Predictors of Science Success: The Impact of Motivation and Learning Strategies on College Chemistry Performance

ERIC Educational Resources Information Center

Obrentz, Shari B.

2012-01-01

As the number of college students studying science continues to grow, it is important to identify variables that predict their success. The literature indicates that motivation and learning strategy use facilitate science success. Research findings show these variables can change throughout a semester and differ by performance level, gender and…

Building Models to Predict Hint-or-Attempt Actions of Students

ERIC Educational Resources Information Center

Castro, Francisco Enrique Vicente; Adjei, Seth; Colombo, Tyler; Heffernan, Neil

2015-01-01

A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…

Orchiopexy for intra-abdominal testes: factors predicting success.

PubMed

Stec, Andrew A; Tanaka, Stacy T; Adams, Mark C; Pope, John C; Thomas, John C; Brock, John W

2009-10-01

Intra-abdominal testes can be treated with several surgical procedures. We evaluated factors influencing the outcome of orchiopexy for intra-abdominal testis. We retrospectively reviewed 156 consecutive orchiopexies performed for intra-abdominal testis, defined as a nonpalpable testis on examination and located in the abdomen at surgery. All surgical approaches were included in the study. Primary outcome was the overall success rate and secondary outcomes were success based on surgical approach, age and a patent processus vaginalis. Success was considered a testis with normal texture and size compared to the contralateral testis at followup. Multivariate analysis was performed to determine factors predictive of success. The overall success rate of all orchiopexies was 79.5%. Median patient age at orchiopexy was 12 months and mean followup was 16 months. Of the patients 117 had a patent processus vaginalis at surgery. One-stage abdominal orchiopexy was performed in 92 testes with 89.1% success. Of these cases 32 were performed laparoscopically with 96.9% success. One-stage Fowler-Stephens orchiopexy was performed in 27 testes and 2-stage Fowler-Stephens orchiopexy was performed in 37 with success in 63.0% and 67.6%, respectively. Multivariate analysis revealed that 1-stage orchiopexy without vessel division had more successful outcomes than 1 and 2-stage Fowler-Stephens orchiopexy (OR 0.24, p = 0.007 and 0.29, p = 0.19, respectively). Neither age at surgery nor an open internal ring was significant (p = 0.49 and 0.12, respectively). The overall success of orchiopexy for intra-abdominal testis is 79.5%. While patient selection remains a critical factor, 1-stage orchiopexy without vessel division was significantly more successful and a laparoscopic approach was associated with the fewest failures for intra-abdominal testes.

Conspecific reproductive success and breeding habitat selection: Implications for the study of coloniality

USGS Publications Warehouse

Danchin, E.; Boulinier, T.; Massot, M.

1998-01-01

Habitat selection is a crucial process in the life cycle of animals because it can affect most components of fitness. It has been proposed that some animals cue on the reproductive success of conspecifics to select breeding habitats. We tested this hypothesis with demographic and behavioral data from a 17-yr study of the Black-legged Kittiwake (Rissa tridactyla), a cliff-nesting seabird. As the hypothesis assumes, the Black-legged Kittiwake nesting environment was patchy, and the relative quality of the different patches (i.e., breeding cliffs) varied in time. The average reproductive success of the breeders of a given cliff was predictable from one year to the next, but this predictability faded after several years. The dynamic nature of cliff quality in the long term is partly explained by the autocorrelation of the prevalence of an ectoparasite that influences reproductive success. As predicted by the performance-based conspecific attraction hypothesis, the reproductive success of current breeders on a given cliff was predictive of the reproductive success of new recruits on the cliff in the following year. Breeders tended to recruit to the previous year's most productive cliffs and to emigrate from the least productive ones. Consequently, the dynamics of breeder numbers on the cliffs were explained by local reproductive success on a year-to-year basis. Because, on average, young Black-legged Kittiwakes first breed when 4 yr old, such a relationship probably results from individual choices based on the assessment of previous-year local quality. When breeders changed breeding cliffs between years, they selected cliffs of per capita higher reproductive success. Furthermore, after accounting for the potential effects of age and sex as well as between-year variations, the effect of individual breeding performance on breeding dispersal was strongly influenced by the average reproductive success of other breeders on the same cliff. Individual breeding performance did not appear to influence the probability of dispersing for birds breeding on cliffs with high local reproductive success, whereas individual breeding performance did have a strong effect on dispersal for birds that bred on cliffs with lower local reproductive success. This suggests that the reproductive success of locally breeding conspecifics may be sufficient to override an individual's own breeding experience when deciding whether to emigrate. These results, which are supported by behavioral observations of the role of prospecting in recruitment, suggest that both first breeders and adults rely on the reproductive success of conspecifics as 'public information' to assess their own chances of breeding successfully in a given patch and to make settling decisions. A corollary prediction is that individuals should attempt to breed near successful conspecifics (a form of social attraction) in order to benefit from the same favorable local environmental conditions. Such a performance-based conspecific attraction mechanism can thus lead to an aggregative distribution of nests and may have played a role in the evolution of coloniality.

Modeling student success in engineering education

NASA Astrophysics Data System (ADS)

Jin, Qu

In order for the United States to maintain its global competitiveness, the long-term success of our engineering students in specific courses, programs, and colleges is now, more than ever, an extremely high priority. Numerous studies have focused on factors that impact student success, namely academic performance, retention, and/or graduation. However, there are only a limited number of works that have systematically developed models to investigate important factors and to predict student success in engineering. Therefore, this research presents three separate but highly connected investigations to address this gap. The first investigation involves explaining and predicting engineering students' success in Calculus I courses using statistical models. The participants were more than 4000 first-year engineering students (cohort years 2004 - 2008) who enrolled in Calculus I courses during the first semester in a large Midwestern university. Predictions from statistical models were proposed to be used to place engineering students into calculus courses. The success rates were improved by 12% in Calculus IA using predictions from models developed over traditional placement method. The results showed that these statistical models provided a more accurate calculus placement method than traditional placement methods and help improve success rates in those courses. In the second investigation, multi-outcome and single-outcome neural network models were designed to understand and to predict first-year retention and first-year GPA of engineering students. The participants were more than 3000 first year engineering students (cohort years 2004 - 2005) enrolled in a large Midwestern university. The independent variables include both high school academic performance factors and affective factors measured prior to entry. The prediction performances of the multi-outcome and single-outcome models were comparable. The ability to predict cumulative GPA at the end of an engineering student's first year of college was about a half of a grade point for both models. The predictors of retention and cumulative GPA while being similar differ in that high school academic metrics play a more important role in predicting cumulative GPA with the affective measures playing a more important role in predicting retention. In the last investigation, multi-outcome neural network models were used to understand and to predict engineering students' retention, GPA, and graduation from entry to departure. The participants were more than 4000 engineering students (cohort years 2004 - 2006) enrolled in a large Midwestern university. Different patterns of important predictors were identified for GPA, retention, and graduation. Overall, this research explores the feasibility of using modeling to enhance a student's educational experience in engineering. Student success modeling was used to identify the most important cognitive and affective predictors for a student's first calculus course retention, GPA, and graduation. The results suggest that the statistical modeling methods have great potential to assist decision making and help ensure student success in engineering education.

The Impact of Proactive Student-Success Coaching Using Predictive Analytics on Community College Students

ERIC Educational Resources Information Center

Hall, Mark Monroe

2017-01-01

The purpose of this study was to examine the effects of proactive student-success coaching, informed by predictive analytics, on student academic performance and persistence. Specifically, semester GPA and semester-to-semester student persistence were the investigated outcomes. Uniquely, the community college focused the intervention on only…

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

PubMed Central

2016-01-01

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

Using Performance Data Gathered at Several Stages of Achievement in Predicting Subsequent Performance.

ERIC Educational Resources Information Center

Owen, Steven V.; Feldhusen, John F.

This study compares the effectiveness of three models of multivariate prediction for academic success in identifying the criterion variance of achievement in nursing education. The first model involves the use of an optimum set of predictors and one equation derived from a regression analysis on first semester grade average in predicting the…

Successful prediction and performance in waterflooding Wesson Hogg Sand Unit, Ouachita County, Arkansas

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

Clanton, H.W.

1966-01-01

By unitization and waterflooding, the Hogg Sand reservoir will increase ultimate recovery by 21,500,000 bbl. The predicted ultimate recovery of 1,103 bbl per acre-ft is considered well above average for waterflood projects. Predicted reservoir performance has closely paralleled actual performance in many areas of investigation, viz., recovery in bbl per acre-ft, flood pattern, water percent at depletion, and attaining a reservoir pressure which would sustain production by natural flow. A departure from the generally accepted practices utilized in waterflooding has not been a detriment in successfully flooding the Hogg Sand reservoir. The major factors contributing to the high degree ofmore » success can be found in the excellent reservoir characteristics. Operating costs of $0.2429 per bbl, including amortization, is approximately 1/4 of that normally expected in waterfloods. Remaining oil after flooding is indicated to be 49% of the oil in place and clearly indicates a need for concentrated efforts in the field of tertiary recovery.« less

Predicting Success: How Predictive Analytics Are Transforming Student Support and Success Programs

ERIC Educational Resources Information Center

Boerner, Heather

2015-01-01

Every year, Lone Star College in Texas hosts a "Men of Honor" program to provide assistance and programming to male students, but particularly those who are Hispanic and black, in hopes their academic performance will improve. Lone Star might have kept directing its limited resources toward these students--and totally missed the subset…

What Matters from Admissions? Identifying Success and Risk Among Canadian Dental Students.

PubMed

Plouffe, Rachel A; Hammond, Robert; Goldberg, Harvey A; Chahine, Saad

2018-05-01

The aims of this study were to determine whether different student profiles would emerge in terms of high and low GPA performance in each year of dental school and to investigate the utility of preadmissions variables in predicting performance and performance stability throughout each year of dental school. Data from 11 graduating cohorts (2004-14) at the Schulich School of Medicine & Dentistry, University of Western Ontario, Canada, were collected and analyzed using bivariate correlations, latent profile analysis, and hierarchical generalized linear models (HGLMs). The data analyzed were for 616 students in total (332 males and 284 females). Four models were developed to predict adequate and poor performance throughout each of four dental school years. An additional model was developed to predict student performance stability across time. Two separate student profiles reflecting high and low GPA performance across each year of dental school were identified, and scores on cognitive preadmissions variables differentially predicted the probability of grouping into high and low performance profiles. Students with higher pre-dental GPAs and DAT chemistry were most likely to remain stable in a high-performance group across each year of dental school. Overall, the findings suggest that selection committees should consider pre-dental GPA and DAT chemistry scores as important tools for predicting dental school performance and stability across time. This research is important in determining how to better predict success and failure in various areas of preclinical dentistry courses and to provide low-performing students with adequate academic assistance.

Predicting athletic success motivation using mental skin and emotional intelligence and its components in male athletes.

PubMed

Kajbafnezhad, H; Ahadi, H; Heidarie, A; Askari, P; Enayati, M

2012-10-01

The aim of this study was to predict athletic success motivation by mental skills, emotional intelligence and its components. The research sample consisted of 153 male athletes who were selected through random multistage sampling. The subjects completed the Mental Skills Questionnaire, Bar-On Emotional Intelligence questionnaire and the perception of sport success questionnaire. Data were analyzed using Pearson correlation coefficient and multiple regressions. Regression analysis shows that between the two variables of mental skill and emotional intelligence, mental skill is the best predictor for athletic success motivation and has a better ability to predict the success rate of the participants. Regression analysis results showed that among all the components of emotional intelligence, self-respect had a significantly higher ability to predict athletic success motivation. The use of psychological skills and emotional intelligence as an mediating and regulating factor and organizer cause leads to improved performance and can not only can to help athletes in making suitable and effective decisions for reaching a desired goal.

Using managerial role motivation theory to predict career success.

PubMed

Holland, M G; Black, C H; Miner, J B

1987-01-01

Managerial role motivation theory has proved to be useful for understanding executive performance in a wide range of highly structured organizational environments. Consistent results of studies indicate that the theory may be useful for understanding managerial behavior and predicting performance in health care organizations.

Establishing Decision Trees for Predicting Successful Postpyloric Nasoenteric Tube Placement in Critically Ill Patients.

PubMed

Chen, Weisheng; Sun, Cheng; Wei, Ru; Zhang, Yanlin; Ye, Heng; Chi, Ruibin; Zhang, Yichen; Hu, Bei; Lv, Bo; Chen, Lifang; Zhang, Xiunong; Lan, Huilan; Chen, Chunbo

2016-08-31

Despite the use of prokinetic agents, the overall success rate for postpyloric placement via a self-propelled spiral nasoenteric tube is quite low. This retrospective study was conducted in the intensive care units of 11 university hospitals from 2006 to 2016 among adult patients who underwent self-propelled spiral nasoenteric tube insertion. Success was defined as postpyloric nasoenteric tube placement confirmed by abdominal x-ray scan 24 hours after tube insertion. Chi-square automatic interaction detection (CHAID), simple classification and regression trees (SimpleCart), and J48 methodologies were used to develop decision tree models, and multiple logistic regression (LR) methodology was used to develop an LR model for predicting successful postpyloric nasoenteric tube placement. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models. Successful postpyloric nasoenteric tube placement was confirmed in 427 of 939 patients enrolled. For predicting successful postpyloric nasoenteric tube placement, the performance of the 3 decision trees was similar in terms of the AUCs: 0.715 for the CHAID model, 0.682 for the SimpleCart model, and 0.671 for the J48 model. The AUC of the LR model was 0.729, which outperformed the J48 model. Both the CHAID and LR models achieved an acceptable discrimination for predicting successful postpyloric nasoenteric tube placement and were useful for intensivists in the setting of self-propelled spiral nasoenteric tube insertion. © 2016 American Society for Parenteral and Enteral Nutrition.

Establishing Decision Trees for Predicting Successful Postpyloric Nasoenteric Tube Placement in Critically Ill Patients.

PubMed

Chen, Weisheng; Sun, Cheng; Wei, Ru; Zhang, Yanlin; Ye, Heng; Chi, Ruibin; Zhang, Yichen; Hu, Bei; Lv, Bo; Chen, Lifang; Zhang, Xiunong; Lan, Huilan; Chen, Chunbo

2018-01-01

Despite the use of prokinetic agents, the overall success rate for postpyloric placement via a self-propelled spiral nasoenteric tube is quite low. This retrospective study was conducted in the intensive care units of 11 university hospitals from 2006 to 2016 among adult patients who underwent self-propelled spiral nasoenteric tube insertion. Success was defined as postpyloric nasoenteric tube placement confirmed by abdominal x-ray scan 24 hours after tube insertion. Chi-square automatic interaction detection (CHAID), simple classification and regression trees (SimpleCart), and J48 methodologies were used to develop decision tree models, and multiple logistic regression (LR) methodology was used to develop an LR model for predicting successful postpyloric nasoenteric tube placement. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of these models. Successful postpyloric nasoenteric tube placement was confirmed in 427 of 939 patients enrolled. For predicting successful postpyloric nasoenteric tube placement, the performance of the 3 decision trees was similar in terms of the AUCs: 0.715 for the CHAID model, 0.682 for the SimpleCart model, and 0.671 for the J48 model. The AUC of the LR model was 0.729, which outperformed the J48 model. Both the CHAID and LR models achieved an acceptable discrimination for predicting successful postpyloric nasoenteric tube placement and were useful for intensivists in the setting of self-propelled spiral nasoenteric tube insertion. © 2016 American Society for Parenteral and Enteral Nutrition.

Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor

ERIC Educational Resources Information Center

Lee, Young-Jin

2015-01-01

This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…

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

PubMed

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

2011-12-01

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

Predicting course performance in freshman and sophomore physics courses: Women are more predictable than men

NASA Astrophysics Data System (ADS)

McCammon, Susan; Golden, Jeannie; Wuensch, Karl L.

This study investigated the extent to which thinking skills and mathematical competency would predict the course performance of freshman and sophomore science majors enrolled in physics courses. Multiple-regression equations revealed that algebra and critical thinking skills were the best overall predictors across several physics courses. Although arithmetic skills, math anxiety, and primary mental abilities scores also correlated with performance, they were redundant with the algebra and critical thinking. The most surprising finding of the study was the differential validity by sex; predictor variables were successful in predicting course performance for women but not for men.

Using Neural Network and Logistic Regression Analysis to Predict Prospective Mathematics Teachers' Academic Success upon Entering Graduate Education

ERIC Educational Resources Information Center

Bahadir, Elif

2016-01-01

The ability to predict the success of students when they enter a graduate program is critical for educational institutions because it allows them to develop strategic programs that will help improve students' performances during their stay at an institution. In this study, we present the results of an experimental comparison study of Logistic…

Improved therapy-success prediction with GSS estimated from clinical HIV-1 sequences.

PubMed

Pironti, Alejandro; Pfeifer, Nico; Kaiser, Rolf; Walter, Hauke; Lengauer, Thomas

2014-01-01

Rules-based HIV-1 drug-resistance interpretation (DRI) systems disregard many amino-acid positions of the drug's target protein. The aims of this study are (1) the development of a drug-resistance interpretation system that is based on HIV-1 sequences from clinical practice rather than hard-to-get phenotypes, and (2) the assessment of the benefit of taking all available amino-acid positions into account for DRI. A dataset containing 34,934 therapy-naïve and 30,520 drug-exposed HIV-1 pol sequences with treatment history was extracted from the EuResist database and the Los Alamos National Laboratory database. 2,550 therapy-change-episode baseline sequences (TCEB) were assigned to test set A. Test set B contains 1,084 TCEB from the HIVdb TCE repository. Sequences from patients absent in the test sets were used to train three linear support vector machines to produce scores that predict drug exposure pertaining to each of 20 antiretrovirals: the first one uses the full amino-acid sequences (DEfull), the second one only considers IAS drug-resistance positions (DEonlyIAS), and the third one disregards IAS drug-resistance positions (DEnoIAS). For performance comparison, test sets A and B were evaluated with DEfull, DEnoIAS, DEonlyIAS, geno2pheno[resistance], HIVdb, ANRS, HIV-GRADE, and REGA. Clinically-validated cut-offs were used to convert the continuous output of the first four methods into susceptible-intermediate-resistant (SIR) predictions. With each method, a genetic susceptibility score (GSS) was calculated for each therapy episode in each test set by converting the SIR prediction for its compounds to integer: S=2, I=1, and R=0. The GSS were used to predict therapy success as defined by the EuResist standard datum definition. Statistical significance was assessed using a Wilcoxon signed-rank test. A comparison of the therapy-success prediction performances among the different interpretation systems for test set A can be found in Table 1, while those for test set B are found in Figure 1. Therapy-success prediction of first-line therapies with DEnoIAS performed better than DEonlyIAS (p<10-16). Therapy success prediction benefits from the consideration of all available mutations. The increase in performance was largest in first-line therapies with transmitted drug-resistance mutations.

Development and Validation of a Novel Scoring System for Predicting Technical Success of Chronic Total Occlusion Percutaneous Coronary Interventions: The PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) Score.

PubMed

Christopoulos, Georgios; Kandzari, David E; Yeh, Robert W; Jaffer, Farouc A; Karmpaliotis, Dimitri; Wyman, Michael R; Alaswad, Khaldoon; Lombardi, William; Grantham, J Aaron; Moses, Jeffrey; Christakopoulos, Georgios; Tarar, Muhammad Nauman J; Rangan, Bavana V; Lembo, Nicholas; Garcia, Santiago; Cipher, Daisha; Thompson, Craig A; Banerjee, Subhash; Brilakis, Emmanouil S

2016-01-11

This study sought to develop a novel parsimonious score for predicting technical success of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) performed using the hybrid approach. Predicting technical success of CTO PCI can facilitate clinical decision making and procedural planning. We analyzed clinical and angiographic parameters from 781 CTO PCIs included in PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) using a derivation and validation cohort (2:1 sampling ratio). Variables with strong association with technical success in multivariable analysis were assigned 1 point, and a 4-point score was developed from summing all points. The PROGRESS CTO score was subsequently compared with the J-CTO (Multicenter Chronic Total Occlusion Registry in Japan) score in the validation cohort. Technical success was 92.9%. On multivariable analysis, factors associated with technical success included proximal cap ambiguity (beta coefficient [b] = 0.88), moderate/severe tortuosity (b = 1.18), circumflex artery CTO (b = 0.99), and absence of "interventional" collaterals (b = 0.88). The resulting score demonstrated good calibration and discriminatory capacity in the derivation (Hosmer-Lemeshow chi-square = 2.633; p = 0.268, and receiver-operator characteristic [ROC] area = 0.778) and validation (Hosmer-Lemeshow chi-square = 5.333; p = 0.070, and ROC area = 0.720) subset. In the validation cohort, the PROGRESS CTO and J-CTO scores performed similarly in predicting technical success (ROC area 0.720 vs. 0.746, area under the curve difference = 0.026, 95% confidence interval = -0.093 to 0.144). The PROGRESS CTO score is a novel useful tool for estimating technical success in CTO PCI performed using the hybrid approach. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Predicting Military Recruiter Effectiveness: A Literature Review

DTIC Science & Technology

1987-04-01

employing commanding officer nominations and/or supervisor ratings as criteria for success in recruiting. Wollack and KiDnis (1960). Commanding officer...ratings can be used to predict field recruiter performance. The authors attribute the failure to predict field recruiter performance to the...Time to Complete -12 -27 -5 -09 5. MC 431 Completion/ Failure 08 Studies 1. Cross-validities obtained via rMonte Carlo procedure by Borman, Toquam

Bike and run pacing on downhill segments predict Ironman triathlon relative success.

PubMed

Johnson, Evan C; Pryor, J Luke; Casa, Douglas J; Belval, Luke N; Vance, James S; DeMartini, Julie K; Maresh, Carl M; Armstrong, Lawrence E

2015-01-01

Determine if performance and physiological based pacing characteristics over the varied terrain of a triathlon predicted relative bike, run, and/or overall success. Poor self-regulation of intensity during long distance (Full Iron) triathlon can manifest in adverse discontinuities in performance. Observational study of a random sample of Ironman World Championship athletes. High performing and low performing groups were established upon race completion. Participants wore global positioning system and heart rate enabled watches during the race. Percentage difference from pre-race disclosed goal pace (%off) and mean HR were calculated for nine segments of the bike and 11 segments of the run. Normalized graded running pace (accounting for changes in elevation) was computed via analysis software. Step-wise regression analyses identified segments predictive of relative success and HP and LP were compared at these segments to confirm importance. %Off of goal velocity during two downhill segments of the bike (HP: -6.8±3.2%, -14.2±2.6% versus LP: -1.2±4.2%, -5.1±11.5%; p<0.020) and %off from NGP during one downhill segment of the run (HP: 4.8±5.2% versus LP: 33.3±38.7%; p=0.033) significantly predicted relative performance. Also, HP displayed more consistency in mean HR (141±12 to 138±11 bpm) compared to LP (139±17 to 131±16 bpm; p=0.019) over the climb and descent from the turn-around point during the bike component. Athletes who maintained faster relative speeds on downhill segments, and who had smaller changes in HR between consecutive up and downhill segments were more successful relative to their goal times. Copyright © 2013 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Developing and Testing a Model to Predict Outcomes of Organizational Change

PubMed Central

Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

2003-01-01

Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

Applying the Newman-Peacock Prognostic System to a Portuguese Obstetrical Population - A Useful Tool?

PubMed

Mendes Silva, Rita; Clode, Nuno

2018-01-01

 External cephalic version (ECV) is a maneuver that enables the rotation of the non-cephalic fetus to a cephalic presentation. The Newman-Peacock (NP) index, which was proposed by Newman et al. in a study published in 1993, was described as a prediction tool of the success of this procedure; it was validated in a North-American population, and three prognostic groups were identified.  To evaluate the value of the NP score for the prediction of a successful ECV in a Portuguese obstetrical population, and to evaluate maternal and fetal safety.  We present an observational study conducted from 1997-2016 with pregnant women at 36-38 weeks of pregnancy who were candidates for external cephalic version in our department. Demographic and obstetrical data were collected, including the parameters included in the NP index (parity, cervical dilatation, estimated fetal weight, placental location and fetal station). The calculation of the NP score was performed, and the percentages of success were compared among the three prognostic groups and with the original study by Newman et al. The performance of the score was determined using the Student t -test, the Chi-squared test, and a receiver operating characteristic (ROC) curve.  In total, 337 women were included. The overall success rate was of 43.6%. The univariate analysis revealed that multiparity, posterior placentation and a less engaged fetus were factors that favored a successful maneuver ( p  < 0.05). Moreover, a higher amniotic fluid index was also a relevant predictive factor ( p  < 0.05). The Newman-Peacock score had a poorer performance in our population compared with that of the sample of the original study, but we still found a positive relationship between higher scores and higher prediction of success ( p  < 0.001). No fetal or maternal morbidities were registered.  The Newman-Peacock score had a poorer performance among our population compared to its performance in the original study, but the results suggest that this score is still a useful tool to guide our clinical practice and counsel the candidate regarding ECV. Thieme Revinter Publicações Ltda Rio de Janeiro, Brazil.

Drug choice as a self-handicapping strategy in response to noncontingent success.

PubMed

Berglas, S; Jones, E E

1978-04-01

In two closely related experiments, college student subjects were instructed to choose between a drug that allegedly interfered with performance and a drug that allegedly enhanced performance. This choice was the main dependent measure of the experiment. The drug choice intervened between work on soluble or insoluble problems and a promised retest on similar problems. In Experiment 1, all subjects received success feedback after their initial problem-solving attempts, thus creating one condition in which the success appeared to be accidental (noncontingent on performance) and one in which the success appeared to be contingent on appropriate knowledge. Males in the noncontingent-success condition were alone in preferring the performance-inhibiting drug, presumably because they wished to externalize probable failure on the retest. The predicted effect, however, did not hold for female subjects. Experiment 2 replicated the unique preference shown by males after noncontingent success and showed the critical importance of success feedback.

Admissions Roulette: Predictive Factors for Success in Practice

ERIC Educational Resources Information Center

Pfouts, Jane H.; Henley, H. Carl, Jr.

1977-01-01

A multivariate predictive index of student field performance to be used as an admissions tool in graduate schools of social work is described. It measures the effect on field performance of (1) a measure of the student's intellectual ability, (2) undergraduate school quality, (3) prior work experience, and (4) student sex. (Author/LBH)

The Relationship between Self-Regulation and Online Learning in a Blended Learning Context

ERIC Educational Resources Information Center

Lynch, Richard; Dembo, Myron

2004-01-01

This study reviewed the distance education and self-regulation literatures to identify learner self-regulation skills predictive of academic success in a blended education context. Five self-regulatory attributes were judged likely to be predictive of academic performance: intrinsic goal orientation, self-efficacy for learning and performance,…

The Paradox of the Contented Female Business Owner

ERIC Educational Resources Information Center

Powell, Gary N.; Eddleston, Kimberly A.

2008-01-01

According to survey responses from 201 business owners, although the firms of male business owners were more successful than those of female business owners on frequently used measures of business success (business performance compared to competitors and sales), business owner sex did not predict satisfaction with business success, supporting the…

Do Traditional Admissions Criteria Reflect Applicant Creativity?

ERIC Educational Resources Information Center

Pretz, Jean E.; Kaufman, James C.

2017-01-01

College admissions decisions have traditionally focused on high school academic performance and standardized test scores. An ongoing debate is the validity of these measures for predicting success in college; part of this debate includes how success is defined. One potential way of defining college success is a student's creative accomplishments.…

Predicting Firm Success From the Facial Appearance of Chief Executive Officers of Non-Profit Organizations.

PubMed

Re, Daniel E; Rule, Nicholas O

2016-10-01

Recent research has demonstrated that judgments of Chief Executive Officers' (CEOs') faces predict their firms' financial performance, finding that characteristics associated with higher power (e.g., dominance) predict greater profits. Most of these studies have focused on CEOs of profit-based businesses, where the main criterion for success is financial gain. Here, we examined whether facial appearance might predict measures of success in a sample of CEOs of non-profit organizations (NPOs). Indeed, contrary to findings for the CEOs of profit-based businesses, judgments of leadership and power from the faces of CEOs of NPOs negatively correlated with multiple measures of charitable success (Study 1). Moreover, CEOs of NPOs looked less powerful than the CEOs of profit-based businesses (Study 2) and leadership ratings positively associated with warmth-based traits and NPO success when participants knew the faces belonged to CEOs of NPOs (Study 3). CEOs who look less dominant may therefore achieve greater success in leading NPOs, opposite the relationship found for the CEOs of profit-based companies. Thus, the relationship between facial appearance and leadership success varies by organizational context. © The Author(s) 2016.

Predictability of physiological testing and the role of maturation in talent identification for adolescent team sports.

PubMed

Pearson, D T; Naughton, G A; Torode, M

2006-08-01

Entrepreneurial marketing of sport increases demands on sport development officers to identify talented individuals for specialist development at the youngest possible age. Talent identification results in the streamlining of resources to produce optimal returns from a sports investment. However, the process of talent identification for team sports is complex and success prediction is imperfect. The aim of this review is to describe existing practices in physiological tests used for talent identification in team sports and discuss the impact of maturity-related differences on the long term outcomes particularly for male participants. Maturation is a major confounding variable in talent identification during adolescence. A myriad of hormonal changes during puberty results in physical and physiological characteristics important for sporting performance. Significant changes during puberty make the prediction of adult performance difficult from adolescent data. Furthermore, for talent identification programs to succeed, valid and reliable testing procedures must be accepted and implemented in a range of performance-related categories. Limited success in scientifically based talent identification is evident in a range of team sports. Genetic advances challenge the ethics of talent identification in adolescent sport. However, the environment remains a significant component of success prediction in sport. Considerations for supporting talented young male athletes are discussed.

Ensemble framework based real-time respiratory motion prediction for adaptive radiotherapy applications.

PubMed

Tatinati, Sivanagaraja; Nazarpour, Kianoush; Tech Ang, Wei; Veluvolu, Kalyana C

2016-08-01

Successful treatment of tumors with motion-adaptive radiotherapy requires accurate prediction of respiratory motion, ideally with a prediction horizon larger than the latency in radiotherapy system. Accurate prediction of respiratory motion is however a non-trivial task due to the presence of irregularities and intra-trace variabilities, such as baseline drift and temporal changes in fundamental frequency pattern. In this paper, to enhance the accuracy of the respiratory motion prediction, we propose a stacked regression ensemble framework that integrates heterogeneous respiratory motion prediction algorithms. We further address two crucial issues for developing a successful ensemble framework: (1) selection of appropriate prediction methods to ensemble (level-0 methods) among the best existing prediction methods; and (2) finding a suitable generalization approach that can successfully exploit the relative advantages of the chosen level-0 methods. The efficacy of the developed ensemble framework is assessed with real respiratory motion traces acquired from 31 patients undergoing treatment. Results show that the developed ensemble framework improves the prediction performance significantly compared to the best existing methods. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Sense and simplicity in HADDOCK scoring: Lessons from CASP‐CAPRI round 1

PubMed Central

Vangone, A.; Rodrigues, J. P. G. L. M.; Xue, L. C.; van Zundert, G. C. P.; Geng, C.; Kurkcuoglu, Z.; Nellen, M.; Narasimhan, S.; Karaca, E.; van Dijk, M.; Melquiond, A. S. J.; Visscher, K. M.; Trellet, M.; Kastritis, P. L.

2016-01-01

ABSTRACT Our information‐driven docking approach HADDOCK is a consistent top predictor and scorer since the start of its participation in the CAPRI community‐wide experiment. This sustained performance is due, in part, to its ability to integrate experimental data and/or bioinformatics information into the modelling process, and also to the overall robustness of the scoring function used to assess and rank the predictions. In the CASP‐CAPRI Round 1 scoring experiment we successfully selected acceptable/medium quality models for 18/14 of the 25 targets – a top‐ranking performance among all scorers. Considering that for only 20 targets acceptable models were generated by the community, our effective success rate reaches as high as 90% (18/20). This was achieved using the standard HADDOCK scoring function, which, thirteen years after its original publication, still consists of a simple linear combination of intermolecular van der Waals and Coulomb electrostatics energies and an empirically derived desolvation energy term. Despite its simplicity, this scoring function makes sense from a physico‐chemical perspective, encoding key aspects of biomolecular recognition. In addition to its success in the scoring experiment, the HADDOCK server takes the first place in the server prediction category, with 16 successful predictions. Much like our scoring protocol, because of the limited time per target, the predictions relied mainly on either an ab initio center‐of‐mass and symmetry restrained protocol, or on a template‐based approach whenever applicable. These results underline the success of our simple but sensible prediction and scoring scheme. Proteins 2017; 85:417–423. © 2016 Wiley Periodicals, Inc. PMID:27802573

A Model for Predicting Student Performance on High-Stakes Assessment

ERIC Educational Resources Information Center

Dammann, Matthew Walter

2010-01-01

This research study examined the use of student achievement on reading and math state assessments to predict success on the science state assessment. Multiple regression analysis was utilized to test the prediction for all students in grades 5 and 8 in a mid-Atlantic state. The prediction model developed from the analysis explored the combined…

Plasmonic Light Trapping in Thin-Film Solar Cells: Impact of Modeling on Performance Prediction

PubMed Central

Micco, Alberto; Pisco, Marco; Ricciardi, Armando; Mercaldo, Lucia V.; Usatii, Iurie; La Ferrara, Vera; Delli Veneri, Paola; Cutolo, Antonello; Cusano, Andrea

2015-01-01

We present a comparative study on numerical models used to predict the absorption enhancement in thin-film solar cells due to the presence of structured back-reflectors exciting, at specific wavelengths, hybrid plasmonic-photonic resonances. To evaluate the effectiveness of the analyzed models, they have been applied in a case study: starting from a U-shaped textured glass thin-film, µc-Si:H solar cells have been successfully fabricated. The fabricated cells, with different intrinsic layer thicknesses, have been morphologically, optically and electrically characterized. The experimental results have been successively compared with the numerical predictions. We have found that, in contrast to basic models based on the underlying schematics of the cell, numerical models taking into account the real morphology of the fabricated device, are able to effectively predict the cells performances in terms of both optical absorption and short-circuit current values.

Occupational-Specific Strength Predicts Astronaut-Related Task Performance in a Weighted Suit.

PubMed

Taylor, Andrew; Kotarsky, Christopher J; Bond, Colin W; Hackney, Kyle J

2018-01-01

Future space missions beyond low Earth orbit will require deconditioned astronauts to perform occupationally relevant tasks within a planetary spacesuit. The prediction of time-to-completion (TTC) of astronaut tasks will be critical for crew safety, autonomous operations, and mission success. This exploratory study determined if the addition of task-specific strength testing to current standard lower body testing would enhance the prediction of TTC in a 1-G test battery. Eight healthy participants completed NASA lower body strength tests, occupationally specific strength tests, and performed six task simulations (hand drilling, construction wrenching, incline walking, collecting weighted samples, and dragging an unresponsive crewmember to safety) in a 48-kg weighted suit. The TTC for each task was recorded and summed to obtain a total TTC for the test battery. Linear regression was used to predict total TTC with two models: 1) NASA lower body strength tests; and 2) NASA lower body strength tests + occupationally specific strength tests. Total TTC of the test battery ranged from 20.2-44.5 min. The lower body strength test alone accounted for 61% of the variability in total TTC. The addition of hand drilling and wrenching strength tests accounted for 99% of the variability in total TTC. Adding occupationally specific strength tests (hand drilling and wrenching) to standard lower body strength tests successfully predicted total TTC in a performance test battery within a weighted suit. Future research should couple these strength tests with higher fidelity task simulations to determine the utility and efficacy of task performance prediction.Taylor A, Kotarsky CJ, Bond CW, Hackney KJ. Occupational-specific strength predicts astronaut-related task performance in a weighted suit. Aerosp Med Hum Perform. 2018; 89(1):58-62.

Improved LTVMPC design for steering control of autonomous vehicle

NASA Astrophysics Data System (ADS)

Velhal, Shridhar; Thomas, Susy

2017-01-01

An improved linear time varying model predictive control for steering control of autonomous vehicle running on slippery road is presented. Control strategy is designed such that the vehicle will follow the predefined trajectory with highest possible entry speed. In linear time varying model predictive control, nonlinear vehicle model is successively linearized at each sampling instant. This linear time varying model is used to design MPC which will predict the future horizon. By incorporating predicted input horizon in each successive linearization the effectiveness of controller has been improved. The tracking performance using steering with front wheel and braking at four wheels are presented to illustrate the effectiveness of the proposed method.

Personality and academic performance of three cohorts of veterinary students in South Africa.

PubMed

van der Walt, H S; Pickworth, Glynis

2007-01-01

To aid in selecting students for admission to undergraduate veterinary training, admissions procedures often take into account students' previous academic performance as well as the results of an interview. The study reported here investigated the relationship between personality and academic success. Students from three entry cohorts to the second year of study of a six-year BVSc program at the University of Pretoria completed the 16 Personality Factor Questionnaire. A meta-analytic approach was used to estimate the relationship between academic performance in two major final-year subjects and academic performance on entry, an interview score, and the personality factors. The study confirmed the value of previous academic performance and the interview in selecting students for the veterinary degree program. The findings also indicate that the inclusion of a measure of intellectual ability could be of value. The value of various personality characteristics in predicting good study habits and examination performance is highlighted by the study results: students were more successful if they were conscientious, emotionally stable, socially adept, self-disciplined, practical rather than imaginative, and relaxed rather than anxious. It appears worthwhile to consider including an appropriate personality questionnaire in the selection process to improve the accuracy of predictions of students' success. A sound personality make-up will not only increase the likelihood of academic success but should also be beneficial in the successful management of a veterinary practice and in enjoying veterinary science as a career.

Neural correlates of encoding processes predicting subsequent cued recall and source memory.

PubMed

Angel, Lucie; Isingrini, Michel; Bouazzaoui, Badiâa; Fay, Séverine

2013-03-06

In this experiment, event-related potentials were used to examine whether the neural correlates of encoding processes predicting subsequent successful recall differed from those predicting successful source memory retrieval. During encoding, participants studied lists of words and were instructed to memorize each word and the list in which it occurred. At test, they had to complete stems (the first four letters) with a studied word and then make a judgment of the initial temporal context (i.e. list). Event-related potentials recorded during encoding were segregated according to subsequent memory performance to examine subsequent memory effects (SMEs) reflecting successful cued recall (cued recall SME) and successful source retrieval (source memory SME). Data showed a cued recall SME on parietal electrode sites from 400 to 1200 ms and a late inversed cued recall SME on frontal sites in the 1200-1400 ms period. Moreover, a source memory SME was reported from 400 to 1400 ms on frontal areas. These findings indicate that patterns of encoding-related activity predicting successful recall and source memory are clearly dissociated.

VWPS: A Ventilator Weaning Prediction System with Artificial Intelligence

NASA Astrophysics Data System (ADS)

Chen, Austin H.; Chen, Guan-Ting

How to wean patients efficiently off mechanical ventilation continues to be a challenge for medical professionals. In this paper we have described a novel approach to the study of a ventilator weaning prediction system (VWPS). Firstly, we have developed and written three Artificial Neural Network (ANN) algorithms to predict a weaning successful rate based on the clinical data. Secondly, we have implemented two user-friendly weaning success rate prediction systems; the VWPS system and the BWAP system. Both systems could be used to help doctors objectively and effectively predict whether weaning is appropriate for patients based on the patients' clinical data. Our system utilizes the powerful processing abilities of MatLab. Thirdly, we have calculated the performance through measures such as sensitivity and accuracy for these three algorithms. The results show a very high sensitivity (around 80%) and accuracy (around 70%). To our knowledge, this is the first design approach of its kind to be used in the study of ventilator weaning success rate prediction.

Factors predicting labor induction success: a critical analysis.

PubMed

Crane, Joan M G

2006-09-01

Because of the risk of failed induction of labor, a variety of maternal and fetal factors as well as screening tests have been suggested to predict labor induction success. Certain characteristics of the woman (including parity, age, weight, height and body mass index), and of the fetus (including birth weight and gestational age) are associated with the success of labor induction; with parous, young women who are taller and lower weight having a higher rate of induction success. Fetuses with a lower birth weight or increased gestational age are also associated with increased induction success. The condition of the cervix at the start of induction is an important predictor, with the modified Bishop score being a widely used scoring system. The most important element of the Bishop score is dilatation. Other predictors, including transvaginal ultrasound (TVUS) and biochemical markers [including fetal fibronectin (fFN)] have been suggested. Meta-analyses of studies identified from MEDLINE, PubMed, and EMBASE and published from 1990 to October 2005 were performed evaluating the use of TVUS and fFN in predicting labor induction success in women at term with singleton gestations. Both TVUS and Bishop score predicted successful induction [likelihood ratio (LR)=1.82, 95% confidence interval (CI)=1.51-2.20 and LR=2.10, 95%CI=1.67-2.64, respectively]. As well, fFN and Bishop score predicted successful induction (LR=1.49, 95%CI=1.20-1.85, and LR=2.62, 95%CI=1.88-3.64, respectively). Although TVUS and fFN predicted successful labor induction, neither has been shown to be superior to Bishop score. Further research is needed to evaluate these potential predictors and insulin-like growth factor binding protein-1 (IGFBP-1), another potential biochemical marker.

Use of computed tomography to predict the outcome of a noninvasive intranasal infusion in dogs with nasal aspergillosis

PubMed Central

Saunders, Jimmy H.; Duchateau, Luc; Störk, Christophe; van Bree, Henri

2003-01-01

Computed tomography (CT) was performed on 36 dogs with nasal aspergillosis to assess whether this imaging technique can be used to predict the success of a noninvasive intranasal infusion of enilconazole. A CT score based on the severity of the disease was given to each dog, prior to treatment, by dividing the nasal cavities and frontal sinuses into 8 anatomical regions. After therapy, the dogs were classified into 2 response groups (success group: dogs cured after 1 treatment; failure group: dogs needing more than 1 treatment or with treatment failure). No significant relationship on the logistic scale was found between the CT score and the response to treatment. High sensitivity (treatment failures correctly predicted) and specificity (treatment successes correctly predicted) could not be obtained at the same time, whatever the cut-off value chosen. The results of this study suggest that CT cannot predict the therapeutic success of nasal aspergillosis in dogs treated with a 1-hour infusion of enilconazole. However, dogs with a low score seem to be good candidates to respond after 1 treatment. PMID:12715982

A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2013-02-01

The purpose of the present study is to compare the prediction performances of three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) for landslide susceptibility mapping at Penang Hill area, Malaysia. The necessary input parameters for the landslide susceptibility assessments were obtained from various sources. At first, landslide locations were identified by aerial photographs and field surveys and a total of 113 landslide locations were constructed. The study area contains 340,608 pixels while total 8403 pixels include landslides. The landslide inventory was randomly partitioned into two subsets: (1) part 1 that contains 50% (4000 landslide grid cells) was used in the training phase of the models; (2) part 2 is a validation dataset 50% (4000 landslide grid cells) for validation of three models and to confirm its accuracy. The digitally processed images of input parameters were combined in GIS. Finally, landslide susceptibility maps were produced, and the performances were assessed and discussed. Total fifteen landslide susceptibility maps were produced using DT, SVM and ANFIS based models, and the resultant maps were validated using the landslide locations. Prediction performances of these maps were checked by receiver operating characteristics (ROC) by using both success rate curve and prediction rate curve. The validation results showed that, area under the ROC curve for the fifteen models produced using DT, SVM and ANFIS varied from 0.8204 to 0.9421 for success rate curve and 0.7580 to 0.8307 for prediction rate curves, respectively. Moreover, the prediction curves revealed that model 5 of DT has slightly higher prediction performance (83.07), whereas the success rate showed that model 5 of ANFIS has better prediction (94.21) capability among all models. The results of this study showed that landslide susceptibility mapping in the Penang Hill area using the three approaches (e.g., DT, SVM and ANFIS) is viable. As far as the performance of the models are concerned, the results appeared to be quite satisfactory, i.e., the zones determined on the map being zones of relative susceptibility.

Germination prediction from soil moisture and temperature in the Great Basin

USDA-ARS?s Scientific Manuscript database

Preventing cheatgrass (Bromus tectorum L.) dominance associated with frequent wildfires may depend on successful establishment of desirable species sown in rehabilitation and fuel control projects. Ranking potential species success to develop more performance-based species selection for revegetatio...

What predicts performance during clinical psychology training?

PubMed Central

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

2014-01-01

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

Predictive Performance Assessment: Trait and State Dimensions Should not be Confused

NASA Astrophysics Data System (ADS)

Pattyn, N.; Migeotte, P.-F.; Morais, J.; Cluydts, R.; Soetens, E.; Meeusen, R.; de Schutter, G.; Nederhof, E.; Kolinsky, R.

2008-06-01

One of the major aims of performance investigation is to obtain a measure predicting real-life performance, in order to prevent consequences of a potential decrement. Whereas the predictive validity of such assessment has been extensively described for long-term outcomes, as is the case for testing in selection context, equivalent evidence is lacking regarding the short-term predictive value of cognitive testing, i.e., whether these results reflect real-life performance on an immediately subsequent task. In this series of experiments, we investigated both medium-term and short-term predictive value of psychophysiological testing with regard to real-life performance in two operational settings: military student pilots with regard to their success on an evaluation flight, and special forces candidates with regard to their performance on their training course. Our results showed some relationships between test performance and medium-term outcomes. However, no short-term predictive value could be identified for cognitive testing, despite the fact physiological data showed interesting trends. We recommend a critical distinction between "state" and "trait" dimensions of performance with regard to the predictive value of testing.

Against the Odds: Influences on the Post-School Success of "Low Performers"

ERIC Educational Resources Information Center

Thomson, Sue; Hillman, Kylie

2010-01-01

The link between academic achievement and labour market outcomes is well established. But how well does a student's achievement in a test predict their later success in life? This study examines this question, with "success" considered to encompass satisfaction with life together with the extent to which young people are fully occupied…

A Course Specific Perspective in the Prediction of Academic Success.

ERIC Educational Resources Information Center

Beaulieu, R. P.

1990-01-01

Students (N=94) enrolled in a senior-level management course over six semesters were used to investigate the ability of four measures from two industrial tests to predict course performance. The resulting multiple regression equation with four predictors could accurately predict achievement of males, but not of females. (Author/TE)

Determining Functional Reliability of Pyrotechnic Mechanical Devices

NASA Technical Reports Server (NTRS)

Bement, Laurence J.; Multhaup, Herbert A.

1997-01-01

This paper describes a new approach for evaluating mechanical performance and predicting the mechanical functional reliability of pyrotechnic devices. Not included are other possible failure modes, such as the initiation of the pyrotechnic energy source. The requirement of hundreds or thousands of consecutive, successful tests on identical components for reliability predictions, using the generally accepted go/no-go statistical approach routinely ignores physics of failure. The approach described in this paper begins with measuring, understanding and controlling mechanical performance variables. Then, the energy required to accomplish the function is compared to that delivered by the pyrotechnic energy source to determine mechanical functional margin. Finally, the data collected in establishing functional margin is analyzed to predict mechanical functional reliability, using small-sample statistics. A careful application of this approach can provide considerable cost improvements and understanding over that of go/no-go statistics. Performance and the effects of variables can be defined, and reliability predictions can be made by evaluating 20 or fewer units. The application of this approach to a pin puller used on a successful NASA mission is provided as an example.

Team Teaching.

ERIC Educational Resources Information Center

Cunningham, David C.

1963-01-01

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

Predicting Airport Screening Officers' Visual Search Competency With a Rapid Assessment.

PubMed

Mitroff, Stephen R; Ericson, Justin M; Sharpe, Benjamin

2018-03-01

Objective The study's objective was to assess a new personnel selection and assessment tool for aviation security screeners. A mobile app was modified to create a tool, and the question was whether it could predict professional screeners' on-job performance. Background A variety of professions (airport security, radiology, the military, etc.) rely on visual search performance-being able to detect targets. Given the importance of such professions, it is necessary to maximize performance, and one means to do so is to select individuals who excel at visual search. A critical question is whether it is possible to predict search competency within a professional search environment. Method Professional searchers from the USA Transportation Security Administration (TSA) completed a rapid assessment on a tablet-based X-ray simulator (XRAY Screener, derived from the mobile technology app Airport Scanner; Kedlin Company). The assessment contained 72 trials that were simulated X-ray images of bags. Participants searched for prohibited items and tapped on them with their finger. Results Performance on the assessment significantly related to on-job performance measures for the TSA officers such that those who were better XRAY Screener performers were both more accurate and faster at the actual airport checkpoint. Conclusion XRAY Screener successfully predicted on-job performance for professional aviation security officers. While questions remain about the underlying cognitive mechanisms, this quick assessment was found to significantly predict on-job success for a task that relies on visual search performance. Application It may be possible to quickly assess an individual's visual search competency, which could help organizations select new hires and assess their current workforce.

Seeing what you want to see: priors for one's own actions represent exaggerated expectations of success

PubMed Central

Wolpe, Noham; Wolpert, Daniel M.; Rowe, James B.

2014-01-01

People perceive the consequences of their own actions differently to how they perceive other sensory events. A large body of psychology research has shown that people also consistently overrate their own performance relative to others, yet little is known about how these “illusions of superiority” are normally maintained. Here we examined the visual perception of the sensory consequences of self-generated and observed goal-directed actions. Across a series of visuomotor tasks, we found that the perception of the sensory consequences of one's own actions is more biased toward success relative to the perception of observed actions. Using Bayesian models, we show that this bias could be explained by priors that represent exaggerated predictions of success. The degree of exaggeration of priors was unaffected by learning, but was correlated with individual differences in trait optimism. In contrast, when observing these actions, priors represented more accurate predictions of the actual performance. The results suggest that the brain internally represents optimistic predictions for one's own actions. Such exaggerated predictions bind the sensory consequences of our own actions with our intended goal, explaining how it is that when acting we tend to see what we want to see. PMID:25018710

Can Medical School Performance Predict Residency Performance? Resident Selection and Predictors of Successful Performance in Obstetrics and Gynecology

PubMed Central

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

What predicts performance during clinical psychology training?

PubMed

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

2014-06-01

While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Longitudinal cross-sectional study using prospective and retrospective data. Characteristics at application were analysed in relation to a range of in-course assessments for 274 trainee clinical psychologists who had completed or were in the final stage of their training. Trainees were diverse in age, pre-training experience, and academic performance at A-level (advanced level certificate required for university admission), but not in gender or ethnicity. Failure rates across the three performance domains (academic, clinical, research) were very low, suggesting that selection was successful in screening out less suitable candidates. Key predictors of good performance on the course were better A-levels and better degree class. Non-white students performed less well on two outcomes. Type and extent of pre-training clinical experience on outcomes had varied effects on outcome. Research supervisor ratings emerged as global indicators and predicted nearly all outcomes, but may have been biased as they were retrospective. Referee ratings predicted only one of the seven outcomes examined, and interview ratings predicted none of the outcomes. Predicting who will do well or poorly in clinical psychology training is complex. Interview and referee ratings may well be successful in screening out unsuitable candidates, but appear to be a poor guide to performance on the course. © 2013 The Authors. British Journal of Clinical Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.

Performance Measures for Adaptive Decisioning Systems

DTIC Science & Technology

1991-09-11

set to hypothesis space mapping best approximates the known map. Two assumptions, a sufficiently representative training set and the ability of the...successful prediction of LINEXT performance. The LINEXT algorithm above performs the decision space mapping on the training-set ele- ments exactly. For a

Psychosocial Characteristics of Optimum Performance in Isolated and Confined Environments (ICE)

NASA Technical Reports Server (NTRS)

Palinkas, Lawrence A.; Keeton, Kathryn E.; Shea, Camille; Leveton, Lauren B.

2010-01-01

The Behavioral Health and Performance (BHP) Element addresses human health risks in the NASA Human Research Program (HRP), including the Risk of Adverse Behavioral Conditions and the Risk of Psychiatric Disorders. BHP supports and conducts research to help characteristics and mitigate the Behavioral Medicine risk for exploration missions, and in some instances, current Flight Medical Operations. The Behavioral Health and Performance (BHP) Element identified research gaps within the Behavioral Medicine Risk, including Gap BMed6: What psychosocial characteristics predict success in an isolated, confined environment (ICE)? To address this gap, we conducted an extensive and exhaustive literature review to identify the following: 1) psychosocial characteristics that predict success in ICE environments; 2) characteristics that are most malleable; and 3) specific countermeasures that could enhance malleable characteristics.

The hot hand belief and framing effects.

PubMed

MacMahon, Clare; Köppen, Jörn; Raab, Markus

2014-09-01

Recent evidence of the hot hand in sport-where success breeds success in a positive recency of successful shots, for instance-indicates that this pattern does not actually exist. Yet the belief persists. We used 2 studies to explore the effects of framing on the hot hand belief in sport. We looked at the effect of sport experience and task on the perception of baseball pitch behavior as well as the hot hand belief and free-throw behavior in basketball. Study 1 asked participants to designate outcomes with different alternation rates as the result of baseball pitches or coin tosses. Study 2 examined basketball free-throw behavior and measured predicted success before each shot as well as general belief in the hot hand pattern. The results of Study 1 illustrate that experience and stimulus alternation rates influence the perception of chance in human performance tasks. Study 2 shows that physically performing an act and making judgments are related. Specifically, beliefs were related to overall performance, with more successful shooters showing greater belief in the hot hand and greater predicted success for upcoming shots. Both of these studies highlight that the hot hand belief is influenced by framing, which leads to instability and situational contingencies. We show the specific effects of framing using accumulated experience of the individual with the sport and knowledge of its structure and specific experience with sport actions (basketball shots) prior to judgments.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation.

PubMed

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-08-01

The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient ( P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation

PubMed Central

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-01-01

Background and Aims: The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. Materials and Methods: In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. Results: The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient (P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). Conclusion: The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning. PMID:28904477

Connecting English Language Learning and Academic Performance: A Prediction Study

ERIC Educational Resources Information Center

Kong, Jadie; Powers, Sonya; Starr, Laura; Williams, Natasha

2012-01-01

The purpose of this study was to investigate the use of English language proficiency and academic reading assessment scores to predict the future academic success of English learner (EL) students. Data from two cohorts of middle-school ELs were used to evaluate three prediction models. One cohort of students was used to develop the prediction…

Are corticosterone levels a good indicator of food availability and reproductive performance in a kittiwake colony?

USGS Publications Warehouse

Lanctot, Richard B.; Hatch, Shyla A.; Gill, Verena A.; Eens, Marcel

2003-01-01

We evaluated the use of corticosterone to gauge forage availability and predict reproductive performance in black-legged kittiwakes (Rissa tridactyla) breeding in Alaska during 1999 and 2000. We modeled the relationship between baseline levels of corticosterone and a suite of individual and temporal characteristics of the sampled birds. We also provided supplemental food to a sample of pairs and compared their corticosterone levels with that of pairs that were not fed. Corticosterone levels were a good predictor of forage availability in some situations, although inconsistencies between corticosterone levels and reproductive performance of fed and unfed kittiwakes suggested that this was not always the case. In general, higher corticosterone levels were found in birds that lacked breeding experience and in birds sampled shortly after arriving from their wintering grounds. All parameters investigated, however, explained only a small proportion of the variance in corticosterone levels. We also investigated whether corticosterone, supplemental feeding, year of the study, breeding experience, body weight, and sex of a bird were able to predict laying, hatching, and fledging success in kittiwakes. Here, breeding experience, year of the study, and body weight were the best predictors of a bird’s performance. Corticosterone level and supplemental feeding were good predictors of kittiwake reproductive performance in some cases. For example, corticosterone levels of birds sampled during the arrival stage reliably predicted laying success, but were less reliable at predicting hatching and fledging success. Counts of active nests with eggs or chicks may be more reliable estimates of the actual productivity of the colony. Supplemental feeding had strong effects on kittiwake productivity when natural forage was poor, but had little effect when natural forage was plentiful.

Vital Signs: How Early Can Resident Evaluation Predict Acquisition of Competency in Surgical Pathology?

PubMed Central

Ducatman, Barbara S.; Williams, H. James; Hobbs, Gerald; Gyure, Kymberly A.

2009-01-01

Objectives To determine whether a longitudinal, case-based evaluation system can predict acquisition of competency in surgical pathology and how trainees at risk can be identified early. Design Data were collected for trainee performance on surgical pathology cases (how well their diagnosis agreed with the faculty diagnosis) and compared with training outcomes. Negative training outcomes included failure to complete the residency, failure to pass the anatomic pathology component of the American Board of Pathology examination, and/or failure to obtain or hold a position immediately following training. Findings Thirty-three trainees recorded diagnoses for 54 326 surgical pathology cases, with outcome data available for 15 residents. Mean case-based performance was significantly higher for those with positive outcomes, and outcome status could be predicted as early as postgraduate year-1 (P  =  .0001). Performance on the first postgraduate year-1 rotation was significantly associated with the outcome (P  =  .02). Although trainees with unsuccessful outcomes improved their performance more rapidly, they started below residents with successful outcomes and did not make up the difference during training. There was no significant difference in Step 1 or 2 United States Medical Licensing Examination (USMLE) scores when compared with performance or final outcomes (P  =  .43 and P  =  .68, respectively) and the resident in-service examination (RISE) had limited predictive ability. Discussion Differences between successful- and unsuccessful-outcome residents were most evident in early residency, ideal for designing interventions or counseling residents to consider another specialty. Conclusion Our longitudinal case-based system successfully identified trainees at risk for failure to acquire critical competencies for surgical pathology early in the program. PMID:21975705

Predicting Success of Developmental Math Students

ERIC Educational Resources Information Center

Martinez, Isaac

2017-01-01

Addressing the needs of developmental math students has been one of the most challenging problems in higher education. Administrators at a private university were concerned about poor academic performance of math-deficient students and sought to identify factors that influenced students' successful progression from developmental to college-level…

Predictive models to determine imagery strategies employed by children to judge hand laterality.

