pain response via t tests and logistic regression, whereas other measures of sleep continuity were nonsignificant. Recursive partitioning analyses identified a minimum cut-point of 382 min of TST achieved at mid-treatment in order to best predict pain improvements 6-month posttreatment. Actigraphy results followed the same pattern as daily diary-based results. Clinically significant pain reductions in response to both CBT-I and BD were optimally predicted by achieving approximately 6.5 hr sleep duration by mid-treatment. Thus, tailoring interventions to increase TST early in treatment may be an effective strategy to promote long-term pain reductions. More comprehensive research on components of behavioral sleep medicine treatments that contribute to pain response is warranted. © Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

  12. Cognitive function predicts listening effort performance during complex tasks in normally aging adults

    Directory of Open Access Journals (Sweden)

    Jennine Harvey

    2017-01-01

    Full Text Available Purpose: This study examines whether cognitive function, as measured by the subtests of the Woodcock–Johnson III (WCJ-III assessment, predicts listening-effort performance during dual tasks across the adults of varying ages. Materials and Methods: Participants were divided into two groups. Group 1 consisted of 14 listeners (number of females = 11 who were 41–61 years old [mean = 53.18; standard deviation (SD = 5.97]. Group 2 consisted of 15 listeners (number of females = 9 who were 63–81 years old (mean = 72.07; SD = 5.11. Participants were administered the WCJ-III Memory for Words, Auditory Working Memory, Visual Matching, and Decision Speed subtests. All participants were tested in each of the following three dual-task experimental conditions, which were varying in complexity: (1 auditory word recognition + visual processing, (2 auditory working memory (word + visual processing, and (3 auditory working memory (sentence + visual processing in noise. Results: A repeated measures analysis of variance revealed that task complexity significantly affected the performance measures of auditory accuracy, visual accuracy, and processing speed. Linear regression revealed that the cognitive subtests of the WCJ-III test significantly predicted performance across dependent variable measures. Conclusion: Listening effort is significantly affected by task complexity, regardless of age. Performance on the WCJ-III test may predict listening effort in adults and may assist speech-language pathologist (SLPs to understand challenges faced by participants when subjected to noise.

  13. Texas cracking performance prediction, simulation, and binder recommendation.

    Science.gov (United States)

    2014-10-01

    Recent studies show some mixes with softer binders used outside of Texas (e.g., Minnesotas Cold Weather Road Research Facility mixes) have both good rutting and cracking performance. However, the current binder performance grading (PG) system fail...

  14. Predicting Performance with Contextualized Inventories, No Frame-of-reference Effect?

    NARCIS (Netherlands)

    Holtrop, D.J.; Born, M.P.; de Vries, R.E.

    2014-01-01

    A recent meta-analysis showed that contextualized personality inventories have incremental predictive validity over generic personality inventories when predicting job performance. This study aimed to investigate the differences between two types of contextualization of items: Adding an 'at work'

  15. Architectural Development and Performance Analysis of a Primary Data Cache with Read Miss Address Prediction Capability

    National Research Council Canada - National Science Library

    Christensen, Kathryn

    1998-01-01

    .... The Predictive Read Cache (PRC) further improves the overall memory hierarchy performance by tracking the data read miss patterns of memory accesses, developing a prediction for the next access and prefetching the data into the faster cache memory...

  16. Holland Type as a Moderator of Personality-Performance Predictions.

    Science.gov (United States)

    Fritzsche, Barbara A.; McIntire, Sandra A.; Yost, Amy Powell

    2002-01-01

    Data from 559 undergraduates provided modest evidence that Holland's taxonomy of work environments moderated the relationship between personality and performance. The traits of agreeableness and conscientiousness were better predictors of performance in certain environments. The important relationship between personality and performance may be…

  17. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Directory of Open Access Journals (Sweden)

    Magdalena Ewa Król

    Full Text Available Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  18. The trickle-down effect of predictability: Secondary task performance benefits from predictability in the primary task.

    Science.gov (United States)

    Król, Magdalena Ewa; Król, Michał

    2017-01-01

    Predictions optimize processing by reducing attentional resources allocation to expected or predictable sensory data. Our study demonstrates that these saved processing resources can be then used on concurrent stimuli, and in consequence improve their processing and encoding. We illustrate this "trickle-down" effect with a dual task, where the primary task varied in terms of predictability. The primary task involved detection of a pre-specified symbol that appeared at some point of a short video of a dot moving along a random, semi-predictable or predictable trajectory. The concurrent secondary task involved memorization of photographs representing either emotionally neutral or non-neutral (social or threatening) content. Performance in the secondary task was measured by a memory test. We found that participants allocated more attention to unpredictable (random and semi-predictable) stimuli than to predictable stimuli. Additionally, when the stimuli in the primary task were more predictable, participants performed better in the secondary task, as evidenced by higher sensitivity in the memory test. Finally, social or threatening stimuli were allocated more "looking time" and a larger number of saccades than neutral stimuli. This effect was stronger for the threatening stimuli than social stimuli. Thus, predictability of environmental input is used in optimizing the allocation of attentional resources, which trickles-down and benefits the processing of concurrent stimuli.

  19. Clinical significance of the neutrophil-lymphocyte ratio as an early predictive marker for adverse outcomes in patients with acute pancreatitis.

    Science.gov (United States)

    Jeon, Tae Joo; Park, Ji Young

    2017-06-07

    To investigated the prognostic value of the neutrophil-lymphocyte ratio (NLR) in patients with acute pancreatitis and determined an optimal cut-off value for the prediction of adverse outcomes in these patients. We retrospectively analyzed 490 patients with acute pancreatitis diagnosed between March 2007 and December 2012. NLRs were calculated at admission and 24, 48, and 72 h after admission. Patients were grouped according to acute pancreatitis severity and organ failure occurrence, and a comparative analysis was performed to compare the NLR between groups. Among the 490 patients, 70 had severe acute pancreatitis with 31 experiencing organ failure. The severe acute pancreatitis group had a significantly higher NLR than the mild acute pancreatitis group on all 4 d (median, 6.14, 6.71, 5.70, and 4.00 vs 4.74, 4.47, 3.20, and 3.30, respectively, P pancreatitis. Elevated baseline NLR correlates with severe acute pancreatitis and organ failure.

  20. Flow Simulation and Performance Prediction of Centrifugal Pumps ...

    African Journals Online (AJOL)

    With the aid of computational fluid dynamics, the complex internal flows in water pump impellers can be well predicted, thus facilitating the product development process of pumps. In this paper a commercial CFD code was used to solve the governing equations of the flow field. A 2-D simulation of turbulent fluid flow is ...

  1. Next-Term Student Performance Prediction: A Recommender Systems Approach

    Science.gov (United States)

    Sweeney, Mack; Rangwala, Huzefa; Lester, Jaime; Johri, Aditya

    2016-01-01

    An enduring issue in higher education is student retention to successful graduation. National statistics indicate that most higher education institutions have four-year degree completion rates around 50%, or just half of their student populations. While there are prediction models which illuminate what factors assist with college student success,…

  2. Predicting Student Performance in a Collaborative Learning Environment

    Science.gov (United States)

    Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

    2015-01-01

    Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…

  3. Selection procedures in sports: Improving predictions of athletes’ future performance

    NARCIS (Netherlands)

    den Hartigh, Jan Rudolf; Niessen, Anna; Frencken, Wouter; Meijer, Rob R.

    The selection of athletes has been a central topic in sports sciences for decades. Yet, little consideration has been given to the theoretical underpinnings and predictive validity of the procedures. In this paper, we evaluate current selection procedures in sports given what we know from the

  4. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available discusses some of the short comings of this law in the current age. We propose a theoretical model for predicting the behavior of a distributed algorithm given the network restrictions of the cluster used. The paper focuses on the impact of latency...

  5. 10 km running performance predicted by a multiple linear regression model with allometrically adjusted variables.

    Science.gov (United States)

    Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O

    2016-06-01

    The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.

  6. Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

    Directory of Open Access Journals (Sweden)

    Daan Nieboer

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

  7. Perceived Medical School stress of undergraduate medical students predicts academic performance: an observational study.

    Science.gov (United States)

    Kötter, Thomas; Wagner, Josefin; Brüheim, Linda; Voltmer, Edgar

    2017-12-16

    Medical students are exposed to high amounts of stress. Stress and poor academic performance can become part of a vicious circle. In order to counteract this circularity, it seems important to better understand the relationship between stress and performance during medical education. The most widespread stress questionnaire designed for use in Medical School is the "Perceived Medical School Stress Instrument" (PMSS). It addresses a wide range of stressors, including workload, competition, social isolation and financial worries. Our aim was to examine the relation between the perceived Medical School stress of undergraduate medical students and academic performance. We measured Medical School stress using the PMSS at two different time points (at the end of freshman year and at the end of sophomore year) and matched stress scores together with age and gender to the first medical examination (M1) grade of the students (n = 456). PMSS scores from 2 and 14 months before M1 proved to be significant predictors for medical students' M1 grade. Age and gender also predict academic performance, making older female students with high stress scores a potential risk group for entering the vicious circle of stress and poor academic performance. PMSS sum scores 2 and 14 months before the M1 exam seem to have an independent predictive validity for medical students' M1 grade. More research is needed to identify potential confounders.

  8. Trait impulsivity predicts D-KEFS tower test performance in university students.

    Science.gov (United States)

    Lyvers, Michael; Basch, Vanessa; Duff, Helen; Edwards, Mark S

    2015-01-01

    The present study examined a widely used self-report index of trait impulsiveness in relation to performance on a well-known neuropsychological executive function test in 70 university undergraduate students (50 women, 20 men) aged 18 to 24 years old. Participants completed the Barratt Impulsiveness Scale (BIS-11) and the Frontal Systems Behavior Scale (FrSBe), after which they performed the Tower Test of the Delis-Kaplan Executive Function System. Hierarchical linear regression showed that after controlling for gender, current alcohol consumption, age at onset of weekly alcohol use, and FrSBe scores, BIS-11 significantly predicted Tower Test Achievement scores, β = -.44, p impulsiveness is associated with poorer executive cognitive performance even in a sample likely to be characterized by relatively high general cognitive functioning (i.e., university students). The results also support the role of inhibition as a key aspect of executive task performance. Elevated scores on the BIS-11 and FrSBe are known to be linked to risky drinking in young adults as confirmed in this sample; however, only BIS-11 predicted Tower Test performance.

  9. Dataset size and composition impact the reliability of performance benchmarks for peptide-MHC binding predictions

    DEFF Research Database (Denmark)

    Kim, Yohan; Sidney, John; Buus, Søren

    2014-01-01

    Background: It is important to accurately determine the performance of peptide: MHC binding predictions, as this enables users to compare and choose between different prediction methods and provides estimates of the expected error rate. Two common approaches to determine prediction performance...... are cross-validation, in which all available data are iteratively split into training and testing data, and the use of blind sets generated separately from the data used to construct the predictive method. In the present study, we have compared cross-validated prediction performances generated on our last...

  10. Predictive value of age of walking for later motor performance in children with mental retardation.

    Science.gov (United States)

    Kokubun, M; Haishi, K; Okuzumi, H; Hosobuchi, T; Koike, T

    1996-12-01

    The purpose of the present study was to clarify the predictive value of age of walking for later motor performance in children with mental retardation. While paying due attention to other factors, our investigation focused on the relationship between a subject's age of walking, and his or her subsequent beam-walking performance. The subjects were 85 children with mental retardation with an average age of 13 years and 3 months. Beam-walking performance was measured by a procedure developed by the authors. Five low beams (5 cm) which varied in width (12.5, 10, 7.5, 5 and 2.5 cm) were employed. The performance of subjects was scored from zero to five points according to the width of the beam that they were able to walk without falling off. From the results of multiple regression analysis, three independent variables were found to be significantly related to beam-walking performance. The age of walking was the most basic variable: partial correlation coefficient (PCC) = -45; standardized partial regression coefficient (SPRC) = -0.41. The next variable in importance was walking duration (PCC = 0.38; SPRC = 0.31). The autism variable also contributed significantly (PCC = 0.28; SPRC = 0.22). Therefore, within the age range used in the present study, the age of walking in children with mental retardation was thought to have sufficient predictive value, even when the variables which might have possibly affected their subsequent performance were taken into consideration; the earlier the age of walking, the better the beam-walking performance.

  11. Computational Model-Based Prediction of Human Episodic Memory Performance Based on Eye Movements

    Science.gov (United States)

    Sato, Naoyuki; Yamaguchi, Yoko

    Subjects' episodic memory performance is not simply reflected by eye movements. We use a ‘theta phase coding’ model of the hippocampus to predict subjects' memory performance from their eye movements. Results demonstrate the ability of the model to predict subjects' memory performance. These studies provide a novel approach to computational modeling in the human-machine interface.

  12. Predicting Performance of a Face Recognition System Based on Image Quality

    NARCIS (Netherlands)

    Dutta, A.

    2015-01-01

    In this dissertation, we focus on several aspects of models that aim to predict performance of a face recognition system. Performance prediction models are commonly based on the following two types of performance predictor features: a) image quality features; and b) features derived solely from

  13. Knowledge Tracing and Prediction of Future Trainee Performance

    National Research Council Canada - National Science Library

    Jastrzembski, Tiffany S; Gluck, Kevin A; Gunzelmann, Glenn

    2006-01-01

    ...). This model represents the system's estimate of the student's current knowledge or skill level, established from a performance history. Knowledge tracing (Aleven & Koedinger, 2002; Anderson, Conrad, & Corbett, 1989...

  14. Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

    Directory of Open Access Journals (Sweden)

    Senol Celik

    Full Text Available ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth and testicular (testicular length, scrotal length, and scrotal circumference measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1 and with interaction (MARS_2 terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.

  15. Prediction of a photovoltaic system performance using cumulative frequency curves of radiation

    Energy Technology Data Exchange (ETDEWEB)

    Lasnier, F; Sivoththaman, S [Asian Inst. of Technology, Bangkok (TH). Div. of Energy Technology

    1990-01-01

    The system performance of stand-alone photovoltaic systems is analysed. From the hourly radiation data for Bangkok (from 1984 to 1987) the cumulative frequency curves of radiation are generated and a typical meteorological day (TMD) is created each year. The system performance is determined using both the TMD radiation and the actual radiation values. The comparison results show that the TMD method can be applied for the sizing of stand-alone photovoltaic systems. The storage batteries of realistic sizes usually exhibit a daily cyclic variation in state-of-charge, with constant load consumption. Only very large and unrealistic sizes of batteries show a seasonal variation in state-of-charge. This is the fact that prompted the attempt to predict the system performance for a season by using a single representative day (TMD) of that season. Apart from giving reliable results, the TMD method significantly reduces the computation time and simplifies the process. (author).

  16. Comparing observed and predicted mortality among ICUs using different prognostic systems: why do performance assessments differ?

    Science.gov (United States)

    Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E

    2015-02-01

    To compare ICU performance using standardized mortality ratios generated by the Acute Physiology and Chronic Health Evaluation IVa and a National Quality Forum-endorsed methodology and examine potential reasons for model-based standardized mortality ratio differences. Retrospective analysis of day 1 hospital mortality predictions at the ICU level using Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models on the same patient cohort. Forty-seven ICUs at 36 U.S. hospitals from January 2008 to May 2013. Eighty-nine thousand three hundred fifty-three consecutive unselected ICU admissions. None. We assessed standardized mortality ratios for each ICU using data for patients eligible for Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum predictions in order to compare unit-level model performance, differences in ICU rankings, and how case-mix adjustment might explain standardized mortality ratio differences. Hospital mortality was 11.5%. Overall standardized mortality ratio was 0.89 using Acute Physiology and Chronic Health Evaluation IVa and 1.07 using National Quality Forum, the latter having a widely dispersed and multimodal standardized mortality ratio distribution. Model exclusion criteria eliminated mortality predictions for 10.6% of patients for Acute Physiology and Chronic Health Evaluation IVa and 27.9% for National Quality Forum. The two models agreed on the significance and direction of standardized mortality ratio only 45% of the time. Four ICUs had standardized mortality ratios significantly less than 1.0 using Acute Physiology and Chronic Health Evaluation IVa, but significantly greater than 1.0 using National Quality Forum. Two ICUs had standardized mortality ratios exceeding 1.75 using National Quality Forum, but nonsignificant performance using Acute Physiology and Chronic Health Evaluation IVa. Stratification by patient and institutional characteristics indicated that units caring for more

  17. A unified tool for performance modelling and prediction

    International Nuclear Information System (INIS)

    Gilmore, Stephen; Kloul, Leila

    2005-01-01

    We describe a novel performability modelling approach, which facilitates the efficient solution of performance models extracted from high-level descriptions of systems. The notation which we use for our high-level designs is the Unified Modelling Language (UML) graphical modelling language. The technology which provides the efficient representation capability for the underlying performance model is the multi-terminal binary decision diagram (MTBDD)-based PRISM probabilistic model checker. The UML models are compiled through an intermediate language, the stochastic process algebra PEPA, before translation into MTBDDs for solution. We illustrate our approach on a real-world analysis problem from the domain of mobile telephony

  18. Identification of New Tools to Predict Surgical Performance of Novices using a Plastic Surgery Simulator.

    Science.gov (United States)

    Kazan, Roy; Viezel-Mathieu, Alex; Cyr, Shantale; Hemmerling, Thomas M; Lin, Samuel J; Gilardino, Mirko S

    2018-04-09

    To identify new tools capable of predicting surgical performance of novices on an augmentation mammoplasty simulator. The pace of technical skills acquisition varies between residents and may necessitate more time than that allotted by residency training before reaching competence. Identifying applicants with superior innate technical abilities might shorten learning curves and the time to reach competence. The objective of this study is to identify new tools that could predict surgical performance of novices on a mammoplasty simulator. We recruited 14 medical students and recorded their performance in 2 skill-games: Mikado and Perplexus Epic, and in 2 video games: Star War Racer (Sony Playstation 3) and Super Monkey Ball 2 (Nintendo Wii). Then, each participant performed an augmentation mammoplasty procedure on a Mammoplasty Part-task Trainer, which allows the simulation of the essential steps of the procedure. The average age of participants was 25.4 years. Correlation studies showed significant association between Perplexus Epic, Star Wars Racer, Super Monkey Ball scores and the modified OSATS score with r s = 0.8491 (p 41 (p = 0.005), and r s = 0.7309 (p < 0.003), but not with the Mikado score r s = -0.0255 (p = 0.9). Linear regressions were strongest for Perplexus Epic and Super Monkey Ball scores with coefficients of determination of 0.59 and 0.55, respectively. A combined score (Perplexus/Super-Monkey-Ball) was computed and showed a significant correlation with the modified OSATS score having an r s = 0.8107 (p < 0.001) and R 2 = 0.75, respectively. This study identified a combination of skill games that correlated to better performance of novices on a surgical simulator. With refinement, such tools could serve to help screen plastic surgery applicants and identify those with higher surgical performance predictors. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  19. Prediction of polymer flooding performance using an analytical method

    International Nuclear Information System (INIS)

    Tan Czek Hoong; Mariyamni Awang; Foo Kok Wai

    2001-01-01

    The study investigated the applicability of an analytical method developed by El-Khatib in polymer flooding. Results from a simulator UTCHEM and experiments were compared with the El-Khatib prediction method. In general, by assuming a constant viscosity polymer injection, the method gave much higher recovery values than the simulation runs and the experiments. A modification of the method gave better correlation, albeit only oil production. Investigation is continuing on modifying the method so that a better overall fit can be obtained for polymer flooding. (Author)

  20. IT infrastructure and competitive aggressiveness in explaining and predicting performance

    NARCIS (Netherlands)

    Ajamieh, Aseel; Benitez, Jose; Braojos, Jessica; Gelhard, Carsten Volker

    2016-01-01

    While prior Information Systems and Operations Management literature emphasizes the role of both the firm's IT infrastructure and the general degree of competition as antecedents of firm performance, the organizational capabilities that mediate these important relationships remain undetermined.

  1. Utilizing Lab Tests to Predict Asphalt Concrete Overlay Performance

    Science.gov (United States)

    2017-12-01

    A series of five experimental projects and three demonstration projects were constructed to better understand the performance of pavement overlays using various levels of asphalt binder replacement (ABR) from reclaimed asphalt pavement (RAP), recycle...

  2. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    Science.gov (United States)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

  3. SKread predicts handwriting performance in patients with low vision.

    Science.gov (United States)

    Downes, Ken; Walker, Laura L; Fletcher, Donald C

    2015-06-01

    To assess whether performance on the Smith-Kettlewell Reading (SKread) test is a reliable predictor of handwriting performance in patients with low vision. Cross-sectional study. Sixty-six patients at their initial low-vision rehabilitation evaluation. The patients completed all components of a routine low-vision appointment including logMAR acuity, performed the SKread test, and performed a handwriting task. Patients were timed while performing each task and their accuracy was recorded. The handwriting task was performed by having patients write 5 5-letter words into sets of boxes where each letter is separated by a box. The boxes were 15 × 15 mm, and accuracy was scored with 50 points possible from 25 letters: 1 point for each letter within the confines of a box and 1 point if the letter was legible. Correlation analysis was then performed. Median age of participants was 84 (range 54-97) years. Fifty-seven patients (86%) had age-related macular degeneration or some other maculopathy, whereas 9 patients (14%) had visual impairment from media opacity or neurologic impairment. Median Early Treatment Diabetic Retinopathy Study acuity was 20/133 (range 20/22 to 20/1000), and median logMAR acuity was 0.82 (range 0.04-1.70). SKread errors per block correlated with logMAR acuity (r = 0.6), and SKread time per block correlated with logMAR acuity (r = 0.51). SKread errors per block correlated with handwriting task time/accuracy ratio (r = 0.61). SKread time per block correlated with handwriting task time/accuracy ratio (r = 0.7). LogMAR acuity score correlated with handwriting task time/accuracy ratio (r = 0.42). All p values were handwriting performance in patients with low vision better than logMAR acuity. Copyright © 2015 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

  4. Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences.

    Science.gov (United States)

    Mi, Tian; Merlin, Jerlin Camilus; Deverasetty, Sandeep; Gryk, Michael R; Bill, Travis J; Brooks, Andrew W; Lee, Logan Y; Rathnayake, Viraj; Ross, Christian A; Sargeant, David P; Strong, Christy L; Watts, Paula; Rajasekaran, Sanguthevar; Schiller, Martin R

    2012-01-01

    Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.

  5. Visuospatial and psychomotor aptitude predicts endovascular performance of inexperienced individuals on a virtual reality simulator.

