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Sample records for model successfully predicted

  1. A Predictive Model for MSSW Student Success

    Science.gov (United States)

    Napier, Angela Michele

    2011-01-01

    This study tested a hypothetical model for predicting both graduate GPA and graduation of University of Louisville Kent School of Social Work Master of Science in Social Work (MSSW) students entering the program during the 2001-2005 school years. The preexisting characteristics of demographics, academic preparedness and culture shock along with…

  2. Models Predicting Success of Infertility Treatment: A Systematic Review

    Science.gov (United States)

    Zarinara, Alireza; Zeraati, Hojjat; Kamali, Koorosh; Mohammad, Kazem; Shahnazari, Parisa; Akhondi, Mohammad Mehdi

    2016-01-01

    Background: Infertile couples are faced with problems that affect their marital life. Infertility treatment is expensive and time consuming and occasionally isn’t simply possible. Prediction models for infertility treatment have been proposed and prediction of treatment success is a new field in infertility treatment. Because prediction of treatment success is a new need for infertile couples, this paper reviewed previous studies for catching a general concept in applicability of the models. Methods: This study was conducted as a systematic review at Avicenna Research Institute in 2015. Six data bases were searched based on WHO definitions and MESH key words. Papers about prediction models in infertility were evaluated. Results: Eighty one papers were eligible for the study. Papers covered years after 1986 and studies were designed retrospectively and prospectively. IVF prediction models have more shares in papers. Most common predictors were age, duration of infertility, ovarian and tubal problems. Conclusion: Prediction model can be clinically applied if the model can be statistically evaluated and has a good validation for treatment success. To achieve better results, the physician and the couples’ needs estimation for treatment success rate were based on history, the examination and clinical tests. Models must be checked for theoretical approach and appropriate validation. The privileges for applying the prediction models are the decrease in the cost and time, avoiding painful treatment of patients, assessment of treatment approach for physicians and decision making for health managers. The selection of the approach for designing and using these models is inevitable. PMID:27141461

  3. Improving student success using predictive models and data visualisations

    Directory of Open Access Journals (Sweden)

    Hanan Ayad

    2012-08-01

    Full Text Available The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50–60%. At the college level in the US only 30% of students graduate from 2-year colleges in 3 years or less and approximately 50% graduate from 4-year colleges in 5 years or less. A basic challenge in delivering global education, therefore, is improving student success. By student success we mean improving retention, completion and graduation rates. In this paper we describe a Student Success System (S3 that provides a holistic, analytical view of student academic progress.1 The core of S3 is a flexible predictive modelling engine that uses machine intelligence and statistical techniques to identify at-risk students pre-emptively. S3 also provides a set of advanced data visualisations for reaching diagnostic insights and a case management tool for managing interventions. S3's open modular architecture will also allow integration and plug-ins with both open and proprietary software. Powered by learning analytics, S3 is intended as an end-to-end solution for identifying at-risk students, understanding why they are at risk, designing interventions to mitigate that risk and finally closing the feedback look by tracking the efficacy of the applied intervention.

  4. Academic dropout or academic success: a model for prediction.

    Science.gov (United States)

    Kegel-Flom, P

    1986-09-01

    Why do some students who qualify for admission to optometry school become academic dropouts while others succeed? This question was addressed in a study which compared the admission records of 21 academic dropouts from three classes at the University of Houston College of Optometry (UHCO) with 269 retained students. Academic dropouts were found to have significantly lower preoptometry grades, lower Optometry College Admission Test (OCAT) scores, attended less competitive (i.e., less selective) undergraduate institutions, scored lower on the California Psychological Inventory (CPI), and were older than retained students. When these differentiating admission variables, excepting age, were applied to a new entering class, prediction of subsequent academic dismissal or serious academic difficulty was highly accurate. However, it was found that such prediction must take into account not only areas of weakness, i.e., academic and psychological factors which place a student at risk, but also areas of strength which give the student an advantage. For all students, regardless of age, sex, or ethnic origin, it was the ratio of "advantage" factors to "risk" factors which gave the most valid prediction of academic success or failure.

  5. Predicting Classroom Success.

    Science.gov (United States)

    Kessler, Ronald P.

    A study was conducted at Rancho Santiago College (RSC) to identify personal and academic factors that are predictive of students' success in their courses. The study examined the following possible predictors of success: language and math test scores; background characteristics; length of time out of high school; high school background; college…

  6. Modelled three-dimensional suction accuracy predicts prey capture success in three species of centrarchid fishes

    Science.gov (United States)

    Kane, Emily A.; Higham, Timothy E.

    2014-01-01

    Prey capture is critical for survival, and differences in correctly positioning and timing a strike (accuracy) are likely related to variation in capture success. However, an ability to quantify accuracy under natural conditions, particularly for fishes, is lacking. We developed a predictive model of suction hydrodynamics and applied it to natural behaviours using three-dimensional kinematics of three centrarchid fishes capturing evasive and non-evasive prey. A spheroid ingested volume of water (IVW) with dimensions predicted by peak gape and ram speed was verified with known hydrodynamics for two species. Differences in capture success occurred primarily with evasive prey (64–96% success). Micropterus salmoides had the greatest ram and gape when capturing evasive prey, resulting in the largest and most elongate IVW. Accuracy predicted capture success, although other factors may also be important. The lower accuracy previously observed in M. salmoides was not replicated, but this is likely due to more natural conditions in our study. Additionally, we discuss the role of modulation and integrated behaviours in shaping the IVW and determining accuracy. With our model, accuracy is a more accessible performance measure for suction-feeding fishes, which can be used to explore macroevolutionary patterns of prey capture evolution. PMID:24718455

  7. Validation of a Prediction Model for Vaginal Birth after Cesarean Delivery Reveals Unexpected Success in a Diverse American Population

    Science.gov (United States)

    Maykin, Melanie Mai; Mularz, Amanda J.; Lee, Lydia K.; Valderramos, Stephanie Gaw

    2017-01-01

    Objective To investigate the validity of a prediction model for success of vaginal birth after cesarean delivery (VBAC) in an ethnically diverse population. Methods We performed a retrospective cohort study of women admitted at a single academic institution for a trial of labor after cesarean from May 2007 to January 2015. Individual predicted success rates were calculated using the Maternal–Fetal Medicine Units Network prediction model. Participants were stratified into three probability-of-success groups: low (65%). The actual versus predicted success rates were compared. Results In total, 568 women met inclusion criteria. Successful VBAC occurred in 402 (71%), compared with a predicted success rate of 66% (p = 0.016). Actual VBAC success rates were higher than predicted by the model in the low (57 vs. 29%; p < 0.001) and moderate (61 vs. 52%; p = 0.003) groups. In the high probability group, the observed and predicted VBAC rates were the same (79%). Conclusion When the predicted success rate was above 65%, the model was highly accurate. In contrast, for women with predicted success rates <35%, actual VBAC rates were nearly twofold higher in our population, suggesting that they should not be discouraged by a low prediction score.

  8. Validation of a Prediction Model for Vaginal Birth after Cesarean Delivery Reveals Unexpected Success in a Diverse American Population.

    Science.gov (United States)

    Maykin, Melanie Mai; Mularz, Amanda J; Lee, Lydia K; Valderramos, Stephanie Gaw

    2017-01-01

    Objective To investigate the validity of a prediction model for success of vaginal birth after cesarean delivery (VBAC) in an ethnically diverse population. Methods We performed a retrospective cohort study of women admitted at a single academic institution for a trial of labor after cesarean from May 2007 to January 2015. Individual predicted success rates were calculated using the Maternal-Fetal Medicine Units Network prediction model. Participants were stratified into three probability-of-success groups: low (65%). The actual versus predicted success rates were compared. Results In total, 568 women met inclusion criteria. Successful VBAC occurred in 402 (71%), compared with a predicted success rate of 66% (p = 0.016). Actual VBAC success rates were higher than predicted by the model in the low (57 vs. 29%; p success rate was above 65%, the model was highly accurate. In contrast, for women with predicted success rates <35%, actual VBAC rates were nearly twofold higher in our population, suggesting that they should not be discouraged by a low prediction score.

  9. Hierarchical Bayesian Markov switching models with application to predicting spawning success of shovelnose sturgeon

    Science.gov (United States)

    Holan, S.H.; Davis, G.M.; Wildhaber, M.L.; DeLonay, A.J.; Papoulias, D.M.

    2009-01-01

    The timing of spawning in fish is tightly linked to environmental factors; however, these factors are not very well understood for many species. Specifically, little information is available to guide recruitment efforts for endangered species such as the sturgeon. Therefore, we propose a Bayesian hierarchical model for predicting the success of spawning of the shovelnose sturgeon which uses both biological and behavioural (longitudinal) data. In particular, we use data that were produced from a tracking study that was conducted in the Lower Missouri River. The data that were produced from this study consist of biological variables associated with readiness to spawn along with longitudinal behavioural data collected by using telemetry and archival data storage tags. These high frequency data are complex both biologically and in the underlying behavioural process. To accommodate such complexity we developed a hierarchical linear regression model that uses an eigenvalue predictor, derived from the transition probability matrix of a two-state Markov switching model with generalized auto-regressive conditional heteroscedastic dynamics. Finally, to minimize the computational burden that is associated with estimation of this model, a parallel computing approach is proposed. ?? Journal compilation 2009 Royal Statistical Society.

  10. A Model for Intervention and Predicting Success on the National Council Licensure Examination for Registered Nurses.

    Science.gov (United States)

    Heupel, Carol

    1994-01-01

    The relationship of selected academic variables to National Council Licensure Examination for Registered Nurses (NCLEX-RN) performance was studied and a "best set" of indicators predictive of NCLEX-RN success was identified. Results indicated that selected nursing theory courses and the junior year grade point average could be used to…

  11. Predicting Success in Elementary Algebra

    Science.gov (United States)

    Mogull, R. G.; Rosengarten, W., Jr.

    1974-01-01

    The purpose of this study was to develop a device for predicting student success in a high school Elementary Algebra course. It was intended to assist guidance counselors in advising students in selecting the most appropriate mathematics course. (Editor)

  12. An Empirical Test of a Comprehensive Model for Predicting Successful Information Systems Implementation

    Science.gov (United States)

    1989-12-01

    among the issues related to IS implementation success. A study by Albert Lederer and Aubrey Mendelow concentrates on just that issue. Specifically, they...Wiley & Sons, 1987. 26. Lederer, Albert L. and Aubrey L. Mendelow . "Information Systems Planning: Top Management Takes Control, Business Horizons, 31

  13. Pacific salmon in hot water: applying aerobic scope models and biotelemetry to predict the success of spawning migrations.

    Science.gov (United States)

    Farrell, A P; Hinch, S G; Cooke, S J; Patterson, D A; Crossin, G T; Lapointe, M; Mathes, M T

    2008-01-01

    Concern over global climate change is widespread, but quantifying relationships between temperature change and animal fitness has been a challenge for scientists. Our approach to this challenge was to study migratory Pacific salmon (Oncorhynchus spp.), fish whose lifetime fitness hinges on a once-in-a-lifetime river migration to natal spawning grounds. Here, we suggest that their thermal optimum for aerobic scope is adaptive for river migration at the population level. We base this suggestion on several lines of evidence. The theoretical line of evidence comes from a direct association between the temperature optimum for aerobic metabolic scope and the temperatures historically experienced by three Fraser River salmon populations during their river migration. This close association was then used to predict that the occurrence of a period of anomalously high river temperatures in 2004 led to a complete collapse of aerobic scope during river migration for a portion of one of the sockeye salmon (Oncorhynchus nerka) populations. This prediction was corroborated with empirical data from our biotelemetry studies, which tracked the migration of individual sockeye salmon in the Fraser River and revealed that the success of river migration for the same sockeye population was temperature dependent. Therefore, we suggest that collapse of aerobic scope was an important mechanism to explain the high salmon mortality observed during their migration. Consequently, models based on thermal optima for aerobic scope for ectothermic animals should improve predictions of population fitness under future climate scenarios.

  14. Prediction of success for polymerase chain reactions using the Markov maximal order model and support vector machine.

    Science.gov (United States)

    Li, Chun; Yang, Yan; Fei, Wenchao; He, Ping-an; Yu, Xiaoqing; Zhang, Defu; Yi, Shumin; Li, Xuepeng; Zhu, Jin; Wang, Changzhong; Wang, Zhifu

    2015-03-21

    Polymerase chain reaction (PCR) is hailed as one of the monumental scientific techniques of the twentieth century, and has become a common and often indispensable technique in many areas. However, researchers still frequently find some DNA templates very hard to amplify with PCR, although many kinds of endeavors were introduced to optimize the amplification. In fact, during the past decades, the experimental procedure of PCR was always the focus of attention, while the analysis of a DNA template, the PCR experimental subject itself, was almost neglected. Up to now, nobody can certainly identify whether a fragment of DNA can be simply amplified using conventional Taq DNA polymerase-based PCR protocol. Characterizing a DNA template and then developing a reliable and efficient method to predict the success of PCR reactions is thus urgently needed. In this study, by means of the Markov maximal order model, we construct a 48-D feature vector to represent a DNA template. Support vector machine (SVM) is then employed to help evaluate PCR result. To examine the anticipated success rates of our predictor, jackknife cross-validation test is adopted. The overall accuracy of our approach arrives at 93.12%, with the sensitivity, specificity, and MCC of 94.68%, 91.58%, and 0.863%, respectively.

  15. A Hybrid Method to Predict Success of Dental Implants

    OpenAIRE

    Reyhaneh Sadat Moayeri; Mehdi Khalili; Mahsa Nazari

    2016-01-01

    Background/Objectives: The market demand for dental implants is growing at a significant pace. Results obtained from real cases shows that some dental implants do not lead to success. Hence, the main problem is whether machine learning techniques can be successful in prediction of success of dental implants. Methods/Statistical Analysis: This paper presents a combined predictive model to evaluate the success of dental implants. The classifiers used in this model are W-J48, SVM, Neural Network...

  16. Successive smoothing algorithm for constructing the semiempirical model developed at ONERA to predict unsteady aerodynamic forces. [aeroelasticity in helicopters

    Science.gov (United States)

    Petot, D.; Loiseau, H.

    1982-01-01

    Unsteady aerodynamic methods adopted for the study of aeroelasticity in helicopters are considered with focus on the development of a semiempirical model of unsteady aerodynamic forces acting on an oscillating profile at high incidence. The successive smoothing algorithm described leads to the model's coefficients in a very satisfactory manner.

  17. A prognostic model to predict the success of artificial insemination in dairy cows based on readily available data.

    Science.gov (United States)

    Rutten, C J; Steeneveld, W; Vernooij, J C M; Huijps, K; Nielen, M; Hogeveen, H

    2016-08-01

    A prognosis of the likelihood of insemination success is valuable information for the decision to start inseminating a cow. This decision is important for the reproduction management of dairy farms. The aim of this study was to develop a prognostic model for the likelihood of successful first insemination. The parameters considered for the model are readily available on farm at the time a farmer makes breeding decisions. In the first step, variables are selected for the prognostic model that have prognostic value for the likelihood of a successful first insemination. In the second step, farm effects on the likelihood of a successful insemination are quantified and the prognostic model is cross-validated. Logistic regression with a random effect for farm was used to develop the prognostic model. Insemination and test-day milk production data from 2,000 commercial Dutch dairy farms were obtained, and 190,541 first inseminations from this data set were used for model selection. The following variables were used in the selection process: parity, days in milk, days to peak production, production level relative to herd mates, milk yield, breed of the cow, insemination season and calving season, log of the ratio of fat to protein content, and body condition score at insemination. Variables were selected in a forward selection and backward elimination, based on the Akaike information criterion. The variables that contributed most to the model were random farm effect, relative production factor, and milk yield at insemination. The parameters were estimated in a bootstrap analysis and a cross-validation was conducted within this bootstrap analysis. The parameter estimates for body condition score at insemination varied most, indicating that this effect varied most among Dutch dairy farms. The cross-validation showed that the prognosis of insemination success closely resembled the mean insemination success observed in the data set. Insemination success depends on

  18. Predicting Success Study Using Students GPA Category

    Directory of Open Access Journals (Sweden)

    Awan Setiawan

    2015-07-01

    Full Text Available Abstract. Maintaining student graduation rates are the main tasks of a University. High rates of student graduation and the quality of graduates is a success indicator of a university, which will have an impact on public confidence as stakeholders of higher education and the National Accreditation Board as a regulator (government. Making predictions of student graduation and determine the factors that hinders will be a valuable input for University. Data mining system facilitates the University to create the segmentation of students’ performance and prediction of their graduation. Segmentation of student by their performance can be classified in a quadrant chart is divided into 4 segments based on grade point average and the growth rate of students performance index per semester. Standard methodology in data mining i.e CRISP-DM (Cross Industry Standard Procedure for Data Mining will be implemented in this research. Making predictions, graduation can be done through the modeling process by utilizing the college database. Some algorithms such as C5, C & R Tree, CHAID, and Logistic Regression tested in order to find the best model. This research utilizes student performance data for several classes. Parameters used in addition to GPA also included the master's students data are expected to build the student profile data. The outcome of the study is the student category based on their study performance and prediction of graduation. Based on this prediction, the  university may recommend actions to be taken to improve the student  achievement index and graduation rates.Keywords: graduation, segmentation, quadrant GPA, data mining, modeling algorithms

  19. Predicting Species-Resolved Macronutrient Acquisition during Succession in a Model Phototrophic Biofilm Using an Integrated ‘Omics Approach

    Directory of Open Access Journals (Sweden)

    Stephen R. Lindemann

    2017-06-01

    Full Text Available The principles governing acquisition and interspecies exchange of nutrients in microbial communities and how those exchanges impact community productivity are poorly understood. Here, we examine energy and macronutrient acquisition in unicyanobacterial consortia for which species-resolved genome information exists for all members, allowing us to use multi-omic approaches to predict species’ abilities to acquire resources and examine expression of resource-acquisition genes during succession. Metabolic reconstruction indicated that a majority of heterotrophic community members lacked the genes required to directly acquire the inorganic nutrients provided in culture medium, suggesting high metabolic interdependency. The sole primary producer in consortium UCC-O, cyanobacterium Phormidium sp. OSCR, displayed declining expression of energy harvest, carbon fixation, and nitrate and sulfate reduction proteins but sharply increasing phosphate transporter expression over 28 days. Most heterotrophic members likewise exhibited signs of phosphorus starvation during succession. Though similar in their responses to phosphorus limitation, heterotrophs displayed species-specific expression of nitrogen acquisition genes. These results suggest niche partitioning around nitrogen sources may structure the community when organisms directly compete for limited phosphate. Such niche complementarity around nitrogen sources may increase community diversity and productivity in phosphate-limited phototrophic communities.

  20. Predicting Marital Success with PREPARE: A Predictive Validity Study.

    Science.gov (United States)

    Fowers, Blaine J.; Olson, David H.

    1986-01-01

    Assessed the utility of the premarital inventory, PREPARE, in predicting marital success. Conducted a three-year follow-up study with couples (N=164) who took PREPARE during their engagement. Found that the PREPARE scores from three months before marriage could predict with 80-90% accuracy which couples were separated and divorced from those that…

  1. Psychosocial Factors Predicting First-Year College Student Success

    Science.gov (United States)

    Krumrei-Mancuso, Elizabeth J.; Newton, Fred B.; Kim, Eunhee; Wilcox, Dan

    2013-01-01

    This study made use of a model of college success that involves students achieving academic goals and life satisfaction. Hierarchical regressions examined the role of six psychosocial factors for college success among 579 first-year college students. Academic self-efficacy and organization and attention to study were predictive of first semester…

  2. Predicting successful intended vaginal delivery after previous caesarean section : external validation of two predictive models in a Dutch nationwide registration-based cohort with a high intended vaginal delivery rate

    NARCIS (Netherlands)

    Schoorel, E. N. C.; Melman, S.; van Kuijk, S. M. J.; Grobman, W. A.; Kwee, A.; Mol, B. W. J.; Nijhuis, J. G.; Smits, L. J. M.; Aardenburg, R.; de Boer, K.; Delemarre, F. M. C.; van Dooren, I. M.; Franssen, M. T. M.; Kleiverda, G.; Kaplan, M.; Kuppens, S. M. I.; Lim, F. T. H.; Sikkema, J. M.; Smid-Koopman, E.; Visser, H.; Vrouenraets, F. P. J. M.; Woiski, M.; Hermens, R. P. M. G.; Scheepers, H. C. J.

    2014-01-01

    ObjectiveTo externally validate two models from the USA (entry-to-care [ETC] and close-to-delivery [CTD]) that predict successful intended vaginal birth after caesarean (VBAC) for the Dutch population. DesignA nationwide registration-based cohort study. SettingSeventeen hospitals in the Netherlands.

  3. Using Neural Networks to Predict MBA Student Success

    Science.gov (United States)

    Naik, Bijayananda; Ragothaman, Srinivasan

    2004-01-01

    Predicting MBA student performance for admission decisions is crucial for educational institutions. This paper evaluates the ability of three different models--neural networks, logit, and probit to predict MBA student performance in graduate programs. The neural network technique was used to classify applicants into successful and marginal student…

  4. Models of Success

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    @@ Wu Renbao made national celebrity for his commitment to achieving common prosperity among his co-villagers in Huaxi Village, Jiangsu Province.Wu's recipe for success was to take advantage of collective strength by encouraging mutual assistance between villages and households.

  5. Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation.

    Science.gov (United States)

    Ławryńczuk, Maciej

    2017-03-01

    This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Predicting Scientific Success Based on Coauthorship Networks

    CERN Document Server

    Sarigöl, Emre; Scholtes, Ingo; Garas, Antonios; Schweitzer, Frank

    2014-01-01

    We address the question to what extent the success of scientific articles is due to social influence. Analyzing a data set of over 100000 publications from the field of Computer Science, we study how centrality in the coauthorship network differs between authors who have highly cited papers and those who do not. We further show that a machine learning classifier, based only on coauthorship network centrality measures at time of publication, is able to predict with high precision whether an article will be highly cited five years after publication. By this we provide quantitative insight into the social dimension of scientific publishing - challenging the perception of citations as an objective, socially unbiased measure of scientific success.

  7. A Hybrid Method to Predict Success of Dental Implants

    Directory of Open Access Journals (Sweden)

    Reyhaneh Sadat Moayeri

    2016-05-01

    Full Text Available Background/Objectives: The market demand for dental implants is growing at a significant pace. Results obtained from real cases shows that some dental implants do not lead to success. Hence, the main problem is whether machine learning techniques can be successful in prediction of success of dental implants. Methods/Statistical Analysis: This paper presents a combined predictive model to evaluate the success of dental implants. The classifiers used in this model are W-J48, SVM, Neural Network, K-NN and Naïve Bayes. All internal parameters of each classifier are optimized. These classifiers are combined in a way that results in the highest possible accuracies. Results: The performance of the proposed method is compared with single classifiers. Results of our study show that the combinative approach can achieve higher performance than the best of the single classifiers. Using the combinative approach improves the sensitivity indicator by up to 13.3%. Conclusion/Application: Since diagnosis of patients whose implant does not lead to success is very important in implant surgery, the presented model can help surgeons to make a more reliable decision on level of success of implant operation prior to surgery.

  8. Predicting minority students' success in medical school.

    Science.gov (United States)

    Sedlacek, W E; Prieto, D O

    1990-03-01

    Despite recent attention to minority student recruitment and retention, data on predicting the success of minority medical students are scarce. Traditional predictors (college grades and scores on the Medical College Admission Test) have modest correlations with medical school grades and scores on the National Board of Medical Examiners examination for minority students. Nonetheless, admission committees also consider nontraditional variables when selecting minority students. Measures of nontraditional variables seem to assess types of intelligence not covered by traditional means. A system of organizing nontraditional or noncognitive variables into eight dimensions is proposed. The dimensions are self-concept, realistic, self-appraisal, understanding and dealing with racism, long-range goals, having a strong support person, showing leadership, having community involvement, and nontraditional knowledge acquired. Further, assessment should place more emphasis on recognizing and defining problems and on performance rather than knowledge. Combining traditional and nontraditional methods is best in selecting minority students, and sufficiently well developed measures exist in each area to make this a practical recommendation for any admission program.

  9. Impact of bacterial activity on turnover of insoluble hydrophobic substrates (phenanthrene and pyrene)-Model simulations for prediction of bioremediation success.

    Science.gov (United States)

    Rein, Arno; Adam, Iris K U; Miltner, Anja; Brumme, Katja; Kästner, Matthias; Trapp, Stefan

    2016-04-05

    Many attempts for bioremediation of polycyclic aromatic hydrocarbon (PAH) contaminated sites failed in the past, but the reasons for this failure are not well understood. Here we apply and improve a model for integrated assessment of mass transfer, biodegradation and residual concentrations for predicting the success of remediation actions. First, we provide growth parameters for Mycobacterium rutilum and Mycobacterium pallens growing on phenanthrene (PHE) or pyrene (PYR) degraded the PAH completely at all investigated concentrations. Maximum metabolic rates vmax and growth rates μ were similar for the substrates PHE and PYR and for both strains. The investigated Mycobacterium species were not superior in PHE degradation to strains investigated earlier with this method. Real-world degradation scenario simulations including diffusive flux to the microbial cells indicate: that (i) bioaugmentation only has a small, short-lived effect; (ii) Increasing sorption shifts the remaining PAH to the adsorbed/sequestered PAH pool; (iii) mobilizing by solvents or surfactants resulted in a significant decrease of the sequestered PAH, and (iv) co-metabolization e.g. by compost addition can contribute significantly to the reduction of PAH, because active biomass is maintained at a high level by the compost. The model therefore is a valuable contribution to the assessment of potential remediation action at PAH-polluted sites.

  10. Emotional intelligence predicts success in medical school.

    Science.gov (United States)

    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.

  11. Improving Localization Accuracy: Successive Measurements Error Modeling

    Directory of Open Access Journals (Sweden)

    Najah Abu Ali

    2015-07-01

    Full Text Available Vehicle self-localization is an essential requirement for many of the safety applications envisioned for vehicular networks. The mathematical models used in current vehicular localization schemes focus on modeling the localization error itself, and overlook the potential correlation between successive localization measurement errors. In this paper, we first investigate the existence of correlation between successive positioning measurements, and then incorporate this correlation into the modeling positioning error. We use the Yule Walker equations to determine the degree of correlation between a vehicle’s future position and its past positions, and then propose a -order Gauss–Markov model to predict the future position of a vehicle from its past  positions. We investigate the existence of correlation for two datasets representing the mobility traces of two vehicles over a period of time. We prove the existence of correlation between successive measurements in the two datasets, and show that the time correlation between measurements can have a value up to four minutes. Through simulations, we validate the robustness of our model and show that it is possible to use the first-order Gauss–Markov model, which has the least complexity, and still maintain an accurate estimation of a vehicle’s future location over time using only its current position. Our model can assist in providing better modeling of positioning errors and can be used as a prediction tool to improve the performance of classical localization algorithms such as the Kalman filter.

  12. Predicting student success in General Chemistry

    Science.gov (United States)

    Figueroa, Daphne Elizabeth

    The goal of this research was to determine the predictors of student success in college level General Chemistry. The potential predictors were categorized as cognitive, non-cognitive, affective, or demographic factors. A broader goal of the study was to provide a reference for academic personnel to better judge the prerequisite skills, knowledge and attitudes that students should attain before enrolling in General Chemistry. Therefore, the study is relevant to chemical educators who are attempting to matriculate candidates for the scientific workforce and to chemical education researches who are interested in student success, student retention and curricular reform. The major hypotheses were that several factors from each category would emerge as significant predictors and that these would differ for students enrolled at three different post-secondary institutions: a community college, a private university and a public university. These hypotheses were tested using multiple regression techniques to analyze grade, student survey and post-test data collected from General Chemistry students at the three institutions. Over-all, twelve factors (six demographic, three cognitive and three affective) emerged as strong, significant predictors of student success. In addition, there were marked differences in which factors emerged based on the type of institution and on how student success was defined. Thus, the major hypotheses of the study were supported. Over-all, this study has significant implications for educational policy, theory, and practice. With regard to policy, there is a need for institutions and departments that offer General Chemistry to provide support for a diverse population of students. And, at the community college level, in particular, there is a need for better academic advising and more institutional support for underprepared students. In the classroom, the professor plays a critical role in influencing students' academic self-concept, which in turn

  13. Personal Factors Predicting College Student Success

    Science.gov (United States)

    Aydin, Gokcen

    2017-01-01

    Purpose: With the changing perspective in modern education systems, success means more than grades and includes emotional, social, cognitive, and academic development. The aim of this study was to investigate the role of personal factors (academic self-efficacy, organization and attention to study, time utilization, classroom communication, stress…

  14. SNP CHARACTERISTICS PREDICT REPLICATION SUCCESS IN ASSOCIATION STUDIES

    Science.gov (United States)

    Gorlov, Ivan P.; Moore, Jason H.; Peng, Bo; Jin, Jennifer L.; Gorlova, Olga Y.; Amos, Christopher I.

    2014-01-01

    Successful independent replication is the most direct approach for distinguishing real genotype-disease associations from false discoveries in Genome Wide Association Studies (GWAS). Selecting SNPs for replication has been primarily based on p-values from the discovery stage, although additional characteristics of SNPs may be used to improve replication success. We used disease-associated SNPs from more than 2,000 published GWASs to identify predictors of SNP reproducibility. SNP reproducibility was defined as a proportion of successful replications among all replication attempts. The study reporting association for the first time was considered to be discovery and all consequent studies targeting the same phenotype replications. We found that −Log(P), where P is a p-value from the discovery study, is the strongest predictor of the SNP reproducibility. Other significant predictors include type of the SNP (e.g. missense vs intronic SNPs) and minor allele frequency. Features of the genes linked to the disease-associated SNP also predict SNP reproducibility. Based on empirically defined rules, we developed a reproducibility score (RS) to predict SNP reproducibility independently of −Log(P). We used data from two lung cancer GWAS studies as well as recently reported disease-associated SNPs to validate RS. Minus Log(P) outperforms RS when the very top SNPs are selected, while RS works better with relaxed selection criteria. In conclusion, we propose an empirical model to predict SNP reproducibility, which can be used to select SNPs for validation and prioritization. PMID:25273843

  15. Successful Succession in Family Businesses : Individual Level Factors and Succession Planning Models.

    OpenAIRE

    Aleem, Majid; Islam, Md. Shariful

    2009-01-01

    Individual level factors related to the successor have a central role to play in the succession process of the business. When these factors are viewed in relation to succession planning models, these factors have a direct relation to the succession models in terms of success or failure of the succession process. The major contributing factor to the success or failure of the succession process is that of the leadership provided to the organization by the predecessor. These leadership qualities...

  16. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  17. Predicting Success in Psychological Statistics Courses.

    Science.gov (United States)

    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.

  18. Functional brain imaging predicts public health campaign success.

    Science.gov (United States)

    Falk, Emily B; O'Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

    2016-02-01

    Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns.

  19. Rorschach Prediction of Success in Clinical Training: A Second Look

    Science.gov (United States)

    Carlson, Rae

    1969-01-01

    A Rorschach Index based on ego-psychological conceptualization of an optimal personality picture predicted for 155 trainees was compared with predictions from the Miller Analogies Test (MAT) and the Strong Vocational Interest Blank (SVIB). The Index predicted success and failure more effectively. (Author)

  20. INSIGHTS FROM MACHINE-LEARNED DIET SUCCESS PREDICTION.

    Science.gov (United States)

    Weber, Ingmar; Achananuparp, Palakorn

    2016-01-01

    To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider "quantified self" movement and many opt-in to publicly share their logged data. In this paper, we use public food diaries of more than 4,000 long-term active MyFitnessPal users to study the characteristics of a (un-)successful diet. Concretely, we train a machine learning model to predict repeatedly being over or under self-set daily calories goals and then look at which features contribute to the model's prediction. Our findings include both expected results, such as the token "mcdonalds" or the category "dessert" being indicative for being over the calories goal, but also less obvious ones such as the difference between pork and poultry concerning dieting success, or the use of the "quick added calories" functionality being indicative of over-shooting calorie-wise. This study also hints at the feasibility of using such data for more in-depth data mining, e.g., looking at the interaction between consumed foods such as mixing protein- and carbohydrate-rich foods. To the best of our knowledge, this is the first systematic study of public food diaries.

  1. Social Factors That Predict Fear of Academic Success

    Science.gov (United States)

    Gore, Jonathan S.; Thomas, Jessica; Jones, Stevy; Mahoney, Lauren; Dukes, Kristina; Treadway, Jodi

    2016-01-01

    Fear of academic success is ultimately a fear of social exclusion. Therefore, various forms of social inclusion may alleviate this fear. Three studies tested the hypothesis that social inclusion variables negatively predict fear of success. In Study 1, middle and high school students (n = 129) completed surveys of parental involvement, parental…

  2. Authentic Leadership and Emotional Intelligence: Predicting Student Success

    Science.gov (United States)

    Jasso, Sonia Lizette

    2016-01-01

    Student success has been predicted conservatively, using academic, demographic, and economic variables. Since many colleges are feeling the pressure to produce more graduates, student success is at the forefront of all universities. This study looks to find a relationship between traditional and non-traditional variables. The objective of the…

  3. Authentic Leadership and Emotional Intelligence: Predicting Student Success

    Science.gov (United States)

    Jasso, Sonia Lizette

    2016-01-01

    Student success has been predicted conservatively, using academic, demographic, and economic variables. Since many colleges are feeling the pressure to produce more graduates, student success is at the forefront of all universities. This study looks to find a relationship between traditional and non-traditional variables. The objective of the…

  4. The Complex Route to Success: Complex Problem-Solving Skills in the Prediction of University Success

    Science.gov (United States)

    Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M.

    2016-01-01

    Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…

  5. The Complex Route to Success: Complex Problem-Solving Skills in the Prediction of University Success

    Science.gov (United States)

    Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M.

    2016-01-01

    Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…

  6. Predicting Scenarios for Successful Autodissemination of Pyriproxyfen by Malaria Vectors from Their Resting Sites to Aquatic Habitats; Description and Simulation Analysis of a Field-Parameterizable Model.

    Directory of Open Access Journals (Sweden)

    Samson S Kiware

    Full Text Available Large-cage experiments indicate pyriproxifen (PPF can be transferred from resting sites to aquatic habitats by Anopheles arabiensis--malaria vector mosquitoes to inhibit emergence of their own offspring. PPF coverage is amplified twice: (1 partial coverage of resting sites with PPF contamination results in far higher contamination coverage of adult mosquitoes because they are mobile and use numerous resting sites per gonotrophic cycle, and (2 even greater contamination coverage of aquatic habitats results from accumulation of PPF from multiple oviposition events.Deterministic mathematical models are described that use only field-measurable input parameters and capture the biological processes that mediate PPF autodissemination. Recent successes in large cages can be rationalized, and the plausibility of success under full field conditions can be evaluated a priori. The model also defines measurable properties of PPF delivery prototypes that may be optimized under controlled experimental conditions to maximize chances of success in full field trials. The most obvious flaw in this model is the endogenous relationship that inevitably occurs between the larval habitat coverage and the measured rate of oviposition into those habitats if the target mosquito species is used to mediate PPF transfer. However, this inconsistency also illustrates the potential advantages of using a different, non-target mosquito species for contamination at selected resting sites that shares the same aquatic habitats as the primary target. For autodissemination interventions to eliminate malaria transmission or vector populations during the dry season window of opportunity will require comprehensive contamination of the most challenging subset of aquatic habitats [Formula: see text] that persist or retain PPF activity (Ux for only one week [Formula: see text], where Ux = 7 days. To achieve >99% contamination coverage of these habitats will necessitate values for the

  7. Predicting Scenarios for Successful Autodissemination of Pyriproxyfen by Malaria Vectors from Their Resting Sites to Aquatic Habitats; Description and Simulation Analysis of a Field-Parameterizable Model

    Science.gov (United States)

    Kiware, Samson S.; Corliss, George; Merrill, Stephen; Lwetoijera, Dickson W.; Devine, Gregor; Majambere, Silas; Killeen, Gerry F.

    2015-01-01

    Background Large-cage experiments indicate pyriproxifen (PPF) can be transferred from resting sites to aquatic habitats by Anopheles arabiensis - malaria vector mosquitoes to inhibit emergence of their own offspring. PPF coverage is amplified twice: (1) partial coverage of resting sites with PPF contamination results in far higher contamination coverage of adult mosquitoes because they are mobile and use numerous resting sites per gonotrophic cycle, and (2) even greater contamination coverage of aquatic habitats results from accumulation of PPF from multiple oviposition events. Methods and Findings Deterministic mathematical models are described that use only field-measurable input parameters and capture the biological processes that mediate PPF autodissemination. Recent successes in large cages can be rationalized, and the plausibility of success under full field conditions can be evaluated a priori. The model also defines measurable properties of PPF delivery prototypes that may be optimized under controlled experimental conditions to maximize chances of success in full field trials. The most obvious flaw in this model is the endogenous relationship that inevitably occurs between the larval habitat coverage and the measured rate of oviposition into those habitats if the target mosquito species is used to mediate PPF transfer. However, this inconsistency also illustrates the potential advantages of using a different, non-target mosquito species for contamination at selected resting sites that shares the same aquatic habitats as the primary target. For autodissemination interventions to eliminate malaria transmission or vector populations during the dry season window of opportunity will require comprehensive contamination of the most challenging subset of aquatic habitats (Clx) that persist or retain PPF activity (Ux) for only one week (Clx→1, where Ux = 7 days). To achieve >99% contamination coverage of these habitats will necessitate values for the product of

  8. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  9. Melanoma risk prediction models

    Directory of Open Access Journals (Sweden)

    Nikolić Jelena

    2014-01-01

    only present in melanoma patients and thus were strongly associated with melanoma. The percentage of correctly classified subjects in the LR model was 74.9%, sensitivity 71%, specificity 78.7% and AUC 0.805. For the ADT percentage of correctly classified instances was 71.9%, sensitivity 71.9%, specificity 79.4% and AUC 0.808. Conclusion. Application of different models for risk assessment and prediction of melanoma should provide efficient and standardized tool in the hands of clinicians. The presented models offer effective discrimination of individuals at high risk, transparent decision making and real-time implementation suitable for clinical practice. A continuous melanoma database growth would provide for further adjustments and enhancements in model accuracy as well as offering a possibility for successful application of more advanced data mining algorithms.

  10. Temperamental Predictive Factors for Success in Korean Professional Baseball Players

    OpenAIRE

    Kang, Kyoung Doo; Han, Doug Hyun; Hannon, James C.; Hall, Morgan S.; Choi, Jae Won

    2015-01-01

    Objective In this five-year cohort study, we hypothesize that factors of temperament and character in professional baseball players predict the speed of obtaining success and the quality of success as well as anxiety control. Methods Participants included 120 male rookie players from the Korea Baseball Organization (KBO) and 107 male non-players with no history of playing baseball. The personality/characters and state/trait anxieties of participants were assessed with the Temperament and Char...

  11. NCLEX-RN Performance: Predicting Success on the Computerized Examination.

    Science.gov (United States)

    Waterhouse, Julie Keith; Beeman, Pamela Butler

    2001-01-01

    Discriminant analysis was used to identify variables predictive of success in the computerized National Council Licensure Examination for Registered Nurses with data from 289 nursing graduates. Using seven significant predictors, 94% of passes and 92% of failures were correctly identified. (Contains 23 references.) (SK)

  12. Predicting Success in a Master of Information Science Degree Programme

    Science.gov (United States)

    Agbonlaho, Rosemary O.; Offor, Uzoamaka J.

    2008-01-01

    This study provides an insight into factors that can help predict the success of students admitted to a Master of information science (MInfSc) programme and aid admission committees in selecting candidates that are most likely to succeed in a graduate programme of information science, using the MInfSc programme at the Africa Regional Centre for…

  13. Using Emotional and Social Factors To Predict Student Success.

    Science.gov (United States)

    Pritchard, Mary E.; Wilson, Gregory S.

    2003-01-01

    College academic success and retention have traditionally been predicted using demographic and academic variables. This study moved beyond traditional predictors. A survey of 218 undergraduate students revealed that emotional and social factors (e.g., stress, frequency of alcohol consumption) related to GPA and emotional factors (e.g.,…

  14. Predictive models in urology.

    Science.gov (United States)

    Cestari, Andrea

    2013-01-01

    Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology.

  15. Predicting NCLEX-RN success in a diverse student population.

    Science.gov (United States)

    Alameida, Marshall D; Prive, Alice; Davis, Harvey C; Landry, Lynette; Renwanz-Boyle, Andrea; Dunham, Michelle

    2011-05-01

    Many schools of nursing have implemented standardized testing using platforms such as those developed by Assessment Technologies Institute (ATI) to better prepare students for success on the National Council Licensure Examination for Registered Nurses® (NCLEX-RN). This study extends and replicates the research on standardized testing to predict first-time pass success in a diverse student population and across two prelicensure program types. The final sample consisted of 589 students who graduated between 2003 and 2009. Demographic data, as well as academic performance and scores on the ATI RN Comprehensive Predictor, were analyzed. The findings in this study indicate that scores on the ATI RN Comprehensive Predictor were positively, significantly associated with first-time pass success. Students in jeopardy of failing the NCLEX-RN on their first attempt can be identified prior to graduation and remediation efforts can be strengthened to improve their success.

  16. Decision trees for predicting the academic success of students

    Directory of Open Access Journals (Sweden)

    Josip Mesarić

    2016-12-01

    Full Text Available The aim of this paper is to create a model that successfully classifies students into one of two categories, depending on their success at the end of their first academic year, and finding meaningful variables affecting their success. This model is based on information regarding student success in high school and their courses after completing their first year of study, as well as the rank of preferences assigned to the observed faculty, and attempts to classify students into one of the two categories in line with their academic success. Creating a model required collecting data on all undergraduate students enrolled into their second year at the Faculty of Economics, University of Osijek, as well as data on completion of the state exam. These two datasets were combined and used for the model. Several classification algorithms for constructing decision trees were compared and the statistical significance (t-test of the results was analyzed. Finally, the algorithm that produced the highest accuracy was chosen as the most successful algorithm for modeling the academic success of students. The highest classification rate of 79% was produced using the REPTree decision tree algorithm, but the tree was not as successful in classifying both classes. Therefore, the average rate of classification was calculated for two models that gave the highest total rate of classification, where a higher percentage is achieved using the model relying on the algorithm J48. The most significant variables were total points in the state exam, points from high school and points in the Croatian language exam.

  17. Predictive factors of successful microdissection testicular sperm extraction.

    Science.gov (United States)

    Bernie, Aaron M; Ramasamy, Ranjith; Schlegel, Peter N

    2013-01-01

    Azoospermia in men requires microsurgical reconstruction or a procedure for sperm retrieval with assisted reproduction to allow fertility. While the chance of successful retrieval of sperm in men with obstructive azoospermia approaches >90%, the chances of sperm retrieval in men with non-obstructive azoospermia (NOA) are not as high. Conventional procedures such as fine needle aspiration of the testis, testicular biopsy and testicular sperm extraction are successful in 20-45% of men with NOA. With microdissection testicular sperm extraction (micro-TESE), the chance of successful retrieval can be up to 60%. Despite this increased success, the ability to counsel patients preoperatively on their probability of successful sperm retrieval has remained challenging. A combination of variables such as age, serum FSH and inhibin B levels, testicular size, genetic analysis, history of Klinefelter syndrome, history of cryptorchidism or varicocele and histopathology on diagnostic biopsy have provided some insight into the chance of successful sperm retrieval in men with NOA. The goal of this review was to evaluate the preoperative factors that are currently available to predict the outcome for success with micro-TESE.

  18. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... paper, we will present an introduction to the theory and application of MPC with Matlab codes written to ... model predictive control, linear systems, discrete-time systems, ... and then compute very rapidly for this open-loop con-.

  19. Predicting NCLEX-PN success with the HESI Exit Exam.

    Science.gov (United States)

    Young, Anne; Willson, Pamela

    2010-01-01

    Surveys were mailed to directors of 72 randomly selected practical nursing (PN) schools that administered Elsevier's HESI Exit Exam for Practical Nurses (E2-PN) during the 2006-2007 academic year. Data were collected regarding students' NCLEX-PN outcomes and the schools' benchmarking and remediation policies. The first version of the E2-PN was 99.48% accurate in predicting NCLEX-PN success. Versions two and three of the E2-PN, which were administered to students who were remediated because they did not achieve the faculty-designated benchmark, were also highly accurate in predicting NCLEX-PN success. Most faculties set 850 as their school's E2-PN benchmark, and 73% of the respondents required remediation for students who did not achieve the benchmark score. The most frequently cited remediation strategy was tutoring.