PubMed

Spruijt, Steffie; Jongsma, Marijtje L A; van der Kamp, John; Steenbergen, Bert

2015-01-01

A commonly used paradigm to study motor imagery is the hand laterality judgment task. The present study aimed to determine which strategies young children employ to successfully perform this task. Children of 5 to 8 years old (N = 92) judged laterality of back and palm view hand pictures in different rotation angles. Response accuracy and response duration were registered. Response durations of the trials with a correct judgment were fitted to a-priori defined predictive sinusoid models, representing different strategies to successfully perform the hand laterality judgment task. The first model predicted systematic changes in response duration as a function of rotation angle of the displayed hand. The second model predicted that response durations are affected by biomechanical constraints of hand rotation. If observed data could be best described by the first model, this would argue for a mental imagery strategy that does not involve motor processes to solve the task. The second model reflects a motor imagery strategy to solve the task. In line with previous research, we showed an age-related increase in response accuracy and decrease in response duration in children. Observed data for both back and palm view showed that motor imagery strategies were used to perform hand laterality judgments, but that not all the children use these strategies (appropriately) at all times. A direct comparison of response duration patterns across age sheds new light on age-related differences in the strategies employed to solve the task. Importantly, the employment of the motor imagery strategy for successful task performance did not change with age.

Preoperative Ultrasound Prediction of Essential Landmarks for Successful Fetoscopic Laser Treatment of Twin-Twin Transfusion Syndrome.

PubMed

Miller, Jena L; Block-Abraham, Dana M; Blakemore, Karin J; Baschat, Ahmet A

2018-06-06

The insertion site of the fetoscope for laser occlusion (FLOC) treatment of twin-twin transfusion syndrome (TTTS) determines the likelihood of treatment success. We assessed a standardized preoperative ultrasound approach for its ability to identify critical landmarks for successful FLOC. Three surgeons independently performed preoperative ultrasound and deduced the likely orientation of the intertwin membrane (ITM) and vascular equator (VE) based on the sites of the cord insertion, the lie of the donor, and the size discordance between twins. At FLOC, these landmarks were visually verified and compared to preoperative assessments. Fifty consecutive FLOC surgeries had 127 preoperative assessments. Basic ITM and VE orientation were accurately predicted in 115 (90.6%), 109 (85.8%), and 105 (82.7%) assessments. Predictions were anatomically correct in 96 (75.6%), 70 (55.1%), and 58 (45.7%) assessments with no differences in accuracy between operators of different training level. The ITM/VE relationship was most poorly predicted in stage-3 TTTS (χ2, p = 0.016). In TTTS, preoperative ultrasound identification of placental cord insertion sites, lie of the donor twin, and size discordance enables preoperative prediction of key landmarks for successful FLOC. © 2018 S. Karger AG, Basel.

Academic Performance in MBA Programs: Do Prerequisites Really Matter?

ERIC Educational Resources Information Center

Christensen, Donald Gene; Nance, William R.; White, Darin W.

2012-01-01

Many researchers have examined criteria used in Master of Business Administration (MBA) admissions decisions. However, prior research has not examined predictive ability of undergraduate prerequisite courses in core business disciplines. The authors investigated whether undergraduate prerequisite courses predicted MBA success by analyzing the…

On the relation between personality and job performance of airline pilots.

PubMed

Hormann, H J; Maschke, P

1996-01-01

The validity of a personality questionnaire for the prediction of job success of airline pilots is compared to validities of a simulator checkflight and of flying experience data. During selection, 274 pilots applying for employment with a European charter airline were examined with a multidimensional personality questionnaire (Temperature Structure Scales; TSS). Additionally, the applicants were graded in a simulator checkflight. On the basis of training records, the pilots were classified as performing at standard or below standard after about 3 years of employment in the hiring company. In a multiple-regression model, this dichotomous criterion for job success can be predicted with 73.8% accuracy through the simulator checkflight and flying experience prior to employment. By adding the personality questionnaire to the regression equation, the number of correct classifications increases to 79.3%. On average, successful pilots score substantially higher on interpersonal scales and lower on emotional scales of the TSS.

The Mars Exploration Rover (MER) Transverse Impulse Rocket System (TIRS)

NASA Technical Reports Server (NTRS)

SanMartin, Alejandro Miguel; Bailey, Erik

2005-01-01

In a very short period of time the MER project successfully developed and tested a system, TIRS/DIMES, to improve the probability of success in the presence of large Martian winds. The successful development of TIRS/DIMES played a big role in the landing site selection process by enabling the landing of Spirit on Gusev crater, a site of very high scientific interest but with known high wind conditions. The performance of TIRS by Spirit at Gusev Crater was excellent. The velocity prediction error was small and Big TIRS was fired reducing the impact horizontal velocity from approximately 23 meters per second to approximately 11 meters per second, well within the airbag capabilities. The performance of TIRS by Opportunity at Meridiani was good. The velocity prediction error was rather large (approximately 6 meters per second, a less than 2 sigma value, but TIRS did not fire which was the correct action.

Draft-camp predictors of subsequent career success in the Australian Football League.

PubMed

Burgess, Darren; Naughton, Geraldine; Hopkins, Will

2012-11-01

The National Draft Camp results are generally considered to be important for informing talent scouts about the physical performance capacities of talented young Australian Rules Football (AFL) players. The purpose of this project was to determine magnitude of associations between five year career success in the AFL and physical draft camp tests, final draft selection order and previous match physical performance. Physical testing data of 99 players from the National Under 18 (U 18) competition were retrospectively analysed across 2002 and 2003 National Draft Camps. Physical match data was collected on these players and links with subsequent early career success (AFL games played) were explored. TrakPerformance Software was used to quantify the movement of 92 players during competitive games of the National U 18 Championships. Linear modelling using results from draft camp data involving 95 U 18 players, along with final draft selection order, was used to predict five year career success in senior AFL. Multiple U 18 match variables demonstrated large associations (sprints/min=43% more games, % sprint=43% more games) with five year career success in AFL. Final draft order and single variable predictors had moderate associations with career success. Neither U 18 matches nor draft camp testing was predictive of injuries incurring over the five years. Variability in senior AFL career success had a large association with a combination of match physical variables and draft test results. The objective data available should be considered in the selection of prospective player success. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Investigating Academic Success Factors for Undergraduate Business Students

ERIC Educational Resources Information Center

Kaighobadi, Mehdi; Allen, Marcus T.

2008-01-01

Student academic performance is of major interest to all stakeholders of higher education institutions. This study questions whether or not statistical analysis of information that is readily available in most universities' official records system can be used to predict overall academic success. In particular, this study is an attempt to…

The Relationship between Career Motivation and Self-Efficacy with Protege Career Success

ERIC Educational Resources Information Center

Day, Rachel; Allen, Tammy D.

2004-01-01

Research exploring the underlying processes involved in successful mentorships has been lacking. In the present study, the roles of career motivation and career self-efficacy as explanatory factors were examined. Career motivation mediated the relationship between career mentoring and performance effectiveness. Contrary to prediction, only…

Suggesting a new framework for predictive performance assessment: Trait vs State dimensions.

NASA Astrophysics Data System (ADS)

Pattyn, Nathalie; Neyt, Xavier; Migeotte, Pierre-François; Morais, José; Soetens, Eric; Cluydts, Raymond; Meeusen, Romain; de Schutter, Guy; Nederhof, Esther; Kolinsky, Régine

IntroductionA major aim of performance investigation is to predict real-life performance, which is why both ESA (1) and NASA (2) have described the need to validly and reliably detect potential performance decrement as absolute requirements to manned long-duration missions. Whereas the predictive validity of such assessment has been extensively described for medium-term to long-term outcomes, as is the case for cognitive performance selection of student pilots for example, similar evidence is lacking regarding the immediate predictive value of cognitive testing, i.e., whether these results reflect real-life performance on an immediately subsequent task. Furthermore, whereas selection procedures are derived from population-based approaches, real-time monitoring of performance is often meant to be individual, which is an additional call for caution before concluding results from one setting to be applied to another. The MiniCog Rapid Assessment Battery (MRAB), which was termed by its authors "a blood pressure cuff for the mind" (3), aims at reflecting the functional status of a subject at any given moment. This battery was designed to provide a remote cognitive assessment of astronauts on a regular basis. We investigated its predictive value for real-life performance, together with a new approach to the assessment of cognitive performance in operational conditions, based on interference paradigms, the addition of emotionally loaded material and the concomitant measure of cardio-respiratory responses (4). MethodIn a first experiment, we investigated whether psychophysiological results would predict success of military student pilots (SPs; N=14) on a major evaluation flight right after the testing, and success in the rest of their flight training after a 6 months period. In a second experiment, we investigated whether extensive preliminary cognitive testing and individually tailored longitudinal monitoring of physical and cognitive performance could predict success of Special Forces trainees (N=7) during their training. ResultsThe first experiment showed no relationship whatsoever between cognitive performance on the very broad array of tests and immediately subsequent performance on the evaluation flight. However, physiological results showed a trend for students who passed the test to exhibit a larger physiological reactivity. Furthermore, the medium-term outcome of SPs in their flight training showed to be related to their test performance. Results of the second experiment (still in progress) will show whether, for an individual monitoring situation, there is a potential link between performance IQ and success on the training, and whether the longitudinal assessment of both cognitive performance, physical performance and physiological reactivity relates to immediately subsequent performance. DiscussionThese results suggest that a critical distinction could be made regarding predictive performance assessment, namely trait and state dimensions. Since one of the intended uses of operational test batteries is to provide an instantaneous measure of the cognitive status of the subject to allow the immediate execution of critical tasks, our results show this would be an inappropriate application so far. However, a dimension showing promising potential is the physiological reactivity. Whereas operational priorities clearly state the need for performance evaluation tools, their application cannot guide operational choices before sufficient validation allows justifying such decisions. References(1) HUMEX: Study on the Survivability and Adaptation of Humans to Long-duration Exploratory Missions (2000). European Space Agency. (2)BPCR: Bioastronautics Critical Path Roadmap (2004). National Aeronautics and Space Administration. (3) Shephard, J. M. and Kosslyn, S. M. (2005). The MiniCog rapid assessment battery: Developing a "blood pressure cuff for the mind". Avn Space Enl Medicine, 76, B192-B197. (4) Pattyn, N.; Migeotte, P.F.; Morais, J.; Soetens, E.; Cluydts, R. and Kolinsky, R. (2007). Crew performance monitoring: Putting some feeling into it. Proceedings of the 58th International Astronautical Congress, IAC-07-A1.1.04.

The nature and use of prediction skills in a biological computer simulation

NASA Astrophysics Data System (ADS)

Lavoie, Derrick R.; Good, Ron

The primary goal of this study was to examine the science process skill of prediction using qualitative research methodology. The think-aloud interview, modeled after Ericsson and Simon (1984), let to the identification of 63 program exploration and prediction behaviors.The performance of seven formal and seven concrete operational high-school biology students were videotaped during a three-phase learning sequence on water pollution. Subjects explored the effects of five independent variables on two dependent variables over time using a computer-simulation program. Predictions were made concerning the effect of the independent variables upon dependent variables through time. Subjects were identified according to initial knowledge of the subject matter and success at solving three selected prediction problems.Successful predictors generally had high initial knowledge of the subject matter and were formal operational. Unsuccessful predictors generally had low initial knowledge and were concrete operational. High initial knowledge seemed to be more important to predictive success than stage of Piagetian cognitive development.Successful prediction behaviors involved systematic manipulation of the independent variables, note taking, identification and use of appropriate independent-dependent variable relationships, high interest and motivation, and in general, higher-level thinking skills. Behaviors characteristic of unsuccessful predictors were nonsystematic manipulation of independent variables, lack of motivation and persistence, misconceptions, and the identification and use of inappropriate independent-dependent variable relationships.

The Use of High Performance Computing (HPC) to Strengthen the Development of Army Systems

DTIC Science & Technology

2011-11-01

accurately predicting the supersonic magus effect about spinning cones, ogive- cylinders , and boat-tailed afterbodies. This work led to the successful...successful computer model of the proposed product or system, one can then build prototypes on the computer and study the effects on the performance of...needed. The NRC report discusses the requirements for effective use of such computing power. One needs “models, algorithms, software, hardware

A Comparative Study of Classification and Regression Algorithms for Modelling Students' Academic Performance

ERIC Educational Resources Information Center

Strecht, Pedro; Cruz, Luís; Soares, Carlos; Mendes-Moreira, João; Abreu, Rui

2015-01-01

Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…

Ant colony optimization algorithm for interpretable Bayesian classifiers combination: application to medical predictions.

PubMed

Bouktif, Salah; Hanna, Eileen Marie; Zaki, Nazar; Abu Khousa, Eman

2014-01-01

Prediction and classification techniques have been well studied by machine learning researchers and developed for several real-word problems. However, the level of acceptance and success of prediction models are still below expectation due to some difficulties such as the low performance of prediction models when they are applied in different environments. Such a problem has been addressed by many researchers, mainly from the machine learning community. A second problem, principally raised by model users in different communities, such as managers, economists, engineers, biologists, and medical practitioners, etc., is the prediction models' interpretability. The latter is the ability of a model to explain its predictions and exhibit the causality relationships between the inputs and the outputs. In the case of classification, a successful way to alleviate the low performance is to use ensemble classiers. It is an intuitive strategy to activate collaboration between different classifiers towards a better performance than individual classier. Unfortunately, ensemble classifiers method do not take into account the interpretability of the final classification outcome. It even worsens the original interpretability of the individual classifiers. In this paper we propose a novel implementation of classifiers combination approach that does not only promote the overall performance but also preserves the interpretability of the resulting model. We propose a solution based on Ant Colony Optimization and tailored for the case of Bayesian classifiers. We validate our proposed solution with case studies from medical domain namely, heart disease and Cardiotography-based predictions, problems where interpretability is critical to make appropriate clinical decisions. The datasets, Prediction Models and software tool together with supplementary materials are available at http://faculty.uaeu.ac.ae/salahb/ACO4BC.htm.

Using Reflective Writing as a Predictor of Academic Success in Different Assessment Formats.

PubMed

Tsingos-Lucas, Cherie; Bosnic-Anticevich, Sinthia; Schneider, Carl R; Smith, Lorraine

2017-02-25

Objectives. To investigate whether reflective-writing skills are associated with academic success. Methods. Two hundred sixty-four students enrolled in a pharmacy practice course completed reflective statements. Regression procedures were conducted to determine whether reflective-writing skills were associated with academic success in different assessment formats: written, oral, and video tasks. Results. Reflective-writing skills were found to be a predictor of academic performance in some formats of assessment: written examination; oral assessment task and overall score for the Unit of Study (UoS). Reflective writing skills were not found to predict academic success in the video assessment task. Conclusions. Possessing good reflective-writing skills was associated with improved academic performance. Further research is recommended investigating the impact of reflective skill development on academic performance measures in other health education.

Predicting subcontractor performance using web-based Evolutionary Fuzzy Neural Networks.

PubMed

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.

Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks

PubMed Central

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. PMID:23864830

CREOG In-Training Examination Results: Contemporary Use to Predict ABOG Written Examination Outcomes

PubMed Central

Lingenfelter, Brandon M.; Jiang, Xuezhi; Schnatz, Peter F.; O'Sullivan, David M.; Minassian, Shahab S.; Forstein, David A.

2016-01-01

Background The in-training examination (ITE) offers formative assessments of residents' developing medical knowledge. Identification of an ITE performance level associated with success on the specialty board examination allows identification of “at risk” residents. Objective This study sought to identify a threshold score for obstetrics and gynecology residents' performance on the Council on Resident Education in Obstetrics and Gynecology (CREOG) ITE that predicts successful performance on the American Board of Obstetrics and Gynecology (ABOG) written examination. Methods We analyzed ITE and ABOG results of 80 residents who completed 4 years of CREOG ITEs at 2 institutions between 2002 and 2012. We assessed the level of performance associated with successful performance on the ABOG written examination. Results Data analyzed included scores for 71 of 80 residents (89%), with an overall pass rate of 82%. A postgraduate year (PGY) 4 score of 200 on the CREOG ITE or twice in any of the PGY training years was associated with a 100% ABOG pass rate. Scoring ≥ 205 in any PGY also was associated with a 100% pass rate. Residents who did not attain a score of 200 had a 35% to 45% chance of failing the ABOG written examination, depending on the PGY of the ITE performance. Conclusions Our findings suggest that a CREOG ITE score of at least 200 twice, or as a PGY-4, offers assurance of successful performance on the ABOG examination. Scores lower than this threshold may be used to identify “at risk” residents for added learning and provide program elements in need of improvement. PMID:27413437

CREOG In-Training Examination Results: Contemporary Use to Predict ABOG Written Examination Outcomes.

PubMed

Lingenfelter, Brandon M; Jiang, Xuezhi; Schnatz, Peter F; O'Sullivan, David M; Minassian, Shahab S; Forstein, David A

2016-07-01

The in-training examination (ITE) offers formative assessments of residents' developing medical knowledge. Identification of an ITE performance level associated with success on the specialty board examination allows identification of "at risk" residents. This study sought to identify a threshold score for obstetrics and gynecology residents' performance on the Council on Resident Education in Obstetrics and Gynecology (CREOG) ITE that predicts successful performance on the American Board of Obstetrics and Gynecology (ABOG) written examination. We analyzed ITE and ABOG results of 80 residents who completed 4 years of CREOG ITEs at 2 institutions between 2002 and 2012. We assessed the level of performance associated with successful performance on the ABOG written examination. Data analyzed included scores for 71 of 80 residents (89%), with an overall pass rate of 82%. A postgraduate year (PGY) 4 score of 200 on the CREOG ITE or twice in any of the PGY training years was associated with a 100% ABOG pass rate. Scoring ≥ 205 in any PGY also was associated with a 100% pass rate. Residents who did not attain a score of 200 had a 35% to 45% chance of failing the ABOG written examination, depending on the PGY of the ITE performance. Our findings suggest that a CREOG ITE score of at least 200 twice, or as a PGY-4, offers assurance of successful performance on the ABOG examination. Scores lower than this threshold may be used to identify "at risk" residents for added learning and provide program elements in need of improvement.

Transcatheter Arterial Embolization for Gastrointestinal Bleeding Associated with Gastric Carcinoma: Prognostic Factors Predicting Successful Hemostasis and Survival.

PubMed

Park, Sangik; Shin, Ji Hoon; Gwon, Dong-Il; Kim, Hyoung Jung; Sung, Kyu-Bo; Yoon, Hyun-Ki; Ko, Gi-Young; Ko, Heung Kyu

2017-07-01

To evaluate outcomes of transcatheter arterial embolization (TAE) for gastric cancer-related gastrointestinal (GI) bleeding and factors associated with successful TAE and improved survival after TAE. This retrospective study included 43 patients (34 men; age 60.6 y ± 13.6) with gastric cancer-related GI bleeding undergoing angiography between January 2000 and December 2015. Clinical course, laboratory findings, and TAE characteristics were reviewed. Technical success of TAE was defined as target area devascularization, and clinical success was defined as bleeding cessation with hemodynamic stability during 72 hours after TAE. Student t test was used for comparison of continuous variables, and Fisher exact test was used for categorical variables. Univariate and multivariate analysis were performed to identify predictors of successful TAE and 30-day survival after TAE. TAE was performed in 40 patients. Technical and clinical success rates of TAE were 85.0% and 65.0%, respectively. Splenic infarction occurred in 2 patients as a minor complication. Rebleeding after TAE occurred in 7 patients. Death related to bleeding occurred in 5 patients. Active bleeding (P = .044) and higher transfusion requirement (3.3 U ± 2.6 vs 1.8 U ± 1.7; P = .039) were associated with TAE failure. Successful TAE predicted improved 30-day survival after TAE on univariate and multivariate analysis (P = .018 and P = .022; odds ratio, 0.132). TAE for gastric cancer-associated GI bleeding may be a lifesaving procedure. Severe bleeding with a higher transfusion requirement and active bleeding on angiography predicted TAE failure. Copyright © 2017 SIR. Published by Elsevier Inc. All rights reserved.

Environment assisted degradation mechanisms in advanced light metals

NASA Technical Reports Server (NTRS)

Gangloff, R. P.; Stoner, G. E.; Swanson, R. E.

1989-01-01

A multifaceted research program on the performance of advanced light metallic alloys in aggressive aerospace environments, and associated environmental failure mechanisms was initiated. The general goal is to characterize alloy behavior quantitatively and to develop predictive mechanisms for environmental failure modes. Successes in this regard will provide the basis for metallurgical optimization of alloy performance, for chemical control of aggressive environments, and for engineering life prediction with damage tolerance and long term reliability.

Emotional intelligence predicts success in medical school.

PubMed

Libbrecht, Nele; Lievens, Filip; Carette, Bernd; Côté, Stéphane

2014-02-01

Accumulating evidence suggests that effective communication and interpersonal sensitivity during interactions between doctors and patients impact therapeutic outcomes. There is an important need to identify predictors of these behaviors, because traditional tests used in medical admissions offer limited predictions of "bedside manners" in medical practice. This study examined whether emotional intelligence would predict the performance of 367 medical students in medical school courses on communication and interpersonal sensitivity. One of the dimensions of emotional intelligence, the ability to regulate emotions, predicted performance in courses on communication and interpersonal sensitivity over the next 3 years of medical school, over and above cognitive ability and conscientiousness. Emotional intelligence did not predict performance on courses on medical subject domains. The results suggest that medical schools may better predict who will communicate effectively and show interpersonal sensitivity if they include measures of emotional intelligence in their admission systems. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Predicting success on the certification examinations of the American Board of Anesthesiology.

PubMed

McClintock, Joseph C; Gravlee, Glenn P

2010-01-01

Currently, residency programs lack objective predictors for passing the sequenced American Board of Anesthesiology (ABA) certification examinations on the first attempt. Our hypothesis was that performance on the ABA/American Society of Anesthesiologists In-Training Examination (ITE) and other variables can predict combined success on the ABA Part 1 and Part 2 examinations. The authors studied 2,458 subjects who took the ITE immediately after completing the first year of clinical anesthesia training and took the ABA Part 1 examination for primary certification immediately after completing residency training 2 yr later. ITE scores and other variables were used to predict which residents would complete the certification process (passing the ABA Part 1 and Part 2 examinations) in the shortest possible time after graduation. ITE scores alone accounted for most of the explained variation in the desired outcome of certification in the shortest possible time. In addition, almost half of the observed variation and most of the explained variance in ABA Part 1 scores was accounted for by ITE scores. A combined model using ITE scores, residency program accreditation cycle length, country of medical school, and gender best predicted which residents would complete the certification examinations in the shortest possible time. The principal implication of this study is that higher ABA/ American Society of Anesthesiologists ITE scores taken at the end of the first clinical anesthesia year serve as a significant and moderately strong predictor of high performance on the ABA Part 1 (written) examination, and a significant predictor of success in completing both the Part 1 and Part 2 examinations within the calendar year after the year of graduation from residency. Future studies may identify other predictors, and it would be helpful to identify factors that predict clinical performance as well.

Sex Differences in Secondary School Success: Why Female Students Perform Better

ERIC Educational Resources Information Center

Fischer, Franziska; Schult, Johannes; Hell, Benedikt

2013-01-01

School success is closely linked to intelligence but also to non-cognitive factors such as achievement motivation. The present study examines which non-cognitive factors predict secondary school grades and looks at reasons why female students tend to outperform their male counterparts. A sample of 554 German freshman students provided measures of…

Predicting Individuals' Learning Success from Patterns of Pre-Learning MRI Activity

PubMed Central

Vo, Loan T. K.; Walther, Dirk B.; Kramer, Arthur F.; Erickson, Kirk I.; Boot, Walter R.; Voss, Michelle W.; Prakash, Ruchika S.; Lee, Hyunkyu; Fabiani, Monica; Gratton, Gabriele; Simons, Daniel J.; Sutton, Bradley P.; Wang, Michelle Y.

2011-01-01

Performance in most complex cognitive and psychomotor tasks improves with training, yet the extent of improvement varies among individuals. Is it possible to forecast the benefit that a person might reap from training? Several behavioral measures have been used to predict individual differences in task improvement, but their predictive power is limited. Here we show that individual differences in patterns of time-averaged T2*-weighted MRI images in the dorsal striatum recorded at the initial stage of training predict subsequent learning success in a complex video game with high accuracy. These predictions explained more than half of the variance in learning success among individuals, suggesting that individual differences in neuroanatomy or persistent physiology predict whether and to what extent people will benefit from training in a complex task. Surprisingly, predictions from white matter were highly accurate, while voxels in the gray matter of the dorsal striatum did not contain any information about future training success. Prediction accuracy was higher in the anterior than the posterior half of the dorsal striatum. The link between trainability and the time-averaged T2*-weighted signal in the dorsal striatum reaffirms the role of this part of the basal ganglia in learning and executive functions, such as task-switching and task coordination processes. The ability to predict who will benefit from training by using neuroimaging data collected in the early training phase may have far-reaching implications for the assessment of candidates for specific training programs as well as the study of populations that show deficiencies in learning new skills. PMID:21264257

Qualitative Differences in Real-Time Solution of Standardized Figural Analogies.

ERIC Educational Resources Information Center

Schiano, Diane J.; And Others

Performance on standardized figural analogy tests is considered highly predictive of academic success. While information-processing models of analogy solution attribute performance differences to quantitative differences in processing parameters, the problem-solving literature suggests that qualitative differences in problem representation and…

Correlation of admissions statistics to graduate student success in medical physics

PubMed Central

McSpadden, Erin; Rakowski, Joseph; Nalichowski, Adrian; Yudelev, Mark; Snyder, Michael

2014-01-01

The purpose of this work is to develop metrics for evaluation of medical physics graduate student performance, assess relationships between success and other quantifiable factors, and determine whether graduate student performance can be accurately predicted by admissions statistics. A cohort of 108 medical physics graduate students from a single institution were rated for performance after matriculation based on final scores in specific courses, first year graduate Grade Point Average (GPA), performance on the program exit exam, performance in oral review sessions, and faculty rating. Admissions statistics including matriculating program (MS vs. PhD); undergraduate degree type, GPA, and country; graduate degree; general and subject GRE scores; traditional vs. nontraditional status; and ranking by admissions committee were evaluated for potential correlation with the performance metrics. GRE verbal and quantitative scores were correlated with higher scores in the most difficult courses in the program and with the program exit exam; however, the GRE section most correlated with overall faculty rating was the analytical writing section. Students with undergraduate degrees in engineering had a higher faculty rating than those from other disciplines and faculty rating was strongly correlated with undergraduate country. Undergraduate GPA was not statistically correlated with any success metrics investigated in this study. However, the high degree of selection on GPA and quantitative GRE scores during the admissions process results in relatively narrow ranges for these quantities. As such, these results do not necessarily imply that one should not strongly consider traditional metrics, such as undergraduate GPA and quantitative GRE score, during the admissions process. They suggest that once applicants have been initially filtered by these metrics, additional selection should be performed via the other metrics shown here to be correlated with success. The parameters used to make admissions decisions for our program are accurate in predicting student success, as illustrated by the very strong statistical correlation between admissions rank and course average, first year graduate GPA, and faculty rating (p<0.002). Overall, this study indicates that an undergraduate degree in physics should not be considered a fundamental requirement for entry into our program and that within the relatively narrow range of undergraduate GPA and quantitative GRE scores of those admitted into our program, additional variations in these metrics are not important predictors of success. While the high degree of selection on particular statistics involved in the admissions process, along with the relatively small sample size, makes it difficult to draw concrete conclusions about the meaning of correlations here, these results suggest that success in medical physics is based on more than quantitative capabilities. Specifically, they indicate that analytical and communication skills play a major role in student success in our program, as well as predicted future success by program faculty members. Finally, this study confirms that our current admissions process is effective in identifying candidates who will be successful in our program and are expected to be successful after graduation, and provides additional insight useful in improving our admissions selection process. PACS number: 01.40.‐d PMID:24423842

Fractal Tempo Fluctuation and Pulse Prediction

PubMed Central

Rankin, Summer K.; Large, Edward W.; Fink, Philip W.

2010-01-01

WE INVESTIGATED PEOPLES’ ABILITY TO ADAPT TO THE fluctuating tempi of music performance. In Experiment 1, four pieces from different musical styles were chosen, and performances were recorded from a skilled pianist who was instructed to play with natural expression. Spectral and rescaled range analyses on interbeat interval time-series revealed long-range (1/f type) serial correlations and fractal scaling in each piece. Stimuli for Experiment 2 included two of the performances from Experiment 1, with mechanical versions serving as controls. Participants tapped the beat at ¼- and ⅛-note metrical levels, successfully adapting to large tempo fluctuations in both performances. Participants predicted the structured tempo fluctuations, with superior performance at the ¼-note level. Thus, listeners may exploit long-range correlations and fractal scaling to predict tempo changes in music. PMID:25190901

Mars Science Laboratory Interplanetary Navigation Performance

NASA Technical Reports Server (NTRS)

Martin-Mur, Tomas J.; Kruizinga, Gerhard; Wong, Mau

2013-01-01

The Mars Science Laboratory spacecraft, carrying the Curiosity rover to Mars, hit the top of the Martian atmosphere just 200 meters from where it had been predicted more than six days earlier, and 2.6 million kilometers away. This un-expected level of accuracy was achieved by a combination of factors including: spacecraft performance, tracking data processing, dynamical modeling choices, and navigation filter setup. This paper will describe our best understanding of what were the factors that contributed to this excellent interplanetary trajectory prediction performance. The accurate interplanetary navigation contributed to the very precise landing performance, and to the overall success of the mission.

Computer-Related Success and Failure: A Longitudinal Field Study of the Factors Influencing Computer-Related Performance.

ERIC Educational Resources Information Center

Rozell, E. J.; Gardner, W. L., III

1999-01-01

A model of the intrapersonal processes impacting computer-related performance was tested using data from 75 manufacturing employees in a computer training course. Gender, computer experience, and attributional style were predictive of computer attitudes, which were in turn related to computer efficacy, task-specific performance expectations, and…

Unrealistic Optimism in the Pursuit of Academic Success

ERIC Educational Resources Information Center

Lewine, Rich; Sommers, Alison A.

2016-01-01

Although the ability to evaluate one's own knowledge and performance is critical to learning, the correlation between students' self-evaluation and actual performance measures is modest at best. In this study we examine the effect of offering extra credit for students' accurate prediction (self-accuracy) of their performance on four exams in two…

Identifying factors that predict the choice and success rate of radial artery catheterisation in contemporary real world cardiology practice: a sub-analysis of the PREVAIL study data.

PubMed

Pristipino, Christian; Roncella, Adriana; Trani, Carlo; Nazzaro, Marco S; Berni, Andrea; Di Sciascio, Germano; Sciahbasi, Alessandro; Musarò, Salvatore Donato; Mazzarotto, Pietro; Gioffrè, Gaetano; Speciale, Giulio

2010-06-01

To assess: the reasons behind an operator choosing to perform radial artery catheterisation (RAC) as against femoral arterial catheterisation, and to explore why RAC may fail in the real world. A pre-determined analysis of PREVAIL study database was performed. Relevant data were collected in a prospective, observational survey of 1,052 consecutive patients undergoing invasive cardiovascular procedures at nine Italian hospitals over a one month observation period. By multivariate analysis, the independent predictors of RAC choice were having the procedure performed: (1) at a high procedural volume centre; and (2) by an operator who performs a high volume of radial procedures; clinical variables played no statistically significant role. RAC failure was predicted independently by (1) a lower operator propensity to use RAC; and (2) the presence of obstructive peripheral artery disease. A 10-fold lower rate of RAC failure was observed among operators who perform RAC for > 85% of their personal caseload than among those who use RAC < 25% of the time (3.8% vs. 33.0%, respectively); by receiver operator characteristic (ROC) analysis, no threshold value for operator RAC volume predicted RAC failure. A routine RAC in all-comers is superior to a selective strategy in terms of feasibility and success rate.

Environment assisted degradation mechanisms in advanced light metals

NASA Technical Reports Server (NTRS)

Gangloff, Richard P.; Stoner, Glenn E.; Swanson, Robert E.

1988-01-01

The general goals of the research program are to characterize alloy behavior quantitatively and to develop predictive mechanisms for environmental failure modes. Successes in this regard will provide the basis for metallurgical optimization of alloy performance, for chemical control of aggressive environments, and for engineering life prediction with damage tolerance and long term reliability.

Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models.

PubMed

Liang, Shih-Hsiung; Walther, Bruno Andreas; Shieh, Bao-Sen

2017-01-01

Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction. Our final optimal models achieved relatively high performance values, and we discuss differences in performance with regard to sample size and variable treatments. Our results showed that, for both the establishment model and introduction model, the number of invaded countries was the most important or second most important determinant, respectively. Therefore, we suggest that future success for introduction and establishment of exotic birds may be gauged by simply looking at previous success in invading other countries. Finally, we found that species traits related to reproduction were more important in establishment models than in introduction models; importantly, these determinants were not averaged but either minimum or maximum values of species traits. Therefore, we suggest that in addition to averaged values, reproductive potential represented by minimum and maximum values of species traits should be considered in invasion studies.

Contrasting determinants for the introduction and establishment success of exotic birds in Taiwan using decision trees models

PubMed Central

Liang, Shih-Hsiung; Walther, Bruno Andreas

2017-01-01

Background Biological invasions have become a major threat to biodiversity, and identifying determinants underlying success at different stages of the invasion process is essential for both prevention management and testing ecological theories. To investigate variables associated with different stages of the invasion process in a local region such as Taiwan, potential problems using traditional parametric analyses include too many variables of different data types (nominal, ordinal, and interval) and a relatively small data set with too many missing values. Methods We therefore used five decision tree models instead and compared their performance. Our dataset contains 283 exotic bird species which were transported to Taiwan; of these 283 species, 95 species escaped to the field successfully (introduction success); of these 95 introduced species, 36 species reproduced in the field of Taiwan successfully (establishment success). For each species, we collected 22 variables associated with human selectivity and species traits which may determine success during the introduction stage and establishment stage. For each decision tree model, we performed three variable treatments: (I) including all 22 variables, (II) excluding nominal variables, and (III) excluding nominal variables and replacing ordinal values with binary ones. Five performance measures were used to compare models, namely, area under the receiver operating characteristic curve (AUROC), specificity, precision, recall, and accuracy. Results The gradient boosting models performed best overall among the five decision tree models for both introduction and establishment success and across variable treatments. The most important variables for predicting introduction success were the bird family, the number of invaded countries, and variables associated with environmental adaptation, whereas the most important variables for predicting establishment success were the number of invaded countries and variables associated with reproduction. Discussion Our final optimal models achieved relatively high performance values, and we discuss differences in performance with regard to sample size and variable treatments. Our results showed that, for both the establishment model and introduction model, the number of invaded countries was the most important or second most important determinant, respectively. Therefore, we suggest that future success for introduction and establishment of exotic birds may be gauged by simply looking at previous success in invading other countries. Finally, we found that species traits related to reproduction were more important in establishment models than in introduction models; importantly, these determinants were not averaged but either minimum or maximum values of species traits. Therefore, we suggest that in addition to averaged values, reproductive potential represented by minimum and maximum values of species traits should be considered in invasion studies. PMID:28316893

Predicting Success in Psychological Statistics Courses.

PubMed

Lester, David

2016-06-01

Many students perform poorly in courses on psychological statistics, and it is useful to be able to predict which students will have difficulties. In a study of 93 undergraduates enrolled in Statistical Methods (18 men, 75 women; M age = 22.0 years, SD = 5.1), performance was significantly associated with sex (female students performed better) and proficiency in algebra in a linear regression analysis. Anxiety about statistics was not associated with course performance, indicating that basic mathematical skills are the best correlate for performance in statistics courses and can usefully be used to stream students into classes by ability. © The Author(s) 2016.

A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals.

PubMed

Kim, Yoon Jae; Park, Sung Woo; Yeom, Hong Gi; Bang, Moon Suk; Kim, June Sic; Chung, Chun Kee; Kim, Sungwan

2015-08-20

A brain-machine interface (BMI) should be able to help people with disabilities by replacing their lost motor functions. To replace lost functions, robot arms have been developed that are controlled by invasive neural signals. Although invasive neural signals have a high spatial resolution, non-invasive neural signals are valuable because they provide an interface without surgery. Thus, various researchers have developed robot arms driven by non-invasive neural signals. However, robot arm control based on the imagined trajectory of a human hand can be more intuitive for patients. In this study, therefore, an integrated robot arm-gripper system (IRAGS) that is driven by three-dimensional (3D) hand trajectories predicted from non-invasive neural signals was developed and verified. The IRAGS was developed by integrating a six-degree of freedom robot arm and adaptive robot gripper. The system was used to perform reaching and grasping motions for verification. The non-invasive neural signals, magnetoencephalography (MEG) and electroencephalography (EEG), were obtained to control the system. The 3D trajectories were predicted by multiple linear regressions. A target sphere was placed at the terminal point of the real trajectories, and the system was commanded to grasp the target at the terminal point of the predicted trajectories. The average correlation coefficient between the predicted and real trajectories in the MEG case was [Formula: see text] ([Formula: see text]). In the EEG case, it was [Formula: see text] ([Formula: see text]). The success rates in grasping the target plastic sphere were 18.75 and 7.50 % with MEG and EEG, respectively. The success rates of touching the target were 52.50 and 58.75 % respectively. A robot arm driven by 3D trajectories predicted from non-invasive neural signals was implemented, and reaching and grasping motions were performed. In most cases, the robot closely approached the target, but the success rate was not very high because the non-invasive neural signal is less accurate. However the success rate could be sufficiently improved for practical applications by using additional sensors. Robot arm control based on hand trajectories predicted from EEG would allow for portability, and the performance with EEG was comparable to that with MEG.

[Effect of stock abundance and environmental factors on the recruitment success of small yellow croaker in the East China Sea].

PubMed

Liu, Zun-lei; Yuan, Xing-wei; Yang, Lin-lin; Yan, Li-ping; Zhang, Hui; Cheng, Jia-hua

2015-02-01

Multiple hypotheses are available to explain recruitment rate. Model selection methods can be used to identify the best model that supports a particular hypothesis. However, using a single model for estimating recruitment success is often inadequate for overexploited population because of high model uncertainty. In this study, stock-recruitment data of small yellow croaker in the East China Sea collected from fishery dependent and independent surveys between 1992 and 2012 were used to examine density-dependent effects on recruitment success. Model selection methods based on frequentist (AIC, maximum adjusted R2 and P-values) and Bayesian (Bayesian model averaging, BMA) methods were applied to identify the relationship between recruitment and environment conditions. Interannual variability of the East China Sea environment was indicated by sea surface temperature ( SST) , meridional wind stress (MWS), zonal wind stress (ZWS), sea surface pressure (SPP) and runoff of Changjiang River ( RCR). Mean absolute error, mean squared predictive error and continuous ranked probability score were calculated to evaluate the predictive performance of recruitment success. The results showed that models structures were not consistent based on three kinds of model selection methods, predictive variables of models were spawning abundance and MWS by AIC, spawning abundance by P-values, spawning abundance, MWS and RCR by maximum adjusted R2. The recruitment success decreased linearly with stock abundance (P < 0.01), suggesting overcompensation effect in the recruitment success might be due to cannibalism or food competition. Meridional wind intensity showed marginally significant and positive effects on the recruitment success (P = 0.06), while runoff of Changjiang River showed a marginally negative effect (P = 0.07). Based on mean absolute error and continuous ranked probability score, predictive error associated with models obtained from BMA was the smallest amongst different approaches, while that from models selected based on the P-value of the independent variables was the highest. However, mean squared predictive error from models selected based on the maximum adjusted R2 was highest. We found that BMA method could improve the prediction of recruitment success, derive more accurate prediction interval and quantitatively evaluate model uncertainty.

Performance of multiple docking and refinement methods in the pose prediction D3R prospective Grand Challenge 2016

NASA Astrophysics Data System (ADS)

Fradera, Xavier; Verras, Andreas; Hu, Yuan; Wang, Deping; Wang, Hongwu; Fells, James I.; Armacost, Kira A.; Crespo, Alejandro; Sherborne, Brad; Wang, Huijun; Peng, Zhengwei; Gao, Ying-Duo

2018-01-01

We describe the performance of multiple pose prediction methods for the D3R 2016 Grand Challenge. The pose prediction challenge includes 36 ligands, which represent 4 chemotypes and some miscellaneous structures against the FXR ligand binding domain. In this study we use a mix of fully automated methods as well as human-guided methods with considerations of both the challenge data and publicly available data. The methods include ensemble docking, colony entropy pose prediction, target selection by molecular similarity, molecular dynamics guided pose refinement, and pose selection by visual inspection. We evaluated the success of our predictions by method, chemotype, and relevance of publicly available data. For the overall data set, ensemble docking, visual inspection, and molecular dynamics guided pose prediction performed the best with overall mean RMSDs of 2.4, 2.2, and 2.2 Å respectively. For several individual challenge molecules, the best performing method is evaluated in light of that particular ligand. We also describe the protein, ligand, and public information data preparations that are typical of our binding mode prediction workflow.

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

PubMed

Jing, Xiaoyang; Dong, Qiwen

2017-05-25

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

Predicting College Students' First Year Success: Should Soft Skills Be Taken into Consideration to More Accurately Predict the Academic Achievement of College Freshmen?

ERIC Educational Resources Information Center

Powell, Erica Dion

2013-01-01

This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…

Student Pilot Aptitude as an Indicator of Success in a Part 141 Collegiate Flight Training Program

ERIC Educational Resources Information Center

McFarland, Maureen R.

2017-01-01

Predicting flight training success has been well researched in military aviation yet there is limited information pertaining to general aviation. The purpose of this study was to determine if attributes of pilot performance could be used to differentiate students in a collegiate flight training program. Several pre-entry and flight training…

Predicting Academic Success and Psychological Wellness in a Sample of Canadian Undergraduate Students

ERIC Educational Resources Information Center

Chow, Henry P. H.

2010-01-01

Introduction: University students need to cope with a complex new life role and to achieve academic success. This article explores the academic performance and psychological well-being among university students in a western Canadian city. Method: Using a convenience sample, a total of 501 undergraduate students in Regina, Saskatchewan took part in…

The Validity of Interpersonal Skills Assessment via Situational Judgment Tests for Predicting Academic Success and Job Performance

ERIC Educational Resources Information Center

Lievens, Filip; Sackett, Paul R.

2012-01-01

This study provides conceptual and empirical arguments why an assessment of applicants' procedural knowledge about interpersonal behavior via a video-based situational judgment test might be valid for academic and postacademic success criteria. Four cohorts of medical students (N = 723) were followed from admission to employment. Procedural…

Predicting Community College Student Success by Participation in a First-Year Experience Course

ERIC Educational Resources Information Center

Gardner, Andy Franklin

2013-01-01

A first-year experience is a collaborative effort of many initiatives, with varying names that have the greatest impact on student success during the first year of college. A first-year experience course, a feature of the first-year experience, is an intervention program designed to increase student academic performance and integration (Braxton…

Motivational Correlates of Academic Success in an Educational Psychology Course

ERIC Educational Resources Information Center

Herman, William E.

2011-01-01

The variables of class attendance and the institution-wide Early Alert Grading System were employed to predict academic success at the end of the semester. Classroom attendance was found to be statistically and significantly related to final average and accounted for 14-16% of the variance in academic performance. Class attendance was found to…

The influence of speed abilities and technical skills in early adolescence on adult success in soccer: A long-term prospective analysis using ANOVA and SEM approaches

PubMed Central

2017-01-01

Several talent development programs in youth soccer have implemented motor diagnostics measuring performance factors. However, the predictive value of such tests for adult success is a controversial topic in talent research. This prospective cohort study evaluated the long-term predictive value of 1) motor tests and 2) players’ speed abilities (SA) and technical skills (TS) in early adolescence. The sample consisted of 14,178 U12 players from the German talent development program. Five tests (sprint, agility, dribbling, ball control, shooting) were conducted and players’ height, weight as well as relative age were assessed at nationwide diagnostics between 2004 and 2006. In the 2014/15 season, the players were then categorized as professional (n = 89), semi-professional (n = 913), or non-professional players (n = 13,176), indicating their adult performance level (APL). The motor tests’ prognostic relevance was determined using ANOVAs. Players’ future success was predicted by a logistic regression threshold model. This structural equation model comprised a measurement model with the motor tests and two correlated latent factors, SA and TS, with simultaneous consideration for the manifest covariates height, weight and relative age. Each motor predictor and anthropometric characteristic discriminated significantly between the APL (p < .001; η2 ≤ .02). The threshold model significantly predicted the APL (R2 = 24.8%), and in early adolescence the factor TS (p < .001) seems to have a stronger effect on adult performance than SA (p < .05). Both approaches (ANOVA, SEM) verified the diagnostics’ predictive validity over a long-term period (≈ 9 years). However, because of the limited effect sizes, the motor tests’ prognostic relevance remains ambiguous. A challenge for future research lies in the integration of different (e.g., person-oriented or multilevel) multivariate approaches that expand beyond the “traditional” topic of single tests’ predictive validity and toward more theoretically founded issues. PMID:28806410

Thirty years on: examination performance and career success of the 1950-1 intake of Cambridge medical students.

PubMed

Wakeford, R; Roberts, S

1983-06-04

The relation between preclinical tripos and clinical examination results and subsequent career success of 188 medical graduates of Cambridge University was measured using five indicators of success. A generally positive relation was found, but this was not specific enough to make accurate individual predictions. Present levels of appointment were more closely related to clinical than preclinical results. No support was found for the local assertion that "2.1s" do better than "firsts" in clinical medicine. Since undergraduate examination results seem to be inaccurate predictors of later performance they should not be used as the principal evidence in making selection decisions.

Two signs indicative of successful access in nuclear medicine cerebrospinal fluid diversionary shunt studies.

PubMed

Bermo, Mohammed S; Khalatbari, Hedieh; Parisi, Marguerite T

2018-05-08

Successful shunt access is the first step in a properly performed nuclear medicine cerebrospinal fluid (CSF) shunt study. To determine the significance of the radiotracer configuration at the injection site during initial nuclear medicine CSF shunt imaging and the lack of early systemic radiotracer activity as predictors of successful shunt access. With Institutional Review Board approval, three nuclear medicine physicians performed a retrospective review of all consecutive CSF shunt studies performed in children at our institution in 2015. Antecedent nuclear medicine CSF shunt studies in these patients were also assessed and included in the review. The appearance of the reservoir site immediately after radiotracer injection was classified as either figure-of-eight or round/ovoid configuration. The presence or absence of early systemic distribution of the tracer on the 5-min static images was noted and separately evaluated. A total of 98 nuclear medicine ventriculoperitoneal CSF shunt studies were evaluated. Figure-of-eight configuration was identified in 87% of studies and, when present, had 93% sensitivity, 78% specificity, 92% accuracy, 98% positive predictive value (PPV) and 54% negative predictive value (NPV) as a predictor of successful shunt access. Early systemic activity was absent in 89 of 98 studies. Lack of early systemic distribution of the radiotracer had 98% sensitivity, 78% specificity, 96% accuracy, 98% PPV and 78% NPV as a predictor of successful shunt access. Figure-of-eight configuration in conjunction with the absence of early systemic tracer activity had 99% PPV for successful shunt access. Figure-of-eight configuration at the injection site or lack of early systemic radiotracer activity had moderate specificity for successful shunt access. Specificity and PPV significantly improved when both signs were combined in assessment.

Psychological factors determining success in a medical career: a 10-year longitudinal study.

PubMed

Tartas, Malgorzata; Walkiewicz, Maciej; Majkowicz, Mikolaj; Budzinski, Waldemar

2011-01-01

Systemic review of predictors of success in medical career is an important tool to recognize the indicators of proper training. To determine psychological factors that predict success in a medical career. The success is defined as professional competence, satisfaction with medicine as a career, occupational stress and burnout and quality of life (QOF). Part I (1999-2005), medical students were examined each subsequent year, beginning with admission. Assessment included academic achievement (high school final examination results, entrance exam results, academic results during medical school) and psychological characteristics (sense of coherence (SOC), depression, anxiety, coping styles, value system and need for social approval). Part II (2008-2009), the same participants completed an Internet survey 4 years after graduation. Results of the postgraduate medical exam were taken under consideration. Academic achievement predicts only professional competence. Coping styles are significant indicators of satisfaction with medicine as a career. SOC, while assessed with anxiety and depression during studies, enabled us to recognize future QOF of medical graduates. Professional stress is not predictable to such an extent as other success indicators. There are significant psychological qualities useful to draw the outline of the future job and life performance of medical graduates.

Mars Pathfinder Atmospheric Entry Navigation Operations

NASA Technical Reports Server (NTRS)

Braun, R. D.; Spencer, D. A.; Kallemeyn, P. H.; Vaughan, R. M.

1997-01-01

On July 4, 1997, after traveling close to 500 million km, the Pathfinder spacecraft successfully completed entry, descent, and landing, coming to rest on the surface of Mars just 27 km from its target point. In the present paper, the atmospheric entry and approach navigation activities required in support of this mission are discussed. In particular, the flight software parameter update and landing site prediction analyses performed by the Pathfinder operations navigation team are described. A suite of simulation tools developed during Pathfinder's design cycle, but extendible to Pathfinder operations, are also presented. Data regarding the accuracy of the primary parachute deployment algorithm is extracted from the Pathfinder flight data, demonstrating that this algorithm performed as predicted. The increased probability of mission success through the software parameter update process is discussed. This paper also demonstrates the importance of modeling atmospheric flight uncertainties in the estimation of an accurate landing site. With these atmospheric effects included, the final landed ellipse prediction differs from the post-flight determined landing site by less then 0.5 km in downtrack.

Digital filtering and model updating methods for improving the robustness of near-infrared multivariate calibrations.

PubMed

Kramer, Kirsten E; Small, Gary W

2009-02-01

Fourier transform near-infrared (NIR) transmission spectra are used for quantitative analysis of glucose for 17 sets of prediction data sampled as much as six months outside the timeframe of the corresponding calibration data. Aqueous samples containing physiological levels of glucose in a matrix of bovine serum albumin and triacetin are used to simulate clinical samples such as blood plasma. Background spectra of a single analyte-free matrix sample acquired during the instrumental warm-up period on the prediction day are used for calibration updating and for determining the optimal frequency response of a preprocessing infinite impulse response time-domain digital filter. By tuning the filter and the calibration model to the specific instrumental response associated with the prediction day, the calibration model is given enhanced ability to operate over time. This methodology is demonstrated in conjunction with partial least squares calibration models built with a spectral range of 4700-4300 cm(-1). By using a subset of the background spectra to evaluate the prediction performance of the updated model, projections can be made regarding the success of subsequent glucose predictions. If a threshold standard error of prediction (SEP) of 1.5 mM is used to establish successful model performance with the glucose samples, the corresponding threshold for the SEP of the background spectra is found to be 1.3 mM. For calibration updating in conjunction with digital filtering, SEP values of all 17 prediction sets collected over 3-178 days displaced from the calibration data are below 1.5 mM. In addition, the diagnostic based on the background spectra correctly assesses the prediction performance in 16 of the 17 cases.

Joining the Conversation: Predictors of Success on the United States Medical Licensing Examinations (USMLE)

ERIC Educational Resources Information Center

Gohara, Sabry; Shapiro, Joseph I.; Jacob, Adam N.; Khuder, Sadik A.; Gandy, Robyn A.; Metting, Patricia J.; Gold, Jeffrey; Kleshinski, James; and James Kleshinski

2011-01-01

The purpose of this study was to evaluate whether models based on pre-admission testing, including performance on the Medical College Admission Test (MCAT), performance on required courses in the medical school curriculum, or a combination of both could accurately predict performance of medical students on the United States Medical Licensing…

Academic Performance and Learning Style Self-Predictions by Second Language Students in an Introductory Biology Course

ERIC Educational Resources Information Center

Breckler, Jennifer; Teoh, Chia Shan; Role, Kemi

2011-01-01

Academic success in first-year college science coursework can strongly influence future career paths and usually includes a solid performance in introductory biology. We wanted to know whether factors affecting biology student performance might include learning style preferences and one's ability and confidence in self-assessing those learning…

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Strategies for maximizing your chances for weaning success. Limitations--and advantages--of common predictive indices.

PubMed

Patel, R G; Petrini, M F; Norman, J R

1995-06-01

Using indices to predict weaning outcome can avoid premature extubation and unnecessary prolongation of ventilatory support. Unfortunately, none of the indices is consistently able to predict outcome. The key to successful weaning is to assess respiratory function repeatedly with several indices, not just one. The patient should be able to sustain spontaneous breathing for at least 24 hours on minimal partial ventilatory support (a pressure support or a continuous positive airway pressure of 5 cm H2O or a T piece, for example). Indices of maximal inspiratory pressure; work of breathing; and rapid, shallow breathing are useful in evaluating a patient's respiratory muscle performance; airway occlusion pressure is helpful as well when increased neuromuscular drive is a problem.

Do instability markers predict satisfactory reduction and requirement for later surgery in emergency department patients with wrist fracture?

PubMed

Winayak, Amar; Gossat, Alyza; Cooper, Jenny; Ritchie, Peter; Lim, Wei; Klim, Sharon; Kelly, Anne-Maree

2018-02-01

Research suggests that the presence of instability markers in patients with displaced distal radial fractures is associated with poorer outcome. Our aims were to determine whether the presence of previously defined instability markers could predict the likelihood of successful ED reduction and requirement for a secondary procedure after ED reduction. Retrospective cohort study performed by medical record review. Adult ED patients coded as having an isolated wrist fracture and having fracture reduction in ED were eligible for inclusion. Data collected included demographics, history of osteoporosis, mechanism of injury, radiological features on X-rays and performance of a secondary procedure. Outcomes of interest were the rate of successful fracture reduction in ED (against defined radiological criteria), the rate of secondary procedures and the association between the number of defined instability risk factors and successful reduction and performance of a secondary surgical procedure. Analysis was by χ 2 test, receiver operating characteristic curve, logistic regression analyses. Three hundred and nineteen patients were studied; median age 62 years, 77% female. Sixty-five per cent of patients had satisfactory fracture reduction in ED (95% CI 59%-70%). Eighty-six patients underwent a secondary procedure to reduce/stabilise their fracture (28%, 95% CI 23%-33%). Younger age, lack of satisfactory ED reduction and increased number of instability factors were independently predictive of the performance of a secondary procedure. Instability risk factors are common in patients with wrist fractures requiring reduction in ED. The number of instability factors is not a strong predictor of the performance of secondary procedures. © 2017 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Senescence rates and late adulthood reproductive success are strongly influenced by personality in a long-lived seabird

PubMed Central

Patrick, Samantha C.; Weimerskirch, Henri

2015-01-01

Studies are increasingly demonstrating that individuals differ in their rate of ageing, and this is postulated to emerge from a trade-off between current and future reproduction. Recent theory predicts a correlation between individual personality and life-history strategy, and from this comes the prediction that personality may predict the intensity of senescence. Here we show that boldness correlates with reproductive success and foraging behaviour in wandering albatrosses, with strong sex-specific differences. Shy males show a strong decline in reproductive performance with age, and bold females have lower reproductive success in later adulthood. In both sexes, bolder birds have longer foraging trips and gain more mass per trip as they get older. However, the benefit of this behaviour appears to differ between the sexes, such that it is only matched by high reproductive success in males. Together our results suggest that personality linked foraging adaptations with age are strongly sex-specific in their fitness benefits and that the impact of boldness on senescence is linked to ecological parameters. PMID:25473008

The Eighth Grade CRCT as a Predictive Measure of Student Success on the Ninth Grade EOCT

ERIC Educational Resources Information Center

Body, Matthew

2013-01-01

Student performance on high stakes testing in secondary education has contributed to the need for students' testing potential to be identified before entering high school. There is evidence to suggest that a greater understanding of how earlier test scores predict later test scores will help educators and school officials increase student…

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

ERIC Educational Resources Information Center

Wintling, Cheral Ann

2012-01-01

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

Performance prediction: A case study using a multi-ring KSR-1 machine

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Zhu, Jianping

1995-01-01

While computers with tens of thousands of processors have successfully delivered high performance power for solving some of the so-called 'grand-challenge' applications, the notion of scalability is becoming an important metric in the evaluation of parallel machine architectures and algorithms. In this study, the prediction of scalability and its application are carefully investigated. A simple formula is presented to show the relation between scalability, single processor computing power, and degradation of parallelism. A case study is conducted on a multi-ring KSR1 shared virtual memory machine. Experimental and theoretical results show that the influence of topology variation of an architecture is predictable. Therefore, the performance of an algorithm on a sophisticated, heirarchical architecture can be predicted and the best algorithm-machine combination can be selected for a given application.

Does the choice of definition for defibrillation and CPR success impact the predictability of ventricular fibrillation waveform analysis?

PubMed

Jin, Danian; Dai, Chenxi; Gong, Yushun; Lu, Yubao; Zhang, Lei; Quan, Weilun; Li, Yongqin

2017-02-01

Quantitative analysis of ventricular fibrillation (VF), such as amplitude spectral area (AMSA), predicts shock outcomes. However, there is no uniform definition of shock/cardiopulmonary resuscitation (CPR) success in out-of-hospital cardiac arrest (OHCA). The objective of this study is to investigate post-shock rhythm variations and the impact of shock/CPR success definition on the predictability of AMSA. A total of 554 shocks from 257 OHCA patients with VF as initial rhythm were analyzed. Post-shock rhythms were analyzed every 5s up to 120s and annotated as VF, asystole (AS) and organized rhythm (OR) at serial time intervals. Three shock/CPR success definitions were used to evaluate the predictability of AMSA: (1) termination of VF (ToVF); (2) return of organized electrical activity (ROEA); (3) return of potentially perfusing rhythm (RPPR). Rhythm changes occurred after 54.5% (N=302) of shocks and 85.8% (N=259) of them occurred within 60s after shock delivery. The observed post-shock rhythm changes were (1) from AS to VF (24.9%), (2) from OR to VF (16.1%), and (3) from AS to OR (12.1%). The area under the receiver operating characteristic curve (AUC) for AMSA as a predictor of shock/CPR success reached its maximum 60s post-shock. The AUC was 0.646 for ToVF, 0.782 for ROEA, and 0.835 for RPPR (p<0.001) respectively. Post-shock rhythm is unstable in the first minute after the shock. The predictability of AMSA varies depending on the definition of shock/CPR success and performs best with the return of potentially perfusing rhythm endpoint for OHCA. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection.