    Science.gov (United States)

    Van Herzeele, Isabelle; O'Donoghue, Kevin G L; Aggarwal, Rajesh; Vermassen, Frank; Darzi, Ara; Cheshire, Nicholas J W

    2010-04-01

    This study evaluated virtual reality (VR) simulation for endovascular training of medical students to determine whether innate perceptual, visuospatial, and psychomotor aptitude (VSA) can predict initial and plateau phase of technical endovascular skills acquisition. Twenty medical students received didactic and endovascular training on a commercially available VR simulator. Each student treated a series of 10 identical noncomplex renal artery stenoses endovascularly. The simulator recorded performance data instantly and objectively. An experienced interventionalist rated the performance at the initial and final sessions using generic (out of 40) and procedure-specific (out of 30) rating scales. VSA were tested with fine motor dexterity (FMD, Perdue Pegboard), psychomotor ability (minimally invasive virtual reality surgical trainer [MIST-VR]), image recall (Rey-Osterrieth), and organizational aptitude (map-planning). VSA performance scores were correlated with the assessment parameters of endovascular skills at commencement and completion of training. Medical students exhibited statistically significant learning curves from the initial to the plateau performance for contrast usage (medians, 28 vs 17 mL, P dexterity as well as with image recall at end of the training period. In addition to current recruitment strategies, VSA may be a useful tool for predictive validity studies.

  6. A core competency-based objective structured clinical examination (OSCE) can predict future resident performance.

    Science.gov (United States)

    Wallenstein, Joshua; Heron, Sheryl; Santen, Sally; Shayne, Philip; Ander, Douglas

    2010-10-01

    This study evaluated the ability of an objective structured clinical examination (OSCE) administered in the first month of residency to predict future resident performance in the Accreditation Council for Graduate Medical Education (ACGME) core competencies. Eighteen Postgraduate Year 1 (PGY-1) residents completed a five-station OSCE in the first month of postgraduate training. Performance was graded in each of the ACGME core competencies. At the end of 18 months of training, faculty evaluations of resident performance in the emergency department (ED) were used to calculate a cumulative clinical evaluation score for each core competency. The correlations between OSCE scores and clinical evaluation scores at 18 months were assessed on an overall level and in each core competency. There was a statistically significant correlation between overall OSCE scores and overall clinical evaluation scores (R = 0.48, p competencies of patient care (R = 0.49, p competencies. An early-residency OSCE has the ability to predict future postgraduate performance on a global level and in specific core competencies. Used appropriately, such information can be a valuable tool for program directors in monitoring residents' progress and providing more tailored guidance. © 2010 by the Society for Academic Emergency Medicine.

  7. The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression

    Directory of Open Access Journals (Sweden)

    Chunxiao Zhang

    2012-01-01

    Full Text Available The prediction of the aero-engine performance parameters is very important for aero-engine condition monitoring and fault diagnosis. In this paper, the chaotic phase space of engine exhaust temperature (EGT time series which come from actual air-borne ACARS data is reconstructed through selecting some suitable nearby points. The partial least square (PLS based on the cubic spline function or the kernel function transformation is adopted to obtain chaotic predictive function of EGT series. The experiment results indicate that the proposed PLS chaotic prediction algorithm based on biweight kernel function transformation has significant advantage in overcoming multicollinearity of the independent variables and solve the stability of regression model. Our predictive NMSE is 16.5 percent less than that of the traditional linear least squares (OLS method and 10.38 percent less than that of the linear PLS approach. At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.

  8. Remaining uncertainties in predicting long-term performance of nuclear waste glass from experiments

    International Nuclear Information System (INIS)

    Grambow, B.

    1994-01-01

    The current knowledge on the glass dissolution mechanism and the representation of glass dissolution concepts within overall repository performance assessment models are briefly summarized and uncertainties related to mechanism, radionuclide chemistry and parameters are discussed. Understanding of the major glass dissolution processes has been significantly increased in recent years. Long-term glass stability is related to the long-term maintenance of silica saturated conditions. The behavior of individual radionuclides in the presence of a dissolving glass has not been sufficiently and results do no yet allow meaningful predictions. Conserving long-term predictions of glass matrix dissolution as upper limit for radionuclide release can be made with sufficient confidence, however these estimations generally result in a situation where the barrier function of the glass is masked by the efficiency of the geologic barrier. Realistic long-term predictions may show that the borosilicate waste glass contributes to overall repository safety to a much larger extent than indicated by overconservatism. Today realistic predictions remain highly uncertain and much more research work is necessary. In particular, the long-term rate under silica saturated conditions needs to be understood and the behavior of individual radionuclides in the presence of a dissolving glass deserves more systematic investigations

  9. Performance Comparison Between Support Vector Regression and Artificial Neural Network for Prediction of Oil Palm Production

    Directory of Open Access Journals (Sweden)

    Mustakim Mustakim

    2016-02-01

    Full Text Available The largest region that produces oil palm in Indonesia has an important role in improving the welfare of society and economy. Oil palm has increased significantly in Riau Province in every period, to determine the production development for the next few years with the functions and benefits of oil palm carried prediction production results that were seen from time series data last 8 years (2005-2013. In its prediction implementation, it was done by comparing the performance of Support Vector Regression (SVR method and Artificial Neural Network (ANN. From the experiment, SVR produced the best model compared with ANN. It is indicated by the correlation coefficient of 95% and 6% for MSE in the kernel Radial Basis Function (RBF, whereas ANN produced only 74% for R2 and 9% for MSE on the 8th experiment with hiden neuron 20 and learning rate 0,1. SVR model generates predictions for next 3 years which increased between 3% - 6% from actual data and RBF model predictions.

  10. A prediction score for significant coronary artery disease in Chinese patients ≥50 years old referred for rheumatic valvular heart disease surgery.

    Science.gov (United States)

    Xu, Zhenjun; Pan, Jun; Chen, Tao; Zhou, Qing; Wang, Qiang; Cao, Hailong; Fan, Fudong; Luo, Xuan; Ge, Min; Wang, Dongjin

    2018-04-01

    Our goal was to establish a prediction score and protocol for the preoperative prediction of significant coronary artery disease (CAD) in patients with rheumatic valvular heart disease. Using multivariate logistic regression analysis, we validated the model based on 490 patients without a history of myocardial infarction and who underwent preoperative screening coronary angiography. Significant CAD was defined as ≥50% narrowing of the diameter of the lumen of the left main coronary artery or ≥70% narrowing of the diameter of the lumen of the left anterior descending coronary artery, left circumflex artery or right coronary artery. Significant CAD was present in 9.8% of patients. Age, smoking, diabetes mellitus, diastolic blood pressure, low-density lipoprotein cholesterol and ischaemia evident on an electrocardiogram were independently associated with significant CAD and were entered into the multivariate model. According to the logistic regression predictive risk score, preoperative coronary angiography is recommended in (i) postmenopausal women between 50 and 59 years of age with ≥9.1% logistic regression predictive risk score; (ii) postmenopausal women who are ≥60 years old with a logistic regression predictive risk score ≥6.6% and (iii) men ≥50 years old whose logistic regression predictive risk score was ≥2.8%. Based on this predictive model, 246 (50.2%) preoperative coronary angiograms could be safely avoided. The negative predictive value of the model was 98.8% (246 of 249). This model was accurate for the preoperative prediction of significant CAD in patients with rheumatic valvular heart disease. This model must be validated in larger cohorts and various populations.

  11. How the choice of safety performance function affects the identification of important crash prediction variables.

    Science.gov (United States)

    Wang, Ketong; Simandl, Jenna K; Porter, Michael D; Graettinger, Andrew J; Smith, Randy K

    2016-03-01

    Across the nation, researchers and transportation engineers are developing safety performance functions (SPFs) to predict crash rates and develop crash modification factors to improve traffic safety at roadway segments and intersections. Generalized linear models (GLMs), such as Poisson or negative binomial regression, are most commonly used to develop SPFs with annual average daily traffic as the primary roadway characteristic to predict crashes. However, while more complex to interpret, data mining models such as boosted regression trees have improved upon GLMs crash prediction performance due to their ability to handle more data characteristics, accommodate non-linearities, and include interaction effects between the characteristics. An intersection data inventory of 36 safety relevant parameters for three- and four-legged non-signalized intersections along state routes in Alabama was used to study the importance of intersection characteristics on crash rate and the interaction effects between key characteristics. Four different SPFs were investigated and compared: Poisson regression, negative binomial regression, regularized generalized linear model, and boosted regression trees. The models did not agree on which intersection characteristics were most related to the crash rate. The boosted regression tree model significantly outperformed the other models and identified several intersection characteristics as having strong interaction effects. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Predicting Intention Perform Breast Self-Examination: Application of the Theory of Reasoned Action

    Science.gov (United States)

    Dewi, Triana Kesuma; Zein, Rizqy Amelia

    2017-11-26

    Objective: The present study aimed to examine the applicability of the theory of reasoned action to explain intention to perform breast self-examination (BSE). Methods: A questionnaire was constructed to collect data. The hypothesis was tested in two steps. First, to assess the strength of the correlation among the constructs of theory of reasoned action (TRA), Pearson’s product moment correlations were applied. Second, multivariate relationships among the constructs were examined by performing hierarchical multiple linear regression analysis. Result: The findings supported the TRA model, explaining 45.8% of the variance in the students’ BSE intention, which was significantly correlated with attitude (r = 0.609, p = 0.000) and subjective norms (r = 0.420, p =0 .000). Conclusion: TRA could be a suitable model to predict BSE intentions . Participants who believed that doing BSE regularly is beneficial for early diagnosis of breast cancer and also believed that their significant referents think that doing BSE would significantly detect breast cancer earlier, were more likely to intend to perform BSE regularly. Therefore, the research findings supported the conclusion that promoting the importance of BSE at the community/social level would enhance individuals to perform BSE routinely. Creative Commons Attribution License

  13. Predicting the seismic performance of typical R/C healthcare facilities: emphasis on hospitals

    Science.gov (United States)

    Bilgin, Huseyin; Frangu, Idlir

    2017-09-01

    Reinforced concrete (RC) type of buildings constitutes an important part of the current building stock in earthquake prone countries such as Albania. Seismic response of structures during a severe earthquake plays a vital role in the extent of structural damage and resulting injuries and losses. In this context, this study evaluates the expected performance of a five-story RC healthcare facility, representative of common practice in Albania, designed according to older codes. The design was based on the code requirements used in this region during the mid-1980s. Non-linear static and dynamic time history analyses were conducted on the structural model using the Zeus NL computer program. The dynamic time history analysis was conducted with a set of ground motions from real earthquakes. The building responses were estimated in global levels. FEMA 356 criteria were used to predict the seismic performance of the building. The structural response measures such as capacity curve and inter-story drift under the set of ground motions and pushover analyses results were compared and detailed seismic performance assessment was done. The main aim of this study is considering the application and methodology for the earthquake performance assessment of existing buildings. The seismic performance of the structural model varied significantly under different ground motions. Results indicate that case study building exhibit inadequate seismic performance under different seismic excitations. In addition, reasons for the poor performance of the building is discussed.

  14. Does Tacit Knowledge Predict Organizational Performance? A Scrutiny of Firms in the Upstream Sector in Nigeria

    Directory of Open Access Journals (Sweden)

    Vincent I.O Odiri

    2016-02-01

    Full Text Available This paper examined tacit knowledge so as to see whether tacit knowledge when properly put to use can lead to improved performance by upstream sector firms in Nigeria. Knowledge as we believe, is very vital to both corporate entities and individuals. Knowledge encompasses both explicit and tacit. This paper focused on one aspect of knowledge – ‘tacit’ which is in the psyche or brain of the individual possessing it. Inspite of the central role it plays, tacit knowledge has been downplayed by most firms. However, we adopted a survey research design via questionnaires administered to 504 employees randomly selected from 3 different oil firms. The data obtained were analyzed using inferential statistics. Also, multi-collinearity diagnoses of tacit knowledge and organizational performance was performed. The result suggests that tacit knowledge is linearly correlated with organizational performance. This implies that tacit knowledge predicts organizational performance. This study is significant in that the findings would be useful to management of firms, as it divulge how tacit knowledge when properly harnessed can lead to increased performance. Most prior studies in this area were conducted in other countries, hence our study is one of the first in Nigeria that examined tacit knowledge and organizational performance.

  15. Iowa calibration of MEPDG performance prediction models : [summary].

    Science.gov (United States)

    2013-06-01

    The latest AASHTOWare DARWin-METM (now referred to as Pavement ME Design), and the Mechanistic-Empirical Pavement Design Guide (MEPDG) (AASHTO 2008) are significantly improved methodologies for the analysis and design of pavement structures. DARWin...

  16. Predicting Subsequent Task Performance From Goal Motivation and Goal Failure

    Directory of Open Access Journals (Sweden)

    Laura Catherine Healy

    2015-07-01

    Full Text Available Recent research has demonstrated that the cognitive processes associated with goal pursuit can continue to interfere with unrelated tasks when a goal is unfulfilled. Drawing from the self-regulation and goal-striving literatures, the present study explored the impact of goal failure on subsequent cognitive and physical task performance. Furthermore, we examined if the autonomous or controlled motivation underpinning goal striving moderates the responses to goal failure. Athletes (75 male, 59 female, Mage = 19.90 years, SDage = 3.50 completed a cycling trial with the goal of covering a given distance in 8 minutes. Prior to the trial, their motivation was primed using a video. During the trial they were provided with manipulated performance feedback, thus creating conditions of goal success or failure. No differences emerged in the responses to goal failure between the primed motivation or performance feedback conditions. We make recommendations for future research into how individuals can deal with failure in goal striving.

  17. Predicted performance of an integrated modular engine system

    Science.gov (United States)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator (ROCETS) program. The nominal steady-state performance is simulated, as well as turbopump thrust chamber and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  18. [Predictive factors of clinically significant drug-drug interactions among regimens based on protease inhibitors, non-nucleoside reverse transcriptase inhibitors and raltegravir].

    Science.gov (United States)

    Cervero, Miguel; Torres, Rafael; Jusdado, Juan José; Pastor, Susana; Agud, Jose Luis

    2016-04-15

    To determine the prevalence and types of clinically significant drug-drug interactions (CSDI) in the drug regimens of HIV-infected patients receiving antiretroviral treatment. retrospective review of database. Centre: Hospital Universitario Severo Ochoa, Infectious Unit. one hundred and forty-two participants followed by one of the authors were selected from January 1985 to December 2014. from their outpatient medical records we reviewed information from the last available visit of the participants, in relation to HIV infection, comorbidities, demographics and the drugs that they were receiving; both antiretroviral drugs and drugs not related to HIV infection. We defined CSDI from the information sheet and/or database on antiretroviral drug interactions of the University of Liverpool (http://www.hiv-druginteractions.org) and we developed a diagnostic tool to predict the possibility of CSDI. By multivariate logistic regression analysis and by estimating the diagnostic performance curve obtained, we identified a quick tool to predict the existence of drug interactions. Of 142 patients, 39 (29.11%) had some type of CSDI and in 11.2% 2 or more interactions were detected. In only one patient the combination of drugs was contraindicated (this patient was receiving darunavir/r and quetiapine). In multivariate analyses, predictors of CSDI were regimen type (PI or NNRTI) and the use of 3 or more non-antiretroviral drugs (AUC 0.886, 95% CI 0.828 to 0.944; P=.0001). The risk was 18.55 times in those receiving NNRTI and 27,95 times in those receiving IP compared to those taking raltegravir. Drug interactions, including those defined as clinically significant, are common in HIV-infected patients treated with antiretroviral drugs, and the risk is greater in IP-based regimens. Raltegravir-based prescribing, especially in patients who receive at least 3 non-HIV drugs could avoid interactions. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

  19. Methodologies for predicting the part-load performance of aero-derivative gas turbines

    DEFF Research Database (Denmark)

    Haglind, Fredrik; Elmegaard, Brian

    2009-01-01

    Prediction of the part-load performance of gas turbines is advantageous in various applications. Sometimes reasonable part-load performance is sufficient, while in other cases complete agreement with the performance of an existing machine is desirable. This paper is aimed at providing some guidance...... on methodologies for predicting part-load performance of aero-derivative gas turbines. Two different design models – one simple and one more complex – are created. Subsequently, for each of these models, the part-load performance is predicted using component maps and turbine constants, respectively. Comparisons...... with manufacturer data are made. With respect to the design models, the simple model, featuring a compressor, combustor and turbines, results in equally good performance prediction in terms of thermal efficiency and exhaust temperature as does a more complex model. As for part-load predictions, the results suggest...

  20. Performance prediction of industrial centrifuges using scale-down models.

    Science.gov (United States)

    Boychyn, M; Yim, S S S; Bulmer, M; More, J; Bracewell, D G; Hoare, M

    2004-12-01

    Computational fluid dynamics was used to model the high flow forces found in the feed zone of a multichamber-bowl centrifuge and reproduce these in a small, high-speed rotating disc device. Linking the device to scale-down centrifugation, permitted good estimation of the performance of various continuous-flow centrifuges (disc stack, multichamber bowl, CARR Powerfuge) for shear-sensitive protein precipitates. Critically, the ultra scale-down centrifugation process proved to be a much more accurate predictor of production multichamber-bowl performance than was the pilot centrifuge.

  1. Financial performance evaluation and bankruptcy prediction (failure1

    Directory of Open Access Journals (Sweden)

    Talal A. Al-Kassar, Dr.

    2014-10-01

    The research also demonstrates the need to include measures of both financial and non-financial performance in the evaluation as they complement each other. Without both financial and non-financial, the evaluation process is incomplete and does not provide desired results or the correct image of the process. The research suggests including comprehensive measures of performance evaluation of projects by using indicators of adopted criteria. Thus, the application of both models leads to better results and assists users in maintaining greater objectivity while obtaining more accurate results than from analysis based on personal evaluation alone.

  2. Performance of the Sellick maneuver significantly improves when residents and trained nurses use a visually interactive guidance device in simulation

    International Nuclear Information System (INIS)

    Connor, Christopher W; Saffary, Roya; Feliz, Eddy

    2013-01-01

    We examined the proper performance of the Sellick maneuver, a maneuver used to reduce the risk of aspiration of stomach contents during induction of general anesthesia, using a novel device that measures and visualizes the force applied to the cricoid cartilage using thin-film force sensitive resistors in a form suitable for in vivo use. Performance was tested in three stages with twenty anaesthesiology residents and twenty trained operating room nurses. Firstly, subjects applied force to the cricoid cartilage as was customary to them. Secondly, subjects used the device to guide the application of that force. Thirdly, subjects were again asked to perform the manoeuvre without visual guidance. Each test lasted 1 min and the amount of force applied was measured throughout. Overall, the Sellick maneuver was often not applied properly, with large variance between individual subjects. Performance and inter-subject consistency improved to a very highly significant degree when subjects were able to use the device as a visual guide (p < 0.001). Subsequent significant improvements in performances during the last, unguided test demonstrated that the device initiated learning. (paper)

  3. Performance of the Sellick maneuver significantly improves when residents and trained nurses use a visually interactive guidance device in simulation

    Energy Technology Data Exchange (ETDEWEB)

    Connor, Christopher W; Saffary, Roya; Feliz, Eddy [Department of Anesthesiology Boston Medical Center, Boston, MA (United States)

    2013-12-15

    We examined the proper performance of the Sellick maneuver, a maneuver used to reduce the risk of aspiration of stomach contents during induction of general anesthesia, using a novel device that measures and visualizes the force applied to the cricoid cartilage using thin-film force sensitive resistors in a form suitable for in vivo use. Performance was tested in three stages with twenty anaesthesiology residents and twenty trained operating room nurses. Firstly, subjects applied force to the cricoid cartilage as was customary to them. Secondly, subjects used the device to guide the application of that force. Thirdly, subjects were again asked to perform the manoeuvre without visual guidance. Each test lasted 1 min and the amount of force applied was measured throughout. Overall, the Sellick maneuver was often not applied properly, with large variance between individual subjects. Performance and inter-subject consistency improved to a very highly significant degree when subjects were able to use the device as a visual guide (p < 0.001). Subsequent significant improvements in performances during the last, unguided test demonstrated that the device initiated learning. (paper)

  4. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    Science.gov (United States)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  5. Translation Ambiguity but Not Word Class Predicts Translation Performance

    Science.gov (United States)

    Prior, Anat; Kroll, Judith F.; Macwhinney, Brian

    2013-01-01

    We investigated the influence of word class and translation ambiguity on cross-linguistic representation and processing. Bilingual speakers of English and Spanish performed translation production and translation recognition tasks on nouns and verbs in both languages. Words either had a single translation or more than one translation. Translation…

  6. Predictive Performance Tuning of OpenACC Accelerated Applications

    KAUST Repository

    Siddiqui, Shahzeb; Feki, Saber

    2014-01-01

    , with the introduction of high level programming models such as OpenACC [1] and OpenMP 4.0 [2], these devices are becoming more accessible and practical to use by a larger scientific community. However, performance optimization of OpenACC accelerated applications usually

  7. Predicting Performance Under Acute Stress : The Role of Individual Characteristics

    NARCIS (Netherlands)

    Delahaij, R.; Dam, K. van; Gaillard, A.W.K.; Soeters, J.

    2011-01-01

    This prospective study examined how differences in coping style, coping self-efficacy, and metacognitive awareness influence coping behavior and performance during a realistic acute stressful exercise in 2 military samples (n = 122 and n = 132). Results showed that coping self-efficacy and coping

  8. Goal orientations predict academic performance beyond intelligence and personality

    NARCIS (Netherlands)

    Steinmayr, R.; Bipp, T.; Spinath, B.

    2011-01-01

    Goal orientations are thought to be an important predictor of scholastic achievement. The present paper investigated the joint influence of goal orientations, intelligence, and personality on school performance in a sample of N = 520 11th and 12th graders (303 female; mean age M = 16.94 years).

  9. Fine-motor skills testing and prediction of endovascular performance

    DEFF Research Database (Denmark)

    Bech, Bo; Lönn, Lars; Schroeder, Torben V

    2013-01-01

    Performing endovascular procedures requires good control of fine-motor digital movements and hand-eye coordination. Objective assessment of such skills is difficult. Trainees acquire control of catheter/wire movements at various paces. However, little is known to what extent talent plays for novice...

  10. Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

    Science.gov (United States)

    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…

  11. Predicting timing performance of advanced mechatronics control systems

    NARCIS (Netherlands)

    Voeten, J.P.M.; Hendriks, T.; Theelen, B.D.; Schuddemat, J.; Tabingh Suermondt, W.; Gemei, J.; Kotterink, C.; Huet, van J.; Eichler, G.; Kuepper, A.; Schau, V.; Fouchal, H.; Unger, H.

    2011-01-01

    Embedded control is a key product technology differentiator for many high-tech industries, including ASML. The strong increase in complexity of embedded control systems, combined with the occurrence of late changes in control requirements, results in many timing performance problems showing up only

  12. Students' Metacomprehension Knowledge: Components That Predict Comprehension Performance

    Science.gov (United States)

    Zabrucky, Karen M.; Moore, DeWayne; Agler, Lin-Miao Lin; Cummings, Andrea M.