  20. Who Is Your Successful Aging Role Model?

    Science.gov (United States)

    Jopp, Daniela S; Jung, Seojung; Damarin, Amanda K; Mirpuri, Sheena; Spini, Dario

    2017-03-01

    Having a role model of successful aging may contribute to views on aging. This article investigated the nature and correlates of young, middle-aged, and older adults' successful aging role models. One hundred and fifty-one individuals aged 18-99 were asked whether they had a role model of successful aging and if so, the reasons for their choice. Open-ended answers were coded for recurring themes. Views on aging and attitudes toward own aging were assessed with questionnaires. Eighty-five percent of participants indicated at least one role model. Most mentioned role models from their family, including parents and grandparents. Role models were gender matched. Most frequent reasons for model choices were health, activities, and social resources. Participants with family role models had less negative views on aging. Mediation analyses confirmed that family role models were associated with more reasons for role model choice, which in turn was associated with less negative views on aging. Furthermore, the effect of reasons on attitudes toward own aging was mediated by negative views on aging. Young, middle-aged, and older adults have role models for successful aging. Links between role model features and views on aging suggest that role models may be useful in promoting successful aging.

  1. Pediatric extracorporeal shock wave lithotripsy: Predicting successful outcomes.

    Science.gov (United States)

    McAdams, Sean; Shukla, Aseem R

    2010-10-01

    Extracorporeal shock wave lithotripsy (ESWL) is currently a first-line procedure of most upper urinary tract stones ionizing radiation, perhaps utilizing advancements in ultrasound and magnetic resonance imaging. This report provides a review of the current literature evaluating the patient attributes and stone factors that may be predictive of successful ESWL outcomes along with reviewing the role of pre-operative imaging and considerations for patient safety.

  2. Aging Successfully: A Four-Factor Model

    Science.gov (United States)

    Lee, Pai-Lin; Lan, William; Yen, Tung-Wen

    2011-01-01

    The study was designed to validate a model for a successful aging process and examine the gender differences in the aging process. Three hundred twelve participants who were 65 or older completed a Taiwan Social Change Survey that measures four factors that define successful aging process: including physical, psychological, social support, and…

  3. Aging Successfully: A Four-Factor Model

    Science.gov (United States)

    Lee, Pai-Lin; Lan, William; Yen, Tung-Wen

    2011-01-01

    The study was designed to validate a model for a successful aging process and examine the gender differences in the aging process. Three hundred twelve participants who were 65 or older completed a Taiwan Social Change Survey that measures four factors that define successful aging process: including physical, psychological, social support, and…

  4. Nominal model predictive control

    OpenAIRE

    Grüne, Lars

    2013-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  5. Nominal Model Predictive Control

    OpenAIRE

    Grüne, Lars

    2014-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  6. MODEL OF TRAINING OF SUCCESS IN LIFE

    Directory of Open Access Journals (Sweden)

    Екатерина Александровна Лежнева

    2014-04-01

    Full Text Available The article explains the importance of the development of motive to succeed in adolescence. It is determined the value of the motive to achieve success in the further development of the teenager: a motive to achieve effective internal forces mobilized for the implementation of successful operation ensures the active involvement of teenagers in social and interpersonal relationships. As the primary means of motive development success is considered training. The author provides a definition of "training for success in life," creates a model of training for success in life, and describes its units (targeted, informative, technological, productive, reveals the successful development of the technology life strategy used during the training (self-presentation, targets, incentives, subject-orientation. The author pays attention to the need for a future psychologist to develop teenagers’ motive to achieve success through the mastery of competence in constructing a model of training for success in life, and its implementation in the course of professional activities. The main means of training students of psychology to the use of training success in life identified the additional educational programs and psychological section.DOI: http://dx.doi.org/10.12731/2218-7405-2013-9-77

  7. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  8. Pediatric extracorporeal shock wave lithotripsy: Predicting successful outcomes

    Directory of Open Access Journals (Sweden)

    Sean McAdams

    2010-01-01

    Full Text Available Extracorporeal shock wave lithotripsy (ESWL is currently a first-line procedure of most upper urinary tract stones <2 cm of size because of established success rates, its minimal invasiveness and long-term safety with minimal complications. Given that alternative surgical and endourological options exist for the management of stone disease and that ESWL failure often results in the need for repeat ESWL or secondary procedures, it is highly desirable to identify variables predicting successful outcomes of ESWL in the pediatric population. Despite numerous reports and growing experience, few prospective studies and guidelines for pediatric ESWL have been completed. Variation in the methods by which study parameters are measured and reported can make it difficult to compare individual studies or make definitive recommendations. There is ongoing work and a need for continuing improvement of imaging protocols in children with renal colic, with a current focus on minimizing exposure to ionizing radiation, perhaps utilizing advancements in ultrasound and magnetic resonance imaging. This report provides a review of the current literature evaluating the patient attributes and stone factors that may be predictive of successful ESWL outcomes along with reviewing the role of pre-operative imaging and considerations for patient safety.

  9. Impact of bacterial activity on turnover of insoluble hydrophobic substrates (phenanthrene and pyrene)—Model simulations for prediction of bioremediation success

    DEFF Research Database (Denmark)

    Rein, Arno; Adam, Iris K.U.; Miltner, Anja

    2016-01-01

    Many attempts for bioremediation of polycyclic aromatic hydrocarbon (PAH) contaminated sites failed in the past, but the reasons for this failure are not well understood. Here we apply and improve a model for integrated assessment of mass transfer, biodegradation and residual concentrations...

  10. Expanding on Successful Concepts, Models, and Organization

    Energy Technology Data Exchange (ETDEWEB)

    Teeguarden, Justin G.; Tan, Yu-Mei; Edwards, Stephen W.; Leonard, Jeremy A.; Anderson, Kim A.; Corley, Richard A.; Kile, Molly L.; L. Massey Simonich, Staci; Stone, David; Tanguay, Robert L.; Waters, Katrina M.; Harper, Stacey L.; Williams, David E.

    2016-09-06

    In her letter to the editor1 regarding our recent Feature Article “Completing the Link between Exposure Science and Toxicology for Improved Environmental Health Decision Making: The Aggregate Exposure Pathway Framework” 2, Dr. von Göetz expressed several concerns about terminology, and the perception that we propose the replacement of successful approaches and models for exposure assessment with a concept. We are glad to have the opportunity to address these issues here. If the goal of the AEP framework was to replace existing exposure models or databases for organizing exposure data with a concept, we would share Dr. von Göetz concerns. Instead, the outcome we promote is broader use of an organizational framework for exposure science. The framework would support improved generation, organization, and interpretation of data as well as modeling and prediction, not replacement of models. The field of toxicology has seen the benefits of wide use of one or more organizational frameworks (e.g., mode and mechanism of action, adverse outcome pathway). These frameworks influence how experiments are designed, data are collected, curated, stored and interpreted and ultimately how data are used in risk assessment. Exposure science is poised to similarly benefit from broader use of a parallel organizational framework, which Dr. von Göetz correctly points out, is currently used in the exposure modeling community. In our view, the concepts used so effectively in the exposure modeling community, expanded upon in the AEP framework, could see wider adoption by the field as a whole. The value of such a framework was recognized by the National Academy of Sciences.3 Replacement of models, databases, or any application with the AEP framework was not proposed in our article. The positive role broader more consistent use of such a framework might have in enabling and advancing “general activities such as data acquisition, organization…,” and exposure modeling was discussed

  11. Predicting Student Success using Analytics in Course Learning Management Systems

    Energy Technology Data Exchange (ETDEWEB)

    Olama, Mohammed M [ORNL; Thakur, Gautam [ORNL; McNair, Wade [ORNL; Sukumar, Sreenivas R [ORNL

    2014-01-01

    Educational data analytics is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the student and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present the efforts carried out at Oak Ridge National Laboratory (ORNL) toward conducting predictive analytics to academic data collected from 2009 through 2013 and available in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total GPA at the same term they enrolled in the course. Then, Logistic Regression and Neural Network predictive models are used to identify students as early as possible that are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy.

  12. Predicting student success using analytics in course learning management systems

    Science.gov (United States)

    Olama, Mohammed M.; Thakur, Gautam; McNair, Allen W.; Sukumar, Sreenivas R.

    2014-05-01

    Educational data analytics is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the student and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present the efforts carried out at Oak Ridge National Laboratory (ORNL) toward conducting predictive analytics to academic data collected from 2009 through 2013 and available in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for predicting student outcomes such as students' scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total GPA at the same term they enrolled in the course. Then, Logistic Regression and Neural Network predictive models are used to identify students as early as possible that are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy.

  13. Executive functions predict the success of top-soccer players.

    Science.gov (United States)

    Vestberg, Torbjörn; Gustafson, Roland; Maurex, Liselotte; Ingvar, Martin; Petrovic, Predrag

    2012-01-01

    While the importance of physical abilities and motor coordination is non-contested in sport, more focus has recently been turned toward cognitive processes important for different sports. However, this line of studies has often investigated sport-specific cognitive traits, while few studies have focused on general cognitive traits. We explored if measures of general executive functions can predict the success of a soccer player. The present study used standardized neuropsychological assessment tools assessing players' general executive functions including on-line multi-processing such as creativity, response inhibition, and cognitive flexibility. In a first cross-sectional part of the study we compared the results between High Division players (HD), Lower Division players (LD) and a standardized norm group. The result shows that both HD and LD players had significantly better measures of executive functions in comparison to the norm group for both men and women. Moreover, the HD players outperformed the LD players in these tests. In the second prospective part of the study, a partial correlation test showed a significant correlation between the result from the executive test and the numbers of goals and assists the players had scored two seasons later. The results from this study strongly suggest that results in cognitive function tests predict the success of ball sport players.

  14. Executive functions predict the success of top-soccer players.

    Directory of Open Access Journals (Sweden)

    Torbjörn Vestberg

    Full Text Available While the importance of physical abilities and motor coordination is non-contested in sport, more focus has recently been turned toward cognitive processes important for different sports. However, this line of studies has often investigated sport-specific cognitive traits, while few studies have focused on general cognitive traits. We explored if measures of general executive functions can predict the success of a soccer player. The present study used standardized neuropsychological assessment tools assessing players' general executive functions including on-line multi-processing such as creativity, response inhibition, and cognitive flexibility. In a first cross-sectional part of the study we compared the results between High Division players (HD, Lower Division players (LD and a standardized norm group. The result shows that both HD and LD players had significantly better measures of executive functions in comparison to the norm group for both men and women. Moreover, the HD players outperformed the LD players in these tests. In the second prospective part of the study, a partial correlation test showed a significant correlation between the result from the executive test and the numbers of goals and assists the players had scored two seasons later. The results from this study strongly suggest that results in cognitive function tests predict the success of ball sport players.

  15. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...

  16. Successful and unsuccessful psychopaths: a neurobiological model.

    Science.gov (United States)

    Gao, Yu; Raine, Adrian

    2010-01-01

    Despite increasing interest in psychopathy research, surprisingly little is known about the etiology of non-incarcerated, successful psychopaths. This review provides an analysis of current knowledge on the similarities and differences between successful and unsuccessful psychopaths derived from five population sources: community samples, individuals from employment agencies, college students, industrial psychopaths, and serial killers. An initial neurobiological model of successful and unsuccessful psychopathy is outlined. It is hypothesized that successful psychopaths have intact or enhanced neurobiological functioning that underlies their normal or even superior cognitive functioning, which in turn helps them to achieve their goals using more covert and nonviolent methods. In contrast, in unsuccessful, caught psychopaths, brain structural and functional impairments together with autonomic nervous system dysfunction are hypothesized to underlie cognitive and emotional deficits and more overt violent offending.

  17. Predicting nest success from habitat features in aspen forests of the central Rocky Mountains

    Science.gov (United States)

    Heather M. Struempf; Deborah M. Finch; Gregory Hayward; Stanley Anderson

    2001-01-01

    We collected nesting data on bird use of aspen stands in the Routt and Medicine Bow National Forests between 1987 and 1989. We found active nest sites of 28 species of small nongame birds on nine study plots in undisturbed aspen forests. We compared logistic regression models predicting nest success (at least one nestling) from nest-site or stand-level habitat...

  18. What predicts successful literacy acquisition in a second language?

    Science.gov (United States)

    Frost, Ram; Siegelman, Noam; Narkiss, Alona; Afek, Liron

    2013-07-01

    In the study reported here, we examined whether success (or failure) in assimilating the structure of a second language can be predicted by general statistical-learning abilities that are nonlinguistic 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 was not correlated with abilities related to a general g factor or working memory. We found that, on average, native speakers of English who more accurately picked up the implicit statistical structure embedded in the continuous stream of shapes better assimilated the Semitic structure of Hebrew words. Languages and their writing systems are characterized by idiosyncratic correlations of form and meaning, and our findings suggest that these correlations 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.

  19. Assessing and predicting successful tube placement outcomes in ALS patients.

    Science.gov (United States)

    Beggs, Kathleen; Choi, Marcia; Travlos, Andrew

    2010-01-01

    This study reviews feeding tube placement outcomes in 69 ALS outpatients seen at an outpatient interdisciplinary ALS clinic in British Columbia, Canada. The objective was to determine at which point the risks outweigh the benefits of tube placement by reviewing outcomes against parameters of respiratory function, nutritional status and speech and swallowing deterioration. The study was a retrospective review of tube placements between January 2000 and 2005, analysing data on respiratory function (forced vital capacity and respiratory status), weight change from usual body weight (UBW) and speech/swallowing deterioration using ALS Severity Score ratings (Hillel et al., 1989) at time of tube placement. Results show a statistically significant association between nutritional status and successful tube placement outcomes (p=0.003), and none between respiratory status, speech/swallowing variables, or number of deteriorated variables in each patient. Study findings were impacted by lack of available respiratory data. The only study variable that predicted successful tube placement outcome was a body weight greater than or equal to 74% UBW at time of tube placement. In the absence of access to respiratory testing, the relatively simple assessment of weight may assist patients and caregivers in appropriate decisions around tube placement.

  20. Forest-succession models and their ecological and management implications

    Energy Technology Data Exchange (ETDEWEB)

    West, D.; Smith, T.M.; Weinstein, D.A.; Shugart, H.H.

    1981-01-01

    Computer models of forest succession have been developed to an extent that allows their use as a tool for predicting forest ecosystem behavior over long periods of time. This paper outlines the use of one approach to forest succession modeling for a variety of problems including: (1) determining the effect of climate change on forests; (2) integrating information on wildlife habitat changes with the changes in forest structure associated with timber management; (3) assessing the potential effect of air pollutants on forest dynamics; and (4) determining the theoretical importance of disturbance on forest community diversity and function.

  1. Factors predicting recurrence in successfully treated cases of anisometropic amblyopia

    Directory of Open Access Journals (Sweden)

    Rohit Saxena

    2013-01-01

    Full Text Available Context: Recurrence after successful treatment of amblyopia is known and understanding the risk factors could help effective management. Aim: To measure incidence of recurrence in successfully treated cases of anisometropic amblyopia and evaluate factors predicting it. Settings and Design: Cohort Study at a tertiary level institution. Materials and Methods: Successfully treated anisometropic amblyopes aged 4−12 years were followed up for 1 year after stopping therapy. Best corrected visual acuity (BCVA, refractive error, stereoacuity and contrast sensitivity were evaluated at baseline and follow-up. Statistical Analysis: Intergroup analysis with appropriate tests: Chi-square test, Fisher′s exact test, Wilcoxon rank sum test and paired t-test. Results: One hundred and two patients with mean age at diagnosis 7.06 μ 1.81 years were followed-up for a mean duration of 1.0 μ 0.2 years. The mean pre-treatment BCVA (LogMAR score at diagnosis was 0.73 μ 0.36 units which improved to 0.20 μ 0.00 with treatment and after 1 year of stopping treatment was 0.22 μ 0.07. Thirteen (12.74% patients showed amblyopia recurrence during follow-up. Risk of recurrence was higher with older age of onset of treatment (6.64 μ 1.77 years without recurrence v/s 8.53 μ 1.39 years with recurrence, P = 0.0014. Greater extent of improvement of VA (P = 0.048 and final VA at stopping occlusion (P = 0.03 were associated with higher recurrence. Binocularity status or stereoacuity changes were not associated with risk of recurrence. Conclusions: Significant numbers of children suffer recurrence of amblyopia after stopping therapy. Older age, better BCVA after stopping therapy and greater magnitude of improvement in BCVA are important risk factors for recurrence. Careful follow-up is essential for early detection and management of recurrence.

  2. Honey bee success predicted by landscape composition in Ohio, USA

    Directory of Open Access Journals (Sweden)

    DB Sponsler

    2015-03-01

    Full Text Available Foraging honey bees (Apis mellifera L. can routinely travel as far as several kilometers from their hive in the process of collecting nectar and pollen from floral patches within the surrounding landscape. Since the availability of floral resources at the landscape scale is a function of landscape composition, apiculturists have long recognized that landscape composition is a critical determinant of honey bee colony success. Nevertheless, very few studies present quantitative data relating colony success metrics to local landscape composition. We employed a beekeeper survey in conjunction with GIS-based landscape analysis to model colony success as a function of landscape composition in the State of Ohio, USA, a region characterized by intensive cropland, urban development, deciduous forest, and grassland. We found that colony food accumulation and wax production were positively related to cropland and negatively related to forest and grassland, a pattern that may be driven by the abundance of dandelion and clovers in agricultural areas compared to forest or mature grassland. Colony food accumulation was also negatively correlated with urban land cover in sites dominated by urban and agricultural land use, which does not support the popular opinion that the urban environment is more favorable to honey bees than cropland.

  3. Electronic Commerce Success Model: A Search for Multiple Criteria

    Directory of Open Access Journals (Sweden)

    Didi Achjari

    2004-01-01

    Full Text Available The current study attempts to develop and examine framework of e-commerce success. In order to obtain comprehensive and robust measures, the framework accomodates key factors that are identified in the literature concerning the success of electronic commerce. The structural model comprises of four exogenous variables (Internal Driver, Internal Impediment, External Driver and Exgternal Impediment and one endogenous variable (Electornic Commerce Success eith 24 observed variables. The study that was administered within large Australian companies using questionaire survey concluded that benefits for both internal organization and external parties from the use of e-commerce were the main factor tro predict perceived and/or expected success of electronic commerce.

  4. Developing a Successful Open Source Training Model

    Directory of Open Access Journals (Sweden)

    Belinda Lopez

    2010-01-01

    Full Text Available Training programs for open source software provide a tangible, and sellable, product. A successful training program not only builds revenue, it also adds to the overall body of knowledge available for the open source project. By gathering best practices and taking advantage of the collective expertise within a community, it may be possible for a business to partner with an open source project to build a curriculum that promotes the project and supports the needs of the company's training customers. This article describes the initial approach used by Canonical, the commercial sponsor of the Ubuntu Linux operating system, to engage the community in the creation of its training offerings. We then discuss alternate curriculum creation models and some of the conditions that are necessary for successful collaboration between creators of existing documentation and commercial training providers.

  5. Food cravings prospectively predict decreases in perceived self-regulatory success in dieting.

    Science.gov (United States)

    Meule, Adrian; Richard, Anna; Platte, Petra

    2017-01-01

    Food cravings are assumed to hamper dieting success, but most findings are based on cross-sectional studies. In the current study, female students were tested at the beginning of their first semester at university and six months later. They completed the Food Cravings Questionnaire-Trait-reduced (FCQ-T-r), the disinhibition subscale of the Eating Inventory, and the Perceived Self-Regulatory Success in Dieting Scale, and their height and weight were measured. Scores on the FCQ-T-r prospectively predicted higher disinhibition and lower perceived self-regulatory success in dieting after six months. Although FCQ-T-r scores did not predict increases in body mass index (BMI) directly, a serial mediation model revealed an indirect effect of FCQ-T-r scores at baseline on BMI after six months via increased disinhibition scores and decreased perceived self-regulatory success in dieting. To conclude, the current results provide evidence for a prospective relationship between trait food craving and decreases in dieting success. Furthermore, they suggest a possible mediator of this association (i.e., increases in disinhibited eating) as well as an indirect effect on body weight. Measurement of trait food craving may be a useful tool for predicting or monitoring treatment changes and relapse in eating- and weight disorders.

  6. Predictive Models for Music

    OpenAIRE

    Paiement, Jean-François; Grandvalet, Yves; Bengio, Samy

    2008-01-01

    Modeling long-term dependencies in time series has proved very difficult to achieve with traditional machine learning methods. This problem occurs when considering music data. In this paper, we introduce generative models for melodies. We decompose melodic modeling into two subtasks. We first propose a rhythm model based on the distributions of distances between subsequences. Then, we define a generative model for melodies given chords and rhythms based on modeling sequences of Narmour featur...

  7. The success of cardiotocography in predicting perinatal outcome

    Directory of Open Access Journals (Sweden)

    Alpaslan Kaban

    2012-06-01

    Full Text Available Objectives: The determination of the fetal condition duringlabor is important to minimize fetal death due to asphyxiaand the neurological sequelae of fetal hypoxia.This study evaluated the success of fetal cardiotocographyin predicting perinatal consequences.Materials and methods: This study enrolled 101 full-termpregnant women admitted for delivery to Vakif GurebaTraining and Research Hospital between October 2009and February 2010. Women were included if they wereaged 18-45 years and within 36-41 weeks of gestation.During a 20-min period of fetal monitoring, a change inFHR (fetal heart rate lasting for 15 s or two elevated runsof 15 beats was evaluated as a reactive NST (non-stresstest. The umbilical artery pH was used as the “gold standard”for assessing fetal asphyxia.Results: The mean age of the women included in thestudy was 27.82 ± 5.29 years, the average parity was1.09± 0.96. The pH was normal in 85 neonates, while 13 hadfetal asphyxia. No significant difference in umbilical cordblood pH, pO2, or pCO2 was observed between these twogroups (p = 0.497, p = 0.722, and p = 0.053, respectively.No significant difference in maternal age, parity, or birthweight was found between the group with fetal distressbased on CTG (cardiotocography and the normal group.Conclusion: Cardiotocography is an important test duringlabor for labor management, it is insufficient for predictingthe perinatal outcome. Therefore, labor should beevaluated on an individualized basis. J Clin Exp Invest2012; 3(2: 168-171

  8. Medial Temporal Lobe Activity Predicts Successful Relational Memory Binding

    Science.gov (United States)

    Hannula, Deborah E.; Ranganath, Charan

    2009-01-01

    Previous neuropsychological findings have implicated medial temporal lobe (MTL) structures in retaining object-location relations over the course of short delays, but MTL effects have not always been reported in neuroimaging investigations with similar short-term memory requirements. Here, we used event-related functional magnetic resonance imaging to test the hypothesis that the hippocampus and related MTL structures support accurate retention of relational memory representations, even across short delays. On every trial, four objects were presented, each in one of nine possible locations of a three-dimensional grid. Participants were to mentally rotate the grid and then maintain the rotated representation in anticipation of a test stimulus: a rendering of the grid, rotated 90° from the original viewpoint. The test stimulus was either a “match” display, in which object-location relations were intact, or a “mismatch” display, in which one object occupied a new, previously unfilled location (mismatch position), or two objects had swapped locations (mismatch swap). Encoding phase activation in anterior and posterior regions of the left hippocampus, and in bilateral perirhinal cortex, predicted subsequent accuracy on the short-term memory decision, as did bilateral posterior hippocampal activity after the test stimulus. Notably, activation in these posterior hippocampal regions was also sensitive to the degree to which object-location bindings were preserved in the test stimulus; activation was greatest for match displays, followed by mismatch-position displays, and finally mismatch-swap displays. These results indicate that the hippocampus and related MTL structures contribute to successful encoding and retrieval of relational information in visual short-term memory. PMID:18171929

  9. [Predicting the success of occupational retraining using the occupational aptitude test battery].

    Science.gov (United States)

    Kreuzpointner, L

    2009-04-01

    In vocational retraining centres, a test battery including several performance tests is generally administered to assess the occupational aptitude of rehabilitants and to predict their success in occupational retraining. This paper presents the multiple regressions of a set of achievement scores on "grades of retraining" and "grades of final examination", respectively, concerning retraining to become an office management assistant. It was shown that only few variables are adequate to clarify a maximum of variance of the criterions. Four different regression models were identified; each of them could clarify about 25% of variance. Significant predictors were indicators for verbal skills and basic numeracy. In each model a measurement for nonverbal intelligence had to be taken into account as a suppressor variable. To put all in a nutshell, in order to predict the success of vocational retraining to become an office management assistant it is more important to focus on strengthening school knowledge than on general intelligence.

  10. Zephyr - the prediction models

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg

    2001-01-01

    This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Dani...

  11. On-treatment predictions of success in peg-interferon/ribavirin treatment using a novel formula

    Institute of Scientific and Technical Information of China (English)

    Hidetsugu; Saito; Hirotoshi; Ebinuma; Keisuke; Ojiro; Kanji; Wakabayashi; Mika; Inoue; Shinichiro; Tada; Toshifumi; Hibi

    2010-01-01

    AIM:To predict treatment success using only simple clinical data from peg-interferon plus ribavirin therapy for chronic hepatitis C. METHODS:We analyzed the clinical data of 176 patients with chronic hepatitis and hepatitis C virus genotype 1 who received 48 wk standard therapy, derived a predictive formula to assess a sustained virological response of the individual patient using a logistic regression model and confirmed the validity of this formula.The formula was constructed using data from the first 100...

  12. Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data

    CERN Document Server

    Mestyán, Márton; Kertész, János

    2012-01-01

    Use of socially generated "big data" to access information about collective states of the minds in human societies becomes a new paradigm in the emerging field of computational social science. One of the natural application of this would be prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging between "real time monitoring" and "early predicting" remains as a big challenge. Here, we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie could be predicted well in advance by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.

  13. Early prediction of movie box office success based on Wikipedia activity big data.

    Directory of Open Access Journals (Sweden)

    Márton Mestyán

    Full Text Available Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.

  14. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used...... to distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...

  15. Modelling, controlling, predicting blackouts

    CERN Document Server

    Wang, Chengwei; Baptista, Murilo S

    2016-01-01

    The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids, and another one for smart grids. The control strategie...

  16. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Can success and failure be predicted for baccalaureate graduates on the computerized NCLEX-RN?

    Science.gov (United States)

    Seldomridge, Lisa A; Dibartolo, Mary C

    2004-01-01

    The current shortage of nurses and declining national pass rate on the National Council Licensure Examination for Registered Nurses (NCLEX-RN) has heightened educators' interest in identifying students at risk for failure. A retrospective descriptive study was conducted at a rural, public baccalaureate nursing program to determine variables that best predict NCLEX-RN success and failure. Data collected from 1998 through 2002 (N = 186) included entry as native or transfer student, preadmission grade point average (GPA), GPA after completing one semester of nursing courses, cumulative GPA at graduation, grades earned in prerequisite and core nursing courses, test averages in beginning and advanced medical/surgical nursing courses, and performance on the National League for Nursing Comprehensive Achievement Test for Baccalaureate Students (NLNCATBS). Logistic regression analysis revealed that a combination of test average in advanced medical/surgical nursing and percentile score on the NLNCATBS predicted 94.7 percent of NCLEX-RN passes and 33.3 percent of failures. The combination of NLNCATBS score and pathophysiology grade predicted 93.3 percent of NCLEX-RN passes and 50 percent of failures. Although success could be accurately predicted across all models, predicting failure was far more difficult.

  18. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy production......The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...... and HIRLAM predictions. The statistical models belong to the class of conditional parametric models. The models are estimated using local polynomial regression, but the estimation method is here extended to be adaptive in order to allow for slow changes in the system e.g. caused by the annual variations...

  19. Bilingual nurse education program: applicant characteristics that predict success.

    Science.gov (United States)

    Bosch, Paul C; Doshier, Sally A; Gess-Newsome, Julie

    2012-01-01

    Nurses are in great demand across the United States, but those fluent in both Spanish and English are in particularly short supply. This study examined three cohorts of students that entered a Spanish-English nursing education program to determine characteristics of applicants that produced student success. Unlike many nursing programs, entrance requirements for this bilingual program did not include a minimal grade point average (GPA) or previous course completions. Logistic regression was used to analyze the relationship between five different characteristics of entering students and their later success in the program. Success was measured in terms of program persistence and performance on the NCLEX-PN and NCLEX-RN exams. Incoming students with relatively high GPAs (M = 3.2) were significantly more likely to persist through the entire nursing 0ronram and oass the NCLEX-RN exam (t < .05) than those with lower GPAs (M = 2.5).

  20. Style in the Age of Instagram: Predicting Success within the Fashion Industry using Social Media

    CERN Document Server

    Park, Jaehyuk; Ferrara, Emilio

    2015-01-01

    Fashion is a multi-billion dollar industry with social and economic implications worldwide. To gain popularity, brands want to be represented by the top popular models. As new faces are selected using stringent (and often criticized) aesthetic criteria, \\emph{a priori} predictions are made difficult by information cascades and other fundamental trend-setting mechanisms. However, the increasing usage of social media within and without the industry may be affecting this traditional system. We therefore seek to understand the ingredients of success of fashion models in the age of Instagram. Combining data from a comprehensive online fashion database and the popular mobile image-sharing platform, we apply a machine learning framework to predict the tenure of a cohort of new faces for the 2015 Spring\\,/\\,Summer season throughout the subsequent 2015-16 Fall\\,/\\,Winter season. Our framework successfully predicts most of the new popular models who appeared in 2015. In particular, we find that a strong social media pr...

  1. Predicting MBA Student Success and Streamlining the Admissions Process

    Science.gov (United States)

    Pratt, William R.

    2015-01-01

    Within this study the author examines factors commonly employed as master of business administration applicant evaluation criteria to see if these criteria are important in determining an applicant's potential for success. The findings indicate that the Graduate Management Admissions Test (GMAT) is not a significant predictor of student success…

  2. Predicting MBA Student Success and Streamlining the Admissions Process

    Science.gov (United States)

    Pratt, William R.

    2015-01-01

    Within this study the author examines factors commonly employed as master of business administration applicant evaluation criteria to see if these criteria are important in determining an applicant's potential for success. The findings indicate that the Graduate Management Admissions Test (GMAT) is not a significant predictor of student success…

  3. Predicting the Future: Incarcerated Women's Views of Reentry Success

    Science.gov (United States)

    Cobbina, Jennifer E.; Bender, Kimberly A.

    2012-01-01

    Research reveals that most incarcerated adults are optimistic about their chances of success after release and believe they will be less likely to reoffend than other prisoners. Moreover, studies suggest that optimism shapes desistance. This raises the interesting question of how and why female inmates maintain an optimistic outlook about their…

  4. Factors predictive of drop-out and weight loss success in weight management of obese patients.

    Science.gov (United States)

    Hadžiabdić, M Ortner; Mucalo, I; Hrabač, P; Matić, T; Rahelić, D; Božikov, V

    2015-02-01

    The prevention and treatment of overweight and obese individuals on a population-wide basis is challenging because patients have difficulties with adhering to weight loss programmes. The present study aimed to evaluate patients' adherence to the weight reduction programme by identifying factors predictive of both drop-out rate and weight loss success. One-hundred and twenty-four obese patients participated in a 12-month weight reduction programme, involving group therapy during an intensive 5-day educational intervention, followed by five, 2-h follow-up visits. The primary outcome measures included drop-out rate and percentage weight loss. Sociodemographic and clinical characteristics, as well as type of diet, were explored as potential predictive factors. Type of diet was assigned based on randomisation. Regression analyses were conducted to identify predictive variables of drop-out and weight loss success. In total, 33.1% of all recruited participants were deemed successful because they reduced the initial weight by more than 5% after the 12-month intervention. The overall attrition rate was 32.3%. In a multiple regression model, initial weight loss and marital status were the strongest predictors of weight loss success after 1-year period (r(2) = 0.481, P drop-out were those with a lower educational level [odds ratio (OR) = 3.26, 95% confidence interval (CI) = 1.22-8.70, P = 0.018] and a higher level of obesity (OR = 0.974, 95% CI = 0.95-0.99, P = 0.010). The present study demonstrates that initial weight loss at 1 month made the strongest unique contribution to the prediction of percentage weight loss after 12 months, whereas being married was a negative predictor. Those with a lower educational level and a higher level of obesity were more likely to drop-out. © 2014 The British Dietetic Association Ltd.

  5. Predicting NCLEX-RN Success: Can It Be Simplified?

    Science.gov (United States)

    Waterhouse, Julie Keith; Beeman, Pamela B.

    2003-01-01

    The Risk Appraisal Instrument was adapted and applied to records of 538 graduates of a nursing program 1995-1998. The instrument correctly classified nearly 61% of failures on the National Council Licensure Exam for Registered Nurses and correctly predicted 72% of overall results. In comparison, statistically more complex methods classify 76-92%…

  6. Prediction of Success at Typing. Technical Report 539.

    Science.gov (United States)

    Cleaver, Thomas G.; O'Connor, Carol A.

    A study evaluated the validity of the use of digital dexterity and reaction time as variables to predict students' gross typing speed. To gather data for the study, researchers tested approximately 120 students from three typing classes at Jefferson Community College in Louisiana and one typing class at the University of Louisville (Kentucky). In…

  7. Predicting Student Success Following Transition from Bilingual Programs.

    Science.gov (United States)

    Fischer, Kathleen B.; Cabello, Beverly

    A bilingual prediction study was conducted in order to gather information that school districts could use in making decisions about instructional transition for students in transitional bilingual programs. In 1976, 115 third graders were tested in reading, verbal ability, and aural comprehension in both English and Spanish. Attitude toward…

  8. Post-graduation factors predicting NCLEX-RN success.

    Science.gov (United States)

    Beeman, Pamela Butler; Waterhouse, Julie Keith

    2003-01-01

    The academic and nonacademic factors that influence nursing students' success on the licensure exam have been widely reported. However, many questions remain as to why certain candidates fail the exam. This pilot study explores postgraduation influences on the NCLEX-RN.(R) Factors such as length and type of study, work hours, review course participation, sleep, and stress were recorded using the newly developed NCLEX Preparation Survey. Results suggest both expected and unexpected relationships between these factors and NCLEX-RN mastery.

  9. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik

    2001-01-01

    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence...

  10. Successful prediction of horse racing results using a neural network

    OpenAIRE

    Allinson, N. M.; Merritt, D.

    1991-01-01

    Most application work within neural computing continues to employ multi-layer perceptrons (MLP). Though many variations of the fully interconnected feed-forward MLP, and even more variations of the back propagation learning rule, exist; the first section of the paper attempts to highlight several properties of these standard networks. The second section outlines an application-namely the prediction of horse racing results

  11. Global Solar Dynamo Models: Simulations and Predictions

    Indian Academy of Sciences (India)

    Mausumi Dikpati; Peter A. Gilman

    2008-03-01

    Flux-transport type solar dynamos have achieved considerable success in correctly simulating many solar cycle features, and are now being used for prediction of solar cycle timing and amplitude.We first define flux-transport dynamos and demonstrate how they work. The essential added ingredient in this class of models is meridional circulation, which governs the dynamo period and also plays a crucial role in determining the Sun’s memory about its past magnetic fields.We show that flux-transport dynamo models can explain many key features of solar cycles. Then we show that a predictive tool can be built from this class of dynamo that can be used to predict mean solar cycle features by assimilating magnetic field data from previous cycles.

  12. Predicting parameters of degradation succession processes of Tibetan Kobresia grasslands

    Science.gov (United States)

    Lin, L.; Li, Y. K.; Xu, X. L.; Zhang, F. W.; Du, Y. G.; Liu, S. L.; Guo, X. W.; Cao, G. M.

    2015-11-01

    In the past two decades, increasing human activity (i.e., overgrazing) in the Tibetan Plateau has strongly influenced plant succession processes, resulting in the degradation of alpine grasslands. Therefore, it is necessary to diagnose the degree of degradation to enable implementation of appropriate management for sustainable exploitation and protection of alpine grasslands. Here, we investigated environmental factors and plant functional group (PFG) quantity factors during the alpine grassland succession processes. Principal component analysis (PCA) was used to identify the parameters indicative of degradation. We divided the entire degradation process into six stages. PFG types shifted from rhizome bunchgrasses to rhizome plexus and dense-plexus grasses during the degradation process. Leguminosae and Gramineae plants were replaced by sedges during the advanced stages of degradation. The PFGs were classified into two reaction groups: the grazing-sensitive group, containing Kobresia humilis Mey, and Gramineae and Leguminosae plants, and the grazing-insensitive group, containing Kobresia pygmaea Clarke. The first group was correlated with live root biomass in the surface soil (0-10 cm), whereas the second group was strongly correlated with mattic epipedon thickness and K. pygmaea characteristics. The degree of degradation of alpine meadows may be delineated by development of mattic epipedon and PFG composition. Thus, meadows could be easily graded and their use adjusted based on our scaling system, which would help prevent irreversible degradation of important grasslands. Because relatively few environmental factors are investigated, this approach can save time and labor to formulate a conservation management plan for degraded alpine meadows.

  13. Methodology for predicting the young wrestlers success of sporting activities in various stages of ontogeny.

    Directory of Open Access Journals (Sweden)

    Horiakov V.A.

    2011-04-01

    Full Text Available The mathematical models to predict the success of judo 9-16 years, up to 81% are designed. It is based on anthropometric and psychophysiological parameters. For wrestlers 9-11 years the most important prognostic indicators are features of somatotype and the power of anaerobic energy mechanism. In the 12-13 years in the first place are the power of anaerobic energy mechanism and the functional state of sensory systems. For wrestlers aged 14-16 is the most important system-wide properties of the brain and the ergic of nervous system.

  14. Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning

    Directory of Open Access Journals (Sweden)

    Shandilya Sharad

    2012-10-01

    Full Text Available Abstract Background Ventricular Fibrillation (VF is a common presenting dysrhythmia in the setting of cardiac arrest whose main treatment is defibrillation through direct current countershock to achieve return of spontaneous circulation. However, often defibrillation is unsuccessful and may even lead to the transition of VF to more nefarious rhythms such as asystole or pulseless electrical activity. Multiple methods have been proposed for predicting defibrillation success based on examination of the VF waveform. To date, however, no analytical technique has been widely accepted. We developed a unique approach of computational VF waveform analysis, with and without addition of the signal of end-tidal carbon dioxide (PetCO2, using advanced machine learning algorithms. We compare these results with those obtained using the Amplitude Spectral Area (AMSA technique. Methods A total of 90 pre-countershock ECG signals were analyzed form an accessible preshosptial cardiac arrest database. A unified predictive model, based on signal processing and machine learning, was developed with time-series and dual-tree complex wavelet transform features. Upon selection of correlated variables, a parametrically optimized support vector machine (SVM model was trained for predicting outcomes on the test sets. Training and testing was performed with nested 10-fold cross validation and 6–10 features for each test fold. Results The integrative model performs real-time, short-term (7.8 second analysis of the Electrocardiogram (ECG. For a total of 90 signals, 34 successful and 56 unsuccessful defibrillations were classified with an average Accuracy and Receiver Operator Characteristic (ROC Area Under the Curve (AUC of 82.2% and 85%, respectively. Incorporation of the end-tidal carbon dioxide signal boosted Accuracy and ROC AUC to 83.3% and 93.8%, respectively, for a smaller dataset containing 48 signals. VF analysis using AMSA resulted in accuracy and ROC AUC of 64

  15. Predictive models of forest dynamics.

    Science.gov (United States)

    Purves, Drew; Pacala, Stephen

    2008-06-13

    Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

  16. Transfer Student Success: Educationally Purposeful Activities Predictive of Undergraduate GPA

    Science.gov (United States)

    Fauria, Renee M.; Fuller, Matthew B.

    2015-01-01

    Researchers evaluated the effects of Educationally Purposeful Activities (EPAs) on transfer and nontransfer students' cumulative GPAs. Hierarchical, linear, and multiple regression models yielded seven statistically significant educationally purposeful items that influenced undergraduate student GPAs. Statistically significant positive EPAs for…

  17. Predicting students' success at pre-university studies using linear and logistic regressions

    Science.gov (United States)

    Suliman, Noor Azizah; Abidin, Basir; Manan, Norhafizah Abdul; Razali, Ahmad Mahir

    2014-09-01

    The study is aimed to find the most suitable model that could predict the students' success at the medical pre-university studies, Centre for Foundation in Science, Languages and General Studies of Cyberjaya University College of Medical Sciences (CUCMS). The predictors under investigation were the national high school exit examination-Sijil Pelajaran Malaysia (SPM) achievements such as Biology, Chemistry, Physics, Additional Mathematics, Mathematics, English and Bahasa Malaysia results as well as gender and high school background factors. The outcomes showed that there is a significant difference in the final CGPA, Biology and Mathematics subjects at pre-university by gender factor, while by high school background also for Mathematics subject. In general, the correlation between the academic achievements at the high school and medical pre-university is moderately significant at α-level of 0.05, except for languages subjects. It was found also that logistic regression techniques gave better prediction models than the multiple linear regression technique for this data set. The developed logistic models were able to give the probability that is almost accurate with the real case. Hence, it could be used to identify successful students who are qualified to enter the CUCMS medical faculty before accepting any students to its foundation program.

  18. Predicting Successful Recanalization in Patients with Native Coronary Chronic Total Occlusion: The Busan CTO Score.

    Science.gov (United States)

    Jin, Cai De; Kim, Moo Hyun; Kim, Soo Jin; Lee, Kwang Min; Kim, Tae Hyung; Cho, Young-Rak; Serebruany, Victor L

    2017-01-01

    The optimal strategy to manage chronic total occlusion (CTO) remains unclear. The Japanese CTO multicenter registry (J-CTO) score is an established tool for predicting successful recanalization. However, it does not take into account nonangiographic predictors for final technique success. In the present study, we designed and tested a scoring model called the Busan single-center CTO registry (B-CTO) score combining clinical and angiographic characteristics to predict successful CTO recanalization in Korean patients. Prospectively enrolled CTO patients (n = 438) undergoing coronary intervention (1999-2015) were assessed. The B-CTO score comprises 6 independent predictors: age 60-74 years and lesion length ≥20 mm were assigned 1 point each, while age ≥75 years, female gender, lesion location in the right coronary artery, blunt stump, and bending >45° were assigned 2 points each. For each predictor, the points assigned were based on the associated odds ratio by multivariate analysis. The lesions were classified into 4 groups according to the summation of points scored to assess the probability of successful CTO recanalization: easy (score 0-1), intermediate (score 2-3), difficult (score 4-5), and very difficult (score ≥6). CTO opening was designated as the primary endpoint regardless of the interventional era or the skill of the operator. The final success rate for B-CTO was 81.1%. The probability of successful recanalization for patient groups classified as easy (n = 64), intermediate (n = 148), difficult (n = 134), and very difficult (n = 92) was 95.3, 86.5, 79.1 and 65.2%, respectively (p for trend CTO, the B-CTO score demonstrated a significant improvement in discrimination as indicated by the area under the receiver-operator characteristic curve (AUC 0.083; 95% CI 0.025-0.141), with a positive integrated discrimination improvement of 0.042 and a net reclassification improvement of 56.0%. The B-CTO score has been designed and validated in Korean patients

  19. Predicting successful introduction of novel fruit to preschool children.

    Science.gov (United States)

    Blissett, Jacqueline; Bennett, Carmel; Donohoe, Jessica; Rogers, Samantha; Higgs, Suzanne

    2012-12-01

    Few children eat sufficient fruits and vegetables despite their established health benefits. The feeding practices used by parents when introducing novel foods to their children, and their efficacy, require further investigation. We aimed to establish which feeding strategies parents commonly use when introducing a novel fruit to their preschool-aged children and assess the effectiveness of these feeding strategies on children's willingness to try a novel fruit. Correlational design. Twenty-five parents and their children aged 2 to 4 years attended our laboratory and consumed a standardized lunch, including a novel fruit. Interactions between parent and child were recorded and coded. Pearson's correlations and multiple linear regression analyses. The frequency with which children swallowed and enjoyed the novel fruit, and the frequency of taste exposures to the novel fruit during the meal, were positively correlated with parental use of physical prompting and rewarding/bargaining. Earlier introduction of solids was related to higher frequency of child acceptance behaviors. The child's age at introduction of solids and the number of physical prompts displayed by parents significantly predicted the frequency of swallowing and enjoying the novel fruit. Age of introduction to solids and parental use of rewards/bargaining significantly predicted the frequency of taste exposures. Prompting a child to eat and using rewards or bargains during a positive mealtime interaction can help to overcome barriers to novel fruit consumption. Early introduction of solids is also associated with greater willingness to consume a novel fruit. Copyright © 2012 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

  20. Remote health monitoring: predicting outcome success based on contextual features for cardiovascular disease.

    Science.gov (United States)

    Alshurafa, Nabil; Eastwood, Jo-Ann; Pourhomayoun, Mohammad; Liu, Jason J; Sarrafzadeh, Majid

    2014-01-01

    Current studies have produced a plethora of remote health monitoring (RHM) systems designed to enhance the care of patients with chronic diseases. Many RHM systems are designed to improve patient risk factors for cardiovascular disease, including physiological parameters such as body mass index (BMI) and waist circumference, and lipid profiles such as low density lipoprotein (LDL) and high density lipoprotein (HDL). There are several patient characteristics that could be determining factors for a patient's RHM outcome success, but these characteristics have been largely unidentified. In this paper, we analyze results from an RHM system deployed in a six month Women's Heart Health study of 90 patients, and apply advanced feature selection and machine learning algorithms to identify patients' key baseline contextual features and build effective prediction models that help determine RHM outcome success. We introduce Wanda-CVD, a smartphone-based RHM system designed to help participants with cardiovascular disease risk factors by motivating participants through wireless coaching using feedback and prompts as social support. We analyze key contextual features that secure positive patient outcomes in both physiological parameters and lipid profiles. Results from the Women's Heart Health study show that health threat of heart disease, quality of life, family history, stress factors, social support, and anxiety at baseline all help predict patient RHM outcome success.