PubMed

Ma, Xin; Guo, Jing; Sun, Xiao

2015-01-01

The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed by incremental feature selection (IFS). We incorporated features of conjoint triad features and three novel features: binding propensity (BP), nonbinding propensity (NBP), and evolutionary information combined with physicochemical properties (EIPP). The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient). High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

Analysis of Free Modeling Predictions by RBO Aleph in CASP11

PubMed Central

Mabrouk, Mahmoud; Werner, Tim; Schneider, Michael; Putz, Ines; Brock, Oliver

2015-01-01

The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue–residue contact prediction by EPC-map and contact–guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. PMID:26492194

Longitudinal motor performance development in early adolescence and its relationship to adult success: An 8-year prospective study of highly talented soccer players

PubMed Central

Kelava, Augustin; Raabe, Johannes; Höner, Oliver

2018-01-01

Several talent identification and development (TID) programs in soccer have implemented diagnostics to measure players’ motor performance. Yet, there is a lack of research investigating the relationship between motor development in adolescence and future, adult performance. This longitudinal study analyzed the three-year development of highly talented young soccer players’ speed abilities and technical skills and examined the relevance of this development to their adult success. The current research sample consisted of N = 1,134 players born between 1993 and 1995 who were selected for the German Soccer Association’s TID program and participated in nationwide motor diagnostics (sprinting, agility, dribbling, ball control, shooting) four times between the Under 12 (U12) and Under 15 (U15) age class. Relative age (RA) was assessed for all players, and a total motor score was calculated based on performances in the individual tests. In order to investigate players’ future success, participants were divided into two groups according to their adult performance level (APL) in the 2014/2015 season: Elite (1st-5th German division; N = 145, 12.8%) and non-elite players (lower divisions; N = 989, 87.2%). Using multilevel regression analyses each motor performance was predicted by Time, Time2 (level-1 predictors), APL, and RA (level-2 covariates) with simultaneous consideration for interaction effects between the respective variables. Time and Time2 were significant predictors for each test performance. A predictive value for RA was confirmed for sprinting and the total motor score. A significant relationship between APL and the motor score as well as between APL and agility, dribbling, ball control, and shooting emerged. Interaction effects distinctly failed to reach significance. The study found a non-linear improvement in players’ performance for all considered motor performance factors over a three-year period from early to middle adolescence. While their predictive value for future success was confirmed by a significant relationship between APL and most of the considered factors, there was no significant interaction between APL and Time. These findings indicate that future elite players had already been better at the beginning of the TID program and maintained this high level throughout their promotion from U12 to U15. PMID:29723200

Longitudinal motor performance development in early adolescence and its relationship to adult success: An 8-year prospective study of highly talented soccer players.

PubMed

Leyhr, Daniel; Kelava, Augustin; Raabe, Johannes; Höner, Oliver

2018-01-01

Several talent identification and development (TID) programs in soccer have implemented diagnostics to measure players' motor performance. Yet, there is a lack of research investigating the relationship between motor development in adolescence and future, adult performance. This longitudinal study analyzed the three-year development of highly talented young soccer players' speed abilities and technical skills and examined the relevance of this development to their adult success. The current research sample consisted of N = 1,134 players born between 1993 and 1995 who were selected for the German Soccer Association's TID program and participated in nationwide motor diagnostics (sprinting, agility, dribbling, ball control, shooting) four times between the Under 12 (U12) and Under 15 (U15) age class. Relative age (RA) was assessed for all players, and a total motor score was calculated based on performances in the individual tests. In order to investigate players' future success, participants were divided into two groups according to their adult performance level (APL) in the 2014/2015 season: Elite (1st-5th German division; N = 145, 12.8%) and non-elite players (lower divisions; N = 989, 87.2%). Using multilevel regression analyses each motor performance was predicted by Time, Time2 (level-1 predictors), APL, and RA (level-2 covariates) with simultaneous consideration for interaction effects between the respective variables. Time and Time2 were significant predictors for each test performance. A predictive value for RA was confirmed for sprinting and the total motor score. A significant relationship between APL and the motor score as well as between APL and agility, dribbling, ball control, and shooting emerged. Interaction effects distinctly failed to reach significance. The study found a non-linear improvement in players' performance for all considered motor performance factors over a three-year period from early to middle adolescence. While their predictive value for future success was confirmed by a significant relationship between APL and most of the considered factors, there was no significant interaction between APL and Time. These findings indicate that future elite players had already been better at the beginning of the TID program and maintained this high level throughout their promotion from U12 to U15.

Factors Associated With Success in an Occupational Rehabilitation Program for Work-Related Musculoskeletal Disorders

PubMed Central

Hardison, Mark E.

2017-01-01

Work-related musculoskeletal disorders are a significant burden; however, no consensus has been reached on how to maximize occupational rehabilitation programs for people with these disorders, and the impact of simulating work tasks as a mode of intervention has not been well examined. In this retrospective cohort study, the authors used logistic regression to identify client and program factors predicting success for 95 clients in a general occupational rehabilitation program and 71 clients in a comprehensive occupational rehabilitation program. The final predictive model for general rehabilitation included gender, number of sessions completed, and performance of work simulation activities. Maximum hours per session was the only significant predictor of success in the comprehensive rehabilitation program. This study identifies new factors associated with success in occupational rehabilitation, specifically highlighting the importance of intensity (i.e., session length and number of sessions) of therapy and occupation-based activities for this population. PMID:28027046

Does taking endurance into account improve the prediction of weaning outcome in mechanically ventilated children?

PubMed Central

Noizet, Odile; Leclerc, Francis; Sadik, Ahmed; Grandbastien, Bruno; Riou, Yvon; Dorkenoo, Aimée; Fourier, Catherine; Cremer, Robin; Leteurtre, Stephane

2005-01-01

Introduction We conducted the present study to determine whether a combination of the mechanical ventilation weaning predictors proposed by the collective Task Force of the American College of Chest Physicians (TF) and weaning endurance indices enhance prediction of weaning success. Method Conducted in a tertiary paediatric intensive care unit at a university hospital, this prospective study included 54 children receiving mechanical ventilation (≥6 hours) who underwent 57 episodes of weaning. We calculated the indices proposed by the TF (spontaneous respiratory rate, paediatric rapid shallow breathing, rapid shallow breathing occlusion pressure [ROP] and maximal inspiratory pressure during an occlusion test [Pimax]) and weaning endurance indices (pressure-time index, tension-time index obtained from P0.1 [TTI1] and from airway pressure [TTI2]) during spontaneous breathing. Performances of each TF index and combinations of them were calculated, and the best single index and combination were identified. Weaning endurance parameters (TTI1 and TTI2) were calculated and the best index was determined using a logistic regression model. Regression coefficients were estimated using the maximum likelihood ratio (LR) method. Hosmer–Lemeshow test was used to estimate goodness-of-fit of the model. An equation was constructed to predict weaning success. Finally, we calculated the performances of combinations of best TF indices and best endurance index. Results The best single TF index was ROP, the best TF combination was represented by the expression (0.66 × ROP) + (0.34 × Pimax), and the best endurance index was the TTI2, although their performance was poor. The best model resulting from the combination of these indices was defined by the following expression: (0.6 × ROP) – (0.1 × Pimax) + (0.5 × TTI2). This integrated index was a good weaning predictor (P < 0.01), with a LR+ of 6.4 and LR+/LR- ratio of 12.5. However, at a threshold value <1.3 it was only predictive of weaning success (LR- = 0.5). Conclusion The proposed combined index, incorporating endurance, was of modest value in predicting weaning outcome. This is the first report of the value of endurance parameters in predicting weaning success in children. Currently, clinical judgement associated with spontaneous breathing trials apparently remain superior. PMID:16356229

Relationship between college success and employer competency ratings for graduates of a baccalaureate nursing program.

PubMed

Bolin, S E; Hogle, E L

1984-01-01

This expost facto correlational study sought to determine which measures of academic success in one class of BSN graduates predicted their competence as employees one year after graduation, as judged by their employers. The relationship between pre-entrance test scores, clinical experience grades, GPA, State Board Test Pool examination scores, and employer competency ratings were also determined. In keeping with the literature in fields other than nursing, the findings suggest that there may be little relationship between academic performance in a nursing program and subsequent job performance as a nurse, even though verbal ability may be predictive of success in school. While significant positive correlations were found between pre-entrance test data and final grade point averages, as well as pre-entrance test scores and State Board Test Pool examination scores, there was little evidence that pre-entrance test scores were predictive of nursing abilities. Isolated correlations were found between the clinical components of some nursing courses and specific nursing abilities. Using multiple regression analysis, no clinical course grade was found to be a significant predictor of the mean employer competency rating. Significant predictors were found for only four of the individual nursing abilities, with the clinical component of Leadership in Nursing being the most frequent and best predictor.

Baseline Gray- and White Matter Volume Predict Successful Weight Loss in the Elderly

PubMed Central

Mokhtari, Fatemeh; Paolini, Brielle M.; Burdette, Jonathan H.; Marsh, Anthony P.; Rejeski, W. Jack; Laurienti, Paul J.

2016-01-01

Objective The purpose of this study is to investigate if structural brain phenotypes can be used to predict weight loss success following behavioral interventions in older adults that are overweight or obese and have cardiometabolic dysfunction. Methods A support vector machine (SVM) with a repeated random subsampling validation approach was used to classify participants into the upper and lower halves of the weight loss distribution following 18 months of a weight loss intervention. Predictions were based on baseline brain gray matter (GM) and white matter (WM) volume from 52 individuals that completed the intervention and a magnetic resonance imaging session. Results The SVM resulted in an average classification accuracy of 72.62 % based on GM and WM volume. A receiver operating characteristic analysis indicated that classification performance was robust based on an area under the curve of 0.82. Conclusions Our findings suggest that baseline brain structure is able to predict weight loss success following 18 months of treatment. The identification of brain structure as a predictor of successful weight loss is an innovative approach to identifying phenotypes for responsiveness to intensive lifestyle interventions. This phenotype could prove useful in future research focusing on the tailoring of treatment for weight loss. PMID:27804273

Prediction of Success in External Cephalic Version under Tocolysis: Still a Challenge.

PubMed

Vaz de Macedo, Carolina; Clode, Nuno; Mendes da Graça, Luís

2015-01-01

External cephalic version is a procedure of fetal rotation to a cephalic presentation through manoeuvres applied to the maternal abdomen. There are several prognostic factors described in literature for external cephalic version success and prediction scores have been proposed, but their true implication in clinical practice is controversial. We aim to identify possible factors that could contribute to the success of an external cephalic version attempt in our population. We retrospectively examined 207 consecutive external cephalic version attempts under tocolysis conducted between January 1997 and July 2012. We consulted the department's database for the following variables: race, age, parity, maternal body mass index, gestational age, estimated fetal weight, breech category, placental location and amniotic fluid index. We performed descriptive and analytical statistics for each variable and binary logistic regression. External cephalic version was successful in 46.9% of cases (97/207). None of the included variables was associated with the outcome of external cephalic version attempts after adjustment for confounding factors. We present a success rate similar to what has been previously described in literature. However, in contrast to previous authors, we could not associate any of the analysed variables with success of the external cephalic version attempt. We believe this discrepancy is partly related to the type of statistical analysis performed. Even though there are numerous prognostic factors identified for the success in external cephalic version, care must be taken when counselling and selecting patients for this procedure. The data obtained suggests that external cephalic version should continue being offered to all eligible patients regardless of prognostic factors for success.

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

NASA Astrophysics Data System (ADS)

Maljaars, E.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J. M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A. A.; Vu, N. M. T.; The EUROfusion MST1-team; The TCV-team

2017-12-01

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols.

PubMed

Bohari, Mohammed H; Sastry, G Narahari

2012-09-01

Efficient drug discovery programs can be designed by utilizing existing pools of knowledge from the already approved drugs. This can be achieved in one way by repositioning of drugs approved for some indications to newer indications. Complex of drug to its target gives fundamental insight into molecular recognition and a clear understanding of putative binding site. Five popular docking protocols, Glide, Gold, FlexX, Cdocker and LigandFit have been evaluated on a dataset of 199 FDA approved drug-target complexes for their accuracy in predicting the experimental pose. Performance for all the protocols is assessed at default settings, with root mean square deviation (RMSD) between the experimental ligand pose and the docked pose of less than 2.0 Å as the success criteria in predicting the pose. Glide (38.7 %) is found to be the most accurate in top ranked pose and Cdocker (58.8 %) in top RMSD pose. Ligand flexibility is a major bottleneck in failure of docking protocols to correctly predict the pose. Resolution of the crystal structure shows an inverse relationship with the performance of docking protocol. All the protocols perform optimally when a balanced type of hydrophilic and hydrophobic interaction or dominant hydrophilic interaction exists. Overall in 16 different target classes, hydrophobic interactions dominate in the binding site and maximum success is achieved for all the docking protocols in nuclear hormone receptor class while performance for the rest of the classes varied based on individual protocol.

Evaluation of cough peak expiratory flow as a predictor of successful mechanical ventilation discontinuation: a narrative review of the literature.

PubMed

Jiang, Chuan; Esquinas, Antonio; Mina, Bushra

2017-01-01

A crucial step in the transition from mechanical ventilation to extubation is the successful performance of a spontaneous breathing trial (SBT). The American College of Chest Physicians (ACCP) Guidelines recommend removal of the endotracheal tube upon successful completion of a SBT. However, this does not guarantee successful extubation as there remains a risk of re-intubation. Guidelines have outlined ventilator liberation protocols, selected use of non-invasive ventilation on extubation, early mobilization, and dynamic ventilator metrics to prevent and better predict extubation failure. However, a significant percentage of patients still fail mechanical ventilation discontinuation. A common reason for re-intubation is having a weak cough strength, which reflects the inability to protect the airway. Evaluation of cough strength via objective measures using peak expiratory flow rate is a non-invasive and easily reproducible assessment which can predict extubation failure. We conducted a narrative review of the literature regarding use of cough strength as a predictive index for extubation failure risk. Results of our review show that cough strength, quantified objectively with a cough peak expiratory flow measurement (CPEF), is strongly associated with extubation success. Furthermore, various cutoff thresholds have been identified and can provide reasonable diagnostic accuracy and predictive power for extubation failure. These results demonstrate that measurement of the CPEF can be a useful tool to predict extubation failure in patients on MV who have passed a SBT. In addition, the data suggest that this diagnostic modality may reduce ICU length of stay, ICU expenditures, and morbidity and mortality.

Predictors of operating room extubation in adult cardiac surgery.

PubMed

Subramaniam, Kathirvel; DeAndrade, Diana S; Mandell, Daniel R; Althouse, Andrew D; Manmohan, Rajan; Esper, Stephen A; Varga, Jeffrey M; Badhwar, Vinay

2017-11-01

The primary objective of the study was to identify perioperative factors associated with successful immediate extubation in the operating room after adult cardiac surgery. The secondary objective was to derive a simplified predictive scoring system to guide clinicians in operating room extubation. All 1518 patients in this retrospective cohort study underwent standardized fast-track cardiac anesthetic protocol during adult cardiac surgery. Perioperative variables between patients who had successful extubation in the operating room versus in the intensive care unit were retrospectively analyzed using both univariate and multivariable logistic regression analyses. A predictive score of successful operating room extubation was constructed from the multivariable results of 800 patients (derivation set), and the scoring system was further tested using a validation set of 398 patients. Younger age, lower body mass index, higher preoperative serum albumin, absence of chronic lung disease and diabetes, less-invasive surgical approach, isolated coronary bypass surgery, elective surgery, and lower doses of intraoperative intravenous fentanyl were independently associated with higher probability of operating room extubation. The extubation prediction score created in a derivation set of patients performed well in the validation set. Patient scores less than 0 had a minimal probability of successful operating room extubation. Operating room extubation was highly predicted with scores of 5 or greater. Perioperative factors that are independently associated with successful operating room extubation after adult cardiac operations were identified, and an operating room extubation prediction scoring system was validated. This scoring system may be used to guide safe operating room extubation after cardiac operations. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Thirty years on: examination performance and career success of the 1950-1 intake of Cambridge medical students.

PubMed Central

Wakeford, R; Roberts, S

1983-01-01

The relation between preclinical tripos and clinical examination results and subsequent career success of 188 medical graduates of Cambridge University was measured using five indicators of success. A generally positive relation was found, but this was not specific enough to make accurate individual predictions. Present levels of appointment were more closely related to clinical than preclinical results. No support was found for the local assertion that "2.1s" do better than "firsts" in clinical medicine. Since undergraduate examination results seem to be inaccurate predictors of later performance they should not be used as the principal evidence in making selection decisions. PMID:6407573

Clinical models are inaccurate in predicting bile duct stones in situ for patients with gallbladder.

PubMed

Topal, B; Fieuws, S; Tomczyk, K; Aerts, R; Van Steenbergen, W; Verslype, C; Penninckx, F

2009-01-01

The probability that a patient has common bile duct stones (CBDS) is a key factor in determining diagnostic and treatment strategies. This prospective cohort study evaluated the accuracy of clinical models in predicting CBDS for patients who will undergo cholecystectomy for lithiasis. From October 2005 until September 2006, 335 consecutive patients with symptoms of gallstone disease underwent cholecystectomy. Statistical analysis was performed on prospective patient data obtained at the time of first presentation to the hospital. Demonstrable CBDS at the time of endoscopic retrograde cholangiopancreatography (ERCP) or intraoperative cholangiography (IOC) was considered the gold standard for the presence of CBDS. Common bile duct stones were demonstrated in 53 patients. For 35 patients, ERCP was performed, with successful stone clearance in 24 of 30 patients who had proven CBDS. In 29 patients, IOC showed CBDS, which were managed successfully via laparoscopic common bile duct exploration, with stone extraction at the time of cholecystectomy. Prospective validation of the existing model for CBDS resulted in a predictive accuracy rate of 73%. The new model showed a predictive accuracy rate of 79%. Clinical models are inaccurate in predicting CBDS in patients with cholelithiasis. Management strategies should be based on the local availability of therapeutic expertise.

Cochlea-scaled spectral entropy predicts rate-invariant intelligibility of temporally distorted sentences.

PubMed

Stilp, Christian E; Kiefte, Michael; Alexander, Joshua M; Kluender, Keith R

2010-10-01

Some evidence, mostly drawn from experiments using only a single moderate rate of speech, suggests that low-frequency amplitude modulations may be particularly important for intelligibility. Here, two experiments investigated intelligibility of temporally distorted sentences across a wide range of simulated speaking rates, and two metrics were used to predict results. Sentence intelligibility was assessed when successive segments of fixed duration were temporally reversed (exp. 1), and when sentences were processed through four third-octave-band filters, the outputs of which were desynchronized (exp. 2). For both experiments, intelligibility decreased with increasing distortion. However, in exp. 2, intelligibility recovered modestly with longer desynchronization. Across conditions, performances measured as a function of proportion of utterance distorted converged to a common function. Estimates of intelligibility derived from modulation transfer functions predict a substantial proportion of the variance in listeners' responses in exp. 1, but fail to predict performance in exp. 2. By contrast, a metric of potential information, quantified as relative dissimilarity (change) between successive cochlear-scaled spectra, is introduced. This metric reliably predicts listeners' intelligibility across the full range of speaking rates in both experiments. Results support an information-theoretic approach to speech perception and the significance of spectral change rather than physical units of time.

Factors Predicting Academic Success in Second and Third Language among Russian-Speaking Immigrant Students Studying in Israeli Schools

ERIC Educational Resources Information Center

Haim, Orly

2014-01-01

The purpose of this study was to investigate the factors predicting academic proficiency (AP), the specialised domains required for performing academic tasks, among Russian speaking (L1) immigrants currently studying Hebrew as a second language (L2) and English as a third language (L3) in Israeli schools. Specifically, the study examined the…

Hardiness commitment, gender, and age differentiate university academic performance.

PubMed

Sheard, Michael

2009-03-01

The increasing diversity of students, particularly in age, attending university has seen a concomitant interest in factors predicting academic success. This 2-year correlational study examined whether age, gender (demographic variables), and hardiness (cognitive/emotional variable) differentiate and predict university final degree grade point average (GPA) and final-year dissertation mark. Data are reported from a total of 134 university undergraduate students. Participants provided baseline data in questionnaires administered during the first week of their second year of undergraduate study and gave consent for their academic progress to be tracked. Final degree GPA and dissertation mark were the academic performance criteria. Mature-age students achieved higher final degree GPA compared to young undergraduates. Female students significantly outperformed their male counterparts in each measured academic assessment criteria. Female students also reported a significantly higher mean score on hardiness commitment compared to male students. commitment was the most significant positive correlate of academic achievement. Final degree GPA and dissertation mark were significantly predicted by commitment, and commitment and gender, respectively. The findings have implications for universities targeting academic support services to maximize student scholastic potential. Future research should incorporate hardiness, gender, and age with other variables known to predict academic success.

Linking the development and functioning of a carnivorous pitcher plant's microbial digestive community.

PubMed

Armitage, David W

2017-11-01

Ecosystem development theory predicts that successional turnover in community composition can influence ecosystem functioning. However, tests of this theory in natural systems are made difficult by a lack of replicable and tractable model systems. Using the microbial digestive associates of a carnivorous pitcher plant, I tested hypotheses linking host age-driven microbial community development to host functioning. Monitoring the yearlong development of independent microbial digestive communities in two pitcher plant populations revealed a number of trends in community succession matching theoretical predictions. These included mid-successional peaks in bacterial diversity and metabolic substrate use, predictable and parallel successional trajectories among microbial communities, and convergence giving way to divergence in community composition and carbon substrate use. Bacterial composition, biomass, and diversity positively influenced the rate of prey decomposition, which was in turn positively associated with a host leaf's nitrogen uptake efficiency. Overall digestive performance was greatest during late summer. These results highlight links between community succession and ecosystem functioning and extend succession theory to host-associated microbial communities.

Endoscopic third ventriculostomy in the treatment of childhood hydrocephalus.

PubMed

Kulkarni, Abhaya V; Drake, James M; Mallucci, Conor L; Sgouros, Spyros; Roth, Jonathan; Constantini, Shlomi

2009-08-01

To develop a model to predict the probability of endoscopic third ventriculostomy (ETV) success in the treatment for hydrocephalus on the basis of a child's individual characteristics. We analyzed 618 ETVs performed consecutively on children at 12 international institutions to identify predictors of ETV success at 6 months. A multivariable logistic regression model was developed on 70% of the dataset (training set) and validated on 30% of the dataset (validation set). In the training set, 305/455 ETVs (67.0%) were successful. The regression model (containing patient age, cause of hydrocephalus, and previous cerebrospinal fluid shunt) demonstrated good fit (Hosmer-Lemeshow, P = .78) and discrimination (C statistic = 0.70). In the validation set, 105/163 ETVs (64.4%) were successful and the model maintained good fit (Hosmer-Lemeshow, P = .45), discrimination (C statistic = 0.68), and calibration (calibration slope = 0.88). A simplified ETV Success Score was devised that closely approximates the predicted probability of ETV success. Children most likely to succeed with ETV can now be accurately identified and spared the long-term complications of CSF shunting.

Automated System Checkout to Support Predictive Maintenance for the Reusable Launch Vehicle

NASA Technical Reports Server (NTRS)

Patterson-Hine, Ann; Deb, Somnath; Kulkarni, Deepak; Wang, Yao; Lau, Sonie (Technical Monitor)

1998-01-01

The Propulsion Checkout and Control System (PCCS) is a predictive maintenance software system. The real-time checkout procedures and diagnostics are designed to detect components that need maintenance based on their condition, rather than using more conventional approaches such as scheduled or reliability centered maintenance. Predictive maintenance can reduce turn-around time and cost and increase safety as compared to conventional maintenance approaches. Real-time sensor validation, limit checking, statistical anomaly detection, and failure prediction based on simulation models are employed. Multi-signal models, useful for testability analysis during system design, are used during the operational phase to detect and isolate degraded or failed components. The TEAMS-RT real-time diagnostic engine was developed to utilize the multi-signal models by Qualtech Systems, Inc. Capability of predicting the maintenance condition was successfully demonstrated with a variety of data, from simulation to actual operation on the Integrated Propulsion Technology Demonstrator (IPTD) at Marshall Space Flight Center (MSFC). Playback of IPTD valve actuations for feature recognition updates identified an otherwise undetectable Main Propulsion System 12 inch prevalve degradation. The algorithms were loaded into the Propulsion Checkout and Control System for further development and are the first known application of predictive Integrated Vehicle Health Management to an operational cryogenic testbed. The software performed successfully in real-time, meeting the required performance goal of 1 second cycle time.

Dimensionality and predictive validity of the HAM-Nat, a test of natural sciences for medical school admission

PubMed Central

2011-01-01

Background Knowledge in natural sciences generally predicts study performance in the first two years of the medical curriculum. In order to reduce delay and dropout in the preclinical years, Hamburg Medical School decided to develop a natural science test (HAM-Nat) for student selection. In the present study, two different approaches to scale construction are presented: a unidimensional scale and a scale composed of three subject specific dimensions. Their psychometric properties and relations to academic success are compared. Methods 334 first year medical students of the 2006 cohort responded to 52 multiple choice items from biology, physics, and chemistry. For the construction of scales we generated two random subsamples, one for development and one for validation. In the development sample, unidimensional item sets were extracted from the item pool by means of weighted least squares (WLS) factor analysis, and subsequently fitted to the Rasch model. In the validation sample, the scales were subjected to confirmatory factor analysis and, again, Rasch modelling. The outcome measure was academic success after two years. Results Although the correlational structure within the item set is weak, a unidimensional scale could be fitted to the Rasch model. However, psychometric properties of this scale deteriorated in the validation sample. A model with three highly correlated subject specific factors performed better. All summary scales predicted academic success with an odds ratio of about 2.0. Prediction was independent of high school grades and there was a slight tendency for prediction to be better in females than in males. Conclusions A model separating biology, physics, and chemistry into different Rasch scales seems to be more suitable for item bank development than a unidimensional model, even when these scales are highly correlated and enter into a global score. When such a combination scale is used to select the upper quartile of applicants, the proportion of successful completion of the curriculum after two years is expected to rise substantially. PMID:21999767

Dimensionality and predictive validity of the HAM-Nat, a test of natural sciences for medical school admission.

PubMed

Hissbach, Johanna C; Klusmann, Dietrich; Hampe, Wolfgang

2011-10-14

Knowledge in natural sciences generally predicts study performance in the first two years of the medical curriculum. In order to reduce delay and dropout in the preclinical years, Hamburg Medical School decided to develop a natural science test (HAM-Nat) for student selection. In the present study, two different approaches to scale construction are presented: a unidimensional scale and a scale composed of three subject specific dimensions. Their psychometric properties and relations to academic success are compared. 334 first year medical students of the 2006 cohort responded to 52 multiple choice items from biology, physics, and chemistry. For the construction of scales we generated two random subsamples, one for development and one for validation. In the development sample, unidimensional item sets were extracted from the item pool by means of weighted least squares (WLS) factor analysis, and subsequently fitted to the Rasch model. In the validation sample, the scales were subjected to confirmatory factor analysis and, again, Rasch modelling. The outcome measure was academic success after two years. Although the correlational structure within the item set is weak, a unidimensional scale could be fitted to the Rasch model. However, psychometric properties of this scale deteriorated in the validation sample. A model with three highly correlated subject specific factors performed better. All summary scales predicted academic success with an odds ratio of about 2.0. Prediction was independent of high school grades and there was a slight tendency for prediction to be better in females than in males. A model separating biology, physics, and chemistry into different Rasch scales seems to be more suitable for item bank development than a unidimensional model, even when these scales are highly correlated and enter into a global score. When such a combination scale is used to select the upper quartile of applicants, the proportion of successful completion of the curriculum after two years is expected to rise substantially.

Meta-Analysis of Predictors of Dental School Performance

ERIC Educational Resources Information Center

DeCastro, Jeanette E.

2012-01-01

Accurate prediction of which candidates show the most promise of success in dental school is imperative for the candidates, the profession, and the public. Several studies suggested that predental GPAs and the Dental Admissions Test (DAT) produce a range of correlations with dental school performance measures. While there have been similarities,…

Resilience Does Not Predict Academic Performance in Gross Anatomy

ERIC Educational Resources Information Center

Elizondo-Omana, Rodrigo Enrique; Garcia-Rodriguez, Maria de los Angeles; Hinojosa-Amaya, Jose Miguel; Villarreal-Silva, Eliud Enrique; Avilan, Rosa Ivette Guzman; Cruz, Juan Jose Bazaldua; Guzman-Lopez, Santos

2010-01-01

Few studies have evaluated resilience in an academic environment as it relates to academic success or failure. This work sought to assess resilience in regular and remedial students of gross anatomy during the first and second semesters of medical school and to correlate this personal trait with academic performance. Two groups of students were…

Assessing Teachers' Skills in Detecting and Identifying Effective Interactions in the Classroom: Theory and Measurement

ERIC Educational Resources Information Center

Jamil, Faiza M.; Sabol, Terri J.; Hamre, Bridget K.; Pianta, Robert C.

2015-01-01

Contemporary education reforms focus on assessing teachers' performance and developing selection mechanisms for hiring effective teachers. Tools that enable the prediction of teachers' classroom performance promote schools' ability to hire teachers more likely to be successful in the classroom. In addition, these assessment tools can be used for…

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

PubMed

McGuffin, Liam J

2009-01-01

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

A High Performance Cloud-Based Protein-Ligand Docking Prediction Algorithm

PubMed Central

Chen, Jui-Le; Yang, Chu-Sing

2013-01-01

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result. PMID:23762864

Network-based ranking methods for prediction of novel disease associated microRNAs.

PubMed

Le, Duc-Hau

2015-10-01

Many studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a "disease module" principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the "disease module" principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction. We constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm. Analyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In addition, the performance of PRINCE, PRP and KSM was comparable with that of RWR, whereas it was worst for the neighborhood-based algorithm. Moreover, all the algorithms were stable with the change of parameters. Final, using the integrated network, we predicted six novel miRNAs (i.e., hsa-miR-101, hsa-miR-181d, hsa-miR-192, hsa-miR-423-3p, hsa-miR-484 and hsa-miR-98) associated with breast cancer. Network-based ranking algorithms, which were successfully applied for either disease gene prediction or for studying social/web networks, can be also used effectively for disease microRNA prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Core executive functions are associated with success in young elite soccer players.

PubMed

Vestberg, Torbjörn; Reinebo, Gustaf; Maurex, Liselotte; Ingvar, Martin; Petrovic, Predrag

2017-01-01

Physical capacity and coordination cannot alone predict success in team sports such as soccer. Instead, more focus has been directed towards the importance of cognitive abilities, and it has been suggested that executive functions (EF) are fundamentally important for success in soccer. However, executive functions are going through a steep development from adolescence to adulthood. Moreover, more complex EF involving manipulation of information (higher level EF) develop later than simple executive functions such as those linked to simple working memory capacity (Core EF). The link between EF and success in young soccer players is therefore not obvious. In the present study we investigated whether EF are associated with success in soccer in young elite soccer players. We performed tests measuring core EF (a demanding working memory task involving a variable n-back task; dWM) and higher level EF (Design Fluency test; DF). Color-Word Interference Test and Trail Making Test were performed on an exploratory level as they contain a linguistic element. The lower level EF test (dWM) was taken from CogStateSport computerized concussion testing and the higher level EF test (DF) was from Delis-Kaplan Executive Function System test battery (D-KEFS). In a group of young elite soccer players (n = 30; aged 12-19 years) we show that they perform better than the norm in both the dWM (+0.49 SD) and DF (+0.86 SD). Moreover, we could show that both dWM and DF correlate with the number of goals the players perform during the season. The effect was more prominent for dWM (r = 0.437) than for DF (r = 0.349), but strongest for a combined measurement (r = 0.550). The effect was still present when we controlled for intelligence, length and age in a partial correlation analysis. Thus, our study suggests that both core and higher level EF may predict success in soccer also in young players.

Core executive functions are associated with success in young elite soccer players

PubMed Central

Reinebo, Gustaf; Maurex, Liselotte; Ingvar, Martin; Petrovic, Predrag

2017-01-01

Physical capacity and coordination cannot alone predict success in team sports such as soccer. Instead, more focus has been directed towards the importance of cognitive abilities, and it has been suggested that executive functions (EF) are fundamentally important for success in soccer. However, executive functions are going through a steep development from adolescence to adulthood. Moreover, more complex EF involving manipulation of information (higher level EF) develop later than simple executive functions such as those linked to simple working memory capacity (Core EF). The link between EF and success in young soccer players is therefore not obvious. In the present study we investigated whether EF are associated with success in soccer in young elite soccer players. We performed tests measuring core EF (a demanding working memory task involving a variable n-back task; dWM) and higher level EF (Design Fluency test; DF). Color-Word Interference Test and Trail Making Test were performed on an exploratory level as they contain a linguistic element. The lower level EF test (dWM) was taken from CogStateSport computerized concussion testing and the higher level EF test (DF) was from Delis-Kaplan Executive Function System test battery (D-KEFS). In a group of young elite soccer players (n = 30; aged 12–19 years) we show that they perform better than the norm in both the dWM (+0.49 SD) and DF (+0.86 SD). Moreover, we could show that both dWM and DF correlate with the number of goals the players perform during the season. The effect was more prominent for dWM (r = 0.437) than for DF (r = 0.349), but strongest for a combined measurement (r = 0.550). The effect was still present when we controlled for intelligence, length and age in a partial correlation analysis. Thus, our study suggests that both core and higher level EF may predict success in soccer also in young players. PMID:28178738

Risk factors for cesarean section and instrumental vaginal delivery after successful external cephalic version.

PubMed

de Hundt, Marcella; Vlemmix, Floortje; Bais, Joke M J; de Groot, Christianne J; Mol, Ben Willem; Kok, Marjolein

2016-01-01

Aim of this article is to examine if we could identify factors that predict cesarean section and instrumental vaginal delivery in women who had a successful external cephalic version. We used data from a previous randomized trial among 25 hospitals and their referring midwife practices in the Netherlands. With the data of this trial, we performed a cohort study among women attempting vaginal delivery after successful ECV. We evaluated whether maternal age, gestational age, parity, time interval between ECV and delivery, birth weight, neonatal gender, and induction of labor were predictive for a vaginal delivery on one hand or a CS or instrumental vaginal delivery on the other hand. Unadjusted and adjusted odds ratios were calculated with univariate and multivariate logistic regression analysis. Among 301 women who attempted vaginal delivery after a successful external cephalic version attempt, the cesarean section rate was 13% and the instrumental vaginal delivery rate 6%, resulting in a combined instrumental delivery rate of 19%. Nulliparity increased the risk of cesarean section (OR 2.7 (95% CI 1.2-6.1)) and instrumental delivery (OR 4.2 (95% CI 2.1-8.6)). Maternal age, gestational age at delivery, time interval between external cephalic version and delivery, birth weight and neonatal gender did not contribute to the prediction of failed spontaneous vaginal delivery. In our cohort of 301 women with a successful external cephalic version, nulliparity was the only one of seven factors that predicted the risk for cesarean section and instrumental vaginal delivery.

Prediction on carbon dioxide emissions based on fuzzy rules

NASA Astrophysics Data System (ADS)

Pauzi, Herrini; Abdullah, Lazim

2014-06-01

There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

Can terrestrial diversity be predicted from soil morphology?

NASA Astrophysics Data System (ADS)

Fournier, Bertrand; Guenat, Claire; Mitchell, Edward

2010-05-01

Restoration ecology is a young discipline and, as a consequence, many concepts and methods are not yet mature. A good example of this is the case of floodplains which have been intensively embanked, dammed or otherwise engineered in industrialized countries, but are now increasingly being restored, often at high cost. There is however much confusion over the goals of floodplain restoration projects and the methods, criteria, and indicators to assess their success. Nature practitioners are interested in knowing how many and which variables are needed for an efficient monitoring and/or assessment. Although many restoration success assessment methods have been developed to meet this need, most indicators currently used are complicated and expensive or provide only spatially or temporally limited information on these complex systems. Perhaps as a result, no standard method has yet been defined and post-restoration monitoring is not systematically done. Optimizing indicators would help improve the credibility of restoration projects and would thus help to convince stakeholders and managers to support monitoring programs. As a result, defining the predictive power of restoration success indicators, as well as selecting the most pertinent variables among the ones currently used is of major importance for a sustainable and adaptive management of our river ecosystems. Soil characteristics determine key functions (e.g. decomposition) and ecosystem structure (e.g. vegetation) in terrestrial ecosystems. They therefore have a high potential information value that is, however, generally not considered in floodplain restoration assessment. In order to explore this potential, we recently developed a new synthetic indicator based on soil morphology for the evaluation of river restoration success. Following Hutchinson's ecological niche concept, we hypothesised that terrestrial biodiversity can be predicted based on soil characteristics, but that these characteristics do not perform equivalently for all taxonomic group. In this study, we explored the potential of soil morphology as a proxy for biodiversity. We used results of a previous research seeking at developing soil morphology based indicators for floodplain restoration assessment, as well as surveys of vegetation, bacteria, earthworms, and terrestrial arthropods from the same site (River Thur, CCES project RECORD: http://www.swiss-experiment.ch/index.php/Record:Home) to analyse the relationships among soil morphology and biodiversity variables and assess the efficiency of this river widening. Furthermore, we defined the best performing predictive soil variables for each taxa. Soil morphology indicators performed well in predicting terrestrial arthropod richness supporting the idea that this relatively simple indicator may represent a useful tool for the rapid assessment of floodplain restoration success. However, the indicators performed variously concerning other taxa highlighting the methods limitation and giving clues for future improvements. We conclude by discussing the potential of soil morphology in conservation biology and its possible applications for nature practitioners.

Analytic Guided-Search Model of Human Performance Accuracy in Target- Localization Search Tasks

NASA Technical Reports Server (NTRS)

Eckstein, Miguel P.; Beutter, Brent R.; Stone, Leland S.

2000-01-01

Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

PubMed Central

Xue, Li C.; Jordan, Rafael A.; EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2015-01-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. Dock-Rank uses interface residues predicted by partner-specific sequence homology-based protein–protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. PMID:23873600

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

PubMed

Xue, Li C; Jordan, Rafael A; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-02-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. Copyright © 2013 Wiley Periodicals, Inc.

Performance considerations in long-term spaceflight

NASA Technical Reports Server (NTRS)

Akins, F. R.

1979-01-01

Maintenance of skilled performance during extended space flight is of critical importance to both the health and safety of crew members and to the overall success of mission goals. An examination of long term effects and performance requirements is therefore a factor of immense importance to the planning of future missions. Factors that were investigated include: definition of performance categories to be investigated; methods for assessing and predicting performance levels; in-flight factors which can affect performance; and factors pertinent to the maintenance of skilled performance.

Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance.

PubMed

Keerativittayayut, Ruedeerat; Aoki, Ryuta; Sarabi, Mitra Taghizadeh; Jimura, Koji; Nakahara, Kiyoshi

2018-06-18

Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding. © 2018, Keerativittayayut et al.

Stress, Social Support and Adjustment.

DTIC Science & Technology

1982-03-01

approach was also used successfully by Vroom (1964) to predict job performance . Third, and perhaps most importantly, results from several recent...influence him to stay. Finally, we note that the effect of job satisfaction on turnover is moderated by performance : job satisfaction keeps poor...Steers, R. M. Performance as a moderator of the job satisfaction - turnover relationship. Journal of Applied Psychology, 1981, 66, 511-514. Thurstone, L

The Use of Remotely Controlled Mandibular Positioner as a Predictive Screening Tool for Mandibular Advancement Device Therapy in Patients with Obstructive Sleep Apnea through Single-Night Progressive Titration of the Mandible: A Systematic Review

PubMed Central

Kastoer, Chloé; Dieltjens, Marijke; Oorts, Eline; Hamans, Evert; Braem, Marc J.; Van de Heyning, Paul H.; Vanderveken, Olivier M.

2016-01-01

Study Objectives: To perform a review of the current evidence regarding the use of a remotely controlled mandibular positioner (RCMP) and to analyze the efficacy of RCMP as a predictive selection tool in the treatment of obstructive sleep apnea (OSA) with oral appliances that protrude the mandible (OAm), exclusively relying on single-night RCMP titration. Methods: An extensive literature search is performed through PubMed.com, Thecochranelibrary.com (CENTRAL only), Embase.com, and recent conference meeting abstracts in the field. Results: A total of 254 OSA patients from four full-text articles and 5 conference meeting abstracts contribute data to the review. Criteria for successful RCMP test and success with OAm differed between studies. Study populations were not fully comparable due to range-difference in baseline apneahypopnea index (AHI). However, in all studies elimination of airway obstruction events during sleep by RCMP titration predicted OAm therapy success by the determination of the most effective target protrusive position (ETPP). A statistically significant association is found between mean AHI predicted outcome with RCMP and treatment outcome with OAm on polysomnographic or portable sleep monitoring evaluation (p < 0.05). Conclusions: The existing evidence regarding the use of RCMP in patients with OSA indicates that it might be possible to protrude the mandible progressively during sleep under poly(somno)graphic observation by RCMP until respiratory events are eliminated without disturbing sleep or arousing the patient. ETPP as measured by the use of RCMP was significantly associated with success of OAm therapy in the reported studies. RCMP might be a promising instrument for predicting OAm treatment outcome and targeting the degree of mandibular advancement needed. Citation: Kastoer C, Dieltjens M, Oorts E, Hamans E, Braem MJ, Van de Heyning PH, Vanderveken OM. The use of remotely controlled mandibular positioner as a predictive screening tool for mandibular advancement device therapy in patients with obstructive sleep apnea through single-night progressive titration of the mandible: a systematic review. J Clin Sleep Med 2016;12(10):1411–1421. PMID:27568892

Entry Grades and Academic Performance in Nigerian Universities.

ERIC Educational Resources Information Center

Ojo, Folayan

1976-01-01

The reliability of Nigeria's entry qualification examinations as a predictor of success at the university level is examined. Results indicate a positive correlation in the science-based fields and very low predictability in the social sciences. (JMF)

A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues

NASA Technical Reports Server (NTRS)

Tucker, David A.

2007-01-01

Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.

A novel adjuvant to the resident selection process: the hartman value profile.

PubMed

Cone, Jeffrey D; Byrum, C Stephen; Payne, Wyatt G; Smith, David J

2012-01-01

The goal of resident selection is twofold: (1) select candidates who will be successful residents and eventually successful practitioners and (2) avoid selecting candidates who will be unsuccessful residents and/or eventually unsuccessful practitioners. Traditional tools used to select residents have well-known limitations. The Hartman Value Profile (HVP) is a proven adjuvant tool to predicting future performance in candidates for advanced positions in the corporate setting. No literature exists to indicate use of the HVP for resident selection. The HVP evaluates the structure and the dynamics of an individual value system. Given the potential impact, we implemented its use beginning in 2007 as an adjuvant tool to the traditional selection process. Experience gained from incorporating the HVP into the residency selection process suggests that it may add objectivity and refinement in predicting resident performance. Further evaluation is warranted with longer follow-up times.

A Novel Adjuvant to the Resident Selection Process: the Hartman Value Profile

PubMed Central

Cone, Jeffrey D.; Byrum, C. Stephen; Payne, Wyatt G.; Smith, David J.

2012-01-01

Objectives: The goal of resident selection is twofold: (1) select candidates who will be successful residents and eventually successful practitioners and (2) avoid selecting candidates who will be unsuccessful residents and/or eventually unsuccessful practitioners. Traditional tools used to select residents have well-known limitations. The Hartman Value Profile (HVP) is a proven adjuvant tool to predicting future performance in candidates for advanced positions in the corporate setting. Methods: No literature exists to indicate use of the HVP for resident selection. Results: The HVP evaluates the structure and the dynamics of an individual value system. Given the potential impact, we implemented its use beginning in 2007 as an adjuvant tool to the traditional selection process. Conclusions: Experience gained from incorporating the HVP into the residency selection process suggests that it may add objectivity and refinement in predicting resident performance. Further evaluation is warranted with longer follow-up times. PMID:22720114

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

PubMed

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.

The multiple mini-interview for emergency medicine resident selection.

PubMed

Hopson, Laura R; Burkhardt, John C; Stansfield, R Brent; Vohra, Taher; Turner-Lawrence, Danielle; Losman, Eve D

2014-04-01

The Multiple Mini-Interview (MMI) uses multiple, short-structured contacts to evaluate communication and professionalism. It predicts medical school success better than the traditional interview and application. Its acceptability and utility in emergency medicine (EM) residency selection are unknown. We theorized that participants would judge the MMI equal to a traditional unstructured interview and it would provide new information for candidate assessment. Seventy-one interns from 3 programs in the first month of training completed an eight-station MMI focused on EM topics. Pre- and post-surveys assessed reactions. MMI scores were compared with application data. EM grades correlated with MMI performance (F[1, 66] = 4.18; p < 0.05) with honors students having higher scores. Higher third-year clerkship grades were associated with higher MMI performance, although this was not statistically significant. MMI performance did not correlate with match desirability and did not predict most other components of an application. There was a correlation between lower MMI scores and lower global ranking on the Standardized Letter of Recommendation. Participants preferred a traditional interview (mean difference = 1.36; p < 0.01). A mixed format (traditional interview and MMI) was preferred over a MMI alone (mean difference = 1.1; p < 0.01). MMI performance did not significantly correlate with preference for the MMI. Although the MMI alone was viewed less favorably than a traditional interview, participants were receptive to a mixed-methods interview. The MMI does correlate with performance on the EM clerkship and therefore can measure important abilities for EM success. Future work will determine whether MMI performance predicts residency performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Engagement vs Performance: Using Electronic Portfolios to Predict First Semester Engineering Student Persistence

ERIC Educational Resources Information Center

Aguiar, Everaldo; Ambrose, G. Alex; Chawla, Nitesh V.; Goodrich, Victoria; Brockman, Jay

2014-01-01

As providers of higher education begin to harness the power of big data analytics, one very fitting application for these new techniques is that of predicting student attrition. The ability to pinpoint students who might soon decide to drop out, or who may be following a suboptimal path to success, allows those in charge not only to understand the…

Can Creatinine Height Index Predict Weaning and Survival Outcomes in Patients on Prolonged Mechanical Ventilation After Critical Illness?

PubMed

Datta, Debapriya; Foley, Raymond; Wu, Rong; Grady, James; Scalise, Paul

2018-02-01

Malnutrition is common in chronic critically ill patients on prolonged mechanical ventilation (PMV) and may affect weaning. The creatinine height index (CHI), which reflects lean muscle mass, is regarded as the most accurate indicator of malnutrition. The objective of this study was to determine the impact of CHI in comparison with other traditional nutritional indices on successful weaning and survival in patients on PMV after critical illness. Records of 167 patients on PMV following critical illness, admitted for weaning, were reviewed. Parameters studied included age, gender, body mass index (BMI), percentage ideal body weight (%IBW), total protein, albumin, prealbumin, hemoglobin (Hb), and cause of respiratory failure. Number successfully weaned and number discharged alive and time to wean and time to discharge alive were determined from records. The CHI was calculated from 24-hour urine creatinine using a standard formula. Unpaired 2-sample t test was performed to determine the association between the studied nutritional parameters and outcomes. Predictive value of studied parameters for successful weaning and survival was determined by multivariate logistic regression analysis to model dichotomous outcome of successful weaning and survival. Mean age was 68 ± 14 years, 49% were males, 64% were successfully weaned, and 65.8% survived. Total protein, Hb, and CHI had a significant impact on successful weaning. Weight, %IBW, BMI, and CHI had a significant effect on survival. Of all parameters, CHI was most strongly predictive of successful weaning and survival. The CHI is a strong predictor of successful weaning and survival in patients on PMV.

When they listen and when they watch: Pianists’ use of nonverbal audio and visual cues during duet performance

PubMed Central

Goebl, Werner

2015-01-01

Nonverbal auditory and visual communication helps ensemble musicians predict each other’s intentions and coordinate their actions. When structural characteristics of the music make predicting co-performers’ intentions difficult (e.g., following long pauses or during ritardandi), reliance on incoming auditory and visual signals may change. This study tested whether attention to visual cues during piano–piano and piano–violin duet performance increases in such situations. Pianists performed the secondo part to three duets, synchronizing with recordings of violinists or pianists playing the primo parts. Secondos’ access to incoming audio and visual signals and to their own auditory feedback was manipulated. Synchronization was most successful when primo audio was available, deteriorating when primo audio was removed and only cues from primo visual signals were available. Visual cues were used effectively following long pauses in the music, however, even in the absence of primo audio. Synchronization was unaffected by the removal of secondos’ own auditory feedback. Differences were observed in how successfully piano–piano and piano–violin duos synchronized, but these effects of instrument pairing were not consistent across pieces. Pianists’ success at synchronizing with violinists and other pianists is likely moderated by piece characteristics and individual differences in the clarity of cueing gestures used. PMID:26279610

Bioreactor design for successive culture of anchorage-dependent cells operated in an automated manner.

PubMed

Kino-Oka, Masahiro; Ogawa, Natsuki; Umegaki, Ryota; Taya, Masahito

2005-01-01

A novel bioreactor system was designed to perform a series of batchwise cultures of anchorage-dependent cells by means of automated operations of medium change and passage for cell transfer. The experimental data on contamination frequency ensured the biological cleanliness in the bioreactor system, which facilitated the operations in a closed environment, as compared with that in flask culture system with manual handlings. In addition, the tools for growth prediction (based on growth kinetics) and real-time growth monitoring by measurement of medium components (based on small-volume analyzing machinery) were installed into the bioreactor system to schedule the operations of medium change and passage and to confirm that culture proceeds as scheduled, respectively. The successive culture of anchorage-dependent cells was conducted with the bioreactor running in an automated way. The automated bioreactor gave a successful culture performance with fair accordance to preset scheduling based on the information in the latest subculture, realizing 79- fold cell expansion for 169 h. In addition, the correlation factor between experimental data and scheduled values through the bioreactor performance was 0.998. It was concluded that the proposed bioreactor with the integration of the prediction and monitoring tools could offer a feasible system for the manufacturing process of cultured tissue products.

The differential effects of intrinsic and identified motivation on well-being and performance: prospective, experimental, and implicit approaches to self-determination theory.

PubMed

Burton, Kimberly D; Lydon, John E; D'Alessandro, David U; Koestner, Richard

2006-10-01

Self-determination theory research has demonstrated that intrinsic and identified self-regulations are associated with successful adaptation. However, few distinctions are typically made between these regulations and their outcomes. In the present studies, the associations between intrinsic and identified motivations and outcomes of psychological well-being and academic performance are compared in educational settings. In Study 1, intrinsic self-regulation predicted psychological well-being, independent of academic performance. In contrast, identified regulation predicted academic performance. Additionally, the more that students demonstrated an identified academic regulation, the more that their psychological well-being was contingent on performance. In Study 2a, priming intrinsic self-regulation led to greater psychological well-being 10 days later. In Study 2b, an implicit measure of identified regulation predicted academic performance 6 weeks later. Results indicate the need to address important distinctions between intrinsic and identified regulations. 2006 APA, all rights reserved

Selecting the minimum prediction base of historical data to perform 5-year predictions of the cancer burden: The GoF-optimal method.

PubMed

Valls, Joan; Castellà, Gerard; Dyba, Tadeusz; Clèries, Ramon

2015-06-01

Predicting the future burden of cancer is a key issue for health services planning, where a method for selecting the predictive model and the prediction base is a challenge. A method, named here Goodness-of-Fit optimal (GoF-optimal), is presented to determine the minimum prediction base of historical data to perform 5-year predictions of the number of new cancer cases or deaths. An empirical ex-post evaluation exercise for cancer mortality data in Spain and cancer incidence in Finland using simple linear and log-linear Poisson models was performed. Prediction bases were considered within the time periods 1951-2006 in Spain and 1975-2007 in Finland, and then predictions were made for 37 and 33 single years in these periods, respectively. The performance of three fixed different prediction bases (last 5, 10, and 20 years of historical data) was compared to that of the prediction base determined by the GoF-optimal method. The coverage (COV) of the 95% prediction interval and the discrepancy ratio (DR) were calculated to assess the success of the prediction. The results showed that (i) models using the prediction base selected through GoF-optimal method reached the highest COV and the lowest DR and (ii) the best alternative strategy to GoF-optimal was the one using the base of prediction of 5-years. The GoF-optimal approach can be used as a selection criterion in order to find an adequate base of prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Locus of Control & Motivation Strategies for Learning Questionnaire: Predictors of Student Success on the ATI Comprehensive Predictor Exam & NCLEX-RN Examination

ERIC Educational Resources Information Center

Carpenter, Jane H.

2011-01-01

The two purposes of this study were to determine whether locus of control (LOC) was predictive of how a student would perform on the ATI Comprehensive Predictor Exam and the NCLEX-RN, and if the Motivated Strategies for Learning Questionnaire (MSLQ) provided information that would help determine predictors of success on these two exams. The study…

Cultural differences in self-recognition: the early development of autonomous and related selves?

PubMed

Ross, Josephine; Yilmaz, Mandy; Dale, Rachel; Cassidy, Rose; Yildirim, Iraz; Suzanne Zeedyk, M

2017-05-01

Fifteen- to 18-month-old infants from three nationalities were observed interacting with their mothers and during two self-recognition tasks. Scottish interactions were characterized by distal contact, Zambian interactions by proximal contact, and Turkish interactions by a mixture of contact strategies. These culturally distinct experiences may scaffold different perspectives on self. In support, Scottish infants performed best in a task requiring recognition of the self in an individualistic context (mirror self-recognition), whereas Zambian infants performed best in a task requiring recognition of the self in a less individualistic context (body-as-obstacle task). Turkish infants performed similarly to Zambian infants on the body-as-obstacle task, but outperformed Zambians on the mirror self-recognition task. Verbal contact (a distal strategy) was positively related to mirror self-recognition and negatively related to passing the body-as-obstacle task. Directive action and speech (proximal strategies) were negatively related to mirror self-recognition. Self-awareness performance was best predicted by cultural context; autonomous settings predicted success in mirror self-recognition, and related settings predicted success in the body-as-obstacle task. These novel data substantiate the idea that cultural factors may play a role in the early expression of self-awareness. More broadly, the results highlight the importance of moving beyond the mark test, and designing culturally sensitive tests of self-awareness. © 2016 John Wiley & Sons Ltd.

Low Motivational Incongruence Predicts Successful EEG Resting-state Neurofeedback Performance in Healthy Adults.

PubMed

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.

Analysis of free modeling predictions by RBO aleph in CASP11.

PubMed

Mabrouk, Mahmoud; Werner, Tim; Schneider, Michael; Putz, Ines; Brock, Oliver

2016-09-01

The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue-residue contact prediction by EPC-map and contact-guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. Proteins 2016; 84(Suppl 1):87-104. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Levels of mania and cognitive performance two years after ECT in patients with bipolar I disorder - results from a follow-up study.

PubMed

Haghighi, Mohammad; Barikani, Reza; Jahangard, Leila; Ahmadpanah, Mohammad; Bajoghli, Hafez; Sadeghi Bahmani, Dena; Holsboer-Trachsler, Edith; Brand, Serge

2016-08-01

There is limited evidence on the long-term outcomes for patients with bipolar I disorder (BP-I-D) and treated with ECT. Therefore, we asked whether mania scores and cognitive performance at the end of ECT treatment (baseline/BL) predicted mania scores, cognitive performance, recurrence, treatment adherence, and mood (depression; hypomania) two years later (follow-up/FU). 38 patients with BP-I-D undergoing ECT at baseline were followed up two years later. A brief psychiatric and cognitive assessment (Mini Mental State Examination; short-term verbal memory test) was performed; patients completed questionnaires covering recurrence, treatment adherence, and mood (depression; hypomania). High cognitive performance at BL predicted high cognitive performance at FU; low mania scores at BL predicted low mania scores at FU. By FU, cognitive performance had increased and mania scores decreased. Mania scores and cognitive performance at BL did not predict recurrence, or adherence to medication, or mood (depression; hypomania). The pattern of results suggests that after two years of successful treatment of acute mania with ECT, cognitive impairment, measured by MMSE and a short-term verbal memory test, is not impaired and mood symptom recurrence seems to be improved. Mania scores and cognitive performance at the end of ECT treatment predicted neither mood (depression; hypomania), nor recurrence, or adherence to medication two years later. Copyright © 2016 Elsevier Inc. All rights reserved.

University Students' Academic Performance: An Integrative Conceptual Framework and Empirical Analysis

ERIC Educational Resources Information Center

Fenollar, Pedro; Roman, Sergio; Cuestas, Pedro J.

2007-01-01

Background: The prediction and explanation of academic performance and the investigation of the factors relating to the academic success and persistence of students are topics of utmost importance in higher education. Aims: The main aim of the present study is to develop and test a conceptual framework in a university context, where the effects of…

Analysis of Student Performance in Large-Enrollment Life Science Courses

ERIC Educational Resources Information Center

Creech, Leah Renee; Sweeder, Ryan D.