    2015-01-01

    In the present study, we assessed students' metacomprehension knowledge and examined the components of knowledge most related to comprehension of expository texts. We used the Revised Metacomprehension Scale (RMCS) to investigate the relations between students' metacomprehension knowledge and comprehension performance. Students who evaluated and…

  13. Adult age differences in predicting memory performance: the effects of normative information and task experience.

    Science.gov (United States)

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

    1994-03-01

    Two experiments addressed the effects of task information and experience on younger and older adults' ability to predict their memory for words. The first study examined the effects of normative task information on subjects' predictions for 30-word lists across three trials. The second study looked at the effects of making predictions and recalling either an easy (15) or a difficult (45) word list prior to making predictions and recalling a moderately difficult (30) word list. The results from both studies showed that task information and experience affected subjects' predictions and that elderly adults predicted their performance more accurately than younger adults.

  14. Energy Prediction versus Energy Performance of Green Buildings in Malaysia. Comparison of Predicted and Operational Measurement of GBI Certified Green Office in Kuala Lumpur

    Directory of Open Access Journals (Sweden)

    Zaid Suzaini M

    2016-01-01

    Full Text Available Forward from the sustainability agenda of Brundtland in 1987 and the increasing demand for energy efficient buildings, the building industry has taken steps in meeting the challenge of reducing its environmental impact. Initiatives such as ‘green’ or ‘sustainable’ design have been at the forefront of architecture, while green assessment tools have been used to predict the energy performance of building during its operational phase. However, there is still a significant hap between predicted or simulated energy measurements compared to actual operational energy consumption, or is more commonly referred as the ‘performance gap’. This paper tries to bridge this gap by comparing measured operational energy consumption of a Green Building Index (GBI certified office building in Kuala Lumpur, with its predicted energy rating qualification.

  15. Contribution of temporal data to predictive performance in 30-day readmission of morbidly obese patients

    Directory of Open Access Journals (Sweden)

    Petra Povalej Brzan

    2017-04-01

    Full Text Available Background Reduction of readmissions after discharge represents an important challenge for many hospitals and has attracted the interest of many researchers in the past few years. Most of the studies in this field focus on building cross-sectional predictive models that aim to predict the occurrence of readmission within 30-days based on information from the current hospitalization. The aim of this study is demonstration of predictive performance gain obtained by inclusion of information from historical hospitalization records among morbidly obese patients. Methods The California Statewide inpatient database was used to build regularized logistic regression models for prediction of readmission in morbidly obese patients (n = 18,881. Temporal features were extracted from historical patient hospitalization records in a one-year timeframe. Five different datasets of patients were prepared based on the number of available hospitalizations per patient. Sample size of the five datasets ranged from 4,787 patients with more than five hospitalizations to 20,521 patients with at least two hospitalization records in one year. A 10-fold cross validation was repeted 100 times to assess the variability of the results. Additionally, random forest and extreme gradient boosting were used to confirm the results. Results Area under the ROC curve increased significantly when including information from up to three historical records on all datasets. The inclusion of more than three historical records was not efficient. Similar results can be observed for Brier score and PPV value. The number of selected predictors corresponded to the complexity of the dataset ranging from an average of 29.50 selected features on the smallest dataset to 184.96 on the largest dataset based on 100 repetitions of 10-fold cross-validation. Discussion The results show positive influence of adding information from historical hospitalization records on predictive performance using all

  16. A Bayesian Performance Prediction Model for Mathematics Education: A Prototypical Approach for Effective Group Composition

    Science.gov (United States)

    Bekele, Rahel; McPherson, Maggie

    2011-01-01

    This research work presents a Bayesian Performance Prediction Model that was created in order to determine the strength of personality traits in predicting the level of mathematics performance of high school students in Addis Ababa. It is an automated tool that can be used to collect information from students for the purpose of effective group…

  17. Ski jump takeoff performance predictions for a mixed-flow, remote-lift STOVL aircraft

    Science.gov (United States)

    Birckelbaw, Lourdes G.

    1992-01-01

    A ski jump model was developed to predict ski jump takeoff performance for a short takeoff and vertical landing (STOVL) aircraft. The objective was to verify the model with results from a piloted simulation of a mixed flow, remote lift STOVL aircraft. The prediction model is discussed. The predicted results are compared with the piloted simulation results. The ski jump model can be utilized for basic research of other thrust vectoring STOVL aircraft performing a ski jump takeoff.

  18. Evaluation and prediction of the performance of positive displacement motor

    Energy Technology Data Exchange (ETDEWEB)

    Tudor, R.; Ginzburg, L. [Canadian Fracmaster Ltd., Calgary, AB (Canada); Xu, H. [Japan National Oil Corp (Japan); Li, J.; Robello, G.; Grigor, C.

    1998-12-31

    Test results of positive displacement motors (PDMs) collected by using various PDMs from a number of different suppliers have been analyzed. Various correlations have been developed and motor performance pumped with incompressible drilling fluid was evaluated based on test data provided by suppliers in the form of pressure drop versus torque output. Conclusions drawn from the study suggest that when a motor is operated at less than full load, the correlation between mechanical power and hydraulic power across the PDM power section can be described with a simple linear equation (different for each PDM type). Assuming the availability of patented geometric information for each PDM type, the performance of PDMs can be described by both the geometric parameters of the motor and the rheological properties of the circulation fluid. 9 refs., 8 figs.

  19. Testing the performance of technical trading rules in the Chinese markets based on superior predictive test

    Science.gov (United States)

    Wang, Shan; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing

    2015-12-01

    Technical trading rules have a long history of being used by practitioners in financial markets. The profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousand traditional technical trading rules on the Shanghai Securities Composite Index (SSCI) from May 21, 1992 through June 30, 2013 and China Securities Index 300 (CSI 300) from April 8, 2005 through June 30, 2013 to check whether an effective trading strategy could be found by using the performance measurements based on the return and Sharpe ratio. To correct for the influence of the data-snooping effect, we adopt the Superior Predictive Ability test to evaluate if there exists a trading rule that can significantly outperform the benchmark. The result shows that for SSCI, technical trading rules offer significant profitability, while for CSI 300, this ability is lost. We further partition the SSCI into two sub-series and find that the efficiency of technical trading in sub-series, which have exactly the same spanning period as that of CSI 300, is severely weakened. By testing the trading rules on both indexes with a five-year moving window, we find that during the financial bubble from 2005 to 2007, the effectiveness of technical trading rules is greatly improved. This is consistent with the predictive ability of technical trading rules which appears when the market is less efficient.

  20. Addendum to the article: Misuse of null hypothesis significance testing: Would estimation of positive and negative predictive values improve certainty of chemical risk assessment?

    Science.gov (United States)

    Bundschuh, Mirco; Newman, Michael C; Zubrod, Jochen P; Seitz, Frank; Rosenfeldt, Ricki R; Schulz, Ralf

    2015-03-01

    We argued recently that the positive predictive value (PPV) and the negative predictive value (NPV) are valuable metrics to include during null hypothesis significance testing: They inform the researcher about the probability of statistically significant and non-significant test outcomes actually being true. Although commonly misunderstood, a reported p value estimates only the probability of obtaining the results or more extreme results if the null hypothesis of no effect was true. Calculations of the more informative PPV and NPV require a priori estimate of the probability (R). The present document discusses challenges of estimating R.

  1. Reverse translated and gold standard continuous performance tests predict global cognitive performance in schizophrenia.

    Science.gov (United States)

    Bismark, Andrew W; Thomas, Michael L; Tarasenko, Melissa; Shiluk, Alexandra L; Rackelmann, Sonia Y; Young, Jared W; Light, Gregory A

    2018-04-12

    Attentional dysfunction contributes to functional impairments in schizophrenia (SZ). Sustained attention is typically assessed via continuous performance tasks (CPTs), though many CPTs have limited cross-species translational validity and place demands on additional cognitive domains. A reverse-translated 5-Choice Continuous Performance Task (5C-CPT) for human testing-originally developed for use in rodents-was designed to minimize demands on perceptual, visual learning, processing speed, or working memory functions. To-date, no studies have validated the 5C-CPT against gold standard attentional measures nor evaluated how 5C-CPT scores relate to cognition in SZ. Here we examined the relationship between the 5C-CPT and the CPT-Identical Pairs (CPT-IP), an established and psychometrically robust measure of vigilance from the MATRICS Consensus Cognitive Battery (MCCB) in a sample of SZ patients (n = 35). Relationships to global and individual subdomains of cognition were also assessed. 5C-CPT and CPT-IP measures of performance (d-prime) were strongly correlated (r = 0.60). In a regression model, the 5C-CPT and CPT-IP collectively accounted for 54% of the total variance in MCCB total scores, and 27.6% of overall cognitive variance was shared between the 5C-CPT and CPT-IP. These results indicate that the reverse translated 5C-CPT and the gold standard CPT-IP index a common attentional construct that also significantly overlaps with variance in general cognitive performance. The use of simple, cross-species validated behavioral indices of attentional/cognitive functioning such as the 5C-CPT could accelerate the development of novel generalized pro-cognitive therapeutics for SZ and related neuropsychiatric disorders.

  2. Revised MITG design, fabrication procedure, and performance predictions

    International Nuclear Information System (INIS)

    Schock, A.

    1983-01-01

    The design, analysis, and key features of the Modular Isotopic Thermoelectric Generator (MITG) were described in a 1981 IECEC paper; and the design, fabrication, testing, and post-test analysis of test assemblies simulating prototypical MITG modules were described in preceding papers in these proceedings. These analyses succeeded in identifying and explaining the principal causes of thermal-stress problems encountered in the tests, and in confirming the effectiveness of design changes for alleviating them. The present paper presents additional design improvements for solving these and other problems, and describes new thermoelectric material properties generated by independent laboratories over the past two years. Based on these changes and on a revised fabrication procedure, it presents a reoptimization of the MITG design and computes the power-to-weight ratio for the revised design. That ratio is appreciably lower than the 1981 prediction, primarily because of changes in material properties; but it is still much higher than the specific power of current-generation RTGs

  3. Performance predictions affect attentional processes of event-based prospective memory.

    Science.gov (United States)

    Rummel, Jan; Kuhlmann, Beatrice G; Touron, Dayna R

    2013-09-01

    To investigate whether making performance predictions affects prospective memory (PM) processing, we asked one group of participants to predict their performance in a PM task embedded in an ongoing task and compared their performance with a control group that made no predictions. A third group gave not only PM predictions but also ongoing-task predictions. Exclusive PM predictions resulted in slower ongoing-task responding both in a nonfocal (Experiment 1) and in a focal (Experiment 2) PM task. Only in the nonfocal task was the additional slowing accompanied by improved PM performance. Even in the nonfocal task, however, was the correlation between ongoing-task speed and PM performance reduced after predictions, suggesting that the slowing was not completely functional for PM. Prediction-induced changes could be avoided by asking participants to additionally predict their performance in the ongoing task. In sum, the present findings substantiate a role of metamemory for attention-allocation strategies of PM. Copyright © 2013 Elsevier Inc. All rights reserved.

  4. Independent predictive factors for significant liver histological changes in patients with HBeAg-positive high-viral-load chronic HBV infection and a normal alanine aminotransferase level

    Directory of Open Access Journals (Sweden)

    LI Qiang

    2016-07-01

    Full Text Available Objective To investigate the independent predictive factors for significant liver histological changes (SLHCs in patients with HBeAg-positive high-viral-load chronic hepatitis B virus (HBV infection and a normal alanine aminotransferase (ALT level. MethodsA retrospective analysis was performed on the clinical data of 116 previously untreated patients with HBeAg-positive high-viral-load (HBV DNA≥105 copies/ml chronic HBV infection and a normal ALT level (<50 U/L who were hospitalized in Shanghai Public Health Clinical Center Affiliated to Fudan University from June 2013 to August 2015. The definition of SLHCs was inflammation ≥G2 and/or fibrosis≥S2. The t-test or Mann-Whitney U rank sum test was used for comparison of continuous data between groups, and the chi-square test was used for comparison of categorical data between groups. Univariate and multivariate regression analyses were used to determine independent predictive factors for SLHCs. ResultsOf all the 116 patients, 47(40.5% had SLHCs. The multivariate analysis showed that age (OR=2.828, P<0.05, ALT (OR=1.011, P<0.05, and gamma-glutamyl transpeptidase (GGT (OR=1.089, P<0.05 were independent predictors for SLHCs in patients with HBeAg-positive high-viral-load chronic HBV infection and a normal ALT level. The patients aged ≤30 years had a significantly lower incidence rate of SLHCs than those aged>30 years (21.6% vs 49.4%, χ2=6.42, P=0.015, the patients with ALT ≤30 U/L had a significantly lower incidence rate of SLHCs than those with 30 U/L<ALT≤50 U/L (17.6% vs 50.0%, χ2=19.86, P<0.001, and the patients with GGT≤40 U/L had a significantly lower incidence rate of SLHCs than those with GGT>40 U/L (28.8% vs 66.7%, χ2=28.63, P<0.001. ConclusionIn patients with HBeAg-positive high-viral-load chronic HBV infection and a normal ALT level, those with an age of>30 years, ALT>30 U/L, and GGT>40 U/L tend to develop SLHCs and need liver biopsy.

  5. Balancing Model Performance and Simplicity to Predict Postoperative Primary Care Blood Pressure Elevation.

    Science.gov (United States)

    Schonberger, Robert B; Dai, Feng; Brandt, Cynthia A; Burg, Matthew M

    2015-09-01

    Because of uncertainty regarding the reliability of perioperative blood pressures and traditional notions downplaying the role of anesthesiologists in longitudinal patient care, there is no consensus for anesthesiologists to recommend postoperative primary care blood pressure follow-up for patients presenting for surgery with an increased blood pressure. The decision of whom to refer should ideally be based on a predictive model that balances performance with ease-of-use. If an acceptable decision rule was developed, a new practice paradigm integrating the surgical encounter into broader public health efforts could be tested, with the goal of reducing long-term morbidity from hypertension among surgical patients. Using national data from US veterans receiving surgical care, we determined the prevalence of poorly controlled outpatient clinic blood pressures ≥140/90 mm Hg, based on the mean of up to 4 readings in the year after surgery. Four increasingly complex logistic regression models were assessed to predict this outcome. The first included the mean of 2 preoperative blood pressure readings; other models progressively added a broad array of demographic and clinical data. After internal validation, the C-statistics and the Net Reclassification Index between the simplest and most complex models were assessed. The performance characteristics of several simple blood pressure referral thresholds were then calculated. Among 215,621 patients, poorly controlled outpatient clinic blood pressure was present postoperatively in 25.7% (95% confidence interval [CI], 25.5%-25.9%) including 14.2% (95% CI, 13.9%-14.6%) of patients lacking a hypertension history. The most complex prediction model demonstrated statistically significant, but clinically marginal, improvement in discrimination over a model based on preoperative blood pressure alone (C-statistic, 0.736 [95% CI, 0.734-0.739] vs 0.721 [95% CI, 0.718-0.723]; P for difference 1 of 4 patients (95% CI, 25

  6. Do physiological measures predict selected CrossFit® benchmark performance?

    Science.gov (United States)

    Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

    2015-01-01

    Purpose CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit “Workouts of the Day” (WODs). Materials and methods Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs “Grace” (30 clean and jerks for time), “Fran” (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and “Cindy” (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the “CrossFit Total” (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Results Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=−0.88 and −0.65, respectively) and anaerobic threshold (r=−0.61 and −0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. Conclusion CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs. PMID:26261428

  7. Do physiological measures predict selected CrossFit® benchmark performance?

    Directory of Open Access Journals (Sweden)

    Butcher SJ

    2015-07-01

    Full Text Available Scotty J Butcher,1,2 Tyler J Neyedly,3 Karla J Horvey,1 Chad R Benko2,41Physical Therapy, University of Saskatchewan, 2BOSS Strength Institute, 3Physiology, University of Saskatchewan, 4Synergy Strength and Conditioning, Saskatoon, SK, CanadaPurpose: CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit "Workouts of the Day" (WODs.Materials and methods: Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs "Grace" (30 clean and jerks for time, "Fran" (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions, and "Cindy" (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats, as well as the "CrossFit Total" (1 repetition max [1RM] back squat, overhead press, and deadlift, maximal oxygen consumption (VO2max, and Wingate anaerobic power/capacity testing.Results: Performance of Grace and Fran was related to whole-body strength (CrossFit Total (r=-0.88 and -0.65, respectively and anaerobic threshold (r=-0.61 and -0.53, respectively; however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively. There were no significant associations or predictors for Cindy.Conclusion: CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training

  8. Algorithms and Methods for High-Performance Model Predictive Control

    DEFF Research Database (Denmark)

    Frison, Gianluca

    routines employed in the numerical tests. The main focus of this thesis is on linear MPC problems. In this thesis, both the algorithms and their implementation are equally important. About the implementation, a novel implementation strategy for the dense linear algebra routines in embedded optimization...... is proposed, aiming at improving the computational performance in case of small matrices. About the algorithms, they are built on top of the proposed linear algebra, and they are tailored to exploit the high-level structure of the MPC problems, with special care on reducing the computational complexity....

  9. Basic considerations in predicting error probabilities in human task performance

    International Nuclear Information System (INIS)

    Fleishman, E.A.; Buffardi, L.C.; Allen, J.A.; Gaskins, R.C. III

    1990-04-01

    It is well established that human error plays a major role in the malfunctioning of complex systems. This report takes a broad look at the study of human error and addresses the conceptual, methodological, and measurement issues involved in defining and describing errors in complex systems. In addition, a review of existing sources of human reliability data and approaches to human performance data base development is presented. Alternative task taxonomies, which are promising for establishing the comparability on nuclear and non-nuclear tasks, are also identified. Based on such taxonomic schemes, various data base prototypes for generalizing human error rates across settings are proposed. 60 refs., 3 figs., 7 tabs

  10. Can Medical School Performance Predict Residency Performance? Resident Selection and Predictors of Successful Performance in Obstetrics and Gynecology

    Science.gov (United States)

    Stohl, Hindi E.; Hueppchen, Nancy A.; Bienstock, Jessica L.

    2010-01-01

    Background During the evaluation process, Residency Admissions Committees typically gather data on objective and subjective measures of a medical student's performance through the Electronic Residency Application Service, including medical school grades, standardized test scores, research achievements, nonacademic accomplishments, letters of recommendation, the dean's letter, and personal statements. Using these data to identify which medical students are likely to become successful residents in an academic residency program in obstetrics and gynecology is difficult and to date, not well studied. Objective To determine whether objective information in medical students' applications can help predict resident success. Method We performed a retrospective cohort study of all residents who matched into the Johns Hopkins University residency program in obstetrics and gynecology between 1994 and 2004 and entered the program through the National Resident Matching Program as a postgraduate year-1 resident. Residents were independently evaluated by faculty and ranked in 4 groups according to perceived level of success. Applications from residents in the highest and lowest group were abstracted. Groups were compared using the Fisher exact test and the Student t test. Results Seventy-five residents met inclusion criteria and 29 residents were ranked in the highest and lowest quartiles (15 in highest, 14 in lowest). Univariate analysis identified no variables as consistent predictors of resident success. Conclusion In a program designed to train academic obstetrician-gynecologists, objective data from medical students' applications did not correlate with successful resident performance in our obstetrics-gynecology residency program. We need to continue our search for evaluation criteria that can accurately and reliably select the medical students that are best fit for our specialty. PMID:21976076

  11. Submillimetre wave imaging and security: imaging performance and prediction

    Science.gov (United States)

    Appleby, R.; Ferguson, S.

    2016-10-01

    Within the European Commission Seventh Framework Programme (FP7), CONSORTIS (Concealed Object Stand-Off Real-Time Imaging for Security) has designed and is fabricating a stand-off system operating at sub-millimetre wave frequencies for the detection of objects concealed on people. This system scans people as they walk by the sensor. This paper presents the top level system design which brings together both passive and active sensors to provide good performance. The passive system operates in two bands between 100 and 600GHz and is based on a cryogen free cooled focal plane array sensor whilst the active system is a solid-state 340GHz radar. A modified version of OpenFX was used for modelling the passive system. This model was recently modified to include realistic location-specific skin temperature and to accept animated characters wearing up to three layers of clothing that move dynamically, such as those typically found in cinematography. Targets under clothing have been modelled and the performance simulated. The strengths and weaknesses of this modelling approach are discussed.

  12. Investigation into the performance of different models for predicting stutter.

    Science.gov (United States)

    Bright, Jo-Anne; Curran, James M; Buckleton, John S

    2013-07-01

    In this paper we have examined five possible models for the behaviour of the stutter ratio, SR. These were two log-normal models, two gamma models, and a two-component normal mixture model. A two-component normal mixture model was chosen with different behaviours of variance; at each locus SR was described with two distributions, both with the same mean. The distributions have difference variances: one for the majority of the observations and a second for the less well-behaved ones. We apply each model to a set of known single source Identifiler™, NGM SElect™ and PowerPlex(®) 21 DNA profiles to show the applicability of our findings to different data sets. SR determined from the single source profiles were compared to the calculated SR after application of the models. The model performance was tested by calculating the log-likelihoods and comparing the difference in Akaike information criterion (AIC). The two-component normal mixture model systematically outperformed all others, despite the increase in the number of parameters. This model, as well as performing well statistically, has intuitive appeal for forensic biologists and could be implemented in an expert system with a continuous method for DNA interpretation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  13. Predicting performance in competitive apnea diving, part II: dynamic apnoea.

    Science.gov (United States)

    Schagatay, Erika

    2010-03-01

    Part I of this series of articles identified the main physiological factors defining the limits of static apnea, while this paper reviews the factors involved when physical work is added in the dynamic distance disciplines, performed in shallow water in a swimming pool. Little scientific work has been done concerning the prerequisites and limitations of swimming with or without fins whilst breath holding to extreme limits. Apneic duration influences all competitive apnea disciplines, and can be prolonged by any means that increase gas storage or tolerance to asphyxia, or reduce metabolic rate, as reviewed in the first article. For horizontal underwater distance swimming, the main challenge is to restrict metabolism despite the work, and to direct blood flow only to areas where demand is greatest, to allow sustained function. Here, work economy, local tissue energy and oxygen stores and the anaerobic capacity of the muscles are key components. Improvements in swimming techniques and, especially in swimming with fins, equipment have already contributed to enhanced performance and may do so further. High lactate levels observed after competition swims suggest a high anaerobic component, and muscle hypoxia could ultimately limit muscle work and swimming distance. However, the frequency of syncope, especially in swimming without fins, suggests that cerebral oxygenation may often be compromised before this occurs. In these pool disciplines, safety is high and the dive can be interrupted by the competitor or safety diver within seconds. The safety routines in place during pool competitions are described.

  14. Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.

    Science.gov (United States)

    Le, Nguyen-Quoc-Khanh; Ou, Yu-Yen

    2016-07-30

    Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9-45 % and its Matthew's correlation coefficient was 0.14-0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron

  15. Predicting Performance: A Comparison of University Supervisors' Predictions and Teacher Candidates' Scores on a Teaching Performance Assessment

    Science.gov (United States)

    Sandholtz, Judith Haymore; Shea, Lauren M.