  1. Predicting STEM Career Success by STI Knowledge Utilization Patterns

    Energy Technology Data Exchange (ETDEWEB)

    Bozeman, B.; Youtie, J.; Bretschneider, S.

    2016-07-01

    As a part of discussion on knowledge utilization on science and technology, the mixed of papers presented in the panel discussion is designed to illustrate the patterns of collaboration, mobility, and diffusion of knowledge as well as those of labor force. In particular, the first two papers presented in the panel explore the potential of STEM career success through cosmopolitan collaboration and international community collaboration (focused on the relationships between China and Russia) in nanotechnology, which would provide implications on national and international benchmarking of innovation. For policy implications on graduate education and innovation, mobility pattern of non-U.S. Ph.D. degree holders is examined, and impact of a policy report on the target academic communities is investigated through development of credibility map. This panel is designed to highlight a recent effort of understanding geographical, cognitive or social spaces that are present in the scientific and technological activity as well as in doctoral education. The papers presented in this panel, therefore, will provide a rich set of significant and relevant insights drawn from examining STI knowledge utilization patterns to the STI-ENID community. The anticipated length of the event may be 90 minutes and there is no preferred number of attendees in particular although it is expected to be in between 35 and 60 at the minimum. (Author)

  2. Some uses of predictive probability of success in clinical drug development

    Directory of Open Access Journals (Sweden)

    Mauro Gasparini

    2013-03-01

    Full Text Available Predictive probability of success is a (subjective Bayesian evaluation of the prob- ability of a future successful event in a given state of information. In the context of pharmaceutical clinical drug development, successful events relate to the accrual of positive evidence on the therapy which is being developed, like demonstration of su- perior efficacy or ascertainment of safety. Positive evidence will usually be obtained via standard frequentist tools, according to the regulations imposed in the world of pharmaceutical development.Within a single trial, predictive probability of success can be identified with expected power, i.e. the evaluation of the success probability of the trial. Success means, for example, obtaining a significant result of a standard superiority test.Across trials, predictive probability of success can be the probability of a successful completion of an entire part of clinical development, for example a successful phase III development in the presence of phase II data.Calculations of predictive probability of success in the presence of normal data with known variance will be illustrated, both for within-trial and across-trial predictions.

  3. Dive characteristics can predict foraging success in Australian fur seals (Arctocephalus pusillus doriferus as validated by animal-borne video

    Directory of Open Access Journals (Sweden)

    Beth L. Volpov

    2016-03-01

    Full Text Available Dive characteristics and dive shape are often used to infer foraging success in pinnipeds. However, these inferences have not been directly validated in the field with video, and it remains unclear if this method can be applied to benthic foraging animals. This study assessed the ability of dive characteristics from time-depth recorders (TDR to predict attempted prey capture events (APC that were directly observed on animal-borne video in Australian fur seals (Arctocephalus pusillus doriferus, n=11. The most parsimonious model predicting the probability of a dive with ≥1 APC on video included only descent rate as a predictor variable. The majority (94% of the 389 total APC were successful, and the majority of the dives (68% contained at least one successful APC. The best model predicting these successful dives included descent rate as a predictor. Comparisons of the TDR model predictions to video yielded a maximum accuracy of 77.5% in classifying dives as either APC or non-APC or 77.1% in classifying dives as successful verses unsuccessful. Foraging intensity, measured as either total APC per dive or total successful APC per dive, was best predicted by bottom duration and ascent rate. The accuracy in predicting total APC per dive varied based on the number of APC per dive with maximum accuracy occurring at 1 APC for both total (54% and only successful APC (52%. Results from this study linking verified foraging dives to dive characteristics potentially opens the door to decades of historical TDR datasets across several otariid species.

  4. Prediction models from CAD models of 3D objects

    Science.gov (United States)

    Camps, Octavia I.

    1992-11-01

    In this paper we present a probabilistic prediction based approach for CAD-based object recognition. Given a CAD model of an object, the PREMIO system combines techniques of analytic graphics and physical models of lights and sensors to predict how features of the object will appear in images. In nearly 4,000 experiments on analytically-generated and real images, we show that in a semi-controlled environment, predicting the detectability of features of the image can successfully guide a search procedure to make informed choices of model and image features in its search for correspondences that can be used to hypothesize the pose of the object. Furthermore, we provide a rigorous experimental protocol that can be used to determine the optimal number of correspondences to seek so that the probability of failing to find a pose and of finding an inaccurate pose are minimized.

  5. DKIST Polarization Modeling and Performance Predictions

    Science.gov (United States)

    Harrington, David

    2016-05-01

    Calibrating the Mueller matrices of large aperture telescopes and associated coude instrumentation requires astronomical sources and several modeling assumptions to predict the behavior of the system polarization with field of view, altitude, azimuth and wavelength. The Daniel K Inouye Solar Telescope (DKIST) polarimetric instrumentation requires very high accuracy calibration of a complex coude path with an off-axis f/2 primary mirror, time dependent optical configurations and substantial field of view. Polarization predictions across a diversity of optical configurations, tracking scenarios, slit geometries and vendor coating formulations are critical to both construction and contined operations efforts. Recent daytime sky based polarization calibrations of the 4m AEOS telescope and HiVIS spectropolarimeter on Haleakala have provided system Mueller matrices over full telescope articulation for a 15-reflection coude system. AEOS and HiVIS are a DKIST analog with a many-fold coude optical feed and similar mirror coatings creating 100% polarization cross-talk with altitude, azimuth and wavelength. Polarization modeling predictions using Zemax have successfully matched the altitude-azimuth-wavelength dependence on HiVIS with the few percent amplitude limitations of several instrument artifacts. Polarization predictions for coude beam paths depend greatly on modeling the angle-of-incidence dependences in powered optics and the mirror coating formulations. A 6 month HiVIS daytime sky calibration plan has been analyzed for accuracy under a wide range of sky conditions and data analysis algorithms. Predictions of polarimetric performance for the DKIST first-light instrumentation suite have been created under a range of configurations. These new modeling tools and polarization predictions have substantial impact for the design, fabrication and calibration process in the presence of manufacturing issues, science use-case requirements and ultimate system calibration

  6. Ball Speed and Release Consistency Predict Pitching Success in Major League Baseball.

    Science.gov (United States)

    Whiteside, David; Martini, Douglas N; Zernicke, Ronald F; Goulet, Grant C

    2016-07-01

    Whiteside, D, Martini, DN, Zernicke, RF, and Goulet, GC. Ball speed and release consistency predict pitching success in Major League Baseball. J Strength Cond Res XX(X): 000-000, 2015-This study aimed to quantify how ball flight kinematics (i.e., ball speed and movement), release location, and variations therein relate to pitching success in Major League Baseball (MLB). One hundred ninety starting MLB pitchers met the inclusion criteria for this study. Ball trajectory information was collected for 76,000 pitches and inserted into a forward stepwise multiple regression model, which examined how (a) pitch selection, (b) ball speed, (c) ball movement (horizontal and lateral), (d) release location (horizontal and lateral), (e) variation in pitch speed, (f) variation in ball movement, and (g) variation in release location related to pitching success (as measured by fielding independent pitching-FIP). Pitch speed, release location variability, variation in pitch speed, and horizontal release location were significant predictors of FIP and, collectively, accounted for 24% of the variance in FIP. These findings suggest that (a) maximizing ball speed, (b) refining a consistent spatial release location, and (c) using varied pitch speeds should be primary foci for the pitching coach. However, between-pitcher variations underline how training interventions should be administered at the individual level, with consideration given to the pitcher's injury history. Finally, despite offering significant predictors of success, these three factors explained only 22% of the variance in FIP and should not be considered the only, or preeminent, indicators of a pitcher's effectiveness. Evidently, traditional pitching metrics only partly account for a pitcher's effectiveness, and future research is necessary to uncover the remaining contributors to success.

  7. Prediction of successful induction of labour wıth dinoprostone in a ...

    African Journals Online (AJOL)

    Several systematic reviews have shown that prostaglandins are superior to placebo and ... fail in predicting the success of labour induction, particularly in patients with an ... the onset of cervical dilatation and contractions. The follow-up.

  8. Caries risk assessment models in caries prediction

    Directory of Open Access Journals (Sweden)

    Amila Zukanović

    2013-11-01

    Full Text Available Objective. The aim of this research was to assess the efficiency of different multifactor models in caries prediction. Material and methods. Data from the questionnaire and objective examination of 109 examinees was entered into the Cariogram, Previser and Caries-Risk Assessment Tool (CAT multifactor risk assessment models. Caries risk was assessed with the help of all three models for each patient, classifying them as low, medium or high-risk patients. The development of new caries lesions over a period of three years [Decay Missing Filled Tooth (DMFT increment = difference between Decay Missing Filled Tooth Surface (DMFTS index at baseline and follow up], provided for examination of the predictive capacity concerning different multifactor models. Results. The data gathered showed that different multifactor risk assessment models give significantly different results (Friedman test: Chi square = 100.073, p=0.000. Cariogram is the model which identified the majority of examinees as medium risk patients (70%. The other two models were more radical in risk assessment, giving more unfavorable risk –profiles for patients. In only 12% of the patients did the three multifactor models assess the risk in the same way. Previser and CAT gave the same results in 63% of cases – the Wilcoxon test showed that there is no statistically significant difference in caries risk assessment between these two models (Z = -1.805, p=0.071. Conclusions. Evaluation of three different multifactor caries risk assessment models (Cariogram, PreViser and CAT showed that only the Cariogram can successfully predict new caries development in 12-year-old Bosnian children.

  9. Blinded Observer Evaluation of Distal Skin Temperature for Predicting Lateral Infraclavicular Block Success

    DEFF Research Database (Denmark)

    Asghar, Semera; Lange, Kai H W; Lundstrøm, Lars H

    2015-01-01

    BACKGROUND: Changes in digit skin temperature may be used to predict and determine upper limb nerve block success. We investigated whether a temperature difference between the blocked and the nonblocked hands, simply registered by touching the skin of the 5th and 2nd digit was valid and reliable...... as a diagnostic test for predicting a successful lateral infraclavicular block. METHODS: Blinded observers investigated temperature difference between the blocked and the nonblocked hands of 40 patients. Sensitivity, specificity, and predictive values of a positive and a negative test were estimated...... of the test. RESULTS: As a stand-alone test, a temperature difference between the corresponding 2nd and 5th digits of the blocked and the nonblocked hands predicted a successful block with a sensitivity of 92% (95 % confidence interval (CI), 83%-97%) and with a predictive value of a positive test of 95% (CI...

  10. Financial modeling: Rx for financial success.

    Science.gov (United States)

    Marino, D

    2001-01-01

    In an era of managed care, cost cutting and finding ways to increase revenue are key goals in the survival of group practices. Many practices find that they have to boost their revenue by a certain amount (for example, 20-30% within the next three years) to maintain viability in the health care marketplace. Understanding how to generate that revenue and influence short-term and long-term financial outcomes is a far trickier process. This article details how practice administrators can influence a practice's bottom line through a three-step process: (1) identify the components of the practice's financial performance and drivers of performance results, (2) diagnose the practice's current financial situation, and (3) pinpoint benchmarks and targets for success.

  11. Relative roles of cognitive ability and practical intelligence in the prediction of success.

    Science.gov (United States)

    Taub, G E; Hayes, B G; Cunningham, W R; Sivo, S A

    2001-06-01

    Initial investigations into the construct of practical intelligence have identified a new general factor of practical intelligence (gp), which is believed to be independent of general cognitive ability. This construct, gp, is also believed to be a better predictor of success than cognitive ability, personality, or any combination of variables independent of gp. The existence of this construct and its independence from Spearman's g is, however, under debate. The purpose of the present study is to investigate both the relationship between gp and g and the relative roles of practical intelligence and cognitive ability in the prediction of success. The participants included 197 college students. Each completed both the Multidimensional Aptitude Battery and Sternberg and Wagner's measure of practical intelligence in academic psychology. The results of structural equation modeling support Sternberg and Wagner's assertion that practical intelligence and general cognitive ability are relatively independent constructs. Results of regression analysis, however, do not support their contention that practical intelligence is related to success after controlling for general cognitive ability. Implications of these results for research and theory on practical intelligence are discussed.

  12. Using Standardized Tests to Identify Prior Knowledge Necessary for Success in Algebra: A Predictive Analysis

    Science.gov (United States)

    Jensen, Jennifer

    2014-01-01

    This study sought to determine if there is a relationship between students' scores on the eighth-grade Indiana State Test of Education Progress Plus (ISTEP+) exam and success on Indiana's Algebra End-of-Course Assessment (ECA). Additionally, it sought to determine if algebra success could be significantly predicted by the achievement in one or…

  13. Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

    Science.gov (United States)

    Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

    2009-01-01

    Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

  14. Value of College Education Mediating the Predictive Effects of Causal Attributions on Academic Success

    Science.gov (United States)

    Dong, Ying; Stupnisky, Robert H.; Obade, Masela; Gerszewski, Tammy; Ruthig, Joelle C.

    2015-01-01

    Causal attributions (explanations for outcomes) have been found to predict college students' academic success; however, not all students attributing success or failure to adaptive (i.e., controllable) causes perform well in university. Eccles et al.'s ("Achievement and achievement motives." W.H. Freeman, San Francisco, pp 75-145, 1983)…

  15. Using Standardized Tests to Identify Prior Knowledge Necessary for Success in Algebra: A Predictive Analysis

    Science.gov (United States)

    Jensen, Jennifer

    2014-01-01

    This study sought to determine if there is a relationship between students' scores on the eighth-grade Indiana State Test of Education Progress Plus (ISTEP+) exam and success on Indiana's Algebra End-of-Course Assessment (ECA). Additionally, it sought to determine if algebra success could be significantly predicted by the achievement in one or…

  16. Using an admissions exam to predict student success in an ADN program.

    Science.gov (United States)

    Gallagher, P A; Bomba, C; Crane, L R

    2001-01-01

    Nursing faculty strive to admit students who are likely to successfully complete the nursing curriculum and pass NCLEX-RN. The high cost of academic preparation and the nursing shortage make this selection process even more critical. The authors discuss how one community college nursing program examined academic achievement measures to determine how well they predicted student success. Results provided faculty with useful data to improve the success and retention of nursing.

  17. Does Trait Emotional Intelligence Predict Unique Variance in Early Career Success Beyond IQ and Personality?

    OpenAIRE

    Haro García, José Manuel de; Castejón Costa, Juan Luis

    2014-01-01

    In order to determine the contribution of emotional intelligence (EI) to career success, in this study, we analyzed the relationship between trait EI (TEI), general mental ability (GMA), the big five personality traits, and career success indicators, in a sample of 130 graduates who were in the early stages of their careers. Results from hierarchical regression analyses indicated that TEI, and especially its dimension “repair,” has incremental validity in predicting one of the career success ...

  18. Does Trait Emotional Intelligence Predict Unique Variance in Early Career Success Beyond IQ and Personality?

    OpenAIRE

    Haro García, José Manuel de; Castejón Costa, Juan Luis (coord.)

    2014-01-01

    In order to determine the contribution of emotional intelligence (EI) to career success, in this study, we analyzed the relationship between trait EI (TEI), general mental ability (GMA), the big five personality traits, and career success indicators, in a sample of 130 graduates who were in the early stages of their careers. Results from hierarchical regression analyses indicated that TEI, and especially its dimension “repair,” has incremental validity in predicting one of the career success ...

  19. Some uses of predictive probability of success in clinical drug development

    OpenAIRE

    Mauro Gasparini; Lilla Di Scala; Frank Bretz; Amy Racine-Poon

    2013-01-01

    Predictive probability of success is a (subjective) Bayesian evaluation of the prob- ability of a future successful event in a given state of information. In the context of pharmaceutical clinical drug development, successful events relate to the accrual of positive evidence on the therapy which is being developed, like demonstration of su- perior efficacy or ascertainment of safety. Positive evidence will usually be obtained via standard frequentist tools, according to the regulations impose...

  20. Prediction of bypass transition with differential Reynolds stress models

    NARCIS (Netherlands)

    Westin, K.J.A.; Henkes, R.A.W.M.

    1998-01-01

    Boundary layer transition induced by high levels of free stream turbulence (FSl), so called bypass transition, can not be predicted with conventional stability calculations (e.g. the en-method). The use of turbulence models for transition prediction has shown some success for this type of flows, and

  1. Humor Ability Reveals Intelligence, Predicts Mating Success, and Is Higher in Males

    Science.gov (United States)

    Greengross, Gil; Miller, Geoffrey

    2011-01-01

    A good sense of humor is sexually attractive, perhaps because it reveals intelligence, creativity, and other "good genes" or "good parent" traits. If so, intelligence should predict humor production ability, which in turn should predict mating success. In this study, 400 university students (200 men and 200 women) completed…

  2. Predicting Academic Success from Academic Motivation and Learning Approaches in Classroom Teaching Students

    Science.gov (United States)

    Çetin, Baris

    2015-01-01

    Our aim was to determine whether learning approaches and academic motivation together predict academic success of classroom teaching students. The sample of the study included 536 students (386 female, 150 male) studying at the Classroom Teaching Division of Canakkale 18 Mart University. Our research was designed as a prediction study. Data was…

  3. Humor Ability Reveals Intelligence, Predicts Mating Success, and Is Higher in Males

    Science.gov (United States)

    Greengross, Gil; Miller, Geoffrey

    2011-01-01

    A good sense of humor is sexually attractive, perhaps because it reveals intelligence, creativity, and other "good genes" or "good parent" traits. If so, intelligence should predict humor production ability, which in turn should predict mating success. In this study, 400 university students (200 men and 200 women) completed…

  4. Expanding on Successful Concepts, Models, and Organization

    Science.gov (United States)

    If the goal of the AEP framework was to replace existing exposure models or databases for organizing exposure data with a concept, we would share Dr. von Göetz concerns. Instead, the outcome we promote is broader use of an organizational framework for exposure science. The f...

  5. Predicting success of pharmacy students in basic science and clinical clerkship courses.

    Science.gov (United States)

    Kimberlin, C L; Hadsall, R S; Gourley, D R; Benedict, L K

    1983-04-01

    A number of studies on the ability of admissions variables to predict success in pharmacy schools have examined only success in the first professional year, which typically consists primarily of basic science courses. This study examined not only grades in basic science courses but also performance on clinical clerkships, for two classes of students. It also examined the ability of various personality variables to predict performance in clinical and basic science coursework. Previous grade point average (GPA) was the best single predictor of performance. In one class, the personality variable of Responsibility best predicted clinical clerkship performance. However, it only accounted for 13 percent of the variance in clerkship grades. Pharmacy College Admission Test (PCAT) Biology and PCAT Verbal Ability scores added to the predictive ability of previous GPA in one class, but none of the PCAT scales entered a prediction equation for the other class. The limitations on our ability to predict, with any consistency, academic performance in pharmacy school is discussed.

  6. LIFE DISTRIBUTION OF SERIES UNDER THE SUCCESSIVE DAMAGE MODEL

    Institute of Scientific and Technical Information of China (English)

    WANG Dongqian; C. D. Lai; LI Guoying

    2003-01-01

    We analyse further the reliability behaviour of series and parallel systems in the successive damage model initiated by Downton. The results are compared with those obtained for other models with different bivariate distributions.

  7. Model of key success factors for Business Intelligence implementation

    Directory of Open Access Journals (Sweden)

    Peter Mesaros

    2016-07-01

    Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

  8. Predictive Score Card in Lumbar Disc Herniation: Is It Reflective of Patient Surgical Success after Discectomy?

    Science.gov (United States)

    Azimi, Parisa; Benzel, Edward C; Montazeri, Ali

    2016-01-01

    Does the Finneson-Cooper score reflect the true value of predicting surgical success before discectomy? The aim of this study was to identify reliable predictors for surgical success two year after surgery for patients with LDH. Prospective analysis of 154 patients with LDH who underwent single-level lumbar discectomy was performed. Pre- and post-surgical success was assessed by the Oswestry Disability Index (ODI) over a 2-year period. The Finneson-Cooper score also was used for evaluation of the clinical results. Using the ODI, surgical success was defined as a 30% (or more) improvement on the ODI score from the baseline. The ODI was considered the gold standard in this study. Finally, the sensitivity, specificity, and positive and negative predictive power of the Finneson-Cooper score in predicting surgical success were calculated. The mean age of the patients was 49.6 (SD = 9.3) years and 47.4% were male. Significant improvement from the pre- to post-operative ODI scores was observed (P score. Regarding patients' surgical success, the sensitivity, specificity, and accuracy of the Finneson-Cooper ratings correlated with success rate. The findings indicated that the Finneson-Cooper score was reflective of surgical success before discectomy.

  9. The use of discriminant function analysis to predict student success on the NCLEX-RN.

    Science.gov (United States)

    Haas, Richard E; Nugent, Katherine E; Rule, Rebecca A

    2004-10-01

    Predicting whether a student will be successful on the National Council Licensure Examination for Registered Nurses (NCLEX-RN) has been an important endeavor for faculty in schools of nursing for the past 2 decades. Extensive documentation exists in the literature concerning research aimed at exploring the academic and nonacademic predictors of success on the NCLEX-RN. Reviews of the findings of these studies indicate that various factors emerge as academic predictors of success. The results of this study suggest that first-time success on the NCLEX-RN can be predicted with a high level of accuracy using existing student data. The findings also support the belief that it is possible to identify students who may be at risk for unsuccessful first time performance on the NCLEX-RN. Early identification of at-risk students will promote timely intervention strategies to optimize the students' potential for success.

  10. Predictive In Vivo Models for Oncology.

    Science.gov (United States)

    Behrens, Diana; Rolff, Jana; Hoffmann, Jens

    2016-01-01

    Experimental oncology research and preclinical drug development both substantially require specific, clinically relevant in vitro and in vivo tumor models. The increasing knowledge about the heterogeneity of cancer requested a substantial restructuring of the test systems for the different stages of development. To be able to cope with the complexity of the disease, larger panels of patient-derived tumor models have to be implemented and extensively characterized. Together with individual genetically engineered tumor models and supported by core functions for expression profiling and data analysis, an integrated discovery process has been generated for predictive and personalized drug development.Improved “humanized” mouse models should help to overcome current limitations given by xenogeneic barrier between humans and mice. Establishment of a functional human immune system and a corresponding human microenvironment in laboratory animals will strongly support further research.Drug discovery, systems biology, and translational research are moving closer together to address all the new hallmarks of cancer, increase the success rate of drug development, and increase the predictive value of preclinical models.

  11. A Model of Successful School Leadership from the International Successful School Principalship Project

    Directory of Open Access Journals (Sweden)

    David Gurr

    2015-03-01

    Full Text Available The International Successful School Principalship Project (ISSPP has been actively conducting research about the work of successful principals since 2001. Findings from four project books and eight models derived from this project are synthesised into a model of successful school leadership. Building on Gurr, Drysdale and Mulford’s earlier model, the work of school leaders is described as engaging within the school context to influence student and school outcomes through interventions in teaching and learning, school capacity building, and the wider context. The qualities a leader brings to their role, a portfolio approach to using leadership ideas, constructing networks, collaborations and partnerships, and utilising accountability and evaluation for evidence-informed improvement, are important additional elements. The model is applicable to all in leadership roles in schools.

  12. The Road of ERP Success: A Framework Model for Successful ERP Implementation

    Directory of Open Access Journals (Sweden)

    Sevenpri Candra

    2011-11-01

    Full Text Available To compete with nowadays business is to implement technology and align it into their business strategy. One of technology that commonly implement is Enterprise Resource Planning (ERP. This research will examined what are critical success factor of ERP and the impact of their business outcomes. A framework model for ERP Implementation success is constructs from several research or previous study in Implementation ERP. This study will extends in the research field of successful implementation ERP and implication factor for business practice to have more knowledge in term of implementation ERP and their business strategy. 

  13. PREDICT : model for prediction of survival in localized prostate cancer

    NARCIS (Netherlands)

    Kerkmeijer, Linda G W; Monninkhof, Evelyn M.; van Oort, Inge M.; van der Poel, Henk G.; de Meerleer, Gert; van Vulpen, Marco

    2016-01-01

    Purpose: Current models for prediction of prostate cancer-specific survival do not incorporate all present-day interventions. In the present study, a pre-treatment prediction model for patients with localized prostate cancer was developed.Methods: From 1989 to 2008, 3383 patients were treated with I

  14. Prediction of junior faculty success in biomedical research: comparison of metrics and effects of mentoring programs.

    Science.gov (United States)

    von Bartheld, Christopher S; Houmanfar, Ramona; Candido, Amber

    2015-01-01

    Measuring and predicting the success of junior faculty is of considerable interest to faculty, academic institutions, funding agencies and faculty development and mentoring programs. Various metrics have been proposed to evaluate and predict research success and impact, such as the h-index, and modifications of this index, but they have not been evaluated and validated side-by-side in a rigorous empirical study. Our study provides a retrospective analysis of how well bibliographic metrics and formulas (numbers of total, first- and co-authored papers in the PubMed database, numbers of papers in high-impact journals) would have predicted the success of biomedical investigators (n = 40) affiliated with the University of Nevada, Reno, prior to, and after completion of significant mentoring and research support (through funded Centers of Biomedical Research Excellence, COBREs), or lack thereof (unfunded COBREs), in 2000-2014. The h-index and similar indices had little prognostic value. Publishing as mid- or even first author in only one high-impact journal was poorly correlated with future success. Remarkably, junior investigators with >6 first-author papers within 10 years were significantly (p COBRE-support increased the success rate of junior faculty approximately 3-fold, from 15% to 47%. Our work defines a previously neglected set of metrics that predicted the success of junior faculty with high fidelity-thus defining the pool of faculty that will benefit the most from faculty development programs such as COBREs.

  15. A prediction model for Clostridium difficile recurrence

    Directory of Open Access Journals (Sweden)

    Francis D. LaBarbera

    2015-02-01

    Full Text Available Background: Clostridium difficile infection (CDI is a growing problem in the community and hospital setting. Its incidence has been on the rise over the past two decades, and it is quickly becoming a major concern for the health care system. High rate of recurrence is one of the major hurdles in the successful treatment of C. difficile infection. There have been few studies that have looked at patterns of recurrence. The studies currently available have shown a number of risk factors associated with C. difficile recurrence (CDR; however, there is little consensus on the impact of most of the identified risk factors. Methods: Our study was a retrospective chart review of 198 patients diagnosed with CDI via Polymerase Chain Reaction (PCR from February 2009 to Jun 2013. In our study, we decided to use a machine learning algorithm called the Random Forest (RF to analyze all of the factors proposed to be associated with CDR. This model is capable of making predictions based on a large number of variables, and has outperformed numerous other models and statistical methods. Results: We came up with a model that was able to accurately predict the CDR with a sensitivity of 83.3%, specificity of 63.1%, and area under curve of 82.6%. Like other similar studies that have used the RF model, we also had very impressive results. Conclusions: We hope that in the future, machine learning algorithms, such as the RF, will see a wider application.

  16. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  17. Modeling Success: Using Preenrollment Data to Identify Academically At-Risk Students

    Science.gov (United States)

    Gansemer-Topf, Ann M.; Compton, Jonathan; Wohlgemuth, Darin; Forbes, Greg; Ralston, Ekaterina

    2015-01-01

    Improving student success and degree completion is one of the core principles of strategic enrollment management. To address this principle, institutional data were used to develop a statistical model to identify academically at-risk students. The model employs multiple linear regression techniques to predict students at risk of earning below a…

  18. Successes and Challenges Porting Weather and Climate Models to GPUs

    Science.gov (United States)

    Govett, M. W.; Middlecoff, J.; Henderson, T. B.; Rosinski, J.; Madden, P.

    2011-12-01

    NOAA ESRL has had significant success parallelizing and running the Non-Hydrostatic Icosahedral Model (NIM) dynamical core on GPUs. A key ingredient in the success was the development of our Fortran-to-CUDA compiler (called F2C-ACC) to convert the model code. Compiler directives, inserted by the user, define regions of code to be run on the GPU, identify where fine-grain parallelism can be exploited, and manage data transfers between CPU and GPU. In 2009, we demonstrated that our compiler, with limited analysis capabilities, was able to produce code that ran the NIM 25x faster on a single GPU than a similar generation CPU. As F2C-ACC matured, fewer hand-translations were required until the GPU parallelization of NIM became fully automatic. The usefulness of F2C-ACC as a language translation tool will diminish as commercial compilers from CAPS, PGI and Cray mature; however, porting codes to GPUs will continue to require significant user involvement due to limited tools to support parallelization. Code inspection and analysis is currently very challenging and requires heavy user involvement to parallelize, debug, and achieve respectable speedup on GPUs. Users must inspect their code to locate fine grain parallelism, determine performance bottlenecks, manage data transfers, identify data dependencies, place inter-GPU communications, and manage a myriad of other issues in porting CPU-based codes to GPU architectures. This talk will describe the F2C-ACC compiler, discuss code porting challenges, and describe further development of the analysis capabilities of F2C-ACC to improve GPU parallelization of Fortran-based, Numerical Weather Prediction codes.

  19. A STUDY ON THE SUCCESSION MODEL OF FAMILY BUSINESSS

    OpenAIRE

    Hung-Jung Chang; Szu-Ju Lin

    2011-01-01

    Family business has to face issues such as ownership issue, governance structure issue and succession issue, etc. in enterprise development history. Among them, the succession issue is an important transition point in enterprise’s survival and development. It is thus thought of as one of the most important strategic and decision making issues in the enterprise. This article aims at investigating the succession model of Family business. First, reviews are done on the meaning of Family business...

  20. Predicting success: factors associated with weight change in obese youth undertaking a weight management program.

    Science.gov (United States)

    Baxter, Kimberley A; Ware, Robert S; Batch, Jennifer A; Truby, Helen

    2013-01-01

    To explore which baseline physiological and psychosocial variables predict change in body mass index (BMI) z-score in obese youth after 12 weeks of a dietary weight management study. Participants were obese young people participating in a dietary intervention trial in Brisbane Australia. The outcome variable was change in BMI z-score. Potential predictors considered included demographic, physiological and psychosocial parameters of the young person, and demographic characteristics of their parents. A multivariable regression model was constructed to examine the effect of potential predictive variables. Participants (n = 88) were predominantly female (69.3%), and had a mean(standard deviation) age of 13.1(1.9) years and BMI z-score of 2.2(0.4) on presentation. Lower BMI z-score (p resistance (p = 0.04) at baseline, referral from a paediatrician (p = 0.02) and being more socially advantaged (p = 0.046) were significantly associated with weight loss. Macronutrient distribution of diet and physical activity level did not contribute. Early intervention in obesity treatment in young people improves likelihood of success. Other factors such as degree of insulin resistance, social advantage and referral source also appear to play a role. Assessing presenting characteristics and factors associated with treatment outcome may allow practicing clinicians to individualise a weight management program or determine the 'best-fit' treatment for an obese adolescent. © 2013 Asian Oceanian Association for the Study of Obesity . Published by Elsevier Ltd. All rights reserved.

  1. Predictive Modeling of Cardiac Ischemia

    Science.gov (United States)

    Anderson, Gary T.

    1996-01-01

    The goal of the Contextual Alarms Management System (CALMS) project is to develop sophisticated models to predict the onset of clinical cardiac ischemia before it occurs. The system will continuously monitor cardiac patients and set off an alarm when they appear about to suffer an ischemic episode. The models take as inputs information from patient history and combine it with continuously updated information extracted from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural network and rough set methodologies are then used to forecast the onset of clinical ischemia before it transpires, thus allowing early intervention aimed at preventing morbid complications from occurring. The models will differ from previous attempts by including combinations of continuous and discrete inputs. A commercial medical instrumentation and software company has invested funds in the project with a goal of commercialization of the technology. The end product will be a system that analyzes physiologic parameters and produces an alarm when myocardial ischemia is present. If proven feasible, a CALMS-based system will be added to existing heart monitoring hardware.

  2. Predicting Treatment Success in Child and Parent Therapy Among Families in Poverty.

    Science.gov (United States)

    Mattek, Ryan J; Harris, Sara E; Fox, Robert A

    2016-01-01

    Behavior problems are prevalent in young children and those living in poverty are at increased risk for stable, high-intensity behavioral problems. Research has demonstrated that participation in child and parent therapy (CPT) programs significantly reduces problematic child behaviors while increasing positive behaviors. However, CPT programs, particularly those implemented with low-income populations, frequently report high rates of attrition (over 50%). Parental attributional style has shown some promise as a contributing factor to treatment attendance and termination in previous research. The authors examined if parental attributional style could predict treatment success in a CPT program, specifically targeting low-income urban children with behavior problems. A hierarchical logistic regression was used with a sample of 425 families to assess if parent- and child-referent attributions variables predicted treatment success over and above demographic variables and symptom severity. Parent-referent attributions, child-referent attributions, and child symptom severity were found to be significant predictors of treatment success. Results indicated that caregivers who viewed themselves as a contributing factor for their child's behavior problems were significantly more likely to demonstrate treatment success. Alternatively, caregivers who viewed their child as more responsible for their own behavior problems were less likely to demonstrate treatment success. Additionally, more severe behavior problems were also predictive of treatment success. Clinical and research implications of these results are discussed.

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

    Science.gov (United States)

    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.

  4. Numerical weather prediction model tuning via ensemble prediction system

    Science.gov (United States)

    Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

    2011-12-01

    This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

  5. [Active ageing and success: A brief history of conceptual models].

    Science.gov (United States)

    Petretto, Donatella Rita; Pili, Roberto; Gaviano, Luca; Matos López, Cristina; Zuddas, Carlo

    2016-01-01

    The aim of this paper is to analyse and describe different conceptual models of successful ageing, active and healthy ageing developed in Europe and in America in the 20° century, starting from Rowe and Kahn's original model (1987, 1997). A narrative review was conducted on the literature on successful ageing. Our review included definition of successful ageing from European and American scholars. Models were found that aimed to describe indexes of active and healthy ageing, models devoted to describe processes involved in successful ageing, and additional views that emphasise subjective and objective perception of successful ageing. A description is also given of critiques on previous models and remedies according to Martin et al. (2014) and strategies for successful ageing according to Jeste and Depp (2014). The need is discussed for the enhancement of Rowe and Kahn's model and other models with a more inclusive, universal description of ageing, incorporating scientific evidence regarding active ageing. Copyright © 2015 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.

  6. Modesto Junior College's Student Success Plan: A Model for Student Success/PFE Planning.

    Science.gov (United States)

    McKuin, Kathleen

    This is a report on the student success model designed by Modesto Junior College (MJC) (California) in conjunction with the state-established Partnership for Excellence (PFE) program goals. The PFE program addresses goals of the community college's mission along with more direct emphasis on transfer programs, degrees and certificates awarded,…

  7. Modesto Junior College's Student Success Plan: A Model for Student Success/PFE Planning.

    Science.gov (United States)

    McKuin, Kathleen

    This is a report on the student success model designed by Modesto Junior College (MJC) (California) in conjunction with the state-established Partnership for Excellence (PFE) program goals. The PFE program addresses goals of the community college's mission along with more direct emphasis on transfer programs, degrees and certificates awarded,…

  8. Establishing a Cloud Computing Success Model for Hospitals in Taiwan

    Directory of Open Access Journals (Sweden)

    Jiunn-Woei Lian PhD

    2017-01-01

    Full Text Available The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services.

  9. A STUDY ON THE SUCCESSION MODEL OF FAMILY BUSINESSS

    Directory of Open Access Journals (Sweden)

    Hung-Jung Chang

    2011-10-01

    Full Text Available Family business has to face issues such as ownership issue, governance structure issue and succession issue, etc. in enterprise development history. Among them, the succession issue is an important transition point in enterprise’s survival and development. It is thus thought of as one of the most important strategic and decision making issues in the enterprise. This article aims at investigating the succession model of Family business. First, reviews are done on the meaning of Family business. Next, reviews and comments are made on the related models of the succession of Family business. It can be seen from the research that the ways of succession of Family business can be divided into process point of view and psychological point of view. Finally, main conclusions of this article are summarized and perspectives are also made on the future researches.

  10. Establishing a Cloud Computing Success Model for Hospitals in Taiwan.

    Science.gov (United States)

    Lian, Jiunn-Woei

    2017-01-01

    The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services.

  11. Critique of the two-fold measure of prediction success for ratios: application for the assessment of drug-drug interactions.

    Science.gov (United States)

    Guest, Eleanor J; Aarons, Leon; Houston, J Brian; Rostami-Hodjegan, Amin; Galetin, Aleksandra

    2011-02-01

    Current assessment of drug-drug interaction (DDI) prediction success is based on whether predictions fall within a two-fold range of the observed data. This strategy results in a potential bias toward successful prediction at lower interaction levels [ratio of the area under the concentration-time profile (AUC) in the presence of inhibitor/inducer compared with control is assessment of different DDI prediction algorithms if databases contain large proportion of interactions in this lower range. Therefore, the current study proposes an alternative method to assess prediction success with a variable prediction margin dependent on the particular AUC ratio. The method is applicable for assessment of both induction and inhibition-related algorithms. The inclusion of variability into this predictive measure is also considered using midazolam as a case study. Comparison of the traditional two-fold and the new predictive method was performed on a subset of midazolam DDIs collated from previous databases; in each case, DDIs were predicted using the dynamic model in Simcyp simulator. A 21% reduction in prediction accuracy was evident using the new predictive measure, in particular at the level of no/weak interaction (AUC ratio assessed via the new predictive measure. Thus, the study proposes a more logical method for the assessment of prediction success and its application for induction and inhibition DDIs.

  12. Design-phase prediction of potential cancer clinical trial accrual success using a research data mart

    Science.gov (United States)

    London, Jack W; Balestrucci, Luanne; Chatterjee, Devjani; Zhan, Tingting

    2013-01-01

    Background Many cancer interventional clinical trials are not completed because the required number of eligible patients are not enrolled. Objective To assess the value of using a research data mart (RDM) during the design of cancer clinical trials as a predictor of potential patient accrual, so that less trials fail to meet enrollment requirements. Materials and methods The eligibility criteria for 90 interventional cancer trials were translated into i2b2 RDM queries and cohort sizes obtained for the 2 years prior to the trial initiation. These RDM cohort numbers were compared to the trial accrual requirements, generating predictions of accrual success. These predictions were then compared to the actual accrual performance to evaluate the ability of this methodology to predict the trials’ likelihood of enrolling sufficient patients. Results Our methodology predicted successful accrual (specificity) with 0.969 (=31/32 trials) accuracy (95% CI 0.908 to 1) and predicted failed accrual (sensitivity) with 0.397 (=23/58 trials) accuracy (95% CI 0.271 to 0.522). The positive predictive value, or precision rate, is 0.958 (=23/24) (95% CI 0.878 to 1). Discussion A prediction of ‘failed accrual’ by this methodology is very reliable, whereas a prediction of accrual success is less so, as causes of accrual failure other than an insufficient eligible patient pool are not considered. Conclusions The application of this methodology to cancer clinical design would significantly improve cancer clinical research by reducing the costly efforts expended initiating trials that predictably will fail to meet accrual requirements. PMID:23851466

  13. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...

  14. Executive Functioning Predicts School Readiness and Success: Implications for Assessment and Intervention

    Science.gov (United States)

    Cantin, Rachelle H.; Mann, Trisha D.; Hund, Alycia M.

    2012-01-01

    In recent years, executive functioning (EF) has received increasing attention from researchers and practitioners focusing on how EF predicts important outcomes such as success at school and in life. For example, EF has been described as the single best predictor of school readiness (Blair & Razza, 2007). Moreover, EF has been implicated in…

  15. Threat Related Selective Attention Predicts Treatment Success in Childhood Anxiety Disorders

    Science.gov (United States)

    Legerstee, Jeroen S.; Tulen, Joke H. M.; Kallen, Victor L.; Dieleman, Gwen C.; Treffers, Philip D. A.; Verhulst, Frank C.; Utens, Elisabeth M. W. J.

    2009-01-01

    Threat-related selective attention was found to predict the success of the treatment of childhood anxiety disorders through administering a pictorial dot-probe task to 131 children with anxiety disorders prior to cognitive behavioral therapy. The diagnostic status of the subjects was evaluated with a semistructured clinical interview at both pre-…

  16. Academic Life Satisfaction Scale (ALSS) and Its Effectiveness in Predicting Academic Success

    Science.gov (United States)

    Kumar, P.K. Sudheesh; P., Dileep

    2006-01-01

    This study is undertaken to examine the effectiveness of a newly constructed psychometric instrument to assess Academic Life Satisfaction along with the components of Emotional Intelligence. The Academic Life Satisfaction Scale is used to predict the scholastic achievement as an index of Academic success. The investigators found that Academic Life…

  17. A Comparison of Logistic Regression, Neural Networks, and Classification Trees Predicting Success of Actuarial Students

    Science.gov (United States)

    Schumacher, Phyllis; Olinsky, Alan; Quinn, John; Smith, Richard

    2010-01-01

    The authors extended previous research by 2 of the authors who conducted a study designed to predict the successful completion of students enrolled in an actuarial program. They used logistic regression to determine the probability of an actuarial student graduating in the major or dropping out. They compared the results of this study with those…

  18. Predicting Success Using HESI A2 Entrance Tests in an Associate Degree Nursing Program

    Science.gov (United States)

    Bodman, Susan

    2012-01-01

    A challenge presented to nurse educators is retention of nursing students. This has led nursing faculty to review admission requirements and question how well entrance tests predict success in Associate Degree Nursing Programs. The purpose of this study was to investigate the relationship between the HESI Admission Assessment Exam (HESI A2) and…

  19. Threat Related Selective Attention Predicts Treatment Success in Childhood Anxiety Disorders

    Science.gov (United States)

    Legerstee, Jeroen S.; Tulen, Joke H. M.; Kallen, Victor L.; Dieleman, Gwen C.; Treffers, Philip D. A.; Verhulst, Frank C.; Utens, Elisabeth M. W. J.

    2009-01-01

    Threat-related selective attention was found to predict the success of the treatment of childhood anxiety disorders through administering a pictorial dot-probe task to 131 children with anxiety disorders prior to cognitive behavioral therapy. The diagnostic status of the subjects was evaluated with a semistructured clinical interview at both pre-…

  20. Recognizing Challenges and Predicting Success in First-Generation University Students

    Science.gov (United States)

    Katrevich, Alina V.; Aruguete, Mara S.