2012-01-01

This study examined the historical performance of students at Michigan State University in 12 life sciences courses over 13 yr to find variables impacting student success. Hierarchical linear modeling predicted 25.0-62.8% of the variance in students' grades in the courses analyzed. The primary predictor of a student's course grade was his or her…

Adjustment to University and Academic Performance: Brief Report of a Follow-Up Study

ERIC Educational Resources Information Center

Petersen, Il-haam; Louw, Johann; Dumont, Kitty; Malope, Nomxolisi

2010-01-01

This study presents data that extend an earlier analysis of predictors of academic performance from one to three years. None of the adjustment and other psychosocial variables (help-seeking, academic motivation, self-esteem, perceived stress and perceived academic overload) could predict success at university at the end of three years of study.…

Military Aptitude Testing: The Past Fifty Years

DTIC Science & Technology

1993-06-01

61 Relationship Between the STP and the Joint-Service Program ............. 64 CHAPTER 4 NORMING AND SCALING MILITARY SELECTION...34* Identify the skills and knowledge that underlie performance in an occupational area. "* Develop experimental tests that may predict performance in...and nuclear technicians.) "* Construct experimental tests that measure the skills , knowledge, and aptitudes needed for success in that occupational

The Relation of Student Engagement and Other Admission Metrics to Master of Accounting Student Performance

ERIC Educational Resources Information Center

Buckless, Frank; Krawczyk, Kathy

2016-01-01

This paper examines whether the use of student engagement (SE) information as part of the admissions process can help us to predict student academic success in Master of Accounting (MAC) programs. The association of SE, undergraduate grade point average (UGPA), and Graduate Management Admissions Test (GMAT) score to academic performance was tested…

Predicting Performance in Practical Writing: Factors That Influence Success in the Introductory Business Communication Course.

ERIC Educational Resources Information Center

Siegel, Gerald

A study attempted to develop and test a questionnaire that could combine various sorts of demographic information to identify strong or weak students and forecast their course performance. The study determined if a significant relationship existed between students' personal and academic profiles and their final course grades in an introductory…

Scoring annual earthquake predictions in China

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang; Jiang, Changsheng

2012-02-01

The Annual Consultation Meeting on Earthquake Tendency in China is held by the China Earthquake Administration (CEA) in order to provide one-year earthquake predictions over most China. In these predictions, regions of concern are denoted together with the corresponding magnitude range of the largest earthquake expected during the next year. Evaluating the performance of these earthquake predictions is rather difficult, especially for regions that are of no concern, because they are made on arbitrary regions with flexible magnitude ranges. In the present study, the gambling score is used to evaluate the performance of these earthquake predictions. Based on a reference model, this scoring method rewards successful predictions and penalizes failures according to the risk (probability of being failure) that the predictors have taken. Using the Poisson model, which is spatially inhomogeneous and temporally stationary, with the Gutenberg-Richter law for earthquake magnitudes as the reference model, we evaluate the CEA predictions based on 1) a partial score for evaluating whether issuing the alarmed regions is based on information that differs from the reference model (knowledge of average seismicity level) and 2) a complete score that evaluates whether the overall performance of the prediction is better than the reference model. The predictions made by the Annual Consultation Meetings on Earthquake Tendency from 1990 to 2003 are found to include significant precursory information, but the overall performance is close to that of the reference model.

Modeling the prediction of business intelligence system effectiveness.

PubMed

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

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

PubMed Central

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

2011-01-01

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

Success rates of a skeletal anchorage system in orthodontics: A retrospective analysis.

PubMed

Lam, Raymond; Goonewardene, Mithran S; Allan, Brent P; Sugawara, Junji

2018-01-01

To evaluate the premise that skeletal anchorage with SAS miniplates are highly successful and predictable for a range of complex orthodontic movements. This retrospective cross-sectional analysis consisted of 421 bone plates placed by one clinician in 163 patients (95 female, 68 male, mean age 29.4 years ± 12.02). Simple descriptive statistics were performed for a wide range of malocclusions and desired movements to obtain success, complication, and failure rates. The success rate of skeletal anchorage system miniplates was 98.6%, where approximately 40% of cases experienced mild complications. The most common complication was soft tissue inflammation, which was amenable to focused oral hygiene and antiseptic rinses. Infection occurred in approximately 15% of patients where there was a statistically significant correlation with poor oral hygiene. The most common movements were distalization and intrusion of teeth. More than a third of the cases involved complex movements in more than one plane of space. The success rate of skeletal anchorage system miniplates is high and predictable for a wide range of complex orthodontic movements.

Sexual selection gradients change over time in a simultaneous hermaphrodite

PubMed Central

Hoffer, Jeroen NA; Mariën, Janine; Ellers, Jacintha; Koene, Joris M

2017-01-01

Sexual selection is generally predicted to act more strongly on males than on females. The Darwin-Bateman paradigm predicts that this should also hold for hermaphrodites. However, measuring this strength of selection is less straightforward when both sexual functions are performed throughout the organism’s lifetime. Besides, quantifications of sexual selection are usually done during a short time window, while many animals store sperm and are long-lived. To explore whether the chosen time frame affects estimated measures of sexual selection, we recorded mating success and reproductive success over time, using a simultaneous hermaphrodite. Our results show that male sexual selection gradients are consistently positive. However, an individual’s female mating success seems to negatively affect its own male reproductive success, an effect that only becomes visible several weeks into the experiment, highlighting that the time frame is crucial for the quantification and interpretation of sexual selection measures, an insight that applies to any iteroparous mating system. DOI: http://dx.doi.org/10.7554/eLife.25139.001 PMID:28613158

Novel Automated Approach to Predict the Outcome of Laser Peripheral Iridotomy for Primary Angle Closure Suspect Eyes Using Anterior Segment Optical Coherence Tomography.

PubMed

Koh, Victor; Swamidoss, Issac Niwas; Aquino, Maria Cecilia D; Chew, Paul T; Sng, Chelvin

2018-04-27

Develop an algorithm to predict the success of laser peripheral iridotomy (LPI) in primary angle closure suspect (PACS), using pre-treatment anterior segment optical coherence tomography (ASOCT) scans. A total of 116 eyes with PACS underwent LPI and time-domain ASOCT scans (temporal and nasal cuts) were performed before and 1 month after LPI. All the post-treatment scans were classified to one of the following categories: (a) both angles open, (b) one of two angles open and (c) both angles closed. After LPI, success is defined as one or more angles changed from close to open. In this proposed method, the pre and post-LPI ASOCT scans were registered at the corresponding angles based on similarities between the respective local descriptor features and random sample consensus technique was used to identify the largest consensus set of correspondences between the pre and post-LPI ASOCT scans. Subsequently, features such as correlation co-efficient (CC) and structural similarity index (SSIM) were extracted and correlated with the success of LPI. We included 116 eyes and 91 (78.44%) eyes fulfilled the criteria for success after LPI. Using the CC and SSIM index scores from this training set of ASOCT images, our algorithm showed that the success of LPI in eyes with narrow angles can be predicted with 89.7% accuracy, specificity of 95.2% and sensitivity of 36.4% based on pre-LPI ASOCT scans only. Using pre-LPI ASOCT scans, our proposed algorithm showed good accuracy in predicting the success of LPI for PACS eyes. This fully-automated algorithm could aid decision making in offering LPI as a prophylactic treatment for PACS.

A support vector machine for predicting defibrillation outcomes from waveform metrics.

PubMed

Howe, Andrew; Escalona, Omar J; Di Maio, Rebecca; Massot, Bertrand; Cromie, Nick A; Darragh, Karen M; Adgey, Jennifer; McEneaney, David J

2014-03-01

Algorithms to predict shock success based on VF waveform metrics could significantly enhance resuscitation by optimising the timing of defibrillation. To investigate robust methods of predicting defibrillation success in VF cardiac arrest patients, by using a support vector machine (SVM) optimisation approach. Frequency-domain (AMSA, dominant frequency and median frequency) and time-domain (slope and RMS amplitude) VF waveform metrics were calculated in a 4.1Y window prior to defibrillation. Conventional prediction test validity of each waveform parameter was conducted and used AUC>0.6 as the criterion for inclusion as a corroborative attribute processed by the SVM classification model. The latter used a Gaussian radial-basis-function (RBF) kernel and the error penalty factor C was fixed to 1. A two-fold cross-validation resampling technique was employed. A total of 41 patients had 115 defibrillation instances. AMSA, slope and RMS waveform metrics performed test validation with AUC>0.6 for predicting termination of VF and return-to-organised rhythm. Predictive accuracy of the optimised SVM design for termination of VF was 81.9% (± 1.24 SD); positive and negative predictivity were respectively 84.3% (± 1.98 SD) and 77.4% (± 1.24 SD); sensitivity and specificity were 87.6% (± 2.69 SD) and 71.6% (± 9.38 SD) respectively. AMSA, slope and RMS were the best VF waveform frequency-time parameters predictors of termination of VF according to test validity assessment. This a priori can be used for a simplified SVM optimised design that combines the predictive attributes of these VF waveform metrics for improved prediction accuracy and generalisation performance without requiring the definition of any threshold value on waveform metrics. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

[Two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education].

PubMed

Lee, Soon Ok; Lee, Sang Yeoup; Baek, Sunyong; Woo, Jae Seok; Im, Sun Ju; Yune, So Jung; Lee, Sun Hee; Kam, Beesung

2015-06-01

We performed a two-and-a-half year follow-up study of strategy factors in successful learning to predict academic achievements in medical education. Strategy factors in successful learning were identified using a content analysis of open-ended responses from 30 medical students who were ranked in the top 10 of their class. Core words were selected among their responses in each category and the frequency of the words were counted. Then, a factors survey was conducted among year 2 students, before the second semester. Finally, we performed an analysis to assess the association between the factors score and academic achievement for the same students 2.5 years later. The core words were "planning and execution," "daily reviews" in the study schedule category; "focusing in class" and "taking notes" among class-related category; and "lecture notes," "previous exams or papers," and "textbooks" in the primary self-learning resources category. There were associations between the factors scores for study planning and execution, focusing in class, and taking notes and academic achievement, representing the second year second semester credit score, third year written exam scores and fourth year written and skill exam scores. Study planning was only one independent variable to predict fourth year summative written exam scores. In a two-and-a-half year follow-up study, associations were founded between academic achievement and the factors scores for study planning and execution, focusing in class, and taking notes. Study planning as only one independent variable is useful for predicting fourth year summative written exam score.

Predicting presidential performance in the United States: equation replication on recent survey results.

PubMed

Simonton, D K

2001-06-01

For more than 2 decades, researchers have tried to identify the variables that predict the overall performance of U.S. presidents. In 1986, there emerged a 6-variable prediction equation (D. K. Simonton, 1986c, 1987b) that has been replicated repeatedly. The predictors are years in office, war years, scandal, assassination, heroism in war, and intellectual brilliance. The author again replicated the equation on recent rankings of all presidents from George Washington through William Jefferson Clinton according to a survey of 719 experts (W. R. Ridings, Jr., & S. B. McIver, 1997). The original 6-variable equation successfully predicted both the overall rankings as well as the 5 core components of the rankings (leadership qualities, accomplishment, political skill, appointments, character and integrity). The predictive value of the equation was illustrated for the presidencies of Ronald W. Reagan, George H. W. Bush, and Clinton.

The application of SHERPA (Systematic Human Error Reduction and Prediction Approach) in the development of compensatory cognitive rehabilitation strategies for stroke patients with left and right brain damage.

PubMed

Hughes, Charmayne M L; Baber, Chris; Bienkiewicz, Marta; Worthington, Andrew; Hazell, Alexa; Hermsdörfer, Joachim

2015-01-01

Approximately 33% of stroke patients have difficulty performing activities of daily living, often committing errors during the planning and execution of such activities. The objective of this study was to evaluate the ability of the human error identification (HEI) technique SHERPA (Systematic Human Error Reduction and Prediction Approach) to predict errors during the performance of daily activities in stroke patients with left and right hemisphere lesions. Using SHERPA we successfully predicted 36 of the 38 observed errors, with analysis indicating that the proportion of predicted and observed errors was similar for all sub-tasks and severity levels. HEI results were used to develop compensatory cognitive strategies that clinicians could employ to reduce or prevent errors from occurring. This study provides evidence for the reliability and validity of SHERPA in the design of cognitive rehabilitation strategies in stroke populations.

Individualized Prediction of Heat Stress in Firefighters: A Data-Driven Approach Using Classification and Regression Trees.

PubMed

Mani, Ashutosh; Rao, Marepalli; James, Kelley; Bhattacharya, Amit

2015-01-01

The purpose of this study was to explore data-driven models, based on decision trees, to develop practical and easy to use predictive models for early identification of firefighters who are likely to cross the threshold of hyperthermia during live-fire training. Predictive models were created for three consecutive live-fire training scenarios. The final predicted outcome was a categorical variable: will a firefighter cross the upper threshold of hyperthermia - Yes/No. Two tiers of models were built, one with and one without taking into account the outcome (whether a firefighter crossed hyperthermia or not) from the previous training scenario. First tier of models included age, baseline heart rate and core body temperature, body mass index, and duration of training scenario as predictors. The second tier of models included the outcome of the previous scenario in the prediction space, in addition to all the predictors from the first tier of models. Classification and regression trees were used independently for prediction. The response variable for the regression tree was the quantitative variable: core body temperature at the end of each scenario. The predicted quantitative variable from regression trees was compared to the upper threshold of hyperthermia (38°C) to predict whether a firefighter would enter hyperthermia. The performance of classification and regression tree models was satisfactory for the second (success rate = 79%) and third (success rate = 89%) training scenarios but not for the first (success rate = 43%). Data-driven models based on decision trees can be a useful tool for predicting physiological response without modeling the underlying physiological systems. Early prediction of heat stress coupled with proactive interventions, such as pre-cooling, can help reduce heat stress in firefighters.

Flight performance in the altricial zebra finch: Developmental effects and reproductive consequences.

PubMed

Crino, Ondi L; Klaassen van Oorschot, Brett; Crandell, Kristen E; Breuner, Creagh W; Tobalske, Bret W

2017-04-01

The environmental conditions animals experience during development can have sustained effects on morphology, physiology, and behavior. Exposure to elevated levels of stress hormones (glucocorticoids, GCs) during development is one such condition that can have long-term effects on animal phenotype. Many of the phenotypic effects of GC exposure during development (developmental stress) appear negative. However, there is increasing evidence that developmental stress can induce adaptive phenotypic changes. This hypothesis can be tested by examining the effect of developmental stress on fitness-related traits. In birds, flight performance is an ideal metric to assess the fitness consequences of developmental stress. As fledglings, mastering takeoff is crucial to avoid bodily damage and escape predation. As adults, takeoff can contribute to mating and foraging success as well as escape and, thus, can affect both reproductive success and survival. We examined the effects of developmental stress on flight performance across life-history stages in zebra finches ( Taeniopygia guttata ). Specifically, we examined the effects of oral administration of corticosterone (CORT, the dominant avian glucocorticoid) during development on ground-reaction forces and velocity during takeoff. Additionally, we tested for associations between flight performance and reproductive success in adult male zebra finches. Developmental stress had no effect on flight performance at all ages. In contrast, brood size (an unmanipulated variable) had sustained, negative effects on takeoff performance across life-history stages with birds from small broods performing better than birds from large broods. Flight performance at 100 days posthatching predicted future reproductive success in males; the best fliers had significantly higher reproductive success. Our results demonstrate that some environmental factors experienced during development (e.g. clutch size) have stronger, more sustained effects than others (e.g. GC exposure). Additionally, our data provide the first link between flight performance and a direct measure of reproductive success.

A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine.

PubMed

Jain, Dharm Skandh; Gupte, Sanket Rajan; Aduri, Raviprasad

2018-06-22

RNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA. Here, we present a data-driven model for RPI prediction using a gradient boosting classifier. Amino acids and nucleotides are classified based on the high-resolution structural data of RNA protein complexes. The minimum structural unit consisting of five residues is used as the descriptor. Comparative analysis of existing methods shows the consistently higher performance of our method irrespective of the length of RNA present in the RPI. The method has been successfully applied to map RPI networks involving both long noncoding RNA as well as TERRA RNA. The method is also shown to successfully predict RNA and protein hubs present in RPI networks of four different organisms. The robustness of this method will provide a way for predicting RPI networks of yet unknown interactions for both long noncoding RNA and microRNA.

Insects in fluctuating thermal environments.

PubMed

Colinet, Hervé; Sinclair, Brent J; Vernon, Philippe; Renault, David

2015-01-07

All climate change scenarios predict an increase in both global temperature means and the magnitude of seasonal and diel temperature variation. The nonlinear relationship between temperature and biological processes means that fluctuating temperatures lead to physiological, life history, and ecological consequences for ectothermic insects that diverge from those predicted from constant temperatures. Fluctuating temperatures that remain within permissive temperature ranges generally improve performance. By contrast, those which extend to stressful temperatures may have either positive impacts, allowing repair of damage accrued during exposure to thermal extremes, or negative impacts from cumulative damage during successive exposures. We discuss the mechanisms underlying these differing effects. Fluctuating temperatures could be used to enhance or weaken insects in applied rearing programs, and any prediction of insect performance in the field-including models of climate change or population performance-must account for the effect of fluctuating temperatures.

On the importance of identifying, characterizing, and predicting fundamental phenomena towards microbial electrochemistry applications.

PubMed

Torres, César Iván

2014-06-01

The development of microbial electrochemistry research toward technological applications has increased significantly in the past years, leading to many process configurations. This short review focuses on the need to identify and characterize the fundamental phenomena that control the performance of microbial electrochemical cells (MXCs). Specifically, it discusses the importance of recent efforts to discover and characterize novel microorganisms for MXC applications, as well as recent developments to understand transport limitations in MXCs. As we increase our understanding of how MXCs operate, it is imperative to continue modeling efforts in order to effectively predict their performance, design efficient MXC technologies, and implement them commercially. Thus, the success of MXC technologies largely depends on the path of identifying, understanding, and predicting fundamental phenomena that determine MXC performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Continuous Quality Improvement Airway Program Results in Sustained Increases in Intubation Success.

PubMed

Olvera, David J; Stuhlmiller, David F E; Wolfe, Allen; Swearingen, Charles F; Pennington, Troy; Davis, Daniel P

2018-02-21

Airway management is a critical skill for air medical providers, including the use of rapid sequence intubation (RSI) medications. Mediocre success rates and a high incidence of complications has challenged air medical providers to improve training and performance improvement efforts to improve clinical performance. The aim of this research was to describe the experience with a novel, integrated advanced airway management program across a large air medical company and explore the impact of the program on improvement in RSI success. The Helicopter Advanced Resuscitation Training (HeART) program was implemented across 160 bases in 2015. The HeART program includes a novel conceptual framework based on thorough understanding of physiology, critical thinking using a novel algorithm, difficult airway predictive tools, training in the optimal use of specific airway techniques and devices, and integrated performance improvement efforts to address opportunities for improvement. The C-MAC video/direct laryngoscope and high-fidelity human patient simulation laboratories were implemented during the study period. Chi-square test for trend was used to evaluate for improvements in airway management and RSI success (overall intubation success, first-attempt success, first-attempt success without desaturation) over the 25-month study period following HeART implementation. A total of 5,132 patients underwent RSI during the study period. Improvements in first-attempt intubation success (85% to 95%, p < 0.01) and first-attempt success without desaturation (84% to 94%, p < 0.01) were observed. Overall intubation success increased from 95% to 99% over the study period, but the trend was not statistically significant (p = 0.311). An integrated advanced airway management program was successful in improving RSI intubation performance in a large air medical company.

CF6 jet engine performance improvement program. Short core exhaust nozzle performance improvement concept. [specific fuel consumption reduction

NASA Technical Reports Server (NTRS)

Fasching, W. A.

1979-01-01

The short core exhaust nozzle was evaluated in CF6-50 engine ground tests including performance, acoustic, and endurance tests. The test results verified the performance predictions from scale model tests. The short core exhaust nozzle provides an internal cruise sfc reduction of 0.9 percent without an increase in engine noise. The nozzle hardware successfully completed 1000 flight cycles of endurance testing without any signs of distress.

Predictive factors for the success of McRoberts' manoeuvre and suprapubic pressure in relieving shoulder dystocia: a cross-sectional study.

PubMed

Lok, Zara Lin Zau; Cheng, Yvonne Kwun Yue; Leung, Tak Yeung

2016-10-29

McRoberts' and suprapubic pressure are often recommended as the initial choices of manoeuvres to manage shoulder dystocia, as they are believed to be less invasive compared to other manoeuvres. However, their success rates range from 23 to 40 %. This study aims to investigate the predictive factors for the success of McRoberts' manoeuvre with or without suprapubic pressure (M+/-S). All cases of shoulder dystocia in a tertiary hospital in South East Asia were recruited from 1995 to 2009. Subjects were analysed according to either 'success' or 'failure' of M+/-S. Maternal and fetal antenatal and intrapartum factors were compared by univariate and multivariate analysis. Among 198 cases of shoulder dystocia, M+/-S as the primary manoeuvre was successful in 25.8 %. The other 74.2 % needed either rotational or posterior arm manoeuvres or combination of manoeuvres. Instrumental delivery was the single most significant factor associated with an increased risk of failed M+/-S on logistic regression (p < 0.001, OR 4.88, 95 % CI 2.05-11.60). The success rate of M+/-S was only 15.0 % if shoulder dystocia occurred after instrumental delivery but was 47.7 % after spontaneous vaginal delivery. When shoulder dystocia occurs after instrumental vaginal delivery, the chance of failure of M+/-S is 85 %, which is 4.7 times higher than that after spontaneous vaginal delivery. Hence all operators performing instrumental delivery should be proficient in performing all manoeuvres to relieve shoulder dystocia when M+/-S cannot do so.

Cloud prediction of protein structure and function with PredictProtein for Debian.

PubMed

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

Cloud Prediction of Protein Structure and Function with PredictProtein for Debian

PubMed Central

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome. PMID:23971032

Pre-stimulus thalamic theta power predicts human memory formation.

PubMed

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

2016-09-01

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

OCEAN: Optimized Cross rEActivity estimatioN.

PubMed

Czodrowski, Paul; Bolick, Wolf-Guido

2016-10-24

The prediction of molecular targets is highly beneficial during the drug discovery process, be it for off-target elucidation or deconvolution of phenotypic screens. Here, we present OCEAN, a target prediction tool exclusively utilizing publically available ChEMBL data. OCEAN uses a heuristics approach based on a validation set containing almost 1000 drug ← → target relationships. New ChEMBL data (ChEMBL20 as well as ChEMBL21) released after the validation was used for a prospective OCEAN performance check. The success rates of OCEAN to predict correctly the targets within the TOP10 ranks are 77% for recently marketed drugs and 62% for all new ChEMBL20 compounds and 51% for all new ChEMBL21 compounds. OCEAN is also capable of identifying polypharmacological compounds; the success rate for molecules simultaneously hitting at least two targets is 64% to be correctly predicted within the TOP10 ranks. The source code of OCEAN can be found at http://www.github.com/rdkit/OCEAN.

Shuttle TPS thermal performance and analysis methodology

NASA Technical Reports Server (NTRS)

Neuenschwander, W. E.; Mcbride, D. U.; Armour, G. A.

1983-01-01

Thermal performance of the thermal protection system was approximately as predicted. The only extensive anomalies were filler bar scorching and over-predictions in the high Delta p gap heating regions of the orbiter. A technique to predict filler bar scorching has been developed that can aid in defining a solution. Improvement in high Delta p gap heating methodology is still under study. Minor anomalies were also examined for improvements in modeling techniques and prediction capabilities. These include improved definition of low Delta p gap heating, an analytical model for inner mode line convection heat transfer, better modeling of structure, and inclusion of sneak heating. The limited number of problems related to penetration items that presented themselves during orbital flight tests were resolved expeditiously, and designs were changed and proved successful within the time frame of that program.

Educational Objectives and Academic Performance in Higher Education. Volume 1. Prediction of Academic Performance. Volume 2. Aims and Objectives.

ERIC Educational Resources Information Center

Entwistle, Noel J.; And Others

1977-01-01

Volume 1 discusses a large-scale follow-up study of the correlates of academic success in 2,595 college students. Volume 2 presents a philosophical and historical approach to studying educational objectives. (Available in microfiche from: Carfax Publishing Company, Haddon House, Dorchester-on-Thames, Oxford 0X9 8JZ, England.) (CP)

Predicting Academic Self-Handicapping in Different Age Groups: The Role of Personal Achievement Goals and Social Goals

ERIC Educational Resources Information Center

Leondari, Angeliki; Gonida, Eleftheria

2007-01-01

Background: Academic self-handicapping refers to the use of impediments to successful performance on academic tasks. Previous studies have shown that it is related to personal achievement goals. A performance goal orientation is a positive predictor of self-handicapping, whereas a task goal orientation is unrelated to self-handicapping. Aims: The…

The role of mind-wandering in measurements of general aptitude.

PubMed

Mrazek, Michael D; Smallwood, Jonathan; Franklin, Michael S; Chin, Jason M; Baird, Benjamin; Schooler, Jonathan W

2012-11-01

Tests of working memory capacity (WMC) and fluid intelligence (gF) are thought to capture variability in a crucial cognitive capacity that is broadly predictive of success, yet pinpointing the exact nature of this capacity is an area of ongoing controversy. We propose that mind-wandering is associated with performance on tests of WMC and gF, thereby partially explaining both the reliable correlations between these tests and their broad predictive utility. Existing evidence indicates that both WMC and gF are correlated with performance on tasks of attention, yet more decisive evidence requires an assessment of the role of attention and, in particular, mind-wandering during performance of these tests. Four studies employing complementary methodological designs embedded thought sampling into tests of general aptitude and determined that mind-wandering was consistently associated with worse performance on these measures. Collectively, these studies implicate the capacity to avoid mind-wandering during demanding tasks as a potentially important source of success on measures of general aptitude, while also raising important questions about whether the previously documented relationship between WMC and mind-wandering can be exclusively attributed to executive failures preceding mind-wandering (McVay & Kane, 2010b). (PsycINFO Database Record (c) 2012 APA, all rights reserved).

A simple and efficient method for predicting protein-protein interaction sites.

PubMed

Higa, R H; Tozzi, C L

2008-09-23

Computational methods for predicting protein-protein interaction sites based on structural data are characterized by an accuracy between 70 and 80%. Some experimental studies indicate that only a fraction of the residues, forming clusters in the center of the interaction site, are energetically important for binding. In addition, the analysis of amino acid composition has shown that residues located in the center of the interaction site can be better discriminated from the residues in other parts of the protein surface. In the present study, we implement a simple method to predict interaction site residues exploiting this fact and show that it achieves a very competitive performance compared to other methods using the same dataset and criteria for performance evaluation (success rate of 82.1%).

Predicting β-Turns in Protein Using Kernel Logistic Regression

PubMed Central

Elbashir, Murtada Khalafallah; Sheng, Yu; Wang, Jianxin; Wu, FangXiang; Li, Min

2013-01-01

A β-turn is a secondary protein structure type that plays a significant role in protein configuration and function. On average 25% of amino acids in protein structures are located in β-turns. It is very important to develope an accurate and efficient method for β-turns prediction. Most of the current successful β-turns prediction methods use support vector machines (SVMs) or neural networks (NNs). The kernel logistic regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems. However, it is often not found in β-turns classification, mainly because it is computationally expensive. In this paper, we used KLR to obtain sparse β-turns prediction in short evolution time. Secondary structure information and position-specific scoring matrices (PSSMs) are utilized as input features. We achieved Q total of 80.7% and MCC of 50% on BT426 dataset. These results show that KLR method with the right algorithm can yield performance equivalent to or even better than NNs and SVMs in β-turns prediction. In addition, KLR yields probabilistic outcome and has a well-defined extension to multiclass case. PMID:23509793

Predicting β-turns in protein using kernel logistic regression.

PubMed

Elbashir, Murtada Khalafallah; Sheng, Yu; Wang, Jianxin; Wu, Fangxiang; Li, Min

2013-01-01

A β-turn is a secondary protein structure type that plays a significant role in protein configuration and function. On average 25% of amino acids in protein structures are located in β-turns. It is very important to develope an accurate and efficient method for β-turns prediction. Most of the current successful β-turns prediction methods use support vector machines (SVMs) or neural networks (NNs). The kernel logistic regression (KLR) is a powerful classification technique that has been applied successfully in many classification problems. However, it is often not found in β-turns classification, mainly because it is computationally expensive. In this paper, we used KLR to obtain sparse β-turns prediction in short evolution time. Secondary structure information and position-specific scoring matrices (PSSMs) are utilized as input features. We achieved Q total of 80.7% and MCC of 50% on BT426 dataset. These results show that KLR method with the right algorithm can yield performance equivalent to or even better than NNs and SVMs in β-turns prediction. In addition, KLR yields probabilistic outcome and has a well-defined extension to multiclass case.

A problem with problem solving: motivational traits, but not cognition, predict success on novel operant foraging tasks.

PubMed

van Horik, Jayden O; Madden, Joah R

2016-04-01

Rates of innovative foraging behaviours and success on problem-solving tasks are often used to assay differences in cognition, both within and across species. Yet the cognitive features of some problem-solving tasks can be unclear. As such, explanations that attribute cognitive mechanisms to individual variation in problem-solving performance have revealed conflicting results. We investigated individual consistency in problem-solving performances in captive-reared pheasant chicks, Phasianus colchicus , and addressed whether success depends on cognitive processes, such as trial-and-error associative learning, or whether performances may be driven solely via noncognitive motivational mechanisms, revealed through subjects' willingness to approach, engage with and persist in their interactions with an apparatus, or via physiological traits such as body condition. While subjects' participation and success were consistent within the same problems and across similar tasks, their performances were inconsistent across different types of task. Moreover, subjects' latencies to approach each test apparatus and their attempts to access the reward were not repeatable across trials. Successful individuals did not improve their performances with experience, nor were they consistent in their techniques in repeated presentations of a task. However, individuals that were highly motivated to enter the experimental chamber were more likely to participate. Successful individuals were also faster to approach each test apparatus and more persistent in their attempts to solve the tasks than unsuccessful individuals. Our findings therefore suggest that individual differences in problem-solving success can arise from inherent motivational differences alone and hence be achieved without inferring more complex cognitive processes.

A problem with problem solving: motivational traits, but not cognition, predict success on novel operant foraging tasks

PubMed Central

van Horik, Jayden O.; Madden, Joah R.

2016-01-01

Rates of innovative foraging behaviours and success on problem-solving tasks are often used to assay differences in cognition, both within and across species. Yet the cognitive features of some problem-solving tasks can be unclear. As such, explanations that attribute cognitive mechanisms to individual variation in problem-solving performance have revealed conflicting results. We investigated individual consistency in problem-solving performances in captive-reared pheasant chicks, Phasianus colchicus, and addressed whether success depends on cognitive processes, such as trial-and-error associative learning, or whether performances may be driven solely via noncognitive motivational mechanisms, revealed through subjects' willingness to approach, engage with and persist in their interactions with an apparatus, or via physiological traits such as body condition. While subjects' participation and success were consistent within the same problems and across similar tasks, their performances were inconsistent across different types of task. Moreover, subjects' latencies to approach each test apparatus and their attempts to access the reward were not repeatable across trials. Successful individuals did not improve their performances with experience, nor were they consistent in their techniques in repeated presentations of a task. However, individuals that were highly motivated to enter the experimental chamber were more likely to participate. Successful individuals were also faster to approach each test apparatus and more persistent in their attempts to solve the tasks than unsuccessful individuals. Our findings therefore suggest that individual differences in problem-solving success can arise from inherent motivational differences alone and hence be achieved without inferring more complex cognitive processes. PMID:27122637

Computer-Assisted Decision Support for Student Admissions Based on Their Predicted Academic Performance.

PubMed

Muratov, Eugene; Lewis, Margaret; Fourches, Denis; Tropsha, Alexander; Cox, Wendy C

2017-04-01

Objective. To develop predictive computational models forecasting the academic performance of students in the didactic-rich portion of a doctor of pharmacy (PharmD) curriculum as admission-assisting tools. Methods. All PharmD candidates over three admission cycles were divided into two groups: those who completed the PharmD program with a GPA ≥ 3; and the remaining candidates. Random Forest machine learning technique was used to develop a binary classification model based on 11 pre-admission parameters. Results. Robust and externally predictive models were developed that had particularly high overall accuracy of 77% for candidates with high or low academic performance. These multivariate models were highly accurate in predicting these groups to those obtained using undergraduate GPA and composite PCAT scores only. Conclusion. The models developed in this study can be used to improve the admission process as preliminary filters and thus quickly identify candidates who are likely to be successful in the PharmD curriculum.

Academic success across the transition from primary to secondary schooling among lower-income adolescents: understanding the effects of family resources and gender.

PubMed

Serbin, Lisa A; Stack, Dale M; Kingdon, Danielle

2013-09-01

Successful academic performance during adolescence is a key predictor of lifetime achievement, including occupational and social success. The present study investigated the important transition from primary to secondary schooling during early adolescence, when academic performance among youth often declines. The goal of the study was to understand how risk factors, specifically lower family resources and male gender, threaten academic success following this "critical transition" in schooling. The study involved a longitudinal examination of the predictors of academic performance in grades 7-8 among 127 (56 % girls) French-speaking Quebec (Canada) adolescents from lower-income backgrounds. As hypothesized based on transition theory, hierarchical regression analyses showed that supportive parenting and specific academic, social and behavioral competencies (including spelling ability, social skills, and lower levels of attention problems) predicted success across this transition among at-risk youth. Multiple-mediation procedures demonstrated that the set of compensatory factors fully mediated the negative impact of lower family resources on academic success in grades 7-8. Unique mediators (social skills, spelling ability, supportive parenting) also were identified. In addition, the "gender gap" in performance across the transition could be attributed statistically to differences between boys and girls in specific competencies observed prior to the transition, as well as differential parenting (i.e., support from mother) towards girls and boys. The present results contribute to our understanding of the processes by which established risk factors, such as low family income and gender impact development and academic performance during early adolescence. These "transitional" processes and subsequent academic performance may have consequences across adolescence and beyond, with an impact on lifetime patterns of achievement and occupational success.

Self-Initiated Development of Leadership Capabilities: Toward Establishing the Validity of Key Motivational Constructs and Assessment Tools

DTIC Science & Technology

2010-11-01

such as pay increases, promotions, increases in leader- ship responsibility, leadership performance /behavior ratings, and satisfaction at work. The... Vroom , 1964), self-efficacy (or expectation that one will succeed at a task) is a sub-component or direct predictor of overall motivation to perform a... satisfaction . Comparing Motivation to Lead and Motivation to Develop Leadership in Predicting Leadership Performance and Career Success In this

Administering Spatial and Cognitive Instruments In-class and On-line: Are These Equivalent?

NASA Astrophysics Data System (ADS)

Williamson, Kenneth C.; Williamson, Vickie M.; Hinze, Scott R.

2017-02-01

Standardized, well-established paper-and-pencil tests, which measure spatial abilities or which measure reasoning abilities, have long been found to be predictive of success in the STEM (science, technology, engineering, and mathematics) fields. Instructors can use these tests for prediction of success and to inform instruction. A comparative administration of spatial visualization and cognitive reasoning tests, between in-class (proctored paper and pencil) and on-line (unproctored Internet) ( N = 457), was used to investigate and to determine whether the differing instrument formats yielded equal measures of spatial ability and reasoning ability in large first-semester general chemistry sections. Although some gender differences were found, findings suggest that some differences across administration formats, but that on-line administration had similar properties of predicting chemistry performance as the in-class version. Therefore, on-line administration is a viable option for instructors to consider especially when dealing with large classes.

Prediction of antiepileptic drug treatment outcomes using machine learning.

PubMed

Colic, Sinisa; Wither, Robert G; Lang, Min; Zhang, Liang; Eubanks, James H; Bardakjian, Berj L

2017-02-01

Antiepileptic drug (AED) treatments produce inconsistent outcomes, often necessitating patients to go through several drug trials until a successful treatment can be found. This study proposes the use of machine learning techniques to predict epilepsy treatment outcomes of commonly used AEDs. Machine learning algorithms were trained and evaluated using features obtained from intracranial electroencephalogram (iEEG) recordings of the epileptiform discharges observed in Mecp2-deficient mouse model of the Rett Syndrome. Previous work have linked the presence of cross-frequency coupling (I CFC ) of the delta (2-5 Hz) rhythm with the fast ripple (400-600 Hz) rhythm in epileptiform discharges. Using the I CFC to label post-treatment outcomes we compared support vector machines (SVMs) and random forest (RF) machine learning classifiers for providing likelihood scores of successful treatment outcomes. (a) There was heterogeneity in AED treatment outcomes, (b) machine learning techniques could be used to rank the efficacy of AEDs by estimating likelihood scores for successful treatment outcome, (c) I CFC features yielded the most effective a priori identification of appropriate AED treatment, and (d) both classifiers performed comparably. Machine learning approaches yielded predictions of successful drug treatment outcomes which in turn could reduce the burdens of drug trials and lead to substantial improvements in patient quality of life.

Prediction of antiepileptic drug treatment outcomes using machine learning

NASA Astrophysics Data System (ADS)

Colic, Sinisa; Wither, Robert G.; Lang, Min; Zhang, Liang; Eubanks, James H.; Bardakjian, Berj L.

2017-02-01

Objective. Antiepileptic drug (AED) treatments produce inconsistent outcomes, often necessitating patients to go through several drug trials until a successful treatment can be found. This study proposes the use of machine learning techniques to predict epilepsy treatment outcomes of commonly used AEDs. Approach. Machine learning algorithms were trained and evaluated using features obtained from intracranial electroencephalogram (iEEG) recordings of the epileptiform discharges observed in Mecp2-deficient mouse model of the Rett Syndrome. Previous work have linked the presence of cross-frequency coupling (I CFC) of the delta (2-5 Hz) rhythm with the fast ripple (400-600 Hz) rhythm in epileptiform discharges. Using the I CFC to label post-treatment outcomes we compared support vector machines (SVMs) and random forest (RF) machine learning classifiers for providing likelihood scores of successful treatment outcomes. Main results. (a) There was heterogeneity in AED treatment outcomes, (b) machine learning techniques could be used to rank the efficacy of AEDs by estimating likelihood scores for successful treatment outcome, (c) I CFC features yielded the most effective a priori identification of appropriate AED treatment, and (d) both classifiers performed comparably. Significance. Machine learning approaches yielded predictions of successful drug treatment outcomes which in turn could reduce the burdens of drug trials and lead to substantial improvements in patient quality of life.

Pneumatic balloon dilation in pediatric achalasia: efficacy and factors predicting outcome at a single tertiary pediatric gastroenterology center.

PubMed

Di Nardo, Giovanni; Rossi, Paolo; Oliva, Salvatore; Aloi, Marina; Cozzi, Denis A; Frediani, Simone; Redler, Adriano; Mallardo, Saverio; Ferrari, Federica; Cucchiara, Salvatore

2012-11-01

The use of pneumatic dilation (PD) is well established in adults with achalasia; however, it is less commonly used in children. To evaluate the efficacy of PD in pediatric achalasia and to define predictive factors for its treatment failure. Single-center, prospective cohort study. Academic tertiary referral center. Twenty-four patients with achalasia were enrolled from January 2004 to November 2009 and were followed for a median of 6 years. PD was performed with the patients under general anesthesia. Efficacy and safety of PD. Follow-up was performed by using the Eckardt score, barium swallow contrast studies, and esophageal manometry at baseline; 1, 3, and 6 months after dilation; and every year thereafter. A Cox regression model was used to identify independent predictors of failure after the first PD. The PD success rate was 67%. In 8 patients, the first PD failed, but the parents of one patient refused a second PD and requested surgery. Of the 7 patients who underwent repeated treatment, the second PD failed in 3 (43%). Overall, only 3 of the 24 patients underwent surgery (overall success rate after a maximum of 3 PDs was 87%). Multivariate analysis showed that only older age was independently associated with a higher probability of the procedure success (hazard ratio [HR] 0.66; 95% CI, 0.45-0.97). Small sample size, single-center study. PD is a safe and effective technique in the management of pediatric achalasia. Young age is an independent negative predictive factor for successful clinical outcome. Copyright © 2012 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

Model-data assimilation of multiple phenological observations to constrain and predict leaf area index.

PubMed

Viskari, Toni; Hardiman, Brady; Desai, Ankur R; Dietze, Michael C

2015-03-01

Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002-2005 at Willow Creek, Wisconsin, USA, a mature, even-aged, northern hardwood, deciduous forest. The ecosystem demography model version 2 (ED2) was used as the prediction model, forced by offline climate data. EAKF successfully incorporated information from both the observations and model predictions weighted by their respective uncertainties. The resulting. estimate reproduced the observed leaf phenological cycle in the spring and the fall better than a parametric model prediction. These results indicate that during spring the observations contribute most in determining the correct bud-burst date, after which the model performs well, but accurately modeling fall leaf senesce requires continuous model updating from observations. While the predicted net ecosystem exchange (NEE) of CO2 precedes tower observations and unassimilated model predictions in the spring, overall the prediction follows observed NEE better than the model alone. Our results show state data assimilation successfully simulates the evolution of plant leaf phenology and improves model predictions of forest NEE.

Analysis of Gauntlet Test Performance and Injury Risk in Intercollegiate Division I Female Soccer (Football) Players: A Retrospective Study.

PubMed

Ness, Brandon M; Zimney, Kory; Schweinle, William E

2017-11-01

Injury risk factors and relevant assessments have been identified in women's soccer athletes. Other tests assess fitness (eg, the Gauntlet Test [GT]). However, little empirical support exists for the utility of the GT to predict time loss injury. To examine the GT as a predictor of injury in intercollegiate Division I female soccer athletes. Retrospective, nonexperimental descriptive cohort study. College athletic facilities. 71 female Division I soccer athletes (age 19.6 ± 1.24 y, BMI 23.0 ± 2.19). GT, demographic, and injury data were collected over 3 consecutive seasons. GT trials were administered by coaching staff each preseason. Participation in team-based activities (practices, matches) was restricted until a successful GT trial. Soccer-related injuries that resulted in time loss from participation were recorded. 71 subjects met the inclusion criteria, with 12 lower body time loss injuries sustained. Logistic regression models indicated that with each unsuccessful GT attempt, the odds of sustaining an injury increased by a factor of 3.5 (P < .02). The Youden index was 2 GT trials for success, at which sensitivity = .92 and specificity = .46. For successive GT trials before success (1, 2, or 3), the predicted probabilities for injury were .063, .194, and .463, respectively. The GT appears to be a convenient and predictive screen for potential lowerbody injuries among female soccer athletes in this cohort. Further investigation into the appropriate application of the GT for injury prediction is warranted given the scope of this study.

A multichannel model-based methodology for extubation readiness decision of patients on weaning trials.

PubMed

Casaseca-de-la-Higuera, Pablo; Simmross-Wattenberg, Federico; Martín-Fernández, Marcos; Alberola-López, Carlos

2009-07-01

Discontinuation of mechanical ventilation is a challenging task that involves a number of subtle clinical issues. The gradual removal of the respiratory support (referred to as weaning) should be performed as soon as autonomous respiration can be sustained. However, the prediction rate of successful extubation is still below 25% based on previous studies. Construction of an automatic system that provides information on extubation readiness is thus desirable. Recent works have demonstrated that the breathing pattern variability is a useful extubation readiness indicator, with improving performance when multiple respiratory signals are jointly processed. However, the existing methods for predictor extraction present several drawbacks when length-limited time series are to be processed in heterogeneous groups of patients. In this paper, we propose a model-based methodology for automatic readiness prediction. It is intended to deal with multichannel, nonstationary, short records of the breathing pattern. Results on experimental data yield an 87.27% of successful readiness prediction, which is in line with the best figures reported in the literature. A comparative analysis shows that our methodology overcomes the shortcomings of so far proposed methods when applied to length-limited records on heterogeneous groups of patients.

Parts and Components Reliability Assessment: A Cost Effective Approach

NASA Technical Reports Server (NTRS)

Lee, Lydia

2009-01-01

System reliability assessment is a methodology which incorporates reliability analyses performed at parts and components level such as Reliability Prediction, Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) to assess risks, perform design tradeoffs, and therefore, to ensure effective productivity and/or mission success. The system reliability is used to optimize the product design to accommodate today?s mandated budget, manpower, and schedule constraints. Stand ard based reliability assessment is an effective approach consisting of reliability predictions together with other reliability analyses for electronic, electrical, and electro-mechanical (EEE) complex parts and components of large systems based on failure rate estimates published by the United States (U.S.) military or commercial standards and handbooks. Many of these standards are globally accepted and recognized. The reliability assessment is especially useful during the initial stages when the system design is still in the development and hard failure data is not yet available or manufacturers are not contractually obliged by their customers to publish the reliability estimates/predictions for their parts and components. This paper presents a methodology to assess system reliability using parts and components reliability estimates to ensure effective productivity and/or mission success in an efficient manner, low cost, and tight schedule.

Emotion blocks the path to learning under stereotype threat

PubMed Central

Good, Catherine; Whiteman, Ronald C.; Maniscalco, Brian; Dweck, Carol S.

2012-01-01

Gender-based stereotypes undermine females’ performance on challenging math tests, but how do they influence their ability to learn from the errors they make? Females under stereotype threat or non-threat were presented with accuracy feedback after each problem on a GRE-like math test, followed by an optional interactive tutorial that provided step-wise problem-solving instruction. Event-related potentials tracked the initial detection of the negative feedback following errors [feedback related negativity (FRN), P3a], as well as any subsequent sustained attention/arousal to that information [late positive potential (LPP)]. Learning was defined as success in applying tutorial information to correction of initial test errors on a surprise retest 24-h later. Under non-threat conditions, emotional responses to negative feedback did not curtail exploration of the tutor, and the amount of tutor exploration predicted learning success. In the stereotype threat condition, however, greater initial salience of the failure (FRN) predicted less exploration of the tutor, and sustained attention to the negative feedback (LPP) predicted poor learning from what was explored. Thus, under stereotype threat, emotional responses to negative feedback predicted both disengagement from learning and interference with learning attempts. We discuss the importance of emotion regulation in successful rebound from failure for stigmatized groups in stereotype-salient environments. PMID:21252312

Emotion blocks the path to learning under stereotype threat.

PubMed

Mangels, Jennifer A; Good, Catherine; Whiteman, Ronald C; Maniscalco, Brian; Dweck, Carol S

2012-02-01

Gender-based stereotypes undermine females' performance on challenging math tests, but how do they influence their ability to learn from the errors they make? Females under stereotype threat or non-threat were presented with accuracy feedback after each problem on a GRE-like math test, followed by an optional interactive tutorial that provided step-wise problem-solving instruction. Event-related potentials tracked the initial detection of the negative feedback following errors [feedback related negativity (FRN), P3a], as well as any subsequent sustained attention/arousal to that information [late positive potential (LPP)]. Learning was defined as success in applying tutorial information to correction of initial test errors on a surprise retest 24-h later. Under non-threat conditions, emotional responses to negative feedback did not curtail exploration of the tutor, and the amount of tutor exploration predicted learning success. In the stereotype threat condition, however, greater initial salience of the failure (FRN) predicted less exploration of the tutor, and sustained attention to the negative feedback (LPP) predicted poor learning from what was explored. Thus, under stereotype threat, emotional responses to negative feedback predicted both disengagement from learning and interference with learning attempts. We discuss the importance of emotion regulation in successful rebound from failure for stigmatized groups in stereotype-salient environments.

Network-based de-noising improves prediction from microarray data.

PubMed

Kato, Tsuyoshi; Murata, Yukio; Miura, Koh; Asai, Kiyoshi; Horton, Paul B; Koji, Tsuda; Fujibuchi, Wataru

2006-03-20

Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as the high variance of living cell responses to drugs. Hence there is a strong need for more practical and robust methods than standard methods for real-value prediction. We devised an extended version of the off-subspace noise-reduction (de-noising) method to incorporate heterogeneous network data such as sequence similarity or protein-protein interactions into a single framework. Using that method, we first de-noise the gene expression data for training and test data and also the drug-response data for training data. Then we predict the unknown responses of each drug from the de-noised input data. For ascertaining whether de-noising improves prediction or not, we carry out 12-fold cross-validation for assessment of the prediction performance. We use the Pearson's correlation coefficient between the true and predicted response values as the prediction performance. De-noising improves the prediction performance for 65% of drugs. Furthermore, we found that this noise reduction method is robust and effective even when a large amount of artificial noise is added to the input data. We found that our extended off-subspace noise-reduction method combining heterogeneous biological data is successful and quite useful to improve prediction of human cell cancer drug responses from microarray data.

Using the American Board of Surgery In-Training Examination to predict board certification: a cautionary study.

PubMed

Jones, Andrew T; Biester, Thomas W; Buyske, Jo; Lewis, Frank R; Malangoni, Mark A

2014-01-01

Although designed as a low-stakes formative examination, the American Board of Surgery In-Training Examination (ABSITE) is often used in high-stakes decisions such as promotion, remediation, and retention owing to its perceived ability to predict the outcome of board certification. Because of the discrepancy between intent and use, the ability of ABSITE scores to predict passing the American Board of Surgery certification examinations was analyzed. All first-time American Board of Surgery qualifying examination (QE) examinees between 2006 and 2012 were reviewed. Examinees' postgraduate year (PGY) 1 and PGY5 ABSITE standard scores were linked to QE scores and pass/fail outcomes (n = 6912 and 6846, respectively) as well as first-time certifying examination (CE) pass/fail results (n = 1329). Linear and logistic regression analyses were performed to evaluate the utility of ABSITE scores to predict board certification scores and pass/fail outcomes. PGY1 ABSITE scores accounted for 22% of the variance in QE scores (p < 0.001). PGY5 scores were a slightly better predictor, accounting for 30% of QE score variance (p < 0.001). Analyses showed that selecting a PGY5 ABSITE score that maximized overall decision accuracy for predicting QE pass/fail outcomes (86% accuracy) resulted in 98% sensitivity, 13% specificity, a positive predictive value of 87%, and a negative predictive value of 57%. ABSITE scores were not predictive of success on the CE. ABSITE scores are a useful predictor of QE scores and outcomes but do not predict passing the CE. Although scoring well on the ABSITE is highly predictive of QE success, using low ABSITE scores to predict QE failure results in frequent decision errors. Program directors and other evaluators should use additional sources of information when making high-stakes decisions about resident performance. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Still under the microscope: can a surgical aptitude test predict otolaryngology resident performance?

PubMed

Moore, Eric J; Price, Daniel L; Van Abel, Kathryn M; Carlson, Matthew L

2015-02-01

Application to otolaryngology-head and neck surgery residency is highly competitive, and the interview process strives to select qualified applicants with a high aptitude for the specialty. Commonly employed criteria for applicant selection have failed to show correlation with proficiency during residency training. We evaluate the correlation between the results of a surgical aptitude test administered to otolaryngology resident applicants and their performance during residency. Retrospective study at an academic otolaryngology-head and neck surgery residency program. Between 2007 and 2013, 224 resident applicants participated in a previously described surgical aptitude test administered at a microvascular surgical station. The composite score and attitudinal scores for 24 consecutive residents who matched at our institution were recorded, and their residency performance was analyzed by faculty survey on a five-point scale. The composite and attitudinal scores were analyzed for correlation with residency performance score by regression analysis. Twenty-four residents were evaluated for overall quality as a clinician by eight faculty members who were blinded to the results of surgical aptitude testing. The results of these surveys showed good inter-rater reliability. Both the overall aptitude test scores and the subset attitudinal score showed reliability in predicting performance during residency training. The goal of the residency selection process is to evaluate the candidate's potential for success in residency and beyond. The results of this study suggest that a simple-to-administer clinical skills test may have predictive value for success in residency and clinician quality. 4. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

Designing and benchmarking the MULTICOM protein structure prediction system

PubMed Central

2013-01-01

Background Predicting protein structure from sequence is one of the most significant and challenging problems in bioinformatics. Numerous bioinformatics techniques and tools have been developed to tackle almost every aspect of protein structure prediction ranging from structural feature prediction, template identification and query-template alignment to structure sampling, model quality assessment, and model refinement. How to synergistically select, integrate and improve the strengths of the complementary techniques at each prediction stage and build a high-performance system is becoming a critical issue for constructing a successful, competitive protein structure predictor. Results Over the past several years, we have constructed a standalone protein structure prediction system MULTICOM that combines multiple sources of information and complementary methods at all five stages of the protein structure prediction process including template identification, template combination, model generation, model assessment, and model refinement. The system was blindly tested during the ninth Critical Assessment of Techniques for Protein Structure Prediction (CASP9) in 2010 and yielded very good performance. In addition to studying the overall performance on the CASP9 benchmark, we thoroughly investigated the performance and contributions of each component at each stage of prediction. Conclusions Our comprehensive and comparative study not only provides useful and practical insights about how to select, improve, and integrate complementary methods to build a cutting-edge protein structure prediction system but also identifies a few new sources of information that may help improve the design of a protein structure prediction system. Several components used in the MULTICOM system are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:23442819

Multivariate predictors of music perception and appraisal by adult cochlear implant users.

PubMed

Gfeller, Kate; Oleson, Jacob; Knutson, John F; Breheny, Patrick; Driscoll, Virginia; Olszewski, Carol

2008-02-01

The research examined whether performance by adult cochlear implant recipients on a variety of recognition and appraisal tests derived from real-world music could be predicted from technological, demographic, and life experience variables, as well as speech recognition scores. A representative sample of 209 adults implanted between 1985 and 2006 participated. Using multiple linear regression models and generalized linear mixed models, sets of optimal predictor variables were selected that effectively predicted performance on a test battery that assessed different aspects of music listening. These analyses established the importance of distinguishing between the accuracy of music perception and the appraisal of musical stimuli when using music listening as an index of implant success. Importantly, neither device type nor processing strategy predicted music perception or music appraisal. Speech recognition performance was not a strong predictor of music perception, and primarily predicted music perception when the test stimuli included lyrics. Additionally, limitations in the utility of speech perception in predicting musical perception and appraisal underscore the utility of music perception as an alternative outcome measure for evaluating implant outcomes. Music listening background, residual hearing (i.e., hearing aid use), cognitive factors, and some demographic factors predicted several indices of perceptual accuracy or appraisal of music.

Performance of a steel spar wind turbine blade on the Mod-0 100 kW experimental wind turbine

NASA Technical Reports Server (NTRS)

Keith, T. G., Jr.; Sullivan, T. L.; Viterna, L. A.

1980-01-01

The performance and loading of a large wind rotor, 38.4 m in diameter and composed of two low-cost steel spar blades were examined. Two blades were fabricated at Lewis Research Center and successfully operated on the Mod-0 wind turbine at Plum Brook. The blades were operated on a tower on which the natural bending frequency were altered by placing the tower on a leaf-spring apparatus. It was found that neither blade performance nor loading were affected significantly by this tower softening technique. Rotor performance exceeded prediction while blade loads were found to be in reasonable agreement with those predicted. Seventy-five hours of operation over a five month period resulted in no deterioration in the blade.

The variability puzzle in human memory.

PubMed

Kahana, Michael J; Aggarwal, Eash V; Phan, Tung D

2018-04-26

Memory performance exhibits a high level of variability from moment to moment. Much of this variability may reflect inadequately controlled experimental variables, such as word memorability, past practice and subject fatigue. Alternatively, stochastic variability in performance may largely reflect the efficiency of endogenous neural processes that govern memory function. To help adjudicate between these competing views, the authors conducted a multisession study in which subjects completed 552 trials of a delayed free-recall task. Applying a statistical model to predict variability in each subject's recall performance uncovered modest effects of word memorability, proactive interference, and other variables. In contrast to the limited explanatory power of these experimental variables, performance on the prior list strongly predicted current list recall. These findings suggest that endogenous factors underlying successful encoding and retrieval drive variability in performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Different behavioral patterns of success for men and women in an online introductory science course: Addressing the course grade gender gap

NASA Astrophysics Data System (ADS)

Mead, C.; Horodyskyj, L.; Buxner, S.; Semken, S. C.; Anbar, A. D.

2016-12-01

In this study, we explore how data provided by an online learning environment can provide fine-grained behavioral context for the performance gender gap commonly observed in introductory college science courses. Previous studies reported that women earn lower grades than men in such courses, often ascribed to reduced engagement and resilience driven by sociocultural causes, such as stereotype threat. This may be exacerbated in courses graded primarily based on high-stakes exams. Here, we use student data (n = 1121) from Habitable Worlds, an online laboratory science course, to identify behavioral differences between men and women. In Habitable Worlds, students earn points from 30 "trainings," which are scored on completion, and 30 "applications," which are scored on correctness. The lack of high-stakes cumulative exams represents a valuable contrast with typical science courses in which gender gaps have been reported. Our data indicate that a gender gap exists even for these low-stakes assessments. Results of a generalized linear model show that course success among women is much more strongly predicted by training scores than by application scores, while those factors have roughly equal predictive value among men. Predicted success among women is also modulated by the total number of attempts made on questions throughout the course, where more attempts implies lower success (holding other factors constant). This relationship is non-significant for men. Our interpretation of these model results is that obstacles such as stereotype threat represent a tax for women on effort and engagement, such that equivalent effort yields lesser success than for men. Thus, the women who do succeed differ sharply from lower performing women on indicators of effort. Future work should build on this result both as an indicator of conditions under which women are more likely to succeed and as a way to more quickly identify students who may struggle.

PREDICTING FIELD PERFORMANCE OF HERBACEOUS SPECIES FOR PHYTOREMEDIATION OF PERCHLORATE

EPA Science Inventory

Results of these short-term experiments coupled with ecological knowledge of the nine herbaceous plant species tested suggest that several species may by successful in on-site remediation of perchlorate. The two wetland species which appear to be most suitable for field experimen...