    2012-01-01

    The implementation of teaching performance assessments has prompted a range of concerns. Some educators question whether these assessments provide information beyond what university supervisors gain through their formative evaluations and classroom observations of candidates. This research examines the relationship between supervisors' predictions…

  16. Academic Performance of First-Year Students at a College of Pharmacy in East Tennessee: Models for Prediction

    Science.gov (United States)

    Clavier, Cheri Whitehead

    2013-01-01

    With the increase of students applying to pharmacy programs, it is imperative that admissions committees choose appropriate measures to analyze student readiness. The purpose of this research was to identify significant factors that predict the academic performance, defined as grade point average (GPA) at the end of the first professional year, of…

  17. Plasma property and performance prediction for mercury ion thrusters

    Science.gov (United States)

    Longhurst, G. R.; Wilbur, P. J.

    1979-01-01

    The discharge chambers of mercury ion thrusters are modelled so the principal effects and processes which govern discharge plasma properties and thruster performance are described. The conservation relations for mass, charge and energy when applied to the Maxwellian electron population in the ion production region yield equations which may be made one-dimensional by the proper choice of coordinates. Solutions to these equations with the appropriate boundary conditions give electron density and temperature profiles which agree reasonably well with measurements. It is then possible to estimate plasma properties from thruster design data and those operating parameters which are directly controllable. By varying the operating parameter inputs to the computer code written to solve these equations, perfromance curves are obtained which agree quite well with measurements.

  18. Performance prediction of electrohydrodynamic thrusters by the perturbation method

    International Nuclear Information System (INIS)

    Shibata, H.; Watanabe, Y.; Suzuki, K.

    2016-01-01

    In this paper, we present a novel method for analyzing electrohydrodynamic (EHD) thrusters. The method is based on a perturbation technique applied to a set of drift-diffusion equations, similar to the one introduced in our previous study on estimating breakdown voltage. The thrust-to-current ratio is generalized to represent the performance of EHD thrusters. We have compared the thrust-to-current ratio obtained theoretically with that obtained from the proposed method under atmospheric air conditions, and we have obtained good quantitative agreement. Also, we have conducted a numerical simulation in more complex thruster geometries, such as the dual-stage thruster developed by Masuyama and Barrett [Proc. R. Soc. A 469, 20120623 (2013)]. We quantitatively clarify the fact that if the magnitude of a third electrode voltage is low, the effective gap distance shortens, whereas if the magnitude of the third electrode voltage is sufficiently high, the effective gap distance lengthens.

  19. Prediction of the Effect of Vortex Generators on Airfoil Performance

    International Nuclear Information System (INIS)

    Sørensen, Niels N; Zahle, F; Bak, C; Vronsky, T

    2014-01-01

    Vortex Generators (VGs) are widely used by the wind turbine industry, to control the flow over blade sections. The present work describes a computational fluid dynamic procedure that can handle a geometrical resolved VG on an airfoil section. After describing the method, it is applied to two different airfoils at a Reynolds number of 3 million, the FFA- W3-301 and FFA-W3-360, respectively. The computations are compared with wind tunnel measurements from the Stuttgart Laminar Wind Tunnel with respect to lift and drag variation as function of angle of attack. Even though the method does not exactly capture the measured performance, it can be used to compare different VG setups qualitatively with respect to chord- wise position, inter and intra-spacing and inclination of the VGs already in the design phase

  20. Serum 25-hydroxyvitamin D predicts cognitive performance in adults

    Directory of Open Access Journals (Sweden)

    Darwish H

    2015-08-01

    Full Text Available Hala Darwish,1 Pia Zeinoun,2 Husam Ghusn,3,4 Brigitte Khoury,2 Hani Tamim,5 Samia J Khoury6 1Hariri School of Nursing, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 2Psychiatry Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 3Internal Medicine Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 4Geriatrics Department, Ain Wazein Hospital, El Chouf, Lebanon; 5Clinical Research Institute, Faculty of Medicine, American University of Beirut, Beirut, Lebanon; 6Neurology Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon Background: Vitamin D is an endogenous hormone known to regulate calcium levels in the body and plays a role in cognitive performance. Studies have shown an association between vitamin D deficiency and cognitive impairment in older adults. Lebanon has a high 25-hydroxyvitamin D (25(OHD deficiency prevalence across all age groups. Methods: In this cross-sectional study, we explored the cognitive performance and serum 25(OHD levels using an electrochemoluminescent immunoassay in 254 older (>60 years as well as younger (30–60 years adults. Subjects’ characteristics, including age, years of education, wearing of veil, alcohol consumption, smoking, and physical exercise, were collected. Participants were screened for depression prior to cognitive screening using the Montreal Cognitive Assessment Arabic version. Visuospatial memory was tested using the Rey Complex Figure Test and Recognition Trial, and speed of processing was assessed using the Symbol Digit Modalities test. Results: Pearson’s correlation and stepwise linear regression analyses showed that a low vitamin D level was associated with greater risk of cognitive impairment in older as well as younger adults. Conclusion: These findings suggest that correction of vitamin D needs to be explored as an intervention to prevent cognitive impairment. Prospective

  1. Performance prediction for a magnetostrictive actuator using a simplified model

    Science.gov (United States)

    Yoo, Jin-Hyeong; Jones, Nicholas J.

    2018-03-01

    Iron-Gallium alloys (Galfenol) are promising transducer materials that combine high magnetostriction, desirable mechanical properties, high permeability, and a wide operational temperature range. Most of all, the material is capable of operating under tensile stress, and is relatively resistant to shock. These materials are generally characterized using a solid, cylindrically-shaped specimen under controlled compressive stress and magnetization conditions. Because the magnetostriction strongly depends on both the applied stress and magnetization, the characterization of the material is usually conducted under controlled conditions so each parameter is varied independently of the other. However, in a real application the applied stress and magnetization will not be maintained constant during operation. Even though the controlled characterization measurement gives insight into standard material properties, usage of this data in an application, while possible, is not straight forward. This study presents an engineering modeling methodology for magnetostrictive materials based on a piezo-electric governing equation. This model suggests phenomenological, nonlinear, three-dimensional functions for strain and magnetic flux density responses as functions of applied stress and magnetic field. Load line performances as a function of maximum magnetic field input were simulated based on the model. To verify the modeling performance, a polycrystalline magnetostrictive rod (Fe-Ga alloy, Galfenol) was characterized under compressive loads using a dead-weight test setup, with strain gages on the rod and a magnetic field driving coil around the sample. The magnetic flux density through the Galfenol rod was measured with a sensing coil; the compressive loads were measured using a load cell on the bottom of the Galfenol rod. The experimental results are compared with the simulation results using the suggested model, showing good agreement.

  2. Review Of Mechanistic Understanding And Modeling And Uncertainty Analysis Methods For Predicting Cementitious Barrier Performance

    International Nuclear Information System (INIS)

    Langton, C.; Kosson, D.

    2009-01-01

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

  3. REVIEW OF MECHANISTIC UNDERSTANDING AND MODELING AND UNCERTAINTY ANALYSIS METHODS FOR PREDICTING CEMENTITIOUS BARRIER PERFORMANCE

    Energy Technology Data Exchange (ETDEWEB)

    Langton, C.; Kosson, D.

    2009-11-30

    Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various

  4. The significance and predictive value of free light chains in the urine of patients with chronic inflammatory rheumatic disease.

    Science.gov (United States)

    Bramlage, Carsten Paul; Froelich, Britta; Wallbach, Manuel; Minguet, Joan; Grupp, Clemens; Deutsch, Cornelia; Bramlage, Peter; Koziolek, Michael; Müller, Gerhard Anton

    2016-12-01

    In patients with rheumatic diseases, reliable markers for determining disease activity are scarce. One potential parameter is the level of immunoglobulin free light chains (FLCs), which is known to be elevated in the blood of patients with certain rheumatic diseases. Few studies have quantified FLCs in urine, a convenient source of test sample, in patients with different rheumatic diseases. We carried out a retrospective analysis of patients with rheumatic disease attending the University hospital of Goettingen, Germany. Subjects were included if they had urine levels of both κ and λ FLCs available and did not have myeloma. Data regarding systemic inflammation and kidney function were recorded, and FLC levels were correlated with inflammatory markers. Of the 382 patients with rheumatic disease, 40.1 % had chronic polyarthritis, 21.2 % connective tissue disease, 18.6 % spondyloarthritis and 15.7 % vasculitis. Elevated levels of κ FLCs were found for 84 % of patients and elevated λ for 52.7 %. For the patients with rheumatoid arthritis, FLCs correlated with C-reactive protein (κ, r = 0.368, p rheumatic disease, but not in κ/λ ratio. The correlation between FLCs and inflammatory markers in patients with rheumatoid arthritis demonstrates their potential for predicting disease activity.

  5. The joint effects of personality and workplace social exchange relationships in predicting task performance and citizenship performance.

    Science.gov (United States)

    Kamdar, Dishan; Van Dyne, Linn

    2007-09-01

    This field study examines the joint effects of social exchange relationships at work (leader-member exchange and team-member exchange) and employee personality (conscientiousness and agreeableness) in predicting task performance and citizenship performance. Consistent with trait activation theory, matched data on 230 employees, their coworkers, and their supervisors demonstrated interactions in which high quality social exchange relationships weakened the positive relationships between personality and performance. Results demonstrate the benefits of consonant predictions in which predictors and outcomes are matched on the basis of specific targets. We discuss theoretical and practical implications. (c) 2007 APA.

  6. Significant pre-accession factors predicting success or failure during a Marine Corps officer’s initial service obligation

    OpenAIRE

    Johnson, Jacob A.

    2015-01-01

    Approved for public release; distribution is unlimited Increasing diversity and equal opportunity in the military is a congressional and executive priority. At the same time, improving recruiting practices is a priority of the commandant of the Marine Corps. In an effort to provide information to the Marine Corps that may improve recruiting practice and enable retention of a higher quality and more diverse officer corps, probit econometric models are estimated to identify significant facto...

  7. Executive functioning performance predicts subjective and physiological acute stress reactivity: preliminary results.

    Science.gov (United States)

    Hendrawan, Donny; Yamakawa, Kaori; Kimura, Motohiro; Murakami, Hiroki; Ohira, Hideki

    2012-06-01

    Individual differences in baseline executive functioning (EF) capacities have been shown to predict state anxiety during acute stressor exposure. However, no previous studies have clearly demonstrated the relationship between EF and physiological measures of stress. The present study investigated the efficacy of several well-known EF tests (letter fluency, Stroop test, and Wisconsin Card Sorting Test) in predicting both subjective and physiological stress reactivity during acute psychosocial stress exposure. Our results show that letter fluency served as the best predictor for both types of reactivity. Specifically, the higher the letter fluency score, the lower the acute stress reactivity after controlling for the baseline stress response, as indicated by lower levels of state anxiety, negative mood, salivary cortisol, and skin conductance. Moreover, the predictive power of the letter fluency test remained significant for state anxiety and cortisol indices even after further adjustments for covariates by adding the body mass index (BMI) as a covariate. Thus, good EF performance, as reflected by high letter fluency scores, may dampen acute stress responses, which suggests that EF processes are directly associated with aspects of stress regulation. Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Learning to avoid spiders: fear predicts performance, not competence.

    Science.gov (United States)

    Luo, Xijia; Becker, Eni S; Rinck, Mike

    2018-01-05

    We used an immersive virtual environment to examine avoidance learning in spider-fearful participants. In 3 experiments, participants were asked to repeatedly lift one of 3 virtual boxes, under which either a toy car or a spider appeared and then approached the participant. Participants were not told that the probability of encountering a spider differed across boxes. When the difference was large (Exps. 1 and 2), spider-fearfuls learned to avoid spiders by lifting the few-spiders-box more often and the many-spiders-box less often than non-fearful controls did. However, they hardly managed to do so when the probability differences were small (Exp. 3), and they did not escape from threat more quickly (Exp. 2). In contrast to the observed performance differences, spider-fearfuls and non-fearfuls showed equal competence, that is comparable post-experimental knowledge about the probability to encounter spiders under the 3 boxes. The limitations and implications of the present study are discussed.

  9. Working memory capacity predicts conflict-task performance.

    Science.gov (United States)

    Gulbinaite, Rasa; Johnson, Addie

    2014-01-01

    The relationship between the ability to maintain task goals and working memory capacity (WMC) is firmly established, but evidence for WMC-related differences in conflict processing is mixed. We investigated whether WMC (measured using two complex-span tasks) mediates differences in adjustments of cognitive control in response to conflict. Participants performed a Simon task in which congruent and incongruent trials were equiprobable, but in which the proportion of congruency repetitions (congruent trials followed by congruent trials or incongruent trials followed by incongruent trials) and thus the need for trial-by-trial adjustments in cognitive control varied by block. The overall Simon effect did not depend on WMC capacity. However, for the low-WMC participants the Simon effect decreased as the proportion of congruency repetitions decreased, whereas for the high- and average-WMC participants it was relatively constant across conditions. Distribution analysis of the Simon effect showed more evidence for the inhibition of stimulus location in the low- than in the high-WMC participants, especially when the proportion of congruency repetitions was low. We hypothesize that low-WMC individuals exhibit more interference from task-irrelevant information due to weaker preparatory control prior to stimulus presentation and, thus, stronger reliance on reactive recruitment of cognitive control.

  10. Investigation and Prediction of RF Window Performance in APT Accelerators

    International Nuclear Information System (INIS)

    Humphries, S. Jr.

    1997-01-01

    The work described in this report was performed between November 1996 and May 1997 in support of the APT (Accelerator Production of Tritium) Program at Los Alamos National Laboratory. The goal was to write and to test computer programs for charged particle orbits in RF fields. The well-documented programs were written in portable form and compiled for standard personal computers for easy distribution to LANL researchers. They will be used in several APT applications including the following. Minimization of multipactor effects in the moderate β superconducting linac cavities under design for the APT accelerator. Investigation of suppression techniques for electron multipactoring in high-power RF feedthroughs. Modeling of the response of electron detectors for the protection of high power RF vacuum windows. In the contract period two new codes, Trak-RF and WaveSim, were completed and several critical benchmark etests were carried out. Trak-RF numerically tracks charged particle orbits in combined electrostatic, magnetostatic and electromagnetic fields. WaveSim determines frequency-domain RF field solutions and provides a key input to Trak-RF. The two-dimensional programs handle planar or cylindrical geometries. They have several unique characteristics

  11. Visuo-motor coordination ability predicts performance with brain-computer interfaces controlled by modulation of sensorimotor rhythms (SMR

    Directory of Open Access Journals (Sweden)

    Eva Maria Hammer

    2014-08-01

    Full Text Available Modulation of sensorimotor rhythms (SMR was suggested as a control signal for brain-computer interfaces (BCI. Yet, there is a population of users estimated between 10 to 50% not able to achieve reliable control and only about 20% of users achieve high (80-100% performance. Predicting performance prior to BCI use would facilitate selection of the most feasible system for an individual, thus constitute a practical benefit for the user, and increase our knowledge about the correlates of BCI control. In a recent study, we predicted SMR-BCI performance from psychological variables that were assessed prior to the BCI sessions and BCI control was supported with machine-learning techniques. We described two significant psychological predictors, namely the visuo-motor coordination ability and the ability to concentrate on the task. The purpose of the current study was to replicate these results thereby validating these predictors within a neurofeedback based SMR-BCI that involved no machine learning. Thirty-three healthy BCI novices participated in a calibration session and three further neurofeedback training sessions. Two variables were related with mean SMR-BCI performance: (1 A measure for the accuracy of fine motor skills, i.e. a trade for a person’s visuo-motor control ability and (2 subject’s attentional impulsivity. In a linear regression they accounted for almost 20% in variance of SMR-BCI performance, but predictor (1 failed significance. Nevertheless, on the basis of our prior regression model for sensorimotor control ability we could predict current SMR-BCI performance with an average prediction error of M = 12.07%. In more than 50% of the participants, the prediction error was smaller than 10%. Hence, psychological variables played a moderate role in predicting SMR-BCI performance in a neurofeedback approach that involved no machine learning. Future studies are needed to further consolidate (or reject the present predictors.

  12. The European Academy laparoscopic “Suturing Training and Testing’’ (SUTT) significantly improves surgeons’ performance

    Science.gov (United States)

    Sleiman, Z.; Tanos, V.; Van Belle, Y.; Carvalho, J.L.; Campo, R.

    2015-01-01

    The efficiency of suturing training and testing (SUTT) model by laparoscopy was evaluated, measuring the suturingskill acquisition of trainee gynecologists at the beginning and at the end of a teaching course. During a workshop organized by the European Academy of Gynecological Surgery (EAGS), 25 participants with three different experience levels in laparoscopy (minor, intermediate and major) performed the 4 exercises of the SUTT model (Ex 1: both hands stitching and continuous suturing, Ex 2: right hand stitching and intracorporeal knotting, Ex 3: left hand stitching and intracorporeal knotting, Ex 4: dominant hand stitching, tissue approximation and intracorporeal knotting). The time needed to perform the exercises is recorded for each trainee and group and statistical analysis used to note the differences. Overall, all trainees achieved significant improvement in suturing time (p psychomotor skills, surgery, teaching, training suturing model. PMID:26977264

  13. Evaluation of ischemic corticospinal tract damage by diffusion tensor MRI. Its significance to predict functional outcome of corona radiata infarct

    International Nuclear Information System (INIS)

    Tanaka, Hideki

    2010-01-01

    Motor impairment is one of the most frequent symptoms among stroke patients and often leads to poststroke dependency. Recent advances of diffusion tensor MR imaging made it possible to identify corticospinal tract (CST) three-dimensionally and evaluate structural damage, so precise evaluation of the ischemic CST damage became feasible.Motor impairment, lesion size and location upon diffusion weighted MR image and clinical outcome were assessed in 23 acute to subacute capsular and corona radiata infarct patients. According to the lesion size, patients were grouped into A, maximal diameter below 15 mm and B, that above 15 mm. Motor impairment was graded severe: limb movement synergy level, moderate: selective muscle activity possible and mild: isolated movements well co-ordinated, each corresponding to Brunnstrom stage 1-3, 4-5, and 6, respectively. Outcome at the time of discharge was assessed by modified Rankin Scale (mRS), discharge destination and length of hospital stay were also registered. Diffusion tensor MR imaging was conducted in 15 corona radiata infarct patients at 2.3+-2.2 days from the onset of the clinical symptoms. CST was 3-dimensionally identified with dTV. II. SR and Volume-one 1.72 and CST-FA ratio (ipsi-/contralesional CST-FA) and CST-Area% (CST lesion free area/whole CST area) were obtained at the level where ischemic damage was most prominent and correlation of these parameters to motor impairment and clinical outcome was studied. CST-FA ratio and CST-Area% were in good correlation to motor impairment at presentation. Patients with severe motor impairment had lower CST-FA ratio and CSF-Area% than those with moderate or mild. CST-FA ratio was 0.73+-0.22 in patients with poor clinical outcome (mRS 3-6) and 0.93+-0.09 with good clinical outcome (mRS 0-2) (p=0.038). Diffusion tensor MR imaging is useful in evaluating motor impairment and predicting functional outcome of corona radiata infarct patient in the acute to subacute stage. (author)

  14. Sebum and Hydration Levels in Specific Regions of Human Face Significantly Predict the Nature and Diversity of Facial Skin Microbiome.

    Science.gov (United States)

    Mukherjee, Souvik; Mitra, Rupak; Maitra, Arindam; Gupta, Satyaranjan; Kumaran, Srikala; Chakrabortty, Amit; Majumder, Partha P

    2016-10-27

    The skin microbiome varies across individuals. The causes of these variations are inadequately understood. We tested the hypothesis that inter-individual variation in facial skin microbiome can be significantly explained by variation in sebum and hydration levels in specific facial regions of humans. We measured sebum and hydration from forehead and cheek regions of healthy female volunteers (n = 30). Metagenomic DNA from skin swabs were sequenced for V3-V5 regions of 16S rRNA gene. Altogether, 34 phyla were identified; predominantly Actinobacteria (66.3%), Firmicutes (17.7%), Proteobacteria (13.1%) and Bacteroidetes (1.4%). About 1000 genera were identified; predominantly Propionibacterium (58.6%), Staphylococcus (8.6%), Streptococcus (4.0%), Corynebacterium (3.6%) and Paracoccus (3.3%). A subset (n = 24) of individuals were sampled two months later. Stepwise multiple regression analysis showed that cheek sebum level was the most significant predictor of microbiome composition and diversity followed by forehead hydration level; forehead sebum and cheek hydration levels were not. With increase in cheek sebum, the prevalence of Actinobacteria (p = 0.001)/Propionibacterium (p = 0.002) increased, whereas microbiome diversity decreased (Shannon Index, p = 0.032); this was opposite for other phyla/genera. These trends were reversed for forehead hydration levels. Therefore, the nature and diversity of facial skin microbiome is jointly determined by site-specific lipid and water levels in the stratum corneum.

  15. Predictions from the cloud: using data science to predict sports performance

    NARCIS (Netherlands)

    Blaauw, Frank; Emerencia, Armando Celino; den Hartigh, Jan Rudolf; Milovanović, Marko; Stoter, Inge; de Jonge, Peter

    2018-01-01

    In sport science, a major aim is to unravel the variables and parameters that influence sports performance. A key requirement for investigating these parameters is the availability of high quality data. More specifically, data that contains the variables of interest, and data that could be analyzed

  16. Brake response time is significantly impaired after total knee arthroplasty: investigation of performing an emergency stop while driving a car.

    Science.gov (United States)

    Jordan, Maurice; Hofmann, Ulf-Krister; Rondak, Ina; Götze, Marco; Kluba, Torsten; Ipach, Ingmar

    2015-09-01

    The objective of this study was to investigate whether total knee arthroplasty (TKA) impairs the ability to perform an emergency stop. An automatic transmission brake simulator was developed to evaluate total brake response time. A prospective repeated-measures design was used. Forty patients (20 left/20 right) were measured 8 days and 6, 12, and 52 wks after surgery. Eight days postoperative total brake response time increased significantly by 30% in right TKA and insignificantly by 2% in left TKA. Brake force significantly decreased by 35% in right TKA and by 25% in left TKA during this period. Baseline values were reached at week 12 in right TKA; the impairment of outcome measures, however, was no longer significant at week 6 compared with preoperative values. Total brake response time and brake force in left TKA fell below baseline values at weeks 6 and 12. Brake force in left TKA was the only outcome measure significantly impaired 8 days postoperatively. This study highlights that categorical statements cannot be provided. This study's findings on automatic transmission driving suggest that right TKA patients may resume driving 6 wks postoperatively. Fitness to drive in left TKA is not fully recovered 8 days postoperatively. If testing is not available, patients should refrain from driving until they return from rehabilitation.