    2017-01-01

    Our study explores the challenges of first-generation students while also examining the factors that predict success in this population. We surveyed undergraduate students to compare the academic and social support needs of first-generation and continuing-generation students. First-generation students showed lower grades and critical-thinking…

  1. A Comparison of Logistic Regression, Neural Networks, and Classification Trees Predicting Success of Actuarial Students

    Science.gov (United States)

    Schumacher, Phyllis; Olinsky, Alan; Quinn, John; Smith, Richard

    2010-01-01

    The authors extended previous research by 2 of the authors who conducted a study designed to predict the successful completion of students enrolled in an actuarial program. They used logistic regression to determine the probability of an actuarial student graduating in the major or dropping out. They compared the results of this study with those…

  2. Predictive Power of the Success Tendency and Ego Identity Status of the University Students

    Science.gov (United States)

    Osman, Pepe

    2015-01-01

    The aim of this research is to assess the predictive power of the success tendency and ego identity status of the students of Physical Education and Sports Teaching Department. 581 students of Physical Education and Sports Teaching Department in Kayseri, Nigde, Burdur, Bolu and Diyarbakir participated in this research. The acquired results were…

  3. Reproductive success is predicted by social dynamics and kinship in managed animal populations.

    Science.gov (United States)

    Newman, Saul J; Eyre, Simon; Kimble, Catherine H; Arcos-Burgos, Mauricio; Hogg, Carolyn; Easteal, Simon

    2016-01-01

    Kin and group interactions are important determinants of reproductive success in many species. Their optimization could, therefore, potentially improve the productivity and breeding success of managed populations used for agricultural and conservation purposes. Here we demonstrate this potential using a novel approach to measure and predict the effect of kin and group dynamics on reproductive output in a well-known species, the meerkat Suricata suricatta. Variation in social dynamics predicts 30% of the individual variation in reproductive success of this species in managed populations, and accurately forecasts reproductive output at least two years into the future. Optimization of social dynamics in captive meerkat populations doubles their projected reproductive output. These results demonstrate the utility of a quantitative approach to breeding programs informed by social and kinship dynamics. They suggest that this approach has great potential for improvements in the management of social endangered and agricultural species.

  4. Predictive Model Assessment for Count Data

    Science.gov (United States)

    2007-09-05

    critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts...the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. We consider a recent suggestion by Baker and...Figure 5. Boxplots for various scores for patent data count regressions. 11 Table 1 Four predictive models for larynx cancer counts in Germany, 1998–2002

  5. Prediction of junior faculty success in biomedical research: comparison of metrics and effects of mentoring programs

    Directory of Open Access Journals (Sweden)

    Christopher S. von Bartheld

    2015-09-01

    Full Text Available Measuring and predicting the success of junior faculty is of considerable interest to faculty, academic institutions, funding agencies and faculty development and mentoring programs. Various metrics have been proposed to evaluate and predict research success and impact, such as the h-index, and modifications of this index, but they have not been evaluated and validated side-by-side in a rigorous empirical study. Our study provides a retrospective analysis of how well bibliographic metrics and formulas (numbers of total, first- and co-authored papers in the PubMed database, numbers of papers in high-impact journals would have predicted the success of biomedical investigators (n = 40 affiliated with the University of Nevada, Reno, prior to, and after completion of significant mentoring and research support (through funded Centers of Biomedical Research Excellence, COBREs, or lack thereof (unfunded COBREs, in 2000–2014. The h-index and similar indices had little prognostic value. Publishing as mid- or even first author in only one high-impact journal was poorly correlated with future success. Remarkably, junior investigators with >6 first-author papers within 10 years were significantly (p < 0.0001 more likely (93% to succeed than those with ≤6 first-author papers (4%, regardless of the journal’s impact factor. The benefit of COBRE-support increased the success rate of junior faculty approximately 3-fold, from 15% to 47%. Our work defines a previously neglected set of metrics that predicted the success of junior faculty with high fidelity—thus defining the pool of faculty that will benefit the most from faculty development programs such as COBREs.

  6. A model of succession planning for mental health nurse practitioners.

    Science.gov (United States)

    Hampel, Sally; Procter, Nicholas; Deuter, Kate

    2010-08-01

    This paper reviews current literature on succession planning for mental health nurse practitioners (NPs) and discusses a model of succession planning that is underpinned by principals of leadership development, workforce participation and client engagement. The paper identifies succession planning as a means of managing a present and future workforce, while simultaneously addressing individual and organizational learning and practice development needs. A discussion of the processes attendant upon sustainable succession planning - collegial support, career planning and development, information exchange, capacity building, and mentoring is framed within the potential interrelationships between existing NP, developing NP and service directors and/or team managers. Done effectively and in partnership with wider clinical services, succession planning has the potential to build NP leadership development and leadership transition more broadly within mental health services.

  7. Differential epidural block predicts the success of visceral block in patients with chronic visceral abdominal pain.

    Science.gov (United States)

    Rizk, Maged K; Tolba, Reda; Kapural, Leonardo; Mitchell, Justin; Lopez, Rocio; Mahboobi, Ramatia; Vrooman, Bruce; Mekhail, Nagy

    2012-11-01

    Differential thoracic epidural regional block, also known as a differential neural block (DNB), involves the placement of an epidural catheter placed in the thoracic epidural space to achieve appropriate anesthesia in a dermatomal distribution. This is a retrospective case series evaluating how well a DNB may predict success of subsequent visceral blockade in patients with chronic abdominal pain of visceral origin. Of 402 patients who had a DNB performed for unexplained abdominal pain from January 2000 to January 2009, 81 patients were found to have results consistent with visceral pain and thus underwent subsequent visceral blockade. Basic demographic data, years of chronic pain, history of psychosocial issues, initial visual analog scale (VAS) pain score, pain location, and medication usage were documented in our electronic medical record database. Parameters regarding DNB and visceral blocks also were documented. Descriptive statistics were computed for all variables. The positive predictive value (PPV) for DNB for whom visceral block was successful (at least a 50% reduction in VAS) was calculated. Additionally, subjects with successful visceral blocks were compared to those with unsuccessful visceral blocks. All patients with chronic abdominal pain with normal gastrointestinal studies who underwent DNB. Tertiary Outpatient Pain Management Clinic.   Retrospective Cohort Study. Mean age of patients was 46 (± 15) years, 73% were female, and median duration of pain was 5 years. 67% of subjects were taking opioid analgesics. PPV of DNB was 70.4%. Only factor found to be statistically significant with visceral block success was baseline VAS with higher scores associated with DNB predictive success (6.8 ± 1.7 vs. 5.5, 1.8; P = 0.004). Use of membrane stabilizing medications was significantly more common in subjects for whom visceral block was not successful (46% vs. 25%; P = 0.058). Area underneath curve (AUC) for VAS was found to be 0.70 (95% CI: 0.57, 0

  8. A Career Success Model for Academics at Malaysian Research Universities

    Science.gov (United States)

    Abu Said, Al-Mansor; Mohd Rasdi, Roziah; Abu Samah, Bahaman; Silong, Abu Daud; Sulaiman, Suzaimah

    2015-01-01

    Purpose: The purpose of this paper is to develop a career success model for academics at the Malaysian research universities. Design/methodology/approach: Self-administered and online surveys were used for data collection among 325 academics from Malaysian research universities. Findings: Based on the analysis of structural equation modeling, the…

  9. Formulation of a Success Model in Pharmaceutical R&D

    Directory of Open Access Journals (Sweden)

    Hyunju Rachel Kim

    2014-03-01

    Full Text Available Recently, pharmaceutical R&D has been demanded to increase productivity in terms of time efficiency and innovation as well. There have been discontinuous challenges coming up in this industry, such as globalized R&D competition, stricter regulation, lengthy process of clinical trials, and so on. Considering external changes, high competition, and discontinuities in the industry, it is a good time to redefine the concept of success in pharmaceutical R&D. Thus, this article attempts to formulate a new success model in pharmaceutical R&D, through contextualizing the industry’s success factors.

  10. A third study on predicting NCLEX success with the HESI exit exam.

    Science.gov (United States)

    Nibert, Ainslie T; Young, Anne

    2008-01-01

    This was the third annual validity study designed to assess the accuracy of the HESI Exit Exam (E) in predicting NCLEX success for graduating registered and practical nursing students. As in year I (N = 2,725) and year II (N = 3,752), in year III (N = 6,277), the E was highly predictive of NCLEX success for associate degree nursing, bachelor of science nursing, diploma, and practical nursing students. Unlike previous years, in year III, monitoring was not a significant factor in the predictive accuracy of the E. NCLEX success of low-scoring E students, first examined in year II, was also examined in year III. As in year II, low-scoring E students were significantly more (P = .001) likely to fail the licensure examination than high-scoring E students. In year III, unlike year II, there was no significant difference in the pass rate of low-scoring E students who participated in a remediation program and those who did not. The authors recommended that a more definitive definition of remediation be used in future studies and that such studies focus on E implementation strategies and their relationship to NCLEX success.

  11. Nonlinear chaotic model for predicting storm surges

    Directory of Open Access Journals (Sweden)

    M. Siek

    2010-09-01

    Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

  12. Nonlinear chaotic model for predicting storm surges

    NARCIS (Netherlands)

    Siek, M.; Solomatine, D.P.

    This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables.

  13. Predicting NCLEX-RN Success: the Seventh Validity Study HESI Exit exam.

    Science.gov (United States)

    Young, Anne; Willson, Pamela

    2012-01-01

    The findings of six previously conducted studies indicated that the HESI (E) was highly accurate in predicting NCLEX-RN success. The purpose of this study-the seventh study to investigate the validity of the E-was to examine the accuracy of three parallel versions of the Ein predicting licensure success and to describe program practices regarding E benchmark scores, remediation programs, and retesting policies. The findings of this study again indicated that the E was highly accurate in predicting NCLEX-RN success. Additionally, all three versions of the E were found to have a predictive accuracy above 90%. The most common E benchmark score designated by faculty at the participating schools was 850, and most schools required students to retest with different versions of the E until the faculty-designated E benchmark score was achieved. Remediation seemed to be effective in raising students' E scores, and it was recommended that future research investigate the effectiveness of specific remediation strategies.

  14. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain,...

  15. Psychological approach to successful ageing predicts future quality of life in older adults

    Directory of Open Access Journals (Sweden)

    Iliffe Steve

    2011-03-01

    Full Text Available Abstract Background Public policies aim to promote well-being, and ultimately the quality of later life. Positive perspectives of ageing are underpinned by a range of appraoches to successful ageing. This study aimed to investigate whether baseline biological, psychological and social aproaches to successful ageing predicted future QoL. Methods Postal follow-up in 2007/8 of a national random sample of 999 people aged 65 and over in 1999/2000. Of 496 valid addresses of survivors at follow-up, the follow-up response rate was 58% (287. Measures of the different concepts of successful ageing were constructed using baseline indicators. They were assessed for their ability to independently predict quality of life at follow-up. Results Few respondents achieved all good scores within each of the approaches to successful ageing. Each approach was associated with follow-up QoL when their scores were analysed continuously. The biomedical (health approach failed to achieve significance when the traditional dichotomous cut-off point for successfully aged (full health, or not (less than full health, was used. In multiple regression analyses of the relative predictive ability of each approach, only the psychological approach (perceived self-efficacy and optimism retained significance. Conclusion Only the psychological approach to successful ageing independently predicted QoL at follow-up. Successful ageing is not only about the maintenance of health, but about maximising one's psychological resources, namely self-efficacy and resilience. Increasing use of preventive care, better medical management of morbidity, and changing lifestyles in older people may have beneficial effects on health and longevity, but may not improve their QoL. Adding years to life and life to years may require two distinct and different approaches, one physical and the other psychological. Follow-up health status, number of supporters and social activities, and self-rated active ageing

  16. How to Establish Clinical Prediction Models

    Directory of Open Access Journals (Sweden)

    Yong-ho Lee

    2016-03-01

    Full Text Available A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.

  17. Model predictive control for cooperative control of space robots

    Science.gov (United States)

    Kannan, Somasundar; Alamdari, Seyed Amin Sajadi; Dentler, Jan; Olivares-Mendez, Miguel A.; Voos, Holger

    2017-01-01

    The problem of Orbital Manipulation of Passive body is discussed here. Two scenarios including passive object rigidly attached to robotic servicers and passive body attached to servicers through manipulators are discussed. The Model Predictive Control (MPC) technique is briefly presented and successfully tested through simulations on two cases of position control of passive body in the orbit.

  18. The Drivers of Success in Business Model Transformation

    Directory of Open Access Journals (Sweden)

    Nenad Savič

    2016-01-01

    Full Text Available Existing empirical literature on business models is still inconclusive about the key drivers of successful business model transformation. The paper explores this issue by using a single longitudinal case study design in combination with grounded theory approach on a medium-sized, high-tech and globally oriented company. Based on on-site visits, interviews and secondary documentation data analysis, the study identifies six generic drivers of successful business model transformation: transformational leadership, discovery driven decision-making, industry improvement – customer specific orientation, content-oriented communication, self-initiative collaborators, and phased separation strategy. The new drivers supplement our existing knowledge on how successful transformation takes place and add to existing drivers, while extensive discussion of their implications may help the managers to execute business transformations more effectively.

  19. Predicting the academic success of architecture students by pre-enrolment requirement: using machine-learning techniques

    Directory of Open Access Journals (Sweden)

    Ralph Olusola Aluko

    2016-12-01

    Full Text Available In recent years, there has been an increase in the number of applicants seeking admission into architecture programmes. As expected, prior academic performance (also referred to as pre-enrolment requirement is a major factor considered during the process of selecting applicants. In the present study, machine learning models were used to predict academic success of architecture students based on information provided in prior academic performance. Two modeling techniques, namely K-nearest neighbour (k-NN and linear discriminant analysis were applied in the study. It was found that K-nearest neighbour (k-NN outperforms the linear discriminant analysis model in terms of accuracy. In addition, grades obtained in mathematics (at ordinary level examinations had a significant impact on the academic success of undergraduate architecture students. This paper makes a modest contribution to the ongoing discussion on the relationship between prior academic performance and academic success of undergraduate students by evaluating this proposition. One of the issues that emerges from these findings is that prior academic performance can be used as a predictor of academic success in undergraduate architecture programmes. Overall, the developed k-NN model can serve as a valuable tool during the process of selecting new intakes into undergraduate architecture programmes in Nigeria.

  20. Interaction of species traits and environmental disturbance predicts invasion success of aquatic microorganisms.

    Directory of Open Access Journals (Sweden)

    Elvira Mächler

    Full Text Available Factors such as increased mobility of humans, global trade and climate change are affecting the range of many species, and cause large-scale translocations of species beyond their native range. Many introduced species have a strong negative influence on the new local environment and lead to high economic costs. There is a strong interest to understand why some species are successful in invading new environments and others not. Most of our understanding and generalizations thereof, however, are based on studies of plants and animals, and little is known on invasion processes of microorganisms. We conducted a microcosm experiment to understand factors promoting the success of biological invasions of aquatic microorganisms. In a controlled lab experiment, protist and rotifer species originally isolated in North America invaded into a natural, field-collected community of microorganisms of European origin. To identify the importance of environmental disturbances on invasion success, we either repeatedly disturbed the local patches, or kept them as undisturbed controls. We measured both short-term establishment and long-term invasion success, and correlated it with species-specific life-history traits. We found that environmental disturbances significantly affected invasion success. Depending on the invading species' identity, disturbances were either promoting or decreasing invasion success. The interaction between habitat disturbance and species identity was especially pronounced for long-term invasion success. Growth rate was the most important trait promoting invasion success, especially when the species invaded into a disturbed local community. We conclude that neither species traits nor environmental factors alone conclusively predict invasion success, but an integration of both of them is necessary.

  1. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    is a realization of a continuous-discrete multivariate stochastic transfer function model. The proposed prediction error-methods are demonstrated for a SISO system parameterized by the transfer functions with time delays of a continuous-discrete-time linear stochastic system. The simulations for this case suggest......Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which...... computational resources. The identification method is suitable for predictive control....

  2. Navy Recruit Attrition Prediction Modeling

    Science.gov (United States)

    2014-09-01

    Bernoulli trial, where the outcome has exactly two possible outcomes: “success” and “failure” ( Papoulis , 2002, pp. 57–63). In this case, “success...Assistant Secretary of Defense [Manpower, Reserve Affairs, and Logistics]. Papoulis , A. (2002). “Bernoulli trials.” In Probability, random variables, and

  3. Baculum morphology predicts reproductive success of male house mice under sexual selection.

    Science.gov (United States)

    Stockley, Paula; Ramm, Steven A; Sherborne, Amy L; Thom, Michael D F; Paterson, Steve; Hurst, Jane L

    2013-06-26

    Diversity in penile morphology is characterised by extraordinary variation in the size and shape of the baculum (penis bone) found in many mammals. Although functionally enigmatic, diversity in baculum form is hypothesised to result from sexual selection. According to this hypothesis, the baculum should influence the outcome of reproductive competition among males within promiscuous mating systems. However, a test of this key prediction is currently lacking. Here we show that baculum size explains significant variation in the reproductive success of male house mice under competitive conditions. After controlling for body size and other reproductive traits, the width (but not length) of the house mouse baculum predicts both the mean number of offspring sired per litter and total number of offspring sired. By providing the first evidence linking baculum morphology to male reproductive success, our results support the hypothesis that evolutionary diversity in baculum form is driven by sexual selection.

  4. Role of MR imaging in surgical planning and prediction of successful surgical repair of pelvic organ prolapse

    Directory of Open Access Journals (Sweden)

    Ebtesam Moustafa Kamal

    2013-09-01

    Conclusion: Magnetic resonance imaging can accurately localize pelvic floor defects, evaluate success or failure of surgical procedures, predict the need for more extensive reconstruction, and identify complications.

  5. Modeling Seizure Self-Prediction: An E-Diary Study

    Science.gov (United States)

    Haut, Sheryl R.; Hall, Charles B.; Borkowski, Thomas; Tennen, Howard; Lipton, Richard B.

    2013-01-01

    Purpose A subset of patients with epilepsy successfully self-predicted seizures in a paper diary study. We conducted an e-diary study to ensure that prediction precedes seizures, and to characterize the prodromal features and time windows that underlie self-prediction. Methods Subjects 18 or older with LRE and ≥3 seizures/month maintained an e-diary, reporting AM/PM data daily, including mood, premonitory symptoms, and all seizures. Self-prediction was rated by, “How likely are you to experience a seizure [time frame]”? Five choices ranged from almost certain (>95% chance) to very unlikely. Relative odds of seizure (OR) within time frames was examined using Poisson models with log normal random effects to adjust for multiple observations. Key Findings Nineteen subjects reported 244 eligible seizures. OR for prediction choices within 6hrs was as high as 9.31 (1.92,45.23) for “almost certain”. Prediction was most robust within 6hrs of diary entry, and remained significant up to 12hrs. For 9 best predictors, average sensitivity was 50%. Older age contributed to successful self-prediction, and self-prediction appeared to be driven by mood and premonitory symptoms. In multivariate modeling of seizure occurrence, self-prediction (2.84; 1.68,4.81), favorable change in mood (0.82; 0.67,0.99) and number of premonitory symptoms (1,11; 1.00,1.24) were significant. Significance Some persons with epilepsy can self-predict seizures. In these individuals, the odds of a seizure following a positive prediction are high. Predictions were robust, not attributable to recall bias, and were related to self awareness of mood and premonitory features. The 6-hour prediction window is suitable for the development of pre-emptive therapy. PMID:24111898

  6. A spatial simulation model for forest succession in the Upper Mississippi River floodplain

    Science.gov (United States)

    Yin, Y.; Wu, Y.; Bartell, S.M.

    2009-01-01

    A Markov-chain transition model (FORSUM) and Monte Carlo simulations were used to simulate the succession patterns and predict a long-term impact of flood on the forest structure and growth in the floodplain of the Upper Mississippi River and Illinois River. Model variables, probabilities, functions, and parameters were derived from the analysis of two comprehensive field surveys conducted in this floodplain. This modeling approach describes the establishment, growth, competition, and death of individual trees for modeled species on a 10,000-ha landscape with spatial resolution of 1 ha. The succession characteristics of each Monte Carlo simulation are summed up to describe forest development and dynamics on a landscape level. FORSUM simulated the impacts of flood intensity and frequency on species composition and dynamics in the Upper Mississippi River floodplain ecosystem. The model provides a useful tool for testing hypotheses about forest succession and enables ecologists and managers to evaluate the impacts of flood disturbances and ecosystem restoration on forest succession. The simulation results suggest that the Markov-chain Monte Carlo method is an efficient tool to help organize the existing data and knowledge of forest succession into a system of quantitative predictions for the Upper Mississippi River floodplain ecosystem. ?? 2009 Elsevier B.V.

  7. A thermodynamic model to predict wax formation in petroleum fluids

    Energy Technology Data Exchange (ETDEWEB)

    Coutinho, J.A.P. [Universidade de Aveiro (Portugal). Dept. de Quimica. Centro de Investigacao em Quimica]. E-mail: jcoutinho@dq.ua.pt; Pauly, J.; Daridon, J.L. [Universite de Pau et des Pays de l' Adour, Pau (France). Lab. des Fluides Complexes

    2001-12-01

    Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G{sup E} model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data. (author)

  8. A THERMODYNAMIC MODEL TO PREDICT WAX FORMATION IN PETROLEUM FLUIDS

    Directory of Open Access Journals (Sweden)

    J.A.P. Coutinho

    2001-12-01

    Full Text Available Some years ago the authors proposed a model for the non-ideality of the solid phase, based on the Predictive Local Composition concept. This was first applied to the Wilson equation and latter extended to NRTL and UNIQUAC models. Predictive UNIQUAC proved to be extraordinarily successful in predicting the behaviour of both model and real hydrocarbon fluids at low temperatures. This work illustrates the ability of Predictive UNIQUAC in the description of the low temperature behaviour of petroleum fluids. It will be shown that using Predictive UNIQUAC in the description of the solid phase non-ideality a complete prediction of the low temperature behaviour of synthetic paraffin solutions, fuels and crude oils is achieved. The composition of both liquid and solid phases, the amount of crystals formed and the cloud points are predicted within the accuracy of the experimental data. The extension of Predictive UNIQUAC to high pressures, by coupling it with an EOS/G E model based on the SRK EOS used with the LCVM mixing rule, is proposed and predictions of phase envelopes for live oils are compared with experimental data.

  9. Catalytic cracking models developed for predictive control purposes

    Directory of Open Access Journals (Sweden)

    Dag Ljungqvist

    1993-04-01

    Full Text Available The paper deals with state-space modeling issues in the context of model-predictive control, with application to catalytic cracking. Emphasis is placed on model establishment, verification and online adjustment. Both the Fluid Catalytic Cracking (FCC and the Residual Catalytic Cracking (RCC units are discussed. Catalytic cracking units involve complex interactive processes which are difficult to operate and control in an economically optimal way. The strong nonlinearities of the FCC process mean that the control calculation should be based on a nonlinear model with the relevant constraints included. However, the model can be simple compared to the complexity of the catalytic cracking plant. Model validity is ensured by a robust online model adjustment strategy. Model-predictive control schemes based on linear convolution models have been successfully applied to the supervisory dynamic control of catalytic cracking units, and the control can be further improved by the SSPC scheme.

  10. Prediction of success and failure of behavior modification as treatment for dental anxiety.

    Science.gov (United States)

    Eli, I; Baht, R; Blacher, S

    2004-08-01

    Behavior modification techniques are effective in the treatment of extreme dental anxiety, but their success is by no means absolute. In the present article, the Corah Dental Anxiety Scale (DAS), the self-report symptom inventory SCL-90R and a questionnaire accessing subjects' daydreaming styles (the Short Imaginal Process Inventory) were used to develop possible predictive measures for success and failure of behavior modification as a treatment for dental fear. The patients' level of distractibility and mind wandering, initial dental anxiety and somatization significantly predicted the success of therapy. The odds ratio indicated that the risk of therapy failure increased about 11 times with an increase of one scale of the Poor Attention Control Scale, about three times with an increase of one level of the mean DAS score, and 0.17 times with an increase of one level of somatization. The predictive value of the chosen scales was 80%. Thus, the use of these scales as part of an initial admittance process for patients who suffer from dental anxiety can enhance our ability to better recognize patients who are prone to fail behavior therapy as treatment for their problem, and enable their referral for other possible modes of treatment.

  11. Hormone levels predict individual differences in reproductive success in a passerine bird.

    Science.gov (United States)

    Ouyang, Jenny Q; Sharp, Peter J; Dawson, Alistair; Quetting, Michael; Hau, Michaela

    2011-08-22

    Hormones mediate major physiological and behavioural components of the reproductive phenotype of individuals. To understand basic evolutionary processes in the hormonal regulation of reproductive traits, we need to know whether, and during which reproductive phases, individual variation in hormone concentrations relates to fitness in natural populations. We related circulating concentrations of prolactin and corticosterone to parental behaviour and reproductive success during both the pre-breeding and the chick-rearing stages in both individuals of pairs of free-living house sparrows, Passer domesticus. Prolactin and baseline corticosterone concentrations in pre-breeding females, and prolactin concentrations in pre-breeding males, predicted total number of fledglings. When the strong effect of lay date on total fledgling number was corrected for, only pre-breeding baseline corticosterone, but not prolactin, was negatively correlated with the reproductive success of females. During the breeding season, nestling provisioning rates of both sexes were negatively correlated with stress-induced corticosterone levels. Lastly, individuals of both sexes with low baseline corticosterone before and high baseline corticosterone during breeding raised the most offspring, suggesting that either the plasticity of this trait contributes to reproductive success or that high parental effort leads to increased hormone concentrations. Thus hormone concentrations both before and during breeding, as well as their seasonal dynamics, predict reproductive success, suggesting that individual variation in absolute concentrations and in plasticity is functionally significant, and, if heritable, may be a target of selection.

  12. Traffic Prediction Scheme based on Chaotic Models in Wireless Networks

    Directory of Open Access Journals (Sweden)

    Xiangrong Feng

    2013-09-01

    Full Text Available Based on the local support vector algorithm of chaotic time series analysis, the Hannan-Quinn information criterion and SAX symbolization are introduced. Then a novel prediction algorithm is proposed, which is successfully applied to the prediction of wireless network traffic. For the correct prediction problems of short-term flow with smaller data set size, the weakness of the algorithms during model construction is analyzed by study and comparison to LDK prediction algorithm. It is verified the Hannan-Quinn information principle can be used to calculate the number of neighbor points to replace pervious empirical method, which uses the number of neighbor points to acquire more accurate prediction model. Finally, actual flow data is applied to confirm the accuracy rate of the proposed algorithm LSDHQ. It is testified by our experiments that it also has higher performance in adaptability than that of LSDHQ algorithm.

  13. Case studies in archaeological predictive modelling

    NARCIS (Netherlands)

    Verhagen, Jacobus Wilhelmus Hermanus Philippus

    2007-01-01

    In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing p

  14. Childhood asthma prediction models: a systematic review.

    Science.gov (United States)

    Smit, Henriette A; Pinart, Mariona; Antó, Josep M; Keil, Thomas; Bousquet, Jean; Carlsen, Kai H; Moons, Karel G M; Hooft, Lotty; Carlsen, Karin C Lødrup

    2015-12-01

    Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.

  15. A Lotka-Volterra competition model with seasonal succession.

    Science.gov (United States)

    Hsu, Sze-Bi; Zhao, Xiao-Qiang

    2012-01-01

    A complete classification for the global dynamics of a Lotka-Volterra two species competition model with seasonal succession is obtained via the stability analysis of equilibria and the theory of monotone dynamical systems. The effects of two death rates in the bad season and the proportion of the good season on the competition outcomes are also discussed. © Springer-Verlag 2011

  16. Student Success in College Composition through the Puente Project Model.

    Science.gov (United States)

    Jaffe, Barbara

    Much can be learned from California's Puente Project Model that would help students' success in classrooms as well as in college in general, and in their daily lives. Puente, which means "bridge" in Spanish, began in 1982 at Chabot College in northern California and is now in 38 colleges and 19 high schools statewide. Originally designed…

  17. Perceived Academic Control and Academic Emotions Predict Undergraduate University Student Success: Examining Effects on Dropout Intention and Achievement

    Science.gov (United States)

    Respondek, Lisa; Seufert, Tina; Stupnisky, Robert; Nett, Ulrike E.

    2017-01-01

    The present study addressed concerns over the high risk of university students' academic failure. It examined how perceived academic control and academic emotions predict undergraduate students' academic success, conceptualized as both low dropout intention and high achievement (indicated by GPA). A cross-sectional survey was administered to 883 undergraduate students across all disciplines of a German STEM orientated university. The study additionally compared freshman students (N = 597) vs. second-year students (N = 286). Using structural equation modeling, for the overall sample of undergraduate students we found that perceived academic control positively predicted enjoyment and achievement, as well as negatively predicted boredom and anxiety. The prediction of dropout intention by perceived academic control was fully mediated via anxiety. When taking perceived academic control into account, we found no specific impact of enjoyment or boredom on the intention to dropout and no specific impact of all three academic emotions on achievement. The multi-group analysis showed, however, that perceived academic control, enjoyment, and boredom among second-year students had a direct relationship with dropout intention. A major contribution of the present study was demonstrating the important roles of perceived academic control and anxiety in undergraduate students' academic success. Concerning corresponding institutional support and future research, the results suggested distinguishing incoming from advanced undergraduate students. PMID:28326043

  18. Treatment success in neck pain: The added predictive value of psychosocial variables in addition to clinical variables.

    Science.gov (United States)

    Groeneweg, Ruud; Haanstra, Tsjitske; Bolman, Catherine A W; Oostendorp, Rob A B; van Tulder, Maurits W; Ostelo, Raymond W J G

    2017-01-01

    Identification of psychosocial variables may influence treatment outcome. The objective of this study was to prospectively examine whether psychosocial variables, in addition to clinical variables (pain, functioning, general health, previous neck pain, comorbidity), are predictive factors for treatment outcome (i.e. global perceived effect, functioning and pain) in patients with sub-acute and chronic non-specific neck pain undergoing physical therapy or manual therapy. Psychosocial factors included treatment outcome expectancy and treatment credibility, health locus of control, and fear avoidance beliefs. This study reports a secondary analysis of a primary care-based pragmatic randomized controlled trial. Potential predictors were measured at baseline and outcomes, in 181 patients, at 7 weeks and 26 weeks. Hierarchical logistic regression models showed that treatment outcome expectancy predicted outcome success, in addition to clinical and demographic variables. Expectancy explained additional variance, ranging from 6% (pain) to 17% (functioning) at 7 weeks, and 8% (pain) to 16% (functioning) at 26 weeks. Locus of control and fear avoidance beliefs did not add significantly to predicting outcome. Based on the results of this study we conclude that outcome expectancy, in patients with non-specific sub-acute and chronic neck pain, has additional predictive value for treatment success above and beyond clinical and demographic variables. Psychological processes, health perceptions and how these factors relate to clinical variables may be important for treatment decision making regarding therapeutic options for individual patients. Copyright © 2016 Scandinavian Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  19. Translational PK/PD modeling to increase probability of success in drug discovery and early development.

    Science.gov (United States)

    Lavé, Thierry; Caruso, Antonello; Parrott, Neil; Walz, Antje

    In this review we present ways in which translational PK/PD modeling can address opportunities to enhance probability of success in drug discovery and early development. This is achieved by impacting efficacy and safety-driven attrition rates, through increased focus on the quantitative understanding and modeling of translational PK/PD. Application of the proposed principles early in the discovery and development phases is anticipated to bolster confidence of successfully evaluating proof of mechanism in humans and ultimately improve Phase II success. The present review is centered on the application of predictive modeling and simulation approaches during drug discovery and early development, and more specifically of mechanism-based PK/PD modeling. Case studies are presented, focused on the relevance of M&S contributions to real-world questions and the impact on decision making.

  20. Acquisition Integration Models: How Large Companies Successfully Integrate Startups

    Directory of Open Access Journals (Sweden)

    Peter Carbone

    2011-10-01

    Full Text Available Mergers and acquisitions (M&A have been popular means for many companies to address the increasing pace and level of competition that they face. Large companies have pursued acquisitions to more quickly access technology, markets, and customers, and this approach has always been a viable exit strategy for startups. However, not all deals deliver the anticipated benefits, in large part due to poor integration of the acquired assets into the acquiring company. Integration can greatly impact the success of the acquisition and, indeed, the combined company’s overall market success. In this article, I explore the implementation of several integration models that have been put into place by a large company and extract principles that may assist negotiating parties with maximizing success. This perspective may also be of interest to smaller companies as they explore exit options while trying to ensure continued market success after acquisition. I assert that business success with acquisitions is dependent on an appropriate integration model, but that asset integration is not formulaic. Any integration effort must consider the specific market context and personnel involved.

  1. A nurse manager succession planning model with associated empirical outcomes.

    Science.gov (United States)

    Titzer, Jennifer L; Shirey, Maria R; Hauck, Sheila

    2014-01-01

    Perceptions of leadership and management competency after a formal nurse manager succession planning program were evaluated. A lack of strategic workforce planning and development of a leadership pipeline contributes to a predicted nurse manager shortage. To meet the anticipated needs for future leadership, evidence-based action is critical. A quasi-experimental mixed-methods, 1-group pretest/posttest research design was used. Nurses working in an acute care hospital were recruited for the study and selected using an objective evaluative process. Participant perceptions regarding their leadership and management competencies significantly increased after the leadership program. Program evaluations confirmed that participants found the program beneficial. One year after program completion, 100% of the program participants have been retained at the organization and 73% had transitioned to leadership roles. Succession planning and leadership development serve as beneficial and strategic mechanisms for identifying and developing high-potential individuals for leadership positions, contributing toward the future nursing leadership pipeline.

  2. Groundwater Level Prediction using M5 Model Trees

    Science.gov (United States)

    Nalarajan, Nitha Ayinippully; Mohandas, C.

    2015-01-01

    Groundwater is an important resource, readily available and having high economic value and social benefit. Recently, it had been considered a dependable source of uncontaminated water. During the past two decades, increased rate of extraction and other greedy human actions have resulted in the groundwater crisis, both qualitatively and quantitatively. Under prevailing circumstances, the availability of predicted groundwater levels increase the importance of this valuable resource, as an aid in the planning of groundwater resources. For this purpose, data-driven prediction models are widely used in the present day world. M5 model tree (MT) is a popular soft computing method emerging as a promising method for numeric prediction, producing understandable models. The present study discusses the groundwater level predictions using MT employing only the historical groundwater levels from a groundwater monitoring well. The results showed that MT can be successively used for forecasting groundwater levels.

  3. Variation in circulating testosterone during mating predicts reproductive success in a wild songbird.

    Directory of Open Access Journals (Sweden)

    Beate Apfelbeck

    2016-08-01

    Full Text Available Testosterone is an important sex hormone and mediates reproduction in male vertebrates. There is ample evidence that testosterone coordinates the expression of physiological, morphological and behavioural traits during reproduction and many of these traits are under sexual selection. However, only few studies so far have examined if individual variation in testosterone is correlated with reproductive success. Because socially monogamous bird species pass through different phases within a breeding cycle and each of these phases requires the expression of different behaviours, the relation between testosterone and reproductive success could vary with breeding stage. Here we investigate the link between reproductive success and testosterone in European stonechats – a socially monogamous songbird with biparental care. Previous studies found that territorial aggression in breeding stonechats depends on testosterone and that testosterone levels peak during the mating phase. Thus, high testosterone levels during mating may influence reproductive success by promoting territorial aggression and mate guarding. We found that males with two breeding attempts produced a similar number of fledglings as males with three breeding attempts. However, males with two breeding attempts expressed higher levels of testosterone than males with just one or those with three breeding attempts, regardless of whether testosterone was measured during the mating or the parental phase of the first brood. Furthermore, testosterone levels during mating, but not during parenting correlated with the total annual number of fledglings. Thus, individual variation in levels of plasma testosterone predicted reproductive success in stonechats.

  4. Exploring nursing e-learning systems success based on information system success model.

    Science.gov (United States)

    Chang, Hui-Chuan; Liu, Chung-Feng; Hwang, Hsin-Ginn

    2011-12-01

    E-learning is thought of as an innovative approach to enhance nurses' care service knowledge. Extensive research has provided rich information toward system development, courses design, and nurses' satisfaction with an e-learning system. However, a comprehensive view in understanding nursing e-learning system success is an important but less focused-on topic. The purpose of this research was to explore net benefits of nursing e-learning systems based on the updated DeLone and McLean's Information System Success Model. The study used a self-administered questionnaire to collected 208 valid nurses' responses from 21 of Taiwan's medium- and large-scale hospitals that have implemented nursing e-learning systems. The result confirms that the model is sufficient to explore the nurses' use of e-learning systems in terms of intention to use, user satisfaction, and net benefits. However, while the three exogenous quality factors (system quality, information quality, and service quality) were all found to be critical factors affecting user satisfaction, only information quality showed a direct effect on the intention to use. This study provides useful insights for evaluating nursing e-learning system qualities as well as an understanding of nurses' intentions and satisfaction related to performance benefits.

  5. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  6. SUCCESSFUL INNOVATIVE CLUSTERS IN ROMANIA – A POSSIBLE MODEL

    Directory of Open Access Journals (Sweden)

    Liliana SCUTARU

    2016-08-01

    Full Text Available The present study proposes the construction of a successful innovative cluster model which will help creating strategies and policies to support the Romanian economic growth and development in the medium and long term. One such architecture designed for supporting innovative clusters, including by attracting foreign capital within clusters order to increase their competitiveness, addresses some concrete measures both in terms of organizational system and management strategy as well as the funding system of clusters. The paper is also emphasizing the multiplicity of factors that are contributing to the creation, to the progressive development and to the success of clusters, the activities developed and the relationships established internationally, so as to ensure that the clusters remain on the market and have a good visibility at national and international levels, essentially contributing to the success of cluster.

  7. Predicting the success of minority students in a baccalaureate nursing program.

    Science.gov (United States)

    Boyle, K K

    1986-05-01

    Entering grade point average (ENTGPA), American College Test Assessment (ACT), high school rank (HSRANK), high school GPA (HSGPA), number of college credit hours prior to program admission (HRSPTA), age at admission, and an index of applicant motivation and related experience (MEP) were investigated to determine the best predictive combination of variables for success among minorities in a baccalaureate nursing program. Final GPA, program completion, and State Board Examination (SBTPE) performance were used as indicators of success. Minority students (N = 145) admitted between 1971-1981 were identified by record review. Two minority subgroups, blacks (n = 111) and nonblack minorities (n = 34) were compared using multiple regression and discriminant analysis procedures. ACT was the strongest, most consistent predictor of SBTPE performance and final GPA for all minorities. ENTGPA and ACT provided substantial predictive power for both subgroups, but explained markedly less variance for blacks. HSGPA, HRSPTA, and HSRANK explained some variance differently by subgroup. ENTGPA provided the only discrimination between graduates and dropouts. Cognitive attributes are critical to academic success among minorities, although predictors may vary in explanatory power by minority group. Variables interfering with program completion need to be explored.

  8. Predicting NCLEX-RN success with the HESI Exit Exam: eighth validity study.

    Science.gov (United States)

    Langford, Rae; Young, Anne

    2013-01-01

    Increasingly, Elsevier's HESI Exit Exam (E(2)) is being used to assess students' readiness for the National Council Licensure Examination for Registered Nurses (NCLEX-RN). Seven previously conducted validity studies indicate that the E(2) is 96.36%-99.16% accurate in predicting NCLEX-RN success. Findings of this eighth validity study, which also investigated the predictive accuracy of repeat testing with parallel versions of the E(2), indicated that the E(2) is highly accurate (94.93%-98.32%) in predicting NCLEX-RN success for the initial testing and 2 retests. Of the 66 participating nursing programs, deans and directors from 43 (65.15%) of the programs reported implementing a policy that used E(2) scores as a benchmark for remediation. A score of 850 was the most common E(2) benchmark designated by faculties, and students who failed to achieve the faculty-designated E(2) benchmark score were required to retest with a parallel version of the E(2). Remediation resources used to assist students in achieving faculty-designated E(2) benchmark scores varied widely, with many programs employing multiple remediation methods.

  9. Cytological Sampling Versus Forceps Biopsy During Percutaneous Transhepatic Biliary Drainage and Analysis of Factors Predicting Success

    Energy Technology Data Exchange (ETDEWEB)

    Tapping, C. R.; Byass, O. R.; Cast, J. E. I., E-mail: james.cast@hey.nhs.uk [Hull Royal Infirmary, Department of Radiology (United Kingdom)

    2012-08-15

    Purpose: To assess the accuracy of cytological sampling and forceps biopsy in obstructing biliary lesions and to identify factors predictive of success. Methods: Consecutive patients (n = 119) with suspected malignant inoperable obstructive jaundice treated with percutaneous transhepatic biliary drainage during 7 years were included (60 male; mean age 72.5 years). All patients underwent forceps biopsy plus cytological sampling by washing the forceps device in cytological solution. Patient history, procedural and pathological records, and clinical follow-up were reviewed. Statistical analysis included chi-square test and multivariate regression analysis. Results: Histological diagnosis after forceps biopsy was more successful than cytology: Sensitivity was 78 versus 61%, and negative predictive value was 30 versus 19%. Cytology results were never positive when the forceps biopsy was negative. The cytological sample was negative and forceps sample positive in 2 cases of cholangiocarcinoma, 16 cases of pancreatic carcinoma, and 1 case of benign disease. Diagnostic accuracy was predicted by low bilirubin (p < 0.001), aspartate transaminase (p < 0.05), and white cell count (p {<=} 0.05). Conclusions: This technique is safe and effective and is recommended for histological diagnosis during PTBD in patients with inoperable malignant biliary strictures. Diagnostic yield is greater when bilirubin levels are low and there is no sepsis; histological diagnosis by way of forceps biopsy renders cytological sampling unnecessary.

  10. Concepts, Challenges and Successes in Modeling Thermodynamics of Metabolism

    Directory of Open Access Journals (Sweden)

    William R. Cannon

    2014-11-01

    Full Text Available The modeling of the chemical reactions involved in metabolism is a daunting task. Ideally, the modeling of metabolism would use kinetic simulations, but these simulations require knowledge of the thousands of rate constants involved in the reactions. The measurement of rate constants is very labor intensive, and hence rate constants for most enzymatic reactions are not available. Consequently, flux-based approaches have been the methods of choice because they do not require the use of the rate constants of the law of mass action. However, this convenience also limits the predictive power of flux-based approaches in that the law of mass action is not used directly, making it very difficult to predict metabolite levels or energy requirements of pathways.An alternative to both of these approaches is to model metabolism using simulations of states rather than simulations of reactions, in which the state is defined as the set of all metabolite counts or concentrations. While kinetic simulations model reactions based on the likelihood of the reaction derived from the law of mass action, states are modeled based on likelihood ratios of mass action. Both approaches provide information on the energy requirements of metabolic reactions and pathways. However, modeling states rather than reactions has the advantage that the parameters needed to model states (chemical potentials are much easier to determine than the parameters needed to model reactions (rate constants. Herein we discuss recent results, assumptions and issues in using simulations of state to model metabolism.

  11. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...

  12. The morphology of midcingulate cortex predicts frontal-midline theta neurofeedback success

    Directory of Open Access Journals (Sweden)

    Stefanie eEnriquez-Geppert

    2013-08-01

    Full Text Available Humans differ in their ability to learn how to control their own brain activity by neurofeedback. However, neural mechanisms underlying these inter-individual differences, which may determine training success and associated cognitive enhancement, are not well understood. Here, it is asked whether neurofeedback success of frontal-midline (fm theta, an oscillation related to higher cognitive functions, could be predicted by the morphology of brain structures known to be critically involved in fm-theta generation. Nineteen young, right-handed participants underwent magnetic resonance imaging of T1-weighted brain images, and took part in an individualized, eight-session neurofeedback training in order to learn how to enhance activity in their fm-theta frequency band. Initial training success, measured at the second training session, was correlated with the final outcome measure. We found that the inferior, superior and middle frontal cortices were not associated with training success. However, volume of the midcingulate cortex as well as volume and concentration of the underlying white matter structures act as predictor variables for the general responsiveness to training. These findings suggest a neuroanatomical foundation for the ability to learn to control one’s own brain activity.