Contribution of personality to the prediction of success in initial air traffic control specialist training.

DOT National Transportation Integrated Search

1993-04-01

Reviews have consistently concluded that the validity of personality as a predictor of job performance is low (Besco, 1991; Reilly & Chao, 1982: Tenopyr & Oeltjen, 1982). However, Barrick and Mount's (1991) meta-analysis of studies of personality and...

Predicting Success in Upper-Division Business Communication Classes.

ERIC Educational Resources Information Center

Wilson, Barbara; Plutsky, Susan

1997-01-01

Scores of 102 business communication students on the Descriptive Tests of Language Skills (DTLS) and grades on analytical reports, short assignments, and the overall course were examined. Females received higher course and report grades. The DTLS was a weak predictor of student performance. (SK)

A New Framework for School Climate: Exploring Predictive Capability of School Climate Attributes and Impact on School Performance Scores

ERIC Educational Resources Information Center

Craig, Amy Vermaelen

2012-01-01

Much emphasis is being placed on the use of school performance scores as a means of indicating effective schools. Schools are being held accountable for not only teaching the curriculum, but also affording the student a quality education that encompasses the skills and knowledge needed to be successful. Although many schools have a similar…

Predicting academic performance and clinical competency for international dental students: seeking the most efficient and effective measures.

PubMed

Stacey, D Graham; Whittaker, John M

2005-02-01

Measures used in the selection of international dental students to a U.S. D.D.S. program were examined to identify the grouping that most effectively and efficiently predicted academic performance and clinical competency. Archival records from the International Dental Program (IDP) at Loma Linda University provided data on 171 students who had trained in countries outside the United States. The students sought admission to the D.D.S. degree program, successful completion of which qualified them to sit for U.S. licensure. As with most dental schools, competition is high for admission to the D.D.S. program. The study's goal was to identify what measures contributed to a fair and accurate selection process for dental school applicants from other nations. Multiple regression analyses identified National Board Part II and dexterity measures as significant predictors of academic performance and clinical competency. National Board Part I, TOEFL, and faculty interviews added no significant additional help in predicting eventual academic performance and clinical competency.

Executive function predicts artificial language learning

PubMed Central

Kapa, Leah L.; Colombo, John

2017-01-01

Previous research suggests executive function (EF) advantages among bilinguals compared to monolingual peers, and these advantages are generally attributed to experience controlling two linguistic systems. However, the possibility that the relationship between bilingualism and EF might be bidirectional has not been widely considered; while experience with two languages might improve EF, better EF skills might also facilitate language learning. In the current studies, we tested whether adults’ and preschool children’s EF abilities predicted success in learning a novel artificial language. After controlling for working memory and English receptive vocabulary, adults’ artificial language performance was predicted by their inhibitory control ability (Study 1) and children’s performance was predicted by their attentional monitoring and shifting ability (Study 2). These findings provide preliminary evidence suggesting that EF processes may be employed during initial stages of language learning, particularly vocabulary acquisition, and support the possibility of a bidirectional relationship between EF and language acquisition. PMID:29129958

Prediction of Unshsrouded Rotor Blade Tip Heat Transfer

NASA Technical Reports Server (NTRS)

Ameri, A. A.; Steinthorsson, E.

1994-01-01

The rate of heat transfer on the tip of a turbine rotor blade and on the blade surface in the vicinity of the tip, was successfully predicted. The computations were performed with a multiblock computer code which solves the Reynolds Averaged Navier-Stokes equations using an efficient multigrid method. The case considered for the present calculations was the Space Shuttle Main Engine (SSME) high pressure fuel side turbine. The predictions of the blade tip heat transfer agreed reasonably well with the experimental measurements using the present level of grid refinement. On the tip surface, regions with high rate of heat transfer was found to exist close to the pressure side and suction side edges. Enhancement of the heat transfer was also observed on the blade surface near the tip. Further comparison of the predictions was performed with results obtained from correlations based on fully developed channel flow.

The development of a tool to predict team performance.

PubMed

Sinclair, M A; Siemieniuch, C E; Haslam, R A; Henshaw, M J D C; Evans, L

2012-01-01

The paper describes the development of a tool to predict quantitatively the success of a team when executing a process. The tool was developed for the UK defence industry, though it may be useful in other domains. It is expected to be used by systems engineers in initial stages of systems design, when concepts are still fluid, including the structure of the team(s) which are expected to be operators within the system. It enables answers to be calculated for questions such as "What happens if I reduce team size?" and "Can I reduce the qualifications necessary to execute this process and still achieve the required level of success?". The tool has undergone verification and validation; it predicts fairly well and shows promise. An unexpected finding is that the tool creates a good a priori argument for significant attention to Human Factors Integration in systems projects. The simulations show that if a systems project takes full account of human factors integration (selection, training, process design, interaction design, culture, etc.) then the likelihood of team success will be in excess of 0.95. As the project derogates from this state, the likelihood of team success will drop as low as 0.05. If the team has good internal communications and good individuals in key roles, the likelihood of success rises towards 0.25. Even with a team comprising the best individuals, p(success) will not be greater than 0.35. It is hoped that these results will be useful for human factors professionals involved in systems design. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Simple, validated vaginal birth after cesarean delivery prediction model for use at the time of admission.

PubMed

Metz, Torri D; Stoddard, Gregory J; Henry, Erick; Jackson, Marc; Holmgren, Calla; Esplin, Sean

2013-09-01

To create a simple tool for predicting the likelihood of successful trial of labor after cesarean delivery (TOLAC) during the pregnancy after a primary cesarean delivery using variables available at the time of admission. Data for all deliveries at 14 regional hospitals over an 8-year period were reviewed. Women with one cesarean delivery and one subsequent delivery were included. Variables associated with successful VBAC were identified using multivariable logistic regression. Points were assigned to these characteristics, with weighting based on the coefficients in the regression model to calculate an integer VBAC score. The VBAC score was correlated with TOLAC success rate and was externally validated in an independent cohort using a logistic regression model. A total of 5,445 women met inclusion criteria. Of those women, 1,170 (21.5%) underwent TOLAC. Of the women who underwent trial of labor, 938 (80%) had a successful VBAC. A VBAC score was generated based on the Bishop score (cervical examination) at the time of admission, with points added for history of vaginal birth, age younger than 35 years, absence of recurrent indication, and body mass index less than 30. Women with a VBAC score less than 10 had a likelihood of TOLAC success less than 50%. Women with a VBAC score more than 16 had a TOLAC success rate more than 85%. The model performed well in an independent cohort with an area under the curve of 0.80 (95% confidence interval 0.76-0.84). Prediction of TOLAC success at the time of admission is highly dependent on the initial cervical examination. This simple VBAC score can be utilized when counseling women considering TOLAC. II.

Can blood and semen presepsin levels in males predict pregnancy in couples undergoing intra-cytoplasmic sperm injection?

PubMed

Ovayolu, Ali; Arslanbuğa, Cansev Yilmaz; Gun, Ismet; Devranoglu, Belgin; Ozdemir, Arman; Cakar, Sule Eren

2016-01-01

To determine whether semen and plasma presepsin values measured in men with normozoospermia and oligoasthenospermia undergoing invitro-fertilization would be helpful in predicting ongoing pregnancy and live birth. Group-I was defined as patients who had pregnancy after treatment and Group-II comprised those with no pregnancy. Semen and blood presepsin values were subsequently compared between the groups. Parametric comparisons were performed using Student's t-test, and non-parametric comparisons were conducted using the Mann-Whitney U test. There were 42 patients in Group-I and 72 in Group-II. In the context of successful pregnancy and live birth, semen presepsin values were statistically significantly higher in Group-I than in Group-II (p= 0.004 and p= 0.037, respectively). The most appropriate semen presepsin cut-off value for predicting both ongoing pregnancy and live birth was calculated as 199 pg/mL. Accordingly, their sensitivity was 64.5% to 59.3%, their specificity was 57.0% to 54.2%, and their positive predictive value was 37.0% to 29.6%, respectively; their negative predictive value was 80.4% in both instances. Semen presepsin values could be a new marker that may enable the prediction of successful pregnancy and/or live birth. Its negative predictive values are especially high.

Predicting risky choices from brain activity patterns

PubMed Central

Helfinstein, Sarah M.; Schonberg, Tom; Congdon, Eliza; Karlsgodt, Katherine H.; Mumford, Jeanette A.; Sabb, Fred W.; Cannon, Tyrone D.; London, Edythe D.; Bilder, Robert M.; Poldrack, Russell A.

2014-01-01

Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights. PMID:24550270

Predicting Resident Performance from Preresidency Factors: A Systematic Review and Applicability to Neurosurgical Training.

PubMed

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 recruitment to the greater field of neurosurgery, these data provide support for a national, prospective effort to improve the study of neurosurgery resident selection. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting introductory programming performance: A multi-institutional multivariate study

NASA Astrophysics Data System (ADS)

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.

Predicting red wolf release success in the southeastern United States

USGS Publications Warehouse

van Manen, Frank T.; Crawford, Barron A.; Clark, Joseph D.

2000-01-01

Although the red wolf (Canis rufus) was once found throughout the southeastern United States, indiscriminate killing and habitat destruction reduced its range to a small section of coastal Texas and Louisiana. Wolves trapped from 1973 to 1980 were taken to establish a captive breeding program that was used to repatriate 2 mainland and 3 island red wolf populations. We collected data from 320 red wolf releases in these areas and classified each as a success or failure based on survival and reproductive criteria, and whether recaptures were necessary to resolve conflicts with humans. We evaluated the relations between release success and conditions at the release sites, characteristics of released wolves, and release procedures. Although <44% of the variation in release success was explained, model performance based on jackknife tests indicated a 72-80% correct prediction rate for the 4 operational models we developed. The models indicated that success was associated with human influences on the landscape and the level of wolf habituation to humans prior to release. We applied the models to 31 prospective areas for wolf repatriation and calculated an index of release success for each area. Decision-makers can use these models to objectively rank prospective release areas and compare strengths and weaknesses of each.

Stock price change rate prediction by utilizing social network activities.

PubMed

Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

PubMed Central

Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

Player's success prediction in rugby union: From youth performance to senior level placing.

PubMed

Fontana, Federico Y; Colosio, Alessandro L; Da Lozzo, Giorgio; Pogliaghi, Silvia

2017-04-01

The study questioned if and to what extent specific anthropometric and functional characteristics measured in youth draft camps, can accurately predict subsequent career progression in rugby union. Original research. Anthropometric and functional characteristics of 531 male players (U16) were retrospectively analysed in relation to senior level team representation at age 21-24. Players were classified as International (Int: National team and international clubs) or National (Nat: 1st, 2nd and other divisions and dropout). Multivariate analysis of variance (one-way MANOVA) tested differences between Int and Nat, along a combination of anthropometric (body mass, height, body fat, fat-free mass) and functional variables (SJ, CMJ, t 15m , t 30m , VO 2max ). A discriminant function (DF) was determined to predict group assignment based on the linear combination of variables that best discriminate groups. Correct level assignment was expressed as % hit rate. A combination of anthropometric and functional characteristics reflects future level assignment (Int vs. Nat). Players' success can be accurately predicted (hit rate=81% and 77% for Int and Nat respectively) by a DF that combines anthropometric and functional variables as measured at ∼15 years of age, percent body fat and speed being the most influential predictors of group stratification. Within a group of 15 year-olds with exceptional physical characteristics, future players' success can be predicted using a linear combination of anthropometric and functional variables, among which a lower percent body fat and higher speed over a 15m sprint provide the most important predictors of the highest career success. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Do Predictors of Career Success Differ between Swedish Women and Men? Data from the Swedish Longitudinal Occupational Survey of Health (SLOSH).

PubMed

Nyberg, Anna; Magnusson Hanson, Linda L; Leineweber, Constanze; Johansson, Gunn

2015-01-01

The aim of this prospective study was to explore predictors of objective career success among Swedish women and men, focussing on gender differences. Data were drawn from the 2008 and 2010 waves of the Swedish Longitudinal Occupational Survey of Health (SLOSH) with a total of 3670 female and 2773 male participants. Odds ratios and 95% confidence intervals for job promotion and an above-average salary increase between 2008 and 2010 were obtained through binary logistic regression analyses. Individual and organisational factors measured in 2008 were used as predictors in analyses stratified by sex. Mutual adjustment was performed for these variables, as well as for labour market sector and staff category at baseline. In both sexes, younger age predicted both job promotion and an above-average salary increase. Job promotion was also in both sexes predicted by being part of decision-making processes, having conflicts with superiors, and being eager to advance. Furthermore, promotion was predicted by, among men, being educated to post-graduate level and having an open coping strategy and, among women, working >60 hours/week. An above-average salary increase was predicted in both sexes by having a university education. Postgraduate education, having children living at home, and being very motivated to advance predicted an above-average salary increase among women, as did working 51-60 hours/week and being part of decision-making processes in men. Gender differences were seen in several predictors. In conclusion, the results support previous findings of gender differences in predictors of career success. A high level of education, motivation to advance, and procedural justice appear to be more important predictors of career success among women, while open coping was a more important predictor among men.

Do Predictors of Career Success Differ between Swedish Women and Men? Data from the Swedish Longitudinal Occupational Survey of Health (SLOSH)

PubMed Central

Nyberg, Anna; Johansson, Gunn

2015-01-01

The aim of this prospective study was to explore predictors of objective career success among Swedish women and men, focussing on gender differences. Data were drawn from the 2008 and 2010 waves of the Swedish Longitudinal Occupational Survey of Health (SLOSH) with a total of 3670 female and 2773 male participants. Odds ratios and 95% confidence intervals for job promotion and an above-average salary increase between 2008 and 2010 were obtained through binary logistic regression analyses. Individual and organisational factors measured in 2008 were used as predictors in analyses stratified by sex. Mutual adjustment was performed for these variables, as well as for labour market sector and staff category at baseline. In both sexes, younger age predicted both job promotion and an above-average salary increase. Job promotion was also in both sexes predicted by being part of decision-making processes, having conflicts with superiors, and being eager to advance. Furthermore, promotion was predicted by, among men, being educated to post-graduate level and having an open coping strategy and, among women, working >60 hours/week. An above-average salary increase was predicted in both sexes by having a university education. Postgraduate education, having children living at home, and being very motivated to advance predicted an above-average salary increase among women, as did working 51–60 hours/week and being part of decision-making processes in men. Gender differences were seen in several predictors. In conclusion, the results support previous findings of gender differences in predictors of career success. A high level of education, motivation to advance, and procedural justice appear to be more important predictors of career success among women, while open coping was a more important predictor among men. PMID:26501351

Evaluation of the ASVAB (Armed Services Vocational Aptitude Battery) 8/ 9/10 Clerical Composite for Predicting Training School Performance

DTIC Science & Technology

1983-10-01

specific predictor such as clerical speed or psychomotor skill , since the AR test would probably predict success equally well in many different areas...to specific occupational skills . Ř? When the aptitude area system was reconstituted in 1958, each composite contained only two tests, one measuring... literacy into each composite was that the composites were highly intercorrelated. The same aptitude composites developed for ACB-73 were also used

Filtering sensory information with XCSF: improving learning robustness and robot arm control performance.

PubMed

Kneissler, Jan; Stalph, Patrick O; Drugowitsch, Jan; Butz, Martin V

2014-01-01

It has been shown previously that the control of a robot arm can be efficiently learned using the XCSF learning classifier system, which is a nonlinear regression system based on evolutionary computation. So far, however, the predictive knowledge about how actual motor activity changes the state of the arm system has not been exploited. In this paper, we utilize the forward velocity kinematics knowledge of XCSF to alleviate the negative effect of noisy sensors for successful learning and control. We incorporate Kalman filtering for estimating successive arm positions, iteratively combining sensory readings with XCSF-based predictions of hand position changes over time. The filtered arm position is used to improve both trajectory planning and further learning of the forward velocity kinematics. We test the approach on a simulated kinematic robot arm model. The results show that the combination can improve learning and control performance significantly. However, it also shows that variance estimates of XCSF prediction may be underestimated, in which case self-delusional spiraling effects can hinder effective learning. Thus, we introduce a heuristic parameter, which can be motivated by theory, and which limits the influence of XCSF's predictions on its own further learning input. As a result, we obtain drastic improvements in noise tolerance, allowing the system to cope with more than 10 times higher noise levels.

The relationship between manuscript title structure and success: editorial decisions and citation performance for an ecological journal

PubMed Central

Fox, Charles W; Burns, C Sean

2015-01-01

A poorly chosen article title may make a paper difficult to discover or discourage readership when discovered, reducing an article's impact. Yet, it is unclear how the structure of a manuscript's title influences readership and impact. We used manuscript tracking data for all manuscripts submitted to the journal Functional Ecology from 2004 to 2013 and citation data for papers published in this journal from 1987 to 2011 to examine how title features changed and whether a manuscript's title structure was predictive of success during the manuscript review process and/or impact (citation) after publication. Titles of manuscripts submitted to Functional Ecology became marginally longer (after controlling for other variables), broader in focus (less frequent inclusion of genus and species names), and included more humor and subtitles over the period of the study. Papers with subtitles were less likely to be rejected by editors both pre- and post-peer review, although both effects were small and the presence of subtitles in published papers was not predictive of citations. Papers with specific names of study organisms in their titles fared poorly during editorial (but not peer) review and, if published, were less well cited than papers whose titles did not include specific names. Papers with intermediate length titles were more successful during editorial review, although the effect was small and title word count was not predictive of citations. No features of titles were predictive of reviewer willingness to review papers or the length of time a paper was in peer review. We conclude that titles have changed in structure over time, but features of title structure have only small or no relationship with success during editorial review and post-publication impact. The title feature that was most predictive of manuscript success: papers whose titles emphasize broader conceptual or comparative issues fare better both pre- and post-publication than do papers with organism-specific titles. PMID:26045949

The relationship between manuscript title structure and success: editorial decisions and citation performance for an ecological journal.

PubMed

Fox, Charles W; Burns, C Sean

2015-05-01

A poorly chosen article title may make a paper difficult to discover or discourage readership when discovered, reducing an article's impact. Yet, it is unclear how the structure of a manuscript's title influences readership and impact. We used manuscript tracking data for all manuscripts submitted to the journal Functional Ecology from 2004 to 2013 and citation data for papers published in this journal from 1987 to 2011 to examine how title features changed and whether a manuscript's title structure was predictive of success during the manuscript review process and/or impact (citation) after publication. Titles of manuscripts submitted to Functional Ecology became marginally longer (after controlling for other variables), broader in focus (less frequent inclusion of genus and species names), and included more humor and subtitles over the period of the study. Papers with subtitles were less likely to be rejected by editors both pre- and post-peer review, although both effects were small and the presence of subtitles in published papers was not predictive of citations. Papers with specific names of study organisms in their titles fared poorly during editorial (but not peer) review and, if published, were less well cited than papers whose titles did not include specific names. Papers with intermediate length titles were more successful during editorial review, although the effect was small and title word count was not predictive of citations. No features of titles were predictive of reviewer willingness to review papers or the length of time a paper was in peer review. We conclude that titles have changed in structure over time, but features of title structure have only small or no relationship with success during editorial review and post-publication impact. The title feature that was most predictive of manuscript success: papers whose titles emphasize broader conceptual or comparative issues fare better both pre- and post-publication than do papers with organism-specific titles.

Predicting human olfactory perception from chemical features of odor molecules.

PubMed

Keller, Andreas; Gerkin, Richard C; Guan, Yuanfang; Dhurandhar, Amit; Turu, Gabor; Szalai, Bence; Mainland, Joel D; Ihara, Yusuke; Yu, Chung Wen; Wolfinger, Russ; Vens, Celine; Schietgat, Leander; De Grave, Kurt; Norel, Raquel; Stolovitzky, Gustavo; Cecchi, Guillermo A; Vosshall, Leslie B; Meyer, Pablo

2017-02-24

It is still not possible to predict whether a given molecule will have a perceived odor or what olfactory percept it will produce. We therefore organized the crowd-sourced DREAM Olfaction Prediction Challenge. Using a large olfactory psychophysical data set, teams developed machine-learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models accurately predicted odor intensity and pleasantness and also successfully predicted 8 among 19 rated semantic descriptors ("garlic," "fish," "sweet," "fruit," "burnt," "spices," "flower," and "sour"). Regularized linear models performed nearly as well as random forest-based ones, with a predictive accuracy that closely approaches a key theoretical limit. These models help to predict the perceptual qualities of virtually any molecule with high accuracy and also reverse-engineer the smell of a molecule. Copyright © 2017, American Association for the Advancement of Science.

Size, sounds and sex: interactions between body size and harmonic convergence signals determine mating success in Aedes aegypti.

PubMed

Cator, Lauren J; Zanti, Zacharo

2016-12-01

Several new mosquito control strategies will involve the release of laboratory reared males which will be required to compete with wild males for mates. Currently, the determinants of male mating success remain unclear. The presence of convergence between male and female harmonic flight tone frequencies during a mating attempt have been found to increase male mating success in the yellow fever mosquito, Aedes aegypti. Size has also been implicated as a factor in male mating success. Here, we investigated the relationships among body size, harmonic convergence signalling, and mating success. We predicted that harmonic convergence would be an important determinant of mating success and that large individuals would be more likely to converge. We used diet to manipulate male and female body size and then measured acoustic interactions during mating attempts between pairs of different body sizes. Additionally, we used playback experiments to measure the direct effect of size on signalling performance. In live pair interactions, harmonic convergence was found to be a significant predictor of copula formation. However, we also found interactions between harmonic convergence behaviour and body size. The probability that a given male successfully formed a copula was a consequence of his size, the size of the female encountered, and whether or not they converged. While convergence appears to be predictive of mating success regardless of size, the positive effect of convergence was modulated by size combinations. In playbacks, adult body size did not affect the probability of harmonic convergence responses. Both body size and harmonic convergence signalling were found to be determinants of male mating success. Our results suggest that in addition to measuring convergence ability of mass release lines that the size distribution of released males may need to be adjusted to complement the size distribution of females. We also found that diet amount alone cannot be used to increase male mating success or convergence probability. A clearer understanding of convergence behaviours, their relationship to mating success, and factors influencing convergence ability would provide the groundwork for improving the mating performance of laboratory reared lines.

Validation of the close-to-delivery prediction model for vaginal birth after cesarean delivery in a Middle Eastern cohort.

PubMed

Abdel Aziz, Ahmed; Abd Rabbo, Amal; Sayed Ahmed, Waleed A; Khamees, Rasha E; Atwa, Khaled A

2016-07-01

To validate a prediction model for vaginal birth after cesarean (VBAC) that incorporates variables available at admission for delivery among Middle Eastern women. The present prospective cohort study enrolled women at 37weeks of pregnancy or more with cephalic presentation who were willing to attempt a trial of labor (TOL) after a single prior low transverse cesarean delivery at Al-Jahra Hospital, Kuwait, between June 2013 and June 2014. The predicted success rate of VBAC determined via the close-to-delivery prediction model of Grobman et al. was compared between participants whose TOL was and was not successful. Among 203 enrolled women, 140 (69.0%) had successful VBAC. The predicted VBAC success rate was higher among women with successful TOL (82.4%±13.1%) than among those with failed TOL (67.7%±18.3%; P<0.001). There was a high positive correlation between actual and predicted success rates. For deciles of predicted success rate increasing from >30%-40% to >90%-100%, the actual success rate was 20%, 30.7%, 38.5%, 59.1%, 71.4%, 76%, and 84.5%, respectively (r=0.98, P=0.013). The close-to-delivery prediction model was found to be applicable to Middle Eastern women and might predict VBAC success rates, thereby decreasing morbidities associated with failed TOL. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Effects of Academic Mindsets on College Students' Achievement and Retention

ERIC Educational Resources Information Center

Han, Cheon-woo; Farruggia, Susan P.; Moss, Thomas P.

2017-01-01

Noncognitive factors, such as academic self-efficacy, motivation, and sense of belonging, predict college students' academic performance and retention. It is unclear if varying profiles of academic mindset are differentially associated with student success. We examined first-year college students' academic mindsets (perceived academic…

Prediction of success in FAA air traffic control field training as a function of selection and screening test performance.

DOT National Transportation Integrated Search

1989-05-01

This study compared correlations between Office of Personnel Management (OPM) selection test scores for Air Traffic Control Specialists (ATCSs) and scores from the FAA Academy's second-stage screening program with measures of field training performan...

A theoretical/experimental program to develop active optical pollution sensors

NASA Technical Reports Server (NTRS)

Mills, F. S.; Blais, R. N.; Kindle, E. C.

1977-01-01

Light detection and ranging (LIDAR) technology was applied to the assessment of air quality, and its usefulness was evaluated by actual field tests. Necessary hardware was successfully constructed and operated in the field. Measurements of necessary physical parameters, such as SO2 absorption coefficients were successfully completed and theoretical predictions of differential absorption performance were reported. Plume modeling improvements were proposed. A full scale field test of equipment, data analysis and auxiliary data support was conducted in Maryland during September 1976.

Successful Application of Adaptive Emotion Regulation Skills Predicts the Subsequent Reduction of Depressive Symptom Severity but neither the Reduction of Anxiety nor the Reduction of General Distress during the Treatment of Major Depressive Disorder

PubMed Central

Wirtz, Carolin M.; Radkovsky, Anna; Ebert, David D.; Berking, Matthias

2014-01-01

Objective Deficits in general emotion regulation (ER) skills have been linked to symptoms of depression and are thus considered a promising target in the treatment of Major depressive disorder (MDD). However, at this point, the extent to which such skills are relevant for coping with depression and whether they should instead be considered a transdiagnostic factor remain unclear. Therefore, the present study aimed to investigate whether successful ER skills application is associated with changes in depressive symptom severity (DSS), anxiety symptom severity (ASS), and general distress severity (GDS) over the course of treatment for MDD. Methods Successful ER skills application, DSS, ASS, and GDS were assessed four times during the first three weeks of treatment in 175 inpatients who met the criteria for MDD. We computed Pearson correlations to test whether successful ER skills application and the three indicators of psychopathology are cross-sectionally associated. We then performed latent growth curve modelling to test whether changes in successful ER skills application are negatively associated with a reduction of DSS, ASS, or GDS. Finally, we utilized latent change score models to examine whether successful ER skills application predicts subsequent reduction of DSS, ASS, or GDS. Results Successful ER skills application was cross-sectionally associated with lower levels of DSS, ASS, and GDS at all points of assessment. An increase in successful skills application during treatment was associated with a decrease in DSS and GDS but not ASS. Finally, successful ER skills application predicted changes in subsequent DSS but neither changes in ASS nor changes in GDS. Conclusions Although general ER skills might be relevant for a broad range of psychopathological symptoms, they might be particularly important for the maintenance and treatment of depressive symptoms. PMID:25330159

Application of neural network in the study of combustion rate of natural gas/diesel dual fuel engine.

PubMed

Yan, Zhao-Da; Zhou, Chong-Guang; Su, Shi-Chuan; Liu, Zhen-Tao; Wang, Xi-Zhen

2003-01-01

In order to predict and improve the performance of natural gas/diesel dual fuel engine (DFE), a combustion rate model based on forward neural network was built to study the combustion process of the DFE. The effect of the operating parameters on combustion rate was also studied by means of this model. The study showed that the predicted results were good agreement with the experimental data. It was proved that the developed combustion rate model could be used to successfully predict and optimize the combustion process of dual fuel engine.

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

PubMed

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys.

Drug-target interaction prediction via class imbalance-aware ensemble learning.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2016-12-22

Multiple computational methods for predicting drug-target interactions have been developed to facilitate the drug discovery process. These methods use available data on known drug-target interactions to train classifiers with the purpose of predicting new undiscovered interactions. However, a key challenge regarding this data that has not yet been addressed by these methods, namely class imbalance, is potentially degrading the prediction performance. Class imbalance can be divided into two sub-problems. Firstly, the number of known interacting drug-target pairs is much smaller than that of non-interacting drug-target pairs. This imbalance ratio between interacting and non-interacting drug-target pairs is referred to as the between-class imbalance. Between-class imbalance degrades prediction performance due to the bias in prediction results towards the majority class (i.e. the non-interacting pairs), leading to more prediction errors in the minority class (i.e. the interacting pairs). Secondly, there are multiple types of drug-target interactions in the data with some types having relatively fewer members (or are less represented) than others. This variation in representation of the different interaction types leads to another kind of imbalance referred to as the within-class imbalance. In within-class imbalance, prediction results are biased towards the better represented interaction types, leading to more prediction errors in the less represented interaction types. We propose an ensemble learning method that incorporates techniques to address the issues of between-class imbalance and within-class imbalance. Experiments show that the proposed method improves results over 4 state-of-the-art methods. In addition, we simulated cases for new drugs and targets to see how our method would perform in predicting their interactions. New drugs and targets are those for which no prior interactions are known. Our method displayed satisfactory prediction performance and was able to predict many of the interactions successfully. Our proposed method has improved the prediction performance over the existing work, thus proving the importance of addressing problems pertaining to class imbalance in the data.

Performing a reaching task with one arm while adapting to a visuomotor rotation with the other can lead to complete transfer of motor learning across the arms

PubMed Central

Lei, Yuming; Binder, Jeffrey R.

2015-01-01

The extent to which motor learning is generalized across the limbs is typically very limited. Here, we investigated how two motor learning hypotheses could be used to enhance the extent of interlimb transfer. According to one hypothesis, we predicted that reinforcement of successful actions by providing binary error feedback regarding task success or failure, in addition to terminal error feedback, during initial training would increase the extent of interlimb transfer following visuomotor adaptation (experiment 1). According to the other hypothesis, we predicted that performing a reaching task repeatedly with one arm without providing performance feedback (which prevented learning the task with this arm), while concurrently adapting to a visuomotor rotation with the other arm, would increase the extent of transfer (experiment 2). Results indicate that providing binary error feedback, compared with continuous visual feedback that provided movement direction and amplitude information, had no influence on the extent of transfer. In contrast, repeatedly performing (but not learning) a specific task with one arm while visuomotor adaptation occurred with the other arm led to nearly complete transfer. This suggests that the absence of motor instances associated with specific effectors and task conditions is the major reason for limited interlimb transfer and that reinforcement of successful actions during initial training is not beneficial for interlimb transfer. These findings indicate crucial contributions of effector- and task-specific motor instances, which are thought to underlie (a type of) model-free learning, to optimal motor learning and interlimb transfer. PMID:25632082

Functional MRI in Awake Dogs Predicts Suitability for Assistance Work

PubMed Central

Berns, Gregory S.; Brooks, Andrew M.; Spivak, Mark; Levy, Kerinne

2017-01-01

The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17–21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs’ subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala. PMID:28266550

Functional MRI in Awake Dogs Predicts Suitability for Assistance Work

NASA Astrophysics Data System (ADS)

Berns, Gregory S.; Brooks, Andrew M.; Spivak, Mark; Levy, Kerinne

2017-03-01

The overall goal of this work was to measure the efficacy of fMRI for predicting whether a dog would be a successful service dog. The training and imaging were performed in 49 dogs entering service training at 17-21 months of age. 33 dogs completed service training and were matched with a person, while 10 were released for behavioral reasons (4 were selected as breeders and 2 were released for medical reasons.) After 2 months of training, fMRI responses were measured while each dog observed hand signals indicating either reward or no reward and given by both a familiar handler and a stranger. Using anatomically defined ROIs in the caudate, amygdala, and visual cortex, we developed a classifier based on the dogs’ subsequent training outcomes. The classifier had a positive predictive value of 94% and a negative predictive value of 67%. The area under the ROC curve was 0.91 (0.80 with 4-fold cross-validation, P = 0.01), indicating a significant predictive capability. The magnitude of response in the caudate was positively correlated with a successful outcome, while the response in the amygdala depended on the interaction with the visual cortex during the stranger condition and was negatively correlated with outcome (higher being associated with failure). These results suggest that, as indexed by caudate activity, successful service dogs generalize associations to hand signals regardless who gives them but without excessive arousal as measured in the amygdala.

Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting: An Application of Machine Learning Methods.

PubMed

Uyar, Asli; Bener, Ayse; Ciray, H Nadir

2015-08-01

Multiple embryo transfers in in vitro fertilization (IVF) treatment increase the number of successful pregnancies while elevating the risk of multiple gestations. IVF-associated multiple pregnancies exhibit significant financial, social, and medical implications. Clinicians need to decide the number of embryos to be transferred considering the tradeoff between successful outcomes and multiple pregnancies. To predict implantation outcome of individual embryos in an IVF cycle with the aim of providing decision support on the number of embryos transferred. Retrospective cohort study. Electronic health records of one of the largest IVF clinics in Turkey. The study data set included 2453 embryos transferred at day 2 or day 3 after intracytoplasmic sperm injection (ICSI). Each embryo was represented with 18 clinical features and a class label, +1 or -1, indicating positive and negative implantation outcomes, respectively. For each classifier tested, a model was developed using two-thirds of the data set, and prediction performance was evaluated on the remaining one-third of the samples using receiver operating characteristic (ROC) analysis. The training-testing procedure was repeated 10 times on randomly split (two-thirds to one-third) data. The relative predictive values of clinical input characteristics were assessed using information gain feature weighting and forward feature selection methods. The naïve Bayes model provided 80.4% accuracy, 63.7% sensitivity, and 17.6% false alarm rate in embryo-based implantation prediction. Multiple embryo implantations were predicted at a 63.8% sensitivity level. Predictions using the proposed model resulted in higher accuracy compared with expert judgment alone (on average, 75.7% and 60.1%, respectively). A machine learning-based decision support system would be useful in improving the success rates of IVF treatment. © The Author(s) 2014.

Heatpipe power system and heatpipe bimodal system design and development options

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Predicting Failure of Glyburide Therapy in Gestational Diabetes

PubMed Central

Harper, Lorie M.; Glover, Angelica V.; Biggio, Joseph R.; Tita, Alan

2016-01-01

Objective We sought to develop a prediction model to identify women with gestational diabetes (GDM) who require insulin to achieve glycemic control. Study Design Retrospective cohort of all singletons with GDM treated with glyburide 2007–2013. Glyburide failure was defined as reaching glyburide 20 mg/day and receiving insulin. Glyburide success was defined as any glyburide dose without insulin and >70% of visits with glycemic control. Multivariable logistic regression analysis was performed to create a prediction model. Results Of 360 women, 63 (17.5%) qualified as glyburide failure and 157 (43.6%) glyburide success. The final prediction model for glyburide failure included prior GDM, GDM diagnosis ≤26 weeks, 1-hour GCT ≥228 mg/dL, 3-hour GTT 1-hour value ≥221 mg/dL, ≥7 post-prandial blood sugars >120 mg/dL in the week glyburide started, and ≥1 blood sugar >200 mg/dL. The model accurately classified 81% of subjects. Conclusions Women with GDM who will require insulin can be identified at initiation of pharmacologic therapy. PMID:26796130

Predicting failure of glyburide therapy in gestational diabetes.

PubMed

Harper, L M; Glover, A V; Biggio, J R; Tita, A

2016-05-01

We sought to develop a prediction model to identify women with gestational diabetes (GDM) who require insulin to achieve glycemic control. Retrospective cohort of all singletons with GDM treated with glyburide from 2007 to 2013. Glyburide failure was defined as reaching glyburide 20 mg day(-1) and receiving insulin. Glyburide success was defined as any glyburide dose without insulin and >70% of visits with glycemic control. Multivariable logistic regression analysis was performed to create a prediction model. Of the 360 women, 63 (17.5%) qualified as glyburide failure and 157 (43.6%) as glyburide success. The final prediction model for glyburide failure included prior GDM, GDM diagnosis ⩽26 weeks, 1-h glucose challenge test ⩾228 mg dl(-1), 3-h glucose tolerance test 1-h value ⩾221 mg dl(-1), ⩾7 postprandial blood sugars >120 mg dl(-1) in the week glyburide started and ⩾1 blood sugar >200 mg dl(-1). The model accurately classified 81% of subjects. Women with GDM who will require insulin can be identified at the initiation of pharmacological therapy.

Combining the genetic algorithm and successive projection algorithm for the selection of feature wavelengths to evaluate exudative characteristics in frozen-thawed fish muscle.

PubMed

Cheng, Jun-Hu; Sun, Da-Wen; Pu, Hongbin

2016-04-15

The potential use of feature wavelengths for predicting drip loss in grass carp fish, as affected by being frozen at -20°C for 24 h and thawed at 4°C for 1, 2, 4, and 6 days, was investigated. Hyperspectral images of frozen-thawed fish were obtained and their corresponding spectra were extracted. Least-squares support vector machine and multiple linear regression (MLR) models were established using five key wavelengths, selected by combining a genetic algorithm and successive projections algorithm, and this showed satisfactory performance in drip loss prediction. The MLR model with a determination coefficient of prediction (R(2)P) of 0.9258, and lower root mean square error estimated by a prediction (RMSEP) of 1.12%, was applied to transfer each pixel of the image and generate the distribution maps of exudation changes. The results confirmed that it is feasible to identify the feature wavelengths using variable selection methods and chemometric analysis for developing on-line multispectral imaging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Theory-Based University Admissions Testing for a New Millennium

ERIC Educational Resources Information Center

Sternberg, Robert J.

2004-01-01

This article describes two projects based on Robert J. Sternberg's theory of successful intelligence and designed to provide theory-based testing for university admissions. The first, Rainbow Project, provided a supplementary test of analytical, practical, and creative skills to augment the SAT in predicting college performance. The Rainbow…

Updating The Navy’s Recruit Quality Matrix: An Analysis of Educational Credentials and the Success of First-Term Sailors

DTIC Science & Technology

2004-03-01

Allison , Logistic Regression: Using the SAS System (Cary, NC: SAS Institute, Inc, 2001), 57. 23 using the likelihood ratio that SAS generates...21, respectively. 33 Jesse M. Rothstein, College Performance Predictions and the SAT ( Berkely , CA: UC

Peer Ratings as Predictors of Success in Military Aviation.

ERIC Educational Resources Information Center

Wahlberg, James L.; And Others

Three experimental peer rating forms were developed for use in research in prediction of the aviation training performance criterion--completion/attrition--from the training program for Aviation Warrant Officer Candidates at the U.S. Army Helicopter School. This paper describes the construction of the ratings, the "Potential Aviator…

A Review of Predictive Factors of Student Success in and Satisfaction with Online Learning

ERIC Educational Resources Information Center

Kauffman, Heather

2015-01-01

Students perceive online courses differently than traditional courses. Negative perceptions can lead to unfavourable learning outcomes including decreased motivation and persistence. Throughout this review, a broad range of factors that affect performance and satisfaction within the online learning environment for adult learners will be examined…

Cognitive Styles in Admission Procedures for Assessing Candidates of Architecture

ERIC Educational Resources Information Center

Casakin, Hernan; Gigi, Ariela

2016-01-01

Cognitive style has a strong predictive power in academic and professional success. This study investigated the cognitive profile of candidates studying architecture. Specifically, it explored the relation between visual and verbal cognitive styles, and the performance of candidates in admission procedures. The cognitive styles of candidates who…

Cognitive Integrity Predicts Transitive Inference Performance Bias and Success

ERIC Educational Resources Information Center

Moses, Sandra N.; Villate, Christina; Binns, Malcolm A.; Davidson, Patrick S. R.; Ryan, Jennifer D.

2008-01-01

Transitive inference has traditionally been regarded as a relational proposition-based reasoning task, however, recent investigations question the validity of this assumption. Although some results support the use of a relational proposition-based approach, other studies find evidence for the use of associative learning. We examined whether…

Spatial variability in cost and success of revegetation in a Wyoming big sagebrush community.

PubMed

Boyd, Chad S; Davies, Kirk W

2012-09-01

The ecological integrity of the Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle and A. Young) alliance is being severely interrupted by post-fire invasion of non-native annual grasses. To curtail this invasion, successful post-fire revegetation of perennial grasses is required. Environmental factors impacting post-fire restoration success vary across space within the Wyoming big sagebrush alliance; however, most restorative management practices are applied uniformly. Our objectives were to define probability of revegetation success over space using relevant soil-related environmental factors, use this information to model cost of successful revegetation and compare the importance of vegetation competition and soil factors to revegetation success. We studied a burned Wyoming big sagebrush landscape in southeast Oregon that was reseeded with perennial grasses. We collected soil and vegetation data at plots spaced at 30 m intervals along a 1.5 km transect in the first two years post-burn. Plots were classified as successful (>5 seedlings/m(2)) or unsuccessful based on density of seeded species. Using logistic regression we found that abundance of competing vegetation correctly predicted revegetation success on 51 % of plots, and soil-related variables correctly predicted revegetation performance on 82.4 % of plots. Revegetation estimates varied from $167.06 to $43,033.94/ha across the 1.5 km transect based on probability of success, but were more homogenous at larger scales. Our experimental protocol provides managers with a technique to identify important environmental drivers of restoration success and this process will be of value for spatially allocating logistical and capital expenditures in a variable restoration environment.

Prediction of human adaptation and performance in underwater environments.

PubMed

Colodro Plaza, Joaquín; Garcés de los Fayos Ruiz, Enrique J; López García, Juan J; Colodro Conde, Lucía

2014-01-01

Environmental stressors require the professional diver to undergo a complex process of psychophysiological adaptation in order to overcome the demands of an extreme environment and carry out effective and efficient work under water. The influence of cognitive and personality traits in predicting underwater performance and adaptation has been a common concern for diving psychology, and definitive conclusions have not been reached. In this ex post facto study, psychological and academic data were analyzed from a large sample of personnel participating in scuba diving courses carried out in the Spanish Navy Diving Center. In order to verify the relevance of individual differences in adaptation to a hostile environment, we evaluated the predictive validity of general mental ability and personality traits with regression techniques. The data indicated the existence of psychological variables that can predict the performance ( R² = .30, p <.001) and adaptation ( R²(N) = .51, p <.001) of divers in underwater environment. These findings support the hypothesis that individual differences are related to the probability of successful adaptation and effective performance in professional diving. These results also verify that dispositional traits play a decisive role in diving training and are significant factors in divers' psychological fitness.

Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data.

PubMed

Yılmaz Isıkhan, Selen; Karabulut, Erdem; Alpar, Celal Reha

2016-01-01

Background/Aim . Evaluating the success of dose prediction based on genetic or clinical data has substantially advanced recently. The aim of this study is to predict various clinical dose values from DNA gene expression datasets using data mining techniques. Materials and Methods . Eleven real gene expression datasets containing dose values were included. First, important genes for dose prediction were selected using iterative sure independence screening. Then, the performances of regression trees (RTs), support vector regression (SVR), RT bagging, SVR bagging, and RT boosting were examined. Results . The results demonstrated that a regression-based feature selection method substantially reduced the number of irrelevant genes from raw datasets. Overall, the best prediction performance in nine of 11 datasets was achieved using SVR; the second most accurate performance was provided using a gradient-boosting machine (GBM). Conclusion . Analysis of various dose values based on microarray gene expression data identified common genes found in our study and the referenced studies. According to our findings, SVR and GBM can be good predictors of dose-gene datasets. Another result of the study was to identify the sample size of n = 25 as a cutoff point for RT bagging to outperform a single RT.

Ligand Binding Site Detection by Local Structure Alignment and Its Performance Complementarity

PubMed Central

Lee, Hui Sun; Im, Wonpil

2013-01-01

Accurate determination of potential ligand binding sites (BS) is a key step for protein function characterization and structure-based drug design. Despite promising results of template-based BS prediction methods using global structure alignment (GSA), there is a room to improve the performance by properly incorporating local structure alignment (LSA) because BS are local structures and often similar for proteins with dissimilar global folds. We present a template-based ligand BS prediction method using G-LoSA, our LSA tool. A large benchmark set validation shows that G-LoSA predicts drug-like ligands’ positions in single-chain protein targets more precisely than TM-align, a GSA-based method, while the overall success rate of TM-align is better. G-LoSA is particularly efficient for accurate detection of local structures conserved across proteins with diverse global topologies. Recognizing the performance complementarity of G-LoSA to TM-align and a non-template geometry-based method, fpocket, a robust consensus scoring method, CMCS-BSP (Complementary Methods and Consensus Scoring for ligand Binding Site Prediction), is developed and shows improvement on prediction accuracy. The G-LoSA source code is freely available at http://im.bioinformatics.ku.edu/GLoSA. PMID:23957286

Success and High Predictability of Intraorally Welded Titanium Bar in the Immediate Loading Implants

PubMed Central

Fogli, Vaniel; Camerini, Michele; Carinci, Francesco

2014-01-01

The implants failure may be caused by micromotion and stress exerted on implants during the phase of bone healing. This concept is especially true in case of implants placed in atrophic ridges. So the primary stabilization and fixation of implants are an important goal that can also allow immediate loading and oral rehabilitation on the same day of surgery. This goal may be achieved thanks to the technique of welding titanium bars on implant abutments. In fact, the procedure can be performed directly in the mouth eliminating possibility of errors or distortions due to impression. This paper describes a case report and the most recent data about long-term success and high predictability of intraorally welded titanium bar in immediate loading implants. PMID:24963419

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

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

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

DOE PAGES

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

2017-12-20

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Tracking children's mental states while solving algebra equations.

PubMed

Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M

2012-11-01

Behavioral and function magnetic resonance imagery (fMRI) data were combined to infer the mental states of students as they interacted with an intelligent tutoring system. Sixteen children interacted with a computer tutor for solving linear equations over a six-day period (days 0-5), with days 1 and 5 occurring in an fMRI scanner. Hidden Markov model algorithms combined a model of student behavior with multi-voxel imaging pattern data to predict the mental states of students. We separately assessed the algorithms' ability to predict which step in a problem-solving sequence was performed and whether the step was performed correctly. For day 1, the data patterns of other students were used to predict the mental states of a target student. These predictions were improved on day 5 by adding information about the target student's behavioral and imaging data from day 1. Successful tracking of mental states depended on using the combination of a behavioral model and multi-voxel pattern analysis, illustrating the effectiveness of an integrated approach to tracking the cognition of individuals in real time as they perform complex tasks. Copyright © 2011 Wiley Periodicals, Inc.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance.

PubMed

Astrand, Elaine

2018-06-01

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. 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, [Formula: see text]. 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. 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 using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for individuals with degraded WM capacity.

A continuous time-resolved measure decoded from EEG oscillatory activity predicts working memory task performance

NASA Astrophysics Data System (ADS)

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 using the continuous measure as neurofeedback opens up new possibilities to develop novel rehabilitation techniques for individuals with degraded WM capacity.

Perceived aggressiveness predicts fighting performance in mixed-martial-arts fighters.

PubMed

Trebicky, Vít; Havlícek, Jan; Roberts, S Craig; Little, Anthony C; Kleisner, Karel

2013-09-01

Accurate assessment of competitive ability is a critical component of contest behavior in animals, and it could be just as important in human competition, particularly in human ancestral populations. Here, we tested the role that facial perception plays in this assessment by investigating the association between both perceived aggressiveness and perceived fighting ability in fighters' faces and their actual fighting success. Perceived aggressiveness was positively associated with the proportion of fights won, after we controlled for the effect of weight, which also independently predicted perceived aggression. In contrast, perception of fighting ability was confounded by weight, and an association between perceived fighting ability and actual fighting success was restricted to heavyweight fighters. Shape regressions revealed that aggressive-looking faces are generally wider and have a broader chin, more prominent eyebrows, and a larger nose than less aggressive-looking faces. Our results indicate that perception of aggressiveness and fighting ability might cue different aspects of success in male-male physical confrontation.

Dynamic fMRI networks predict success in a behavioral weight loss program among older adults.

PubMed

Mokhtari, Fatemeh; Rejeski, W Jack; Zhu, Yingying; Wu, Guorong; Simpson, Sean L; Burdette, Jonathan H; Laurienti, Paul J

2018-06-01

More than one-third of adults in the United States are obese, with a higher prevalence among older adults. Obesity among older adults is a major cause of physical dysfunction, hypertension, diabetes, and coronary heart diseases. Many people who engage in lifestyle weight loss interventions fail to reach targeted goals for weight loss, and most will regain what was lost within 1-2 years following cessation of treatment. This variability in treatment efficacy suggests that there are important phenotypes predictive of success with intentional weight loss that could lead to tailored treatment regimen, an idea that is consistent with the concept of precision-based medicine. Although the identification of biochemical and metabolic phenotypes are one potential direction of research, neurobiological measures may prove useful as substantial behavioral change is necessary to achieve success in a lifestyle intervention. In the present study, we use dynamic brain networks from functional magnetic resonance imaging (fMRI) data to prospectively identify individuals most likely to succeed in a behavioral weight loss intervention. Brain imaging was performed in overweight or obese older adults (age: 65-79 years) who participated in an 18-month lifestyle weight loss intervention. Machine learning and functional brain networks were combined to produce multivariate prediction models. The prediction accuracy exceeded 95%, suggesting that there exists a consistent pattern of connectivity which correctly predicts success with weight loss at the individual level. Connectivity patterns that contributed to the prediction consisted of complex multivariate network components that substantially overlapped with known brain networks that are associated with behavior emergence, self-regulation, body awareness, and the sensory features of food. Future work on independent datasets and diverse populations is needed to corroborate our findings. Additionally, we believe that efforts can begin to examine whether these models have clinical utility in tailoring treatment. Copyright © 2018 Elsevier Inc. All rights reserved.

Independent predictors of retrograde failure in CTO-PCI after successful collateral channel crossing.

PubMed

Suzuki, Yoriyasu; Muto, Makoto; Yamane, Masahisa; Muramatsu, Toshiya; Okamura, Atsunori; Igarashi, Yasumi; Fujita, Tsutomu; Nakamura, Shigeru; Oida, Akitsugu; Tsuchikane, Etsuo

2017-07-01

To evaluate factors for predicting retrograde CTO-PCI failure after successful collateral channel crossing. Successful guidewire/catheter collateral channel crossing is important for the retrograde approach in percutaneous coronary intervention (PCI) for chronic total occlusion (CTO). A total of 5984 CTO-PCI procedures performed in 45 centers in Japan from 2009 to 2012 were studied. The retrograde approach was used in 1656 CTO-PCIs (27.7%). We investigated these retrograde procedures to evaluate factors for predicting retrograde CTO-PCI failure even after successful collateral channel crossing. Successful guidewire/catheter collateral crossing was achieved in 77.1% (n = 1,276) of 1656 retrograde CTO-PCI procedures. Retrograde procedural success after successful collateral crossing was achieved in 89.4% (n = 1,141). Univariate analysis showed that the predictors for retrograde CTO-PCI failure were in-stent occlusion (OR = 1.9829, 95%CI = 1.1783 - 3.3370 P = 0.0088), calcified lesions (OR = 1.9233, 95%CI = 1.2463 - 2.9679, P = 0.0027), and lesion tortuosity (OR = 1.5244, 95%CI = 1.0618 - 2.1883, P = 0.0216). On multivariate analysis, lesion calcification was an independent predictor of retrograde CTO-PCI failure after successful collateral channel crossing (OR = 1.3472, 95%CI = 1.0614 - 1.7169, P = 0.0141). The success rate of retrograde CTO-PCI following successful guidewire/catheter collateral channel crossing was high in this registry. Lesion calcification was an independent predictor of retrograde CTO-PCI failure after successful collateral channel crossing. Devices and techniques to overcome complex CTO lesion morphology, such as lesion calcification, are required to further improve the retrograde CTO-PCI success rate. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Academic and non-academic predictors of success on the Nottingham undergraduate medical course 1970-1995.

PubMed

James, D; Chilvers, C

2001-11-01

To identify academic and non-academic predictors of success of entrants to the Nottingham medical course over the first 25 completed years of the course's existence. SETTING, DESIGN AND MAIN OUTCOME MEASURES: Retrospective study of academic and non-academic characteristics of 2270 entrants between 1970 and 1990, and their subsequent success. Analyses were undertaken of two cohorts (entrants between 1970 and 1985 and entrants between 1986 and 1990). Overall, 148 of 2270 (6.5%) entrants left the course, with the highest proportion being from the first 6 years (10.7%). Of the 148 leavers, 58 (39.2%) did so after obtaining their BMedSci degree. Concerning non-academic factors, in the 1970-85 cohort, applicants from the later years and those not taking a year out were more successful. However, these two factors had no influence on outcome in 1986-90. In contrast, ethnicity and gender were highly significant predictors of success in obtaining honours at BMBS in 1986-90 but at no other exam nor in the earlier years. Older, mature or graduate entrants were more successful at obtaining a first-class degree at BMedSci for the whole 21 years. However, they were less likely to be successful at passing the BMBS. With regard to academic factors, overall, A grades at Ordinary level/General Certificate of Secondary Education (O-Level/GCSE) were inconsistent independent predictors of success. However, for 1986-90, high grades at O-Level/GCSE chemistry and biology were strong independent predictors of success at BMedSci and BMBS. Very few Advanced level (A-Level) criteria were independent predictors of success for 1970-85. In contrast, for 1986-90 entrants, achieving a high grade at A-Level chemistry predicted success at obtaining a first-class degree at BMedSci, and a high grade at A-Level biology predicted success at BMBS. Over the 21 years, the majority of entrants achieved significantly lower grades at A-Level than predicted. General Studies A-Level was a poor predictor of achievement. On balance our current GCSE A-grade requirements should remain. Biology should be added to Chemistry as a compulsory A-Level subject. If predicted A-Level grades are borderline then the lower estimate should be used. General Studies should continue not to be used in selection. Performance of more recent mature entrants at BMBS needs further study. The recent gender and ethnic biases in obtaining honours at BMBS is currently being examined. The motivation of applicants planning to take deferred entry should be carefully explored at interview.

Characteristics of Socially Successful Elementary School-Aged Children with Autism

PubMed Central

Locke, Jill; Williams, Justin; Shih, Wendy; Kasari, Connie

2016-01-01

Background The extant literature demonstrates that children with autism spectrum disorder (ASD) often have difficulty interacting and socially connecting with typically developing classmates. However, some children with ASD have social outcomes that are consistent with their typically developing counterparts. Little is known about this subgroup of children with ASD. This study examined the stable (unlikely to change) and malleable (changeable) characteristics of socially successful children with ASD. Methods This study used baseline data from three intervention studies performed in public schools in the Southwestern United States. A total of 148 elementary-aged children with ASD in 130 classrooms in 47 public schools participated. Measures of playground peer engagement and social network salience (inclusion in informal peer groups) were obtained. Results The results demonstrated that a number of malleable factors significantly predicted playground peer engagement (class size, autism symptom severity, peer connections) and social network salience (autism symptom severity, peer connections, received friendships). In addition, age was the only stable factor that significantly predicted social network salience. Interestingly, two malleable (i.e., peer connections and received friendships) and no stable factors (i.e., age, IQ, sex) predicted overall social success (e.g., high playground peer engagement and social network salience) in children with ASD. Conclusions School-based interventions should address malleable factors such as the number of peer connections and received friendships that predict the best social outcomes for children with ASD. PMID:27620949

Similar patterns of neural activity predict memory function during encoding and retrieval.

PubMed

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-01-01

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

Keep your eyes on the ball: smooth pursuit eye movements enhance prediction of visual motion.

PubMed

Spering, Miriam; Schütz, Alexander C; Braun, Doris I; Gegenfurtner, Karl R

2011-04-01

Success of motor behavior often depends on the ability to predict the path of moving objects. Here we asked whether tracking a visual object with smooth pursuit eye movements helps to predict its motion direction. We developed a paradigm, "eye soccer," in which observers had to either track or fixate a visual target (ball) and judge whether it would have hit or missed a stationary vertical line segment (goal). Ball and goal were presented briefly for 100-500 ms and disappeared from the screen together before the perceptual judgment was prompted. In pursuit conditions, the ball moved towards the goal; in fixation conditions, the goal moved towards the stationary ball, resulting in similar retinal stimulation during pursuit and fixation. We also tested the condition in which the goal was fixated and the ball moved. Motion direction prediction was significantly better in pursuit than in fixation trials, regardless of whether ball or goal served as fixation target. In both fixation and pursuit trials, prediction performance was better when eye movements were accurate. Performance also increased with shorter ball-goal distance and longer presentation duration. A longer trajectory did not affect performance. During pursuit, an efference copy signal might provide additional motion information, leading to the advantage in motion prediction.

Multivariate Predictors of Music Perception and Appraisal by Adult Cochlear Implant Users

PubMed Central

Gfeller, Kate; Oleson, Jacob; Knutson, John F.; Breheny, Patrick; Driscoll, Virginia; Olszewski, Carol

2009-01-01

The research examined whether performance by adult cochlear implant recipients on a variety of recognition and appraisal tests derived from real-world music could be predicted from technological, demographic, and life experience variables, as well as speech recognition scores. A representative sample of 209 adults implanted between 1985 and 2006 participated. Using multiple linear regression models and generalized linear mixed models, sets of optimal predictor variables were selected that effectively predicted performance on a test battery that assessed different aspects of music listening. These analyses established the importance of distinguishing between the accuracy of music perception and the appraisal of musical stimuli when using music listening as an index of implant success. Importantly, neither device type nor processing strategy predicted music perception or music appraisal. Speech recognition performance was not a strong predictor of music perception, and primarily predicted music perception when the test stimuli included lyrics. Additionally, limitations in the utility of speech perception in predicting musical perception and appraisal underscore the utility of music perception as an alternative outcome measure for evaluating implant outcomes. Music listening background, residual hearing (i.e., hearing aid use), cognitive factors, and some demographic factors predicted several indices of perceptual accuracy or appraisal of music. PMID:18669126

Body size, performance and fitness in galapagos marine iguanas.