  17. Predicting the Performance and Survival of Islamic Banks in Malaysia to Achieve Growth Sustainability

    Directory of Open Access Journals (Sweden)

    Mazuin Sapuan Noraina

    2017-01-01

    Full Text Available In Malaysia, the growth of the Islamic financial industry has increased tremendously in line with the Government’s ambition to make Malaysia as an international hub for Islamic finance since 2010. With the increasing number of foreign players in this industry plus with the increasing demand from domestic and foreign customers would further enhance the possibility for Malaysia to achieve this ambition. Currently, according to the Economic Transformation Programme, 2012 Malaysia is the world’s third largest market for Shariah assets that cover Islamic banks, Takaful, and sukuk. Malaysia as one of the main contributors to the global Islamic financial assets with Islamic assets in Malaysia grew by 23.8% in 2011 from RM350.8bil to RM434.6bil. The issues of predicting the performance and the survival of Islamic Banks in Malaysia become amongst crucial issues in academic research. By employing multi – layer perceptron neural network and pooled regression, we found that total assets/ size of the Islamic banks (GROWTH have high weightage and significantly influence in predicting the performance and the survival of Islamic banks in Malaysia. With the increasing number of Islamic banking institutions in Malaysia, this study can give insight on the sustainability of the Islamic banking system in Malaysia for the benefit of the investors, shareholder and depositors.

  18. Free Recall Episodic Memory Performance Predicts Dementia Ten Years prior to Clinical Diagnosis: Findings from the Betula Longitudinal Study

    Directory of Open Access Journals (Sweden)

    Carl-Johan Boraxbekk

    2015-05-01

    Full Text Available Background/Aims: Early dementia diagnosis is a considerable challenge. The present study examined the predictive value of cognitive performance for a future clinical diagnosis of late-onset Alzheimer's disease or vascular dementia in a random population sample. Methods: Cognitive performance was retrospectively compared between three groups of participants from the Betula longitudinal cohort. Group 1 developed dementia 11-22 years after baseline testing (n = 111 and group 2 after 1-10 years (n = 280; group 3 showed no deterioration towards dementia during the study period (n = 2,855. Multinomial logistic regression analysis was used to investigate the predictive value of tests reflecting episodic memory performance, semantic memory performance, visuospatial ability, and prospective memory performance. Results: Age- and education-corrected performance on two free recall episodic memory tests significantly predicted dementia 10 years prior to clinical diagnosis. Free recall performance also predicted dementia 11-22 years prior to diagnosis when controlling for education, but not when age was added to the model. Conclusion: The present results support the suggestion that two free recall-based tests of episodic memory function may be useful for detecting individuals at risk of developing dementia 10 years prior to clinical diagnosis.

  19. Predicting performance in a first engineering calculus course: implications for interventions

    Science.gov (United States)

    Hieb, Jeffrey L.; Lyle, Keith B.; Ralston, Patricia A. S.; Chariker, Julia

    2015-01-01

    At the University of Louisville, a large, urban institution in the south-east United States, undergraduate engineering students take their mathematics courses from the school of engineering. In the fall of their freshman year, engineering students take Engineering Analysis I, a calculus-based engineering analysis course. After the first two weeks of the semester, many students end up leaving Engineering Analysis I and moving to a mathematics intervention course. In an effort to retain more students in Engineering Analysis I, the department collaborated with university academic support services to create a summer intervention programme. Students were targeted for the summer programme based on their score on an algebra readiness exam (ARE). In a previous study, the ARE scores were found to be a significant predictor of retention and performance in Engineering Analysis I. This study continues that work, analysing data from students who entered the engineering school in the fall of 2012. The predictive validity of the ARE was verified, and a hierarchical linear regression model was created using math American College Testing (ACT) scores, ARE scores, summer intervention participation, and several metacognitive and motivational factors as measured by subscales of the Motivated Strategies for Learning Questionnaire. In the regression model, ARE score explained an additional 5.1% of the variation in exam performance in Engineering Analysis I beyond math ACT score. Students took the ARE before and after the summer interventions and scores were significantly higher following the intervention. However, intervention participants nonetheless had lower exam scores in Engineering Analysis I. The following factors related to motivation and learning strategies were found to significantly predict exam scores in Engineering Analysis I: time and study environment management, internal goal orientation, and test anxiety. The adjusted R2 for the full model was 0.42, meaning that the

  20. Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

    Science.gov (United States)

    Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

    2013-12-01

    Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

  1. Significant manipulation of output performance of a bridge-structured spin valve magnetoresistance sensor via an electric field

    Science.gov (United States)

    Zhang, Yue; Yan, Baiqian; Ou-Yang, Jun; Wang, Xianghao; Zhu, Benpeng; Chen, Shi; Yang, Xiaofei

    2016-01-01

    Through principles of spin-valve giant magnetoresistance (SV-GMR) effect and its application in magnetic sensors, we have investigated electric-field control of the output performance of a bridge-structured Co/Cu/NiFe/IrMn SV-GMR sensor on a PZN-PT piezoelectric substrate using the micro-magnetic simulation. We centered on the influence of the variation of uniaxial magnetic anisotropy constant (K) of Co on the output of the bridge, and K was manipulated via the stress of Co, which is generated from the strain of a piezoelectric substrate under an electric field. The results indicate that when K varies between 2 × 104 J/m3 and 10 × 104 J/m3, the output performance can be significantly manipulated: The linear range alters from between -330 Oe and 330 Oe to between -650 Oe and 650 Oe, and the sensitivity is tuned by almost 7 times, making it possible to measure magnetic fields with very different ranges. According to the converse piezoelectric effect, we have found that this variation of K can be realized by applying an electric field with the magnitude of about 2-20 kV/cm on a PZN-PT piezoelectric substrate, which is realistic in application. This result means that electric-control of SV-GMR effect has potential application in developing SV-GMR sensors with improved performance.

  2. Predicting meaningful outcomes to medication and self-help treatments for binge-eating disorder in primary care: The significance of early rapid response.

    Science.gov (United States)

    Grilo, Carlos M; White, Marney A; Masheb, Robin M; Gueorguieva, Ralitza

    2015-04-01

    We examined rapid response among obese patients with binge-eating disorder (BED) in a randomized clinical trial testing antiobesity medication and self-help cognitive-behavioral therapy (shCBT), alone and in combination, in primary-care settings. One hundred four obese patients with BED were randomly assigned to 1 of 4 treatments: sibutramine, placebo, shCBT + sibutramine, or shCBT + placebo. Treatments were delivered by generalist primary-care physicians and the medications were given double-blind. Independent assessments were performed by trained and monitored doctoral research clinicians monthly throughout treatment, posttreatment (4 months), and at 6- and 12-month follow-ups (i.e., 16 months after randomization). Rapid response, defined as ≥65% reduction in binge eating by the fourth treatment week, was used to predict outcomes. Rapid response characterized 47% of patients, was unrelated to demographic and baseline clinical characteristics, and was significantly associated, prospectively, with remission from binge eating at posttreatment (51% vs. 9% for nonrapid responders), 6-month (53% vs. 23.6%), and 12-month (46.9% vs. 23.6%) follow-ups. Mixed-effects model analyses revealed that rapid response was significantly associated with greater decreases in binge-eating or eating-disorder psychopathology, depression, and percent weight loss. Our findings, based on a diverse obese patient group receiving medication and shCBT for BED in primary-care settings, indicate that patients who have a rapid response achieve good clinical outcomes through 12-month follow-ups after ending treatment. Rapid response represents a strong prognostic indicator of clinically meaningful outcomes, even in low-intensity medication and self-help interventions. Rapid response has important clinical implications for stepped-care treatment models for BED. clinicaltrials.gov: NCT00537810 (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  3. Goal orientation and work role performance: predicting adaptive and proactive work role performance through self-leadership strategies.

    Science.gov (United States)

    Marques-Quinteiro, Pedro; Curral, Luís Alberto

    2012-01-01

    This article explores the relationship between goal orientation, self-leadership dimensions, and adaptive and proactive work role performances. The authors hypothesize that learning orientation, in contrast to performance orientation, positively predicts proactive and adaptive work role performances and that this relationship is mediated by self-leadership behavior-focused strategies. It is posited that self-leadership natural reward strategies and thought pattern strategies are expected to moderate this relationship. Workers (N = 108) from a software company participated in this study. As expected, learning orientation did predict adaptive and proactive work role performance. Moreover, in the relationship between learning orientation and proactive work role performance through self-leadership behavior-focused strategies, a moderated mediation effect was found for self-leadership natural reward and thought pattern strategies. In the end, the authors discuss the results and implications are discussed and future research directions are proposed.

  4. Comparison of nuclear safety research reactor (TRIGA-ACPR) performance with analytical prediction

    International Nuclear Information System (INIS)

    West, G.B.; Whittemore, W.L.

    1976-01-01

    The NSRR was taken critical on June 30, 1975 at the Japan Atomic Energy Research Institute - Tokai-mura, Japan. Following initial core loading and control rod calibration, a series of pulsing tests was performed to characterize the performance of the reactor. A comparison has been made of performance parameters actually measured in the 157 element core versus predicted values based upon design analyses. The nuclear parameters measured were quite close to prediction. A $4.70 pulse produced a minimum period of 1.12 msec, a peak power of 20,500 MW and yielded a prompt energy release of 103 MW-sec. Pulse tests with experimental UO 2 fuel pins in the central irradiation cavity have produced 320 cal/gm, averaged at the axial center of 10% enriched UO 2 , for a 100 MW-sec pulse. The pulse rods for the NSRR contain B 4 C enriched to about 93 percent in Boron-10 in order to achieve maximum design performance with only three pulse rods. The total worth for the three transient rods was measured to be about $5.05 (vs $5.07 calculated for the 165 element core), thus verifying the effectiveness of the Boron-10 enrichment to achieve the desired result. Analysis of fuel temperature measurements made in the NSRR show that, for fuel temperatures produced during pulsing greater than 900 deg. C, heat transfer in the 0.010-inch gap between fuel and clad is enhanced by the minor outgassing of hydrogen which is characteristic of that temperature region. The hydrogen is normally all reabsorbed within about 100 sec of maximum temperature, at which time the heat transfer is characteristic of air (or argon) in the gap. In some of the temperature-instrumented elements, however, all of the hydrogen was not reabsorbed and as a result these elements gave significantly lower temperatures for high power steady state operation than were recorded prior to pulsing. In general, the NSRR parameters measured during startup were quite close to analytical prediction and the overall performance of the

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

    Directory of Open Access Journals (Sweden)

    Björn U. Christ

    2018-04-01

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

  6. Predicting race performance in triathlon: the role of perfectionism, achievement goals, and personal goal setting.

    Science.gov (United States)

    Stoeber, Joachim; Uphill, Mark A; Hotham, Sarah

    2009-04-01

    The question of how perfectionism affects performance is highly debated. Because empirical studies examining perfectionism and competitive sport performance are missing, the present research investigated how perfectionism affected race performance and what role athletes' goals played in this relationship in two prospective studies with competitive triathletes (Study 1: N = 112; Study 2: N = 321). Regression analyses showed that perfectionistic personal standards, high performance-approach goals, low performance-avoidance goals, and high personal goals predicted race performance beyond athletes' performance level. Moreover, the contrast between performance-avoidance and performance-approach goals mediated the relationship between perfectionistic personal standards and performance, whereas personal goal setting mediated the relationship between performance-approach goals and performance. The findings indicate that perfectionistic personal standards do not undermine competitive performance, but are associated with goals that help athletes achieve their best possible performance.

  7. A human capital predictive model for agent performance in contact centres

    Directory of Open Access Journals (Sweden)

    Chris Jacobs

    2011-10-01

    Research purpose: The primary focus of this article was to develop a theoretically derived human capital predictive model for agent performance in contact centres and Business Process Outsourcing (BPO based on a review of current empirical research literature. Motivation for the study: The study was motivated by the need for a human capital predictive model that can predict agent and overall business performance. Research design: A nonempirical (theoretical research paradigm was adopted for this study and more specifically a theory or model-building approach was followed. A systematic review of published empirical research articles (for the period 2000–2009 in scholarly search portals was performed. Main findings: Eight building blocks of the human capital predictive model for agent performance in contact centres were identified. Forty-two of the human capital contact centre related articles are detailed in this study. Key empirical findings suggest that person– environment fit, job demands-resources, human resources management practices, engagement, agent well-being, agent competence; turnover intention; and agent performance are related to contact centre performance. Practical/managerial implications: The human capital predictive model serves as an operational management model that has performance implications for agents and ultimately influences the contact centre’s overall business performance. Contribution/value-add: This research can contribute to the fields of human resource management (HRM, human capital and performance management within the contact centre and BPO environment.

  8. Driving and Low Vision: Validity of Assessments for Predicting Performance of Drivers

    Science.gov (United States)

    Strong, J. Graham; Jutai, Jeffrey W.; Russell-Minda, Elizabeth; Evans, Mal

    2008-01-01

    The authors conducted a systematic review to examine whether vision-related assessments can predict the driving performance of individuals who have low vision. The results indicate that measures of visual field, contrast sensitivity, cognitive and attention-based tests, and driver screening tools have variable utility for predicting real-world…

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

    Science.gov (United States)

    Ye, Cheng; Biswas, Gautam

    2014-01-01

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

  10. A Prediction Model for Community Colleges Using Graduation Rate as the Performance Indicator

    Science.gov (United States)

    Moosai, Susan

    2010-01-01

    In this thesis a prediction model using graduation rate as the performance indicator is obtained for community colleges for three cohort years, 2003, 2004, and 2005 in the states of California, Florida, and Michigan. Multiple Regression analysis, using an aggregate of seven predictor variables, was employed in determining this prediction model.…

  11. Numerical prediction of a bulb turbine performance hill chart through RANS simulations

    International Nuclear Information System (INIS)

    Guénette, V; Houde, S; Ciocan, G D; Deschênes, C; Dumas, G; Huang, J

    2012-01-01

    Within the framework of an international research consortium on low-head hydraulic turbine flow dynamics, the predictive behavior of Reynolds Averaged Navier-Stokes (RANS) simulations of the efficiency (η) hill chart of a bulb turbine is investigated. The paper presents the impacts of the blade tip gap and the hub gaps on performance predictions.

  12. Prediction of the aerodynamic performance of the Mexico rotor by using airfoil data extracted from CFD

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Xu, Haoran

    2013-01-01

    Blade Element Momentum (BEM) theory is a widely used technique for prediction of wind turbine aerodynamics performance, but the reliability of airfoil data is an important factor to improve the prediction accuracy of aerodynamic loads and power using a BEM code. The airfoil characteristics used...

  13. Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Xu, Haoran

    2014-01-01

    Blade element momentum (BEM) theory with airfoil data is a widely used technique for prediction of wind turbine aerodynamic performance, but the reliability of the airfoil data is an important factor for the prediction accuracy of aerodynamic loads and power. The airfoil characteristics used in BEM...

  14. Hyperformance: predicting high-speed performance of a b-double

    CSIR Research Space (South Africa)

    Berman, Robert J

    2016-11-01

    Full Text Available of the vehicles. The prediction model bridges that gap in the form of a light-weight methodology to predict the PBS performance of a new vehicle design given a set of vehicle input data. Such a model was developed for typical South African 9-axle B-double PBS...

  15. Predicting Eight Grade Students' Equation Solving Performances via Concepts of Variable and Equality

    Science.gov (United States)

    Ertekin, Erhan

    2017-01-01

    This study focused on how two algebraic concepts- equality and variable- predicted 8th grade students' equation solving performance. In this study, predictive design as a correlational research design was used. Randomly selected 407 eight-grade students who were from the central districts of a city in the central region of Turkey participated in…

  16. A multi-source, multi-study investigation of job performance prediction by political skill

    DEFF Research Database (Denmark)

    Blickle, G.; Ferris, G.R.; Munyon, T.P.

    2011-01-01

    -sectional and longitudinal designs, this research tested the hypotheses that employee political skill, measured from the perspective of employees' assessor A, will positively predict job performance rated by assessor B (i.e. Hypothesis 1a), and vice versa, that employee political skill measured by assessor B will predict...

  17. When should fractional flow reserve be performed to assess the significance of borderline coronary artery lesions: Derivation of a simplified scoring system.

    Science.gov (United States)

    Matar, Fadi A; Falasiri, Shayan; Glover, Charles B; Khaliq, Asma; Leung, Calvin C; Mroue, Jad; Ebra, George

    2016-11-01

    To derive a simplified scoring system (SSS) that can assist in selecting patients who would benefit from the application of fractional flow reserve (FFR). Angiographers base decisions to perform FFR on their interpretation of % diameter stenosis (DS), which is subject to variability. Recent studies have shown that the amount of myocardium at jeopardy is an important factor in determining the degree of hemodynamic compromise. We conducted a retrospective multivariable analysis to identify independent predictors of hemodynamic compromise in 289 patients with 317 coronary vessels undergoing FFR. A SSS was derived using the odds ratios as a weighted factor. The receiver operator characteristics curve was used to identify the optimal cutoff (≥3) to discern a functionally significant lesion (FFR≤0.8). Male gender, left anterior descending artery apical wrap, disease proximal to lesion, minimal lumen diameter and % DS predicted abnormal FFR (≤0.8) and lesion location in the left circumflex predicted a normal FFR. Using a cutoff score of ≥3 on the SSS, a specificity of 90.4% (95% CI: 83.0-95.3) and a sensitivity of 38.0% (95% CI: 31.5-44.9) was generated with a positive predictive value of 89.0% (95% CI: 80.7%-94.6%) and negative predictive value of 41.6% (95% CI: 35.1%-48.3%). The decision to use FFR should be based not only on the % DS but also the size of the myocardial mass jeopardized. A score of ≥3 on the SSS should prompt further investigation with a pressure wire. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  18. Building Predictive Human Performance Models of Skill Acquisition in a Data Entry Task

    National Research Council Canada - National Science Library

    Fu, Wai-Tat; Gonzalez, Cleotilde; Healy, Alice F; Kole, James A; Bourne, Jr., Lyle E

    2006-01-01

    .... Since data entry is a central component in most human-machine interaction, a predictive model of performance will provide useful information that informs interface design and effectiveness of training...

  19. In vitro models for the prediction of in vivo performance of oral dosage forms

    NARCIS (Netherlands)

    Kostewicz, E.S.; Abrahamsson, B.; Brewster, M.; Brouwers, J.; Butler, J.; Carlert, S.; Dickinson, P.A.; Dressman, J.; Holm, R.; Klein, S.; Mann, J.; McAllister, M.; Minekus, M.; Muenster, U.; Müllertz, A.; Verwei, M.; Vertzoni, M.; Weitschies, W.; Augustijns, P.

    2014-01-01

    Accurate prediction of the in vivo biopharmaceutical performance of oral drug formulations is critical to efficient drug development. Traditionally, in vitro evaluation of oral drug formulations has focused on disintegration and dissolution testing for quality control (QC) purposes. The connection

  20. Biological lifestyle factors in adult distance education: predicting cognitive and learning performance

    NARCIS (Netherlands)

    Gijselaers, Jérôme

    2015-01-01

    Gijselaers, H. J. M. (2015, 20 October). Biological lifestyle factors in adult distance education: predicting cognitive and learning performance. Presentation given for the inter-faculty Data Science group at the Open University of the Netherlands, Heerlen, The Netherlands.

  1. Mean streamline analysis for performance prediction of cross-flow fans

    International Nuclear Information System (INIS)

    Kim, Jae Won; Oh, Hyoung Woo

    2004-01-01

    This paper presents the mean streamline analysis using the empirical loss correlations for performance prediction of cross-flow fans. Comparison of overall performance predictions with test data of a cross-flow fan system with a simplified vortex wall scroll casing and with the published experimental characteristics for a cross-flow fan has been carried out to demonstrate the accuracy of the proposed method. Predicted performance curves by the present mean streamline analysis agree well with experimental data for two different cross-flow fans over the normal operating conditions. The prediction method presented herein can be used efficiently as a tool for the preliminary design and performance analysis of general-purpose cross-flow fans

  2. When bad stress goes good: increased threat reactivity predicts improved category learning performance.

    Science.gov (United States)

    Ell, Shawn W; Cosley, Brandon; McCoy, Shannon K

    2011-02-01

    The way in which we respond to everyday stressors can have a profound impact on cognitive functioning. Maladaptive stress responses in particular are generally associated with impaired cognitive performance. We argue, however, that the cognitive system mediating task performance is also a critical determinant of the stress-cognition relationship. Consistent with this prediction, we observed that stress reactivity consistent with a maladaptive, threat response differentially predicted performance on two categorization tasks. Increased threat reactivity predicted enhanced performance on an information-integration task (i.e., learning is thought to depend upon a procedural-based memory system), and a (nonsignificant) trend for impaired performance on a rule-based task (i.e., learning is thought to depend upon a hypothesis-testing system). These data suggest that it is critical to consider both variability in the stress response and variability in the cognitive system mediating task performance in order to fully understand the stress-cognition relationship.

  3. Prediction of Rowing Ergometer Performance from Functional Anaerobic Power, Strength and Anthropometric Components

    Directory of Open Access Journals (Sweden)

    Akça Firat

    2014-07-01

    Full Text Available The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE. Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s. Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s. As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.

  4. User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.

    Science.gov (United States)

    Ahn, Minkyu; Cho, Hohyun; Ahn, Sangtae; Jun, Sung C

    2018-01-01

    Performance variation is a critical issue in motor imagery brain-computer interface (MI-BCI), and various neurophysiological, psychological, and anatomical correlates have been reported in the literature. Although the main aim of such studies is to predict MI-BCI performance for the prescreening of poor performers, studies which focus on the user's sense of the motor imagery process and directly estimate MI-BCI performance through the user's self-prediction are lacking. In this study, we first test each user's self-prediction idea regarding motor imagery experimental datasets. Fifty-two subjects participated in a classical, two-class motor imagery experiment and were asked to evaluate their easiness with motor imagery and to predict their own MI-BCI performance. During the motor imagery experiment, an electroencephalogram (EEG) was recorded; however, no feedback on motor imagery was given to subjects. From EEG recordings, the offline classification accuracy was estimated and compared with several questionnaire scores of subjects, as well as with each subject's self-prediction of MI-BCI performance. The subjects' performance predictions during motor imagery task showed a high positive correlation ( r = 0.64, p performance even without feedback information. This implies that the human brain is an active learning system and, by self-experiencing the endogenous motor imagery process, it can sense and adopt the quality of the process. Thus, it is believed that users may be able to predict MI-BCI performance and results may contribute to a better understanding of low performance and advancing BCI.