  13. Perceived emotional intelligence, general intelligence and early professional success: predictive and incremental validity

    Directory of Open Access Journals (Sweden)

    José-Manuel de Haro

    2014-05-01

    Full Text Available Although the study of factors affecting career success has shown connections between biographical and other aspects related to ability, knowledge and personality, few studies have examined the relationship between emotional intelligence and professional success at the initial career stage. When these studies were carried out, the results showed significant relationships between the dimensions of emotional intelligence (emotional self-awareness, self-regulation, social awareness or social skills and the level of professional competence. In this paper, we analyze the relationship between perceived emotional intelligence, measured by the Trait Meta-Mood Scale (TMMS-24 questionnaire, general intelligence assessed by the Cattell factor "g" test, scale 3, and extrinsic indicators of career success, in a sample of 130 graduates at the beginning of their careers. Results from hierarchical regression analysis indicate that emotional intelligence makes a specific contribution to the prediction of salary, after controlling the general intelligence effect. The perceived emotional intelligence dimensions of TMMS repair, TMMS attention and sex show a higher correlation and make a greater contribution to professional success than general intelligence. The implications of these results for the development of socio-emotional skills among University graduates are discussed.

  14. Why achievement motivation predicts success in business but failure in politics: the importance of personal control.

    Science.gov (United States)

    Winter, David G

    2010-12-01

    Several decades of research have established that implicit achievement motivation (n Achievement) is associated with success in business, particularly in entrepreneurial or sales roles. However, several political psychology studies have shown that achievement motivation is not associated with success in politics; rather, implicit power motivation often predicts political success. Having versus lacking control may be a key difference between business and politics. Case studies suggest that achievement-motivated U.S. presidents and other world leaders often become frustrated and thereby fail because of lack of control, whereas power-motivated presidents develop ways to work with this inherent feature of politics. A reevaluation of previous research suggests that, in fact, relationships between achievement motivation and business success only occur when control is high. The theme of control is also prominent in the development of achievement motivation. Cross-national data are also consistent with this analysis: In democratic industrialized countries, national levels of achievement motivation are associated with strong executive control. In countries with low opportunity for education (thus fewer opportunities to develop a sense of personal control), achievement motivation is associated with internal violence. Many of these manifestations of frustrated achievement motivation in politics resemble authoritarianism. This conclusion is tested by data from a longitudinal study of 113 male college students, showing that high initial achievement motivation combined with frustrated desires for control is related to increases in authoritarianism (F-scale scores) during the college years. Implications for the psychology of leadership and practical politics are discussed.

  15. Balloon laryngoplasty for acquired subglottic stenosis in children: predictive factors for success

    Directory of Open Access Journals (Sweden)

    Rebecca Maunsell

    2014-10-01

    Full Text Available INTRODUCTION: The treatment of subglottic stenosis in children remains a challenge for the otorhinolaryngologist, and may involve both endoscopic and open surgery. OBJECTIVE: To report the experience of two tertiary facilities in the treatment of acquired subglottic stenosis in children with balloon laryngoplasty, and to identify predictive factors for success of the technique and its complications. METHODS: Descriptive, prospective study of children diagnosed with acquired subglottic stenosis and submitted to balloon laryngoplasty as primary treatment. RESULTS: Balloon laryngoplasty was performed in 37 children with an average age of 22.5 months; 24 presented chronic subglottic stenosis and 13 acute subglottic stenosis. Success rates were 100% for acute subglottic stenosis and 32% for chronic subglottic stenosis. Success was significantly associated with acute stenosis, initial grade of stenosis, children of a smaller age, and the absence of tracheostomy. Transitory dysphagia was the only complication observed in three children. CONCLUSION: Balloon laryngoplasty may be considered the first line of treatment for acquired subglottic stenosis. In acute cases, the success rate is 100%, and although the results are less promising in chronic cases, complications are not significant and the possibility of open surgery remains without prejudice.

  16. Massive Predictive Modeling using Oracle R Enterprise

    CERN Document Server

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

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

    Science.gov (United States)

    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.

  18. Statistical characteristics of irreversible predictability time in regional ocean models

    Directory of Open Access Journals (Sweden)

    P. C. Chu

    2005-01-01

    Full Text Available Probabilistic aspects of regional ocean model predictability is analyzed using the probability density function (PDF of the irreversible predictability time (IPT (called τ-PDF computed from an unconstrained ensemble of stochastic perturbations in initial conditions, winds, and open boundary conditions. Two-attractors (a chaotic attractor and a small-amplitude stable limit cycle are found in the wind-driven circulation. Relationship between attractor's residence time and IPT determines the τ-PDF for the short (up to several weeks and intermediate (up to two months predictions. The τ-PDF is usually non-Gaussian but not multi-modal for red-noise perturbations in initial conditions and perturbations in the wind and open boundary conditions. Bifurcation of τ-PDF occurs as the tolerance level varies. Generally, extremely successful predictions (corresponding to the τ-PDF's tail toward large IPT domain are not outliers and share the same statistics as a whole ensemble of predictions.

  19. Modelling clinical systemic lupus erythematosus: similarities, differences and success stories.

    Science.gov (United States)

    Celhar, Teja; Fairhurst, Anna-Marie

    2016-12-24

    Mouse models of SLE have been indispensable tools to study disease pathogenesis, to identify genetic susceptibility loci and targets for drug development, and for preclinical testing of novel therapeutics. Recent insights into immunological mechanisms of disease progression have boosted a revival in SLE drug development. Despite promising results in mouse studies, many novel drugs have failed to meet clinical end points. This is probably because of the complexity of the disease, which is driven by polygenic predisposition and diverse environmental factors, resulting in a heterogeneous clinical presentation. Each mouse model recapitulates limited aspects of lupus, especially in terms of the mechanism underlying disease progression. The main mouse models have been fairly successful for the evaluation of broad-acting immunosuppressants. However, the advent of targeted therapeutics calls for a selection of the most appropriate model(s) for testing and, ultimately, identification of patients who will be most likely to respond.

  20. Modelling clinical systemic lupus erythematosus: similarities, differences and success stories

    Science.gov (United States)

    Celhar, Teja

    2017-01-01

    Abstract Mouse models of SLE have been indispensable tools to study disease pathogenesis, to identify genetic susceptibility loci and targets for drug development, and for preclinical testing of novel therapeutics. Recent insights into immunological mechanisms of disease progression have boosted a revival in SLE drug development. Despite promising results in mouse studies, many novel drugs have failed to meet clinical end points. This is probably because of the complexity of the disease, which is driven by polygenic predisposition and diverse environmental factors, resulting in a heterogeneous clinical presentation. Each mouse model recapitulates limited aspects of lupus, especially in terms of the mechanism underlying disease progression. The main mouse models have been fairly successful for the evaluation of broad-acting immunosuppressants. However, the advent of targeted therapeutics calls for a selection of the most appropriate model(s) for testing and, ultimately, identification of patients who will be most likely to respond. PMID:28013204

  1. Dynamic Model of Markets of Successive Product Generations

    OpenAIRE

    Kaldasch, Joachim

    2015-01-01

    A dynamic microeconomic model is presented that establishes the price and unit sales evolution of heterogeneous goods consisting of successive homogenous product generations. It suggests that for a fast growing supply the mean price of the generations are governed by a logistic decline towards a floor price. It is shown that generations of a heterogeneous good are in mutual competition. Their market shares are therefore governed by a Fisher-Pry law while the total unit sales are governed by t...

  2. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara

    2017-01-01

    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...

  3. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  6. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  7. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Improving Student Success Using Predictive Models and Data Visualisations

    Science.gov (United States)

    Essa, Alfred; Ayad, Hanan

    2012-01-01

    The need to educate a competitive workforce is a global problem. In the US, for example, despite billions of dollars spent to improve the educational system, approximately 35% of students never finish high school. The drop rate among some demographic groups is as high as 50-60%. At the college level in the US only 30% of students graduate from…

  16. Posterior Predictive Model Checking in Bayesian Networks

    Science.gov (United States)

    Crawford, Aaron

    2014-01-01

    This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…

  17. A Course in... Model Predictive Control.

    Science.gov (United States)

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  18. Female song rate and structure predict reproductive success in a socially monogamous bird.

    Directory of Open Access Journals (Sweden)

    Dianne Heather Brunton

    2016-03-01

    Full Text Available Bird song is commonly regarded as a male trait that has evolved through sexual selection. However, recent research has prompted a re-evaluation of this view by demonstrating that female song is an ancestral and phylogenetically widespread trait. Species with female song provide opportunities to study selective pressures and mechanisms specific to females within the wider context of social competition. We investigated the relationship between reproductive success and female song performance in the New Zealand bellbird (Anthornis melanura, a passerine resident year round in New Zealand temperate forests. We monitored breeding behavior and song over three years on Tiritiri Matangi Island. Female bellbirds contributed significantly more towards parental care than males (solely incubating young and provisioning chicks at more than twice the rate of males. Female song rate in the vicinity of the nest was higher than that of males during incubation and chick-rearing stages but similar during early-nesting and post-breeding stages. Using GLMs, we found that female song rates during both incubation and chick-rearing stages strongly predicted the number of fledged chicks. However, male song rate and male and female chick provisioning rates had no effect on fledging success. Two measures of female song complexity (number of syllable types and the number of transitions between different syllable types were also good predictors of breeding success (GLM on PC scores. In contrast, song duration, the total number of syllables, and the number of ‘stutter’ syllables per song were not correlated with fledging success. It is unclear why male song rate was not associated with reproductive success and we speculate that extra-pair paternity might play a role. While we have previously demonstrated that female bellbird song is important in intrasexual interactions, we clearly demonstrate here that female song predicts reproductive success. These results, with others

  19. Equivalency and unbiasedness of grey prediction models

    Institute of Scientific and Technical Information of China (English)

    Bo Zeng; Chuan Li; Guo Chen; Xianjun Long

    2015-01-01

    In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction mo-dels, the equivalence and unbiasedness of grey prediction mo-dels are analyzed and verified. The results show that al the grey prediction models that are strictly derived from x(0)(k) +az(1)(k) = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homoge-neous exponential sequence can be accomplished. However, the models derived from dx(1)/dt+ax(1) =b are only close to those derived from x(0)(k)+az(1)(k)=b provided that|a|has to satisfy|a| < 0.1; neither could the unbiased simulation for the homoge-neous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.

  20. Predictability of extreme values in geophysical models

    Directory of Open Access Journals (Sweden)

    A. E. Sterk

    2012-09-01

    Full Text Available Extreme value theory in deterministic systems is concerned with unlikely large (or small values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical models. We study whether finite-time Lyapunov exponents are larger or smaller for initial conditions leading to extremes. General statements on whether extreme values are better or less predictable are not possible: the predictability of extreme values depends on the observable, the attractor of the system, and the prediction lead time.

  1. Model for Predicting Passage of Invasive Fish Species Through Culverts

    Science.gov (United States)

    Neary, V.

    2010-12-01

    Conservation efforts to promote or inhibit fish passage include the application of simple fish passage models to determine whether an open channel flow allows passage of a given fish species. Derivations of simple fish passage models for uniform and nonuniform flow conditions are presented. For uniform flow conditions, a model equation is developed that predicts the mean-current velocity threshold in a fishway, or velocity barrier, which causes exhaustion at a given maximum distance of ascent. The derivation of a simple expression for this exhaustion-threshold (ET) passage model is presented using kinematic principles coupled with fatigue curves for threatened and endangered fish species. Mean current velocities at or above the threshold predict failure to pass. Mean current velocities below the threshold predict successful passage. The model is therefore intuitive and easily applied to predict passage or exclusion. The ET model’s simplicity comes with limitations, however, including its application only to uniform flow, which is rarely found in the field. This limitation is addressed by deriving a model that accounts for nonuniform conditions, including backwater profiles and drawdown curves. Comparison of these models with experimental data from volitional swimming studies of fish indicates reasonable performance, but limitations are still present due to the difficulty in predicting fish behavior and passage strategies that can vary among individuals and different fish species.

  2. Hybrid modeling and prediction of dynamical systems

    Science.gov (United States)

    Lloyd, Alun L.; Flores, Kevin B.

    2017-01-01

    Scientific analysis often relies on the ability to make accurate predictions of a system’s dynamics. Mechanistic models, parameterized by a number of unknown parameters, are often used for this purpose. Accurate estimation of the model state and parameters prior to prediction is necessary, but may be complicated by issues such as noisy data and uncertainty in parameters and initial conditions. At the other end of the spectrum exist nonparametric methods, which rely solely on data to build their predictions. While these nonparametric methods do not require a model of the system, their performance is strongly influenced by the amount and noisiness of the data. In this article, we consider a hybrid approach to modeling and prediction which merges recent advancements in nonparametric analysis with standard parametric methods. The general idea is to replace a subset of a mechanistic model’s equations with their corresponding nonparametric representations, resulting in a hybrid modeling and prediction scheme. Overall, we find that this hybrid approach allows for more robust parameter estimation and improved short-term prediction in situations where there is a large uncertainty in model parameters. We demonstrate these advantages in the classical Lorenz-63 chaotic system and in networks of Hindmarsh-Rose neurons before application to experimentally collected structured population data. PMID:28692642

  3. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children.

  4. Models and methods for wind effect prediction; Modeller og metoder til prediktion af vindeffekt

    Energy Technology Data Exchange (ETDEWEB)

    Joensen, A.

    1997-12-31

    In this report methods and models for predicting power produced by windmills, are considered. Several methods are suggested and investigated on actual observations of wind speed and the corresponding power. In order to improve the predictions meteorological forecasts are used in the formulation of the models. The methods applied cover non-parametric identification, least squares estimation and local regression. It was found that the meteorological forecasts significantly improved the predictions, and that a combination of non-parametric and parametric modelling, proved to be successful. (au) 38 refs.

  5. Inflammation, But Not Telomere Length, Predicts Successful Ageing at Extreme Old Age: A Longitudinal Study of Semi-supercentenarians.

    Science.gov (United States)

    Arai, Yasumichi; Martin-Ruiz, Carmen M; Takayama, Michiyo; Abe, Yukiko; Takebayashi, Toru; Koyasu, Shigeo; Suematsu, Makoto; Hirose, Nobuyoshi; von Zglinicki, Thomas

    2015-10-01

    To determine the most important drivers of successful ageing at extreme old age, we combined community-based prospective cohorts: Tokyo Oldest Old Survey on Total Health (TOOTH), Tokyo Centenarians Study (TCS) and Japanese Semi-Supercentenarians Study (JSS) comprising 1554 individuals including 684 centenarians and (semi-)supercentenarians, 167 pairs of centenarian offspring and spouses, and 536 community-living very old (85 to 99 years). We combined z scores from multiple biomarkers to describe haematopoiesis, inflammation, lipid and glucose metabolism, liver function, renal function, and cellular senescence domains. In Cox proportional hazard models, inflammation predicted all-cause mortality with hazard ratios (95% CI) 1.89 (1.21 to 2.95) and 1.36 (1.05 to 1.78) in the very old and (semi-)supercentenarians, respectively. In linear forward stepwise models, inflammation predicted capability (10.8% variance explained) and cognition (8(.)6% variance explained) in (semi-)supercentenarians better than chronologic age or gender. The inflammation score was also lower in centenarian offspring compared to age-matched controls with Δ (95% CI) = - 0.795 (- 1.436 to - 0.154). Centenarians and their offspring were able to maintain long telomeres, but telomere length was not a predictor of successful ageing in centenarians and semi-supercentenarians. We conclude that inflammation is an important malleable driver of ageing up to extreme old age in humans.

  6. Property predictions using microstructural modeling

    Energy Technology Data Exchange (ETDEWEB)

    Wang, K.G. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)]. E-mail: wangk2@rpi.edu; Guo, Z. [Sente Software Ltd., Surrey Technology Centre, 40 Occam Road, Guildford GU2 7YG (United Kingdom); Sha, W. [Metals Research Group, School of Civil Engineering, Architecture and Planning, The Queen' s University of Belfast, Belfast BT7 1NN (United Kingdom); Glicksman, M.E. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States); Rajan, K. [Department of Materials Science and Engineering, Rensselaer Polytechnic Institute, CII 9219, 110 8th Street, Troy, NY 12180-3590 (United States)

    2005-07-15

    Precipitation hardening in an Fe-12Ni-6Mn maraging steel during overaging is quantified. First, applying our recent kinetic model of coarsening [Phys. Rev. E, 69 (2004) 061507], and incorporating the Ashby-Orowan relationship, we link quantifiable aspects of the microstructures of these steels to their mechanical properties, including especially the hardness. Specifically, hardness measurements allow calculation of the precipitate size as a function of time and temperature through the Ashby-Orowan relationship. Second, calculated precipitate sizes and thermodynamic data determined with Thermo-Calc[copyright] are used with our recent kinetic coarsening model to extract diffusion coefficients during overaging from hardness measurements. Finally, employing more accurate diffusion parameters, we determined the hardness of these alloys independently from theory, and found agreement with experimental hardness data. Diffusion coefficients determined during overaging of these steels are notably higher than those found during the aging - an observation suggesting that precipitate growth during aging and precipitate coarsening during overaging are not controlled by the same diffusion mechanism.

  7. Voice and handgrip strength predict reproductive success in a group of indigenous African females.

    Directory of Open Access Journals (Sweden)

    Jeremy Atkinson

    Full Text Available Evolutionary accounts of human traits are often based on proxies for genetic fitness (e.g., number of sex partners, facial attractiveness. Instead of using proxies, actual differences in reproductive success is a more direct measure of darwinian fitness. Certain voice acoustics such as fundamental frequency and measures of health such as handgrip strength correlate with proxies of fitness, yet there are few studies showing the relation of these traits to reproduction. Here, we explore whether the fundamental frequency of the voice and handgrip strength account for differences in actual reproduction among a population of natural fertility humans. Our results show that both fundamental frequency and handgrip strength predict several measures of reproductive success among a group of indigenous Namibian females, particularly amongst the elderly, with weight also predicting reproductive outcomes among males. These findings demonstrate that both hormonally regulated and phenotypic quality markers can be used as measures of darwinian fitness among humans living under conditions that resemble the evolutionary environment of Homo sapiens. We also argue that these findings provide support for the Grandmother Hypothesis.

  8. A successful solar model using new solar composition data

    CERN Document Server

    Vagnozzi, Sunny; Zurbuchen, Thomas H

    2016-01-01

    A resolution is proposed to the "solar abundance problem", that is, the discrepancy between helioseismological observations and the predictions of solar models, computed implementing state-of-the-art photospheric abundances. We reassess the problem considering a newly determined set of abundances, which indicate a lower limit to the metallicity of $Z_{\\odot} = 0.0196 \\pm 0.0014$, significantly higher than findings during the past decade. Such value for the metallicity is determined in situ, measuring the least fractionated solar winds over the poles of the Sun, rather than spectroscopically. We determine the response of helioseismological observables to the corresponding changes in elemental abundances. Our findings indicate that, taking inversion errors into account, good agreement between models and observations is achieved. The definitive test for these abundances will be measurements of the CNO neutrino fluxes by SNO$^+$ (which we expect to be $\\sim$ 30-50\\% higher than predictions using abundances based ...

  9. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  10. Student Success: Approaches to Modeling Student Matriculation and Retention

    OpenAIRE

    Lin, Jien-Jou

    2013-01-01

    Every year a group of graduates from high schools enter the engineering programs across this country with remarkable academic record. However, as reported in numerous studies, the number of students switching out of engineering majors continues to be an important issue. Previous studies have suggested various factors as predictors for student retention in engineering. To assist the engineering students with timely advising early in their program, an effective prediction model of matriculation...

  11. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp

    2016-01-01

    Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... that describes the variation between subjects. The ODE setup implies that the variation for a single subject is described by a single parameter (or vector), namely the variance (covariance) of the residuals. Furthermore the prediction of the states is given as the solution to the ODEs and hence assumed...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...

  12. Precision Plate Plan View Pattern Predictive Model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yang; YANG Quan; HE An-rui; WANG Xiao-chen; ZHANG Yun

    2011-01-01

    According to the rolling features of plate mill, a 3D elastic-plastic FEM (finite element model) based on full restart method of ANSYS/LS-DYNA was established to study the inhomogeneous plastic deformation of multipass plate rolling. By analyzing the simulation results, the difference of head and tail ends predictive models was found and modified. According to the numerical simulation results of 120 different kinds of conditions, precision plate plan view pattern predictive model was established. Based on these models, the sizing MAS (mizushima automatic plan view pattern control system) method was designed and used on a 2 800 mm plate mill. Comparing the rolled plates with and without PVPP (plan view pattern predictive) model, the reduced width deviation indicates that the olate !olan view Dattern predictive model is preeise.

  13. Predicting NCLEX success with the HESI Exit Exam: fourth annual validity study.

    Science.gov (United States)

    Nibert, Ainslie T; Young, Anne; Adamson, Carolyn

    2008-01-01

    The fourth annual validity study of the Health Education Systems, Inc. (HESI) Exit Exam was designed to examine not only the accuracy of the examination in predicting NCLEX success but also the degree of risk for failure of the licensure examination associated with specific scoring intervals. A descriptive comparative design was used to examine the data provided by schools of nursing regarding students' NCLEX outcomes in the 1999-2000 academic year. As in the 3 previous studies, the examination was found to be a highly accurate predictor of NCLEX success (98.46%). Each scoring interval was significantly different from each of the other scoring intervals (P = .001). In fact, for the combined group of registered nurse and practical nurse students, the percentage of students who failed the NCLEX more than doubled with each successively lower scoring interval. These findings provide the information faculties needed to make evidence-based decisions regarding students' risks for NCLEX failure. Additionally, frequency data were obtained from this survey regarding the use of the examination as a benchmark for progression and remediation, and these findings may also be useful to faculties that are considering establishing such programs.

  14. Prediction of autosomal STR typing success in ancient and Second World War bone samples.

    Science.gov (United States)

    Zupanič Pajnič, Irena; Zupanc, Tomaž; Balažic, Jože; Geršak, Živa Miriam; Stojković, Oliver; Skadrić, Ivan; Črešnar, Matija

    2017-03-01

    Human-specific quantitative PCR (qPCR) has been developed for forensic use in the last 10 years and is the preferred DNA quantification technique since it is very accurate, sensitive, objective, time-effective and automatable. The amount of information that can be gleaned from a single quantification reaction using commercially available quantification kits has increased from the quantity of nuclear DNA to the amount of male DNA, presence of inhibitors and, most recently, to the degree of DNA degradation. In skeletal remains samples from disaster victims, missing persons and war conflict victims, the DNA is usually degraded. Therefore the new commercial qPCR kits able to assess the degree of degradation are potentially able to predict the success of downstream short tandem repeat (STR) typing. The goal of this study was to verify the quantification step using the PowerQuant kit with regard to its suitability as a screening method for autosomal STR typing success on ancient and Second World War (WWII) skeletal remains. We analysed 60 skeletons excavated from five archaeological sites and four WWII mass graves from Slovenia. The bones were cleaned, surface contamination was removed and the bones ground to a powder. Genomic DNA was obtained from 0.5g of bone powder after total demineralization. The DNA was purified using a Biorobot EZ1 device. Following PowerQuant quantification, DNA samples were subjected to autosomal STR amplification using the NGM kit. Up to 2.51ng DNA/g of powder were extracted. No inhibition was detected in any of bones analysed. 82% of the WWII bones gave full profiles while 73% of the ancient bones gave profiles not suitable for interpretation. Four bone extracts yielded no detectable amplification or zero quantification results and no profiles were obtained from any of them. Full or useful partial profiles were produced only from bone extracts where short autosomal (Auto) and long degradation (Deg) PowerQuant targets were detected. It is

  15. Towards predictive food process models: A protocol for parameter estimation.

    Science.gov (United States)

    Vilas, Carlos; Arias-Méndez, Ana; Garcia, Miriam R; Alonso, Antonio A; Balsa-Canto, E

    2016-05-31

    Mathematical models, in particular, physics-based models, are essential tools to food product and process design, optimization and control. The success of mathematical models relies on their predictive capabilities. However, describing physical, chemical and biological changes in food processing requires the values of some, typically unknown, parameters. Therefore, parameter estimation from experimental data is critical to achieving desired model predictive properties. This work takes a new look into the parameter estimation (or identification) problem in food process modeling. First, we examine common pitfalls such as lack of identifiability and multimodality. Second, we present the theoretical background of a parameter identification protocol intended to deal with those challenges. And, to finish, we illustrate the performance of the proposed protocol with an example related to the thermal processing of packaged foods.

  16. NBC Hazard Prediction Model Capability Analysis

    Science.gov (United States)

    1999-09-01

    Puff( SCIPUFF ) Model Verification and Evaluation Study, Air Resources Laboratory, NOAA, May 1998. Based on the NOAA review, the VLSTRACK developers...TO SUBSTANTIAL DIFFERENCES IN PREDICTIONS HPAC uses a transport and dispersion (T&D) model called SCIPUFF and an associated mean wind field model... SCIPUFF is a model for atmospheric dispersion that uses the Gaussian puff method - an arbitrary time-dependent concentration field is represented

  17. Predicting success of labor induction in singleton term pregnancies by combining maternal and ultrasound variables.

    Science.gov (United States)

    Prado, Caio Antonio de Campos; Araujo Júnior, Edward; Duarte, Geraldo; Quintana, Silvana Maria; Tonni, Gabriele; Cavalli, Ricardo de Carvalho; Marcolin, Alessandra Cristina

    2016-11-01

    To assess pre-induction maternal and ultrasonographic factors in the prediction of the onset of labor within 12 h, and vaginal delivery (VD) irrespective of the induction-to-delivery interval in term pregnancies. We performed a prospective cohort study with 204 singleton pregnant women between 37 and 42 weeks of gestation. The following maternal and ultrasonographic variables were assessed: parity, marital status, height, body mass index (BMI), previous cesarean section (Cs), Bishop score, variety of fetal position, single deepest pocket (SDP), fetal middle cerebral and umbilical artery resistance indices, cervical length (CL) measurement, posterior cervical angle (PCA), head circumference (HC) and estimated fetal weight (EFW). χ(2) test and logistic regression analysis were applied to compare the groups. Receiver operating characteristics (ROC) curves were determined. VD occurred in 116 (56.9%) women. Prediction of the onset of labor within 12 h was provided by the BMI and resistance index of the fetal middle cerebral artery. Prediction of the VD irrespective of the induction-to-delivery interval was provided by height, BMI, parity, number of prenatal visits, consistency, effacement and dilation of uterine cervix, PCA, oligohydramnios, HC and EFW. Area under ROC curve for PCA and EFW were 63.5 (sensibility: 66.4%, specificity: 59.1%) and 60.2 (sensibility: 54.3%, specificity: 70.4%), respectively. Several pre-induction maternal and ultrasonographic factors can increase the chance of achieving a successful VD. PCA and EFW were the best ultrasonographic predictors for the success of induction of labor; however, with limited potential to be used in the clinical practice.

  18. Successes and failures of the constituent quark model

    Energy Technology Data Exchange (ETDEWEB)

    Lipkin, H.J.

    1982-01-01

    Our approach considers the model as a possible bridge between QCD and the experimental data and examines its predictions to see where these succeed and where they fail. We also attempt to improve the model by looking for additional simple assumptions which give better fits to the experimental data. But we avoid complicated models with too many ad hoc assumptions and too many free parameters; these can fit everything but teach us nothing. We define our constituent quark model by analogy with the constituent electron model of the atom and the constituent nucleon model of the nucleus. In the same way that an atom is assumed to consist only of constituent electrons and a central Coulomb field and a nucleus is assumed to consist only of constituent nucleons hadrons are assumed to consist only of their constituent valence quarks with no bag, no glue, no ocean, nor other constituents. Although these constituent models are oversimplified and neglect other constituents we push them as far as we can. Atomic physics has photons and vacuum polarization as well as constituent electrons, but the constituent model is adequate for calculating most features of the spectrum when finer details like the Lamb shift are neglected. 54 references.

  19. Corporate prediction models, ratios or regression analysis?

    NARCIS (Netherlands)

    Bijnen, E.J.; Wijn, M.F.C.M.

    1994-01-01

    The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in

  20. Entrepreneurial Women in Radiology: Role Models of Success.

    Science.gov (United States)

    Anzai, Yoshimi; Meltzer, Carolyn C; DeStigter, Kristen K; Destounis, Stamatia; Pawley, Barbara K; Oates, M Elizabeth

    2016-11-01

    Radiology is undeniably male dominated. Alongside surgery and orthopedic surgery, academic radiology ranks near the bottom in having the lowest proportion of full-time female faculty members. Despite many efforts to recruit talented women, the pipeline entering the radiologic disciplines continues to flow at a trickle. One factor is the relative lack of role models for female medical students. Entrepreneurial women in radiology can lead the field with their innovation and creativity, courage, and commitment. In this article, the authors highlight two entrepreneurial female radiologists who shared their success stories at the American Association for Women Radiologists' session at the 2015 ACR annual meeting. Their successes underscore the potential for such women to serve as role models to female medical students and even college undergraduates. Despite the gender gap in radiology, the field has yielded some exceptional women who can take on challenges, overcome barriers and assume risks, create strategies and processes to operationalize their visions, secure funding, and expand their enterprises to make sustainable impacts both at home and abroad. As we move toward more patient- and family-centered care models and become increasingly visible to diverse populations, there is no better time for female leaders in radiology to inspire the next generation to join our essential and rewarding specialty. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  1. Modelling Chemical Reasoning to Predict Reactions

    CERN Document Server

    Segler, Marwin H S

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outperforms a rule-based expert system in the reaction prediction task for 180,000 randomly selected binary reactions. We show that our data-driven model generalises even beyond known reaction types, and is thus capable of effectively (re-) discovering novel transformations (even including transition-metal catalysed reactions). Our model enables computers to infer hypotheses about reactivity and reactions by only considering the intrinsic local structure of the graph, and because each single reaction prediction is typically ac...

  2. How Preschoolers' Social-Emotional Learning Predicts Their Early School Success: Developing Theory-Promoting, Competency-Based Assessments

    Science.gov (United States)

    Denham, Susanne A.; Bassett, Hideko H.; Zinsser, Katherine; Wyatt, Todd M.

    2014-01-01

    Starting on positive trajectories at school entry is important for children's later academic success. Using partial least squares, we sought to specify interrelations among all theory-based components of social-emotional learning (SEL), and their ability to predict later classroom adjustment and academic readiness in a modelling context.…

  3. Preparing for success: Readiness models for rural telehealth

    Directory of Open Access Journals (Sweden)

    Jennett P

    2005-01-01

    Full Text Available Background: Readiness is an integral and preliminary step in the successful implementation of telehealth services into existing health systems within rural communities. Methods and Materials: This paper details and critiques published international peer-reviewed studies that have focused on assessing telehealth readiness for rural and remote health. Background specific to readiness and change theories is provided, followed by a critique of identified telehealth readiness models, including a commentary on their readiness assessment tools. Results: Four current readiness models resulted from the search process. The four models varied across settings, such as rural outpatient practices, hospice programs, rural communities, as well as government agencies, national associations, and organizations. All models provided frameworks for readiness tools. Two specifically provided a mechanism by which communities could be categorized by their level of telehealth readiness. Discussion: Common themes across models included: an appreciation of practice context, strong leadership, and a perceived need to improve practice. Broad dissemination of these telehealth readiness models and tools is necessary to promote awareness and assessment of readiness. This will significantly aid organizations to facilitate the implementation of telehealth.

  4. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  5. Genetic models of homosexuality: generating testable predictions

    OpenAIRE

    Gavrilets, Sergey; Rice, William R.

    2006-01-01

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality inclu...

  6. Predicting Student Success on the Texas Chemistry STAAR Test: A Logistic Regression Analysis

    Science.gov (United States)

    Johnson, William L.; Johnson, Annabel M.; Johnson, Jared

    2012-01-01

    Background: The context is the new Texas STAAR end-of-course testing program. Purpose: The authors developed a logistic regression model to predict who would pass-or-fail the new Texas chemistry STAAR end-of-course exam. Setting: Robert E. Lee High School (5A) with an enrollment of 2700 students, Tyler, Texas. Date of the study was the 2011-2012…

  7. Wind farm production prediction - The Zephyr model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)

    2002-06-01

    This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)

  8. Predicting success or failure of brace treatment for adolescents with idiopathic scoliosis.

    Science.gov (United States)

    Chalmers, Eric; Westover, Lindsey; Jacob, Johith; Donauer, Andreas; Zhao, Vicky H; Parent, Eric C; Moreau, Marc J; Mahood, James K; Hedden, Douglas M; Lou, Edmond H M

    2015-10-01

    Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal deformity. Brace treatment is a common non-surgical treatment, intended to prevent progression (worsening) of the condition during adolescence. Estimating a braced patient's risk of progression is an essential part of planning treatment, so method for predicting this risk would be a useful decision support tool for practitioners. This work attempts to discover whether failure of brace treatment (progression) can be predicted at the start of treatment. Records were obtained for 62 AIS patients who had completed brace treatment. Subjects were labeled as "progressive" if their condition had progressed despite brace treatment and "non-progressive" otherwise. Wrapper-based feature selection selected two useful predictor variables from a list of 14 clinical measurements taken from the records. A logistic regression model was trained to classify patients as "progressive" or "non-progressive" using these two variables. The logistic regression model's simplicity and interpretability should facilitate its clinical acceptance. The model was tested on data from an additional 28 patients and found to be 75 % accurate. This accuracy is sufficient to make the predictions clinically useful. It can be used online: http://www.ece.ualberta.ca/~dchalmer/SimpleBracePredictor.html .

  9. Modeling the prediction of business intelligence system effectiveness.

    Science.gov (United States)

    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.

  10. Using Video Analysis and Machine Learning for Predicting Shot Success in Table Tennis

    Directory of Open Access Journals (Sweden)

    Lukas Draschkowitz

    2015-10-01

    Full Text Available Coaching professional ball players has become more and more dicult and requires among other abilities also good tactical knowledge. This paper describes a program that can assist in tactical coaching for table tennis by extracting and analyzing video data of a table tennis game. The here described application automatically extracts essential information from a table tennis match, such as speed, length, height and others, by analyzing a video of that game. It then uses the well known machine learning library " to learn about the success of a shot. Generalization is tested by using a training and a test set. The program then is able to predict the outcome of shots with high accuracy. This makes it possible to develop and verify tactical suggestions for players as part of an automatic analyzing and coaching tool, completely independent of human interaction.

  11. Habitat fragmentation and reproductive success: a structural equation modelling approach.

    Science.gov (United States)

    Le Tortorec, Eric; Helle, Samuli; Käyhkö, Niina; Suorsa, Petri; Huhta, Esa; Hakkarainen, Harri

    2013-09-01

    1. There is great interest on the effects of habitat fragmentation, whereby habitat is lost and the spatial configuration of remaining habitat patches is altered, on individual breeding performance. However, we still lack consensus of how this important process affects reproductive success, and whether its effects are mainly due to reduced fecundity or nestling survival. 2. The main reason for this may be the way that habitat fragmentation has been previously modelled. Studies have treated habitat loss and altered spatial configuration as two independent processes instead of as one hierarchical and interdependent process, and therefore have not been able to consider the relative direct and indirect effects of habitat loss and altered spatial configuration. 3. We investigated how habitat (i.e. old forest) fragmentation, caused by intense forest harvesting at the territory and landscape scales, is associated with the number of fledged offspring of an area-sensitive passerine, the Eurasian treecreeper (Certhia familiaris). We used structural equation modelling (SEM) to examine the complex hierarchical associations between habitat loss and altered spatial configuration on the number of fledged offspring, by controlling for individual condition and weather conditions during incubation. 4. Against generally held expectations, treecreeper reproductive success did not show a significant association with habitat fragmentation measured at the territory scale. Instead, our analyses suggested that an increasing amount of habitat at the landscape scale caused a significant increase in nest predation rates, leading to reduced reproductive success. This effect operated directly on nest predation rates, instead of acting indirectly through altered spatial configuration. 5. Because habitat amount and configuration are inherently strongly collinear, particularly when multiple scales are considered, our study demonstrates the usefulness of a SEM approach for hierarchical partitioning

  12. Modeling succession of key resource-harvesting traits of mixotrophic plankton

    DEFF Research Database (Denmark)

    Berge, Terje; Chakraborty, Subhendu; Hansen, Per Juel

    2017-01-01

    -based model for mixotrophy with three key resource-harvesting traits: photosynthesis, phagotrophy and inorganic nutrient uptake, which predicts the trophic strategy of species throughout the seasonal cycle. Assuming that simple carbohydrates from photosynthesis fuel respiration, and feeding primarily provides...... in the spring and increased phagotrophy during the summer, reflecting general seasonal succession patterns of temperate waters. Our trait-based model presents a simple and general approach for the inclusion of mixotrophy, succession and evolution in ecosystem models.The ISME Journal advance online publication......Unicellular eukaryotes make up the base of the ocean food web and exist as a continuum in trophic strategy from pure heterotrophy (phagotrophic zooplankton) to pure photoautotrophy (‘phytoplankton’), with a dominance of mixotrophic organisms combining both strategies. Here we formulate a trait...

  13. Latino Definitions of Success: A Cultural Model of Intercultural Competence.

    Science.gov (United States)

    Torres, Lucas

    2009-01-01

    The present study sought to examine Latino intercultural competence via two separate methodologies. Phase 1 entailed discovering and generating themes regarding the features of intercultural competence based on semistructured interviews of 15 Latino adults. Phase 2 included conducting a cultural consensus analysis from the quantitative responses of 46 Latino adults to determine the cultural model of intercultural competence. The major results indicated that the participants, despite variations in socioeconomic and generational statuses, shared a common knowledge base regarding the competencies needed for Latinos to successfully navigate different cultures. Overall, the cultural model of Latino intercultural competence includes a set of skills that integrates traditional cultural values along with attributes of self-efficacy. The findings are discussed within a competence-based conceptualization of cultural adaptation and potential advancements in acculturation research.

  14. Successes and shortcomings of polio eradication: a transmission modeling analysis.

    Science.gov (United States)

    Mayer, Bryan T; Eisenberg, Joseph N S; Henry, Christopher J; Gomes, M Gabriela M; Ionides, Edward L; Koopman, James S

    2013-06-01

    Polio eradication is on the cusp of success, with only a few regions still maintaining transmission. Improving our understanding of why some regions have been successful and others have not will help with both global eradication of polio and development of more effective vaccination strategies for other pathogens. To examine the past 25 years of eradication efforts, we constructed a transmission model for wild poliovirus that incorporates waning immunity (which affects both infection risk and transmissibility of any resulting infection), age-mediated vaccination rates, and transmission of oral polio vaccine. The model produces results consistent with the 4 country categories defined by the Global Polio Eradication Program: elimination with no subsequent outbreaks; elimination with subsequent transient outbreaks; elimination with subsequent outbreaks and transmission detected for more than 12 months; and endemic polio transmission. Analysis of waning immunity rates and oral polio vaccine transmissibility reveals that higher waning immunity rates make eradication more difficult because of increasing numbers of infectious adults, and that higher oral polio vaccine transmission rates make eradication easier as adults become reimmunized. Given these dynamic properties, attention should be given to intervention strategies that complement childhood vaccination. For example, improvement in sanitation can reduce the reproduction number in problematic regions, and adult vaccination can lower adult transmission.

  15. Development of Groundwater Modeling Capacity in Mongolia: Keys to Success

    Science.gov (United States)

    Anderson, M. T.; Valder, J. F.; Carter, J. M.

    2015-12-01

    Ulaanbaatar, the capital city of Mongolia, is totally dependent on groundwater for its municipal and industrial water supply. Water is drawn from a network of shallow wells in an alluvial aquifer along the Tuul River. Evidence, however, suggests that current water use and especially the projected water demand from a rapidly growing urban population, is not sustainable from existing water sources. In response, the Mongolia Ministry of Environment and the Mongolian Fresh Water Institute requested technical assistance on groundwater modeling through the U.S. Army Corps of Engineers to the U.S. Geological Survey (USGS). Scientists from the USGS-SD Water Science Center provided a workshop to Mongolian water experts on basic principles of groundwater modeling using MODFLOW. The purpose of the workshop was to bring together representatives from the Government of Mongolia, local universities, technical experts, and other key stakeholders to build in-country capacity in hydrogeology and groundwater modeling. A preliminary steady-state groundwater flow model was developed to simulate groundwater conditions in the Tuul River Basin and for use in water use decision-making. The model consisted of 2 layers, 226 rows, and 260 columns with uniform 500 meter grid spacing. The upper model layer represented the alluvial aquifer and the lower layer represented the underlying bedrock, which includes areas characterized by permafrost. Estimated groundwater withdrawal was 180 m3/day, and estimated recharge was 114 mm/yr. The model will be modified and updated by Mongolian scientists as more data are available. Ultimately the model will be used to assist managers in developing a sustainable water supply, for current use and changing climate scenarios. A key to success was developing in-country technical capacity and partnerships with the Mongolian University of Science and Technology, Mongolian Freshwater Institute, a non-profit organization, UNESCO, and the government of Mongolia.

  16. Predictive model for segmented poly(urea

    Directory of Open Access Journals (Sweden)

    Frankl P.

    2012-08-01

    Full Text Available Segmented poly(urea has been shown to be of significant benefit in protecting vehicles from blast and impact and there have been several experimental studies to determine the mechanisms by which this protective function might occur. One suggested route is by mechanical activation of the glass transition. In order to enable design of protective structures using this material a constitutive model and equation of state are needed for numerical simulation hydrocodes. Determination of such a predictive model may also help elucidate the beneficial mechanisms that occur in polyurea during high rate loading. The tool deployed to do this has been Group Interaction Modelling (GIM – a mean field technique that has been shown to predict the mechanical and physical properties of polymers from their structure alone. The structure of polyurea has been used to characterise the parameters in the GIM scheme without recourse to experimental data and the equation of state and constitutive model predicts response over a wide range of temperatures and strain rates. The shock Hugoniot has been predicted and validated against existing data. Mechanical response in tensile tests has also been predicted and validated.

  17. Is the First-Year Predictive for Study Success in Subsequent Years? Findings from an Academy of Music

    Science.gov (United States)

    Mennen, Josien; van der Klink, Marcel

    2017-01-01

    In higher education, departments are under increasing pressure to improve study success. Research in this field focusing on higher music education is scarce. The aim of this study was to gain insight into the predictive capability of the first year for study success of students at an academy of music in subsequent years. Data on study progression…

  18. Why some make it and others do not: Identifying psychological factors that predict career success in professional adult soccer

    NARCIS (Netherlands)

    Van Yperen, Nico W.

    2009-01-01

    This prospective study was designed to identify psychological factors that predict career success in professional adult soccer. Post hoc, two groups were distinguished: (1) Male soccer players who Successfully progressed into professional adult soccer (n = 18) and (2) Male soccer players who did not

  19. PREDICTIVE CAPACITY OF ARCH FAMILY MODELS

    Directory of Open Access Journals (Sweden)

    Raphael Silveira Amaro

    2016-03-01

    Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.

  20. Predictive QSAR modeling of phosphodiesterase 4 inhibitors.

    Science.gov (United States)

    Kovalishyn, Vasyl; Tanchuk, Vsevolod; Charochkina, Larisa; Semenuta, Ivan; Prokopenko, Volodymyr

    2012-02-01

    A series of diverse organic compounds, phosphodiesterase type 4 (PDE-4) inhibitors, have been modeled using a QSAR-based approach. 48 QSAR models were compared by following the same procedure with different combinations of descriptors and machine learning methods. QSAR methodologies used random forests and associative neural networks. The predictive ability of the models was tested through leave-one-out cross-validation, giving a Q² = 0.66-0.78 for regression models and total accuracies Ac=0.85-0.91 for classification models. Predictions for the external evaluation sets obtained accuracies in the range of 0.82-0.88 (for active/inactive classifications) and Q² = 0.62-0.76 for regressions. The method showed itself to be a potential tool for estimation of IC₅₀ of new drug-like candidates at early stages of drug development. Copyright © 2011 Elsevier Inc. All rights reserved.