PubMed

Wikelski, Martin; Romero, L Michael

2003-07-01

Complex organismal traits such as body size are influenced by innumerable selective pressures, making the prediction of evolutionary trajectories for those traits difficult. A potentially powerful way to predict fitness in natural systems is to study the composite response of individuals in terms of performance measures, such as foraging or reproductive performance. Once key performance measures are identified in this top-down approach, we can determine the underlying physiological mechanisms and gain predictive power over long-term evolutionary processes. Here we use marine iguanas as a model system where body size differs by more than one order of magnitude between island populations. We identified foraging efficiency as the main performance measure that constrains body size. Mechanistically, foraging performance is determined by food pasture height and the thermal environment, influencing intake and digestion. Stress hormones may be a flexible way of influencing an individual's response to low-food situations that may be caused by high population density, famines, or anthropogenic disturbances like oil spills. Reproductive performance, on the other hand, increases with body size and is mediated by higher survival of larger hatchlings from larger females and increased mating success of larger males. Reproductive performance of males may be adjusted via plastic hormonal feedback mechanisms that allow individuals to assess their social rank annually within the current population size structure. When integrated, these data suggest that reproductive performance favors increased body size (influenced by reproductive hormones), with an overall limit imposed by foraging performance (influenced by stress hormones). Based on our mechanistic understanding of individual performances we predicted an evolutionary increase in maximum body size caused by global warming trends. We support this prediction using specimens collected during 1905. We also show in a common-garden experiment that body size may have a genetic component in iguanids. This 'performance paradigm' allows predictions about adaptive evolution in natural populations.

Design and analysis of a model predictive controller for active queue management.

PubMed

Wang, Ping; Chen, Hong; Yang, Xiaoping; Ma, Yan

2012-01-01

Model predictive (MP) control as a novel active queue management (AQM) algorithm in dynamic computer networks is proposed. According to the predicted future queue length in the data buffer, early packets at the router are dropped reasonably by the MPAQM controller so that the queue length reaches the desired value with minimal tracking error. The drop probability is obtained by optimizing the network performance. Further, randomized algorithms are applied to analyze the robustness of MPAQM successfully, and also to provide the stability domain of systems with uncertain network parameters. The performances of MPAQM are evaluated through a series of simulations in NS2. The simulation results show that the MPAQM algorithm outperforms RED, PI, and REM algorithms in terms of stability, disturbance rejection, and robustness. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Biorelevant in vitro performance testing of orally administered dosage forms-workshop report.

PubMed

Reppas, Christos; Friedel, Horst-Dieter; Barker, Amy R; Buhse, Lucinda F; Cecil, Todd L; Keitel, Susanne; Kraemer, Johannes; Morris, J Michael; Shah, Vinod P; Stickelmeyer, Mary P; Yomota, Chikako; Brown, Cynthia K

2014-07-01

Biorelevant in vitro performance testing of orally administered dosage forms has become an important tool for the assessment of drug product in vivo behavior. An in vitro performance test which mimics the intraluminal performance of an oral dosage form is termed biorelevant. Biorelevant tests have been utilized to decrease the number of in vivo studies required during the drug development process and to mitigate the risk related to in vivo bioequivalence studies. This report reviews the ability of current in vitro performance tests to predict in vivo performance and generate successful in vitro and in vivo correlations for oral dosage forms. It also summarizes efforts to improve the predictability of biorelevant tests. The report is based on the presentations at the 2013 workshop, Biorelevant In Vitro Performance Testing of Orally Administered Dosage Forms, in Washington, DC, sponsored by the FIP Dissolution/Drug Release Focus Group in partnership with the American Association of Pharmaceutical Scientists (AAPS) and a symposium at the AAPS 2012 Annual meeting on the same topic.

Confident failures: Lapses of working memory reveal a metacognitive blind spot.

PubMed

Adam, Kirsten C S; Vogel, Edward K

2017-07-01

Working memory performance fluctuates dramatically from trial to trial. On many trials, performance is no better than chance. Here, we assessed participants' awareness of working memory failures. We used a whole-report visual working memory task to quantify both trial-by-trial performance and trial-by-trial subjective ratings of inattention to the task. In Experiment 1 (N = 41), participants were probed for task-unrelated thoughts immediately following 20% of trials. In Experiment 2 (N = 30), participants gave a rating of their attentional state following 25% of trials. Finally, in Experiments 3a (N = 44) and 3b (N = 34), participants reported confidence of every response using a simple mouse-click judgment. Attention-state ratings and off-task thoughts predicted the number of items correctly identified on each trial, replicating previous findings that subjective measures of attention state predict working memory performance. However, participants correctly identified failures on only around 28% of failure trials. Across experiments, participants' metacognitive judgments reliably predicted variation in working memory performance but consistently and severely underestimated the extent of failures. Further, individual differences in metacognitive accuracy correlated with overall working memory performance, suggesting that metacognitive monitoring may be key to working memory success.

Genetic influence on athletic performance.

PubMed

Guth, Lisa M; Roth, Stephen M

2013-12-01

To summarize the existing literature on the genetics of athletic performance, with particular consideration for the relevance to young athletes. Two gene variants, ACE I/D and ACTN3 R577X, have been consistently associated with endurance (ACE I/I) and power-related (ACTN3 R/R) performance, though neither can be considered predictive. The role of genetic variation in injury risk and outcomes is more sparsely studied, but genetic testing for injury susceptibility could be beneficial in protecting young athletes from serious injury. Little information on the association of genetic variation with athletic performance in young athletes is available; however, genetic testing is becoming more popular as a means of talent identification. Despite this increase in the use of such testing, evidence is lacking for the usefulness of genetic testing over traditional talent selection techniques in predicting athletic ability, and careful consideration should be given to the ethical issues surrounding such testing in children. A favorable genetic profile, when combined with an optimal training environment, is important for elite athletic performance; however, few genes are consistently associated with elite athletic performance, and none are linked strongly enough to warrant their use in predicting athletic success.

Modeling the Insertion Mechanics of Flexible Neural Probes Coated with Sacrificial Polymers for Optimizing Probe Design

PubMed Central

Singh, Sagar; Lo, Meng-Chen; Damodaran, Vinod B.; Kaplan, Hilton M.; Kohn, Joachim; Zahn, Jeffrey D.; Shreiber, David I.

2016-01-01

Single-unit recording neural probes have significant advantages towards improving signal-to-noise ratio and specificity for signal acquisition in brain-to-computer interface devices. Long-term effectiveness is unfortunately limited by the chronic injury response, which has been linked to the mechanical mismatch between rigid probes and compliant brain tissue. Small, flexible microelectrodes may overcome this limitation, but insertion of these probes without buckling requires supporting elements such as a stiff coating with a biodegradable polymer. For these coated probes, there is a design trade-off between the potential for successful insertion into brain tissue and the degree of trauma generated by the insertion. The objective of this study was to develop and validate a finite element model (FEM) to simulate insertion of coated neural probes of varying dimensions and material properties into brain tissue. Simulations were performed to predict the buckling and insertion forces during insertion of coated probes into a tissue phantom with material properties of brain. The simulations were validated with parallel experimental studies where probes were inserted into agarose tissue phantom, ex vivo chick embryonic brain tissue, and ex vivo rat brain tissue. Experiments were performed with uncoated copper wire and both uncoated and coated SU-8 photoresist and Parylene C probes. Model predictions were found to strongly agree with experimental results (<10% error). The ratio of the predicted buckling force-to-predicted insertion force, where a value greater than one would ideally be expected to result in successful insertion, was plotted against the actual success rate from experiments. A sigmoidal relationship was observed, with a ratio of 1.35 corresponding to equal probability of insertion and failure, and a ratio of 3.5 corresponding to a 100% success rate. This ratio was dubbed the “safety factor”, as it indicated the degree to which the coating should be over-designed to ensure successful insertion. Probability color maps were generated to visually compare the influence of design parameters. Statistical metrics derived from the color maps and multi-variable regression analysis confirmed that coating thickness and probe length were the most important features in influencing insertion potential. The model also revealed the effects of manufacturing flaws on insertion potential. PMID:26959021

New and Accurate Predictive Model for the Efficacy of Extracorporeal Shock Wave Therapy in Managing Patients With Chronic Plantar Fasciitis.

PubMed

Yin, Mengchen; Chen, Ni; Huang, Quan; Marla, Anastasia Sulindro; Ma, Junming; Ye, Jie; Mo, Wen

2017-12-01

To identify factors for the outcome of a minimum clinically successful therapy and to establish a predictive model of extracorporeal shock wave therapy (ESWT) in managing patients with chronic plantar fasciitis. Randomized, controlled, prospective study. Outpatient of local medical center settings. Patients treated for symptomatic chronic plantar fasciitis between 2014 and 2016 (N=278). ESWT was performed by the principal authors to treat chronic plantar fasciitis. ESWT was administered in 3 sessions, with an interval of 2 weeks (±4d). In the low-, moderate-, and high-intensity groups, 2400 impulses total of ESWT with an energy flux density of 0.2, 0.4, and 0.6mJ/mm 2 , respectively (a rate of 8 impulses per second), were applied. The independent variables were patient age, sex, body mass index, affected side, duration of symptoms, Roles and Maudsley score, visual analog scale (VAS) score when taking first steps in the morning, edema, bone spurs, and intensity grade of ESWT. A minimal reduction of 50% in the VAS score was considered as minimum clinically successful therapy. The correlations between the achievement of minimum clinically successful therapy and independent variables were analyzed. The statistically significant factors identified were further analyzed by multivariate logistic regression, and the predictive model was established. The success rate of ESWT was 66.9%. Univariate analysis found that VAS score when taking first steps in the morning, edema, and the presence of heel spur in radiograph significantly affected the outcome of the treatment. Logistic regression drew the equation: minimum clinically successful therapy=(1+e [.011+42.807×heel spur+.109×edema+5.395×VAS score] ) -1 .The sensitivity of the predictive factors was 96.77%, 87.63%, and 86.02%, respectively. The specificity of the predictive factors was 45.65%, 42.39%, and 85.87%, respectively. The area under the curve of the predictive factors was .751, .650, and .859, respectively. The Youden index was .4243, .3003, and .7189, respectively. The Hosmer-Lemeshow test showed a good fitting of the predictive model, with an overall accuracy of 89.6%. This study establishes a new and accurate predictive model for the efficacy of ESWT in managing patients with chronic plantar fasciitis. The use of these parameters, in the form of a predictive model for ESWT efficacy, has the potential to improve decision-making in the application of ESWT. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Optimization of Biomathematical Model Predictions for Cognitive Performance Impairment in Individuals: Accounting for Unknown Traits and Uncertain States in Homeostatic and Circadian Processes

PubMed Central

Van Dongen, Hans P. A.; Mott, Christopher G.; Huang, Jen-Kuang; Mollicone, Daniel J.; McKenzie, Frederic D.; Dinges, David F.

2007-01-01

Current biomathematical models of fatigue and performance do not accurately predict cognitive performance for individuals with a priori unknown degrees of trait vulnerability to sleep loss, do not predict performance reliably when initial conditions are uncertain, and do not yield statistically valid estimates of prediction accuracy. These limitations diminish their usefulness for predicting the performance of individuals in operational environments. To overcome these 3 limitations, a novel modeling approach was developed, based on the expansion of a statistical technique called Bayesian forecasting. The expanded Bayesian forecasting procedure was implemented in the two-process model of sleep regulation, which has been used to predict performance on the basis of the combination of a sleep homeostatic process and a circadian process. Employing the two-process model with the Bayesian forecasting procedure to predict performance for individual subjects in the face of unknown traits and uncertain states entailed subject-specific optimization of 3 trait parameters (homeostatic build-up rate, circadian amplitude, and basal performance level) and 2 initial state parameters (initial homeostatic state and circadian phase angle). Prior information about the distribution of the trait parameters in the population at large was extracted from psychomotor vigilance test (PVT) performance measurements in 10 subjects who had participated in a laboratory experiment with 88 h of total sleep deprivation. The PVT performance data of 3 additional subjects in this experiment were set aside beforehand for use in prospective computer simulations. The simulations involved updating the subject-specific model parameters every time the next performance measurement became available, and then predicting performance 24 h ahead. Comparison of the predictions to the subjects' actual data revealed that as more data became available for the individuals at hand, the performance predictions became increasingly more accurate and had progressively smaller 95% confidence intervals, as the model parameters converged efficiently to those that best characterized each individual. Even when more challenging simulations were run (mimicking a change in the initial homeostatic state; simulating the data to be sparse), the predictions were still considerably more accurate than would have been achieved by the two-process model alone. Although the work described here is still limited to periods of consolidated wakefulness with stable circadian rhythms, the results obtained thus far indicate that the Bayesian forecasting procedure can successfully overcome some of the major outstanding challenges for biomathematical prediction of cognitive performance in operational settings. Citation: Van Dongen HPA; Mott CG; Huang JK; Mollicone DJ; McKenzie FD; Dinges DF. Optimization of biomathematical model predictions for cognitive performance impairment in individuals: accounting for unknown traits and uncertain states in homeostatic and circadian processes. SLEEP 2007;30(9):1129-1143. PMID:17910385

Reward contingencies and the recalibration of task monitoring and reward systems: a high-density electrical mapping study.

PubMed

Morie, K P; De Sanctis, P; Foxe, J J

2014-07-25

Task execution almost always occurs in the context of reward-seeking or punishment-avoiding behavior. As such, ongoing task-monitoring systems are influenced by reward anticipation systems. In turn, when a task has been executed either successfully or unsuccessfully, future iterations of that task will be re-titrated on the basis of the task outcome. Here, we examined the neural underpinnings of the task-monitoring and reward-evaluation systems to better understand how they govern reward-seeking behavior. Twenty-three healthy adult participants performed a task where they accrued points that equated to real world value (gift cards) by responding as rapidly as possible within an allotted timeframe, while success rate was titrated online by changing the duration of the timeframe dependent on participant performance. Informative cues initiated each trial, indicating the probability of potential reward or loss (four levels from very low to very high). We manipulated feedback by first informing participants of task success/failure, after which a second feedback signal indicated actual magnitude of reward/loss. High-density electroencephalography (EEG) recordings allowed for examination of event-related potentials (ERPs) to the informative cues and in turn, to both feedback signals. Distinct ERP components associated with reward cues, task-preparatory and task-monitoring processes, and reward feedback processes were identified. Unsurprisingly, participants displayed increased ERP amplitudes associated with task-preparatory processes following cues that predicted higher chances of reward. They also rapidly updated reward and loss prediction information dependent on task performance after the first feedback signal. Finally, upon reward receipt, initial reward probability was no longer taken into account. Rather, ERP measures suggested that only the magnitude of actual reward or loss was now processed. Reward and task-monitoring processes are clearly dissociable, but interact across very fast timescales to update reward predictions as information about task success or failure is accrued. Careful delineation of these processes will be useful in future investigations in clinical groups where such processes are suspected of having gone awry. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Reward Contingencies and the Recalibration of Task Monitoring and Reward Systems: A high-density electrical mapping study

PubMed Central

Morie, Kristen P.; De Sanctis, Pierfilippo; Foxe, John J.

2014-01-01

Task execution almost always occurs in the context of reward-seeking or punishment-avoiding behavior. As such, ongoing task monitoring systems are influenced by reward anticipation systems. In turn, when a task has been executed either successfully or unsuccessfully, future iterations of that task will be re-titrated on the basis of the task outcome. Here, we examined the neural underpinnings of the task-monitoring and reward-evaluation systems to better understand how they govern reward seeking behavior. Twenty-three healthy adult participants performed a task where they accrued points that equated to real world value (gift cards) by responding as rapidly as possible within an allotted timeframe, while success rate was titrated online by changing the duration of the timeframe dependent on participant performance. Informative cues initiated each trial, indicating the probability of potential reward or loss (four levels from very low to very high). We manipulated feedback by first informing participants of task success/failure, after which a second feedback signal indicated actual magnitude of reward/loss. High-density EEG recordings allowed for examination of event-related potentials (ERPs) to the informative cues and in turn, to both feedback signals. Distinct ERP components associated with reward cues, task preparatory and task monitoring processes, and reward feedback processes were identified. Unsurprisingly, participants displayed increased ERP amplitudes associated with task preparatory processes following cues that predicted higher chances of reward. They also rapidly updated reward and loss prediction information dependent on task performance after the first feedback signal. Finally, upon reward receipt, initial reward probability was no longer taken into account. Rather, ERP measures suggested that only the magnitude of actual reward or loss was now processed. Reward and task monitoring processes are clearly dissociable, but interact across very fast timescales to update reward predictions as information about task success or failure is accrued. Careful delineation of these processes will be useful in future investigations in clinical groups where such processes are suspected of having gone awry. PMID:24836852

Prediction of rat protein subcellular localization with pseudo amino acid composition based on multiple sequential features.

PubMed

Shi, Ruijia; Xu, Cunshuan

2011-06-01

The study of rat proteins is an indispensable task in experimental medicine and drug development. The function of a rat protein is closely related to its subcellular location. Based on the above concept, we construct the benchmark rat proteins dataset and develop a combined approach for predicting the subcellular localization of rat proteins. From protein primary sequence, the multiple sequential features are obtained by using of discrete Fourier analysis, position conservation scoring function and increment of diversity, and these sequential features are selected as input parameters of the support vector machine. By the jackknife test, the overall success rate of prediction is 95.6% on the rat proteins dataset. Our method are performed on the apoptosis proteins dataset and the Gram-negative bacterial proteins dataset with the jackknife test, the overall success rates are 89.9% and 96.4%, respectively. The above results indicate that our proposed method is quite promising and may play a complementary role to the existing predictors in this area.

Migration phenology and breeding success are predicted by methylation of a photoperiodic gene in the barn swallow

PubMed Central

Saino, Nicola; Ambrosini, Roberto; Albetti, Benedetta; Caprioli, Manuela; De Giorgio, Barbara; Gatti, Emanuele; Liechti, Felix; Parolini, Marco; Romano, Andrea; Romano, Maria; Scandolara, Chiara; Gianfranceschi, Luca; Bollati, Valentina; Rubolini, Diego

2017-01-01

Individuals often considerably differ in the timing of their life-cycle events, with major consequences for individual fitness, and, ultimately, for population dynamics. Phenological variation can arise from genetic effects but also from epigenetic modifications in DNA expression and translation. Here, we tested if CpG methylation at the poly-Q and 5′-UTR loci of the photoperiodic Clock gene predicted migration and breeding phenology of long-distance migratory barn swallows (Hirundo rustica) that were tracked year-round using light-level geolocators. Increasing methylation at Clock poly-Q was associated with earlier spring departure from the African wintering area, arrival date at the European breeding site, and breeding date. Higher methylation levels also predicted increased breeding success. Thus, we showed for the first time in any species that CpG methylation at a candidate gene may affect phenology and breeding performance. Methylation at Clock may be a candidate mechanism mediating phenological responses of migratory birds to ongoing climate change. PMID:28361883

Migration phenology and breeding success are predicted by methylation of a photoperiodic gene in the barn swallow.

PubMed

Saino, Nicola; Ambrosini, Roberto; Albetti, Benedetta; Caprioli, Manuela; De Giorgio, Barbara; Gatti, Emanuele; Liechti, Felix; Parolini, Marco; Romano, Andrea; Romano, Maria; Scandolara, Chiara; Gianfranceschi, Luca; Bollati, Valentina; Rubolini, Diego

2017-03-31

Individuals often considerably differ in the timing of their life-cycle events, with major consequences for individual fitness, and, ultimately, for population dynamics. Phenological variation can arise from genetic effects but also from epigenetic modifications in DNA expression and translation. Here, we tested if CpG methylation at the poly-Q and 5'-UTR loci of the photoperiodic Clock gene predicted migration and breeding phenology of long-distance migratory barn swallows (Hirundo rustica) that were tracked year-round using light-level geolocators. Increasing methylation at Clock poly-Q was associated with earlier spring departure from the African wintering area, arrival date at the European breeding site, and breeding date. Higher methylation levels also predicted increased breeding success. Thus, we showed for the first time in any species that CpG methylation at a candidate gene may affect phenology and breeding performance. Methylation at Clock may be a candidate mechanism mediating phenological responses of migratory birds to ongoing climate change.

Does the MCAT predict medical school and PGY-1 performance?

PubMed

Saguil, Aaron; Dong, Ting; Gingerich, Robert J; Swygert, Kimberly; LaRochelle, Jeffrey S; Artino, Anthony R; Cruess, David F; Durning, Steven J

2015-04-01

The Medical College Admissions Test (MCAT) is a high-stakes test required for entry to most U. S. medical schools; admissions committees use this test to predict future accomplishment. Although there is evidence that the MCAT predicts success on multiple choice-based assessments, there is little information on whether the MCAT predicts clinical-based assessments of undergraduate and graduate medical education performance. This study looked at associations between the MCAT and medical school grade point average (GPA), Medical Licensing Examination (USMLE) scores, observed patient care encounters, and residency performance assessments. This study used data collected as part of the Long-Term Career Outcome Study to determine associations between MCAT scores, USMLE Step 1, Step 2 clinical knowledge and clinical skill, and Step 3 scores, Objective Structured Clinical Examination performance, medical school GPA, and PGY-1 program director (PD) assessment of physician performance for students graduating 2010 and 2011. MCAT data were available for all students, and the PGY PD evaluation response rate was 86.2% (N = 340). All permutations of MCAT scores (first, last, highest, average) were weakly associated with GPA, Step 2 clinical knowledge scores, and Step 3 scores. MCAT scores were weakly to moderately associated with Step 1 scores. MCAT scores were not significantly associated with Step 2 clinical skills Integrated Clinical Encounter and Communication and Interpersonal Skills subscores, Objective Structured Clinical Examination performance or PGY-1 PD evaluations. MCAT scores were weakly to moderately associated with assessments that rely on multiple choice testing. The association is somewhat stronger for assessments occurring earlier in medical school, such as USMLE Step 1. The MCAT was not able to predict assessments relying on direct clinical observation, nor was it able to predict PD assessment of PGY-1 performance. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Metamemory prediction accuracy for simple prospective and retrospective memory tasks in 5-year-old children.

PubMed

Kvavilashvili, Lia; Ford, Ruth M

2014-11-01

It is well documented that young children greatly overestimate their performance on tests of retrospective memory (RM), but the current investigation is the first to examine children's prediction accuracy for prospective memory (PM). Three studies were conducted, each testing a different group of 5-year-olds. In Study 1 (N=46), participants were asked to predict their success in a simple event-based PM task (remembering to convey a message to a toy mole if they encountered a particular picture during a picture-naming activity). Before naming the pictures, children listened to either a reminder story or a neutral story. Results showed that children were highly accurate in their PM predictions (78% accuracy) and that the reminder story appeared to benefit PM only in children who predicted they would remember the PM response. In Study 2 (N=80), children showed high PM prediction accuracy (69%) regardless of whether the cue was specific or general and despite typical overoptimism regarding their performance on a 10-item RM task using item-by-item prediction. Study 3 (N=35) showed that children were prone to overestimate RM even when asked about their ability to recall a single item-the mole's unusual name. In light of these findings, we consider possible reasons for children's impressive PM prediction accuracy, including the potential involvement of future thinking in performance predictions and PM. Copyright © 2014 Elsevier Inc. All rights reserved.

Brief report: a cost analysis of neuraxial anesthesia to facilitate external cephalic version for breech fetal presentation.

PubMed

Carvalho, Brendan; Tan, Jonathan M; Macario, Alex; El-Sayed, Yasser Y; Sultan, Pervez

2013-07-01

In this study, we sought to determine whether neuraxial anesthesia to facilitate external cephalic version (ECV) increased delivery costs for breech fetal presentation. Using a computer cost model, which considers possible outcomes and probability uncertainties at the same time, we estimated total expected delivery costs for breech presentation managed by a trial of ECV with and without neuraxial anesthesia. From published studies, the average probability of successful ECV with neuraxial anesthesia was 60% (with individual studies ranging from 44% to 87%) compared with 38% (with individual studies ranging from 31% to 58%) without neuraxial anesthesia. The mean expected total delivery costs, including the cost of attempting/performing ECV with anesthesia, equaled $8931 (2.5th-97.5th percentile prediction interval $8541-$9252). The cost was $9207 (2.5th-97.5th percentile prediction interval $8896-$9419) if ECV was attempted/performed without anesthesia. The expected mean incremental difference between the total cost of delivery that includes ECV with anesthesia and ECV without anesthesia was $-276 (2.5th-97.5th percentile prediction interval $-720 to $112). The total cost of delivery in women with breech presentation may be decreased (up to $720) or increased (up to $112) if ECV is attempted/performed with neuraxial anesthesia compared with ECV without neuraxial anesthesia. Increased ECV success with neuraxial anesthesia and the subsequent reduction in breech cesarean delivery rate offset the costs of providing anesthesia to facilitate ECV.

Advanced non-contrasted computed tomography post-processing by CT-Calculometry (CT-CM) outperforms established predictors for the outcome of shock wave lithotripsy.

PubMed

Langenauer, J; Betschart, P; Hechelhammer, L; Güsewell, S; Schmid, H P; Engeler, D S; Abt, D; Zumstein, V

2018-05-29

To evaluate the predictive value of advanced non-contrasted computed tomography (NCCT) post-processing using novel CT-calculometry (CT-CM) parameters compared to established predictors of success of shock wave lithotripsy (SWL) for urinary calculi. NCCT post-processing was retrospectively performed in 312 patients suffering from upper tract urinary calculi who were treated by SWL. Established predictors such as skin to stone distance, body mass index, stone diameter or mean stone attenuation values were assessed. Precise stone size and shape metrics, 3-D greyscale measurements and homogeneity parameters such as skewness and kurtosis, were analysed using CT-CM. Predictive values for SWL outcome were analysed using logistic regression and receiver operating characteristics (ROC) statistics. Overall success rate (stone disintegration and no re-intervention needed) of SWL was 59% (184 patients). CT-CM metrics mainly outperformed established predictors. According to ROC analyses, stone volume and surface area performed better than established stone diameter, mean 3D attenuation value was a stronger predictor than established mean attenuation value, and parameters skewness and kurtosis performed better than recently emerged variation coefficient of stone density. Moreover, prediction of SWL outcome with 80% probability to be correct would be possible in a clearly higher number of patients (up to fivefold) using CT-CM-derived parameters. Advanced NCCT post-processing by CT-CM provides novel parameters that seem to outperform established predictors of SWL response. Implementation of these parameters into clinical routine might reduce SWL failure rates.

AFOSR BRI: Co-Design of Hardware/Software for Predicting MAV Aerodynamics

DTIC Science & Technology

2016-09-27

DOCUMENTATION PAGE Form ApprovedOMB No. 0704-0188 1. REPORT DATE (DD-MM-YYYY) 2. REPORT TYPE 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER 6. AUTHOR(S) 7...703-588-8494 AFOSR BRI While Moore’s Law theoretically doubles processor performance every 24 months, much of the realizable performance remains...past efforts to develop such CFD codes on accelerated processors showed limited success, our hardware/software co-design approach created malleable

Narcotic Independence After Pancreatic Duct Stenting Predicts Narcotic Independence After Lateral Pancreaticojejunostomy for Chronic Pancreatitis.

PubMed

Kwon, Richard S; Young, Benjamin E; Marsteller, William F; Lawrence, Christopher; Wu, Bechien U; Lee, Linda S; Mullady, Daniel; Klibansky, David A; Gardner, Timothy B; Simeone, Diane M

2016-09-01

This study aimed to determine if the improved pain response to endoscopic retrograde cholangiopancreatogrphy (ERCP) and pancreatic stent placement (EPS) predicts pain response in patients with chronic pancreatitis after modified lateral pancreaticojejunostomy (LPJ). A multi-institutional, retrospective review of patients who underwent successful EPS before LPJ between 2001 and 2010 was performed. The primary outcome was narcotic independence (NI) within 2 months after ERCP or LPJ. A total of 31 narcotic-dependent patients with chronic pancreatitis underwent successful EPS before LPJ. Ten (32%) achieved post-LPJ NI (median follow-up, 8.5 months; interquartile range [IQR], 2-38 months). Eight (80%) of 10 patients with NI post-ERCP achieved NI post-LPJ. Two (10%) without NI post-ERCP achieved NI post-LPJ. Narcotic independence post-EPS was associated strongly with NI post-LPJ with an odds ratio of 38 (P = 0.0025) and predicted post-LPJ NI with a sensitivity, specificity, positive predictive value, and negative predictive value of 80%, 90.5%, 80%, and 90.5%, respectively. Narcotic independence after EPS is associated with NI after LPJ. Failure to achieve NI post-ERCP predicts failure to achieve NI post-LPJ. These results support the need for larger studies to confirm the predictive value of pancreatic duct stenting for better selection of chronic pancreatitis patients who will benefit from LPJ.

Can blood and semen presepsin levels in males predict pregnancy in couples undergoing intra-cytoplasmic sperm injection?

PubMed Central

Ovayolu, Ali; Arslanbuğa, Cansev Yilmaz; Gun, Ismet; Devranoglu, Belgin; Ozdemir, Arman; Cakar, Sule Eren

2016-01-01

Objective: To determine whether semen and plasma presepsin values measured in men with normozoospermia and oligoasthenospermia undergoing invitro-fertilization would be helpful in predicting ongoing pregnancy and live birth. Methods: Group-I was defined as patients who had pregnancy after treatment and Group-II comprised those with no pregnancy. Semen and blood presepsin values were subsequently compared between the groups. Parametric comparisons were performed using Student’s t-test, and non-parametric comparisons were conducted using the Mann-Whitney U test. Results: There were 42 patients in Group-I and 72 in Group-II. In the context of successful pregnancy and live birth, semen presepsin values were statistically significantly higher in Group-I than in Group-II (p= 0.004 and p= 0.037, respectively). The most appropriate semen presepsin cut-off value for predicting both ongoing pregnancy and live birth was calculated as 199 pg/mL. Accordingly, their sensitivity was 64.5% to 59.3%, their specificity was 57.0% to 54.2%, and their positive predictive value was 37.0% to 29.6%, respectively; their negative predictive value was 80.4% in both instances. Conclusion: Semen presepsin values could be a new marker that may enable the prediction of successful pregnancy and/or live birth. Its negative predictive values are especially high. PMID:27882005

Career Performance Trajectories in Track and Field Jumping Events from Youth to Senior Success: The Importance of Learning and Development.

PubMed

Boccia, Gennaro; Moisè, Paolo; Franceschi, Alberto; Trova, Francesco; Panero, Davide; La Torre, Antonio; Rainoldi, Alberto; Schena, Federico; Cardinale, Marco

2017-01-01

The idea that early sport success can be detrimental for long-term sport performance is still under debate. Therefore, the aims of this study were to examine the career trajectories of Italian high and long jumpers to provide a better understanding of performance development in jumping events. The official long-jump and high-jump rankings of the Italian Track and Field Federation were collected from the age of 12 to career termination, for both genders from the year 1994 to 2014. Top-level athletes were identified as those with a percentile of their personal best performance between 97 and 100. The age of entering competitions of top-level athletes was not different than the rest of the athletic population, whereas top-level athletes performed their personal best later than the rest of the athletes. Top-level athletes showed an overall higher rate of improvement in performance from the age of 13 to the age of 18 years when compared to all other individuals. Only 10-25% of the top-level adult athletes were top-level at the age of 16. Around 60% of the top-level young at the age of 16 did not maintain the same level of performance in adulthood. Female high-jump represented an exception from this trend since in this group most top-level young become top-level adult athletes. These findings suggest that performance before the age of 16 is not a good predictor of adult performance in long and high jump. The annual rate of improvements from 13 to 18 years should be included as a predictor of success rather than performance per se. Coaches should be careful about predicting future success based on performances obtained during youth in jumping events.

Can Multiple Mini-Interviews Predict Academic Performance of Dental Students? A Two-Year Follow-Up.

PubMed

Alaki, Sumer M; Yamany, Ibrahim A; Shinawi, Lana A; Hassan, Mona H A; Tekian, Ara

2016-11-01

Prior research has shown that students' previous grade point average (GPA) is the best predictor for future academic success. However, it can only partly predict the variability in dental school performance. The aim of this study was to assess the predictive value of multiple mini-interviews (MMI) as an admission criterion by comparing them with the academic performance of dental students over a two-year period. All incoming undergraduate dental students at the King Abdulaziz University Faculty of Dentistry (KAUFD) during academic year 2013-14 were invited to participate in MMI. Students rotated through six objective structured clinical exam (OSCE)-like stations for 30 minutes total and were interviewed by two trained faculty interviewers at each station. The stations were focused on noncognitive skills thought to be essential to academic performance at KAUFD. The academic performance of these students was then followed for two years and linked to their MMI scores. A total of 146 students (71 males and 75 females) participated in an interview (response rate=92.9%). Most students scored in the acceptable range at each MMI station. Students' total MMI score, ambitions, and motives were significant predictors of GPA during the two years of follow-up (p<0.038 and p<0.001, respectively). In this study, MMI was found to be able to predict future academic performance of undergraduate dental students.

Predicting the performance of fingerprint similarity searching.

PubMed

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.

Ceramic Matrix Composites (CMC) Life Prediction Development

NASA Technical Reports Server (NTRS)

Levine, Stanley R.; Verrilli, Michael J.; Thomas, David J.; Halbig, Michael C.; Calomino, Anthony M.; Ellis, John R.; Opila, Elizabeth J.

1990-01-01

Advanced launch systems will very likely incorporate fiber reinforced ceramic matrix composites (CMC) in critical propulsion and airframe components. The use of CMC will save weight, increase operating margin, safety and performance, and improve reuse capability. For reusable and single mission use, accurate life prediction is critical to success. The tools to accomplish this are immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for many applications. This paper describes an approach and progress made to satisfy the need to develop an integrated life prediction system that addresses mechanical durability and environmental degradation.

Different Brain Activities Predict Retrieval Success during Emotional and Semantic Encoding

ERIC Educational Resources Information Center

Padovani, Tullia; Koenig, Thomas; Brandeis, Daniel; Perrig, Walter J.

2011-01-01

There is an increasing line of evidence supporting the idea that the formation of lasting memories involves neural activity preceding stimulus presentation. Following this line, we presented words in an incidental learning setting and manipulated the prestimulus state by asking the participants to perform either an emotional (neutral or emotional)…

A Job Analysis for K-8 Principals in a Nationwide Charter School System

ERIC Educational Resources Information Center

Cumings, Laura; Coryn, Chris L. S.

2009-01-01

Background: Although no single technique on its own can predict job performance, a job analysis is a customary approach for identifying the relevant knowledge, skills, abilities, and other characteristics (KSAO) necessary to successfully complete the job tasks of a position. Once the position requirements are identified, the hiring process is…

Predicting Academic Success: General Intelligence, "Big Five" Personality Traits, and Work Drive

ERIC Educational Resources Information Center

Ridgell, Susan D.; Lounsbury, John W.

2004-01-01

General intelligence, Big Five personality traits, and the construct Work Drive were studied in relation to two measures of collegiate academic performance: a single course grade received by undergraduate students in an introductory psychology course, and self-reported GPA. General intelligence and Work Drive were found to be significantly…

Using Video Feedback to Measure Self-Efficacy

ERIC Educational Resources Information Center

Bobo, Linda; Andrews, Amanda

2010-01-01

When a student has a high sense of self-efficacy, foreseeing success and providing positive guides and supports for performing the skill will usually occur. A low self-efficacy tends to predict failure and anticipation of what could go wrong. Videotape feedback provided to students has reported favorable outcomes. Self-efficacy could alter…

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

ERIC Educational Resources Information Center

Zhang, Zhidong; Telese, James

2012-01-01

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

Simple Predictions Fueled by Capacity Limitations: When Are They Successful?

ERIC Educational Resources Information Center

Gaissmaier, Wolfgang; Schooler, Lael J.; Rieskamp, Jorg

2006-01-01

Counterintuitively, Y. Kareev, I. Lieberman, and M. Lev (1997) found that a lower short-term memory capacity benefits performance on a correlation detection task. They assumed that people with low short-term memory capacity (low spans) perceived the correlations as more extreme because they relied on smaller samples, which are known to exaggerate…

The Key to Successful Achievement as an Undergraduate Student: Confidence and Realistic Expectations?

ERIC Educational Resources Information Center

Nicholson, Laura; Putwain, David; Connors, Liz; Hornby-Atkinson, Pat

2013-01-01

This study examined how expectations of independent study and academic behavioural confidence predicted end-of-semester marks in a sample of undergraduate students. Students' expectations and academic behavioural confidence were measured near the beginning of the semester, and academic performance was taken from aggregated end-of-semester marks.…

Leadership Intelligence: Unlocking the Potential for School Leadership Effectiveness

ERIC Educational Resources Information Center

Gage, Timothy; Smith, Clive

2016-01-01

Top performing companies have long used intelligence tests in their selection procedures to predict who the best leaders are. However, no longer are the brightest favoured, or guaranteed success. A post-modern world demands a fresh outlook on leadership. How can school leaders judge their effectiveness? How can school leaders lead intelligently?…

High performance equipped mirrors for MTG FCI-TA and IRS-FTO

NASA Astrophysics Data System (ADS)

Kazakov, T.; San Juan, J. L.; Serrano, J.; Moreno, J.; González, D.; Rodríguez, G.; López, D.; Vázquez, E.; Aivar, J.; Motos, A.; Rahmouni, Christophe; Imperiali, Stephan; Fappani, Denis

2017-09-01

The Meteosat Third Generation (MTG) Programme is being realised through the well established and successful Cooperation between EUMETSAT and ESA. It will ensure the future continuity of MSG with the capabilities to enhance nowcasting, global and regional numerical weather prediction, climate and atmospheric chemistry monitoring data from Geostationary Orbit.

Teaching Learning Disabled Adolescents to Set Realistic Goals.

ERIC Educational Resources Information Center

Tollefson, Nona; And Others

Sixty-one learning disabled (LD) adolescents in four junior high schools were randomly assigned to experimental or control groups as part of an effort to teach LD students to set realistic goals so they might experience success and satisfaction in school. Ss in the experimental group made achievement contracts and predicted their performance in…

The Importance of Cognitive Development in Middle Childhood for Adulthood Socioeconomic Status, Mental Health, and Problem Behavior

ERIC Educational Resources Information Center

Feinstein, Leon; Bynner, John

2004-01-01

This study examined the extent to which continuities and discontinuities in cognitive performance between ages 5 and 10 predicted adult income, educational success, household worklessness, criminality, teen parenthood, smoking, and depression. Assessed were the degree of this change during middle childhood, the influence of socioeconomic status…

Pre-Assessment and Peer Tutoring as Measures to Improve Performance in Gateway General Chemistry Classes

ERIC Educational Resources Information Center

Allenbaugh, R. J.; Herrera, K. M.

2014-01-01

Determining student readiness for gateway chemistry courses and providing underprepared students effective remediation are important as student bodies are growing increasingly diverse in their precollege preparation. The effectiveness of the ACT Mathematics Test and the Whimbey Analytical Skills Inventory (WASI) in predicting student success in…

Benchmarking performance measurement and lean manufacturing in the rough mill

Treesearch

Dan Cumbo; D. Earl Kline; Matthew S. Bumgardner

2006-01-01

Lean manufacturing represents a set of tools and a stepwise strategy for achieving smooth, predictable product flow, maximum product flexibility, and minimum system waste. While lean manufacturing principles have been successfully applied to some components of the secondary wood products value stream (e.g., moulding, turning, assembly, and finishing), the rough mill is...

Performance Enhancements Under Dual-task Conditions

NASA Technical Reports Server (NTRS)

Kramer, A. F.; Wickens, C. D.; Donchin, E.

1984-01-01

Research on dual-task performance has been concerned with delineating the antecedent conditions which lead to dual-task decrements. Capacity models of attention, which propose that a hypothetical resource structure underlies performance, have been employed as predictive devices. These models predict that tasks which require different processing resources can be more successfully time shared than tasks which require common resources. The conditions under which such dual-task integrality can be fostered were assessed in a study in which three factors likely to influence the integrality between tasks were manipulated: inter-task redundancy, the physical proximity of tasks and the task relevant objects. Twelve subjects participated in three experimental sessions in which they performed both single and dual-tasks. The primary task was a pursuit step tracking task. The secondary tasks required the discrimination between different intensities or different spatial positions of a stimulus. The results are discussed in terms of a model of dual-task integrality.

Comparison Between Simulated and Experimentally Measured Performance of a Four Port Wave Rotor

NASA Technical Reports Server (NTRS)

Paxson, Daniel E.; Wilson, Jack; Welch, Gerard E.

2007-01-01

Performance and operability testing has been completed on a laboratory-scale, four-port wave rotor, of the type suitable for use as a topping cycle on a gas turbine engine. Many design aspects, and performance estimates for the wave rotor were determined using a time-accurate, one-dimensional, computational fluid dynamics-based simulation code developed specifically for wave rotors. The code follows a single rotor passage as it moves past the various ports, which in this reference frame become boundary conditions. This paper compares wave rotor performance predicted with the code to that measured during laboratory testing. Both on and off-design operating conditions were examined. Overall, the match between code and rig was found to be quite good. At operating points where there were disparities, the assumption of larger than expected internal leakage rates successfully realigned code predictions and laboratory measurements. Possible mechanisms for such leakage rates are discussed.

Accelerated second-degree nursing students: predictors of graduation and NCLEX-RN first-time pass rates.

PubMed

Penprase, Barbara B; Harris, Margaret A

2013-01-01

It is important to understand and identify factors that affect students' academic performance before entry into a nursing program and as they progress through the program. The authors discuss a study, and its outcomes, that assessed accelerated second-degree nursing students' prenursing and core nursing grades that served to predict their success at completing the nursing program and passing NCLEX-RN on first attempt. Strategies were identified to help at-risk students to be successful in the program and with first-time passage of NCLEX-RN.

The value of the UK Clinical Aptitude Test in predicting pre-clinical performance: a prospective cohort study at Nottingham Medical School.

PubMed

Yates, Janet; James, David

2010-07-28

The UK Clinical Aptitude Test (UKCAT) was introduced in 2006 as an additional tool for the selection of medical students. It tests mental ability in four distinct domains (Quantitative Reasoning, Verbal Reasoning, Abstract Reasoning, and Decision Analysis), and the results are available to students and admissions panels in advance of the selection process. As yet the predictive validity of the test against course performance is largely unknown.The study objective was to determine whether UKCAT scores predict performance during the first two years of the 5-year undergraduate medical course at Nottingham. We studied a single cohort of students, who entered Nottingham Medical School in October 2007 and had taken the UKCAT. We used linear regression analysis to identify independent predictors of marks for different parts of the 2-year preclinical course. Data were available for 204/260 (78%) of the entry cohort. The UKCAT total score had little predictive value. Quantitative Reasoning was a significant independent predictor of course marks in Theme A ('The Cell'), (p = 0.005), and Verbal Reasoning predicted Theme C ('The Community') (p < 0.001), but otherwise the effects were slight or non-existent. This limited study from a single entry cohort at one medical school suggests that the predictive value of the UKCAT, particularly the total score, is low. Section scores may predict success in specific types of course assessment.The ultimate test of validity will not be available for some years, when current cohorts of students graduate. However, if this test of mental ability does not predict preclinical performance, it is arguably less likely to predict the outcome in the clinical years. Further research from medical schools with different types of curriculum and assessment is needed, with longitudinal studies throughout the course.

Prediction and Factor Extraction of Drug Function by Analyzing Medical Records in Developing Countries.

PubMed

Hu, Min; Nohara, Yasunobu; Nakamura, Masafumi; Nakashima, Naoki

2017-01-01

The World Health Organization has declared Bangladesh one of 58 countries facing acute Human Resources for Health (HRH) crisis. Artificial intelligence in healthcare has been shown to be successful for diagnostics. Using machine learning to predict pharmaceutical prescriptions may solve HRH crises. In this study, we investigate a predictive model by analyzing prescription data of 4,543 subjects in Bangladesh. We predict the function of prescribed drugs, comparing three machine-learning approaches. The approaches compare whether a subject shall be prescribed medicine from the 21 most frequently prescribed drug functions. Receiver Operating Characteristics (ROC) were selected as a way to evaluate and assess prediction models. The results show the drug function with the best prediction performance was oral hypoglycemic drugs, which has an average AUC of 0.962. To understand how the variables affect prediction, we conducted factor analysis based on tree-based algorithms and natural language processing techniques.

Boosting compound-protein interaction prediction by deep learning.

PubMed

Tian, Kai; Shao, Mingyu; Wang, Yang; Guan, Jihong; Zhou, Shuigeng

2016-11-01

The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear and imbalanced nature of biological data, many machine learning approaches have their own limitations. Recently, deep learning techniques show advantages over many state-of-the-art machine learning methods in some applications. In this study, we aim at improving the performance of CPI prediction based on deep learning, and propose a method called DL-CPI (the abbreviation of Deep Learning for Compound-Protein Interactions prediction), which employs deep neural network (DNN) to effectively learn the representations of compound-protein pairs. Extensive experiments show that DL-CPI can learn useful features of compound-protein pairs by a layerwise abstraction, and thus achieves better prediction performance than existing methods on both balanced and imbalanced datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

PubMed

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

PubMed Central

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques. PMID:24416353

The long-term performance degradation of a radioisotope thermoelectric generator using silicon germanium

NASA Technical Reports Server (NTRS)

Stapfer, G.; Truscello, V. C.

1976-01-01

The successful utilization of a radioisotope thermoelectric generator (RTG) as the power source for spaceflight missions requires that the performance of such an RTG be predictable throughout the mission. Several mechanisms occur within the generator which tend to degrade the performance as a function of operating time. The impact which these mechanisms have on the available output power of an RTG depends primarily on such factors as time, temperature and self-limiting effects. The relative magnitudes, rates and temperature dependency of these various degradation mechanisms have been investigated separately by coupon experiments as well as 4-couple and 18-couple module experiments. This paper discusses the different individual mechanisms and summarizes their combined influence on the performance of an RTG. Also presented as part of the RTG long-term performance characteristics is the sensitivity of the available RTG output power to variations of the individual degradation mechanisms thus identifying the areas of greatest concern for a successful long-term mission.

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

PubMed

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

2016-10-01

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

Successful Single-Lung Transplant for Severe Lung Graft-Versus-Host Disease Two Years After Sibling Allograft for Acute Lymphoblastic Leukemia: A Case Report.

PubMed

Irhimeh, M R; Musk, M; Cooney, J P

2016-11-01

Bone marrow transplantation (BMT) has been performed as a successful life-saving treatment for hematological and neoplastic diseases. Despite the predictable long-term survival rates in BMT, pulmonary complications reduce the survival rates significantly mainly because of chronic graft-versus-host disease (GVHD). This report briefly discusses a successful lung transplantation case for severe lung GVHD after allograft for acute lymphoblastic leukemia. This case report supports the scarce evidence in the literature for the importance of lung transplantation as a therapeutic option for patients who develop respiratory failure secondary to BMT. Copyright © 2016. Published by Elsevier Inc.

3D flexible alignment using 2D maximum common substructure: dependence of prediction accuracy on target-reference chemical similarity.

PubMed

Kawabata, Takeshi; Nakamura, Haruki

2014-07-28

A protein-bound conformation of a target molecule can be predicted by aligning the target molecule on the reference molecule obtained from the 3D structure of the compound-protein complex. This strategy is called "similarity-based docking". For this purpose, we develop the flexible alignment program fkcombu, which aligns the target molecule based on atomic correspondences with the reference molecule. The correspondences are obtained by the maximum common substructure (MCS) of 2D chemical structures, using our program kcombu. The prediction performance was evaluated using many target-reference pairs of superimposed ligand 3D structures on the same protein in the PDB, with different ranges of chemical similarity. The details of atomic correspondence largely affected the prediction success. We found that topologically constrained disconnected MCS (TD-MCS) with the simple element-based atomic classification provides the best prediction. The crashing potential energy with the receptor protein improved the performance. We also found that the RMSD between the predicted and correct target conformations significantly correlates with the chemical similarities between target-reference molecules. Generally speaking, if the reference and target compounds have more than 70% chemical similarity, then the average RMSD of 3D conformations is <2.0 Å. We compared the performance with a rigid-body molecular alignment program based on volume-overlap scores (ShaEP). Our MCS-based flexible alignment program performed better than the rigid-body alignment program, especially when the target and reference molecules were sufficiently similar.

Development of a Wake Vortex Spacing System for Airport Capacity Enhancement and Delay Reduction

NASA Technical Reports Server (NTRS)

Hinton, David A.; OConnor, Cornelius J.

2000-01-01

The Terminal Area Productivity project has developed the technologies required (weather measurement, wake prediction, and wake measurement) to determine the aircraft spacing needed to prevent wake vortex encounters in various weather conditions. The system performs weather measurements, predicts bounds on wake vortex behavior in those conditions, derives safe wake spacing criteria, and validates the wake predictions with wake vortex measurements. System performance to date indicates that the potential runway arrival rate increase with Aircraft VOrtex Spacing System (AVOSS), considering common path effects and ATC delivery variance, is 5% to 12% depending on the ratio of large and heavy aircraft. The concept demonstration system, using early generation algorithms and minimal optimization, is performing the wake predictions with adequate robustness such that only 4 hard exceedances have been observed in 1235 wake validation cases. This performance demonstrates the feasibility of predicting wake behavior bounds with multiple uncertainties present, including the unknown aircraft weight and speed, weather persistence between the wake prediction and the observations, and the location of the weather sensors several kilometers from the approach location. A concept for the use of the AVOSS system for parallel runway operations has been suggested, and an initial study at the JFK International Airport suggests that a simplified AVOSS system can be successfully operated using only a single lidar as both the weather sensor and the wake validation instrument. Such a selfcontained AVOSS would be suitable for wake separation close to the airport, as is required for parallel approach concepts such as SOIA.

Understanding the dynamics of terrorism events with multiple-discipline datasets and machine learning approach

PubMed Central

Ding, Fangyu; Ge, Quansheng; Fu, Jingying; Hao, Mengmeng

2017-01-01

Terror events can cause profound consequences for the whole society. Finding out the regularity of terrorist attacks has important meaning for the global counter-terrorism strategy. In the present study, we demonstrate a novel method using relatively popular and robust machine learning methods to simulate the risk of terrorist attacks at a global scale based on multiple resources, long time series and globally distributed datasets. Historical data from 1970 to 2015 was adopted to train and evaluate machine learning models. The model performed fairly well in predicting the places where terror events might occur in 2015, with a success rate of 96.6%. Moreover, it is noteworthy that the model with optimized tuning parameter values successfully predicted 2,037 terrorism event locations where a terrorist attack had never happened before. PMID:28591138

Understanding the dynamics of terrorism events with multiple-discipline datasets and machine learning approach.

PubMed

Ding, Fangyu; Ge, Quansheng; Jiang, Dong; Fu, Jingying; Hao, Mengmeng

2017-01-01

Terror events can cause profound consequences for the whole society. Finding out the regularity of terrorist attacks has important meaning for the global counter-terrorism strategy. In the present study, we demonstrate a novel method using relatively popular and robust machine learning methods to simulate the risk of terrorist attacks at a global scale based on multiple resources, long time series and globally distributed datasets. Historical data from 1970 to 2015 was adopted to train and evaluate machine learning models. The model performed fairly well in predicting the places where terror events might occur in 2015, with a success rate of 96.6%. Moreover, it is noteworthy that the model with optimized tuning parameter values successfully predicted 2,037 terrorism event locations where a terrorist attack had never happened before.

Prefrontal-hippocampal-fusiform activity during encoding predicts intraindividual differences in free recall ability: an event-related functional-anatomic MRI study.

PubMed

Dickerson, B C; Miller, S L; Greve, D N; Dale, A M; Albert, M S; Schacter, D L; Sperling, R A

2007-01-01

The ability to spontaneously recall recently learned information is a fundamental mnemonic activity of daily life, but has received little study using functional neuroimaging. We developed a functional MRI (fMRI) paradigm to study regional brain activity during encoding that predicts free recall. In this event-related fMRI study, ten lists of fourteen pictures of common objects were shown to healthy young individuals and regional brain activity during encoding was analyzed based on subsequent free recall performance. Free recall of items was predicted by activity during encoding in hippocampal, fusiform, and inferior prefrontal cortical regions. Within-subject variance in free recall performance for the ten lists was predicted by a linear combination of condition-specific inferior prefrontal, hippocampal, and fusiform activity. Recall performance was better for lists in which prefrontal activity was greater for all items of the list and hippocampal and fusiform activity were greater specifically for items that were recalled from the list. Thus, the activity of medial temporal, fusiform, and prefrontal brain regions during the learning of new information is important for the subsequent free recall of this information. These fronto-temporal brain regions act together as a large-scale memory-related network, the components of which make distinct yet interacting contributions during encoding that predict subsequent successful free recall performance.

Prefrontal-Hippocampal-Fusiform Activity During Encoding Predicts Intraindividual Differences in Free Recall Ability: An Event-Related Functional-Anatomic MRI Study

PubMed Central

Dickerson, B.C.; Miller, S.L.; Greve, D.N.; Dale, A.M.; Albert, M.S.; Schacter, D.L.; Sperling, R.A.

2009-01-01

The ability to spontaneously recall recently learned information is a fundamental mnemonic activity of daily life, but has received little study using functional neuroimaging. We developed a functional MRI (fMRI) paradigm to study regional brain activity during encoding that predicts free recall. In this event-related fMRI study, ten lists of fourteen pictures of common objects were shown to healthy young individuals and regional brain activity during encoding was analyzed based on subsequent free recall performance. Free recall of items was predicted by activity during encoding in hippocampal, fusiform, and inferior prefrontal cortical regions. Within-subject variance in free recall performance for the ten lists was predicted by a linear combination of condition-specific inferior prefrontal, hippocampal, and fusiform activity. Recall performance was better for lists in which pre-frontal activity was greater for all items of the list and hippocampal and fusi-form activity were greater specifically for items that were recalled from the list. Thus, the activity of medial temporal, fusiform, and prefrontal brain regions during the learning of new information is important for the subsequent free recall of this information. These fronto-temporal brain regions act together as a large-scale memory-related network, the components of which make distinct yet interacting contributions during encoding that predict subsequent successful free recall performance. PMID:17604356

Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database.

PubMed

Wu, Mike; Ghassemi, Marzyeh; Feng, Mengling; Celi, Leo A; Szolovits, Peter; Doshi-Velez, Finale

2017-05-01

The widespread adoption of electronic health records allows us to ask evidence-based questions about the need for and benefits of specific clinical interventions in critical-care settings across large populations. We investigated the prediction of vasopressor administration and weaning in the intensive care unit. Vasopressors are commonly used to control hypotension, and changes in timing and dosage can have a large impact on patient outcomes. We considered a cohort of 15 695 intensive care unit patients without orders for reduced care who were alive 30 days post-discharge. A switching-state autoregressive model (SSAM) was trained to predict the multidimensional physiological time series of patients before, during, and after vasopressor administration. The latent states from the SSAM were used as predictors of vasopressor administration and weaning. The unsupervised SSAM features were able to predict patient vasopressor administration and successful patient weaning. Features derived from the SSAM achieved areas under the receiver operating curve of 0.92, 0.88, and 0.71 for predicting ungapped vasopressor administration, gapped vasopressor administration, and vasopressor weaning, respectively. We also demonstrated many cases where our model predicted weaning well in advance of a successful wean. Models that used SSAM features increased performance on both predictive tasks. These improvements may reflect an underlying, and ultimately predictive, latent state detectable from the physiological time series. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Integration of Attributes from Non-Linear Characterization of Cardiovascular Time-Series for Prediction of Defibrillation Outcomes

PubMed Central

Shandilya, Sharad; Kurz, Michael C.; Ward, Kevin R.; Najarian, Kayvan

2016-01-01

Objective The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR), rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA) patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals. Materials and Methods Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF) was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI) model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA) technique. Results 358 defibrillations were evaluated (218 unsuccessful and 140 successful). Non-linear properties (Lyapunov exponent > 0) of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity) outperformed AMSA (53.6% sensitivity). At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity. Conclusion At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations. Addition of partial end-tidal carbon dioxide (PetCO2) signal improves accuracy and sensitivity of the MDI prediction model. PMID:26741805

Laboratory evaluation of the pointing stability of the ASPS Vernier System

NASA Technical Reports Server (NTRS)

1980-01-01

The annular suspension and pointing system (ASPS) is an end-mount experiment pointing system designed for use in the space shuttle. The results of the ASPS Vernier System (AVS) pointing stability tests conducted in a laboratory environment are documented. A simulated zero-G suspension was used to support the test payload in the laboratory. The AVS and the suspension were modelled and incorporated into a simulation of the laboratory test. Error sources were identified and pointing stability sensitivities were determined via simulation. Statistical predictions of laboratory test performance were derived and compared to actual laboratory test results. The predicted mean pointing stability during simulated shuttle disturbances was 1.22 arc seconds; the actual mean laboratory test pointing stability was 1.36 arc seconds. The successful prediction of laboratory test results provides increased confidence in the analytical understanding of the AVS magnetic bearing technology and allows confident prediction of in-flight performance. Computer simulations of ASPS, operating in the shuttle disturbance environment, predict in-flight pointing stability errors less than 0.01 arc seconds.