  5. Hip external rotation strength predicts hop performance after anterior cruciate ligament reconstruction.

    Science.gov (United States)

    Kline, Paul W; Burnham, Jeremy; Yonz, Michael; Johnson, Darren; Ireland, Mary Lloyd; Noehren, Brian

    2018-04-01

    Quadriceps strength and single-leg hop performance are commonly evaluated prior to return to sport after anterior cruciate ligament reconstruction (ACLR). However, few studies have documented potential hip strength deficits after ACLR, or ascertained the relative contribution of quadriceps and hip strength to hop performance. Patients cleared for return to sports drills after ACLR were compared to a control group. Participants' peak isometric knee extension, hip abduction, hip extension, and hip external rotation (HER) strength were measured. Participants also performed single-leg hops, timed hops, triple hops, and crossover hops. Between-limb comparisons for the ACLR to control limb and the non-operative limb were made using independent two-sample and paired sample t tests. Pearson's correlations and stepwise multiple linear regression were used to determine the relationships and predictive ability of limb strength, graft type, sex, and limb dominance to hop performance. Sixty-five subjects, 20 ACLR [11F, age 22.8 (15-45) years, 8.3 ± 2 months post-op, mass 70.47 ± 12.95 kg, height 1.71 ± 0.08 m, Tegner 5.5 (3-9)] and 45 controls [22F, age 25.8 (15-45) years, mass 74.0 ± 15.2 kg, height 1.74 ± 0.1 m, Tegner 6 (3-7)], were tested. Knee extension (4.4 ± 1.5 vs 5.4 ± 1.8 N/kg, p = 0.02), HER (1.4 ± 0.4 vs 1.7 ± 0.5 N/kg, p = 0.04), single-leg hop (146 ± 37 vs 182 ± 38% limb length, p hop (417 ± 106 vs 519 ± 102% limb length, p hop (3.3 ± 2.0 vs 2.3 ± 0.6 s, p hop (364 ± 107 vs 446 ± 123% limb length, p = 0.01) were significantly impaired in the operative versus control subject limbs. Similar deficits existed between the operative and non-operative limbs. Knee extension and HER strength were significantly correlated with each of the hop tests, but only HER significantly predicted hop performance. After ACLR, patients have persistent HER strength, knee extension strength, and hop test deficits in the

  6. A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance

    Science.gov (United States)

    Astrand, Elaine

    2018-06-01

    Objective. Working memory (WM), crucial for successful behavioral performance in most of our everyday activities, holds a central role in goal-directed behavior. As task demands increase, inducing higher WM load, maintaining successful behavioral performance requires the brain to work at the higher end of its capacity. Because it is depending on both external and internal factors, individual WM load likely varies in a continuous fashion. The feasibility to extract such a continuous measure in time that correlates to behavioral performance during a working memory task remains unsolved. Approach. Multivariate pattern decoding was used to test whether a decoder constructed from two discrete levels of WM load can generalize to produce a continuous measure that predicts task performance. Specifically, a linear regression with L2-regularization was chosen with input features from EEG oscillatory activity recorded from healthy participants while performing the n-back task, n\\in [1,2] . Main results. The feasibility to extract a continuous time-resolved measure that correlates positively to trial-by-trial working memory task performance is demonstrated (r  =  0.47, p  <  0.05). It is furthermore shown that this measure allows to predict task performance before action (r  =  0.49, p  <  0.05). We show that the extracted continuous measure enables to study the temporal dynamics of the complex activation pattern of WM encoding during the n-back task. Specifically, temporally precise contributions of different spectral features are observed which extends previous findings of traditional univariate approaches. Significance. These results constitute an important contribution towards a wide range of applications in the field of cognitive brain–machine interfaces. Monitoring mental processes related to attention and WM load to reduce the risk of committing errors in high-risk environments could potentially prevent many devastating consequences or

  7. Neither here, nor there: impression management does not predict expatriate adjustment and job performance

    OpenAIRE

    HANNAH JACKSON FOLDES; DENIZ S. ONES; HANDAN KEPIR SINANGIL

    2006-01-01

    Social desirability scale scores reflect substantive individual differences related to personality. The objective of the current study was to examine whether social desirability, and impression management specifically (a component of social desirability), is predictive of adjustment and job performance for expatriates. Based on theoretical considerations, it was proposed that impression management might be linked to expatriate job performance in a predictive and mediated relationship through ...

  8. Prediction of tunnel boring machine performance using machine and rock mass data

    International Nuclear Information System (INIS)

    Dastgir, G.

    2012-01-01

    Performance of the tunnel boring machine and its prediction by different methods has been a hot issue since the first TBM came into being. For the sake of safe and sound transport, improvement of hydro-power, mining, civil and many other tunneling projects that cannot be driven efficiently and economically by conventional drill and blast, TBMs are quite frequently used. TBM parameters and rock mass properties, which heavily influence machine performance, should be estimated or known before choice of TBM-type and start of excavation. By applying linear regression analysis (SPSS19), fuzzy logic tools and a special Math-Lab code on actual field data collected from seven TBM driven tunnels (Hieflau expansion, Queen water tunnel, Vereina, Hemerwald, Maen, Pieve and Varzo tunnel), an attempt was made to provide prediction of rock mass class (RMC), rock fracture class (RFC), penetration rate (PR) and advance rate (AR). For detailed analysis of TBM performance, machine parameters (thrust, machine rpm, torque, power etc.), machine types and specification and rock mass properties (UCS, discontinuity in rock mass, RMC, RFC, RMR, etc.) were analyzed by 3-D surface plotting using statistical software R. Correlations between machine parameters and rock mass properties which effectively influence prediction models, are presented as well. In Hieflau expansion tunnel AR linearly decreases with increase of thrust due to high dependence of machine advance rate upon rock strength. For Hieflau expansion tunnel three types of data (TBM, rock mass and seismic data e.g. amplitude, pseudo velocity etc.) were coupled and simultaneously analyzed by plotting 3-D surfaces. No appreciable correlation between seismic data (Amplitude and Pseudo velocity) and rock mass properties and machine parameters could be found. Tool wear as a function of TBM operational parameters was analyzed which revealed that tool wear is minimum if applied thrust is moderate and that tool wear is high when thrust is

  9. Performance in grade 12 mathematics and science predicts student nurses' performance in first year science modules at a university in the Western Cape.

    Science.gov (United States)

    Mthimunye, Katlego D T; Daniels, Felicity M

    2017-10-26

    The demand for highly qualified and skilled nurses is increasing in South Africa as well as around the world. Having a background in science can create a significant advantage for students wishing to enrol for an undergraduate nursing qualification because nursing as profession is grounded in scientific evidence. The aim of this study was to investigate the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. A quantitative research method using a cross-sectional predictive design was employed in this study. The participants included first year Bachelor of Nursing students enrolled at a university in the Western Cape, South Africa. Descriptive and inferential statistics were performed to analyse the data by using the IBM Statistical Package for Social Sciences versions 24. Descriptive analysis of all variables was performed as well as the Spearman's rank correlation test to describe the relationship among the study variables. Standard multiple linear regressions analysis was performed to determine the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. The results of this study showed that grade 12 physical science is not a significant predictor (p > 0.062) of performance in first year science modules. The multiple linear regression revealed that grade 12 mathematics and life science grades explained 37.1% to 38.1% (R2 = 0.381 and adj R2 = 0.371) of the variation in the first year science grade distributions. Based on the results of the study it is evident that performance in grade 12 mathematics (β = 2.997) and life science (β = 3.175) subjects is a significant predictor (p < 0.001) of the performance in first year science modules for student nurses at the university identified for this study.

  10. Significant performance enhancement in AlGaN/GaN high electron mobility transistor by high-κ organic dielectric

    International Nuclear Information System (INIS)

    Ze-Gao, Wang; Yuan-Fu, Chen; Cao, Chen; Ben-Lang, Tian; Fu-Tong, Chu; Xing-Zhao, Liu; Yan-Rong, Li

    2010-01-01

    The electrical properties of AlGaN/GaN high electron mobility transistor (HEMT) with and without high-κ organic dielectrics are investigated. The maximum drain current I D max and the maximum transconductance g m max of the organic dielectric/AlGaN/GaN structure can be enhanced by 74.5%, and 73.7% compared with those of the bare AlGaN/GaN HEMT, respectively. Both the threshold voltage V T and g m max of the dielectric/AlGaN/GaN HEMT are strongly dielectric-constant-dependent. Our results suggest that it is promising to significantly improve the performance of the AlGaN/GaN HEMT by introducing the high-κ organic dielectric. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

  11. Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Chien-Ho Ko

    2013-01-01

    Full Text Available Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs, Fuzzy Logic (FL, and Neural Networks (NNs. FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  12. Predicting subcontractor performance using web-based Evolutionary Fuzzy Neural Networks.

    Science.gov (United States)

    Ko, Chien-Ho

    2013-01-01

    Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs) to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs), Fuzzy Logic (FL), and Neural Networks (NNs). FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

  13. Predictors of early stable symptomatic remission after an exacerbation of schizophrenia: the significance of symptoms, neuropsychological performance and cognitive biases.

    Science.gov (United States)

    Andreou, Christina; Roesch-Ely, Daniela; Veckenstedt, Ruth; Bohn, Francesca; Aghotor, Julia; Köther, Ulf; Pfueller, Ute; Moritz, Steffen

    2013-12-30

    Neuropsychological deficits and severity of initial psychopathology have been repeatedly associated with poor symptomatic outcomes in schizophrenia. The role of higher-order cognitive biases on symptomatic outcomes of the disorder has not yet been investigated. The present study aimed to assess the contribution of cognitive biases, psychopathology and neuropsychological deficits on the probability of achieving early symptomatic remission after a psychotic episode in patients with schizophrenia. Participants were 79 patients with a DSM-IV diagnosis of schizophrenia or schizoaffective disorder undergoing an acute psychotic episode, and 25 healthy controls. According to psychopathology assessments, patients were split into those who had achieved remission after an average follow-up interval of 7 months, and those who had not (NR). Patients who achieved remission exhibited higher premorbid IQ and better performance on the TMT-B, as well as lower baseline positive, disorganized and distress symptoms than NR patients. TMT-B performance and positive symptoms at baseline were the best predictors of remission. Cognitive biases and negative symptoms were not associated with later remission. The findings highlight the significance of initial symptom severity for at least short-term symptomatic outcomes and, thus, the importance of adequate symptomatic treatment and prevention of psychotic outbreaks in patients. © 2013 Elsevier Ireland Ltd. All rights reserved.

  14. Predicting Resident Performance from Preresidency Factors: A Systematic Review and Applicability to Neurosurgical Training.

    Science.gov (United States)

    Zuckerman, Scott L; Kelly, Patrick D; Dewan, Michael C; Morone, Peter J; Yengo-Kahn, Aaron M; Magarik, Jordan A; Baticulon, Ronnie E; Zusman, Edie E; Solomon, Gary S; Wellons, John C

    2018-02-01

    Neurosurgical educators strive to identify the best applicants, yet formal study of resident selection has proved difficult. We conducted a systematic review to answer the following question: What objective and subjective preresidency factors predict resident success? PubMed, ProQuest, Embase, and the CINAHL databases were queried from 1952 to 2015 for literature reporting the impact of preresidency factors (PRFs) on outcomes of residency success (RS), among neurosurgery and all surgical subspecialties. Due to heterogeneity of specialties and outcomes, a qualitative summary and heat map of significant findings were constructed. From 1489 studies, 21 articles met inclusion criteria, which evaluated 1276 resident applicants across five surgical subspecialties. No neurosurgical studies met the inclusion criteria. Common objective PRFs included standardized testing (76%), medical school performance (48%), and Alpha Omega Alpha (43%). Common subjective PRFs included aggregate rank scores (57%), letters of recommendation (38%), research (33%), interviews (19%), and athletic or musical talent (19%). Outcomes of RS included faculty evaluations, in-training/board exams, chief resident status, and research productivity. Among objective factors, standardized test scores correlated well with in-training/board examinations but poorly correlated with faculty evaluations. Among subjective factors, aggregate rank scores, letters of recommendation, and athletic or musical talent demonstrated moderate correlation with faculty evaluations. Standardized testing most strongly correlated with future examination performance but correlated poorly with faculty evaluations. Moderate predictors of faculty evaluations were aggregate rank scores, letters of recommendation, and athletic or musical talent. The ability to predict success of neurosurgical residents using an evidence-based approach is limited, and few factors have correlated with future resident performance. Given the importance of

  15. Significant manipulation of output performance of a bridge-structured spin valve magnetoresistance sensor via an electric field

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yue; Yan, Baiqian; Ou-Yang, Jun; Zhu, Benpeng; Chen, Shi; Yang, Xiaofei, E-mail: hust-yangxiaofei@163.com [School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074 (China); Wang, Xianghao [School of Information Engineering, Wuhan University of Technology, Wuhan 430070 (China)

    2016-01-28

    Through principles of spin-valve giant magnetoresistance (SV-GMR) effect and its application in magnetic sensors, we have investigated electric-field control of the output performance of a bridge-structured Co/Cu/NiFe/IrMn SV-GMR sensor on a PZN-PT piezoelectric substrate using the micro-magnetic simulation. We centered on the influence of the variation of uniaxial magnetic anisotropy constant (K) of Co on the output of the bridge, and K was manipulated via the stress of Co, which is generated from the strain of a piezoelectric substrate under an electric field. The results indicate that when K varies between 2 × 10{sup 4 }J/m{sup 3} and 10 × 10{sup 4 }J/m{sup 3}, the output performance can be significantly manipulated: The linear range alters from between −330 Oe and 330 Oe to between −650 Oe and 650 Oe, and the sensitivity is tuned by almost 7 times, making it possible to measure magnetic fields with very different ranges. According to the converse piezoelectric effect, we have found that this variation of K can be realized by applying an electric field with the magnitude of about 2–20 kV/cm on a PZN-PT piezoelectric substrate, which is realistic in application. This result means that electric-control of SV-GMR effect has potential application in developing SV-GMR sensors with improved performance.

  16. Significant manipulation of output performance of a bridge-structured spin valve magnetoresistance sensor via an electric field

    International Nuclear Information System (INIS)

    Zhang, Yue; Yan, Baiqian; Ou-Yang, Jun; Zhu, Benpeng; Chen, Shi; Yang, Xiaofei; Wang, Xianghao

    2016-01-01

    Through principles of spin-valve giant magnetoresistance (SV-GMR) effect and its application in magnetic sensors, we have investigated electric-field control of the output performance of a bridge-structured Co/Cu/NiFe/IrMn SV-GMR sensor on a PZN-PT piezoelectric substrate using the micro-magnetic simulation. We centered on the influence of the variation of uniaxial magnetic anisotropy constant (K) of Co on the output of the bridge, and K was manipulated via the stress of Co, which is generated from the strain of a piezoelectric substrate under an electric field. The results indicate that when K varies between 2 × 10 4  J/m 3 and 10 × 10 4  J/m 3 , the output performance can be significantly manipulated: The linear range alters from between −330 Oe and 330 Oe to between −650 Oe and 650 Oe, and the sensitivity is tuned by almost 7 times, making it possible to measure magnetic fields with very different ranges. According to the converse piezoelectric effect, we have found that this variation of K can be realized by applying an electric field with the magnitude of about 2–20 kV/cm on a PZN-PT piezoelectric substrate, which is realistic in application. This result means that electric-control of SV-GMR effect has potential application in developing SV-GMR sensors with improved performance

  17. Low Motivational Incongruence Predicts Successful EEG Resting-state Neurofeedback Performance in Healthy Adults.

    Science.gov (United States)

    Diaz Hernandez, Laura; Rieger, Kathryn; Koenig, Thomas

    2018-05-15

    Neurofeedback is becoming increasingly sophisticated and widespread, although predictors of successful performance still remain scarce. Here, we explored the possible predictive value of psychological factors and report the results obtained from a neurofeedback training study designed to enhance the self-regulation of spontaneous EEG microstates of a particular type (microstate class D). Specifically, we were interested in life satisfaction (including motivational incongruence), body awareness, personality and trait anxiety. These variables were quantified with questionnaires before neurofeedback. Individual neurofeedback success was established by means of linear mixed models that accounted for the amount of observed target state (microstate class D contribution) as a function of time and training condition: baseline, training and transfer (results shown in Diaz Hernandez et al.). We found a series of significant negative correlations between motivational incongruence and mean percentage increase of microstate D during the condition transfer, across-sessions (36% of common variance) and mean percentage increase of microstate D during the condition training, within-session (42% of common variance). There were no significant correlations related to other questionnaires, besides a trend in a sub-scale of the Life Satisfaction questionnaire. We conclude that motivational incongruence may be a potential predictor for neurofeedback success, at least in the current protocol. The finding may be explained by the interfering effect on neurofeedback performance produced by incompatible simultaneously active psychological processes, which are indirectly measured by the Motivational Incongruence questionnaire. Copyright © 2016. Published by Elsevier Ltd.

  18. Significance of size dependent and material structure coupling on the characteristics and performance of nanocrystalline micro/nano gyroscopes

    Science.gov (United States)

    Larkin, K.; Ghommem, M.; Abdelkefi, A.

    2018-05-01

    Capacitive-based sensing microelectromechanical (MEMS) and nanoelectromechanical (NEMS) gyroscopes have significant advantages over conventional gyroscopes, such as low power consumption, batch fabrication, and possible integration with electronic circuits. However, inadequacies in the modeling of these inertial sensors have presented issues of reliability and functionality of micro-/nano-scale gyroscopes. In this work, a micromechanical model is developed to represent the unique microstructure of nanocrystalline materials and simulate the response of micro-/nano-gyroscope comprising an electrostatically-actuated cantilever beam with a tip mass at the free end. Couple stress and surface elasticity theories are integrated into the classical Euler-Bernoulli beam model in order to derive a size-dependent model. This model is then used to investigate the influence of size-dependent effects on the static pull-in instability, the natural frequencies and the performance output of gyroscopes as the scale decreases from micro-to nano-scale. The simulation results show significant changes in the static pull-in voltage and the natural frequency as the scale of the system is decreased. However, the differential frequency between the two vibration modes of the gyroscope is observed to drastically decrease as the size of the gyroscope is reduced. As such, the frequency-based operation mode may not be an efficient strategy for nano-gyroscopes. The results show that a strong coupling between the surface elasticity and material structure takes place when smaller grain sizes and higher void percentages are considered.

  19. A comprehensive performance evaluation on the prediction results of existing cooperative transcription factors identification algorithms.

    Science.gov (United States)

    Lai, Fu-Jou; Chang, Hong-Tsun; Huang, Yueh-Min; Wu, Wei-Sheng

    2014-01-01

    Eukaryotic transcriptional regulation is known to be highly connected through the networks of cooperative transcription factors (TFs). Measuring the cooperativity of TFs is helpful for understanding the biological relevance of these TFs in regulating genes. The recent advances in computational techniques led to various predictions of cooperative TF pairs in yeast. As each algorithm integrated different data resources and was developed based on different rationales, it possessed its own merit and claimed outperforming others. However, the claim was prone to subjectivity because each algorithm compared with only a few other algorithms and only used a small set of performance indices for comparison. This motivated us to propose a series of indices to objectively evaluate the prediction performance of existing algorithms. And based on the proposed performance indices, we conducted a comprehensive performance evaluation. We collected 14 sets of predicted cooperative TF pairs (PCTFPs) in yeast from 14 existing algorithms in the literature. Using the eight performance indices we adopted/proposed, the cooperativity of each PCTFP was measured and a ranking score according to the mean cooperativity of the set was given to each set of PCTFPs under evaluation for each performance index. It was seen that the ranking scores of a set of PCTFPs vary with different performance indices, implying that an algorithm used in predicting cooperative TF pairs is of strength somewhere but may be of weakness elsewhere. We finally made a comprehensive ranking for these 14 sets. The results showed that Wang J's study obtained the best performance evaluation on the prediction of cooperative TF pairs in yeast. In this study, we adopted/proposed eight performance indices to make a comprehensive performance evaluation on the prediction results of 14 existing cooperative TFs identification algorithms. Most importantly, these proposed indices can be easily applied to measure the performance of new

  20. Summary of the Blind Test Campaign to predict the High Reynolds number performance of DU00-W-210 airfoil

    DEFF Research Database (Denmark)

    Yilmaz, Özlem Ceyhan; Pires, Oscar; Munduate, Xabier

    2017-01-01

    This paper summarizes the results of a blind test campaign organized in the AVATAR project to predict the high Reynolds number performance of a wind turbine airfoil for wind turbine applications. The DU00-W-210 airfoil was tested in the DNW-HDG pressurized wind tunnel in order to investigate...... the flow at high Reynolds number range from 3 to 15 million which is the operating condition of the future large 10MW+ offshore wind turbine rotors. The results of the experiment was used in a blind test campaign to test the prediction capability of the CFD tools used in the wind turbine rotor simulations....... As a result of the blind test campaign it was found that although the codes are in general capable of predicting increased max lift and decreased minimum drag with Re number, the Re trend predictions in particular the glide ratio (lift over drag) need further improvement. In addition to that, the significant...

  1. A prediction of 3-D viscous flow and performance of the NASA Low-Speed Centrifugal Compressor

    Science.gov (United States)

    Moore, John; Moore, Joan G.

    1990-01-01

    A prediction of the three-dimensional turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation of high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modeling. Recommendations are made for future flow studies in the NASA impeller.

  2. Baseline strength can influence the ability of salivary free testosterone to predict squat and sprinting performance.

    Science.gov (United States)

    Crewther, Blair T; Cook, Christian J; Gaviglio, Chris M; Kilduff, Liam P; Drawer, Scott

    2012-01-01

    The objective of this study was to determine if salivary free testosterone can predict an athlete's performance during back squats and sprints over time and the influence baseline strength on this relationship. Ten weight-trained male athletes were divided into 2 groups based on their 1 repetition maximum (1RM) squats, good squatters (1RM > 2.0 × body weight, n = 5) and average squatters (1RM squat 1RM and 10-m sprint times on 10 separate occasions over a 40-day period. A saliva sample was collected before testing and assayed for free testosterone and cortisol. The pooled testosterone correlations were strong and significant in the good squatters (r = 0.92 for squats, r = -0.87 for sprints, p squats, r = -0.18 for sprints). Cortisol showed no significant correlations with 1RM squat and 10-m sprint performance, and no differences were identified between the 2 squatting groups. In summary, these results suggest that free testosterone is a strong individual predictor of squat and sprinting performance in individuals with relatively high strength levels but a poor predictor in less strong individuals. This information can assist coaches, trainers, and performance scientists working with stronger weight-trained athletes, for example, the preworkout measurement of free testosterone could indicate likely training outcomes or a readiness to train at a certain intensity level, especially if real-time measurements are made. Our results also highlight the need to separate group and individual hormonal data during the repeated testing of athletes with variable strength levels.

  3. Predicting law enforcement officer job performance with the Personality Assessment Inventory.

    Science.gov (United States)

    Lowmaster, Sara E; Morey, Leslie C

    2012-01-01

    This study examined the descriptive and predictive characteristics of the Personality Assessment Inventory (PAI; Morey, 1991) in a sample of 85 law enforcement officer candidates. Descriptive results indicate that mean PAI full-scale and subscale scores are consistently lower than normative community sample scores, with some exceptions noted typically associated with defensive responding. Predictive validity was examined by relating PAI full-scale and subscale scores to supervisor ratings in the areas of job performance, integrity problems, and abuse of disability status. Modest correlations were observed for all domains; however, predictive validity was moderated by defensive response style, with greater predictive validity observed among less defensive responders. These results suggest that the PAI's full scales and subscales are able to predict law enforcement officers' performance, but their utility is appreciably improved when taken in the context of indicators of defensive responding.