  1. A Genetically Optimized Predictive System for Success in General Chemistry Using a Diagnostic Algebra Test

    Science.gov (United States)

    Cooper, Cameron I.; Pearson, Paul T.

    2012-02-01

    In higher education, many high-enrollment introductory courses have evolved into "gatekeeper" courses due to their high failure rates. These courses prevent many students from attaining their educational goals and often become graduation roadblocks. At the authors' home institution, general chemistry has become a gatekeeper course in which approximately 25% of students do not pass. This failure rate in chemistry is common, and often higher, at many other institutions of higher education, and mathematical deficiencies are perceived to be a large contributing factor. This paper details the development of a highly accurate predictive system that identifies students at the beginning of the semester who are "at-risk" for earning a grade of C- or below in chemistry. The predictive accuracy of this system is maximized by using a genetically optimized neural network to analyze the results of a diagnostic algebra test designed for a specific population. Once at-risk students have been identified, they can be helped to improve their chances of success using techniques such as concurrent support courses, online tutorials, "just-in-time" instructional aides, study skills, motivational interviewing, and/or peer mentoring.

  2. Male heterozygosity predicts territory size, song structure and reproductive success in a cooperatively breeding bird.

    Science.gov (United States)

    Seddon, Nathalie; Amos, William; Mulder, Raoul A; Tobias, Joseph A

    2004-09-01

    Recent studies of non-social animals have shown that sexually selected traits signal at least one measure of genetic quality: heterozygosity. To determine whether similar cues reveal group quality in more complex social systems, we examined the relationship between territory size, song structure and heterozygosity in the subdesert mesite (Monias benschi), a group-living bird endemic to Madagascar. Using nine polymorphic microsatellite loci, we found that heterozygosity predicted both the size of territories and the structure of songs used to defend them: more heterozygous groups had larger territories, and more heterozygous males used longer, lower-pitched trills in their songs. Heterozygosity was linked to territory size and song structure in males, but not in females, implying that these traits are sexually selected by female choice and/or male-male competition. To our knowledge, this study provides the first direct evidence in any animal that territory size is related to genetic diversity. We also found a positive association between seasonal reproductive success and heterozygosity, suggesting that this heritable characteristic is a reliable indicator of group quality and fitness. Given that heterozygosity predicts song structure in males, and can therefore be determined by listening to acoustic cues, we identify a mechanism by which social animals may assess rival groups, prospective partners and group mates, information of potential importance in guiding decisions related to conflict, breeding and dispersal.

  3. Semen quality and prediction of IUI success in male subfertility: a systematic review.

    Science.gov (United States)

    Ombelet, Willem; Dhont, Nathalie; Thijssen, Annelies; Bosmans, Eugene; Kruger, Thinus

    2014-03-01

    Many variables may influence success rates after intrauterine insemination (IUI), including sperm quality in the native and washed semen sample. A literature search was performed to investigate the threshold levels of sperm parameters above which IUI pregnancy outcome is significantly improved and/or the cut-off values reaching substantial discriminative performance in an IUI programme. A search of MEDLINE, EMBASE and Cochrane Library revealed a total of 983 papers. Only 55 studies (5.6%) fulfilled the inclusion criteria and these papers were analysed. Sperm parameters most frequently examined were: (i) inseminating motile count after washing: cut-off value between 0.8 and 5 million; (ii) sperm morphology using strict criteria: cut-off value ⩾5% normal morphology; (iii) total motile sperm count in the native sperm sample: cut-off value of 5-10 million; and (iv) total motility in the native sperm sample: threshold value of 30%. The results indicate a lack of prospective studies, a lack of standardization in semen testing methodology and a huge heterogeneity of patient groups and IUI treatment strategies. More prospective cohort trials and prospective randomized trials investigating the predictive value of semen parameters on IUI outcome are urgently needed. It is generally believed that intrauterine insemination (IUI) with homologous semen should be a first-choice treatment to more invasive and expensive techniques of assisted reproduction in cases of cervical, unexplained and moderate male factor subfertility. The rationale for the use of artificial insemination is to increase gamete density at the site of fertilization. Scientific validation of this strategy is difficult because literature is rather confusing and inconclusive. Many variables may influence success rates after IUI treatment procedures. It seems logical that sperm quality has to be one of the main determinants to predict IUI success. Clinical practice would benefit from the establishment of

  4. Evaluation of Spatial Agreement of Distinct Landslide Prediction Models

    Science.gov (United States)

    Sterlacchini, Simone; Bordogna, Gloria; Frigerio, Ivan

    2013-04-01

    The aim of the study was to assess the degree of spatial agreement of different predicted patterns in a majority of coherent landslide prediction maps with almost similar success and prediction rate curves. If two or more models have a similar performance, the choice of the best one is not a trivial operation and cannot be based on success and prediction rate curves only. In fact, it may happen that two or more prediction maps with similar accuracy and predictive power do not have the same degree of agreement in terms of spatial predicted patterns. The selected study area is the high Valtellina valley, in North of Italy, covering a surface of about 450 km2 where mapping of historical landslides is available. In order to assess landslide susceptibility, we applied the Weights of Evidence (WofE) modeling technique implemented by USGS by means of ARC-SDM tool. WofE efficiently investigate the spatial relationships among past events and multiple predisposing factors, providing useful information to identify the most probable location of future landslide occurrences. We have carried out 13 distinct experiments by changing the number of morphometric and geo-environmental explanatory variables in each experiment with the same training set and thus generating distinct models of landslide prediction, computing probability degrees of occurrence of landslides in each pixel. Expert knowledge and previous results from indirect statistically-based methods suggested slope, land use, and geology the best "driving controlling factors". The Success Rate Curve (SRC) was used to estimate how much the results of each model fit the occurrence of landslides used for the training of the models. The Prediction Rate Curve (PRC) was used to estimate how much the model predict the occurrence of landslides in the validation set. We found that the performances were very similar for different models. Also the dendrogram of the Cohen's kappa statistic and Principal Component Analysis (PCA) were

  5. Aptitude Tests and Successful College Students: The Predictive Validity of the General Aptitude Test (GAT) in Saudi Arabia

    Science.gov (United States)

    Alnahdi, Ghaleb Hamad

    2015-01-01

    Aptitude tests should predict student success at the university level. This study examined the predictive validity of the General Aptitude Test (GAT) in Saudi Arabia. Data for 27420 students enrolled at Prince Sattam bin Abdulaziz University were analyzed. Of these students, 17565 were male students, and 9855 were female students. Multiple…

  6. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-02-01

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

  7. Calibrated predictions for multivariate competing risks models.

    Science.gov (United States)

    Gorfine, Malka; Hsu, Li; Zucker, David M; Parmigiani, Giovanni

    2014-04-01

    Prediction models for time-to-event data play a prominent role in assessing the individual risk of a disease, such as cancer. Accurate disease prediction models provide an efficient tool for identifying individuals at high risk, and provide the groundwork for estimating the population burden and cost of disease and for developing patient care guidelines. We focus on risk prediction of a disease in which family history is an important risk factor that reflects inherited genetic susceptibility, shared environment, and common behavior patterns. In this work family history is accommodated using frailty models, with the main novel feature being allowing for competing risks, such as other diseases or mortality. We show through a simulation study that naively treating competing risks as independent right censoring events results in non-calibrated predictions, with the expected number of events overestimated. Discrimination performance is not affected by ignoring competing risks. Our proposed prediction methodologies correctly account for competing events, are very well calibrated, and easy to implement.

  8. Modelling language evolution: Examples and predictions.

    Science.gov (United States)

    Gong, Tao; Shuai, Lan; Zhang, Menghan

    2014-06-01

    We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

  9. Modelling language evolution: Examples and predictions

    Science.gov (United States)

    Gong, Tao; Shuai, Lan; Zhang, Menghan

    2014-06-01

    We survey recent computer modelling research of language evolution, focusing on a rule-based model simulating the lexicon-syntax coevolution and an equation-based model quantifying the language competition dynamics. We discuss four predictions of these models: (a) correlation between domain-general abilities (e.g. sequential learning) and language-specific mechanisms (e.g. word order processing); (b) coevolution of language and relevant competences (e.g. joint attention); (c) effects of cultural transmission and social structure on linguistic understandability; and (d) commonalities between linguistic, biological, and physical phenomena. All these contribute significantly to our understanding of the evolutions of language structures, individual learning mechanisms, and relevant biological and socio-cultural factors. We conclude the survey by highlighting three future directions of modelling studies of language evolution: (a) adopting experimental approaches for model evaluation; (b) consolidating empirical foundations of models; and (c) multi-disciplinary collaboration among modelling, linguistics, and other relevant disciplines.

  10. Model Predictive Control of Sewer Networks

    Science.gov (United States)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik; Poulsen, Niels K.; Falk, Anne K. V.

    2017-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and controlled have thus become essential factors for effcient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control.

  11. Modelling Chemical Reasoning to Predict Reactions

    OpenAIRE

    Segler, Marwin H. S.; Waller, Mark P.

    2016-01-01

    The ability to reason beyond established knowledge allows Organic Chemists to solve synthetic problems and to invent novel transformations. Here, we propose a model which mimics chemical reasoning and formalises reaction prediction as finding missing links in a knowledge graph. We have constructed a knowledge graph containing 14.4 million molecules and 8.2 million binary reactions, which represents the bulk of all chemical reactions ever published in the scientific literature. Our model outpe...

  12. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert; Knox, James

    2016-01-01

    Fully predictive models of the Four Bed Molecular Sieve of the Carbon Dioxide Removal Assembly on the International Space Station are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.

  13. Raman Model Predicting Hardness of Covalent Crystals

    OpenAIRE

    Zhou, Xiang-Feng; Qian, Quang-Rui; Sun, Jian; Tian, Yongjun; Wang, Hui-Tian

    2009-01-01

    Based on the fact that both hardness and vibrational Raman spectrum depend on the intrinsic property of chemical bonds, we propose a new theoretical model for predicting hardness of a covalent crystal. The quantitative relationship between hardness and vibrational Raman frequencies deduced from the typical zincblende covalent crystals is validated to be also applicable for the complex multicomponent crystals. This model enables us to nondestructively and indirectly characterize the hardness o...

  14. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts

  15. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  16. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ

  17. Prediction modelling for population conviction data

    NARCIS (Netherlands)

    Tollenaar, N.

    2017-01-01

    In this thesis, the possibilities of using prediction models for judicial penal case data are investigated. The development and refinement of a risk taxation scale based on these data is discussed. When false positives are weighted equally severe as false negatives, 70% can be classified correctly.

  18. Predictability of extreme values in geophysical models

    NARCIS (Netherlands)

    Sterk, A.E.; Holland, M.P.; Rabassa, P.; Broer, H.W.; Vitolo, R.

    2012-01-01

    Extreme value theory in deterministic systems is concerned with unlikely large (or small) values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical model

  19. A revised prediction model for natural conception

    NARCIS (Netherlands)

    Bensdorp, A.J.; Steeg, J.W. van der; Steures, P.; Habbema, J.D.; Hompes, P.G.; Bossuyt, P.M.; Veen, F. van der; Mol, B.W.; Eijkemans, M.J.; Kremer, J.A.M.; et al.,

    2017-01-01

    One of the aims in reproductive medicine is to differentiate between couples that have favourable chances of conceiving naturally and those that do not. Since the development of the prediction model of Hunault, characteristics of the subfertile population have changed. The objective of this analysis

  20. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  1. Predictive Modelling of Mycotoxins in Cereals

    NARCIS (Netherlands)

    Fels, van der H.J.; Liu, C.

    2015-01-01

    In dit artikel worden de samenvattingen van de presentaties tijdens de 30e bijeenkomst van de Werkgroep Fusarium weergegeven. De onderwerpen zijn: Predictive Modelling of Mycotoxins in Cereals.; Microbial degradation of DON.; Exposure to green leaf volatiles primes wheat against FHB but boosts produ

  2. Leptogenesis in minimal predictive seesaw models

    CERN Document Server

    Björkeroth, Fredrik; Varzielas, Ivo de Medeiros; King, Stephen F

    2015-01-01

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to $(\

  3. A Successive Selection Method for finite element model updating

    Science.gov (United States)

    Gou, Baiyong; Zhang, Weijie; Lu, Qiuhai; Wang, Bo

    2016-03-01

    Finite Element (FE) model can be updated effectively and efficiently by using the Response Surface Method (RSM). However, it often involves performance trade-offs such as high computational cost for better accuracy or loss of efficiency for lots of design parameter updates. This paper proposes a Successive Selection Method (SSM), which is based on the linear Response Surface (RS) function and orthogonal design. SSM rewrites the linear RS function into a number of linear equations to adjust the Design of Experiment (DOE) after every FE calculation. SSM aims to interpret the implicit information provided by the FE analysis, to locate the Design of Experiment (DOE) points more quickly and accurately, and thereby to alleviate the computational burden. This paper introduces the SSM and its application, describes the solution steps of point selection for DOE in detail, and analyzes SSM's high efficiency and accuracy in the FE model updating. A numerical example of a simply supported beam and a practical example of a vehicle brake disc show that the SSM can provide higher speed and precision in FE model updating for engineering problems than traditional RSM.

  4. Application Of Data Mining Techniques For Student Success And Failure Prediction The Case Of DebreMarkos University

    Directory of Open Access Journals (Sweden)

    Muluken Alemu Yehuala

    2015-04-01

    Full Text Available Abstract This research work has investigated the potential applicability of data mining technology to predict student success and failure cases on University students datasets. CRISP-DM Cross Industry Standard Process for Data mining is a data mining methodology to be used by the research. Classification and prediction data mining functionalities are used to extract hidden patterns from students data. These patterns can be seen in relation to different variables in the students records. The classification rule generation process is based on the decision tree and Bayes as a classification technique and the generated rules were studied and evaluated. Data collected from MSEXCEL files and it has been preprocessed for model building. Models were built and tested by using a sample dataset of 11873 regular undergraduate students. Analysis is done by using WEKA 3.7 application software. The research results offer a helpful and constructive recommendations to the academic planners in universities of learning to enhance their decision making process. This will also aid in the curriculum structure and modification in order to improve students academic performance. Students able to decide about their field of study before they are enrolled in specific field of study based on the previous experience taken from the research-findings. The research findings indicated that EHEECE Ethiopian Higher Education Entrance Certificate Examination result Sex Number of students in a class number of courses given in a semester and field of study are the major factors affecting the student performances. So on the bases of the research findings the level of student success will increase and it is possible to prevent educational institutions from serious financial strains.

  5. Specialized Language Models using Dialogue Predictions

    CERN Document Server

    Popovici, C; Popovici, Cosmin; Baggia, Paolo

    1996-01-01

    This paper analyses language modeling in spoken dialogue systems for accessing a database. The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. For this reason several models have been created, each one for a specific system question, such as the request or the confirmation of a parameter. The use of dialogue-dependent language models increases the performance both at the recognition and at the understanding level, especially on answers to system requests. Moreover other methods to increase performance, like automatic clustering of vocabulary words or the use of better acoustic models during recognition, does not affect the improvements given by dialogue-dependent language models. The system used in our experiments is Dialogos, the Italian spoken dialogue system used for accessing railway timetable information over the telephone. The experiments were carried out on a large corpus of dialogues coll...

  6. Self-responsibility predicts the successful outcome of coronary artery bypass surgery

    Directory of Open Access Journals (Sweden)

    C. J. Eales

    2004-02-01

    Full Text Available Purpose: This study was designed to determine whetherthe acceptance of self-responsibility is an important determinant of the successful outcome of coronary artery bypass graft (CABG surgery. The success of this costly intervention may be limited unless patients understand and adhere to the prescribed medical regimen, including diet and exercise after surgery. Patients suffering from chronic diseases must take charge of their own health and not abrogate that responsibility to the care providers.Method: Questionnaires were designed to determine aspects of improved quality of life and self-responsibility. For the study, 73 patients who had undergone CABG surgery were selected from surgical patients in the private as well as the public sector. In order to assess the acceptance of self-responsibility, the spouses/care-givers of the patients were included in the study. Patients were interviewed during the first few days after the operation when they had returned to the wards and again six months and 12 months later. Successful outcome was measured in terms of improved quality of life using the criteria suggested by the Coronary Artery Surgery Study (Coronary Artery Surgical Study PrincipalInvestigators, 1983. The acceptance of self-responsibility was then investigated as a possible factor influencing the improvement of the quality of life of these patients.Results: The acceptance of self-responsibility was a significant factor predicting the successful outcome of CABG surgery in the group of patients who achieved an improved quality of life following surgery (p<0.01. From the results of this study, a profile of South African patients with improved quality of life was identified. They are: Men, married, annual income > R50 000 (US $8 000, who had a normal sex-life prior to the operation.  They differ significantly from the group without an improved quality of life in the following aspects: they spend more hours participating in sport at school (p=0

  7. Disease prediction models and operational readiness.

    Directory of Open Access Journals (Sweden)

    Courtney D Corley

    Full Text Available The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. We define a disease event to be a biological event with focus on the One Health paradigm. These events are characterized by evidence of infection and or disease condition. We reviewed models that attempted to predict a disease event, not merely its transmission dynamics and we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011. We searched commercial and government databases and harvested Google search results for eligible models, using terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche modeling. After removal of duplications and extraneous material, a core collection of 6,524 items was established, and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. As a result, we systematically reviewed 44 papers, and the results are presented in this analysis. We identified 44 models, classified as one or more of the following: event prediction (4, spatial (26, ecological niche (28, diagnostic or clinical (6, spread or response (9, and reviews (3. The model parameters (e.g., etiology, climatic, spatial, cultural and data sources (e.g., remote sensing, non-governmental organizations, expert opinion, epidemiological were recorded and reviewed. A component of this review is the identification of verification and validation (V&V methods applied to each model, if any V&V method was reported. All models were classified as either having undergone Some Verification or Validation method, or No Verification or Validation. We close by outlining an initial set of operational readiness level guidelines for disease prediction models based upon established Technology

  8. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...

  9. Do the urolithiasis scoring systems predict the success of percutaneous nephrolithotomy in cases with anatomical abnormalities?

    Science.gov (United States)

    Kocaaslan, Ramazan; Tepeler, Abdulkadir; Buldu, Ibrahim; Tosun, Muhammed; Utangac, Mehmet Mazhar; Karakan, Tolga; Ozyuvali, Ekrem; Hatipoglu, Namik Kemal; Unsal, Ali; Sarica, Kemal

    2016-07-12

    The objective of this study is to assess the utility of the Guy, S.T.O.N.E., and CROES nephrolithometry scoring systems (SS), and compare the capability of each system to predict percutaneous nephrolithotomy (PNL) outcome in patients with anatomical abnormalities. We retrospectively collected medical records of patients with anatomical abnormalities who underwent PNL for the treatment of renal calculi by experienced surgical teams in four referral centers. All of the patients were graded by a single observer from each department based on preoperative computed tomography images using each SS. Patient demographics and outcomes were compared according to the complexity of the procedure as graded by each scoring system. A total of 137 cases with anatomical abnormalities [horseshoe kidney (n = 46), malrotation (n = 33), kypho and/or scoliosis (n = 31) and ectopic kidney (n = 27)] were assessed retrospectively. The mean stone burden, number, and density were 708.5 mm(2), 1.7, and 791.8 HU, respectively. The mean procedure, fluoroscopy, and hospitalization times were 75.2 ± 35.3 min, 133.4 ± 92.3 s, and 3.5 ± 2.1 days, respectively. Stone-free status was achieved in 106 cases (77.4 %). A total of 17 (13.6 %) complications occurred postoperatively. The mean scores were 2.7, 7.2, and 219.1, for the Guy, S.T.O.N.E., and CROES systems, respectively. CROES score was the independent predictor of PNL success in cases with anatomical abnormalities [p: 0.001, OR 1.01, (95 % CI 1005-1021)]. The CROES scoring system is well correlated with the success of PNL in cases with anatomical abnormalities; the S.T.O.N.E. and Guy scoring systems failed to predict the outcomes of PNL in this specific patient population.

  10. Startle response during smoking and 24 h after withdrawal predicts successful smoking cessation.

    Science.gov (United States)

    Postma, P; Kumari, V; Sharma, T; Hines, M; Gray, J A

    2001-07-01

    The startle response is thought to reflect changes in attentional processes in humans. The startle response shows a number of forms of plasticity, of which prepulse inhibition (PPI) refers to the attenuation of the startle response to a strong sensory stimulus (pulse), when such a pulse is preceded by a stimulus of lower intensity (prepulse). Recent studies have shown that nicotine modulates startle and PPI of the startle reflex in humans and animals. The present study examined individual differences in cognitive benefits obtained from smoking as indexed by startle response and PPI. We investigated, using a within-subjects design, the effects of cigarette smoking via a comparison of baseline and withdrawal measures of startle and PPI in 18 subjects wishing to quit cigarette smoking. The relapse of five of these subjects enabled a between-group comparison of these measures with the successful quitters. Startle and PPI were measured on three separate occasions: before quitting, 24 h after quitting and 1 month after quitting. The presence of a high startle response amplitude while subjects were still engaged in their normal smoking patterns (baseline) and the occurrence of a significant drop of startle amplitude in withdrawal relative to baseline factors were found to be predictive of an individual's ability to quit smoking. Changes in PPI were found to reflect these changes in startle amplitude. The observed response patterns are discussed in terms of individual differences in commitment to quitting and self-dosing to manipulate attentional mechanisms as measured by the acoustic startle response. Furthermore, it is suggested that these specific response profiles may be predictive of the ability to quit smoking.

  11. An exploratory analysis of the model for understanding success in quality.

    Science.gov (United States)

    Kaplan, Heather C; Froehle, Craig M; Cassedy, Amy; Provost, Lloyd P; Margolis, Peter A

    2013-01-01

    Experience suggests that differences in context produce variability in the effectiveness of quality improvement (QI) interventions. However, little is known about which contextual factors affect success or how they exert influence. Using the Model for Understanding Success in Quality (MUSIQ), we perform exploratory quantitative tests of the role of context in QI success. We used a cross-sectional design to survey individuals participating in QI projects in three settings: a pediatric hospital, hospitals affiliated with a state QI collaborative, and organizations sponsoring participants in an improvement advisor training program. Individuals participating in QI projects completed a questionnaire assessing contextual factors included in MUSIQ and measures of perceived success. Path analysis was used to test the direct, indirect, and total effects of context variables on QI success as hypothesized in MUSIQ. In the 74 projects studied, most contextual factors in MUSIQ were found to be significantly related to at least one QI project performance outcome. Contextual factors exhibiting significant effects on two measures of perceived QI success included resource availability, QI team leadership, team QI skills, microsystem motivation, microsystem QI culture, and microsystem QI capability. There was weaker evidence for effects of senior leader project sponsors, organizational QI culture, QI team decision-making, and microsystem QI leadership. These initial tests add to the validity of MUSIQ as a tool for identifying which contextual factors affect improvement success and understanding how they exert influence. Using MUSIQ, managers and QI practitioners can begin to identify aspects of context that must be addressed before or during the execution of QI projects and plan strategies to modify context for increased success. Additional work by QI researchers to improve the theory, refine measurement approaches, and validate MUSIQ as a predictive tool in a wider range of QI

  12. Modeling Forest Succession among Ecological Land Units in Northern Minnesota

    Directory of Open Access Journals (Sweden)

    George Host

    1998-12-01

    Full Text Available Field and modeling studies were used to quantify potential successional pathways among fine-scale ecological classification units within two geomorphic regions of north-central Minnesota. Soil and overstory data were collected on plots stratified across low-relief ground moraines and undulating sand dunes. Each geomorphic feature was sampled across gradients of topography or soil texture. Overstory conditions were sampled using five variable-radius point samples per plot; soil samples were analyzed for carbon and nitrogen content. Climatic, forest composition, and soil data were used to parameterize the sample plots for use with LINKAGES, a forest growth model that simulates changes in composition and soil characteristics over time. Forest composition and soil properties varied within and among geomorphic features. LINKAGES simulations were using "bare ground" and the current overstory as starting conditions. Northern hardwoods or pines dominated the late-successional communities of morainal and dune landforms, respectively. The morainal landforms were dominated by yellow birch and sugar maple; yellow birch reached its maximum abundance in intermediate landscape positions. On the dune sites, pine was most abundant in drier landscape positions, with white spruce increasing in abundance with increasing soil moisture and N content. The differences in measured soil properties and predicted late-successional composition indicate that ecological land units incorporate some of the key variables that govern forest composition and structure. They further show the value of ecological classification and modeling for developing forest management strategies that incorporate the spatial and temporal dynamics of forest ecosystems.

  13. ENSO Prediction using Vector Autoregressive Models

    Science.gov (United States)

    Chapman, D. R.; Cane, M. A.; Henderson, N.; Lee, D.; Chen, C.

    2013-12-01

    A recent comparison (Barnston et al, 2012 BAMS) shows the ENSO forecasting skill of dynamical models now exceeds that of statistical models, but the best statistical models are comparable to all but the very best dynamical models. In this comparison the leading statistical model is the one based on the Empirical Model Reduction (EMR) method. Here we report on experiments with multilevel Vector Autoregressive models using only sea surface temperatures (SSTs) as predictors. VAR(L) models generalizes Linear Inverse Models (LIM), which are a VAR(1) method, as well as multilevel univariate autoregressive models. Optimal forecast skill is achieved using 12 to 14 months of prior state information (i.e 12-14 levels), which allows SSTs alone to capture the effects of other variables such as heat content as well as seasonality. The use of multiple levels allows the model advancing one month at a time to perform at least as well for a 6 month forecast as a model constructed to explicitly forecast 6 months ahead. We infer that the multilevel model has fully captured the linear dynamics (cf. Penland and Magorian, 1993 J. Climate). Finally, while VAR(L) is equivalent to L-level EMR, we show in a 150 year cross validated assessment that we can increase forecast skill by improving on the EMR initialization procedure. The greatest benefit of this change is in allowing the prediction to make effective use of information over many more months.

  14. Electrostatic ion thrusters - towards predictive modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)

    2014-02-15

    The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  15. Gas explosion prediction using CFD models

    Energy Technology Data Exchange (ETDEWEB)

    Niemann-Delius, C.; Okafor, E. [RWTH Aachen Univ. (Germany); Buhrow, C. [TU Bergakademie Freiberg Univ. (Germany)

    2006-07-15

    A number of CFD models are currently available to model gaseous explosions in complex geometries. Some of these tools allow the representation of complex environments within hydrocarbon production plants. In certain explosion scenarios, a correction is usually made for the presence of buildings and other complexities by using crude approximations to obtain realistic estimates of explosion behaviour as can be found when predicting the strength of blast waves resulting from initial explosions. With the advance of computational technology, and greater availability of computing power, computational fluid dynamics (CFD) tools are becoming increasingly available for solving such a wide range of explosion problems. A CFD-based explosion code - FLACS can, for instance, be confidently used to understand the impact of blast overpressures in a plant environment consisting of obstacles such as buildings, structures, and pipes. With its porosity concept representing geometry details smaller than the grid, FLACS can represent geometry well, even when using coarse grid resolutions. The performance of FLACS has been evaluated using a wide range of field data. In the present paper, the concept of computational fluid dynamics (CFD) and its application to gas explosion prediction is presented. Furthermore, the predictive capabilities of CFD-based gaseous explosion simulators are demonstrated using FLACS. Details about the FLACS-code, some extensions made to FLACS, model validation exercises, application, and some results from blast load prediction within an industrial facility are presented. (orig.)

  16. Genetic models of homosexuality: generating testable predictions.

    Science.gov (United States)

    Gavrilets, Sergey; Rice, William R

    2006-12-22

    Homosexuality is a common occurrence in humans and other species, yet its genetic and evolutionary basis is poorly understood. Here, we formulate and study a series of simple mathematical models for the purpose of predicting empirical patterns that can be used to determine the form of selection that leads to polymorphism of genes influencing homosexuality. Specifically, we develop theory to make contrasting predictions about the genetic characteristics of genes influencing homosexuality including: (i) chromosomal location, (ii) dominance among segregating alleles and (iii) effect sizes that distinguish between the two major models for their polymorphism: the overdominance and sexual antagonism models. We conclude that the measurement of the genetic characteristics of quantitative trait loci (QTLs) found in genomic screens for genes influencing homosexuality can be highly informative in resolving the form of natural selection maintaining their polymorphism.

  17. Characterizing Attention with Predictive Network Models.

    Science.gov (United States)

    Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M

    2017-04-01

    Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Predicting Successful Pulmonary Vein Isolation In Patients With Atrial Fibrillation By Brain Natriuretic Peptide Plasma Levels

    Directory of Open Access Journals (Sweden)

    Dong-In Shin

    2009-09-01

    Full Text Available Background: Catheter ablation for atrial fibrillation is a clinically established treatment by now while success rate varies between 60% and 85%. Interventional treatment of atrial fibrillation is still a challenging technique associated with a long procedure time and risk of major complications in up to 6 % of treated patients. The aim of this study was to investigate the predictive value of plasma brain natriuretic peptide (BNP in patients undergoing pulmonary vein isolation concerning stable sinus rhythm after ablation.Methods: In 68 consecutive patients with atrial fibrillation (AF and normal left ventricular ejection fraction, BNP was measured at baseline before pulmonary vein isolation (PVI. All patients received a 7-days-holter monitoring 3 months after radiofrequency (RF ablation in order to detect recurrent AF episodes. Results: 48 patients with paroxysmal and 20 patients with persistent AF were enrolled. Baseline BNP was significantly higher in patients with persistent AF compared to patients with paroxysmal AF (145,5 pg/ml vs. 84,4 pg/ml; p<0,05. 3 months after PVI 38 patients (79,1% with paroxysmal AF had a stable sinus rhythm documented on 7-days-holter monitoring, where as in 10 patients (20,9% AF episodes were detected. Patients with a successful PVI showed significantly lower BNP plasma levels at baseline compared to patients with AF recurrrence (68,7 pg/ml vs. 144,1 pg/ml; p<0,05. In patients with persistent AF 55% (11 cases had no recurrence of AF at 3 months 7-days holter and in 9 patients (45% AF recurred. BNP plasma levels at baseline were lower in patients with stable sinusrhythm after 3 months compared to the group of recurrent AF (105,8 pg/ml vs. 193,3 pg/ml; p=0,11. Conclusion: Patients with AF and low preprocedural BNP plasma levels showed a better outcome after PVI. Thus BNP may be helpful in patient selection for a successful treatment of AF by PVI.

  19. A Study On Distributed Model Predictive Consensus

    CERN Document Server

    Keviczky, Tamas

    2008-01-01

    We investigate convergence properties of a proposed distributed model predictive control (DMPC) scheme, where agents negotiate to compute an optimal consensus point using an incremental subgradient method based on primal decomposition as described in Johansson et al. [2006, 2007]. The objective of the distributed control strategy is to agree upon and achieve an optimal common output value for a group of agents in the presence of constraints on the agent dynamics using local predictive controllers. Stability analysis using a receding horizon implementation of the distributed optimal consensus scheme is performed. Conditions are given under which convergence can be obtained even if the negotiations do not reach full consensus.

  20. Formability prediction for AHSS materials using damage models

    Science.gov (United States)

    Amaral, R.; Santos, Abel D.; José, César de Sá; Miranda, Sara

    2017-05-01

    Advanced high strength steels (AHSS) are seeing an increased use, mostly due to lightweight design in automobile industry and strict regulations on safety and greenhouse gases emissions. However, the use of these materials, characterized by a high strength to weight ratio, stiffness and high work hardening at early stages of plastic deformation, have imposed many challenges in sheet metal industry, mainly their low formability and different behaviour, when compared to traditional steels, which may represent a defying task, both to obtain a successful component and also when using numerical simulation to predict material behaviour and its fracture limits. Although numerical prediction of critical strains in sheet metal forming processes is still very often based on the classic forming limit diagrams, alternative approaches can use damage models, which are based on stress states to predict failure during the forming process and they can be classified as empirical, physics based and phenomenological models. In the present paper a comparative analysis of different ductile damage models is carried out, in order numerically evaluate two isotropic coupled damage models proposed by Johnson-Cook and Gurson-Tvergaard-Needleman (GTN), each of them corresponding to the first two previous group classification. Finite element analysis is used considering these damage mechanics approaches and the obtained results are compared with experimental Nakajima tests, thus being possible to evaluate and validate the ability to predict damage and formability limits for previous defined approaches.

  1. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    R. G. SILVA

    1999-03-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  2. Characteristics of successful opinion leaders in a bounded confidence model

    Science.gov (United States)

    Chen, Shuwei; Glass, David H.; McCartney, Mark

    2016-05-01

    This paper analyses the impact of competing opinion leaders on attracting followers in a social group based on a bounded confidence model in terms of four characteristics: reputation, stubbornness, appeal and extremeness. In the model, reputation differs among leaders and normal agents based on the weights assigned to them, stubbornness of leaders is reflected by their confidence towards normal agents, appeal of the leaders is represented by the confidence of followers towards them, and extremeness is captured by the opinion values of leaders. Simulations show that increasing reputation, stubbornness or extremeness makes it more difficult for the group to achieve consensus, but increasing the appeal will make it easier. The results demonstrate that successful opinion leaders should generally be less stubborn, have greater appeal and be less extreme in order to attract more followers in a competing environment. Furthermore, the number of followers can be very sensitive to small changes in these characteristics. On the other hand, reputation has a more complicated impact: higher reputation helps the leader to attract more followers when the group bound of confidence is high, but can hinder the leader from attracting followers when the group bound of confidence is low.

  3. Business Models for Successfully Maintaining Games for Health.

    Science.gov (United States)

    Baranowski, Moderator Tom; Isaac, Participants Fikry; Ashford, Chris; Goldman, Ron; Lenihan, David J; Poole, Brent; Buday, Richard; van Rijswijk, Jurriaan

    2013-04-01

    Videogames for health provide innovative, exciting, and possibly highly effective new media for helping players change their behaviors or otherwise benefit their health. Getting the right videogames into the hands of players who can benefit most in a way that pays for the continued innovation and creation of such games is a current challenge. Entertainment videogame companies, which create games primarily to enhance players' enjoyment, have used the general business marketplace (e.g., online stores, walk-in stores, app stores) to deliver their products directly to consumers and earn enough capital to invest in making new products. No one believes, however, that enough kids or adults would use the general business marketplace to purchase games for health in sufficient volume to provide the down payment for the innovation and creation of new games for health. A successful business model is critical to the financial future of games for health. We asked members of our Editorial Board who are in health-related companies (Fikry Isaac, MD, MPH), in several game development companies (Chris Ashford, Ron Goldman, David J. Lenihan, Brent Poole, and Richard Buday, FAIA), and the head of the Games for Health Europe Foundation (Jurriaan van Rijswijk, MSc) to address questions in a roundtable about the current and possible future business models for games for health.

  4. Pupil size signals novelty and predicts later retrieval success for declarative memories of natural scenes.

    Science.gov (United States)

    Naber, Marnix; Frässle, Stefan; Rutishauser, Ueli; Einhäuser, Wolfgang

    2013-02-08

    Declarative memories of personal experiences are a key factor in defining oneself as an individual, which becomes particularly evident when this capability is impaired. Assessing the physiological mechanisms of human declarative memory is typically restricted to patients with specific lesions and requires invasive brain access or functional imaging. We investigated whether the pupil, an accessible physiological measure, can be utilized to probe memories for complex natural visual scenes. During memory encoding, scenes that were later remembered elicited a stronger pupil constriction compared to scenes that were later forgotten. Thus, pupil size predicts success or failure of memory formation. In contrast, novel scenes elicited stronger pupil constriction than familiar scenes during retrieval. When viewing previously memorized scenes, those that were forgotten (misjudged as novel) still elicited stronger pupil constrictions than those correctly judged as familiar. Furthermore, pupil constriction was influenced more strongly if images were judged with high confidence. Thus, we propose that pupil constriction can serve as a marker of novelty. Since stimulus novelty modulates the efficacy of memory formation, our pupil measurements during learning indicate that the later forgotten images were perceived as less novel than the later remembered pictures. Taken together, our data provide evidence that pupil constriction is a physiological correlate of a neural novelty signal during formation and retrieval of declarative memories for complex, natural scenes.

  5. Reward type and behavioural patterns predict dogs’ success in a delay of gratification paradigm

    Science.gov (United States)

    Brucks, Désirée; Soliani, Matteo; Range, Friederike; Marshall-Pescini, Sarah

    2017-01-01

    Inhibiting an immediate behaviour in favour of an alternative but more advantageous behaviour has been linked to individual success in life, especially in humans. Dogs, which have been living in the human environment for thousands of years, are exposed to daily situations that require inhibition different in context from other non-domesticated species. One task regularly used to study inhibitory control is the delay of gratification task, which requires individuals to choose between an immediate option of lower value and a delayed option of higher value. We tested sixteen dogs in a non-social delay of gratification task, conducting two different conditions: a quality and a quantity condition. While the majority of dogs failed to wait for more than 10 s, some dogs tolerated delays of up to 140 s, while one dog waited for 15 minutes. Moreover, dogs had more difficulties to wait if the reward increased in terms of quantity than quality. Interestingly, dogs were able to anticipate the delay duration and some dogs developed behavioural patterns that predicted waiting, which seems similar in some respects to ‘coping-strategies’ found in children, chimpanzees and parrots. Our results indicate that strategies to cope with impulsivity seem to be consistent and present across animal taxa. PMID:28272409

  6. Performance model to predict overall defect density

    Directory of Open Access Journals (Sweden)

    J Venkatesh

    2012-08-01

    Full Text Available Management by metrics is the expectation from the IT service providers to stay as a differentiator. Given a project, the associated parameters and dynamics, the behaviour and outcome need to be predicted. There is lot of focus on the end state and in minimizing defect leakage as much as possible. In most of the cases, the actions taken are re-active. It is too late in the life cycle. Root cause analysis and corrective actions can be implemented only to the benefit of the next project. The focus has to shift left, towards the execution phase than waiting for lessons to be learnt post the implementation. How do we pro-actively predict defect metrics and have a preventive action plan in place. This paper illustrates the process performance model to predict overall defect density based on data from projects in an organization.

  7. Neuro-fuzzy modeling in bankruptcy prediction

    Directory of Open Access Journals (Sweden)

    Vlachos D.

    2003-01-01

    Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

  8. Pressure prediction model for compression garment design.

    Science.gov (United States)

    Leung, W Y; Yuen, D W; Ng, Sun Pui; Shi, S Q

    2010-01-01

    Based on the application of Laplace's law to compression garments, an equation for predicting garment pressure, incorporating the body circumference, the cross-sectional area of fabric, applied strain (as a function of reduction factor), and its corresponding Young's modulus, is developed. Design procedures are presented to predict garment pressure using the aforementioned parameters for clinical applications. Compression garments have been widely used in treating burning scars. Fabricating a compression garment with a required pressure is important in the healing process. A systematic and scientific design method can enable the occupational therapist and compression garments' manufacturer to custom-make a compression garment with a specific pressure. The objectives of this study are 1) to develop a pressure prediction model incorporating different design factors to estimate the pressure exerted by the compression garments before fabrication; and 2) to propose more design procedures in clinical applications. Three kinds of fabrics cut at different bias angles were tested under uniaxial tension, as were samples made in a double-layered structure. Sets of nonlinear force-extension data were obtained for calculating the predicted pressure. Using the value at 0° bias angle as reference, the Young's modulus can vary by as much as 29% for fabric type P11117, 43% for fabric type PN2170, and even 360% for fabric type AP85120 at a reduction factor of 20%. When comparing the predicted pressure calculated from the single-layered and double-layered fabrics, the double-layered construction provides a larger range of target pressure at a particular strain. The anisotropic and nonlinear behaviors of the fabrics have thus been determined. Compression garments can be methodically designed by the proposed analytical pressure prediction model.

  9. Statistical assessment of predictive modeling uncertainty

    Science.gov (United States)

    Barzaghi, Riccardo; Marotta, Anna Maria

    2017-04-01

    When the results of geophysical models are compared with data, the uncertainties of the model are typically disregarded. We propose a method for defining the uncertainty of a geophysical model based on a numerical procedure that estimates the empirical auto and cross-covariances of model-estimated quantities. These empirical values are then fitted by proper covariance functions and used to compute the covariance matrix associated with the model predictions. The method is tested using a geophysical finite element model in the Mediterranean region. Using a novel χ2 analysis in which both data and model uncertainties are taken into account, the model's estimated tectonic strain pattern due to the Africa-Eurasia convergence in the area that extends from the Calabrian Arc to the Alpine domain is compared with that estimated from GPS velocities while taking into account the model uncertainty through its covariance structure and the covariance of the GPS estimates. The results indicate that including the estimated model covariance in the testing procedure leads to lower observed χ2 values that have better statistical significance and might help a sharper identification of the best-fitting geophysical models.

  10. Seasonal Predictability in a Model Atmosphere.

    Science.gov (United States)

    Lin, Hai

    2001-07-01

    The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.

  11. Development of an Electronic Portfolio System Success Model: An Information Systems Approach

    Science.gov (United States)

    Balaban, Igor; Mu, Enrique; Divjak, Blazenka

    2013-01-01

    This research has two main goals: to develop an instrument for assessing Electronic Portfolio (ePortfolio) success and to build a corresponding ePortfolio success model using DeLone and McLean's information systems success model as the theoretical framework. For this purpose, we developed an ePortfolio success measurement instrument and structural…

  12. Contact prediction in protein modeling: Scoring, folding and refinement of coarse-grained models

    Directory of Open Access Journals (Sweden)

    Kolinski Andrzej

    2008-08-01

    Full Text Available Abstract Background Several different methods for contact prediction succeeded within the Sixth Critical Assessment of Techniques for Protein Structure Prediction (CASP6. The most relevant were non-local contact predictions for targets from the most difficult categories: fold recognition-analogy and new fold. Such contacts could provide valuable structural information in case a template structure cannot be found in the PDB. Results We described comprehensive tests of the effectiveness of contact data in various aspects of de novo modeling with CABS, an algorithm which was used successfully in CASP6 by the Kolinski-Bujnicki group. We used the predicted contacts in a simple scoring function for the post-simulation ranking of protein models and as a soft bias in the folding simulations and in the fold-refinement procedure. The latter approach turned out to be the most successful. The CABS force field used in the Replica Exchange Monte Carlo simulations cooperated with the true contacts and discriminated the false ones, which resulted in an improvement of the majority of Kolinski-Bujnicki's protein models. In the modeling we tested different sets of predicted contact data submitted to the CASP6 server. According to our results, the best performing were the contacts with the accuracy balanced with the coverage, obtained either from the best two predictors only or by a consensus from as many predictors as possible. Conclusion Our tests have shown that theoretically predicted contacts can be very beneficial for protein structure prediction. Depending on the protein modeling method, a contact data set applied should be prepared with differently balanced coverage and accuracy of predicted contacts. Namely, high coverage of contact data is important for the model ranking and high accuracy for the folding simulations.

  13. Robust predictive modelling of water pollution using biomarker data.

    Science.gov (United States)

    Budka, Marcin; Gabrys, Bogdan; Ravagnan, Elisa

    2010-05-01

    This paper describes the methodology of building a predictive model for the purpose of marine pollution monitoring, based on low quality biomarker data. A step-by-step, systematic data analysis approach is presented, resulting in design of a purely data-driven model, able to accurately discriminate between various coastal water pollution levels. The environmental scientists often try to apply various machine learning techniques to their data without much success, mostly because of the lack of experience with different methods and required 'under the hood' knowledge. Thus this paper is a result of a collaboration between the machine learning and environmental science communities, presenting a predictive model development workflow, as well as discussing and addressing potential pitfalls and difficulties. The novelty of the modelling approach presented lays in successful application of machine learning techniques to high dimensional, incomplete biomarker data, which to our knowledge has not been done before and is the result of close collaboration between machine learning and environmental science communities.