Prediction of P300 BCI Aptitude in Severe Motor Impairment

PubMed Central

Halder, Sebastian; Ruf, Carolin Anne; Furdea, Adrian; Pasqualotto, Emanuele; De Massari, Daniele; van der Heiden, Linda; Bogdan, Martin; Rosenstiel, Wolfgang; Birbaumer, Niels; Kübler, Andrea; Matuz, Tamara

2013-01-01

Brain-computer interfaces (BCIs) provide a non-muscular communication channel for persons with severe motor impairments. Previous studies have shown that the aptitude with which a BCI can be controlled varies from person to person. A reliable predictor of performance could facilitate selection of a suitable BCI paradigm. Eleven severely motor impaired participants performed three sessions of a P300 BCI web browsing task. Before each session auditory oddball data were collected to predict the BCI aptitude of the participants exhibited in the current session. We found a strong relationship of early positive and negative potentials around 200 ms (elicited with the auditory oddball task) with performance. The amplitude of the P2 (r  =  −0.77) and of the N2 (r  =  −0.86) had the strongest correlations. Aptitude prediction using an auditory oddball was successful. The finding that the N2 amplitude is a stronger predictor of performance than P3 amplitude was reproduced after initially showing this effect with a healthy sample of BCI users. This will reduce strain on the end-users by minimizing the time needed to find suitable paradigms and inspire new approaches to improve performance. PMID:24204597

Multi-mode evaluation of power-maximizing cross-flow turbine controllers

DOE PAGES

Forbush, Dominic; Cavagnaro, Robert J.; Donegan, James; ...

2017-09-21

A general method for predicting and evaluating the performance of three candidate cross-flow turbine power-maximizing controllers is presented in this paper using low-order dynamic simulation, scaled laboratory experiments, and full-scale field testing. For each testing mode and candidate controller, performance metrics quantifying energy capture (ability of a controller to maximize power), variation in torque and rotation rate (related to drive train fatigue), and variation in thrust loads (related to structural fatigue) are quantified for two purposes. First, for metrics that could be evaluated across all testing modes, we considered the accuracy with which simulation or laboratory experiments could predict performancemore » at full scale. Second, we explored the utility of these metrics to contrast candidate controller performance. For these turbines and set of candidate controllers, energy capture was found to only differentiate controller performance in simulation, while the other explored metrics were able to predict performance of the full-scale turbine in the field with various degrees of success. Finally, effects of scale between laboratory and full-scale testing are considered, along with recommendations for future improvements to dynamic simulations and controller evaluation.« less

Investigating the interaction between the homeostatic and circadian processes of sleep-wake regulation for the prediction of waking neurobehavioural performance

NASA Technical Reports Server (NTRS)

Van Dongen, Hans P A.; Dinges, David F.

2003-01-01

The two-process model of sleep regulation has been applied successfully to describe, predict, and understand sleep-wake regulation in a variety of experimental protocols such as sleep deprivation and forced desynchrony. A non-linear interaction between the homeostatic and circadian processes was reported when the model was applied to describe alertness and performance data obtained during forced desynchrony. This non-linear interaction could also be due to intrinsic non-linearity in the metrics used to measure alertness and performance, however. Distinguishing these possibilities would be of theoretical interest, but could also have important implications for the design and interpretation of experiments placing sleep at different circadian phases or varying the duration of sleep and/or wakefulness. Although to date no resolution to this controversy has been found, here we show that the issue can be addressed with existing data sets. The interaction between the homeostatic and circadian processes of sleep-wake regulation was investigated using neurobehavioural performance data from a laboratory experiment involving total sleep deprivation. The results provided evidence of an actual non-linear interaction between the homeostatic and circadian processes of sleep-wake regulation for the prediction of waking neurobehavioural performance.

Multi-mode evaluation of power-maximizing cross-flow turbine controllers

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

Forbush, Dominic; Cavagnaro, Robert J.; Donegan, James

A general method for predicting and evaluating the performance of three candidate cross-flow turbine power-maximizing controllers is presented in this paper using low-order dynamic simulation, scaled laboratory experiments, and full-scale field testing. For each testing mode and candidate controller, performance metrics quantifying energy capture (ability of a controller to maximize power), variation in torque and rotation rate (related to drive train fatigue), and variation in thrust loads (related to structural fatigue) are quantified for two purposes. First, for metrics that could be evaluated across all testing modes, we considered the accuracy with which simulation or laboratory experiments could predict performancemore » at full scale. Second, we explored the utility of these metrics to contrast candidate controller performance. For these turbines and set of candidate controllers, energy capture was found to only differentiate controller performance in simulation, while the other explored metrics were able to predict performance of the full-scale turbine in the field with various degrees of success. Finally, effects of scale between laboratory and full-scale testing are considered, along with recommendations for future improvements to dynamic simulations and controller evaluation.« less

Predicting Dishonorable Discharge Among Military Recruits

DTIC Science & Technology

2013-03-01

train its members to give them the highest chance possible at a successful career. Jacob Rodriquez’s study, “Predicting the Military Career Success of...society as a whole. To improve the enlistment process and attract recruits with the highest probability of future career success , based on our...00036840801964450 Rodriguez, John J. (2008, January 1). Predicting the career success of air force academy cadets (Paper AAI3309209). ETD collection for

RTOD- RADIAL TURBINE OFF-DESIGN PERFORMANCE ANALYSIS

NASA Technical Reports Server (NTRS)

Glassman, A. J.

1994-01-01

The RTOD program was developed to accurately predict radial turbine off-design performance. The radial turbine has been used extensively in automotive turbochargers and aircraft auxiliary power units. It is now being given serious consideration for primary powerplant applications. In applications where the turbine will operate over a wide range of power settings, accurate off-design performance prediction is essential for a successful design. RTOD predictions have already illustrated a potential improvement in off-design performance offered by rotor back-sweep for high-work-factor radial turbines. RTOD can be used to analyze other potential performance enhancing design features. RTOD predicts the performance of a radial turbine (with or without rotor blade sweep) as a function of pressure ratio, speed, and stator setting. The program models the flow with the following: 1) stator viscous and trailing edge losses; 2) a vaneless space loss between the stator and the rotor; and 3) rotor incidence, viscous, trailing-edge, clearance, and disk friction losses. The stator and rotor viscous losses each represent the combined effects of profile, endwall, and secondary flow losses. The stator inlet and exit and the rotor inlet flows are modeled by a mean-line analysis, but a sector analysis is used at the rotor exit. The leakage flow through the clearance gap in a pivoting stator is also considered. User input includes gas properties, turbine geometry, and the stator and rotor viscous losses at a reference performance point. RTOD output includes predicted turbine performance over a specified operating range and any user selected flow parameters. The RTOD program is written in FORTRAN IV for batch execution and has been implemented on an IBM 370 series computer with a central memory requirement of approximately 100K of 8 bit bytes. The RTOD program was developed in 1983.

Semen cryopreservation in pubertal boys before gonadotoxic treatment and the role of endocrinologic evaluation in predicting sperm yield.

PubMed

van Casteren, Niels J; Dohle, Gert R; Romijn, Johanens C; de Muinck Keizer-Schrama, Sabine M P F; Weber, Robertus F A; van den Heuvel-Eibrink, Marry M

2008-10-01

To evaluate the feasibility of semen cryopreservation in pubertal boys before they receive gonadotoxic therapy and to identify which pretreatment parameters might predict successful cryopreservation. Retrospective data analysis. Tertiary fertility center, academic children's hospital. Between 1995 and 2005, 80 boys (median age 16.6 years, range 13.7-18.9 years) consulted the outpatient clinic of andrology for semen cryopreservation before a potentially gonadotoxic treatment. We assessed the pretreatment semen parameters, hormone levels, and patients' characteristics. Measurement of the number of adolescents able to cryopreserve semen. Thirteen boys were unable to produce semen by masturbation. In 53 boys semen quality was adequate for cryopreservation. In 14 patients semen analysis did not show motile spermatozoa, and therefore semen cryopreservation could not be performed. Although inhibin B showed a strong correlation with sperm count, no significant difference was found in serum T, inhibin B, LH, and FSH levels in the patients with or without successful sperm yield. Moreover, median age was not different between patients with and without a successful sperm yield. Semen cryopreservation in boys is a feasible method to preserve spermatozoa before gonadotoxic therapy is started and should be offered to all pubertal boys despite their young age. Serum hormone levels do not predict sperm yield.

HPEPDOCK: a web server for blind peptide-protein docking based on a hierarchical algorithm.

PubMed

Zhou, Pei; Jin, Bowen; Li, Hao; Huang, Sheng-You

2018-05-09

Protein-peptide interactions are crucial in many cellular functions. Therefore, determining the structure of protein-peptide complexes is important for understanding the molecular mechanism of related biological processes and developing peptide drugs. HPEPDOCK is a novel web server for blind protein-peptide docking through a hierarchical algorithm. Instead of running lengthy simulations to refine peptide conformations, HPEPDOCK considers the peptide flexibility through an ensemble of peptide conformations generated by our MODPEP program. For blind global peptide docking, HPEPDOCK obtained a success rate of 33.3% in binding mode prediction on a benchmark of 57 unbound cases when the top 10 models were considered, compared to 21.1% for pepATTRACT server. HPEPDOCK also performed well in docking against homology models and obtained a success rate of 29.8% within top 10 predictions. For local peptide docking, HPEPDOCK achieved a high success rate of 72.6% on a benchmark of 62 unbound cases within top 10 predictions, compared to 45.2% for HADDOCK peptide protocol. Our HPEPDOCK server is computationally efficient and consumed an average of 29.8 mins for a global peptide docking job and 14.2 mins for a local peptide docking job. The HPEPDOCK web server is available at http://huanglab.phys.hust.edu.cn/hpepdock/.

Managerial leadership assessment - Personality correlates of and sex differences in ratings by leaders, peers, and followers

NASA Technical Reports Server (NTRS)

Gibson, Robert H.; Wilhelm, John

1989-01-01

A performance appraisal was conducted at a Fortune 500 airline. Evaluations of each manager were taken from his or her management, peers and subordinates. These ratings were related to personality clusters revealing patterns for males similar to those found between personality and performance in pilot populations. A case is made that piloting aircraft requires similar skills to managing other complex enterprises and that similar profiles predict success in each.

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

Students' Midprogram Content Area Performance as a Predictor of End-of-Program NCLEX Readiness.

PubMed

Brussow, Jennifer A; Dunham, Michelle

2017-12-22

Many programs have implemented end-of-program predictive testing to identify students at risk of NCLEX-RN failure. Unfortunately, for many students, end-of-program testing comes too late. Regression and relative importance analysis were used to explore relationships between 9 content area assessments and an end-of-program assessment shown to be predictive of NCLEX-RN success. Results indicate that scores on assessments for content areas such as medical surgical nursing and care of children are predictive of end-of-program test scores, suggesting that instructors should provide remediation at the first sign of lagging performance.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in anyway or used commercially without permission from the journal.

The impact of fraction magnitude knowledge on algebra performance and learning.

PubMed

Booth, Julie L; Newton, Kristie J; Twiss-Garrity, Laura K

2014-02-01

Knowledge of fractions is thought to be crucial for success with algebra, but empirical evidence supporting this conjecture is just beginning to emerge. In the current study, Algebra 1 students completed magnitude estimation tasks on three scales (0-1 [fractions], 0-1,000,000, and 0-62,571) just before beginning their unit on equation solving. Results indicated that fraction magnitude knowledge, and not whole number knowledge, was especially related to students' pretest knowledge of equation solving and encoding of equation features. Pretest fraction knowledge was also predictive of students' improvement in equation solving and equation encoding skills. Students' placement of unit fractions (e.g., those with a numerator of 1) was not especially useful for predicting algebra performance and learning in this population. Placement of non-unit fractions was more predictive, suggesting that proportional reasoning skills might be an important link between fraction knowledge and learning algebra. Copyright © 2013 Elsevier Inc. All rights reserved.

Deep learning methods for protein torsion angle prediction.

PubMed

Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

2017-09-18

Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

Blind predictions of protein interfaces by docking calculations in CAPRI.

PubMed

Lensink, Marc F; Wodak, Shoshana J

2010-11-15

Reliable prediction of the amino acid residues involved in protein-protein interfaces can provide valuable insight into protein function, and inform mutagenesis studies, and drug design applications. A fast-growing number of methods are being proposed for predicting protein interfaces, using structural information, energetic criteria, or sequence conservation or by integrating multiple criteria and approaches. Overall however, their performance remains limited, especially when applied to nonobligate protein complexes, where the individual components are also stable on their own. Here, we evaluate interface predictions derived from protein-protein docking calculations. To this end we measure the overlap between the interfaces in models of protein complexes submitted by 76 participants in CAPRI (Critical Assessment of Predicted Interactions) and those of 46 observed interfaces in 20 CAPRI targets corresponding to nonobligate complexes. Our evaluation considers multiple models for each target interface, submitted by different participants, using a variety of docking methods. Although this results in a substantial variability in the prediction performance across participants and targets, clear trends emerge. Docking methods that perform best in our evaluation predict interfaces with average recall and precision levels of about 60%, for a small majority (60%) of the analyzed interfaces. These levels are significantly higher than those obtained for nonobligate complexes by most extant interface prediction methods. We find furthermore that a sizable fraction (24%) of the interfaces in models ranked as incorrect in the CAPRI assessment are actually correctly predicted (recall and precision ≥50%), and that these models contribute to 70% of the correct docking-based interface predictions overall. Our analysis proves that docking methods are much more successful in identifying interfaces than in predicting complexes, and suggests that these methods have an excellent potential of addressing the interface prediction challenge. © 2010 Wiley-Liss, Inc.

The effects of individual status and group performance on network ties among teammates in the National Basketball Association

PubMed Central

Aven, Brandy

2018-01-01

For individuals, status is derived both from their personal attributes and the groups with whom they are affiliated. Depending on the performance of their groups, the status of individuals may benefit or suffer from identifying closely with the group. When the group excels, high-status members potentially receive much of the credit and increased status. Conversely, high-status members of underperforming groups potentially suffer disproportionate declines in their status relative to the low-status group members. We therefore predict an interaction between group performance and individual status on the willingness to associate with the group and its members. We test our prediction by examining social media ties among teammates in the National Basketball Association. Specifically, we investigate the “following” ties of teammates on Twitter at the end of the 2014–2015 season. Elections to All-Star games are used to measure the status of players, and team performance is measured by recent success in the postseason playoffs. The results show that compared to high-status players on successful teams, high-status players on underperforming teams are less likely to follow their teammates. This result aligns with research on status inconsistency, suggesting that individuals deemphasize their group affiliation when it jeopardizes their individual status. An additional contribution is the advancement of the probit Social Relations Model for the analysis of binary ties in social networks. PMID:29708984

The effects of individual status and group performance on network ties among teammates in the National Basketball Association.

PubMed

Koster, Jeremy; Aven, Brandy

2018-01-01

For individuals, status is derived both from their personal attributes and the groups with whom they are affiliated. Depending on the performance of their groups, the status of individuals may benefit or suffer from identifying closely with the group. When the group excels, high-status members potentially receive much of the credit and increased status. Conversely, high-status members of underperforming groups potentially suffer disproportionate declines in their status relative to the low-status group members. We therefore predict an interaction between group performance and individual status on the willingness to associate with the group and its members. We test our prediction by examining social media ties among teammates in the National Basketball Association. Specifically, we investigate the "following" ties of teammates on Twitter at the end of the 2014-2015 season. Elections to All-Star games are used to measure the status of players, and team performance is measured by recent success in the postseason playoffs. The results show that compared to high-status players on successful teams, high-status players on underperforming teams are less likely to follow their teammates. This result aligns with research on status inconsistency, suggesting that individuals deemphasize their group affiliation when it jeopardizes their individual status. An additional contribution is the advancement of the probit Social Relations Model for the analysis of binary ties in social networks.

A temporary deficiency in self-control: Can heightened motivation overcome this effect?

PubMed

Kelly, Claire L; Crawford, Trevor J; Gowen, Emma; Richardson, Kelly; Sünram-Lea, Sandra I

2017-05-01

Self-control is important for everyday life and involves behavioral regulation. Self-control requires effort, and when completing two successive self-control tasks, there is typically a temporary drop in performance in the second task. High self-reported motivation and being made self-aware somewhat counteract this effect-with the result that performance in the second task is enhanced. The current study explored the relationship between self-awareness and motivation on sequential self-control task performance. Before employing self-control in an antisaccade task, participants initially applied self-control in an incongruent Stroop task or completed a control task. After the Stroop task, participants unscrambled sentences that primed self-awareness (each started with the word "I") or unscrambled neutral sentences. Motivation was measured after the antisaccade task. Findings revealed that, after exerting self-control in the incongruent Stroop task, motivation predicted erroneous responses in the antisaccade task for those that unscrambled neutral sentences, and high motivation led to fewer errors. Those primed with self-awareness were somewhat more motivated overall, but motivation did not significantly predict antisaccade performance. Supporting the resource allocation account, if one was motivated-intrinsically or via the manipulation of self-awareness-resources were allocated to both tasks leading to the successful completion of two sequential self-control tasks. © 2017 The Authors. Psychophysiology published by Wiley Periodicals, Inc. on behalf of Society for Psychophysiological Research.

Cognitive ability is heritable and predicts the success of an alternative mating tactic

PubMed Central

Smith, Carl; Philips, André; Reichard, Martin

2015-01-01

The ability to attract mates, acquire resources for reproduction, and successfully outcompete rivals for fertilizations may make demands on cognitive traits—the mechanisms by which an animal acquires, processes, stores and acts upon information from its environment. Consequently, cognitive traits potentially undergo sexual selection in some mating systems. We investigated the role of cognitive traits on the reproductive performance of male rose bitterling (Rhodeus ocellatus), a freshwater fish with a complex mating system and alternative mating tactics. We quantified the learning accuracy of males and females in a spatial learning task and scored them for learning accuracy. Males were subsequently allowed to play the roles of a guarder and a sneaker in competitive mating trials, with reproductive success measured using paternity analysis. We detected a significant interaction between male mating role and learning accuracy on reproductive success, with the best-performing males in maze trials showing greater reproductive success in a sneaker role than as a guarder. Using a cross-classified breeding design, learning accuracy was demonstrated to be heritable, with significant additive maternal and paternal effects. Our results imply that male cognitive traits may undergo intra-sexual selection. PMID:26041347

Cognitive ability is heritable and predicts the success of an alternative mating tactic.

PubMed

Smith, Carl; Philips, André; Reichard, Martin

2015-06-22

The ability to attract mates, acquire resources for reproduction, and successfully outcompete rivals for fertilizations may make demands on cognitive traits--the mechanisms by which an animal acquires, processes, stores and acts upon information from its environment. Consequently, cognitive traits potentially undergo sexual selection in some mating systems. We investigated the role of cognitive traits on the reproductive performance of male rose bitterling (Rhodeus ocellatus), a freshwater fish with a complex mating system and alternative mating tactics. We quantified the learning accuracy of males and females in a spatial learning task and scored them for learning accuracy. Males were subsequently allowed to play the roles of a guarder and a sneaker in competitive mating trials, with reproductive success measured using paternity analysis. We detected a significant interaction between male mating role and learning accuracy on reproductive success, with the best-performing males in maze trials showing greater reproductive success in a sneaker role than as a guarder. Using a cross-classified breeding design, learning accuracy was demonstrated to be heritable, with significant additive maternal and paternal effects. Our results imply that male cognitive traits may undergo intra-sexual selection. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Prediction of movement intention using connectivity within motor-related network: An electrocorticography study.

PubMed

Kang, Byeong Keun; Kim, June Sic; Ryun, Seokyun; Chung, Chun Kee

2018-01-01

Most brain-machine interface (BMI) studies have focused only on the active state of which a BMI user performs specific movement tasks. Therefore, models developed for predicting movements were optimized only for the active state. The models may not be suitable in the idle state during resting. This potential maladaptation could lead to a sudden accident or unintended movement resulting from prediction error. Prediction of movement intention is important to develop a more efficient and reasonable BMI system which could be selectively operated depending on the user's intention. Physical movement is performed through the serial change of brain states: idle, planning, execution, and recovery. The motor networks in the primary motor cortex and the dorsolateral prefrontal cortex are involved in these movement states. Neuronal communication differs between the states. Therefore, connectivity may change depending on the states. In this study, we investigated the temporal dynamics of connectivity in dorsolateral prefrontal cortex and primary motor cortex to predict movement intention. Movement intention was successfully predicted by connectivity dynamics which may reflect changes in movement states. Furthermore, dorsolateral prefrontal cortex is crucial in predicting movement intention to which primary motor cortex contributes. These results suggest that brain connectivity is an excellent approach in predicting movement intention.

Predicting international medical graduate success on college certification examinations

PubMed Central

Schabort, Inge; Mercuri, Mathew; Grierson, Lawrence E.M.

2014-01-01

Abstract Objective To determine predictors of international medical graduate (IMG) success in accordance with the priorities highlighted by the Thomson and Cohl judicial report on IMG selection. Design Retrospective assessment using regression analyses to compare the information available at the time of resident selection with those trainees’ national certification examination outcomes. Setting McMaster University in Hamilton, Ont. Participants McMaster University IMG residents who completed the program between 2005 and 2011. Main outcome measures Associations between IMG professional experience or demographic characteristics and examination outcomes. Results The analyses revealed that country of study and performance on the Medical Council of Canada Evaluating Examination are among the predictors of performance on the College of Family Physicians of Canada and the Royal College of Physicians and Surgeons of Canada certification examinations. Of interest, the analyses also suggest discipline-specific relationships between previous professional experience and examination success. Conclusion This work presents a useful technique for further improving our understanding of the performance of IMGs on certification examinations in North America, encourages similar interinstitutional analyses, and provides a foundation for the development of tools to assist with IMG education. PMID:25316762

Plant-soil feedbacks from 30-year family-specific soil cultures: phylogeny, soil chemistry and plant life stage.

PubMed

Mehrabi, Zia; Bell, Thomas; Lewis, Owen T

2015-06-01

Intraspecific negative feedback effects, where performance is reduced on soils conditioned by conspecifics, are widely documented in plant communities. However, interspecific feedbacks are less well studied, and their direction, strength, causes, and consequences are poorly understood. If more closely related species share pathogens, or have similar soil resource requirements, plants may perform better on soils conditioned by more distant phylogenetic relatives. There have been few empirical tests of this prediction across plant life stages, and none of which attempt to account for soil chemistry. Here, we test the utility of phylogeny for predicting soil feedback effects on plant survival and performance (germination, seedling survival, growth rate, biomass). We implement a full factorial experiment growing species representing five families on five plant family-specific soil sources. Our experiments exploit soils that have been cultured for over 30 years in plant family-specific beds at Oxford University Botanic Gardens. Plant responses to soil source were idiosyncratic, and species did not perform better on soils cultured by phylogenetically more distant relatives. The magnitude and sign of feedback effects could, however, be explained by differences in the chemical properties of "home" and "away" soils. Furthermore, the direction of soil chemistry-related plant-soil feedbacks was dependent on plant life stage, with the effects of soil chemistry on germination success and accumulation of biomass inversely related. Our results (1) suggest that the phylogenetic distance between plant families cannot predict plant-soil feedbacks across multiple life stages, and (2) highlight the need to consider changes in soil chemistry as an important driver of population responses. The contrasting responses at plant life stages suggest that studies focusing on brief phases in plant demography (e.g., germination success) may not give a full picture of plant-soil feedback effects.

The influence of anthropometrics on physical employment standard performance.

PubMed

Reilly, T; Spivock, M; Prayal-Brown, A; Stockbrugger, B; Blacklock, R

2016-10-01

The Canadian Armed Forces (CAF) recently implemented the Fitness for Operational Requirements of CAF Employment (FORCE), a new physical employment standard (PES). Data collection throughout development included anthropometric profiles of the CAF. To determine if anthropometric measurements and demographic information would predict the performance outcomes of the FORCE and/or Common Military Task Fitness Evaluation (CMTFE). We conducted a secondary analysis of data from FORCE research. We obtained bioelectrical impedance and segmental analysis. Statistical analysis included correlation and linear regression analyses. Among the 668 study subjects, as predicted, any task requiring lifting, pulling or moving of an object was significantly and positively correlated (r > 0.67) to lean body mass (LBM) measurements. LBM correlated with stretcher carry (r = 0.78) and with lifting actions such as sand bag drag (r = 0.77), vehicle extrication (r = 0.71), sand bag fortification (r = 0.68) and sand bag lift time (r = -0.67). The difference between the correlation of dead mass (DM) with task performance compared with LBM was not statistically significant. DM and LBM can be used in a PES to predict success on military tasks such as casualty evacuation and manual material handling. However, there is no minimum LBM required to perform these tasks successfully. These data direct future research on how we should diversify research participants by anthropometrics, in addition to the traditional demographic variables of gender and age, to highlight potential important adverse impact with PES design. In addition, the results can be used to develop better training regimens to facilitate passing a PES. © All rights reserved. ‘The Influence of Anthropometrics on Physical Employment Standard Performance’ has been reproduced with the permission of DND, 2016.

Assessing personal talent determinants in young racquet sport players: a systematic review.

PubMed

Faber, Irene R; Bustin, Paul M J; Oosterveld, Frits G J; Elferink-Gemser, Marije T; Nijhuis-Van der Sanden, Maria W G

2016-01-01

Since junior performances have little predictive value for future success, other solutions are sought to assess a young player's potential. The objectives of this systematic review are (1) to provide an overview of instruments measuring personal talent determinants of young players in racquet sports, and (2) to evaluate these instruments regarding their validity for talent development. Electronic searches were conducted in PubMed, PsychINFO, Web of Knowledge, ScienceDirect and SPORTDiscus (1990 to 31 March 2014). Search terms represented tennis, table tennis, badminton and squash, the concept of talent, methods of testing and children. Thirty articles with information regarding over 100 instruments were included. Validity evaluation showed that instruments focusing on intellectual and perceptual abilities, and coordinative skills discriminate elite from non-elite players and/or are related to current performance, but their predictive validity is not confirmed. There is moderate evidence that the assessments of mental and goal management skills predict future performance. Data on instruments measuring physical characteristics prohibit a conclusion due to conflicting findings. This systematic review yielded an ambiguous end point. The lack of longitudinal studies precludes verification of the instrument's capacity to forecast future performance. Future research should focus on instruments assessing multidimensional talent determinants and their predictive value in longitudinal designs.

Who succeeds at dental school? Factors predicting students' academic performance in a dental school in republic of Korea.

PubMed

Ihm, Jung-Joon; Lee, Gene; Kim, Kack-Kyun; Jang, Ki-Taeg; Jin, Bo-Hyoung

2013-12-01

The purpose of this study was to examine what cognitive and non-cognitive factors were responsible for predicting the academic performance of dental students in a dental school in the Republic of Korea. This school is one of those in Korea that now require applicants to have a bachelor's degree. In terms of cognitive factors, students' undergraduate grade point average (GPA) and Dental Education Eligibility Test (DEET) scores were used, while surveys were conducted to evaluate four non-cognitive measures: locus of control, self-esteem, self-directed learning, and interpersonal skills. A total of 353 students matriculating at Seoul National University School of Dentistry in 2005, 2006, 2007, and 2008 consented to the collection of records and completed the surveys. The main finding was that applicants who scored higher on internal locus of control and self-efficacy were more likely to be academically successful dental students. Self-directed learning was significantly associated with students ranked in the top 50 percent in cumulative GPA. However, students' interpersonal skills were negatively related to their academic performance. In particular, students' lack of achievement could be predicted by monitoring their first-year GPA. Therefore, the identification of those factors to predict dental school performance has implications for the dental curriculum and effective pedagogy in dental education.

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

Evaluating the predictability of distance race performance in NCAA cross country and track and field from high school race times in the United States.

PubMed

Brusa, Jamie L

2017-12-30

Successful recruiting for collegiate track & field athletes has become a more competitive and essential component of coaching. This study aims to determine the relationship between race performances of distance runners at the United States high school and National Collegiate Athletic Association (NCAA) levels. Conditional inference classification tree models were built and analysed to predict the probability that runners would qualify for the NCAA Division I National Cross Country Meet and/or the East or West NCAA Division I Outdoor Track & Field Preliminary Round based on their high school race times in the 800 m, 1600 m, and 3200 m. Prediction accuracies of the classification trees ranged from 60.0 to 76.6 percent. The models produced the most reliable estimates for predicting qualifiers in cross country, the 1500 m, and the 800 m for females and cross country, the 5000 m, and the 800 m for males. NCAA track & field coaches can use the results from this study as a guideline for recruiting decisions. Additionally, future studies can apply the methodological foundations of this research to predicting race performances set at different metrics, such as national meets in other countries or Olympic qualifications, from previous race data.

Literature Review on Concurrent Dual Career Development in the URL (unrestricted Line)

DTIC Science & Technology

1989-06-01

Career Development Systems, (3) Multiple Career Paths in Organizations, (4) Skills Required for Management, (5) Predicting Career Success , (6) Skill...10 Sum m ary .............................................................. 11 Predicting Career Success ................................................. 11...Career Paths in Organizations, (4) Skills Required for Management, (5) Predicting Career Success , (6) Skill Requirements of Jobs, (7) Formal Training, (8

Analysis of Phoenix Anomalies and IV and V Findings Applied to the GRAIL Mission

NASA Technical Reports Server (NTRS)

Larson, Steve

2012-01-01

Analysis of patterns in IV&V findings and their correlation with post-launch anomalies allowed GRAIL to make more efficient use of IV&V services . Fewer issues. . Higher fix rate. . Better communication. . Increased volume of potential issues vetted, at lower cost. . Hard to make predictions of post-launch performance based on IV&V findings . Phoenix made sound fix/use as-is decisions . Things that were fixed eliminated some problems, but hard to quantify. . Broad predictive success in one area, but inverse relationship in others.

Mathematics Preparation and Success in Introductory College Science Courses

NASA Astrophysics Data System (ADS)

Avallone, L. M.; Geiger, L. C.; Luebke, A. E.

2008-12-01

It is a long-held belief that adequate mathematics preparation is a key to success in introductory college science courses. Indeed, a number of recent studies have tested mathematics "fluency" and compared that to performance in introductory physics or chemistry courses. At the University of Colorado at Boulder, we administered a twenty-question math assessment to incoming first-year students as part of orientation registration. The intent of this tool was to provide information for advising new college students about their readiness for college-level science courses, both those for science majors and those for non-scientists. In this presentation we describe the results of the mathematics assessment for two incoming classes in the College of Arts and Sciences at CU-Boulder (about 9,000 students) and its predictive capabilities for success in introductory science courses. We also analyze student performance in these courses (i.e., course grade) with respect to ACT and/or SAT scores. We will present data on the relative success of students in college science courses both with and without prior college-level mathematics courses as well.

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

NASA Technical Reports Server (NTRS)

Grosvenor, Sandy; Jones, Jeremy; Koratkar, Anuradha; Li, Connie; Mackey, Jennifer; Neher, Ken; Wolf, Karl; Obenschain, Arthur F. (Technical Monitor)

2001-01-01

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations more efficiently, The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper examines the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what have been its successes and challenges.

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

NASA Technical Reports Server (NTRS)

Jones, Jeremy; Grosvenor, Sandy; Wolf, Karl; Li, Connie; Koratkar, Anuradha; Powers, Edward I. (Technical Monitor)

2001-01-01

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations. The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper will examine the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what has been its successes and challenges.

The role of personality and self-efficacy in the selection and retention of successful nursing students: a longitudinal study.

PubMed

McLaughlin, Katrina; Moutray, Marianne; Muldoon, Orla T

2008-01-01

This paper is a report of a study to examine the role of personality and self-efficacy in predicting academic performance and attrition in nursing students. Despite a considerable amount of research investigating attrition in nursing students and new nurses, concerns remain. This particular issue highlights the need for a more effective selection process whereby those selected are more likely to complete their preregistration programme successfully, and remain employed as Registered Nurses. A longitudinal design was adopted. A questionnaire, which included measures of personality and occupational and academic self-efficacy, was administered to 384 students early in the first year of the study. At the end of the programme, final marks and attrition rates were obtained from university records for a total of 350 students. The data were collected from 1999 to 2002. Individuals who scored higher on a psychoticism scale were more likely to withdraw from the programme. Occupational self-efficacy was revealed to be a statistically significant predictor of final mark obtained, in that those with higher self-efficacy beliefs were more likely to achieve better final marks. Extraversion was also shown to negatively predict academic performance in that those with higher extraversion scores were more likely to achieve lower marks. More research is needed to explore the attributes of successful nursing students and the potential contribution of psychological profiling to a more effective selection process.

Predictors of academic performance for applicants to an international dental studies program in the United States.

PubMed

Pitigoi-Aron, Gabriela; King, Patricia A; Chambers, David W

2011-12-01

The number of U.S. and Canadian dental schools offering programs for dentists with degrees from other countries leading to the D.D.S. or D.M.D. degree has increased recently. This fact, along with the diversity of educational systems represented by candidates for these programs, increases the importance of identifying valid admissions predictors of success in international dental student programs. Data from 148 students accepted into the international dental studies program at the University of the Pacific from 1994 through 2004 were analyzed. Dependent variables were comprehensive cumulative GPA at the end of both the first and second years of the two-year program. The Test of English as a Foreign Language (TOEFL) and both Parts I and II of the National Board Dental Examination (NBDE) were significant positive predictors of success. Performance on laboratory tests of clinical skill in operative dentistry and in fixed prosthodontics and ratings from interviewers were not predictive of overall success in the program. Although this study confirms the predictive value of written tests such as the TOEFL and NBDE, it also contributes to the literature documenting inconsistent results regarding other types of predictors. It may be the case that characteristics of individual programs or features of the applicant pools for each may require use of admissions predictors that are unique to schools.

Percutaneous Coronary Revascularization for Chronic Total Occlusions: A Novel Predictive Score of Technical Failure Using Advanced Technologies.

PubMed

Galassi, Alfredo R; Boukhris, Marouane; Azzarelli, Salvatore; Castaing, Marine; Marzà, Francesco; Tomasello, Salvatore D

2016-05-09

The aims of this study were to describe the 10-year experience of a single operator dedicated to chronic total occlusion (CTO) and to establish a model for predicting technical failure. During the last decade, the interest in percutaneous coronary interventions (PCIs) of chronic total occlusions (CTOs) has increased, allowing the improvement of success rate. One thousand nineteen patients with CTO underwent 1,073 CTO procedures performed by a single CTO-dedicated operator. The study population was subdivided into 2 groups by time period: period 1 (January 2005 to December 2009, n = 378) and period 2 (January 2010 to December 2014, n = 641). Observations were randomly assigned to a derivation set and a validation set (in a 2:1 ratio). A prediction score was established by assigning points for each independent predictor of technical failure in the derivation set according to the beta coefficient and summing all points accrued. Lesions attempted in period 2 were more complex in comparison with those in period 1. Compared with period 1, both technical and clinical success rates significantly improved (from 87.8% to 94.4% [p = 0.001] and from 77.6% to 89.9% [p < 0.001], respectively). A prediction score for technical failure including age ≥75 years (1 point), ostial location (1 point), and collateral filling Rentrop grade <2 (2 points) was established, stratifying procedures into 4 difficulty groups: easy (0), intermediate (1), difficult (2), and very difficult (3 or 4), with decreasing technical success rates. In derivation and validation sets, areas under the curve were comparable (0.728 and 0.772, respectively). With growing expertise, the success rate has increased despite increasing complexity of attempted lesions. The established model predicted the probability of technical failure and thus might be applied to grading the difficulty of CTO procedures. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Identification of informative features for predicting proinflammatory potentials of engine exhausts.

PubMed

Wang, Chia-Chi; Lin, Ying-Chi; Lin, Yuan-Chung; Jhang, Syu-Ruei; Tung, Chun-Wei

2017-08-18

The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment. To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm. A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively. The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.

Evaluation of three statistical prediction models for forensic age prediction based on DNA methylation.

PubMed

Smeers, Inge; Decorte, Ronny; Van de Voorde, Wim; Bekaert, Bram

2018-05-01

DNA methylation is a promising biomarker for forensic age prediction. A challenge that has emerged in recent studies is the fact that prediction errors become larger with increasing age due to interindividual differences in epigenetic ageing rates. This phenomenon of non-constant variance or heteroscedasticity violates an assumption of the often used method of ordinary least squares (OLS) regression. The aim of this study was to evaluate alternative statistical methods that do take heteroscedasticity into account in order to provide more accurate, age-dependent prediction intervals. A weighted least squares (WLS) regression is proposed as well as a quantile regression model. Their performances were compared against an OLS regression model based on the same dataset. Both models provided age-dependent prediction intervals which account for the increasing variance with age, but WLS regression performed better in terms of success rate in the current dataset. However, quantile regression might be a preferred method when dealing with a variance that is not only non-constant, but also not normally distributed. Ultimately the choice of which model to use should depend on the observed characteristics of the data. Copyright © 2018 Elsevier B.V. All rights reserved.

Success-factors in transition to university mathematics

NASA Astrophysics Data System (ADS)

Bengmark, S.; Thunberg, H.; Winberg, T. M.

2017-11-01

This study examines different factors' relative importance for students' performance in the transition to university mathematics. Students' characteristics (motivation, actions and beliefs) were measured when entering the university and at the end of the first year. Principal component analysis revealed four important constructs: Self-efficacy, Motivation type, Study habits and Views of mathematics. Subsequently, orthogonal partial least squares (OPLS) analysis was used for measuring the constructs' ability to predict students' university mathematics grades. No individual constructs measured at the time of entrance predicted more than 5% of the variation. On the other hand, jointly they predicted 14%, which is almost in pair with upper secondary grades predicting 17%. Constructs measured at the end of the first year were stronger predictors, jointly predicting 37% of the variation in university grades, with Self-efficacy (21%) and Motivation (12%) being the two strongest individual predictors. In general, Study habits were not important for predicting university achievement. However, for students with low upper secondary grades, the textbook and interaction with peers, rather than internet-based resources, contributed positively to achievement. The association between Views of mathematics and performance was weak for all groups and non-existing for students with low grades.

Self-regulating the effortful "social dos".

PubMed

Cortes, Kassandra; Kammrath, Lara K; Scholer, Abigail A; Peetz, Johanna

2014-03-01

In the current research, we explored differences in the self-regulation of the personal dos (i.e., engaging in active and effortful behaviors that benefit the self) and in the self-regulation of the social dos (engaging in those same effortful behaviors to benefit someone else). In 6 studies, we examined whether the same trait self-control abilities that predict task persistence on personal dos would also predict task persistence on social dos. That is, would the same behavior, such as persisting through a tedious and attentionally demanding task, show different associations with trait self-control when it is framed as benefitting the self versus someone else? In Studies 1-3, we directly compared the personal and social dos and found that trait self-control predicted self-reported and behavioral personal dos but not social dos, even when the behaviors were identical and when the incentives were matched. Instead, trait agreeableness--a trait linked to successful self-regulation within the social domain--predicted the social dos. Trait self-control did not predict the social dos even when task difficulty increased (Study 4), but it did predict the social don'ts, consistent with past research (Studies 5-6). The current studies provide support for the importance of distinguishing different domains of self-regulated behaviors and suggest that social dos can be successfully performed through routes other than traditional self-control abilities. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Risk and return: evaluating Reverse Tracing of Precursors earthquake predictions

NASA Astrophysics Data System (ADS)

Zechar, J. Douglas; Zhuang, Jiancang

2010-09-01

In 2003, the Reverse Tracing of Precursors (RTP) algorithm attracted the attention of seismologists and international news agencies when researchers claimed two successful predictions of large earthquakes. These researchers had begun applying RTP to seismicity in Japan, California, the eastern Mediterranean and Italy; they have since applied it to seismicity in the northern Pacific, Oregon and Nevada. RTP is a pattern recognition algorithm that uses earthquake catalogue data to declare alarms, and these alarms indicate that RTP expects a moderate to large earthquake in the following months. The spatial extent of alarms is highly variable and each alarm typically lasts 9 months, although the algorithm may extend alarms in time and space. We examined the record of alarms and outcomes since the prospective application of RTP began, and in this paper we report on the performance of RTP to date. To analyse these predictions, we used a recently developed approach based on a gambling score, and we used a simple reference model to estimate the prior probability of target earthquakes for each alarm. Formally, we believe that RTP investigators did not rigorously specify the first two `successful' predictions in advance of the relevant earthquakes; because this issue is contentious, we consider analyses with and without these alarms. When we included contentious alarms, RTP predictions demonstrate statistically significant skill. Under a stricter interpretation, the predictions are marginally unsuccessful.

The predictive power of SIMION/SDS simulation software for modeling ion mobility spectrometry instruments

NASA Astrophysics Data System (ADS)

Lai, Hanh; McJunkin, Timothy R.; Miller, Carla J.; Scott, Jill R.; Almirall, José R.

2008-09-01

The combined use of SIMION 7.0 and the statistical diffusion simulation (SDS) user program in conjunction with SolidWorks® with COSMSOSFloWorks® fluid dynamics software to model a complete, commercial ion mobility spectrometer (IMS) was demonstrated for the first time and compared to experimental results for tests using compounds of immediate interest in the security industry (e.g., 2,4,6-trinitrotoluene, 2,7-dinitrofluorene, and cocaine). The effort of this research was to evaluate the predictive power of SIMION/SDS for application to IMS instruments. The simulation was evaluated against experimental results in three studies: (1) a drift:carrier gas flow rates study assesses the ability of SIMION/SDS to correctly predict the ion drift times; (2) a drift gas composition study evaluates the accuracy in predicting the resolution; (3) a gate width study compares the simulated peak shape and peak intensity with the experimental values. SIMION/SDS successfully predicted the correct drift time, intensity, and resolution trends for the operating parameters studied. Despite the need for estimations and assumptions in the construction of the simulated instrument, SIMION/SDS was able to predict the resolution between two ion species in air within 3% accuracy. The preliminary success of IMS simulations using SIMION/SDS software holds great promise for the design of future instruments with enhanced performance.

The Predictive Power of SIMION/SDS Simulation Software for Modeling Ion Mobility Spectrometry Instruments

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

Hanh Lai; Timothy R. McJunkin; Carla J. Miller

2008-09-01

The combined use of SIMION 7.0 and the statistical diffusion simulation (SDS) user program in conjunction with SolidWorks® with COSMSOFloWorks® fluid dynamics software to model a complete, commercial ion mobility spectrometer (IMS) was demonstrated for the first time and compared to experimental results for tests using compounds of immediate interest in the security industry (e.g., 2,4,6-trinitrotoluene and cocaine). The effort of this research was to evaluate the predictive power of SIMION/SDS for application to IMS instruments. The simulation was evaluated against experimental results in three studies: 1) a drift:carrier gas flow rates study assesses the ability of SIMION/SDS to correctlymore » predict the ion drift times; 2) a drift gas composition study evaluates the accuracy in predicting the resolution; and 3) a gate width study compares the simulated peak shape and peak intensity with the experimental values. SIMION/SDS successfully predicted the correct drift time, intensity, and resolution trends for the operating parameters studied. Despite the need for estimations and assumptions in the construction of the simulated instrument, SIMION/SDS was able to predict the resolution between two ion species in air within 3% accuracy. The preliminary success of IMS simulations using SIMION/SDS software holds great promise for the design of future instruments with enhanced performance.« less

Anesthesiologists' learning curves for bedside qualitative ultrasound assessment of gastric content: a cohort study.

PubMed

Arzola, Cristian; Carvalho, Jose C A; Cubillos, Javier; Ye, Xiang Y; Perlas, Anahi

2013-08-01

Focused assessment of the gastric antrum by ultrasound is a feasible tool to evaluate the quality of the stomach content. We aimed to determine the amount of training an anesthesiologist would need to achieve competence in the bedside ultrasound technique for qualitative assessment of gastric content. Six anesthesiologists underwent a teaching intervention followed by a formative assessment; then learning curves were constructed. Participants received didactic teaching (reading material, picture library, and lecture) and an interactive hands-on workshop on live models directed by an expert sonographer. The participants were instructed on how to perform a systematic qualitative assessment to diagnose one of three distinct categories of gastric content (empty, clear fluid, solid) in healthy volunteers. Individual learning curves were constructed using the cumulative sum method, and competence was defined as a 90% success rate in a series of ultrasound examinations. A predictive model was further developed based on the entire cohort performance to determine the number of cases required to achieve a 95% success rate. Each anesthesiologist performed 30 ultrasound examinations (a total of 180 assessments), and three of the six participants achieved competence. The average number of cases required to achieve 90% and 95% success rates was estimated to be 24 and 33, respectively. With appropriate training and supervision, it is estimated that anesthesiologists will achieve a 95% success rate in bedside qualitative ultrasound assessment after performing approximately 33 examinations.

The effect of task demand and incentive on neurophysiological and cardiovascular markers of effort.

PubMed

Fairclough, Stephen H; Ewing, Kate

2017-09-01

According to motivational intensity theory, effort is proportional to the level of task demand provided that success is possible and successful performance is deemed worthwhile. The current study represents a simultaneous manipulation of demand (working memory load) and success importance (financial incentive) to investigate neurophysiological (EEG) and cardiovascular measures of effort. A 2×2 repeated-measures study was conducted where 18 participants performed a n-back task under three conditions of demand: easy (1-back), hard (4-back) and very hard (7-back). In addition, participants performed these tasks in the presence of performance-contingent financial incentive or in a no-incentive (pilot trial) condition. Three bands of EEG activity were quantified: theta (4-7Hz), lower-alpha (7.5-10Hz) and upper-alpha (10.5-13Hz). Fronto-medial activity in the theta band and activity in the upper-alpha band at frontal, central and parietal sites were sensitive to demand and indicated greatest effort when the task was challenging and success was possible. Mean systolic blood pressure and activity in the lower-alpha band at parietal sites were also sensitive to demand but also increased in the incentive condition across all levels of task demand. The results of the study largely support the predictions of motivational intensity using neurophysiological markers of effort. Copyright © 2017. Published by Elsevier B.V.

"Eyeball test" of thermographic patterns for predicting a successful lateral infraclavicular block.

PubMed

Andreasen, Asger M; Linnet, Karen E; Asghar, Semera; Rothe, Christian; Rosenstock, Charlotte V; Lange, Kai H W; Lundstrøm, Lars H

2017-11-01

Increased distal skin temperature can be used to predict the success of lateral infraclavicular (LIC) block. We hypothesized that an "eyeball test" of specific infrared thermographic patterns after LIC block could be used to determine block success. In this observational study, five observers trained in four distinct thermographic patterns independently evaluated thermographic images of the hands of 40 patients at baseline and at one-minute intervals for 30 min after a LIC block. Sensitivity, specificity, and predictive values of a positive and a negative test were estimated to evaluate the validity of specific thermographic patterns for predicting a successful block. Sensory and motor block of the musculocutaneous, radial, ulnar, and median nerves defined block success. Fleiss' kappa statistics of multiple interobserver agreements were used to evaluate reliability. As a diagnostic test, the defined specific thermographic patterns of the hand predicted a successful block with increasing accuracy over the 30-min observation period. Block success was predicted with a sensitivity of 92.4% (95% confidence interval [CI], 86.8 to 96.2) and with a specificity of 84.0% (95% CI, 70.3 to 92.4) at min 30. The Fleiss' kappa for the five observers was 0.87 (95% CI, 0.77 to 0.96). We conclude that visual evaluation by an eyeball test of specific thermographic patterns of the blocked hands may be useful as a valid and reliable diagnostic test for predicting a successful LIC block.

Climate change, species distribution models, and physiological performance metrics: predicting when biogeographic models are likely to fail.

PubMed

Woodin, Sarah A; Hilbish, Thomas J; Helmuth, Brian; Jones, Sierra J; Wethey, David S

2013-09-01

Modeling the biogeographic consequences of climate change requires confidence in model predictions under novel conditions. However, models often fail when extended to new locales, and such instances have been used as evidence of a change in physiological tolerance, that is, a fundamental niche shift. We explore an alternative explanation and propose a method for predicting the likelihood of failure based on physiological performance curves and environmental variance in the original and new environments. We define the transient event margin (TEM) as the gap between energetic performance failure, defined as CTmax, and the upper lethal limit, defined as LTmax. If TEM is large relative to environmental fluctuations, models will likely fail in new locales. If TEM is small relative to environmental fluctuations, models are likely to be robust for new locales, even when mechanism is unknown. Using temperature, we predict when biogeographic models are likely to fail and illustrate this with a case study. We suggest that failure is predictable from an understanding of how climate drives nonlethal physiological responses, but for many species such data have not been collected. Successful biogeographic forecasting thus depends on understanding when the mechanisms limiting distribution of a species will differ among geographic regions, or at different times, resulting in realized niche shifts. TEM allows prediction of the likelihood of such model failure.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds.

PubMed

Simkovic, Felix; Thomas, Jens M H; Keegan, Ronan M; Winn, Martyn D; Mayans, Olga; Rigden, Daniel J

2016-07-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions ('decoys'), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue-residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing.

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

PubMed Central

Simkovic, Felix; Thomas, Jens M. H.; Keegan, Ronan M.; Winn, Martyn D.; Mayans, Olga; Rigden, Daniel J.

2016-01-01

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (‘decoys’), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing. PMID:27437113

Using Brain Imaging to Extract the Structure of Complex Events at the Rational Time Band

PubMed Central

Anderson, John R.; Qin, Yulin

2017-01-01

A functional magnetic resonance imaging (fMRI) study was performed in which participants performed a complex series of mental calculations that spanned about 2 min. An Adaptive Control of Thought—Rational (ACT-R) model [Anderson, J. R. How can the human mind occur in the physical universe? New York: Oxford University Press, 2007] was developed that successfully fit the distribution of latencies. This model generated predictions for the fMRI signal in six brain regions that have been associated with modules in the ACT-R theory. The model’s predictions were confirmed for a fusiform region that reflects the visual module, for a prefrontal region that reflects the retrieval module, and for an anterior cingulate region that reflects the goal module. In addition, the only significant deviations to the motor region that reflects the manual module were anticipatory hand movements. In contrast, the predictions were relatively poor for a parietal region that reflects an imaginal module and for a caudate region that reflects the procedural module. Possible explanations of these poor fits are discussed. In addition, exploratory analyses were performed to find regions that might correspond to the predictions of the modules. PMID:18345979

Using brain imaging to extract the structure of complex events at the rational time band.

PubMed

Anderson, John R; Qin, Yulin

2008-09-01

A functional magnetic resonance imaging (fMRI) study was performed in which participants performed a complex series of mental calculations that spanned about 2 min. An Adaptive Control of Thought--Rational (ACT-R) model [Anderson, J. R. How can the human mind occur in the physical universe? New York: Oxford University Press, 2007] was developed that successfully fit the distribution of latencies. This model generated predictions for the fMRI signal in six brain regions that have been associated with modules in the ACT-R theory. The model's predictions were confirmed for a fusiform region that reflects the visual module, for a prefrontal region that reflects the retrieval module, and for an anterior cingulate region that reflects the goal module. In addition, the only significant deviations to the motor region that reflects the manual module were anticipatory hand movements. In contrast, the predictions were relatively poor for a parietal region that reflects an imaginal module and for a caudate region that reflects the procedural module. Possible explanations of these poor fits are discussed. In addition, exploratory analyses were performed to find regions that might correspond to the predictions of the modules.

Requirements for facilities and measurement techniques to support CFD development for hypersonic aircraft

NASA Technical Reports Server (NTRS)

Sellers, William L., III; Dwoyer, Douglas L.

1992-01-01

The design of a hypersonic aircraft poses unique challenges to the engineering community. Problems with duplicating flight conditions in ground based facilities have made performance predictions risky. Computational fluid dynamics (CFD) has been proposed as an additional means of providing design data. At the present time, CFD codes are being validated based on sparse experimental data and then used to predict performance at flight conditions with generally unknown levels of uncertainty. This paper will discuss the facility and measurement techniques that are required to support CFD development for the design of hypersonic aircraft. Illustrations are given of recent success in combining experimental and direct numerical simulation in CFD model development and validation for hypersonic perfect gas flows.

Test and evaluation of the HIDEC engine uptrim algorithm

NASA Technical Reports Server (NTRS)

Ray, R. J.; Myers, L. P.

1986-01-01

The highly integrated digital electronic control (HIDEC) program will demonstrate and evaluate the improvements in performance and mission effectiveness that result from integrated engine-airframe control systems. Performance improvements will result from an adaptive engine stall margin mode, a highly integrated mode that uses the airplane flight conditions and the resulting inlet distortion to continuously compute engine stall margin. When there is excessive stall margin, the engine is uptrimmed for more thrust by increasing engine pressure ratio (EPR). The EPR uptrim logic has been evaluated and implemented into computer simulations. Thrust improvements over 10 percent are predicted for subsonic flight conditions. The EPR uptrim was successfully demonstrated during engine ground tests. Test results verify model predictions at the conditions tested.

Thermal Performance of the Mars Science Laboratory Rover During Mars Surface Operations

NASA Technical Reports Server (NTRS)

Novak, Keith S.; Kempenaar, Joshua E.; Liu, Yuanming; Bhandari, Pradeep; Lee, Chern-Jiin

2013-01-01

On November 26, 2011, NASA launched a large (900 kg) rover as part of the Mars Science Laboratory (MSL) mission to Mars. Eight months later, on August 5, 2012, the MSL rover (Curiosity) successfully touched down on the surface of Mars. As of the writing of this paper, the rover had completed over 200 Sols of Mars surface operations in the Gale Crater landing site (4.5 deg S latitude). This paper describes the thermal performance of the MSL Rover during the early part of its two Earth-0.year (670 Sols) prime surface mission. Curiosity landed in Gale Crater during early Spring (Ls=151) in the Southern Hemisphere of Mars. This paper discusses the thermal performance of the rover from landing day (Sol 0) through Summer Solstice (Sol 197) and out to Sol 204. The rover surface thermal design performance was very close to pre-landing predictions. The very successful thermal design allowed a high level of operational power dissipation immediately after landing without overheating and required a minimal amount of survival heating. Early morning operations of cameras and actuators were aided by successful heating activities. MSL rover surface operations thermal experiences are discussed in this paper. Conclusions about the rover surface operations thermal performance are also presented.

Thermal Performance of the Mars Science Laboratory Rover During Mars Surface Operations

NASA Technical Reports Server (NTRS)

Novak, Keith S.; Kempenaar, Joshua E.; Liu, Yuanming; Bhandari, Pradeep; Lee, Chern-Jiin

2013-01-01

On November 26, 2011, NASA launched a large (900 kg) rover as part of the Mars Science Laboratory (MSL) mission to Mars. Eight months later, on August 5, 2012, the MSL rover (Curiosity) successfully touched down on the surface of Mars. As of the writing of this paper, the rover had completed over 200 Sols of Mars surface operations in the Gale Crater landing site (4.5 degrees South latitude). This paper describes the thermal performance of the MSL Rover during the early part of its two Earth-0.year (670 Sols) prime surface mission. Curiosity landed in Gale Crater during early Spring (Solar longitude=151) in the Southern Hemisphere of Mars. This paper discusses the thermal performance of the rover from landing day (Sol 0) through Summer Solstice (Sol 197) and out to Sol 204. The rover surface thermal design performance was very close to pre-landing predictions. The very successful thermal design allowed a high level of operational power dissipation immediately after landing without overheating and required a minimal amount of survival heating. Early morning operations of cameras and actuators were aided by successful heating activities. MSL rover surface operations thermal experiences are discussed in this paper. Conclusions about the rover surface operations thermal performance are also presented.

The relationship between human resource investments and organizational performance: a firm-level examination of equilibrium theory.

PubMed

Subramony, Mahesh; Krause, Nicole; Norton, Jacqueline; Burns, Gary N

2008-07-01

It is commonly believed that human resource investments can yield positive performance-related outcomes for organizations. Utilizing the theory of organizational equilibrium (H. A. Simon, D. W. Smithburg, & V. A. Thompson, 1950; J. G. March & H. A. Simon, 1958), the authors proposed that organizational inducements in the form of competitive pay will lead to 2 firm-level performance outcomes--labor productivity and customer satisfaction--and that financially successful organizations would be more likely to provide these inducements to their employees. To test their hypotheses, the authors gathered employee-survey and objective performance data from a sample of 126 large publicly traded U.S. organizations over a period of 3 years. Results indicated that (a) firm-level financial performance (net income) predicted employees' shared perceptions of competitive pay, (b) shared pay perceptions predicted future labor productivity, and (c) the relationship between shared pay perceptions and customer satisfaction was fully mediated by employee morale.

Predictive Value of Performance Criteria for First-Time Sophomore Resident Assistants

ERIC Educational Resources Information Center

Severance, Dana A.

2015-01-01

Housing professionals are increasingly compelled to consider hiring resident assistants (RAs) from a pool of applicants that includes students with less college experience than has traditionally been expected. The purpose of the study is to determine if the success of first-time sophomore RAs differs from that of first-time upper-class RAs…

Ethical Considerations in the Practical Application of the Unisa Socio-Critical Model of Student Success

ERIC Educational Resources Information Center

Fynn, Angelo

2016-01-01

The prediction and classification of student performance has always been a central concern within higher education institutions. It is therefore natural for higher education institutions to harvest and analyse student data to inform decisions on education provision in resource constrained South African environments. One of the drivers for the use…

Does Literacy Skill Level Predict Performance in Community College Courses: A Replication and Extension

ERIC Educational Resources Information Center

Allen, Nancy J.; DeLauro, Kimberly A.; Perry, Julia K.; Carman, Carol A.

2017-01-01

Previous research has found a positive relationship between students who had completed a sequence of developmental reading and writing courses and success in a reading-intensive college-level course. This study replicates and expands upon the previous research of Goldstein and Perin (2008) by utilizing a differently diverse sample and an…

Field Dependence/Independence Cognitive Styles: Are They Significant at Different Levels of Vocabulary Knowledge?

ERIC Educational Resources Information Center

Rostampour, Mohammad; Niroomand, Seyyedeh Mitra

2014-01-01

Cognitive styles influence the performance of language learners and can predict their success in the process of language learning. Considering field dependence/independence cognitive styles, this study aims at determining if they are significant in English vocabulary knowledge. A number of EFL university students took part in the study. The…

A Longitudinal Field Study Comparing a Multiplicative and an Additive Model of Motivation and Ability. Technical Report No. 11.