  4. Deep Recurrent Model for Server Load and Performance Prediction in Data Center

    Directory of Open Access Journals (Sweden)

    Zheng Huang

    2017-01-01

    Full Text Available Recurrent neural network (RNN has been widely applied to many sequential tagging tasks such as natural language process (NLP and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory (LSTM units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events (user requests, which is the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center.

  5. A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine.

    Science.gov (United States)

    Ramakrishnan, Sridhar; Wesensten, Nancy J; Kamimori, Gary H; Moon, James E; Balkin, Thomas J; Reifman, Jaques

    2016-10-01

    Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies. We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg). The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% caffeine resulted in improved predictions (after caffeine consumption) by up to 70%. The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance. © 2016 Associated Professional Sleep Societies, LLC.

  6. Search performance is better predicted by tileability than presence of a unique basic feature

    Science.gov (United States)

    Chang, Honghua; Rosenholtz, Ruth

    2016-01-01

    Traditional models of visual search such as feature integration theory (FIT; Treisman & Gelade, 1980), have suggested that a key factor determining task difficulty consists of whether or not the search target contains a “basic feature” not found in the other display items (distractors). Here we discriminate between such traditional models and our recent texture tiling model (TTM) of search (Rosenholtz, Huang, Raj, Balas, & Ilie, 2012b), by designing new experiments that directly pit these models against each other. Doing so is nontrivial, for two reasons. First, the visual representation in TTM is fully specified, and makes clear testable predictions, but its complexity makes getting intuitions difficult. Here we elucidate a rule of thumb for TTM, which enables us to easily design new and interesting search experiments. FIT, on the other hand, is somewhat ill-defined and hard to pin down. To get around this, rather than designing totally new search experiments, we start with five classic experiments that FIT already claims to explain: T among Ls, 2 among 5s, Q among Os, O among Qs, and an orientation/luminance-contrast conjunction search. We find that fairly subtle changes in these search tasks lead to significant changes in performance, in a direction predicted by TTM, providing definitive evidence in favor of the texture tiling model as opposed to traditional views of search. PMID:27548090

  7. Lactation Curve Pattern and Prediction of Milk Production Performance in Crossbred Cows

    Directory of Open Access Journals (Sweden)

    Suresh Jingar

    2014-01-01

    Full Text Available Data pertaining to 11728 test-day daily milk yields of normal and mastitis Karan Fries cows were collected from the institute herd and divided as mastitis and nonmastitis and parity-wise. The data of lactation curves of the normal and mastitis crossbred cows was analyzed using gamma type function. FTDMY in normal and mastitis cows showed an increasing trend from TD-1 to TD-4 and a gradual decrease (P<0.01 thereafter until the end of lactation (TD-21 in different parities. The FTDMY was maximum (peak yield in the fourth parity. Parity-wise lactation curve revealed a decrease in persistency, steeper decline in descending slope (c, and steeper increase in ascending slope (b from 1st to 5th and above parity. The higher coefficient of determination (R2 and lower root mean square error (RMSE indicated goodness and accuracy of the model for the prediction of milk prediction performance under field conditions. Clinical mastitis resulted in a significantly higher loss of milk yield (P<0.05. The FTDMY was maximum (P<0.05 in the fourth parity in comparison to the rest of parity. It is demonstrated that gamma type function can give the best fit lactation curve in normal and mastitis infected crossbred cows.

  8. Near-fault earthquake ground motion prediction by a high-performance spectral element numerical code

    International Nuclear Information System (INIS)

    Paolucci, Roberto; Stupazzini, Marco

    2008-01-01

    Near-fault effects have been widely recognised to produce specific features of earthquake ground motion, that cannot be reliably predicted by 1D seismic wave propagation modelling, used as a standard in engineering applications. These features may have a relevant impact on the structural response, especially in the nonlinear range, that is hard to predict and to be put in a design format, due to the scarcity of significant earthquake records and of reliable numerical simulations. In this contribution a pilot study is presented for the evaluation of seismic ground-motions in the near-fault region, based on a high-performance numerical code for 3D seismic wave propagation analyses, including the seismic fault, the wave propagation path and the near-surface geological or topographical irregularity. For this purpose, the software package GeoELSE is adopted, based on the spectral element method. The set-up of the numerical benchmark of 3D ground motion simulation in the valley of Grenoble (French Alps) is chosen to study the effect of the complex interaction between basin geometry and radiation mechanism on the variability of earthquake ground motion

  9. Emotional facial expressions differentially influence predictions and performance for face recognition.

    Science.gov (United States)

    Nomi, Jason S; Rhodes, Matthew G; Cleary, Anne M

    2013-01-01

    This study examined how participants' predictions of future memory performance are influenced by emotional facial expressions. Participants made judgements of learning (JOLs) predicting the likelihood that they would correctly identify a face displaying a happy, angry, or neutral emotional expression in a future two-alternative forced-choice recognition test of identity (i.e., recognition that a person's face was seen before). JOLs were higher for studied faces with happy and angry emotional expressions than for neutral faces. However, neutral test faces with studied neutral expressions had significantly higher identity recognition rates than neutral test faces studied with happy or angry expressions. Thus, these data are the first to demonstrate that people believe happy and angry emotional expressions will lead to better identity recognition in the future relative to neutral expressions. This occurred despite the fact that neutral expressions elicited better identity recognition than happy and angry expressions. These findings contribute to the growing literature examining the interaction of cognition and emotion.

  10. The better model to predict and improve pediatric health care quality: performance or importance-performance?

    Science.gov (United States)

    Olsen, Rebecca M; Bryant, Carol A; McDermott, Robert J; Ortinau, David

    2013-01-01

    The perpetual search for ways to improve pediatric health care quality has resulted in a multitude of assessments and strategies; however, there is little research evidence as to their conditions for maximum effectiveness. A major reason for the lack of evaluation research and successful quality improvement initiatives is the methodological challenge of measuring quality from the parent perspective. Comparison of performance-only and importance-performance models was done to determine the better predictor of pediatric health care quality and more successful method for improving the quality of care provided to children. Fourteen pediatric health care centers serving approximately 250,000 patients in 70,000 households in three West Central Florida counties were studied. A cross-sectional design was used to determine the importance and performance of 50 pediatric health care attributes and four global assessments of pediatric health care quality. Exploratory factor analysis revealed five dimensions of care (physician care, access, customer service, timeliness of services, and health care facility). Hierarchical multiple regression compared the performance-only and the importance-performance models. In-depth interviews, participant observations, and a direct cognitive structural analysis identified 50 health care attributes included in a mailed survey to parents(n = 1,030). The tailored design method guided survey development and data collection. The importance-performance multiplicative additive model was a better predictor of pediatric health care quality. Attribute importance moderates performance and quality, making the importance-performance model superior for measuring and providing a deeper understanding of pediatric health care quality and a better method for improving the quality of care provided to children. Regardless of attribute performance, if the level of attribute importance is not taken into consideration, health care organizations may spend valuable

  11. Performance of diagnostic biomarkers in predicting liver fibrosis among hepatitis C virus-infected Egyptian children

    Directory of Open Access Journals (Sweden)

    Yasser E Nassef

    2013-11-01

    Full Text Available The aim of the present study was to identify specific markers that mirror liver fibrosis progression as an alternative to biopsy when biopsy is contraindicated, especially in children. After liver biopsies were performed, serum samples from 30 hepatitis C virus (HCV paediatric patients (8-14 years were analysed and compared with samples from 30 healthy subjects. All subjects were tested for the presence of serum anti-HCV antibodies. Direct biomarkers for liver fibrosis, including transforming growth factor-β1, tissue inhibitor of matrix metalloproteinase-1 (TIMP-1, hyaluronic acid (HA, procollagen type III amino-terminal peptide (PIIINP and osteopontin (OPN, were measured. The indirect biomarkers aspartate and alanine aminotransferases, albumin and bilirubin were also tested. The results revealed a significant increase in the serum marker levels in HCV-infected children compared with the healthy group, whereas albumin levels exhibited a significant decrease. Significantly higher levels of PIIINP, TIMP-1, OPN and HA were detected in HCV-infected children with moderate to severe fibrosis compared with children with mild fibrosis (p < 0.05. The diagnostic accuracy of these direct biomarkers, represented by sensitivity, specificity and positive predictive value, emphasises the utility of PIIINP, TIMP-1, OPN and HA as indicators of liver fibrosis among HCV-infected children.

  12. The Prediction of Students' Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning.

    Science.gov (United States)

    Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen

    2015-01-01

    The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.

  13. Using leg muscles as shock absorbers: theoretical predictions and experimental results of drop landing performance.

    Science.gov (United States)

    Minetti, A E; Ardigò, L P; Susta, D; Cotelli, F

    1998-12-01

    The use of muscles as power dissipators is investigated in this study, both from the modellistic and the experimental points of view. Theoretical predictions of the drop landing manoeuvre for a range of initial conditions have been obtained by accounting for the mechanical characteristics of knee extensor muscles, the limb geometry and assuming maximum neural activation. Resulting dynamics have been represented in the phase plane (vertical displacement versus speed) to better classify the damping performance. Predictions of safe landing in sedentary subjects were associated to dropping from a maximum (feet) height of 1.6-2.0 m (about 11 m on the moon). Athletes can extend up to 2.6-3.0 m, while for obese males (m = 100 kg, standard stature) the limit should reduce to 0.9-1.3 m. These results have been calculated by including in the model the estimated stiffness of the 'global elastic elements' acting below the squat position. Experimental landings from a height of 0.4, 0.7, 1.1 m (sedentary males (SM) and male (AM) and female (AF) athletes from the alpine ski national team) showed dynamics similar to the model predictions. While the peak power (for a drop height of about 0.7 m) was similar in SM and AF (AM shows a +40% increase, about 33 W/kg), AF stopped the downward movement after a time interval (0.219 +/- 0.030 s) from touch-down 20% significantly shorter than SM. Landing strategy and the effect of anatomical constraints are discussed in the paper.

  14. Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Qiu, Yuchen; Zheng, Bin

    2018-02-01

    Objective of this study is to develop and test a new computer-aided detection (CAD) scheme with improved region of interest (ROI) segmentation combined with an image feature extraction framework to improve performance in predicting short-term breast cancer risk. A dataset involving 570 sets of "prior" negative mammography screening cases was retrospectively assembled. In the next sequential "current" screening, 285 cases were positive and 285 cases remained negative. A CAD scheme was applied to all 570 "prior" negative images to stratify cases into the high and low risk case group of having cancer detected in the "current" screening. First, a new ROI segmentation algorithm was used to automatically remove useless area of mammograms. Second, from the matched bilateral craniocaudal view images, a set of 43 image features related to frequency characteristics of ROIs were initially computed from the discrete cosine transform and spatial domain of the images. Third, a support vector machine model based machine learning classifier was used to optimally classify the selected optimal image features to build a CAD-based risk prediction model. The classifier was trained using a leave-one-case-out based cross-validation method. Applying this improved CAD scheme to the testing dataset, an area under ROC curve, AUC = 0.70+/-0.04, which was significantly higher than using the extracting features directly from the dataset without the improved ROI segmentation step (AUC = 0.63+/-0.04). This study demonstrated that the proposed approach could improve accuracy on predicting short-term breast cancer risk, which may play an important role in helping eventually establish an optimal personalized breast cancer paradigm.

  15. Prediction of intrinsic motivation and sports performance using 2 x 2 achievement goal framework.

    Science.gov (United States)

    Li, Chiung-Huang; Chi, Likang; Yeh, Suh-Ruu; Guo, Kwei-Bin; Ou, Cheng-Tsung; Kao, Chun-Chieh

    2011-04-01

    The purpose of this study was to examine the influence of 2 x 2 achievement goals on intrinsic motivation and performance in handball. Participants were 164 high school athletes. All completed the 2 x 2 Achievement Goals Questionnaire for Sport and the Intrinsic Motivation subscale of the Sport Motivation Scale; the coach for each team rated his athletes' overall sports performance. Using simultaneous-regression analyses, mastery-approach goals positively predicted both intrinsic motivation and performance in sports, whereas performance-avoidance goals negatively predicted sports performance. These results suggest that athletes who pursue task mastery and improvement of their competence perform well and enjoy their participation. In contrast, those who focus on avoiding normative incompetence perform poorly.

  16. Predicting performance and performance satisfaction: mindfulness and beliefs about the ability to deal with social barriers in sport.

    Science.gov (United States)

    Blecharz, Jan; Luszczynska, Aleksandra; Scholz, Urte; Schwarzer, Ralf; Siekanska, Malgorzata; Cieslak, Roman

    2014-05-01

    This research investigates the role of beliefs about the ability to deal with specific social barriers and its relationships to mindfulness, football performance, and satisfaction with one's own and team performance. Study 1 aimed at eliciting these social barriers. Study 2 tested (i) whether self-efficacy referring to social barriers would predict performance over and above task-related self-efficacy and collective efficacy and (ii) the mediating role of self-efficacy to overcome social barriers in the relationship between mindfulness and performance. Participants were football (soccer) players aged 16-21 years (Study 1: N=30; Study 2: N=101, longitudinal sample: n=88). Study 1 resulted in eliciting 82 social barriers referring to team, peer leadership, and coaches. Study 2 showed that task-related self-efficacy and collective efficacy explained performance satisfaction at seven-month follow-up, whereas self-efficacy referring to social barriers explained shooting performance at seven-month follow-up. Indirect associations between mindfulness and performance were found with three types of self-efficacy referring to social barriers, operating as parallel mediators. Results provide evidence for the role of beliefs about the ability to cope with social barriers and show a complex interplay between different types of self-efficacy and collective efficacy in predicting team sport performance.

  17. The macrophage activation marker sCD163 combined with markers of the Enhanced Liver Fibrosis (ELF) score predicts clinically significant portal hypertension in patients with cirrhosis

    DEFF Research Database (Denmark)

    Sandahl, T D; McGrail, R; Møller, H J

    2016-01-01

    BACKGROUND: Noninvasive identification of significant portal hypertension in patients with cirrhosis is needed in hepatology practice. AIM: To investigate whether the combination of sCD163 as a hepatic inflammation marker and the fibrosis markers of the Enhanced Liver Fibrosis score (ELF) can...... predict portal hypertension in patients with cirrhosis. METHODS: We measured sCD163 and the ELF components (hyaluronic acid, tissue inhibitor of metalloproteinase-1 and procollagen-III aminopeptide) in two separate cohorts of cirrhosis patients that underwent hepatic vein catheterisation. To test...... the predictive accuracy we developed a CD163-fibrosis portal hypertension score in an estimation cohort (n = 80) and validated the score in an independent cohort (n = 80). A HVPG ≥10 mmHg was considered clinically significant. RESULTS: Both sCD163 and the ELF components increased in a stepwise manner...

  18. Performance of local information-based link prediction: a sampling perspective

    Science.gov (United States)

    Zhao, Jichang; Feng, Xu; Dong, Li; Liang, Xiao; Xu, Ke

    2012-08-01

    Link prediction is pervasively employed to uncover the missing links in the snapshots of real-world networks, which are usually obtained through different kinds of sampling methods. In the previous literature, in order to evaluate the performance of the prediction, known edges in the sampled snapshot are divided into the training set and the probe set randomly, without considering the underlying sampling approaches. However, different sampling methods might lead to different missing links, especially for the biased ways. For this reason, random partition-based evaluation of performance is no longer convincing if we take the sampling method into account. In this paper, we try to re-evaluate the performance of local information-based link predictions through sampling method governed division of the training set and the probe set. It is interesting that we find that for different sampling methods, each prediction approach performs unevenly. Moreover, most of these predictions perform weakly when the sampling method is biased, which indicates that the performance of these methods might have been overestimated in the prior works.

  19. In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models.

    Science.gov (United States)

    Sjögren, Erik; Thörn, Helena; Tannergren, Christer

    2016-06-06

    Gastrointestinal (GI) drug absorption is a complex process determined by formulation, physicochemical and biopharmaceutical factors, and GI physiology. Physiologically based in silico absorption models have emerged as a widely used and promising supplement to traditional in vitro assays and preclinical in vivo studies. However, there remains a lack of comparative studies between different models. The aim of this study was to explore the strengths and limitations of the in silico absorption models Simcyp 13.1, GastroPlus 8.0, and GI-Sim 4.1, with respect to their performance in predicting human intestinal drug absorption. This was achieved by adopting an a priori modeling approach and using well-defined input data for 12 drugs associated with incomplete GI absorption and related challenges in predicting the extent of absorption. This approach better mimics the real situation during formulation development where predictive in silico models would be beneficial. Plasma concentration-time profiles for 44 oral drug administrations were calculated by convolution of model-predicted absorption-time profiles and reported pharmacokinetic parameters. Model performance was evaluated by comparing the predicted plasma concentration-time profiles, Cmax, tmax, and exposure (AUC) with observations from clinical studies. The overall prediction accuracies for AUC, given as the absolute average fold error (AAFE) values, were 2.2, 1.6, and 1.3 for Simcyp, GastroPlus, and GI-Sim, respectively. The corresponding AAFE values for Cmax were 2.2, 1.6, and 1.3, respectively, and those for tmax were 1.7, 1.5, and 1.4, respectively. Simcyp was associated with underprediction of AUC and Cmax; the accuracy decreased with decreasing predicted fabs. A tendency for underprediction was also observed for GastroPlus, but there was no correlation with predicted fabs. There were no obvious trends for over- or underprediction for GI-Sim. The models performed similarly in capturing dependencies on dose and

  20. Predicting failing performance on a standardized patient clinical performance examination: the importance of communication and professionalism skills deficits.

    Science.gov (United States)

    Chang, Anna; Boscardin, Christy; Chou, Calvin L; Loeser, Helen; Hauer, Karen E

    2009-10-01

    The purpose is to determine which assessment measures identify medical students at risk of failing a clinical performance examination (CPX). Retrospective case-control, multiyear design, contingency table analysis, n = 149. We identified two predictors of CPX failure in patient-physician interaction skills: low clerkship ratings (odds ratio 1.79, P = .008) and student progress review for communication or professionalism concerns (odds ratio 2.64, P = .002). No assessments predicted CPX failure in clinical skills. Performance concerns in communication and professionalism identify students at risk of failing the patient-physician interaction portion of a CPX. This correlation suggests that both faculty and standardized patients can detect noncognitive traits predictive of failing performance. Early identification of these students may allow for development of a structured supplemental curriculum with increased opportunities for practice and feedback. The lack of predictors in the clinical skills portion suggests limited faculty observation or feedback.

  1. Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

    Science.gov (United States)

    Burtscher, Michael J.; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

    2011-01-01

    In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team…

  2. Predicting Examination Performance Using an Expanded Integrated Hierarchical Model of Test Emotions and Achievement Goals

    Science.gov (United States)

    Putwain, Dave; Deveney, Carolyn

    2009-01-01

    The aim of this study was to examine an expanded integrative hierarchical model of test emotions and achievement goal orientations in predicting the examination performance of undergraduate students. Achievement goals were theorised as mediating the relationship between test emotions and performance. 120 undergraduate students completed…

  3. A Cross-Validation Study of Police Recruit Performance as Predicted by the IPI and MMPI.

    Science.gov (United States)

    Shusman, Elizabeth J.; And Others

    Validation and cross-validation studies were conducted using the Minnesota Multiphasic Personality Inventory (MMPI) and Inwald Personality Inventory (IPI) to predict job performance for 698 urban male police officers who completed a six-month training academy. Job performance criteria evaluated included absence, lateness, derelictions, negative…

  4. Assessing the performance of prediction models: a framework for traditional and novel measures

    DEFF Research Database (Denmark)

    Steyerberg, Ewout W; Vickers, Andrew J; Cook, Nancy R

    2010-01-01

    The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver...

  5. Assessing the performance of prediction models: A framework for traditional and novel measures

    NARCIS (Netherlands)

    E.W. Steyerberg (Ewout); A.J. Vickers (Andrew); N.R. Cook (Nancy); T.A. Gerds (Thomas); M. Gonen (Mithat); N. Obuchowski (Nancy); M. Pencina (Michael); M.W. Kattan (Michael)

    2010-01-01

    textabstractThe performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the

  6. Predicting Arithmetical Achievement from Neuro-Psychological Performance: A Longitudinal Study.

    Science.gov (United States)

    Fayol, Michel; Barrouillet, Pierre; Marinthe, Catherine

    1998-01-01

    Assessed whether performances of 5- and 6-year olds in arithmetic tests can be predicted from their performances in neuropsychological tests. Participants completed neuropsychological, drawing, and arithmetic tests at 5 and 6 years of age. Findings at older age were correctly assumed by conclusions of first evaluation. (LBT)

  7. The Prediction of College Student Academic Performance and Retention: Application of Expectancy and Goal Setting Theories

    Science.gov (United States)

    Friedman, Barry A.; Mandel, Rhonda G.

    2010-01-01

    Student retention and performance in higher education are important issues for educators, students, and the nation facing critical professional labor shortages. Expectancy and goal setting theories were used to predict academic performance and college student retention. Students' academic expectancy motivation at the start of the college…

  8. The Role of Resilience, Delayed Gratification and Stress in Predicting Academic Performance

    Science.gov (United States)

    Cheng, Vivienne; Catling, Jonathan

    2015-01-01

    Transition to university is an important and potentially stressful life event for students. Previous studies have shown that resilience, delay of gratification and stress can affect the academic performance of students. However, none have shown the effect of these factors in predicting academic performance, hence the current study aimed to look at…

  9. Prostate cancer volume adds significantly to prostate-specific antigen in the prediction of early biochemical failure after external beam radiation therapy

    International Nuclear Information System (INIS)

    D'Amico, Anthony V.; Propert, Kathleen J.