  14. A kinetic model for predicting biodegradation.

    Science.gov (United States)

    Dimitrov, S; Pavlov, T; Nedelcheva, D; Reuschenbach, P; Silvani, M; Bias, R; Comber, M; Low, L; Lee, C; Parkerton, T; Mekenyan, O

    2007-01-01

    Biodegradation plays a key role in the environmental risk assessment of organic chemicals. The need to assess biodegradability of a chemical for regulatory purposes supports the development of a model for predicting the extent of biodegradation at different time frames, in particular the extent of ultimate biodegradation within a '10 day window' criterion as well as estimating biodegradation half-lives. Conceptually this implies expressing the rate of catabolic transformations as a function of time. An attempt to correlate the kinetics of biodegradation with molecular structure of chemicals is presented. A simplified biodegradation kinetic model was formulated by combining the probabilistic approach of the original formulation of the CATABOL model with the assumption of first order kinetics of catabolic transformations. Nonlinear regression analysis was used to fit the model parameters to OECD 301F biodegradation kinetic data for a set of 208 chemicals. The new model allows the prediction of biodegradation multi-pathways, primary and ultimate half-lives and simulation of related kinetic biodegradation parameters such as biological oxygen demand (BOD), carbon dioxide production, and the nature and amount of metabolites as a function of time. The model may also be used for evaluating the OECD ready biodegradability potential of a chemical within the '10-day window' criterion.

  15. Disease Prediction Models and Operational Readiness

    Energy Technology Data Exchange (ETDEWEB)

    Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.

    2014-03-19

    INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the

  16. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  17. Predictive Modeling in Actinide Chemistry and Catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-16

    These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.

  18. Can resource-use traits predict native vs. exotic plant success in carbon amended soils?

    Science.gov (United States)

    Steers, Robert J; Funk, Jennifer L; Allen, Edith B

    2011-06-01

    Productivity in desert ecosystems is primarily limited by water followed by nitrogen availability. In the deserts of southern California, nitrogen additions have increased invasive annual plant abundance. Similar findings from other ecosystems have led to a general acceptance that invasive plants, especially annual grasses, are nitrophilous. Consequently, reductions of soil nitrogen via carbon amendments have been conducted by many researchers in a variety of ecosystems in order to disproportionately lower invasive species abundance, but with mixed success. Recent studies suggest that resource-use traits may predict the efficacy of such resource manipulations; however, this theory remains largely untested. We report findings from a carbon amendment experiment that utilized two levels of sucrose additions that were aimed at achieving soil carbon to nitrogen ratios of 50:1 and 100:1 in labile sources. Carbon amendments were applied once each year, for three years, corresponding with the first large precipitation event of each wet season. Plant functional traits measured on the three invasive and 11 native herbaceous species that were most common at the study site showed that exotic and native species did not differ in traits associated with nitrogen use. In fact, plant abundance measures such as density, cover, and biomass showed that carbon amendments were capable of decreasing both native and invasive species. We found that early-germinating species were the most impacted by decreased soil nitrogen resulting from amendments. Because invasive annuals typically germinate earlier and exhibit a rapid phenology compared to most natives, these species are expected to be more competitive than native annuals yet more susceptible to early-season carbon amendments. However, desert annual communities can exhibit high interannual variability in species composition and abundance. Therefore, the relative abundance of native and invasive species at the time of application is

  19. Probabilistic prediction models for aggregate quarry siting

    Science.gov (United States)

    Robinson, G.R.; Larkins, P.M.

    2007-01-01

    Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.

  20. Predicting Footbridge Response using Stochastic Load Models

    DEFF Research Database (Denmark)

    Pedersen, Lars; Frier, Christian

    2013-01-01

    Walking parameters such as step frequency, pedestrian mass, dynamic load factor, etc. are basically stochastic, although it is quite common to adapt deterministic models for these parameters. The present paper considers a stochastic approach to modeling the action of pedestrians, but when doing s...... as it pinpoints which decisions to be concerned about when the goal is to predict footbridge response. The studies involve estimating footbridge responses using Monte-Carlo simulations and focus is on estimating vertical structural response to single person loading....

  1. Nonconvex Model Predictive Control for Commercial Refrigeration

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F.S.; Jørgensen, John Bagterp

    2013-01-01

    is to minimize the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost...... the iterations, which is more than fast enough to run in real-time. We demonstrate our method on a realistic model, with a full year simulation and 15 minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost...

  2. Predicting and understanding forest dynamics using a simple tractable model.

    Science.gov (United States)

    Purves, Drew W; Lichstein, Jeremy W; Strigul, Nikolay; Pacala, Stephen W

    2008-11-04

    The perfect-plasticity approximation (PPA) is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the eight most common species on each of four soil types in the US Lake states (Michigan, Wisconsin, and Minnesota) by using short-term (predictions to chronosequences of stand development. Predictions for the timing and magnitude of basal area dynamics and ecological succession on each soil were accurate, and predictions for the diameter distribution of 100-year-old stands were correct in form and slope. For a given species, the PPA provides analytical metrics for early-successional performance (H(20), height of a 20-year-old open-grown tree) and late-successional performance (Z*, equilibrium canopy height in monoculture). These metrics predicted which species were early or late successional on each soil type. Decomposing Z* showed that (i) succession is driven both by superior understory performance and superior canopy performance of late-successional species, and (ii) performance differences primarily reflect differences in mortality rather than growth. The predicted late-successional dominants matched chronosequences on xeromesic (Quercus rubra) and mesic (codominance by Acer rubrum and Acer saccharum) soil. On hydromesic and hydric soils, the literature reports that the current dominant species in old stands (Thuja occidentalis) is now failing to regenerate. Consistent with this, the PPA predicted that, on these soils, stands are now succeeding to dominance by other late-successional species (e.g., Fraxinus nigra, A. rubrum).

  3. Prediction models in in vitro fertilization; where are we? A mini review

    Directory of Open Access Journals (Sweden)

    Laura van Loendersloot

    2014-05-01

    Full Text Available Since the introduction of in vitro fertilization (IVF in 1978, over five million babies have been born worldwide using IVF. Contrary to the perception of many, IVF does not guarantee success. Almost 50% of couples that start IVF will remain childless, even if they undergo multiple IVF cycles. The decision to start or pursue with IVF is challenging due to the high cost, the burden of the treatment, and the uncertain outcome. In optimal counseling on chances of a pregnancy with IVF, prediction models may play a role, since doctors are not able to correctly predict pregnancy chances. There are three phases of prediction model development: model derivation, model validation, and impact analysis. This review provides an overview on predictive factors in IVF, the available prediction models in IVF and provides key principles that can be used to critically appraise the literature on prediction models in IVF. We will address these points by the three phases of model development.

  4. Merging imagery and models for river current prediction

    Science.gov (United States)

    Blain, Cheryl Ann; Linzell, Robert S.; McKay, Paul

    2011-06-01

    To meet the challenge of operating in river environments with denied access and to improve the riverine intelligence available to the warfighter, advanced high resolution river circulation models are combined with remote sensing feature extraction algorithms to produce a predictive capability for currents and water levels in rivers where a priori knowledge of the river environment is limited. A River Simulation Tool (RST) is developed to facilitate the rapid configuration of a river model. River geometry is extracted from the automated processing of available imagery while minimal user input is collected to complete the parameter and forcing specifications necessary to configure a river model. Contingencies within the RST accommodate missing data such as a lack of water depth information and allow for ensemble computations. Successful application of the RST to river environments is demonstrated for the Snohomish River, WA. Modeled currents compare favorably to in-situ currents reinforcing the value of the developed approach.

  5. Constructing predictive models of human running.

    Science.gov (United States)

    Maus, Horst-Moritz; Revzen, Shai; Guckenheimer, John; Ludwig, Christian; Reger, Johann; Seyfarth, Andre

    2015-02-06

    Running is an essential mode of human locomotion, during which ballistic aerial phases alternate with phases when a single foot contacts the ground. The spring-loaded inverted pendulum (SLIP) provides a starting point for modelling running, and generates ground reaction forces that resemble those of the centre of mass (CoM) of a human runner. Here, we show that while SLIP reproduces within-step kinematics of the CoM in three dimensions, it fails to reproduce stability and predict future motions. We construct SLIP control models using data-driven Floquet analysis, and show how these models may be used to obtain predictive models of human running with six additional states comprising the position and velocity of the swing-leg ankle. Our methods are general, and may be applied to any rhythmic physical system. We provide an approach for identifying an event-driven linear controller that approximates an observed stabilization strategy, and for producing a reduced-state model which closely recovers the observed dynamics. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  6. Statistical Seasonal Sea Surface based Prediction Model

    Science.gov (United States)

    Suarez, Roberto; Rodriguez-Fonseca, Belen; Diouf, Ibrahima

    2014-05-01

    The interannual variability of the sea surface temperature (SST) plays a key role in the strongly seasonal rainfall regime on the West African region. The predictability of the seasonal cycle of rainfall is a field widely discussed by the scientific community, with results that fail to be satisfactory due to the difficulty of dynamical models to reproduce the behavior of the Inter Tropical Convergence Zone (ITCZ). To tackle this problem, a statistical model based on oceanic predictors has been developed at the Universidad Complutense of Madrid (UCM) with the aim to complement and enhance the predictability of the West African Monsoon (WAM) as an alternative to the coupled models. The model, called S4CAST (SST-based Statistical Seasonal Forecast) is based on discriminant analysis techniques, specifically the Maximum Covariance Analysis (MCA) and Canonical Correlation Analysis (CCA). Beyond the application of the model to the prediciton of rainfall in West Africa, its use extends to a range of different oceanic, atmospheric and helth related parameters influenced by the temperature of the sea surface as a defining factor of variability.

  7. Algorithms and Software for Predictive and Perceptual Modeling of Speech

    CERN Document Server

    Atti, Venkatraman

    2010-01-01

    From the early pulse code modulation-based coders to some of the recent multi-rate wideband speech coding standards, the area of speech coding made several significant strides with an objective to attain high quality of speech at the lowest possible bit rate. This book presents some of the recent advances in linear prediction (LP)-based speech analysis that employ perceptual models for narrow- and wide-band speech coding. The LP analysis-synthesis framework has been successful for speech coding because it fits well the source-system paradigm for speech synthesis. Limitations associated with th

  8. A Computationally Efficient Aggregation Optimization Strategy of Model Predictive Control

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on-line computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs. This paper develops an aggregation optimization strategy for MPC that can improve the computational efficiency of MPC. For the regulation problem, an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action.

  9. Improved prediction of genetic predisposition to psychiatric disorders using genomic feature best linear unbiased prediction models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Demontis, Ditte; Børglum, Anders

    Introduction: Accurate prediction of unobserved phenotypes from observed genotypes is essential for the success in predicting disease risk from genotypes. However, the performance is somewhat limited. Genomic feature best linear unbiased prediction (GFBLUP) models separate the total genomic...... is enriched for causal variants. Here we apply the GFBLUP model to a small schizophrenia case-control study to test the promise of this model on psychiatric disorders, and hypothesize that the performance will be increased when applying the model to a larger ADHD case-control study if the genomic feature...... contains the causal variants. Materials and Methods: The schizophrenia study consisted of 882 controls and 888 schizophrenia cases genotyped for 520,000 SNPs. The ADHD study contained 25,954 controls and 16,663 ADHD cases with 8,4 million imputed genotypes. Results: The predictive ability for schizophrenia...

  10. Successful N{sub 2} leptogenesis with flavour coupling effects in realistic unified models

    Energy Technology Data Exchange (ETDEWEB)

    Bari, Pasquale Di; King, Stephen F. [Department of Physics and Astronomy, University of Southampton,Highfield, Southampton SO17 1BJ (United Kingdom)

    2015-10-02

    In realistic unified models involving so-called SO(10)-inspired patterns of Dirac and heavy right-handed (RH) neutrino masses, the lightest right-handed neutrino N{sub 1} is too light to yield successful thermal leptogenesis, barring highly fine tuned solutions, while the second heaviest right-handed neutrino N{sub 2} is typically in the correct mass range. We show that flavour coupling effects in the Boltzmann equations may be crucial to the success of such N{sub 2} dominated leptogenesis, by helping to ensure that the flavour asymmetries produced at the N{sub 2} scale survive N{sub 1} washout. To illustrate these effects we focus on N{sub 2} dominated leptogenesis in an existing model, the A to Z of flavour with Pati-Salam, where the neutrino Dirac mass matrix may be equal to an up-type quark mass matrix and has a particular constrained structure. The numerical results, supported by analytical insight, show that in order to achieve successful N{sub 2} leptogenesis, consistent with neutrino phenomenology, requires a “flavour swap scenario” together with a less hierarchical pattern of RH neutrino masses than naively expected, at the expense of some mild fine-tuning. In the considered A to Z model neutrino masses are predicted to be normal ordered, with an atmospheric neutrino mixing angle well into the second octant and the Dirac phase δ≃20{sup ∘}, a set of predictions that will be tested in the next years in neutrino oscillation experiments. Flavour coupling effects may be relevant for other SO(10)-inspired unified models where N{sub 2} leptogenesis is necessary.

  11. Predictive models for population performance on real biological fitness landscapes.

    Science.gov (United States)

    Rowe, William; Wedge, David C; Platt, Mark; Kell, Douglas B; Knowles, Joshua

    2010-09-01

    Directed evolution, in addition to its principal application of obtaining novel biomolecules, offers significant potential as a vehicle for obtaining useful information about the topologies of biomolecular fitness landscapes. In this article, we make use of a special type of model of fitness landscapes-based on finite state machines-which can be inferred from directed evolution experiments. Importantly, the model is constructed only from the fitness data and phylogeny, not sequence or structural information, which is often absent. The model, called a landscape state machine (LSM), has already been used successfully in the evolutionary computation literature to model the landscapes of artificial optimization problems. Here, we use the method for the first time to simulate a biological fitness landscape based on experimental evaluation. We demonstrate in this study that LSMs are capable not only of representing the structure of model fitness landscapes such as NK-landscapes, but also the fitness landscape of real DNA oligomers binding to a protein (allophycocyanin), data we derived from experimental evaluations on microarrays. The LSMs prove adept at modelling the progress of evolution as a function of various controlling parameters, as validated by evaluations on the real landscapes. Specifically, the ability of the model to 'predict' optimal mutation rates and other parameters of the evolution is demonstrated. A modification to the standard LSM also proves accurate at predicting the effects of recombination on the evolution.

  12. Predictive modeling by the cerebellum improves proprioception.

    Science.gov (United States)

    Bhanpuri, Nasir H; Okamura, Allison M; Bastian, Amy J

    2013-09-04

    Because sensation is delayed, real-time movement control requires not just sensing, but also predicting limb position, a function hypothesized for the cerebellum. Such cerebellar predictions could contribute to perception of limb position (i.e., proprioception), particularly when a person actively moves the limb. Here we show that human cerebellar patients have proprioceptive deficits compared with controls during active movement, but not when the arm is moved passively. Furthermore, when healthy subjects move in a force field with unpredictable dynamics, they have active proprioceptive deficits similar to cerebellar patients. Therefore, muscle activity alone is likely insufficient to enhance proprioception and predictability (i.e., an internal model of the body and environment) is important for active movement to benefit proprioception. We conclude that cerebellar patients have an active proprioceptive deficit consistent with disrupted movement prediction rather than an inability to generally enhance peripheral proprioceptive signals during action and suggest that active proprioceptive deficits should be considered a fundamental cerebellar impairment of clinical importance.

  13. Social Media Success for Academic Knowledge Sharing in Indonesia (Conceptual Model Development)

    Science.gov (United States)

    Assegaff, Setiawan

    2017-04-01

    The aim of this study is to investigate how success is the social media as a tool for knowledge sharing among scholars in Indonesia. To evaluate the success of social media we develop a model base on Delone and McLeane IS Success Model. In this article, we would like discuss the process of developing the research model. In developing the model, we conduct literature review from knowledge management, social media and IS Success Model area from previous study. This study resulted in the social success model for academic knowledge sharing in Indonesia.

  14. Gamma-Ray Pulsars Models and Predictions

    CERN Document Server

    Harding, A K

    2001-01-01

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...

  15. Ground Motion Prediction Models for Caucasus Region

    Science.gov (United States)

    Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

    2016-04-01

    Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

  16. Modeling and Prediction of Krueger Device Noise

    Science.gov (United States)

    Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

    2016-01-01

    This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.

  17. A generative model for predicting terrorist incidents

    Science.gov (United States)

    Verma, Dinesh C.; Verma, Archit; Felmlee, Diane; Pearson, Gavin; Whitaker, Roger

    2017-05-01

    A major concern in coalition peace-support operations is the incidence of terrorist activity. In this paper, we propose a generative model for the occurrence of the terrorist incidents, and illustrate that an increase in diversity, as measured by the number of different social groups to which that an individual belongs, is inversely correlated with the likelihood of a terrorist incident in the society. A generative model is one that can predict the likelihood of events in new contexts, as opposed to statistical models which are used to predict the future incidents based on the history of the incidents in an existing context. Generative models can be useful in planning for persistent Information Surveillance and Reconnaissance (ISR) since they allow an estimation of regions in the theater of operation where terrorist incidents may arise, and thus can be used to better allocate the assignment and deployment of ISR assets. In this paper, we present a taxonomy of terrorist incidents, identify factors related to occurrence of terrorist incidents, and provide a mathematical analysis calculating the likelihood of occurrence of terrorist incidents in three common real-life scenarios arising in peace-keeping operations

  18. Africa's Great Green Wall Initiative: a model for restoration success

    Science.gov (United States)

    Berrahmouni, Nora; Sacande, Moctar

    2014-05-01

    The Great Green Wall for the Sahara and the Sahel Initiative was launched to address the increasing challenges of land degradation, desertification and drought, climate change, food insecurity and poverty in more than 20 countries. Restoration of agro-sylvo-pastoral landscapes and degraded lands is one of the priority interventions initiated, enabling the springing up of green nests of life. When complete, the Great Green Wall of Africa will reverse the seemingly unstoppable desertification and address the development of its drylands' inhabitant rural communities. Today's planting of modest seedlings will grow into vast mosaics of forest and agroforestry landscapes and grasslands, which will provide essential ecosystem goods and services, restore lost livelihoods and create new wealth. The ambition of reforestation efforts within this initiative - the like of which the world has never seen before - sounds like an impossible dream. However, learning from past mistakes and capitalising on current advancement in science and technology, it is a reality that is taking root. Following a successful restoration model that RBG Kew experts have devised, we are helping to mobilise, train and support communities in four border regions in Burkina Faso, Mali and Niger. In collaboration with FAO, the Millennium Seed Bank Partnership is using its unique expertise to ensure that seeds of environmentally well-adapted and economically useful local species are collected and planted in communal gardens and village agroforestry systems managed by the communities themselves. In our first year, an estimated total of 162,000 seedlings and 61 kg of seeds from 40 useful native species, including grasses for livestock, have been planted to cover 237 ha of farmer-managed land in 19 villages. The keen interest it has created has indicated that these figures will rise five-fold in the second year. These green bricks are the foundations of the living wall that will eventually reach across the

  19. Optimal feedback scheduling of model predictive controllers

    Institute of Scientific and Technical Information of China (English)

    Pingfang ZHOU; Jianying XIE; Xiaolong DENG

    2006-01-01

    Model predictive control (MPC) could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling (FS-CBS) of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server (CBS), whose reserved processor time is adjusted dynamically. The constraints in the FSCBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness.

  20. Longevity and lifetime reproductive success of barn swallow offspring are predicted by their hatching date and phenotypic quality.

    Science.gov (United States)

    Saino, Nicola; Romano, Maria; Ambrosini, Roberto; Rubolini, Diego; Boncoraglio, Giuseppe; Caprioli, Manuela; Romano, Andrea

    2012-09-01

    1. Longevity is a major determinant of individual differences in Darwinian fitness. Several studies have analyzed the stochastic, time-dependent causes of variation in longevity, but little information exists from free-ranging animal populations on the effects that environmental conditions and phenotype early in ontogeny have on duration of life. 2. In this long-term (1993-2011) study of a migratory, colonial, passerine bird, the barn swallow (Hirundo rustica), we analyzed longevity and, in a subsample of individuals, lifetime reproductive success (LRS) of the offspring that reached sexual maturity in relation to hatching date, which can affect the rearing environment through a seasonal deterioration in ecological conditions. Moreover, we analyzed the consequences of variation in body size and, for the first time in any species, of a major component of immunity on longevity, both by looking at absolute phenotypic values and at deviations from the brood mean. 3. Accelerated failure time models showed that individuals of both sexes that hatched early in any breeding season enjoyed larger longevity and larger LRS, indicating directional selection for early breeding. Both male and female offspring with large T cell-mediated immune response relative to their siblings and female nestlings that dominated the brood size/age hierarchy had larger longevity than their siblings of inferior phenotypic quality/age. Conversely, absolute phenotypic values did not predict longevity. 4. Frailty modelling disclosed marked spatial heterogeneity in longevity among colonies of origin, again stressing the impact of rearing conditions on longevity. 5. This study therefore reinforces the notion that perinatal environment and maternal decisions over timing and site of breeding, and position in the brood hierarchy can have marked effects on progeny life history that extend well into adulthood. In addition, it provides the first evidence from any bird population in the wild that immune

  1. Objective calibration of numerical weather prediction models

    Science.gov (United States)

    Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

    2017-07-01

    Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

  2. Model predictive control of MSMPR crystallizers

    Science.gov (United States)

    Moldoványi, Nóra; Lakatos, Béla G.; Szeifert, Ferenc

    2005-02-01

    A multi-input-multi-output (MIMO) control problem of isothermal continuous crystallizers is addressed in order to create an adequate model-based control system. The moment equation model of mixed suspension, mixed product removal (MSMPR) crystallizers that forms a dynamical system is used, the state of which is represented by the vector of six variables: the first four leading moments of the crystal size, solute concentration and solvent concentration. Hence, the time evolution of the system occurs in a bounded region of the six-dimensional phase space. The controlled variables are the mean size of the grain; the crystal size-distribution and the manipulated variables are the input concentration of the solute and the flow rate. The controllability and observability as well as the coupling between the inputs and the outputs was analyzed by simulation using the linearized model. It is shown that the crystallizer is a nonlinear MIMO system with strong coupling between the state variables. Considering the possibilities of the model reduction, a third-order model was found quite adequate for the model estimation in model predictive control (MPC). The mean crystal size and the variance of the size distribution can be nearly separately controlled by the residence time and the inlet solute concentration, respectively. By seeding, the controllability of the crystallizer increases significantly, and the overshoots and the oscillations become smaller. The results of the controlling study have shown that the linear MPC is an adaptable and feasible controller of continuous crystallizers.

  3. Predictive modeling of reactive wetting and metal joining.

    Energy Technology Data Exchange (ETDEWEB)

    van Swol, Frank B.

    2013-09-01

    The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.

  4. An Anisotropic Hardening Model for Springback Prediction

    Science.gov (United States)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  5. Establishing versus preserving impressions: Predicting success in the multiple audience problem.

    Science.gov (United States)

    Nichols, Austin Lee; Cottrell, Catherine A

    2015-12-01

    People sometimes seek to convey discrepant impressions of themselves to different audiences simultaneously. Research suggests people are generally successful in this "multiple audience problem." Adding to previous research, the current research sought to examine factors that may limit this success by measuring social anxiety and placing participants into situations requiring them to either establish or preserve multiple impressions simultaneously. In general, participants were more successful when preserving previously conveyed impressions than when establishing impressions for the first time. In contrast, social anxiety did not affect multiple audience success. In all, this research offers valuable insight into potential challenges that people face in many social situations.

  6. Motivational patterns as an instrument for predicting success in promising young football players.

    Science.gov (United States)

    Zuber, Claudia; Zibung, Marc; Conzelmann, Achim

    2015-01-01

    Psychological characteristics are crucial to identifying talents, which is why these are being incorporated in today's multidimensional talent models. In addition to multidimensionality, talent studies are increasingly drawing on holistic theories of development, leading to the use of person-oriented approaches. The present study adopts such an approach by looking at the influence that motivational characteristics have on the development of performance, in a person-oriented way. For this purpose, it looks at how the constructs achievement motive, achievement goal orientation and self-determination interact with one another, what patterns they form and how these patterns are linked to subsequent sports success. Ninety-seven top young football players were questioned twice. Another year later, it was enquired which of these players had been selected for the U15 national team. At both measuring points, four patterns were identified, which displayed a high degree of structural and individual stability. As expected, the highly intrinsically achievement-oriented players were significantly more likely to move up into the U15 national team. The results point to the importance of favourable patterns of motivational variables in the form of specific types, for medium-term performance development among promising football talents, and thus provide valuable clues for the selection and promotion of those.

  7. An Australian Model of Successful School Leadership: Moving from Success to Sustainability

    Science.gov (United States)

    Drysdale, Lawrie; Goode, Helen; Gurr, David

    2009-01-01

    Purpose: This paper seeks to demonstrate how the principal was instrumental in turning around an underperforming school by using a leadership style that modelled appropriate behaviour, and which was consultative, conciliatory, inspirational and empathetic, through having a clearly articulated whole-child-focused educational philosophy, by building…

  8. The Effectiveness of Traditional Admissions Criteria in Predicting College and Graduate Success for American and International Students

    Science.gov (United States)

    Fu, Yanfei

    2012-01-01

    This study examines the effectiveness of traditional admissions criteria, including prior GPA, SAT, GRE, and TOEFL in predicting undergraduate and graduate academic success for American and international students at a large public university in the southwestern United States. Included are the admissions and enrollment data for 25,017 undergraduate…

  9. Predicting Academic Success of Junior Secondary School Students in Mathematics through Cognitive Style and Problem Solving Technique

    Science.gov (United States)

    Badru, Ademola K.

    2015-01-01

    This study examined the prediction of academic success of Junior secondary school mathematics students using their cognitive style and problem solving technique. A descriptive survey of correlation type was adopted for this study. A purposive sampling procedure was used to select five Public Junior secondary schools in Ijebu-Ode local government…

  10. The Prediction of Success in Engineering Graphics Using the Group Embedded Figures Test and the Hidden Figures Test.

    Science.gov (United States)

    Wilson, Russell C.; Davis, Paul D.

    1985-01-01

    A study was conducted to continue the assessment of the Group Embedded Figures Test (GEFT), to assess the value of the Hidden Figures Test (HFT), and to assess the usefulness of the two instruments used in combination as tools for predicting student success and early identification of students who may need special assistance in engineering…

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

    Science.gov (United States)

    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…

  12. Predicting Preservice Music Teachers' Performance Success in Instrumental Courses Using Self-Regulated Study Strategies and Predictor Variables

    Science.gov (United States)

    Ersozlu, Zehra N.; Nietfeld, John L.; Huseynova, Lale

    2017-01-01

    The purpose of this study was to examine the extent to which self-regulated study strategies and predictor variables predict performance success in instrumental performance college courses. Preservice music teachers (N = 123) from a music education department in two state universities in Turkey completed the Music Self-Regulated Studying…

  13. Predicting College Math Success: Do High School Performance and Gender Matter? Evidence from Sultan Qaboos University in Oman

    Science.gov (United States)

    Islam, M. Mazharul; Al-Ghassani, Asma

    2015-01-01

    The objective of this study was to evaluate the performance of students of college of Science of Sultan Qaboos University (SQU) in Calculus I course, and examine the predictive validity of student's high school performance and gender for Calculus I success. The data for the study was extracted from students' database maintained by the Deanship of…

  14. Predictive modelling of ferroelectric tunnel junctions

    Science.gov (United States)

    Velev, Julian P.; Burton, John D.; Zhuravlev, Mikhail Ye; Tsymbal, Evgeny Y.

    2016-05-01

    Ferroelectric tunnel junctions combine the phenomena of quantum-mechanical tunnelling and switchable spontaneous polarisation of a nanometre-thick ferroelectric film into novel device functionality. Switching the ferroelectric barrier polarisation direction produces a sizable change in resistance of the junction—a phenomenon known as the tunnelling electroresistance effect. From a fundamental perspective, ferroelectric tunnel junctions and their version with ferromagnetic electrodes, i.e., multiferroic tunnel junctions, are testbeds for studying the underlying mechanisms of tunnelling electroresistance as well as the interplay between electric and magnetic degrees of freedom and their effect on transport. From a practical perspective, ferroelectric tunnel junctions hold promise for disruptive device applications. In a very short time, they have traversed the path from basic model predictions to prototypes for novel non-volatile ferroelectric random access memories with non-destructive readout. This remarkable progress is to a large extent driven by a productive cycle of predictive modelling and innovative experimental effort. In this review article, we outline the development of the ferroelectric tunnel junction concept and the role of theoretical modelling in guiding experimental work. We discuss a wide range of physical phenomena that control the functional properties of ferroelectric tunnel junctions and summarise the state-of-the-art achievements in the field.

  15. Simple predictions from multifield inflationary models.

    Science.gov (United States)

    Easther, Richard; Frazer, Jonathan; Peiris, Hiranya V; Price, Layne C

    2014-04-25

    We explore whether multifield inflationary models make unambiguous predictions for fundamental cosmological observables. Focusing on N-quadratic inflation, we numerically evaluate the full perturbation equations for models with 2, 3, and O(100) fields, using several distinct methods for specifying the initial values of the background fields. All scenarios are highly predictive, with the probability distribution functions of the cosmological observables becoming more sharply peaked as N increases. For N=100 fields, 95% of our Monte Carlo samples fall in the ranges ns∈(0.9455,0.9534), α∈(-9.741,-7.047)×10-4, r∈(0.1445,0.1449), and riso∈(0.02137,3.510)×10-3 for the spectral index, running, tensor-to-scalar ratio, and isocurvature-to-adiabatic ratio, respectively. The expected amplitude of isocurvature perturbations grows with N, raising the possibility that many-field models may be sensitive to postinflationary physics and suggesting new avenues for testing these scenarios.

  16. A Traffic Light Grading System of Hip Dysplasia to Predict the Success of Arthroscopic Hip Surgery.

    Science.gov (United States)

    Grammatopoulos, George; Davies, Owain L I; El-Bakoury, Ahmed; Gill, Harinderjit S; Pollard, Tom C B; Andrade, Antonio J

    2017-06-01

    The role of hip arthroscopic surgery in dysplasia is controversial. To determine the 7-year joint preservation rate after hip arthroscopic surgery in hip dysplasia and identify anatomic and intraoperative features that predict the success of hip preservation with arthroscopic surgery, allowing the formulation of an evidence-based classification system. Case-control study; Level of evidence, 3. Between 2008 and 2013, 111 hips with dysplastic features (acetabular index [AI] >10° and/or lateral center-edge angle [LCEA] hip (AI, LCEA, extrusion index) were performed. Outcome measures included whether the hip was preserved (ie, did not require arthroplasty) at follow-up and the preoperative and postoperative Non-Arthritic Hip Score (NAHS) and Hip disability and Osteoarthritis Outcome Score (HOOS). The AI and LCEA were calculated, factored by a measure of articular wear (AIf and LCEAf, respectively), according to the University College Hospital, London (UCL) grading system as follows: AIf = AI × (number of UCL wear zones + 1), and LCEAf = LCEA / (number of UCL wear zones + 1). A contour plot of the resulting probability value of failure for every combination of AIf and LCEAf allowed for the determination of the zones with the lowest and highest incidences of failure to preserve the hip. The mean AI and LCEA were 9.8° and 18.0°, respectively. At a mean follow-up of 4.5 years (range, 0.4-8.3 years), 33 hips had failed, requiring hip arthroplasty. The 7-year joint survival rate was 68%. The mean improvements in the NAHS and HOOS were 11 ( P = .001) and 22.8 ( P hip survival rate in hip dysplasia appears inferior compared with that reported in femoroacetabular impingement (78%). Hip arthroscopic surgery is associated with an excellent chance of hip preservation in mild dysplasia (green zone: AI = 0°-15°, LCEA = 15°-25°) and no articular wear. The authors advise that the greatest caution should be used when considering arthroscopic options in cases of severe dysplasia

  17. Predictions of models for environmental radiological assessment

    Energy Technology Data Exchange (ETDEWEB)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa, E-mail: suelip@ird.gov.br, E-mail: dejanira@irg.gov.br [Instituto de Radioprotecao e Dosimetria (IRD/CNEN-RJ), Servico de Avaliacao de Impacto Ambiental, Rio de Janeiro, RJ (Brazil); Mahler, Claudio Fernando [Coppe. Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia, Universidade Federal do Rio de Janeiro (UFRJ) - Programa de Engenharia Civil, RJ (Brazil)

    2011-07-01

    In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for {sup 137}Cs and {sup 60}Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)

  18. Bayesian prediction of placebo analgesia in an instrumental learning model

    Science.gov (United States)

    Jung, Won-Mo; Lee, Ye-Seul; Wallraven, Christian; Chae, Younbyoung

    2017-01-01

    Placebo analgesia can be primarily explained by the Pavlovian conditioning paradigm in which a passively applied cue becomes associated with less pain. In contrast, instrumental conditioning employs an active paradigm that might be more similar to clinical settings. In the present study, an instrumental conditioning paradigm involving a modified trust game in a simulated clinical situation was used to induce placebo analgesia. Additionally, Bayesian modeling was applied to predict the placebo responses of individuals based on their choices. Twenty-four participants engaged in a medical trust game in which decisions to receive treatment from either a doctor (more effective with high cost) or a pharmacy (less effective with low cost) were made after receiving a reference pain stimulus. In the conditioning session, the participants received lower levels of pain following both choices, while high pain stimuli were administered in the test session even after making the decision. The choice-dependent pain in the conditioning session was modulated in terms of both intensity and uncertainty. Participants reported significantly less pain when they chose the doctor or the pharmacy for treatment compared to the control trials. The predicted pain ratings based on Bayesian modeling showed significant correlations with the actual reports from participants for both of the choice categories. The instrumental conditioning paradigm allowed for the active choice of optional cues and was able to induce the placebo analgesia effect. Additionally, Bayesian modeling successfully predicted pain ratings in a simulated clinical situation that fits well with placebo analgesia induced by instrumental conditioning. PMID:28225816

  19. Biofeedback and Relaxation Therapy for Chronic Temporomandibular Joint Pain: Predicting Successful Outcomes.

    Science.gov (United States)

    Funch, Donna P.; Gale, Elliot N.

    1984-01-01

    Randomly assigned 57 patients with chronic temporomandibular joint (TMJ) pain to receive either relaxation or biofeedback therapy. Successful patients in the relaxation condition tended to be younger and had experienced TMJ pain for a shorter period of time than the successful biofeedback patients. (BH)

  20. Pathways, mechanisms and predictability of vegetation change during tropical dry forest succession

    NARCIS (Netherlands)

    Lebrija Trejos, E.E.; Meave, J.; Poorter, L.; Pérez- García, E.A.; Bongers, F.

    2010-01-01

    The development of forest succession theory has been based on studies in temperate and tropical wet forests. As rates and pathways of succession vary with the environment, advances in successional theory and study approaches are challenged by controversies derived from such variation and by the scar

  1. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained......The primary structure of a protein is the sequence of its amino acids. The secondary structure describes structural properties of the molecule such as which parts of it form sheets, helices or coils. Spacial and other properties are described by the higher order structures. The classification task...

  2. A Modified Model Predictive Control Scheme

    Institute of Scientific and Technical Information of China (English)

    Xiao-Bing Hu; Wen-Hua Chen

    2005-01-01

    In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.

  3. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... facilitates plug-and-play addition of subsystems without redesign of any controllers. The method is supported by a number of simulations featuring a three-level smart-grid power control system for a small isolated power grid....

  4. Explicit model predictive control accuracy analysis

    OpenAIRE

    Knyazev, Andrew; Zhu, Peizhen; Di Cairano, Stefano

    2015-01-01

    Model Predictive Control (MPC) can efficiently control constrained systems in real-time applications. MPC feedback law for a linear system with linear inequality constraints can be explicitly computed off-line, which results in an off-line partition of the state space into non-overlapped convex regions, with affine control laws associated to each region of the partition. An actual implementation of this explicit MPC in low cost micro-controllers requires the data to be "quantized", i.e. repre...

  5. Critical conceptualism in environmental modeling and prediction.

    Science.gov (United States)

    Christakos, G

    2003-10-15

    Many important problems in environmental science and engineering are of a conceptual nature. Research and development, however, often becomes so preoccupied with technical issues, which are themselves fascinating, that it neglects essential methodological elements of conceptual reasoning and theoretical inquiry. This work suggests that valuable insight into environmental modeling can be gained by means of critical conceptualism which focuses on the software of human reason and, in practical terms, leads to a powerful methodological framework of space-time modeling and prediction. A knowledge synthesis system develops the rational means for the epistemic integration of various physical knowledge bases relevant to the natural system of interest in order to obtain a realistic representation of the system, provide a rigorous assessment of the uncertainty sources, generate meaningful predictions of environmental processes in space-time, and produce science-based decisions. No restriction is imposed on the shape of the distribution model or the form of the predictor (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated). The scientific reasoning structure underlying knowledge synthesis involves teleologic criteria and stochastic logic principles which have important advantages over the reasoning method of conventional space-time techniques. Insight is gained in terms of real world applications, including the following: the study of global ozone patterns in the atmosphere using data sets generated by instruments on board the Nimbus 7 satellite and secondary information in terms of total ozone-tropopause pressure models; the mapping of arsenic concentrations in the Bangladesh drinking water by assimilating hard and soft data from an extensive network of monitoring wells; and the dynamic imaging of probability distributions of pollutants across the Kalamazoo river.

  6. Predicting Student Success in a Major's Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores

    Science.gov (United States)

    Thompson, E. David; Bowling, Bethany V.; Markle, Ross E.

    2017-02-01

    Studies over the last 30 years have considered various factors related to student success in introductory biology courses. While much of the available literature suggests that the best predictors of success in a college course are prior college grade point average (GPA) and class attendance, faculty often require a valuable predictor of success in those courses wherein the majority of students are in the first semester and have no previous record of college GPA or attendance. In this study, we evaluated the efficacy of the ACT Mathematics subject exam and Lawson's Classroom Test of Scientific Reasoning in predicting success in a major's introductory biology course. A logistic regression was utilized to determine the effectiveness of a combination of scientific reasoning (SR) scores and ACT math (ACT-M) scores to predict student success. In summary, we found that the model—with both SR and ACT-M as significant predictors—could be an effective predictor of student success and thus could potentially be useful in practical decision making for the course, such as directing students to support services at an early point in the semester.

  7. Predicting Successful Aging in a Population-Based Sample of Georgia Centenarians

    Directory of Open Access Journals (Sweden)

    Jonathan Arnold

    2010-01-01

    Full Text Available Used a population-based sample (Georgia Centenarian Study, GCS, to determine proportions of centenarians reaching 100 years as (1 survivors (43% of chronic diseases first experienced between 0–80 years of age, (2 delayers (36% with chronic diseases first experienced between 80–98 years of age, or (3 escapers (17% with chronic diseases only at 98 years of age or older. Diseases fall into two morbidity profiles of 11 chronic diseases; one including cardiovascular disease, cancer, anemia, and osteoporosis, and another including dementia. Centenarians at risk for cancer in their lifetime tended to be escapers (73%, while those at risk for cardiovascular disease tended to be survivors (24%, delayers (39%, or escapers (32%. Approximately half (43% of the centenarians did not experience dementia. Psychiatric disorders were positively associated with dementia, but prevalence of depression, anxiety, and psychoses did not differ significantly between centenarians and an octogenarian control group. However, centenarians were higher on the Geriatric Depression Scale (GDS than octogenarians. Consistent with our model of developmental adaptation in aging, distal life events contribute to predicting survivorship outcome in which health status as survivor, delayer, or escaper appears as adaptation variables late in life.

  8. Predicting successful aging in a population-based sample of georgia centenarians.

    Science.gov (United States)

    Arnold, Jonathan; Dai, Jianliang; Nahapetyan, Lusine; Arte, Ankit; Johnson, Mary Ann; Hausman, Dorothy; Rodgers, Willard L; Hensley, Robert; Martin, Peter; Macdonald, Maurice; Davey, Adam; Siegler, Ilene C; Jazwinski, S Michal; Poon, Leonard W

    2010-01-01

    Used a population-based sample (Georgia Centenarian Study, GCS), to determine proportions of centenarians reaching 100 years as (1) survivors (43%) of chronic diseases first experienced between 0-80 years of age, (2) delayers (36%) with chronic diseases first experienced between 80-98 years of age, or (3) escapers (17%) with chronic diseases only at 98 years of age or older. Diseases fall into two morbidity profiles of 11 chronic diseases; one including cardiovascular disease, cancer, anemia, and osteoporosis, and another including dementia. Centenarians at risk for cancer in their lifetime tended to be escapers (73%), while those at risk for cardiovascular disease tended to be survivors (24%), delayers (39%), or escapers (32%). Approximately half (43%) of the centenarians did not experience dementia. Psychiatric disorders were positively associated with dementia, but prevalence of depression, anxiety, and psychoses did not differ significantly between centenarians and an octogenarian control group. However, centenarians were higher on the Geriatric Depression Scale (GDS) than octogenarians. Consistent with our model of developmental adaptation in aging, distal life events contribute to predicting survivorship outcome in which health status as survivor, delayer, or escaper appears as adaptation variables late in life.

  9. Sweet success, bitter defeat: a taste phenotype predicts social status in selectively bred rats.

    Directory of Open Access Journals (Sweden)

    John M Eaton

    Full Text Available For social omnivores such as rats and humans, taste is far more than a chemical sense activated by food. By virtue of evolutionary and epigenetic elaboration, taste is associated with negative affect, stress vulnerability, responses to psychoactive substances, pain, and social judgment. A crucial gap in this literature, which spans behavior genetics, affective and social neuroscience, and embodied cognition, concerns links between taste and social behavior in rats. Here we show that rats selectively bred for low saccharin intake are subordinate to high-saccharin-consuming rats when they compete in weight-matched dyads for food, a task used to model depression. Statistical and experimental controls suggest that differential resource utilization within dyads is not an artifact of individual-level processes such as apparatus habituation or ingestive motivation. Tail skin temperature measurements showed that LoS rats display larger hyperthermic responses to social interaction after status is established, evidence linking taste, social stress, autonomic reactivity, and depression-like symptoms. Based on regression using early- and late-competition predictors to predict dyadic disparity in final competition scores, we tentatively suggest that HiS rats emerge as dominant both because of an "early surge" on their part and because LoS acquiesce later. These findings should invigorate the comparative study of individual differences in social status and its relationship to mental and physical health.

  10. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  11. Predicting the chance of vaginal delivery after one cesarean section: validation and elaboration of a published prediction model.

    Science.gov (United States)

    Fagerberg, Marie C; Maršál, Karel; Källén, Karin

    2015-05-01

    We aimed to validate a widely used US prediction model for vaginal birth after cesarean (Grobman et al. [8]) and modify it to suit Swedish conditions. Women having experienced one cesarean section and at least one subsequent delivery (n=49,472) in the Swedish Medical Birth Registry 1992-2011 were randomly divided into two data sets. In the development data set, variables associated with successful trial of labor were identified using multiple logistic regression. The predictive ability of the estimates previously published by Grobman et al., and of our modified and new estimates, respectively, was then evaluated using the validation data set. The accuracy of the models for prediction of vaginal birth after cesarean was measured by area under the receiver operating characteristics curve. For maternal age, body mass index, prior vaginal delivery, and prior labor arrest, the odds ratio estimates for vaginal birth after cesarean were similar to those previously published. The prediction accuracy increased when information on indication for the previous cesarean section was added (from area under the receiver operating characteristics curve=0.69-0.71), and increased further when maternal height and delivery unit cesarean section rates were included (area under the receiver operating characteristics curve=0.74). The correlation between the individual predicted vaginal birth after cesarean probability and the observed trial of labor success rate was high in all the respective predicted probability decentiles. Customization of prediction models for vaginal birth after cesarean is of considerable value. Choosing relevant indicators for a Swedish setting made it possible to achieve excellent prediction accuracy for success in trial of labor after cesarean. During the delicate process of counseling about preferred delivery mode after one cesarean section, considering the results of our study may facilitate the choice between a trial of labor or an elective repeat cesarean

  12. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    For the modern railways, maintenance is critical for ensuring safety, train punctuality and overall capacity utilization. The cost of railway maintenance in Europe is high, on average between 30,000 – 100,000 Euro per km per year [1]. Aiming to reduce such maintenance expenditure, this paper...... presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time...... recovery on the track quality after tamping operation and (5) Tamping machine operation factors. A Danish railway track between Odense and Fredericia with 57.2 km of length is applied for a time period of two to four years in the proposed maintenance model. The total cost can be reduced with up to 50...