ERIC Educational Resources Information Center

Barrett, Gerald V.; And Others

The relative contribution of motivation to ability measures in predicting performance criteria of sales personnel from successive fiscal periods was investigated. In this context, the merits of a multiplicative and additive combination of motivation and ability measures were examined. The relationship between satisfaction and motivation and…

Academic Achievement and Personality Traits of Faculty Members of Indian Agricultural Universities: Their Effect on Teaching and Research Performance

ERIC Educational Resources Information Center

Ramesh, P.; Reddy, K. M.; Rao, R. V. S.; Dhandapani, A.; Siva, G. Samba; Ramakrishna, A.

2017-01-01

Purpose: The present study was undertaken to assess academic achievement, teaching aptitude and research attitude of Indian agricultural universities' faculty, to predict indicators for successful teachers and researchers, and thereby enhancing the quality of higher agricultural education. Methodology: Five hundred faculty members were selected to…

The Validity of the Academic Rigor Index (ARI) for Predicting FYGPA. Research Report 2012-5

ERIC Educational Resources Information Center

Mattern, Krista D.; Wyatt, Jeffrey N.

2012-01-01

A recurrent trend in higher education research has been to identify additional predictors of college success beyond the traditional measures of high school grade point average (HSGPA) and standardized test scores, given that a large percentage of unaccounted variance in college performance remains. A recent study by Wyatt, Wiley, Camara, and…

Blood and Black Bile: Four-Style Behavior Models in Training.

ERIC Educational Resources Information Center

O'Brien, Roger T.

1983-01-01

A four-style behavior questionnaire is used as an assessment instrument to help in predicting trainees' behavior. It is argued that the four-style behavior theory has been a helpful training tool and it can be used with measurable success in a number of subject areas: interpersonal communication, performance appraisal, and conflict resolution.…

Developments in Science and Technology.

DTIC Science & Technology

1980-01-01

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

A Logistic Approach to Predicting Student Success in Online Database Courses

ERIC Educational Resources Information Center

Garman, George

2010-01-01

This paper examines the affects of reading comprehension on the performance of online students in a beginning database management class. Reading comprehension is measured by the results of a Cloze Test administered online to the students during the first week of classes. Using data collected from 2002 through 2008, the significance of the Cloze…

Predicting Academic Success in First-Year Mathematics Courses Using ACT Mathematics Scores and High School Grade Point Average

ERIC Educational Resources Information Center

Mayo, Sandra Sims

2012-01-01

Improving college performance and retention is a daunting task for colleges and universities. Many institutions are taking action to increase retention rates by exploring their academic programs. Regression analysis was used to compare the effectiveness of ACT mathematics scores, high school grade point averages (HSGPA), and demographic factors…

Using the Admitted Class Evaluation Service (ACES) to Conduct Institution-Specific Admission or Placement Validity Studies

ERIC Educational Resources Information Center

Shaw, Emily J.

2011-01-01

Presented at the 23rd Annual Historically Black Colleges & Universities (HBCU) Conference in Atlanta, GA, in September 2011. Admitted Class Evaluation Service (ACES) is the College Board's free online service that predicts how admitted students will perform at a college or university generally, and how successful students will be in specific…

High School Advanced Placement and Student Performance in College: STEM Majors, Non-STEM Majors, and Gender Differences

ERIC Educational Resources Information Center

Ackerman, Phillip L.; Kanfer, Ruth; Calderwood, Charles

2013-01-01

Background/Context: The past few decades have seen an explosive growth in high-school student participation in the Advanced Placement program® (AP), with nearly two million exams completed in 2011. Traditionally, universities have considered AP enrollment as an indicator for predicting academic success during the admission process. However, AP…

Early Prediction of Students' Grade Point Averages at Graduation: A Data Mining Approach

ERIC Educational Resources Information Center

Tekin, Ahmet

2014-01-01

Problem Statement: There has recently been interest in educational databases containing a variety of valuable but sometimes hidden data that can be used to help less successful students to improve their academic performance. The extraction of hidden information from these databases often implements aspects of the educational data mining (EDM)…

Predicting Performance in an Advanced Undergraduate Geological Field Camp Experience

ERIC Educational Resources Information Center

Dykas, Matthew J.; Valentino, David W.

2016-01-01

This study examined the factors that contribute to students' success in conducting geological field work. Undergraduate students (n = 49; 51% female; mean age = 22 y) who were enrolled in the 5-wk State University of New York at Oswego (SUNY Oswego) geology field program volunteered to participate in this study. At the beginning of the field…

The Use of MAP as a Predictive Tool for Success on PSSA for English Language Learners

ERIC Educational Resources Information Center

Bove, Carol A.

2012-01-01

Accountability is not new to the educational arena; however, emphasis on using student achievement data as a means of holding schools accountable is (Betebenner & Linn, 2009). The No Child Left Behind Act requires local schools and districts to measure performance with student achievement data (NCLB, 2002). This requirement becomes…

PredPPCrys: Accurate Prediction of Sequence Cloning, Protein Production, Purification and Crystallization Propensity from Protein Sequences Using Multi-Step Heterogeneous Feature Fusion and Selection

PubMed Central

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed ‘PredPPCrys’ using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys. PMID:25148528

Predictors of treatment response to strengthening and stretching exercises for patellofemoral pain: An examination of patellar alignment.

PubMed

Peng, Hsien-Te; Song, Chen-Yi

2015-12-01

Closed kinetic chain and quadriceps strengthening, combined with flexibility exercises of the lower limb musculature, is a common treatment for patellofemoral pain syndrome (PFPS). The effectiveness has been well documented; however, very little is known about which factors predict treatment success. A total of 43 female subjects with PFPS participated in an eight-week progressive leg press (LP) strengthening and stretching exercise program. A decrease of 1.5 cm on a 10 cm visual analog scale (VAS) score was used as an indicator for treatment success. The baseline patellar tilt angle difference (PTA-d) due to quadriceps contraction prior to treatment was evaluated as a predictor of treatment success. The logistic regression and receiver operating characteristics (ROC) curve analysis were performed to investigate the predictive value of PTA-d. PTA-d could significantly predict the treatment success of LP strengthening and stretching exercises. The odds ratio (OR) for having an unsuccessful outcome was 1.19 (95% confidence interval (CI), 1.03-1.39, P<0.021) per degree increment of PTA-d. The most optimal cut-off value for the clinical discrimination of treatment success after LP strengthening and stretching exercise was -1.5° of PTA-d (sensitivity=0.74, specificity=0.71). The area under the ROC curve was 0.73 (standard error=0.08). Female patients with PFPS whose quadriceps contraction reduced the lateral patellar tilt prior to LP strengthening and stretching exercise treatment are more likely to experience pain relief. It seems clinically important to check dynamic patellar tilt characteristics before treatment to aid in clinical decision making. Copyright © 2014 Elsevier B.V. All rights reserved.

Predictive factor analysis for successful performance of iris recognition-assisted dynamic rotational eye tracking during laser in situ keratomileusis.

PubMed

Prakash, Gaurav; Ashok Kumar, Dhivya; Agarwal, Amar; Jacob, Soosan; Sarvanan, Yoga; Agarwal, Athiya

2010-02-01

To analyze the predictive factors associated with success of iris recognition and dynamic rotational eye tracking on a laser in situ keratomileusis (LASIK) platform with active assessment and correction of intraoperative cyclotorsion. Interventional case series. Two hundred seventy-five eyes of 142 consecutive candidates underwent LASIK with attempted iris recognition and dynamic rotational tracking on the Technolas 217z100 platform (Techolas Perfect Vision, St Louis, Missouri, USA) at a tertiary care ophthalmic hospital. The main outcome measures were age, gender, flap creation method (femtosecond, microkeratome, epi-LASIK), success of static rotational tracking, ablation algorithm, pulses, and depth; preablation and intraablation rotational activity were analyzed and evaluated using regression models. Preablation static iris recognition was successful in 247 eyes, without difference in flap creation methods (P = .6). Age (partial correlation, -0.16; P = .014), amount of pulses (partial correlation, 0.39; P = 1.6 x 10(-8)), and gender (P = .02) were significant predictive factors for the amount of intraoperative cyclodeviation. Tracking difficulties leading to linking the ablation with a new intraoperatively acquired iris image were more with femtosecond-assisted flaps (P = 2.8 x 10(-7)) and the amount of intraoperative cyclotorsion (P = .02). However, the number of cases having nonresolvable failure of intraoperative rotational tracking was similar in the 3 flap creation methods (P = .22). Intraoperative cyclotorsional activity depends on the age, gender, and duration of ablation (pulses delivered). Femtosecond flaps do not seem to have a disadvantage over microkeratome flaps as far as iris recognition and success of intraoperative dynamic rotational tracking is concerned. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Effect of posterior tibial tendon dysfunction on unipedal standing balance test.

PubMed

Kulig, Kornelia; Lee, Szu-Ping; Reischl, Stephen F; Noceti-DeWit, Lisa

2015-01-01

Foot pain and diminished functional capacity are characteristics of tibialis posterior tendon dysfunction (TPTD). This study tested the hypotheses that women with TPTD would have impaired performance of a unipedal standing balance test (USBT) and that balance performance would be related to the number of single limb heel raises (SLHR). Thirty-nine middle-aged women, 19 with early stage TPTD (stage I and II), were instructed to perform 2 tasks; a USBT and repeated SLHR. Balance success was defined as a 10-second stance. For those who were successful, center of pressure (COP) data in anterior-posterior (AP) and medial-lateral (ML) directions were recorded as a measure of postural sway. SLHR performance was divided into 3 bins (≤2; 3-9 and > 10 repetitions). The between-balance success on performing the SLHR test was analyzed using the Fisher's exact test (2 × 3). Independent t tests were used to compare between-group differences in postural sway. Relationship of postural sway to the number of heel raises was assessed using Spearman's rho. The success rate of the USBT was significantly lower in women with TPTD than the controls (47% vs 85%, P = .041). In addition, women with TPTD who completed the USBT exhibited increased AP COP displacement (14.0 ± 7.4 vs 8.4 ± 1.3 mm, P = .008), and a strong trend of increased ML COP displacement (8.3 ± 4.5 vs 6.1 ± 1.2 mm, P = .050). The success rate of USBT was correlated with the number of SLHR (P = .01). The AP and ML COP displacement were correlated with SLHR (r = -.538 and .495), respectively. Women with TPTD have difficulty in performing the USBT. Performance of the USBT and SLHR are highly correlated and predictive of each other. A unipedal balance test may be used as a proxy TPTD assessment tool to the heel raising test when pain prevents performance. Level III, case control study. © The Author(s) 2014.

Critical thinking traits of top-tier experts and implications for computer science education

NASA Astrophysics Data System (ADS)

Bushey, Dean E.

A documented shortage of technical leadership and top-tier performers in computer science jeopardizes the technological edge, security, and economic well-being of the nation. The 2005 President's Information and Technology Advisory Committee (PITAC) Report on competitiveness in computational sciences highlights the major impact of science, technology, and innovation in keeping America competitive in the global marketplace. It stresses the fact that the supply of science, technology, and engineering experts is at the core of America's technological edge, national competitiveness and security. However, recent data shows that both undergraduate and postgraduate production of computer scientists is falling. The decline is "a quiet crisis building in the United States," a crisis that, if allowed to continue unchecked, could endanger America's well-being and preeminence among the world's nations. Past research on expert performance has shown that the cognitive traits of critical thinking, creativity, and problem solving possessed by top-tier performers can be identified, observed and measured. The studies show that the identified attributes are applicable across many domains and disciplines. Companies have begun to realize that cognitive skills are important for high-level performance and are reevaluating the traditional academic standards they have used to predict success for their top-tier performers in computer science. Previous research in the computer science field has focused either on programming skills of its experts or has attempted to predict the academic success of students at the undergraduate level. This study, on the other hand, examines the critical-thinking skills found among experts in the computer science field in order to explore the questions, "What cognitive skills do outstanding performers possess that make them successful?" and "How do currently used measures of academic performance correlate to critical-thinking skills among students?" The results of this study suggest a need to examine how critical-thinking abilities are learned in the undergraduate computer science curriculum and the need to foster these abilities in order to produce the high-level, critical-thinking professionals necessary to fill the growing need for these experts. Due to the fact that current measures of academic performance do not adequately depict students' cognitive abilities, assessment of these skills must be incorporated into existing curricula.

Genetic influence on athletic performance

PubMed Central

Guth, Lisa M.; Roth, Stephen M.

2014-01-01

Purpose of review The purpose of this review is to summarize the existing literature on the genetics of athletic performance, with particular consideration for the relevance to young athletes. Recent findings Two gene variants, ACE I/D and ACTN3 R577X, have been consistently associated with endurance (ACE I/I) and power-related (ACTN3 R/R) performance, though neither can be considered predictive. The role of genetic variation in injury risk and outcomes is more sparsely studied, but genetic testing for injury susceptibility could be beneficial in protecting young athletes from serious injury. Little information on the association of genetic variation with athletic performance in young athletes is available; however, genetic testing is becoming more popular as a means of talent identification. Despite this increase in the use of such testing, evidence is lacking for the usefulness of genetic testing over traditional talent selection techniques in predicting athletic ability, and careful consideration should be given to the ethical issues surrounding such testing in children. Summary A favorable genetic profile, when combined with an optimal training environment, is important for elite athletic performance; however, few genes are consistently associated with elite athletic performance, and none are linked strongly enough to warrant their use in predicting athletic success. PMID:24240283

Learning and Study Strategies Inventory subtests and factors as predictors of National Board of Chiropractic Examiners Part 1 examination performance.

PubMed

Schutz, Christine M; Dalton, Leanne; Tepe, Rodger E

2013-01-01

This study was designed to extend research on the relationship between chiropractic students' learning and study strategies and national board examination performance. Sixty-nine first trimester chiropractic students self-administered the Learning and Study Strategies Inventory (LASSI). Linear trends tests (for continuous variables) and Mantel-Haenszel trend tests (for categorical variables) were utilized to determine if the 10 LASSI subtests and 3 factors predicted low, medium and high levels of National Board of Chiropractic Examiners (NBCE) Part 1 scores. Multiple regression was performed to predict overall mean NBCE examination scores using the 3 LASSI factors as predictor variables. Four LASSI subtests (Anxiety, Concentration, Selecting Main Ideas, Test Strategies) and one factor (Goal Orientation) were significantly associated with NBCE examination levels. One factor (Goal Orientation) was a significant predictor of overall mean NBCE examination performance. Learning and study strategies are predictive of NBCE Part 1 examination performance in chiropractic students. The current study found LASSI subtests Anxiety, Concentration, Selecting Main Ideas, and Test Strategies, and the Goal-Orientation factor to be significant predictors of NBCE scores. The LASSI may be useful to educators in preparing students for academic success. Further research is warranted to explore the effects of learning and study strategies training on GPA and NBCE performance.

Selection for Surgical Training: An Evidence-Based Review.

PubMed

Schaverien, Mark V

2016-01-01

The predictive relationship between candidate selection criteria for surgical training programs and future performance during and at the completion of training has been investigated for several surgical specialties, however there is no interspecialty agreement regarding which selection criteria should be used. Better understanding the predictive reliability between factors at selection and future performance may help to optimize the process and lead to greater standardization of the surgical selection process. PubMed and Ovid MEDLINE databases were searched. Over 560 potentially relevant publications were identified using the search strategy and screened using the Cochrane Collaboration Data Extraction and Assessment Template. 57 studies met the inclusion criteria. Several selection criteria used in the traditional selection demonstrated inconsistent correlation with subsequent performance during and at the end of surgical training. The following selection criteria, however, demonstrated good predictive relationships with subsequent resident performance: USMLE examination scores, Letters of Recommendation (LOR) including the Medical Student Performance Evaluation (MSPE), academic performance during clinical clerkships, the interview process, displaying excellence in extracurricular activities, and the use of unadjusted rank lists. This systematic review supports that the current selection process needs to be further evaluated and improved. Multicenter studies using standardized outcome measures of success are now required to improve the reliability of the selection process to select the best trainees. Published by Elsevier Inc.

Use of a machine learning framework to predict substance use disorder treatment success

PubMed Central

Kelmansky, Diana; van der Laan, Mark; Sahker, Ethan; Jones, DeShauna; Arndt, Stephan

2017-01-01

There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitates this decision by combining all identified prediction algorithms pertinent for a particular prediction problem. SL generates a final model that is at least as good as any of the other models considered for predicting the outcome. The overarching aim of this work is to introduce SL to analysts and practitioners. This work compares the performance of logistic regression, penalized regression, random forests, deep learning neural networks, and SL to predict successful substance use disorders (SUD) treatment. A nationwide database including 99,013 SUD treatment patients was used. All algorithms were evaluated using the area under the receiver operating characteristic curve (AUC) in a test sample that was not included in the training sample used to fit the prediction models. AUC for the models ranged between 0.793 and 0.820. SL was superior to all but one of the algorithms compared. An explanation of SL steps is provided. SL is the first step in targeted learning, an analytic framework that yields double robust effect estimation and inference with fewer assumptions than the usual parametric methods. Different aspects of SL depending on the context, its function within the targeted learning framework, and the benefits of this methodology in the addiction field are discussed. PMID:28394905

Use of a machine learning framework to predict substance use disorder treatment success.

PubMed

Acion, Laura; Kelmansky, Diana; van der Laan, Mark; Sahker, Ethan; Jones, DeShauna; Arndt, Stephan

2017-01-01

There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitates this decision by combining all identified prediction algorithms pertinent for a particular prediction problem. SL generates a final model that is at least as good as any of the other models considered for predicting the outcome. The overarching aim of this work is to introduce SL to analysts and practitioners. This work compares the performance of logistic regression, penalized regression, random forests, deep learning neural networks, and SL to predict successful substance use disorders (SUD) treatment. A nationwide database including 99,013 SUD treatment patients was used. All algorithms were evaluated using the area under the receiver operating characteristic curve (AUC) in a test sample that was not included in the training sample used to fit the prediction models. AUC for the models ranged between 0.793 and 0.820. SL was superior to all but one of the algorithms compared. An explanation of SL steps is provided. SL is the first step in targeted learning, an analytic framework that yields double robust effect estimation and inference with fewer assumptions than the usual parametric methods. Different aspects of SL depending on the context, its function within the targeted learning framework, and the benefits of this methodology in the addiction field are discussed.

Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC.

PubMed

Contreras-Torres, Ernesto

2018-06-02

In this study, I introduce novel global and local 0D-protein descriptors based on a statistical quantity named Total Sum of Squares (TSS). This quantity represents the sum of the squares differences of amino acid properties from the arithmetic mean property. As an extension, the amino acid-types and amino acid-groups formalisms are used for describing zones of interest in proteins. To assess the effectiveness of the proposed descriptors, a Nearest Neighbor model for predicting the major four protein structural classes was built. This model has a success rate of 98.53% on the jackknife cross-validation test; this performance being superior to other reported methods despite the simplicity of the predictor. Additionally, this predictor has an average success rate of 98.35% in different cross-validation tests performed. A value of 0.98 for the Kappa statistic clearly discriminates this model from a random predictor. The results obtained by the Nearest Neighbor model demonstrated the ability of the proposed descriptors not only to reflect relevant biochemical information related to the structural classes of proteins but also to allow appropriate interpretability. It can thus be expected that the current method may play a supplementary role to other existing approaches for protein structural class prediction and other protein attributes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Personal factors that influence deaf college students' academic success.

PubMed

Albertini, John A; Kelly, Ronald R; Matchett, Mary Karol

2012-01-01

Research tells us that academic preparation is key to deaf students' success at college. Yet, that is not the whole story. Many academically prepared students drop out during their first year. This study identified entering deaf college students' personal factors as assessed by their individual responses to both the Noel-Levitz College Student Inventory Form B and the Learning and Study Strategies Inventory, second edition (LASSI). Entering students in 3 successive cohorts (total n =437) participated in this study. Results show that in addition to entry measurements of reading and mathematic skills, personal factors contributed to the academic performance of students in their first quarter in college. The Noel-Levitz provided the comparatively better predictive value of academic performance: Motivation for Academic Study Scale (e.g., desire to finish college). The LASSI also showed statistically significant predictors, the Self-Regulation Component (e.g., time management) and Will Component (e.g., self-discipline), but accounted for relatively less variability in the students' initial grade point averages. For this group of underprepared students, results show that personal factors can play a significant role in academic success. Deaf students' personal factors are discussed as they relate to other first-year college students and to their subsequent academic performance and persistence.

Self-Presentation Strategies, Fear of Success and Anticipation of Future Success among University and High School Students.

PubMed

Kosakowska-Berezecka, Natasza; Jurek, Paweł; Besta, Tomasz; Badowska, Sylwia

2017-01-01

The backlash avoidance model (BAM) suggests women insufficiently self-promote because they fear backlash for behavior which is incongruent with traditional gender roles. Avoiding self-promoting behavior is also potentially related to associating success with negative consequences. In two studies we tested whether self-promotion and fear of success will be predictors of lower salaries and anticipation of lower chances of success in an exam. In study 1, prior to the exam they were about to take, we asked 234 students about their predictions concerning exam results and their future earnings. They also filled scales measuring their associations with success (fear of success) and tendency for self-promotion. The tested model proved that in comparison to men, women expect lower salaries in the future, anticipate lower test performance and associate success with more negative consequences. Both tendency for self-promotion and fear of success are related to anticipation of success in test performance and expectations concerning future earnings. In study 2 we repeated the procedure on a sample of younger female and male high school pupils ( N = 100) to verify whether associating success with negative consequences and differences in self-promotion strategies are observable in a younger demographic. Our results show that girls and boys in high school do not differ with regard to fear of success, self-promotion or agency levels. Girls and boys anticipated to obtain similar results in math exam results, but girls expected to have higher results in language exams. Nevertheless, school pupils also differed regarding their future earnings but only in the short term. Fear of success and agency self-ratings were significant predictors of expectations concerning future earnings, but only among high school boys and with regard to earnings expected just after graduation.

Self-Presentation Strategies, Fear of Success and Anticipation of Future Success among University and High School Students

PubMed Central

Kosakowska-Berezecka, Natasza; Jurek, Paweł; Besta, Tomasz; Badowska, Sylwia

2017-01-01

The backlash avoidance model (BAM) suggests women insufficiently self-promote because they fear backlash for behavior which is incongruent with traditional gender roles. Avoiding self-promoting behavior is also potentially related to associating success with negative consequences. In two studies we tested whether self-promotion and fear of success will be predictors of lower salaries and anticipation of lower chances of success in an exam. In study 1, prior to the exam they were about to take, we asked 234 students about their predictions concerning exam results and their future earnings. They also filled scales measuring their associations with success (fear of success) and tendency for self-promotion. The tested model proved that in comparison to men, women expect lower salaries in the future, anticipate lower test performance and associate success with more negative consequences. Both tendency for self-promotion and fear of success are related to anticipation of success in test performance and expectations concerning future earnings. In study 2 we repeated the procedure on a sample of younger female and male high school pupils (N = 100) to verify whether associating success with negative consequences and differences in self-promotion strategies are observable in a younger demographic. Our results show that girls and boys in high school do not differ with regard to fear of success, self-promotion or agency levels. Girls and boys anticipated to obtain similar results in math exam results, but girls expected to have higher results in language exams. Nevertheless, school pupils also differed regarding their future earnings but only in the short term. Fear of success and agency self-ratings were significant predictors of expectations concerning future earnings, but only among high school boys and with regard to earnings expected just after graduation. PMID:29163271

Performance of Earthquake Early Warning Systems during the Major Events of the 2016-2017 Central Italy Seismic Sequence.

NASA Astrophysics Data System (ADS)

Festa, G.; Picozzi, M.; Alessandro, C.; Colombelli, S.; Cattaneo, M.; Chiaraluce, L.; Elia, L.; Martino, C.; Marzorati, S.; Supino, M.; Zollo, A.

2017-12-01

Earthquake early warning systems (EEWS) are systems nowadays contributing to the seismic risk mitigation actions, both in terms of losses and societal resilience, by issuing an alert promptly after the earthquake origin and before the ground shaking impacts the targets to be protected. EEWS systems can be grouped in two main classes: network based and stand-alone systems. Network based EEWS make use of dense seismic networks surrounding the fault (e.g. Near Fault Observatory; NFO) generating the event. The rapid processing of the P-wave early portion allows for the location and magnitude estimation of the event then used to predict the shaking through ground motion prediction equations. Stand-alone systems instead analyze the early P-wave signal to predict the ground shaking carried by the late S or surface waves, through empirically calibrated scaling relationships, at the recording site itself. We compared the network-based (PRESTo, PRobabilistic and Evolutionary early warning SysTem, www.prestoews.org, Satriano et al., 2011) and the stand-alone (SAVE, on-Site-Alert-leVEl, Caruso et al., 2017) systems, by analyzing their performance during the 2016-2017 Central Italy sequence. We analyzed 9 earthquakes having magnitude 5.0 < M < 6.5 at about 200 stations located within 200 km from the epicentral area, including stations of The Altotiberina NFO (TABOO). Performances are evaluated in terms of rate of success of ground shaking intensity prediction and available lead-time, i.e. the time available for security actions. PRESTo also evaluated the accuracy of location and magnitude. Both systems well predict the ground shaking nearby the event source, with a success rate around 90% within the potential damage zone. The lead-time is significantly larger for the network based system, increasing to more than 10s at 40 km from the event epicentre. The stand-alone system better performs in the near-source region showing a positive albeit small lead-time (<3s). Far away from the source, the performances slightly degrade, mostly owing to uncertain calibration of attenuation relationships. This study opens to the possibility of making EEWS operational in Italy, based on the available acceleration networks, by improving the capability of reducing the lead-time related to data telemetry.

A Bayesian network approach to predicting nest presence of thefederally-threatened piping plover (Charadrius melodus) using barrier island features

USGS Publications Warehouse

Gieder, Katherina D.; Karpanty, Sarah M.; Fraser, James D.; Catlin, Daniel H.; Gutierrez, Benjamin T.; Plant, Nathaniel G.; Turecek, Aaron M.; Thieler, E. Robert

2014-01-01

Sea-level rise and human development pose significant threats to shorebirds, particularly for species that utilize barrier island habitat. The piping plover (Charadrius melodus) is a federally-listed shorebird that nests on barrier islands and rapidly responds to changes in its physical environment, making it an excellent species with which to model how shorebird species may respond to habitat change related to sea-level rise and human development. The uncertainty and complexity in predicting sea-level rise, the responses of barrier island habitats to sea-level rise, and the responses of species to sea-level rise and human development necessitate a modelling approach that can link species to the physical habitat features that will be altered by changes in sea level and human development. We used a Bayesian network framework to develop a model that links piping plover nest presence to the physical features of their nesting habitat on a barrier island that is impacted by sea-level rise and human development, using three years of data (1999, 2002, and 2008) from Assateague Island National Seashore in Maryland. Our model performance results showed that we were able to successfully predict nest presence given a wide range of physical conditions within the model’s dataset. We found that model predictions were more successful when the range of physical conditions included in model development was varied rather than when those physical conditions were narrow. We also found that all model predictions had fewer false negatives (nests predicted to be absent when they were actually present in the dataset) than false positives (nests predicted to be present when they were actually absent in the dataset), indicating that our model correctly predicted nest presence better than nest absence. These results indicated that our approach of using a Bayesian network to link specific physical features to nest presence will be useful for modelling impacts of sea-level rise- or human-related habitat change on barrier islands. We recommend that potential users of this method utilize multiple years of data that represent a wide range of physical conditions in model development, because the model performed less well when constructed using a narrow range of physical conditions. Further, given that there will always be some uncertainty in predictions of future physical habitat conditions related to sea-level rise and/or human development, predictive models will perform best when developed using multiple, varied years of data input.

Shared vision promotes family firm performance.

PubMed

Neff, John E

2015-01-01

A clear picture of the influential drivers of private family firm performance has proven to be an elusive target. The unique characteristics of private family owned firms necessitate a broader, non-financial approach to reveal firm performance drivers. This research study sought to specify and evaluate the themes that distinguish successful family firms from less successful family firms. In addition, this study explored the possibility that these themes collectively form an effective organizational culture that improves longer-term firm performance. At an organizational level of analysis, research findings identified four significant variables: Shared Vision (PNS), Role Clarity (RCL), Confidence in Management (CON), and Professional Networking (OLN) that positively impacted family firm financial performance. Shared Vision exhibited the strongest positive influence among the significant factors. In addition, Family Functionality (APGAR), the functional integrity of the family itself, exhibited a significant supporting role. Taken together, the variables collectively represent an effective family business culture (EFBC) that positively impacted the long-term financial sustainability of family owned firms. The index of effective family business culture also exhibited potential as a predictive non-financial model of family firm performance.

Shared vision promotes family firm performance

PubMed Central

Neff, John E.

2015-01-01

A clear picture of the influential drivers of private family firm performance has proven to be an elusive target. The unique characteristics of private family owned firms necessitate a broader, non-financial approach to reveal firm performance drivers. This research study sought to specify and evaluate the themes that distinguish successful family firms from less successful family firms. In addition, this study explored the possibility that these themes collectively form an effective organizational culture that improves longer-term firm performance. At an organizational level of analysis, research findings identified four significant variables: Shared Vision (PNS), Role Clarity (RCL), Confidence in Management (CON), and Professional Networking (OLN) that positively impacted family firm financial performance. Shared Vision exhibited the strongest positive influence among the significant factors. In addition, Family Functionality (APGAR), the functional integrity of the family itself, exhibited a significant supporting role. Taken together, the variables collectively represent an effective family business culture (EFBC) that positively impacted the long-term financial sustainability of family owned firms. The index of effective family business culture also exhibited potential as a predictive non-financial model of family firm performance. PMID:26042075

When is prior ureteral stent placement necessary to access the upper urinary tract in prepubertal children?

PubMed

Corcoran, Anthony T; Smaldone, Marc C; Mally, Dev; Ost, Michael C; Bellinger, Mark F; Schneck, Francis X; Docimo, Steven G; Wu, Hsi-Yang

2008-10-01

We studied the possibility that age, height, weight and body mass index could be used to predict the likelihood of successful ureteroscopic access to the upper urinary tract without previous stent placement in prepubertal children. We retrospectively reviewed all ureteroscopic procedures for upper tract calculi in prepubertal children from 2003 to 2007. We compared age, height, weight and body mass index in patients who underwent successful primary flexible ureteroscopic access and in those who required initial stent placement to perform ureteroscopy. Successful primary ureteroscopic access to the upper tract was achieved in 18 of 30 patients (60%). There was no difference in mean age (9.9 vs 9.5 years, p = 0.8), height (132 vs 128 cm, p = 0.6), weight (37 vs 36 kg, p = 0.86) or body mass index (19.3 vs 20.5 kg/m(2), p = 0.55) between patients with successful vs unsuccessful upper tract access. Locations that prevented access to the upper urinary tract were evenly distributed among the ureteral orifice, iliac vessels and ureteropelvic junction. Age, height, weight and body mass index could not predict the likelihood of successful ureteroscopic access to the upper tract. Placement of a ureteral stent for passive ureteral dilation is not necessary for successful ureteroscopic access to the renal pelvis in prepubertal children. An initial attempt at ureteroscopy, with placement of a ureteral stent if upper tract access is unsuccessful, decreases the number of procedures while maintaining a low complication rate.

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

The rise of deep learning in drug discovery.

PubMed

Chen, Hongming; Engkvist, Ola; Wang, Yinhai; Olivecrona, Marcus; Blaschke, Thomas

2018-06-01

Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other machine learning algorithms in areas such as image and voice recognition, natural language processing, among others. The first wave of applications of deep learning in pharmaceutical research has emerged in recent years, and its utility has gone beyond bioactivity predictions and has shown promise in addressing diverse problems in drug discovery. Examples will be discussed covering bioactivity prediction, de novo molecular design, synthesis prediction and biological image analysis. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evaluating the complementary roles of an SJT and academic assessment for entry into clinical practice.

PubMed

Cousans, Fran; Patterson, Fiona; Edwards, Helena; Walker, Kim; McLachlan, John C; Good, David

2017-05-01

Although there is extensive evidence confirming the predictive validity of situational judgement tests (SJTs) in medical education, there remains a shortage of evidence for their predictive validity for performance of postgraduate trainees in their first role in clinical practice. Moreover, to date few researchers have empirically examined the complementary roles of academic and non-academic selection methods in predicting in-role performance. This is an important area of enquiry as despite it being common practice to use both types of methods within a selection system, there is currently no evidence that this approach translates into increased predictive validity of the selection system as a whole, over that achieved by the use of a single selection method. In this preliminary study, the majority of the range of scores achieved by successful applicants to the UK Foundation Programme provided a unique opportunity to address both of these areas of enquiry. Sampling targeted high (>80th percentile) and low (<20th percentile) scorers on the SJT. Supervisors rated 391 trainees' in-role performance, and incidence of remedial action was collected. SJT and academic performance scores correlated with supervisor ratings (r = .31 and .28, respectively). The relationship was stronger between the SJT and in-role performance for the low scoring group (r = .33, high scoring group r = .11), and between academic performance and in-role performance for the high scoring group (r = .29, low scoring group r = .11). Trainees with low SJT scores were almost five times more likely to receive remedial action. Results indicate that an SJT for entry into trainee physicians' first role in clinical practice has good predictive validity of supervisor-rated performance and incidence of remedial action. In addition, an SJT and a measure of academic performance appeared to be complementary to each other. These initial findings suggest that SJTs may be more predictive at the lower end of a scoring distribution, and academic attainment more predictive at the higher end.

Modeling of impulsive propellant reorientation

NASA Technical Reports Server (NTRS)

Hochstein, John I.; Patag, Alfredo E.; Chato, David J.

1988-01-01

The impulsive propellant reorientation process is modeled using the (Energy Calculations for Liquid Propellants in a Space Environment (ECLIPSE) code. A brief description of the process and the computational model is presented. Code validation is documented via comparison to experimentally derived data for small scale tanks. Predictions of reorientation performance are presented for two tanks designed for use in flight experiments and for a proposed full scale OTV tank. A new dimensionless parameter is developed to correlate reorientation performance in geometrically similar tanks. Its success is demonstrated.

Predicting successful dental examinations for children with autism spectrum disorder in the context of a dental desensitization program.

PubMed

Nelson, Travis; Chim, Amelia; Sheller, Barbara L; McKinney, Christy M; Scott, JoAnna M

2017-07-01

The authors evaluated the effectiveness of a dental desensitization program for children with autism spectrum disorder (ASD) and determined characteristics associated with a successful dental examination. The authors performed a retrospective review of clinical behavioral data and previsit questionnaires for 168 children with ASD who attended a university-based dental desensitization program. Data elements included demographic, treatment, and behavioral characteristics. The primary outcome was receiving a minimal threshold examination (MTE) while seated in a dental chair. An MTE was achieved for 77.4% of all children within 1 to 2 visits and 87.5% in 5 visits or less. Several factors predicted a successful dental examination: ability to be involved in group activities (relative risk [RR], 1.18; P = .02), ability to communicate verbally (RR, 1.17; P < .01), understanding of most language (RR, 1.14; P = .02), moderate versus severe caregiver-rated ASD severity (RR, 1.24; P = .04), and ability to dress self (RR, 1.27; P = .04). Desensitization was effective in achieving an MTE for most children. Those with characteristics consistent of a milder presentation of ASD were more likely to be successful. Desensitization can be a successful approach to providing dental care for children with ASD. Copyright © 2017 American Dental Association. Published by Elsevier Inc. All rights reserved.

The roles of climate, phylogenetic relatedness, introduction effort, and reproductive traits in the establishment of non-native reptiles and amphibians.

PubMed

van Wilgen, Nicola J; Richardson, David M

2012-04-01

We developed a method to predict the potential of non-native reptiles and amphibians (herpetofauna) to establish populations. This method may inform efforts to prevent the introduction of invasive non-native species. We used boosted regression trees to determine whether nine variables influence establishment success of introduced herpetofauna in California and Florida. We used an independent data set to assess model performance. Propagule pressure was the variable most strongly associated with establishment success. Species with short juvenile periods and species with phylogenetically more distant relatives in regional biotas were more likely to establish than species that start breeding later and those that have close relatives. Average climate match (the similarity of climate between native and non-native range) and life form were also important. Frogs and lizards were the taxonomic groups most likely to establish, whereas a much lower proportion of snakes and turtles established. We used results from our best model to compile a spreadsheet-based model for easy use and interpretation. Probability scores obtained from the spreadsheet model were strongly correlated with establishment success as were probabilities predicted for independent data by the boosted regression tree model. However, the error rate for predictions made with independent data was much higher than with cross validation using training data. This difference in predictive power does not preclude use of the model to assess the probability of establishment of herpetofauna because (1) the independent data had no information for two variables (meaning the full predictive capacity of the model could not be realized) and (2) the model structure is consistent with the recent literature on the primary determinants of establishment success for herpetofauna. It may still be difficult to predict the establishment probability of poorly studied taxa, but it is clear that non-native species (especially lizards and frogs) that mature early and come from environments similar to that of the introduction region have the highest probability of establishment. ©2012 Society for Conservation Biology.

The predictive ability of critical thinking, nursing GPA, and SAT scores on first-time NCLEX-RN performance.

PubMed

Romeo, Elizabeth M

2013-01-01

This study was conducted to investigate the predictability of several variables in achieving first-time success on the NCLEX-RN. Several researchers have attempted to investigate the differences between students who passed the NCLEX-RN the first time and those who failed. No studies used a large enough failure group to have statistical significance. The three specific variables in this study were nursing GPA, SAT combined math and verbal scores, and critical thinking measured on a standardized assessment examination. An ex post facto study design was used to examine data from the records of associate degree nursing graduates during a three-year period. The most significant predictors of NCLEX-RN success were the students' nursing GPA and the overall standardized assessment examination score. The findings of this study could potentially influence the identification of students at risk for NCLEX-RN failure.

What predicts successful literacy acquisition in a second language?

PubMed Central

Frost, Ram; Siegelman, Noam; Narkiss, Alona; Afek, Liron

2013-01-01

We examined whether success (or failure) in assimilating the structure of a second language could be predicted by general statistical learning abilities that are non-linguistic in nature. We employed a visual statistical learning (VSL) task, monitoring our participants’ implicit learning of the transitional probabilities of visual shapes. A pretest revealed that performance in the VSL task is not correlated with abilities related to a general G factor or working memory. We found that native speakers of English who picked up the implicit statistical structure embedded in the continuous stream of shapes, on average, better assimilated the Semitic structure of Hebrew words. Our findings thus suggest that languages and their writing systems are characterized by idiosyncratic correlations of form and meaning, and these are picked up in the process of literacy acquisition, as they are picked up in any other type of learning, for the purpose of making sense of the environment. PMID:23698615

Interoceptive Ability Predicts Survival on a London Trading Floor.

PubMed

Kandasamy, Narayanan; Garfinkel, Sarah N; Page, Lionel; Hardy, Ben; Critchley, Hugo D; Gurnell, Mark; Coates, John M

2016-09-19

Interoception is the sensing of physiological signals originating inside the body, such as hunger, pain and heart rate. People with greater sensitivity to interoceptive signals, as measured by, for example, tests of heart beat detection, perform better in laboratory studies of risky decision-making. However, there has been little field work to determine if interoceptive sensitivity contributes to success in real-world, high-stakes risk taking. Here, we report on a study in which we quantified heartbeat detection skills in a group of financial traders working on a London trading floor. We found that traders are better able to perceive their own heartbeats than matched controls from the non-trading population. Moreover, the interoceptive ability of traders predicted their relative profitability, and strikingly, how long they survived in the financial markets. Our results suggest that signals from the body - the gut feelings of financial lore - contribute to success in the markets.

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

PubMed Central

Brazeal, Kathleen R.; Couch, Brian A.

2017-01-01

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

Ecological prediction with nonlinear multivariate time-frequency functional data models

USGS Publications Warehouse

Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

2013-01-01

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

Predicting Slag Generation in Sub-Scale Test Motors Using a Neural Network

NASA Technical Reports Server (NTRS)

Wiesenberg, Brent

1999-01-01

Generation of slag (aluminum oxide) is an important issue for the Reusable Solid Rocket Motor (RSRM). Thiokol performed testing to quantify the relationship between raw material variations and slag generation in solid propellants by testing sub-scale motors cast with propellant containing various combinations of aluminum fuel and ammonium perchlorate (AP) oxidizer particle sizes. The test data were analyzed using statistical methods and an artificial neural network. This paper primarily addresses the neural network results with some comparisons to the statistical results. The neural network showed that the particle sizes of both the aluminum and unground AP have a measurable effect on slag generation. The neural network analysis showed that aluminum particle size is the dominant driver in slag generation, about 40% more influential than AP. The network predictions of the amount of slag produced during firing of sub-scale motors were 16% better than the predictions of a statistically derived empirical equation. Another neural network successfully characterized the slag generated during full-scale motor tests. The success is attributable to the ability of neural networks to characterize multiple complex factors including interactions that affect slag generation.

PREDICTIVE MEASURES OF A RESIDENT'S PERFORMANCE ON WRITTEN ORTHOPAEDIC BOARD SCORES

PubMed Central

Dyrstad, Bradley W; Pope, David; Milbrandt, Joseph C; Beck, Ryan T; Weinhoeft, Anita L.; Idusuyi, Osaretin B

2011-01-01

Objective Residency programs are continually attempting to predict the performance of both current and potential residents. Previous studies have supported the use of USMLE Steps 1 and 2 as predictors of Orthopaedic In-Training Examination (OITE) and eventual American Board of Orthopaedic Surgery success, while others show no significant correlation. A strong performance on OITE examinations does correlate with strong residency performance, and some believe OITE scores are good predictors of future written board success. The current study was designed to examine potential differences in resident assessment measures and their predictive value for written boards. Design/Methods A retrospective review of resident performance data was performed for the past 10 years. Personalized information was removed by the residency coordinator. USMLE Step 1, USMLE Step 2, Orthopaedic In-Training Examination (from first to fifth years of training), and written orthopaedic specialty board scores were collected. Subsequently, the residents were separated into two groups, those scoring above the 35th percentile on written boards and those scoring below. Data were analyzed using correlation and regression analyses to compare and contrast the scores across all tests. Results A significant difference was seen between the groups in regard to USMLE scores for both Step 1 and 2. Also, a significant difference was found between OITE scores for both the second and fifth years. Positive correlations were found for USMLE Step 1, Step 2, OITE 2 and OITE 5 when compared to performance on written boards. One resident initially failed written boards, but passed on the second attempt This resident consistently scored in the 20th and 30th percentiles on the in-training examinations. Conclusions USMLE Step 1 and 2 scores along with OITE scores are helpful in gauging an orthopaedic resident’s performance on written boards. Lower USMLE scores along with consistently low OITE scores likely identify residents at risk of failing their written boards. Close monitoring of the annual OITE scores is recommended and may be useful to identify struggling residents. Future work involving multiple institutions is warranted and would ensure applicability of our findings to other orthopedic residency programs. PMID:22096449

A scoring function based on solvation thermodynamics for protein structure prediction

PubMed Central

Du, Shiqiao; Harano, Yuichi; Kinoshita, Masahiro; Sakurai, Minoru

2012-01-01

We predict protein structure using our recently developed free energy function for describing protein stability, which is focused on solvation thermodynamics. The function is combined with the current most reliable sampling methods, i.e., fragment assembly (FA) and comparative modeling (CM). The prediction is tested using 11 small proteins for which high-resolution crystal structures are available. For 8 of these proteins, sequence similarities are found in the database, and the prediction is performed with CM. Fairly accurate models with average Cα root mean square deviation (RMSD) ∼ 2.0 Å are successfully obtained for all cases. For the rest of the target proteins, we perform the prediction following FA protocols. For 2 cases, we obtain predicted models with an RMSD ∼ 3.0 Å as the best-scored structures. For the other case, the RMSD remains larger than 7 Å. For all the 11 target proteins, our scoring function identifies the experimentally determined native structure as the best structure. Starting from the predicted structure, replica exchange molecular dynamics is performed to further refine the structures. However, we are unable to improve its RMSD toward the experimental structure. The exhaustive sampling by coarse-grained normal mode analysis around the native structures reveals that our function has a linear correlation with RMSDs < 3.0 Å. These results suggest that the function is quite reliable for the protein structure prediction while the sampling method remains one of the major limiting factors in it. The aspects through which the methodology could further be improved are discussed. PMID:27493529

Retrospective evaluation of a method to predict fresh-frozen plasma dosage in anticoagulated patients.

PubMed

Frazee, Lawrence A; Bourguet, Claire C; Gutierrez, Wilson; Elder-Arrington, Jacinta; Elackattu, Alphi E P; Haller, Nairmeen Awad

2008-01-01

In the United States, fresh-frozen plasma (FFP) is commonly used for urgent reversal of warfarin; however, dosage recommendations are difficult to find. If validated, a proposed method that uses a nonlinear relationship between international normalized ratio (INR) and clotting factor activity (CFa) would be useful. This study retrospectively evaluated a proposed equation with adult medical inpatients who received FFP for warfarin reversal. For each patient the equation was used to predict the dose of FFP required to achieve the observed change in INR, which was then compared to the actual dose. The equation was considered successful if the predicted dose was within +/-20% of the actual dose. Subgroup analyses included subjects who received concomitant vitamin K; subjects with supratherapeutic INRs (>3); and subjects with significantly elevated INRs (>5). Of the 209 patients screened, 91 met criteria for inclusion in the study. Use of the equation to calculate the predicted dose of FFP was successful in 11 patients (12.1%) with use of actual body weight for prediction and in 23 patients (25.3%) with use of ideal body weight (P = 0.02). The equation performed similarly in all subgroups analyzed. The mean predicted FFP dose was significantly greater than the actual dose in all patients when actual body weight was used (925.2 mL vs. 620.6 mL; P < 0.001). Least-squares regression modeling of repeat INR (converted to CFa) produced a model that accounted for 57% of the variance in repeat INR. The value predicted from the model was closer to the actual CFa than was the value predicted from the published equation in every comparison, but it was statistically different only when actual body weight was used. This study revealed that a published equation for calculation of FFP dose to reverse oral anticoagulation resulted in doses that were significantly higher than the actual dose. Use of ideal body weight improved accuracy but was still not successful for the majority of patients. Until trials are able to prospectively demonstrate the accuracy of a dose-prediction model for FFP, dosing will remain largely empiric.

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

PubMed

Robbins, Daniel W

2010-11-01

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

Turbopumps for cryogenic upper stage engines. [fabrication and evaluation of turbine pumps for liquid hydrogen and liquid oxygen

NASA Technical Reports Server (NTRS)

Zachary, A. T.; Csomor, A.; Tignac, L. L.

1973-01-01

Small, high-performance LO2 and LH2 turbopump assembly configurations were selected, detail designs were prepared and two of each unit were fabricated with each unit consisting of pump, turbine gas generator, and appropriate controls. Following fabrication, development testing was conducted on each type to demonstrate performance, durability, transient characteristics, and heat transfer under simulated altitude conditions. Following successful completion of development effort, the two LO2 turbopump units and one LH2 turbopump unit were acceptance tested as specified. Inspection of the units following development testing revealed no deleterious effects of testing. The test results of LO2 turbopump assembly testing correlated well with predicted performance while the LH2 turbopump test results, though generally consistent with predicted values, did show lower than anticipated developed head at the design point and in the high flow range of operation.

Numerical Modeling of STARx for Ex Situ Soil Remediation

NASA Astrophysics Data System (ADS)

Gerhard, J.; Solinger, R. L.; Grant, G.; Scholes, G.

2016-12-01

Growing stockpiles of contaminated soils contaminated with petroleum hydrocarbons are an outstanding problem worldwide. Self-sustaining Treatment for Active Remediation (STAR) is an emerging technology based on smouldering combustion that has been successfully deployed for in situ remediation. STAR has also been developed for ex situ applications (STARx). This work used a two-dimensional numerical model to systematically explore the sensitivity of ex situ remedial performance to key design and operational parameters. First the model was calibrated and validated against pilot scale experiments, providing confidence that the rate and extent of treatment were correctly predicted. Simulations then investigated sensitivity of remedial performance to injected air flux, contaminant saturation, system configuration, heterogeneity of intrinsic permeability, heterogeneity of contaminant saturation, and system scale. Remedial performance was predicted to be most sensitive to the injected air flux, with higher air fluxes achieving higher treatment rates and remediating larger fractions of the initial contaminant mass. The uniformity of the advancing smouldering front was predicted to be highly dependent on effective permeability contrasts between treated and untreated sections of the contaminant pack. As a result, increased heterogeneity (of intrinsic permeability in particular) is predicted to lower remedial performance. Full-scale systems were predicted to achieve treatment rates an order of magnitude higher than the pilot scale for similar contaminant saturation and injected air flux. This work contributed to the large scale STARx treatment system that is being tested at a field site in Fall 2016.

How do I know what I can do? Anticipating expectancy of success regarding novel academic tasks.

PubMed

Gorges, Julia; Göke, Thomas

2015-03-01

After graduation from secondary school, academic tasks (i.e., learning contents) are no longer structured in terms of school subjects (i.e., English, mathematics). Therefore, learners lack past performance and mastery experience to inform their expectancy of success (i.e., ability beliefs) regarding novel tasks. In this paper, we investigate how individuals establish expectancy of success regarding novel academic tasks. We hypothesize that individuals draw on ability beliefs regarding known tasks that are deemed similar to novel tasks to estimate expectancy of success (generalization hypothesis). Participants were first-year students (n = 354) in the field of business administration (Study 1), and (Study 2) psychology students predominantly (n = 174). In Study 1, we analysed relations between ability beliefs (i.e., academic self-concepts of ability) regarding four school subjects and four fields of study varying in similarity. In Study 2, we assessed mastery experience regarding two school subjects and expectancy of success (i.e., self-efficacy) regarding a fictitious course manipulating participants' similarity judgement. We analysed the data using mainly structural equation modelling. Results support the generalization hypothesis regarding both indicators of expectancy of success (i.e., self-concept and self-efficacy). Subject-specific self-concepts of ability predict study-related self-concepts of ability according to individuals' similarity judgements. Subject-specific mastery experience predicts expectancy of success only if the respective school subject is emphasized in the course description. Individuals apparently draw on established ability beliefs regarding known tasks to inform their expectancy of success regarding novel tasks. Findings further our understanding of the development of motivation to learn in adulthood. © 2015 The British Psychological Society.

Modeling Spoken Word Recognition Performance by Pediatric Cochlear Implant Users using Feature Identification

PubMed Central

Frisch, Stefan A.; Pisoni, David B.

2012-01-01

Objective Computational simulations were carried out to evaluate the appropriateness of several psycholinguistic theories of spoken word recognition for children who use cochlear implants. These models also investigate the interrelations of commonly used measures of closed-set and open-set tests of speech perception. Design A software simulation of phoneme recognition performance was developed that uses feature identification scores as input. Two simulations of lexical access were developed. In one, early phoneme decisions are used in a lexical search to find the best matching candidate. In the second, phoneme decisions are made only when lexical access occurs. Simulated phoneme and word identification performance was then applied to behavioral data from the Phonetically Balanced Kindergarten test and Lexical Neighborhood Test of open-set word recognition. Simulations of performance were evaluated for children with prelingual sensorineural hearing loss who use cochlear implants with the MPEAK or SPEAK coding strategies. Results Open-set word recognition performance can be successfully predicted using feature identification scores. In addition, we observed no qualitative differences in performance between children using MPEAK and SPEAK, suggesting that both groups of children process spoken words similarly despite differences in input. Word recognition ability was best predicted in the model in which phoneme decisions were delayed until lexical access. Conclusions Closed-set feature identification and open-set word recognition focus on different, but related, levels of language processing. Additional insight for clinical intervention may be achieved by collecting both types of data. The most successful model of performance is consistent with current psycholinguistic theories of spoken word recognition. Thus it appears that the cognitive process of spoken word recognition is fundamentally the same for pediatric cochlear implant users and children and adults with normal hearing. PMID:11132784

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

PubMed Central

Tian, Yin; Zhang, Huiling; Xu, Wei; Zhang, Haiyong; Yang, Li; Zheng, Shuxing; Shi, Yupan

2017-01-01

Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed Residual Time (SRT) scores based on response speed and accuracy trade-off, 20 subjects were divided into two groups, namely high-performance and low-performance groups, to undertake working memory (WM) tasks. We found that spectral entropy derived from the retention period of WM on channel FC4 exhibited a high correlation with SRT scores. To this end, spectral entropy was used in support vector machine classifier with linear kernel to differentiate these two groups. Receiver operating characteristics analysis and leave-one out cross-validation (LOOCV) demonstrated that the averaged classification accuracy (CA) was 90.0 and 92.5% for intra-session and inter-session, respectively, indicating that spectral entropy could be used to distinguish these two different WM performance groups successfully. Furthermore, the support vector regression prediction model with radial basis function kernel and the root-mean-square error of prediction revealed that spectral entropy could be utilized to predict SRT scores on individual WM performance. After testing the changes in SRT scores and spectral entropy for each subject by short-time training, we found that 16 in 20 subjects’ SRT scores were clearly promoted after training and 15 in 20 subjects’ SRT scores showed consistent changes with spectral entropy before and after training. The findings revealed that spectral entropy could be a promising indicator to predict individual’s WM changes by training and further provide a novel application about WM for brain–computer interfaces. PMID:28912701

Load-related brain activation predicts spatial working memory performance in youth aged 9–12 and is associated with executive function at earlier ages

PubMed Central

Huang, Anna S.; Klein, Daniel N.; Leung, Hoi-Chung

2015-01-01

Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9–12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. PMID:26562059

Projecting technology change to improve space technology planning and systems management

NASA Astrophysics Data System (ADS)

Walk, Steven Robert

2011-04-01

Projecting technology performance evolution has been improving over the years. Reliable quantitative forecasting methods have been developed that project the growth, diffusion, and performance of technology in time, including projecting technology substitutions, saturation levels, and performance improvements. These forecasts can be applied at the early stages of space technology planning to better predict available future technology performance, assure the successful selection of technology, and improve technology systems management strategy. Often what is published as a technology forecast is simply scenario planning, usually made by extrapolating current trends into the future, with perhaps some subjective insight added. Typically, the accuracy of such predictions falls rapidly with distance in time. Quantitative technology forecasting (QTF), on the other hand, includes the study of historic data to identify one of or a combination of several recognized universal technology diffusion or substitution patterns. In the same manner that quantitative models of physical phenomena provide excellent predictions of system behavior, so do QTF models provide reliable technological performance trajectories. In practice, a quantitative technology forecast is completed to ascertain with confidence when the projected performance of a technology or system of technologies will occur. Such projections provide reliable time-referenced information when considering cost and performance trade-offs in maintaining, replacing, or migrating a technology, component, or system. This paper introduces various quantitative technology forecasting techniques and illustrates their practical application in space technology and technology systems management.

Load-related brain activation predicts spatial working memory performance in youth aged 9-12 and is associated with executive function at earlier ages.

PubMed

Huang, Anna S; Klein, Daniel N; Leung, Hoi-Chung

2016-02-01

Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9-12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Clinical outcomes after combined Ahmed glaucoma valve implantation and penetrating keratoplasty or pars plana vitrectomy.

PubMed

Lee, Jin Young; Sung, Kyung Rim; Tchah, Hung Won; Yoon, Young Hee; Kim, June Gone; Kim, Myoung Joon; Kim, Jae Yong; Yun, Sung-Cheol; Lee, Joo Yong

2012-12-01

To evaluate whether a combination of penetrating keratoplasty (PKP) or pars plana vitrectomy (PPV) and Ahmed glaucoma valve (AGV) implantation affords a level of success similar to that of AGV implantation alone. Eighteen eyes underwent simultaneous PPV and AGV, 14 eyes with PKP and AGV and 30 eyes with AGV implantation alone were evaluated. Success was defined as attainment of an intraocular pressure (IOP) >5 and <22 mmHg, with or without use of anti-glaucoma medication. Kaplan-Meier survival analysis was performed to compare cumulative survival between the combined surgery groups and the AGV implantation-alone group. Cox proportional hazard regression analysis was conducted to identify factors predictive of success in each of the three groups. Mean (±standard deviation) preoperative IOP was 30.2 ± 10.2 mmHg in the PKP + AGV, 35.2 ± 9.8 mmHg in the PPV + AGV, and 36.2 ± 10.1 mmHg in the AGV implantation-alone group. The cumulative success rate at 18 months was 66.9%, 73.2%, and 70.8% in the three groups, respectively. Neither combined surgery group differed significantly in terms of cumulative success rate compared with the AGV implantation-alone group (p = 0.556, p = 0.487, respectively). The mean number of preoperative anti-glaucoma medications prescribed was significantly associated with success in the PKP + AGV implantation group (hazard ratio, 2.942; p = 0.024). Either PKP or PPV performed in conjunction with AGV implantation afforded similar success rates compared to patients treated with AGV implantation alone. Therefore, in patients with refractory glaucoma who have underlying corneal or retinal pathology requiring treatment with PKP or PPV, AGV implantation can be performed simultaneously.

Analysis of the Shuttle Orbiter reinforced carbon-carbon oxidation protection system

NASA Technical Reports Server (NTRS)

Williams, S. D.; Curry, Donald M.; Chao, Dennis; Pham, Vuong T.

1994-01-01

Reusable, oxidation-protected reinforced carbon-carbon (RCC) has been successfully flown on all Shuttle Orbiter flights. Thermal testing of the silicon carbide-coated RCC to determine its oxidation characteristics has been performed in convective (plasma Arc-Jet) heating facilities. Surface sealant mass loss was characterized as a function of temperature and pressure. High-temperature testing was performed to develop coating recession correlations for predicting performance at the over-temperature flight conditions associated with abort trajectories. Methods for using these test data to establish multi-mission re-use (i.e., mission life) and single mission limits are presented.