    1996-01-01

    Purpose: A new clinical pretreatment quantity that closely approximates the true prostate cancer volume is defined. Methods and Materials: The cancer-specific prostate-specific antigen (PSA), PSA density, prostate cancer volume (V Ca ), and the volume fraction of the gland involved with carcinoma (V Ca fx) were calculated for 227 prostate cancer patients managed definitively with external beam radiation therapy. 1. PSA density PSA/ultrasound prostate gland volume 2. Cancer-specific PSA = PSA - [PSA from benign epithelial tissue] 3. V Ca = Cancer-specific PSA/[PSA in serum per cm 3 of cancer] 4. V Ca fx = V Ca /ultrasound prostate gland volume A Cox multiple regression analysis was used to test whether any of these-clinical pretreatment parameters added significantly to PSA in predicting early postradiation PSA failure. Results: The prostate cancer volume (p = 0.039) and the volume fraction of the gland involved by carcinoma (p = 0.035) significantly added to the PSA in predicting postradiation PSA failure. Conversely, the PSA density and the cancer-specific PSA did not add significantly (p > 0.05) to PSA in predicting postradiation PSA failure. The 20-month actuarial PSA failure-free rates for patients with calculated tumor volumes of ≤0.5 cm 3 , 0.5-4.0 cm 3 , and >4.0 cm 3 were 92, 80, and 47%, respectively (p = 0.00004). Conclusion: The volume of prostate cancer (V Ca ) and the resulting volume fraction of cancer both added significantly to PSA in their ability to predict for early postradiation PSA failure. These new parameters may be used to select patients in prospective randomized trials that examine the efficacy of combining radiation and androgen ablative therapy in patients with clinically localized disease, who are at high risk for early postradiation PSA failure

  10. Harvested Energy Prediction Schemes for Wireless Sensor Networks: Performance Evaluation and Enhancements

    Directory of Open Access Journals (Sweden)

    Muhammad

    2017-01-01

    Full Text Available We review harvested energy prediction schemes to be used in wireless sensor networks and explore the relative merits of landmark solutions. We propose enhancements to the well-known Profile-Energy (Pro-Energy model, the so-called Improved Profile-Energy (IPro-Energy, and compare its performance with Accurate Solar Irradiance Prediction Model (ASIM, Pro-Energy, and Weather Conditioned Moving Average (WCMA. The performance metrics considered are the prediction accuracy and the execution time which measure the implementation complexity. In addition, the effectiveness of the considered models, when integrated in an energy management scheme, is also investigated in terms of the achieved throughput and the energy consumption. Both solar irradiance and wind power datasets are used for the evaluation study. Our results indicate that the proposed IPro-Energy scheme outperforms the other candidate models in terms of the prediction accuracy achieved by up to 78% for short term predictions and 50% for medium term prediction horizons. For long term predictions, its prediction accuracy is comparable to the Pro-Energy model but outperforms the other models by up to 64%. In addition, the IPro scheme is able to achieve the highest throughput when integrated in the developed energy management scheme. Finally, the ASIM scheme reports the smallest implementation complexity.

  11. Analysis of predicted and measured performance of an integrated compound parabolic concentrator (ICPC)

    Energy Technology Data Exchange (ETDEWEB)

    Winston, R.; O' Gallagher, J.J.; Muschaweck, J.; Mahoney, A.R.; Dudley, V.

    1999-07-01

    A variety of configurations of evacuated Integrated Compound Parabolic Concentrator (ICPC) tubes have been under development for many years. A particularly favorable optical design corresponds to the unit concentration limit for a fin CPC solution which is then coupled to a practical, thin, wedge-shaped absorber. Prototype collector modules using tubes with two different fin orientations (horizontal and vertical) have been fabricated and tested. Comprehensive measurements of the optical characteristics of the reflector and absorber have been used together with a detailed ray trace analysis to predict the optical performance characteristics of these designs. The observed performance agrees well with the predicted performance.

  12. A Comparative Study to Predict Student’s Performance Using Educational Data Mining Techniques

    Science.gov (United States)

    Uswatun Khasanah, Annisa; Harwati

    2017-06-01

    Student’s performance prediction is essential to be conducted for a university to prevent student fail. Number of student drop out is one of parameter that can be used to measure student performance and one important point that must be evaluated in Indonesia university accreditation. Data Mining has been widely used to predict student’s performance, and data mining that applied in this field usually called as Educational Data Mining. This study conducted Feature Selection to select high influence attributes with student performance in Department of Industrial Engineering Universitas Islam Indonesia. Then, two popular classification algorithm, Bayesian Network and Decision Tree, were implemented and compared to know the best prediction result. The outcome showed that student’s attendance and GPA in the first semester were in the top rank from all Feature Selection methods, and Bayesian Network is outperforming Decision Tree since it has higher accuracy rate.

  13. Performance prediction of a proton exchange membrane fuel cell using the ANFIS model

    Energy Technology Data Exchange (ETDEWEB)

    Vural, Yasemin; Ingham, Derek B.; Pourkashanian, Mohamed [Centre for Computational Fluid Dynamics, University of Leeds, Houldsworth Building, LS2 9JT Leeds (United Kingdom)

    2009-11-15

    In this study, the performance (current-voltage curve) prediction of a Proton Exchange Membrane Fuel Cell (PEMFC) is performed for different operational conditions using an Adaptive Neuro-Fuzzy Inference System (ANFIS). First, ANFIS is trained with a set of input and output data. The trained model is then tested with an independent set of experimental data. The trained and tested model is then used to predict the performance curve of the PEMFC under various operational conditions. The model shows very good agreement with the experimental data and this indicates that ANFIS is capable of predicting fuel cell performance (in terms of cell voltage) with a high accuracy in an easy, rapid and cost effective way for the case presented. Finally, the capabilities and the limitations of the model for the application in fuel cells have been discussed. (author)

  14. Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

    Directory of Open Access Journals (Sweden)

    Benjamin Stich

    2018-03-01

    Full Text Available Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP, BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY, and tuber yield (TY of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.

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

    Science.gov (United States)

    Ko, P.; Kurosawa, S.

    2014-03-01

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

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

    International Nuclear Information System (INIS)

    Ko, P; Kurosawa, S

    2014-01-01

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

  17. In vitro and in vivo percutaneous absorption of retinol from cosmetic formulations: Significance of the skin reservoir and prediction of systemic absorption

    International Nuclear Information System (INIS)

    Yourick, Jeffrey J.; Jung, Connie T.; Bronaugh, Robert L.

    2008-01-01

    The percutaneous absorption of retinol (Vitamin A) from cosmetic formulations was studied to predict systemic absorption and to understand the significance of the skin reservoir in in vitro absorption studies. Viable skin from fuzzy rat or human subjects was assembled in flow-through diffusion cells for in vitro absorption studies. In vivo absorption studies using fuzzy rats were performed in glass metabolism cages for collection of urine, feces, and body content. Retinol (0.3%) formulations (hydroalcoholic gel and oil-in-water emulsion) containing 3 H-retinol were applied and absorption was measured at 24 or 72 h. All percentages reported are % of applied dose. In vitro studies using human skin and the gel and emulsion vehicles found 0.3 and 1.3% retinol, respectively, in receptor fluid at 24 h. Levels of absorption in the receptor fluid increased over 72 h with the gel and emulsion vehicles. Using the gel vehicle, in vitro rat skin studies found 23% in skin and 6% in receptor fluid at 24 h, while 72-h studies found 18% in skin and 13% in receptor fluid. Thus, significant amounts of retinol remained in rat skin at 24 h and decreased over 72 h, with proportional increases in receptor fluid. In vivo rat studies with the gel found 4% systemic absorption of retinol after 24 h and systemic absorption did not increase at 72 h. Retinol remaining in rat skin after in vivo application was 18% and 13% of the applied dermal dose after 24 and 72 h, respectively. Similar observations were made with the oil-in water emulsion vehicle in the rat. Retinol formed a reservoir in rat skin both in vivo and in vitro. Little additional retinol was bioavailable after 24 h. Comparison of these in vitro and in vivo results for absorption through rat skin indicates that the 24-h in vitro receptor fluid value accurately estimated 24-h in vivo systemic absorption. Therefore, the best single estimate of retinol systemic absorption from in vitro human skin studies is the 24-h receptor fluid

  18. Sub-seasonal prediction of significant wave heights over the Western Pacific and Indian Oceans, part II: The impact of ENSO and MJO

    Science.gov (United States)

    Shukla, Ravi P.; Kinter, James L.; Shin, Chul-Su

    2018-03-01

    This study evaluates the effect of El Niño and the Southern Oscillation (ENSO) and Madden Julian Oscillation (MJO) events on 14-day mean significant wave height (SWH) at 3 weeks lead time (Wk34) over the Western Pacific and Indian Oceans using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2). The WAVEWATCH-3 (WW3) model is forced with daily 10m-winds predicted by a modified version of CFSv2 that is initialized with multiple ocean analyses in both January and May for 1979-2008. A significant anomaly correlation of predicted and observed SWH anomalies (SWHA) at Wk34 lead-time is found over portions of the domain, including the central western Pacific, South China Sea (SCS), Bay of Bengal (BOB) and southern Indian Ocean (IO) in January cases, and over BOB, equatorial western Pacific, the Maritime Continent and southern IO in May cases. The model successfully predicts almost all the important features of the observed composite SWHA during El Niño events in January, including negative SWHA in the central IO where westerly wind anomalies act on an easterly mean state, and positive SWHA over the southern Ocean (SO) where westerly wind anomalies act on a westerly mean state. The model successfully predicts the sign and magnitude of SWHA at Wk34 lead-time in May over the BOB and SCS in composites of combined phases-2-3 and phases-6-7 of MJO. The observed leading mode of SWHA in May and the third mode of SWHA in January are influenced by the combined effects of ENSO and MJO. Based on spatial and temporal correlations, the spatial patterns of SWHA in the model at Wk34 in both January and May are in good agreement with the observations over the equatorial western Pacific, equatorial and southern IO, and SO.

  19. A Unified Model of Performance for Predicting the Effects of Sleep and Caffeine

    Science.gov (United States)

    Ramakrishnan, Sridhar; Wesensten, Nancy J.; Kamimori, Gary H.; Moon, James E.; Balkin, Thomas J.; Reifman, Jaques

    2016-01-01

    Study Objectives: Existing mathematical models of neurobehavioral performance cannot predict the beneficial effects of caffeine across the spectrum of sleep loss conditions, limiting their practical utility. Here, we closed this research gap by integrating a model of caffeine effects with the recently validated unified model of performance (UMP) into a single, unified modeling framework. We then assessed the accuracy of this new UMP in predicting performance across multiple studies. Methods: We hypothesized that the pharmacodynamics of caffeine vary similarly during both wakefulness and sleep, and that caffeine has a multiplicative effect on performance. Accordingly, to represent the effects of caffeine in the UMP, we multiplied a dose-dependent caffeine factor (which accounts for the pharmacokinetics and pharmacodynamics of caffeine) to the performance estimated in the absence of caffeine. We assessed the UMP predictions in 14 distinct laboratory- and field-study conditions, including 7 different sleep-loss schedules (from 5 h of sleep per night to continuous sleep loss for 85 h) and 6 different caffeine doses (from placebo to repeated 200 mg doses to a single dose of 600 mg). Results: The UMP accurately predicted group-average psychomotor vigilance task performance data across the different sleep loss and caffeine conditions (6% caffeine resulted in improved predictions (after caffeine consumption) by up to 70%. Conclusions: The UMP provides the first comprehensive tool for accurate selection of combinations of sleep schedules and caffeine countermeasure strategies to optimize neurobehavioral performance. Citation: Ramakrishnan S, Wesensten NJ, Kamimori GH, Moon JE, Balkin TJ, Reifman J. A unified model of performance for predicting the effects of sleep and caffeine. SLEEP 2016;39(10):1827–1841. PMID:27397562

  20. An ensemble based top performing approach for NCI-DREAM drug sensitivity prediction challenge.

    Directory of Open Access Journals (Sweden)

    Qian Wan

    Full Text Available We consider the problem of predicting sensitivity of cancer cell lines to new drugs based on supervised learning on genomic profiles. The genetic and epigenetic characterization of a cell line provides observations on various aspects of regulation including DNA copy number variations, gene expression, DNA methylation and protein abundance. To extract relevant information from the various data types, we applied a random forest based approach to generate sensitivity predictions from each type of data and combined the predictions in a linear regression model to generate the final drug sensitivity prediction. Our approach when applied to the NCI-DREAM drug sensitivity prediction challenge was a top performer among 47 teams and produced high accuracy predictions. Our results show that the incorporation of multiple genomic characterizations lowered the mean and variance of the estimated bootstrap prediction error. We also applied our approach to the Cancer Cell Line Encyclopedia database for sensitivity prediction and the ability to extract the top targets of an anti-cancer drug. The results illustrate the effectiveness of our approach in predicting drug sensitivity from heterogeneous genomic datasets.

  1. Using tipping points of emotional intelligence and cognitive competencies to predict financial performance of leaders.

    Science.gov (United States)

    Boyatzis, Richard E

    2006-01-01

    Competencies have been shown to differentiate outstanding managers and leaders from their less effective counterparts. Some of the competencies related to effectiveness reflect cognitive intelligence, but many of them are behavioral manifestations of emotional intelligence. Meanwhile, the performance measures used have often been an approximation of effectiveness. A study of leaders in a multi-national, consulting company shows that the frequency with which they demonstrate a variety of competencies, as seen by others, predicts financial performance in the seven quarters following the competency assessment. This, like other studies only clarify which competencies are necessary for outstanding performance. Borrowing from complexity theory, a tipping point analysis allows examination of how much of the competency is sufficient for outstanding performance. Using the tipping point analysis shows an even greater impact of competencies on the financial performance measures of the leaders in the study. The emotional intelligence competencies constituted most (i.e., 13/14) of the validated competencies predicting financial performance.

  2. Optimizing the stimulus presentation paradigm design for the P300-based brain-computer interface using performance prediction

    Science.gov (United States)

    Mainsah, B. O.; Reeves, G.; Collins, L. M.; Throckmorton, C. S.

    2017-08-01

    Objective. The role of a brain-computer interface (BCI) is to discern a user’s intended message or action by extracting and decoding relevant information from brain signals. Stimulus-driven BCIs, such as the P300 speller, rely on detecting event-related potentials (ERPs) in response to a user attending to relevant or target stimulus events. However, this process is error-prone because the ERPs are embedded in noisy electroencephalography (EEG) data, representing a fundamental problem in communication of the uncertainty in the information that is received during noisy transmission. A BCI can be modeled as a noisy communication system and an information-theoretic approach can be exploited to design a stimulus presentation paradigm to maximize the information content that is presented to the user. However, previous methods that focused on designing error-correcting codes failed to provide significant performance improvements due to underestimating the effects of psycho-physiological factors on the P300 ERP elicitation process and a limited ability to predict online performance with their proposed methods. Maximizing the information rate favors the selection of stimulus presentation patterns with increased target presentation frequency, which exacerbates refractory effects and negatively impacts performance within the context of an oddball paradigm. An information-theoretic approach that seeks to understand the fundamental trade-off between information rate and reliability is desirable. Approach. We developed a performance-based paradigm (PBP) by tuning specific parameters of the stimulus presentation paradigm to maximize performance while minimizing refractory effects. We used a probabilistic-based performance prediction method as an evaluation criterion to select a final configuration of the PBP. Main results. With our PBP, we demonstrate statistically significant improvements in online performance, both in accuracy and spelling rate, compared to the conventional

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

    Science.gov (United States)

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

    1995-03-01

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

  4. Predicting performance and injury resilience from movement quality and fitness scores in a basketball team over 2 years.

    Science.gov (United States)

    McGill, Stuart M; Andersen, Jordan T; Horne, Arthur D

    2012-07-01

    The purpose of this study was to see if specific tests of fitness and movement quality could predict injury resilience and performance in a team of basketball players over 2 years (2 playing seasons). It was hypothesized that, in a basketball population, movement and fitness scores would predict performance scores and that movement and fitness scores would predict injury resilience. A basketball team from a major American university (N = 14) served as the test population in this longitudinal trial. Variables linked to fitness, movement ability, speed, strength, and agility were measured together with some National Basketball Association (NBA) combine tests. Dependent variables of performance indicators (such as games and minutes played, points scored, assists, rebounds, steal, and blocks) and injury reports were tracked for the subsequent 2 years. Results showed that better performance was linked with having a stiffer torso, more mobile hips, weaker left grip strength, and a longer standing long jump, to name a few. Of the 3 NBA combine tests administered here, only a faster lane agility time had significant links with performance. Some movement qualities and torso endurance were not linked. No patterns with injury emerged. These observations have implications for preseason testing and subsequent training programs in an attempt to reduce future injury and enhance playing performance.

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

    Science.gov (United States)

    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.

  6. Performance Evaluation of 14 Neural Network Architectures Used for Predicting Heat Transfer Characteristics of Engine Oils

    Science.gov (United States)

    Al-Ajmi, R. M.; Abou-Ziyan, H. Z.; Mahmoud, M. A.

    2012-01-01

    This paper reports the results of a comprehensive study that aimed at identifying best neural network architecture and parameters to predict subcooled boiling characteristics of engine oils. A total of 57 different neural networks (NNs) that were derived from 14 different NN architectures were evaluated for four different prediction cases. The NNs were trained on experimental datasets performed on five engine oils of different chemical compositions. The performance of each NN was evaluated using a rigorous statistical analysis as well as careful examination of smoothness of predicted boiling curves. One NN, out of the 57 evaluated, correctly predicted the boiling curves for all cases considered either for individual oils or for all oils taken together. It was found that the pattern selection and weight update techniques strongly affect the performance of the NNs. It was also revealed that the use of descriptive statistical analysis such as R2, mean error, standard deviation, and T and slope tests, is a necessary but not sufficient condition for evaluating NN performance. The performance criteria should also include inspection of the smoothness of the predicted curves either visually or by plotting the slopes of these curves.

  7. Blood pressure interacts with APOE ε4 to predict memory performance in a midlife sample.

    Science.gov (United States)

    Oberlin, Lauren E; Manuck, Stephen B; Gianaros, Peter J; Ferrell, Robert E; Muldoon, Matthew F; Jennings, J Richard; Flory, Janine D; Erickson, Kirk I

    2015-09-01

    Elevated blood pressure and the Apolipoprotein ε4 allele (APOE ε4) are independent risk factors for Alzheimer's disease. We sought to determine whether the combined presence of the APOE ε4 allele and elevated blood pressure is associated with lower cognitive performance in cognitively healthy middle-aged adults. A total of 975 participants aged 30-54 (mean age = 44.47) were genotyped for APOE. Cardiometabolic risk factors including blood pressure, lipids, and glucose were assessed and cognitive function was measured using the Trail Making Test and the Visual Reproduction and Logical Memory subtests from the Wechsler Memory Scale. Multivariable regression analysis showed that the association between APOE ε4 and episodic memory performance varied as a function of systolic blood pressure (SBP), such that elevated SBP was predictive of poorer episodic memory performance only in APOE ε4 carriers (β = -.092; t = -2.614; p = .009). Notably, this association was apparent at prehypertensive levels (≥130 mmHg), even after adjusting for physical activity, depression, smoking, and other cardiometabolic risk factors. The joint presence of APOE ε4 and elevated SBP, even at prehypertensive levels, is associated with lower cognitive performance in healthy, middle-aged adults. Results of this study suggest that the combination of APOE ε4 and elevated SBP may synergistically compromise memory function well before the appearance of clinically significant impairments. Interventions targeting blood pressure control in APOE ε4 carriers during midlife should be studied as a possible means to reduce the risk of cognitive decline in genetically susceptible samples. (c) 2015 APA, all rights reserved).

  8. Predictions of biochar production and torrefaction performance from sugarcane bagasse using interpolation and regression analysis.

    Science.gov (United States)

    Chen, Wei-Hsin; Hsu, Hung-Jen; Kumar, Gopalakrishnan; Budzianowski, Wojciech M; Ong, Hwai Chyuan

    2017-12-01

    This study focuses on the biochar formation and torrefaction performance of sugarcane bagasse, and they are predicted using the bilinear interpolation (BLI), inverse distance weighting (IDW) interpolation, and regression analysis. It is found that the biomass torrefied at 275°C for 60min or at 300°C for 30min or longer is appropriate to produce biochar as alternative fuel to coal with low carbon footprint, but the energy yield from the torrefaction at 300°C is too low. From the biochar yield, enhancement factor of HHV, and energy yield, the results suggest that the three methods are all feasible for predicting the performance, especially for the enhancement factor. The power parameter of unity in the IDW method provides the best predictions and the error is below 5%. The second order in regression analysis gives a more reasonable approach than the first order, and is recommended for the predictions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Standardizing the performance evaluation of short-term wind prediction models

    DEFF Research Database (Denmark)

    Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

    2005-01-01

    Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

  10. Enhancing performance of next generation FSO communication systems using soft computing-based predictions.

    Science.gov (United States)

    Kazaura, Kamugisha; Omae, Kazunori; Suzuki, Toshiji; Matsumoto, Mitsuji; Mutafungwa, Edward; Korhonen, Timo O; Murakami, Tadaaki; Takahashi, Koichi; Matsumoto, Hideki; Wakamori, Kazuhiko; Arimoto, Yoshinori

    2006-06-12

    The deterioration and deformation of a free-space optical beam wave-front as it propagates through the atmosphere can reduce the link availability and may introduce burst errors thus degrading the performance of the system. We investigate the suitability of utilizing soft-computing (SC) based tools for improving performance of free-space optical (FSO) communications systems. The SC based tools are used for the prediction of key parameters of a FSO communications system. Measured data collected from an experimental FSO communication system is used as training and testing data for a proposed multi-layer neural network predictor (MNNP) used to predict future parameter values. The predicted parameters are essential for reducing transmission errors by improving the antenna's accuracy of tracking data beams. This is particularly essential for periods considered to be of strong atmospheric turbulence. The parameter values predicted using the proposed tool show acceptable conformity with original measurements.

  11. The Role of Sleep in Predicting College Academic Performance: Is It A Unique Predictor?

    OpenAIRE

    Taylor, Daniel J.; Vatthauer, Karlyn E.; Bramoweth, Adam D.; Ruggero, Camilo; Roane, Brandy

    2013-01-01

    Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. The present project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Subjects (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset lat...

  12. On the increase of predictive performance with high-level data fusion

    International Nuclear Information System (INIS)

    Doeswijk, T.G.; Smilde, A.K.; Hageman, J.A.; Westerhuis, J.A.; Eeuwijk, F.A. van

    2011-01-01

    The combination of the different data sources for classification purposes, also called data fusion, can be done at different levels: low-level, i.e. concatenating data matrices, medium-level, i.e. concatenating data matrices after feature selection and high-level, i.e. combining model outputs. In this paper the predictive performance of high-level data fusion is investigated. Partial least squares is used on each of the data sets and dummy variables representing the classes are used as response variables. Based on the estimated responses y-hat j for data set j and class k, a Gaussian distribution p(g k |y-hat j ) is fitted. A simulation study is performed that shows the theoretical performance of high-level data fusion for two classes and two data sets. Within group correlations of the predicted responses of the two models and differences between the predictive ability of each of the separate models and the fused models are studied. Results show that the error rate is always less than or equal to the best performing subset and can theoretically approach zero. Negative within group correlations always improve the predictive performance. However, if the data sets have a joint basis, as with metabolomics data, this is not likely to happen. For equally performing individual classifiers the best results are expected for small within group correlations. Fusion of a non-predictive classifier with a classifier that exhibits discriminative ability lead to increased predictive performance if the within group correlations are strong. An example with real life data shows the applicability of the simulation results.

  13. Human V4 Activity Patterns Predict Behavioral Performance in Imagery of Object Color.

    Science.gov (United States)

    Bannert, Michael M; Bartels, Andreas

    2018-04-11

    Color is special among basic visual features in that it can form a defining part of objects that are engrained in our memory. Whereas most neuroimaging research on human color vision has focused on responses related to external stimulation, the present study investigated how sensory-driven color vision is linked to subjective color perception induced by object imagery. We recorded fMRI activity in male and female volunteers during viewing of abstract color stimuli that were red, green, or yellow in half of the runs. In the other half we asked them to produce mental images of colored, meaningful objects (such as tomato, grapes, banana) corresponding to the same three color categories. Although physically presented color could be decoded from all retinotopically mapped visual areas, only hV4 allowed predicting colors of ima