  13. The business of emergency medicine: a model for success.

    Science.gov (United States)

    Proctor, John; Hall, Peter; Carr, Janet

    2004-02-01

    Today's EPOs and their physicians face an array of daunting challenges. Falling reimbursement, rising malpractice costs. ED and hospital crowding,and demands for improving ED efficiency and patient satisfaction all contribute to the challenging and sometimes threatening environment of EM practice. The EP involved in a busy and often hectic ED shift may feel unduly and unnecessarily distracted when required to continuously acknowledge and address the business aspect of the practice. Nevertheless,regardless of the size and structure, fiscal viability ultimately determines the EPO's ability to continue to offer access to care. This article contends that a comprehensive business strategy drives superior financial performance and supports the organization's mission. The business strategy must identify financial and non-financial determinants of the EPO's success and provide a mechanism for understanding how the organization's resources are converted to value for customers. The section offers a framework for developing this strategy, for identifying possible gaps or deficiencies, and for measuring and monitoring progress in achieving strategic objectives and ultimately, the EPO's mission. The importance of the mission and the dynamic EM environment require that the strategy development process be more than an annual exercise for the leadership of the organization. Though key leaders in any size EPO--set the course for the organization, the entire organization must be aware and understand the strategy before they commit themselves and adopt actions and behaviors that promote it. The model presented here provides a graphic display that lends itself well to consistent communication of a comprehensive strategy in a concise way throughout the organization.Furthermore, the balance of the model, across four perspectives, recognizes the value of balanced organizational objectives and lends itself well to the creation of a measurement system that supports cause and effect

  14. A predictive fitness model for influenza

    Science.gov (United States)

    Łuksza, Marta; Lässig, Michael

    2014-03-01

    The seasonal human influenza A/H3N2 virus undergoes rapid evolution, which produces significant year-to-year sequence turnover in the population of circulating strains. Adaptive mutations respond to human immune challenge and occur primarily in antigenic epitopes, the antibody-binding domains of the viral surface protein haemagglutinin. Here we develop a fitness model for haemagglutinin that predicts the evolution of the viral population from one year to the next. Two factors are shown to determine the fitness of a strain: adaptive epitope changes and deleterious mutations outside the epitopes. We infer both fitness components for the strains circulating in a given year, using population-genetic data of all previous strains. From fitness and frequency of each strain, we predict the frequency of its descendent strains in the following year. This fitness model maps the adaptive history of influenza A and suggests a principled method for vaccine selection. Our results call for a more comprehensive epidemiology of influenza and other fast-evolving pathogens that integrates antigenic phenotypes with other viral functions coupled by genetic linkage.

  15. Predictive Model of Radiative Neutrino Masses

    CERN Document Server

    Babu, K S

    2013-01-01

    We present a simple and predictive model of radiative neutrino masses. It is a special case of the Zee model which introduces two Higgs doublets and a charged singlet. We impose a family-dependent Z_4 symmetry acting on the leptons, which reduces the number of parameters describing neutrino oscillations to four. A variety of predictions follow: The hierarchy of neutrino masses must be inverted; the lightest neutrino mass is extremely small and calculable; one of the neutrino mixing angles is determined in terms of the other two; the phase parameters take CP-conserving values with \\delta_{CP} = \\pi; and the effective mass in neutrinoless double beta decay lies in a narrow range, m_{\\beta \\beta} = (17.6 - 18.5) meV. The ratio of vacuum expectation values of the two Higgs doublets, tan\\beta, is determined to be either 1.9 or 0.19 from neutrino oscillation data. Flavor-conserving and flavor-changing couplings of the Higgs doublets are also determined from neutrino data. The non-standard neutral Higgs bosons, if t...

  16. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...

  17. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  18. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model......A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...

  19. Southpoint: A Search for Predictive Variables for Determination of Success in Alcoholism Rehabilitation

    Science.gov (United States)

    Klein, John Paul

    1973-01-01

    Southpoint is a retrospective study of variables (age, marital status, education, work history, client's use of public assistance or compensation) involved in attempting to relate successful rehabilitation of alcoholics. (EA)

  20. A Partially Annotated Bibliography on Prediction of Parole Success and Delinquency

    Science.gov (United States)

    The bibliography was undertaken to review studies that would be useful in estimating the probability of an offender’s post-release success. Offenders ...correctional treatment and returning a maximum number of offenders to duty with the potential for successful adjustment to Army life. In order to attain...this end, offenders who will not or cannot respond to correction treatment need to be identified and separately processed. Effective correctional

  1. PREDICTING SUCCESS INDICATORS OF AN INTERVENTION PROGRAMME FOR CONVICTED INTIMATE-PARTNER VIOLENCE OFFENDERS: THE CONTEXTO PROGRAMME

    Directory of Open Access Journals (Sweden)

    Enrique Gracia

    2013-01-01

    Full Text Available Recent legal changes in Spain have led to an important increase in the number of men court-mandated to community-based partner violence offender intervention programmes. However, just a few of those interventions have been systematically examined. This study aims to predict success indicators of an intervention programme for convicted intimate-partner violence offenders. The sample consisted of 212 convicted intimate-partner violence offenders who participated in the Contexto Programme. Three “intervention gains” or target criteria were established (increasing the perceived severity of violence, increasing the responsibility assumption for one’s actions, and reducing the risk of recidivism. A structural equations model was tested, fitting data appropriately. Participants with major gain in recidivism risk were those who presented lower levels of alcohol consumption, shorter sentences, lower impulsivity, and a higher degree of life satisfaction. The largest gain in perceived severity was found in younger participants, participants with shorter sentences, lower alcohol consumption, higher life satisfaction, higher participation in their community, and higher self-esteem. And, finally, participants with the highest gains in responsibility assumption were older participants, participants who presented higher intimate support, higher anxiety, higher sexism, lower anger control, higher depression, higher impulsivity and higher self-esteem.

  2. Two criteria for evaluating risk prediction models.

    Science.gov (United States)

    Pfeiffer, R M; Gail, M H

    2011-09-01

    We propose and study two criteria to assess the usefulness of models that predict risk of disease incidence for screening and prevention, or the usefulness of prognostic models for management following disease diagnosis. The first criterion, the proportion of cases followed PCF (q), is the proportion of individuals who will develop disease who are included in the proportion q of individuals in the population at highest risk. The second criterion is the proportion needed to follow-up, PNF (p), namely the proportion of the general population at highest risk that one needs to follow in order that a proportion p of those destined to become cases will be followed. PCF (q) assesses the effectiveness of a program that follows 100q% of the population at highest risk. PNF (p) assess the feasibility of covering 100p% of cases by indicating how much of the population at highest risk must be followed. We show the relationship of those two criteria to the Lorenz curve and its inverse, and present distribution theory for estimates of PCF and PNF. We develop new methods, based on influence functions, for inference for a single risk model, and also for comparing the PCFs and PNFs of two risk models, both of which were evaluated in the same validation data.

  3. Methods for Handling Missing Variables in Risk Prediction Models

    NARCIS (Netherlands)

    Held, Ulrike; Kessels, Alfons; Aymerich, Judith Garcia; Basagana, Xavier; ter Riet, Gerben; Moons, Karel G. M.; Puhan, Milo A.

    2016-01-01

    Prediction models should be externally validated before being used in clinical practice. Many published prediction models have never been validated. Uncollected predictor variables in otherwise suitable validation cohorts are the main factor precluding external validation.We used individual patient

  4. Modelling the rate of secondary succession after farmland abandonment in a Mediterranean mountain area

    NARCIS (Netherlands)

    Beguería, S.; Pueyo, Y.

    2007-01-01

    Secondary succession after farmland abandonment has become a common process in north Mediterranean countries, especially in mountain areas. In this paper a methodology is tested which combines Markov chains and logistic multivariate regression to model secondary succession after farmland abandonment

  5. Predictive value of low tube voltage and dual-energy CT for successful shock wave lithotripsy: an in vitro study.

    Science.gov (United States)

    Largo, Remo; Stolzmann, Paul; Fankhauser, Christian D; Poyet, Cédric; Wolfsgruber, Pirmin; Sulser, Tullio; Alkadhi, Hatem; Winklhofer, Sebastian

    2016-06-01

    This study investigates the capabilities of low tube voltage computed tomography (CT) and dual-energy CT (DECT) for predicting successful shock wave lithotripsy (SWL) of urinary stones in vitro. A total of 33 urinary calculi (six different chemical compositions; mean size 6 ± 3 mm) were scanned using a dual-source CT machine with single- (120 kVp) and dual-energy settings (80/150, 100/150 Sn kVp) resulting in six different datasets. The attenuation (Hounsfield Units) of calculi was measured on single-energy CT images and the dual-energy indices (DEIs) were calculated from DECT acquisitions. Calculi underwent SWL and the number of shock waves for successful disintegration was recorded. The prediction of required shock waves regarding stone attenuation/DEI was calculated using regression analysis (adjusted for stone size and composition) and the correlation between CT attenuation/DEI and the number of shock waves was assessed for all datasets. The median number of shock waves for successful stone disintegration was 72 (interquartile range 30-361). CT attenuation/DEI of stones was a significant, independent predictor (P waves with the best prediction at 80 kVp (β estimate 0.576) (P waves ranged between ρ = 0.31 and 0.68 showing the best correlation at 80 kVp (P < 0.001). The attenuation of urinary stones at low tube voltage CT is the best predictor for successful stone disintegration, being independent of stone composition and size. DECT shows no added value for predicting the success of SWL.

  6. Predictability of the large relaxations in a cellular automaton model

    Energy Technology Data Exchange (ETDEWEB)

    Tejedor, Alejandro; Ambroj, Samuel; Gomez, Javier B; Pacheco, Amalio F [Faculty of Sciences, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza (Spain)

    2008-09-19

    A simple one-dimensional cellular automaton model with threshold dynamics is introduced. It is loaded at a uniform rate and unloaded by abrupt relaxations. The cumulative distribution of the size of the relaxations is analytically computed and behaves as a power law with an exponent equal to -1. This coincides with the phenomenological Gutenberg-Richter behavior observed in seismology for the cumulative statistics of earthquakes at the regional or global scale. The key point of the model is the zero-load state of the system after the occurrence of any relaxation, no matter what its size. This leads to an equipartition of probability between all possible load configurations in the system during the successive loading cycles. Each cycle ends with the occurrence of the greatest-or characteristic-relaxation in the system. The duration of the cycles in the model is statistically distributed with a coefficient of variation ranging from 0.5 to 1. The predictability of the characteristic relaxations is evaluated by means of error diagrams. This model illustrates the value taking into account the refractory periods to obtain a considerable gain in the quality of the predictions.

  7. Acoustic Predictions in Industrial Spaces Using a Diffusion Model

    Directory of Open Access Journals (Sweden)

    Alexis Billon

    2012-01-01

    Full Text Available Industrial spaces are known to be very noisy working environment. This noise exposure can be uncomfortable, tiring, or even harmful, at worst. Industrial spaces have several characteristics: they are often huge flat volumes fitted with many obstacles and sound sources. Moreover, they are usually surrounded by rooms where low noise levels are required. The existing prediction tools can seldom model all these phenomena accurately. In this paper, a prediction model based on a diffusion equation is presented. The successive developments carried out to deal with the various propagating phenomena met in industrial spaces are shown. For each phenomenon, numerical or experimental examples are given to highlight the validity of this model. It is also shown that its computation load is very little in comparison to ray-tracing-based methods. In addition, this model can be used as a reliable and flexible tool to study the physics of the coupling between rooms. Finally, an application to a virtual factory is presented.

  8. Exchange Rate Prediction using Neural – Genetic Model

    Directory of Open Access Journals (Sweden)

    MECHGOUG Raihane

    2012-10-01

    Full Text Available Neural network have successfully used for exchange rate forecasting. However, due to a large number of parameters to be estimated empirically, it is not a simple task to select the appropriate neural network architecture for exchange rate forecasting problem.Researchers often overlook the effect of neural network parameters on the performance of neural network forecasting. The performance of neural network is critically dependant on the learning algorithms, thenetwork architecture and the choice of the control parameters. Even when a suitable setting of parameters (weight can be found, the ability of the resulting network to generalize the data not seen during learning may be far from optimal. For these reasons it seemslogical and attractive to apply genetic algorithms. Genetic algorithms may provide a useful tool for automating the design of neural network. The empirical results on foreign exchange rate prediction indicate that the proposed hybrid model exhibits effectively improved accuracy, when is compared with some other time series forecasting models.

  9. Predicting the ungauged basin: model validation and realism assessment

    Science.gov (United States)

    van Emmerik, Tim; Mulder, Gert; Eilander, Dirk; Piet, Marijn; Savenije, Hubert

    2016-04-01

    The hydrological decade on Predictions in Ungauged Basins (PUB) [1] led to many new insights in model development, calibration strategies, data acquisition and uncertainty analysis. Due to a limited amount of published studies on genuinely ungauged basins, model validation and realism assessment of model outcome has not been discussed to a great extent. With this study [2] we aim to contribute to the discussion on how one can determine the value and validity of a hydrological model developed for an ungauged basin. As in many cases no local, or even regional, data are available, alternative methods should be applied. Using a PUB case study in a genuinely ungauged basin in southern Cambodia, we give several examples of how one can use different types of soft data to improve model design, calibrate and validate the model, and assess the realism of the model output. A rainfall-runoff model was coupled to an irrigation reservoir, allowing the use of additional and unconventional data. The model was mainly forced with remote sensing data, and local knowledge was used to constrain the parameters. Model realism assessment was done using data from surveys. This resulted in a successful reconstruction of the reservoir dynamics, and revealed the different hydrological characteristics of the two topographical classes. We do not present a generic approach that can be transferred to other ungauged catchments, but we aim to show how clever model design and alternative data acquisition can result in a valuable hydrological model for ungauged catchments. [1] Sivapalan, M., Takeuchi, K., Franks, S., Gupta, V., Karambiri, H., Lakshmi, V., et al. (2003). IAHS decade on predictions in ungauged basins (PUB), 2003-2012: shaping an exciting future for the hydrological sciences. Hydrol. Sci. J. 48, 857-880. doi: 10.1623/hysj.48.6.857.51421 [2] van Emmerik, T., Mulder, G., Eilander, D., Piet, M. and Savenije, H. (2015). Predicting the ungauged basin: model validation and realism assessment

  10. Single Derivation Fragmented QRS Can Predict Poor Prognosis in Successfully Revascularized Acute STEMI Patients.

    Science.gov (United States)

    Tanriverdi, Zulkif; Dursun, Huseyin; Colluoglu, Tugce; Kaya, Dayimi

    2017-07-20

    QRS fragmentation (fQRS) is classically defined as the presence of slurred QRS morphology in at least two contiguous leads, and its prognostic importance has been shown in ST elevation myocardial infarction (STEMI). However, no study has investigated the significance of single lead fQRS (sl-fQRS) in surface electrocardiography (ECG). To evaluate whether sl-fQRS is as valuable as classical fQRS in patients with acute STEMI who had successful revascularization with primary percutaneous coronary intervention (pPCI). We included 330 patients with a first STEMI who had been successfully revascularized with pPCI. The patient's electrocardiography was obtained in the first 48 hours, and the patients were divided into three groups according to the absence of fQRS (no-fQRS); fQRS presence in a single lead (sl-fQRS); and ≥2 leads with fQRS (classical fQRS). In-hospital mortality was significantly higher both in patients with sl-fQRS and in patients with ≥ 2 leads with fQRS compared to patients with no-fQRS. In ROC curve analysis, ≥ 1 leads with fQRS yielded a sensitivity of 75% and specificity of 57.4% for the prediction of in-hospital mortality. Multivariate analysis showed that sl-fQRS is an independent predictor of in-hospital mortality (OR: 3.989, 95% CI: 1.237-12.869, p = 0.021). Although the concept of at least two derivations is mentioned for the classical definition of fQRS, our study showed that fQRS in only one lead is also associated with poor outcomes. Therefore, ≥1 leads with fQRS can be useful when describing the patients under high cardiac risk in acute STEMI. A fragmentação do QRS (fQRS) é classicamente definida como a presença de morfologia empastada do QRS em pelo menos duas derivações contíguas e sua importância prognóstica tem sido demonstrada no infarto do miocárdio com elevação do ST (STEMI). No entanto, nenhum estudo investigou a significância do fQRS de derivação única (sl-fQRS) no eletrocardiograma (ECG). Avaliar se o sl

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

    Science.gov (United States)

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

    2016-09-01

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

  12. Determinants of Business Success – Theoretical Model and Empirical Verification

    Directory of Open Access Journals (Sweden)

    Kozielski Robert

    2016-12-01

    Full Text Available Market knowledge, market orientation, learning competencies, and a business performance were the key issues of the research project conducted in the 2006 study. The main findings identified significant relationships between the independent variables (market knowledge, market orientation, learning competencies and the dependent variables (business success. A partial correlation analysis indicated that a business success primarily relies on organisational learning competencies. Organisational learning competencies, to a large extent (almost 60%, may be explained by the level of corporate market knowledge and market orientation. The aim of the paper is to evaluate to what extent the relationships between the variables are still valid. The research was based on primary and secondary data sources. The major field of the research was carried out in the form of quantitative studies. The results of the 2014 study are consistent with the previous (2006 results.

  13. Effective amygdala-prefrontal connectivity predicts individual differences in successful emotion regulation.

    Science.gov (United States)

    Morawetz, Carmen; Bode, Stefan; Baudewig, Juergen; Heekeren, Hauke R

    2016-12-20

    The ability to voluntarily regulate our emotional response to threatening and highly arousing stimuli by using cognitive reappraisal strategies is essential for our mental and physical well-being. This might be achieved by prefrontal brain regions (e.g., inferior frontal gyrus, IFG) down-regulating activity in the amygdala. It is unknown, to which degree effective connectivity within the emotion-regulation network is linked to individual differences in reappraisal skills. Using psychophysiological interaction (PPI) analyses of functional magnetic resonance imaging data, we examined changes in inter-regional connectivity between the amygdala and IFG with other brain regions during reappraisal of emotional responses and used emotion regulation success as an explicit regressor. During down-regulation of emotion, reappraisal success correlated with effective connectivity between IFG with dorsolateral, dorsomedial and ventromedial prefrontal cortex (PFC). During up-regulation of emotion, effective coupling between IFG with anterior cingulate cortex, dorsomedial and ventromedial PFC as well as the amygdala correlated with reappraisal success. Activity in the amygdala covaried with activity in lateral and medial prefrontal regions during the up-regulation of emotion and correlated with reappraisal success. These results suggest that successful reappraisal is linked to changes in effective connectivity between two systems, prefrontal cognitive control regions and regions crucially involved in emotional evaluation.

  14. Estimating the magnitude of prediction uncertainties for the APLE model

    Science.gov (United States)

    Models are often used to predict phosphorus (P) loss from agricultural fields. While it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study, we conduct an uncertainty analysis for the Annual P ...

  15. Predicting lower mantle heterogeneity from 4-D Earth models

    Science.gov (United States)

    Flament, Nicolas; Williams, Simon; Müller, Dietmar; Gurnis, Michael; Bower, Dan J.

    2016-04-01

    The Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs), approximately ˜15000 km in diameter and 500-1000 km high, located under Africa and the Pacific Ocean. The spatial stability and chemical nature of these LLSVPs are debated. Here, we compare the lower mantle structure predicted by forward global mantle flow models constrained by tectonic reconstructions (Bower et al., 2015) to an analysis of five global tomography models. In the dynamic models, spanning 230 million years, slabs subducting deep into the mantle deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour (Rayleigh number Ra), mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify a set of equally-spaced points (average separation ˜0.45°) on the Earth's surface into two groups of points with similar variations in present-day temperature between 1000-2800 km depth, for each model case. Below ˜2400 km depth, this procedure reveals a high-temperature cluster in which mantle temperature is significantly larger than ambient and a low-temperature cluster in which mantle temperature is lower than ambient. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the African and Pacific LLSVPs revealed by a similar cluster analysis of five tomography models (Lekic et al., 2012). Model success is quantified by computing the accuracy and sensitivity of the predicted temperature clusters in predicting the low-velocity cluster obtained from tomography (Lekic et al., 2012). In these cases, the accuracy varies between 0.61-0.80, where a value of 0.5 represents the random case, and the sensitivity ranges between 0.18-0.83. The largest accuracies and sensitivities are obtained for models with Ra ≈ 5 x 107, no asthenosphere (or an asthenosphere restricted to the oceanic domain), and a

  16. The Quantum Atomic Model "Electronium": A Successful Teaching Tool.

    Science.gov (United States)

    Budde, Marion; Niedderer, Hans; Scott, Philip; Leach, John

    2002-01-01

    Focuses on the quantum atomic model Electronium. Outlines the Bremen teaching approach in which this model is used, and analyzes the learning of two students as they progress through the teaching unit. (Author/MM)

  17. Performance prediction model for distributed applications on multicore clusters

    CSIR Research Space (South Africa)

    Khanyile, NP

    2012-07-01

    Full Text Available Distributed processing offers a way of successfully dealing with computationally demanding applications such as scientific problems. Over the years, researchers have investigated ways to predict the performance of parallel algorithms. Amdahl’s law...

  18. Prediction of Catastrophes: an experimental model

    CERN Document Server

    Peters, Randall D; Pomeau, Yves

    2012-01-01

    Catastrophes of all kinds can be roughly defined as short duration-large amplitude events following and followed by long periods of "ripening". Major earthquakes surely belong to the class of 'catastrophic' events. Because of the space-time scales involved, an experimental approach is often difficult, not to say impossible, however desirable it could be. Described in this article is a "laboratory" setup that yields data of a type that is amenable to theoretical methods of prediction. Observations are made of a critical slowing down in the noisy signal of a solder wire creeping under constant stress. This effect is shown to be a fair signal of the forthcoming catastrophe in both of two dynamical models. The first is an "abstract" model in which a time dependent quantity drifts slowly but makes quick jumps from time to time. The second is a realistic physical model for the collective motion of dislocations (the Ananthakrishna set of equations for creep). Hope thus exists that similar changes in the response to ...

  19. Predictive modeling of low solubility semiconductor alloys

    Science.gov (United States)

    Rodriguez, Garrett V.; Millunchick, Joanna M.

    2016-09-01

    GaAsBi is of great interest for applications in high efficiency optoelectronic devices due to its highly tunable bandgap. However, the experimental growth of high Bi content films has proven difficult. Here, we model GaAsBi film growth using a kinetic Monte Carlo simulation that explicitly takes cation and anion reactions into account. The unique behavior of Bi droplets is explored, and a sharp decrease in Bi content upon Bi droplet formation is demonstrated. The high mobility of simulated Bi droplets on GaAsBi surfaces is shown to produce phase separated Ga-Bi droplets as well as depressions on the film surface. A phase diagram for a range of growth rates that predicts both Bi content and droplet formation is presented to guide the experimental growth of high Bi content GaAsBi films.

  20. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  1. Leptogenesis in minimal predictive seesaw models

    Science.gov (United States)

    Björkeroth, Fredrik; de Anda, Francisco J.; de Medeiros Varzielas, Ivo; King, Stephen F.

    2015-10-01

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the "atmospheric" and "solar" neutrino masses with Yukawa couplings to ( ν e , ν μ , ν τ ) proportional to (0, 1, 1) and (1, n, n - 2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A 4 vacuum alignment provides the required Yukawa structures with n = 3, while a {{Z}}_9 symmetry fixes the relatives phase to be a ninth root of unity.

  2. Time series analysis as input for clinical predictive modeling: Modeling cardiac arrest in a pediatric ICU

    Directory of Open Access Journals (Sweden)

    Kennedy Curtis E

    2011-10-01

    Full Text Available Abstract Background Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. Methods We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Results Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1 selecting candidate variables; 2 specifying measurement parameters; 3 defining data format; 4 defining time window duration and resolution; 5 calculating latent variables for candidate variables not directly measured; 6 calculating time series features as latent variables; 7 creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8

  3. Sperm swimming velocity predicts competitive fertilization success in the green swordtail Xiphophorus helleri.

    Directory of Open Access Journals (Sweden)

    Clelia Gasparini

    Full Text Available Sperm competition is expected to favour the evolution of traits that influence the performance of sperm when they compete to fertilize a female's eggs. While there is considerable evidence that selection favours increases in sperm numbers, much less is known about how sperm quality contributes towards competitive fertilization success. Here, we determine whether variation in sperm quality influences competitive fertilization success in the green swordtail Xiphophorus helleri, a highly promiscuous livebearing fish. We use artificial insemination as a method of controlled sperm delivery and show that sperm swimming velocity is the primary determinant of fertilization success when ejaculates from two males compete to fertilize a female's eggs. By contrast, we found no evidence that sperm length had any effect on siring success. We also found no evidence that pre- and postcopulatory sexual traits were phenotypically integrated in this species, suggesting that the previous observation that reproductive skew favours males with high mating rates is unlikely to be due to any direct association between sperm quality and male sexual ornamentation.

  4. Academic Achievement and Emotional Intelligence: Predicting the Successful Transition from High School to University

    Science.gov (United States)

    Parker, James D. A.; Duffy, Jon M.; Wood, Laura M.; Bond, Barbara J.; Hogan, Marjorie J.

    2005-01-01

    This study examined the impact of emotional intelligence (EI) on the successful transition from high school to university. The short form of the Emotional Quotient Inventory (EQ-i) was completed by 1,426 first-year students attending four different universities within the first week of classes (September). At the end of the academic year (May),…

  5. Use of Standardized Test Scores to Predict Success in a Computer Applications Course

    Science.gov (United States)

    Harris, Robert V.; King, Stephanie B.

    2016-01-01

    The purpose of this study was to see if a relationship existed between American College Testing (ACT) scores (i.e., English, reading, mathematics, science reasoning, and composite) and student success in a computer applications course at a Mississippi community college. The study showed that while the ACT scores were excellent predictors of…

  6. Do Institutional Attributes Predict Individuals' Degree Success at Two-Year Colleges?

    Science.gov (United States)

    Goble, Lisbeth J.; Rosenbaum, James E.; Stephan, Jennifer L.

    2008-01-01

    This article explores institutional attributes that matter for two-year college students and how they vary by different subpopulations of students, with an eye toward understanding what institutional attributes better support the success of underprepared students. In particular, the authors address the following questions: (1) Which institutional…

  7. Cognitive ability is heritable and predicts the success of an alternative mating tactic.

    Science.gov (United States)

    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.

  8. Using Learning Analytics to Predict (and Improve) Student Success: A Faculty Perspective

    Science.gov (United States)

    Dietz-Uhler, Beth; Hurn, Janet E.

    2013-01-01

    Learning analytics is receiving increased attention, in part because it offers to assist educational institutions in increasing student retention, improving student success, and easing the burden of accountability. Although these large-scale issues are worthy of consideration, faculty might also be interested in how they can use learning analytics…

  9. Predicting Successful College Experiences: Evidence from a First Year Retention Program

    Science.gov (United States)

    Noble, Kimberly; Flynn, Nicole T.; Lee, James D.; Hilton, David

    2008-01-01

    Research indicates that programs designed to target first year students increase their likelihood of success during that year and their chances of completing an undergraduate education (Bureau & Rromrey, 1994; Conner & Colton, 1999). Theoretically, such programs should help in part because they foster integration into campus communities…

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

    Science.gov (United States)

    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…

  11. How Do Different Aspects of Self-Regulation Predict Successful Adaptation to School?

    Science.gov (United States)

    Neuenschwander, Regula; Rothlisberger, Marianne; Cimeli, Patrizia; Roebers, Claudia M.

    2012-01-01

    Self-regulation plays an important role in successful adaptation to preschool and school contexts as well as in later academic achievement. The current study relates different aspects of self-regulation such as temperamental effortful control and executive functions (updating, inhibition, and shifting) to different aspects of adaptation to school…

  12. The Occupational Success of the Retarded: Critical Factors, Predictive Tests and Remedial Techniques.

    Science.gov (United States)

    Laradon Hall Occupational Center, Denver, CO.

    A job success rating scale was developed by use with 60 mentally retarded young adults (IQ's under 80, ages from 18 to 30), their parents, and employers. Interviews and job histories were analyzed; an experimental test battery measuring 101 aptitude and personality variables was administered. By factor analysis and statistical procedures, 17 tests…

  13. Can magnetic resonance imaging predict the success of parturition in oxytocin-induced pregnant women?

    Energy Technology Data Exchange (ETDEWEB)

    Sabir, N.; Akkemik, B. [Pamukkale Univ., Denizli (Turkey). Dept. of Radiagnostics; Dicle, O. [Dokuz Eyluel Univ., Izmir (Turkey). Dept. of Radiagnostics; Yurdakul, B. [Pamukkale Univ., Denizli (Turkey). Dept. of Obstetrics and Gynecology

    2000-05-01

    The aim of this study was to assess whether magnetic resonance imaging could predict the outcome of attempted vaginal delivery in a group of pregnant women whose parturition had to be induced by oxytocin. The signal intensity and morphology alterations in the cervix of 21 full-term pregnant women were analyzed before the induction of parturition. T2-weighted gradient echo sequences were utilized and signal intensity in the cervix was measured from the anterior and posterior lips of the cervix. An index indicating the brightness range of the cervix was formulated to overcome the effects of the individual intensity changes. Imaging features including the signal intensity and the evidence of effacement were correlated with the actual type of delivery performed. Images were also assessed visually by two independent radiologists. Statistical analysis of brightness indexes that were considered to have a predictive value as an indicator for possible delivery was not significant. However, visually assessed signal intensity of the cervix correlated strongly with the type of delivery. Effacement itself was the most reliable parameter in predicting the progress of the delivery. In conclusion, MR imaging seems to be useful for predicting normal parturition in full-term pregnant women who need oxytocin induction. However, the presence of effacement seems to be a more reliable and practical parameter that will be preferred in that prediction. (orig.)

  14. Triglyceride/HDL ratio as a screening tool for predicting success at reducing anti-diabetic medications following weight loss.

    Directory of Open Access Journals (Sweden)

    Ghanshyam Palamaner Subash Shantha

    Full Text Available BACKGROUND AND OBJECTIVES: Intentional weight loss, by reducing insulin resistance, results in both better glycemic control and decreased need for anti-diabetic medications. However, not everyone who is successful with weight loss is able to reduce anti-diabetic medication use. In this retrospective cohort study, we assessed the predictive accuracy of baseline triglyceride (TGL/HDL ratio, a marker of insulin resistance, to screen patients for success in reducing anti-diabetic medication use with weight loss. METHODS: Case records of 121 overweight and obese attendees at two outpatient weight management centers were analyzed. The weight loss intervention consisted of a calorie-restricted diet (~1000Kcal/day deficit, a behavior modification plan, and a plan for increasing physical activity. RESULTS: Mean period of follow-up was 12.5 ± 3.5 months. By study exit, mean weight loss and mean HbA1c% reduction were 15.4 ± 5.5 kgs and 0.5 ± 0.2% respectively. 81 (67% in the study cohort achieved at least 1 dose reduction of any anti-diabetic medication. Tests for predictive accuracy of baseline TGL/HDL ratio ≤ 3 to determine success with dose reductions of anti-diabetic medications showed a sensitivity, specificity, positive predictive value, negative predictive value, area under the curve, likelihood ratio (LR + and LR-of 81, 83, 90, 70, 78, 4.8 and 0.2, respectively. Reproducibility of TGL/HDL ratio was acceptable. CONCLUSION: TGL/HDL ratio shows promise as an effective screening tool to determine success with dose reductions of anti-diabetic medications. The results of our study may inform the conduct of a systematic review using data from prior weight loss trials.

  15. Triglyceride/HDL ratio as a screening tool for predicting success at reducing anti-diabetic medications following weight loss.

    Science.gov (United States)

    Palamaner Subash Shantha, Ghanshyam; Kumar, Anita Ashok; Kahan, Scott; Irukulla, Pavan Kumar; Cheskin, Lawrence Jay

    2013-01-01

    Intentional weight loss, by reducing insulin resistance, results in both better glycemic control and decreased need for anti-diabetic medications. However, not everyone who is successful with weight loss is able to reduce anti-diabetic medication use. In this retrospective cohort study, we assessed the predictive accuracy of baseline triglyceride (TGL)/HDL ratio, a marker of insulin resistance, to screen patients for success in reducing anti-diabetic medication use with weight loss. Case records of 121 overweight and obese attendees at two outpatient weight management centers were analyzed. The weight loss intervention consisted of a calorie-restricted diet (~1000Kcal/day deficit), a behavior modification plan, and a plan for increasing physical activity. Mean period of follow-up was 12.5 ± 3.5 months. By study exit, mean weight loss and mean HbA1c% reduction were 15.4 ± 5.5 kgs and 0.5 ± 0.2% respectively. 81 (67%) in the study cohort achieved at least 1 dose reduction of any anti-diabetic medication. Tests for predictive accuracy of baseline TGL/HDL ratio ≤ 3 to determine success with dose reductions of anti-diabetic medications showed a sensitivity, specificity, positive predictive value, negative predictive value, area under the curve, likelihood ratio (LR) + and LR-of 81, 83, 90, 70, 78, 4.8 and 0.2, respectively. Reproducibility of TGL/HDL ratio was acceptable. TGL/HDL ratio shows promise as an effective screening tool to determine success with dose reductions of anti-diabetic medications. The results of our study may inform the conduct of a systematic review using data from prior weight loss trials.

  16. Comparing model predictions for ecosystem-based management

    DEFF Research Database (Denmark)

    Jacobsen, Nis Sand; Essington, Timothy E.; Andersen, Ken Haste

    2016-01-01

    Ecosystem modeling is becoming an integral part of fisheries management, but there is a need to identify differences between predictions derived from models employed for scientific and management purposes. Here, we compared two models: a biomass-based food-web model (Ecopath with Ecosim (Ew......E)) and a size-structured fish community model. The models were compared with respect to predicted ecological consequences of fishing to identify commonalities and differences in model predictions for the California Current fish community. We compared the models regarding direct and indirect responses to fishing...... on one or more species. The size-based model predicted a higher fishing mortality needed to reach maximum sustainable yield than EwE for most species. The size-based model also predicted stronger top-down effects of predator removals than EwE. In contrast, EwE predicted stronger bottom-up effects...

  17. Simulating historical landscape dynamics using the landscape fire succession model LANDSUM version 4.0

    Science.gov (United States)

    Robert E. Keane; Lisa M. Holsinger; Sarah D. Pratt

    2006-01-01

    The range and variation of historical landscape dynamics could provide a useful reference for designing fuel treatments on today's landscapes. Simulation modeling is a vehicle that can be used to estimate the range of conditions experienced on historical landscapes. A landscape fire succession model called LANDSUMv4 (LANDscape SUccession Model version 4.0) is...

  18. A Multi-Stage Maturity Model for Long-Term IT Outsourcing Relationship Success

    Science.gov (United States)

    Luong, Ming; Stevens, Jeff

    2015-01-01

    The Multi-Stage Maturity Model for Long-Term IT Outsourcing Relationship Success, a theoretical stages-of-growth model, explains long-term success in IT outsourcing relationships. Research showed the IT outsourcing relationship life cycle consists of four distinct, sequential stages: contract, transition, support, and partnership. The model was…

  19. Nestling erythrocyte resistance to oxidative stress predicts fledging success but not local recruitment in a wild bird.

    Science.gov (United States)

    Losdat, Sylvain; Helfenstein, Fabrice; Blount, Jonathan D; Marri, Viviana; Maronde, Lea; Richner, Heinz

    2013-02-23

    Stressful conditions experienced by individuals during their early development have long-term consequences on various life-history traits such as survival until first reproduction. Oxidative stress has been shown to affect various fitness-related traits and to influence key evolutionary trade-offs but whether an individual's ability to resist oxidative stress in early life affects its survival has rarely been tested. In the present study, we used four years of data obtained from a free-living great tit population (Parus major; n = 1658 offspring) to test whether pre-fledging resistance to oxidative stress, measured as erythrocyte resistance to oxidative stress and oxidative damage to lipids, predicted fledging success and local recruitment. Fledging success and local recruitment, both major correlates of survival, were primarily influenced by offspring body mass prior to fledging. We found that pre-fledging erythrocyte resistance to oxidative stress predicted fledging success, suggesting that individual resistance to oxidative stress is related to short-term survival. However, local recruitment was not influenced by pre-fledging erythrocyte resistance to oxidative stress or oxidative damage. Our results suggest that an individual ability to resist oxidative stress at the offspring stage predicts short-term survival but does not influence survival later in life.

  20. Accuracy of J-CTO Score Derived From Computed Tomography Versus Angiography to Predict Successful Percutaneous Coronary Intervention.

    Science.gov (United States)

    Fujino, Akiko; Otsuji, Satoru; Hasegawa, Katsuyuki; Arita, Toyohiro; Takiuchi, Shin; Fujii, Kenichi; Yabuki, Masanori; Ibuki, Motoaki; Nagayama, Shinya; Ishibuchi, Kasumi; Kashiyama, Toshikazu; Ishii, Rui; Tamaru, Hiroto; Yamamoto, Wataru; Hara, Masahiko; Higashino, Yorihiko

    2017-06-14

    The aim of this study was to compare the ability of conventional versus computed tomography angiography (CTA) to predict procedural success and 30-min wire crossing rates in percutaneous coronary intervention (PCI) for chronic total occlusion (CTO) lesions. Coronary CTA can be used to assess the morphology of CTO lesions. We examined 205 consecutive patients (218 CTO lesions) who underwent coronary CTA pre-PCI. The J-CTO (Multicenter CTO Registry of Japan) score (the sum of the following 5 binary parameters: blunt proximal cap, calcification, bending >45°, and length of occluded segment >20 mm plus previously failed PCI attempt) was calculated using both CTA and conventional coronary angiography and compared. The median patient age was 69 years (interquartile range: 62 to 75 years), 82.4% were male, and a retrograde approach was attempted in 72 (33.0%) cases. The procedural success rate of the CTO-PCI procedures was 82.6%, and 29.4% of cases achieved 30-min wire crossing. The areas under the curve of the CTA-derived J-CTO score for predicting procedural success and 30-min wire crossing were significantly greater than those derived from conventional angiography (0.855 vs. 0.698; p CTO score was a more useful predictor of both procedural success and 30-min wire crossing than the J-CTO score derived from conventional angiography. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

  1. Judgement bias in predicting the success of one's own basketball free throws but not those of others.

    Science.gov (United States)

    Cañal-Bruland, Rouwen; Balch, Lars; Niesert, Loet

    2015-07-01

    Skilled basketball players are supposed to hit more often from the free throw distance than would be predicted by their shooting performances at adjacent distances. This is dubbed an especial skill. In the current study, we examined whether especial skills in free throw performance in basketball map onto especial skills in visually judging the success of basketball free throws. In addition, we tested whether this effect would be present in those who predict their own shots but absent in those who judge shots performed by another person. Eight skilled basketball players were coupled with eight equally skilled players, and performed 150 set shots from five different distances (including the free throw distance) while the yoked partner observed the shots. At the moment of ball release, the performers' and the observers' vision were synchronously occluded using liquid-crystal occlusion goggles, and both independently judged whether the shot was successful or not. Results did not replicate an especial skill effect in shooting performance. Based on signal detection theory (SDT) measures (d' and criterion c), results also revealed no especial skill for visually discriminating successful from unsuccessful shots at the foul line when compared to other distances. However, players showed an especial skill judgement bias towards judging balls 'in' at the foul line, but not at other distances. Importantly, this bias was only present in those who judged the success of their own shots, but not in those who judged the shots performed by someone else.

  2. The Carerra Model: A Success in Pregnancy Prevention.

    Science.gov (United States)

    Elling, Duane M.

    This document outlines the development, evaluation, and replication of the Carrera model for pregnancy prevention. The Carerra model helps teens avoid pregnancy by empowering them to develop and reach personal goals, and by providing them with information on sexual issues, including abstinence, contraception, and the consequences of sexual…

  3. Remaining Useful Lifetime (RUL - Probabilistic Predictive Model

    Directory of Open Access Journals (Sweden)

    Ephraim Suhir

    2011-01-01

    Full Text Available Reliability evaluations and assurances cannot be delayed until the device (system is fabricated and put into operation. Reliability of an electronic product should be conceived at the early stages of its design; implemented during manufacturing; evaluated (considering customer requirements and the existing specifications, by electrical, optical and mechanical measurements and testing; checked (screened during manufacturing (fabrication; and, if necessary and appropriate, maintained in the field during the product’s operation Simple and physically meaningful probabilistic predictive model is suggested for the evaluation of the remaining useful lifetime (RUL of an electronic device (system after an appreciable deviation from its normal operation conditions has been detected, and the increase in the failure rate and the change in the configuration of the wear-out portion of the bathtub has been assessed. The general concepts are illustrated by numerical examples. The model can be employed, along with other PHM forecasting and interfering tools and means, to evaluate and to maintain the high level of the reliability (probability of non-failure of a device (system at the operation stage of its lifetime.

  4. A Predictive Model of Geosynchronous Magnetopause Crossings

    CERN Document Server

    Dmitriev, A; Chao, J -K

    2013-01-01

    We have developed a model predicting whether or not the magnetopause crosses geosynchronous orbit at given location for given solar wind pressure Psw, Bz component of interplanetary magnetic field (IMF) and geomagnetic conditions characterized by 1-min SYM-H index. The model is based on more than 300 geosynchronous magnetopause crossings (GMCs) and about 6000 minutes when geosynchronous satellites of GOES and LANL series are located in the magnetosheath (so-called MSh intervals) in 1994 to 2001. Minimizing of the Psw required for GMCs and MSh intervals at various locations, Bz and SYM-H allows describing both an effect of magnetopause dawn-dusk asymmetry and saturation of Bz influence for very large southward IMF. The asymmetry is strong for large negative Bz and almost disappears when Bz is positive. We found that the larger amplitude of negative SYM-H the lower solar wind pressure is required for GMCs. We attribute this effect to a depletion of the dayside magnetic field by a storm-time intensification of t...

  5. Predictive modeling for EBPC in EBDW

    Science.gov (United States)

    Zimmermann, Rainer; Schulz, Martin; Hoppe, Wolfgang; Stock, Hans-Jürgen; Demmerle, Wolfgang; Zepka, Alex; Isoyan, Artak; Bomholt, Lars; Manakli, Serdar; Pain, Laurent

    2009-10-01

    We demonstrate a flow for e-beam proximity correction (EBPC) to e-beam direct write (EBDW) wafer manufacturing processes, demonstrating a solution that covers all steps from the generation of a test pattern for (experimental or virtual) measurement data creation, over e-beam model fitting, proximity effect correction (PEC), and verification of the results. We base our approach on a predictive, physical e-beam simulation tool, with the possibility to complement this with experimental data, and the goal of preparing the EBPC methods for the advent of high-volume EBDW tools. As an example, we apply and compare dose correction and geometric correction for low and high electron energies on 1D and 2D test patterns. In particular, we show some results of model-based geometric correction as it is typical for the optical case, but enhanced for the particularities of e-beam technology. The results are used to discuss PEC strategies, with respect to short and long range effects.

  6. Predicting First-Year Student Success in Learning Communities: The Power of Pre-College Variables

    Science.gov (United States)

    Sperry, Rita A.

    2015-01-01

    The study used pre-college variables in the prediction of retention and probation status of first-year students in learning communities at a regional public university in South Texas. The correlational study employed multivariate analyses on data collected from the campus registrar about three consecutive cohorts (N = 4,215) of first-year…

  7. Predicting Academic Success in Higher Education: What's More Important than Being Smart?

    Science.gov (United States)

    Kappe, Rutger; van der Flier, Henk

    2012-01-01

    This study investigated the combined predictive validity of intelligence and personality factors on multiple measures of academic achievement. Students in a college of higher education in the Netherlands (N = 137) completed a survey that measured intelligence, the Big Five personality traits, motivation, and four specific personality traits.…

  8. Predicting Academic Success in Higher Education: What's More Important than Being Smart?

    Science.gov (United States)

    Kappe, Rutger; van der Flier, Henk

    2012-01-01

    This study investigated the combined predictive validity of intelligence and personality factors on multiple measures of academic achievement. Students in a college of higher education in the Netherlands (N = 137) completed a survey that measured intelligence, the Big Five personality traits, motivation, and four specific personality traits.…

  9. Predicting Academic Success and Technological Literacy in Secondary Education: A Learning Styles Perspective

    Science.gov (United States)

    Avsec, Stanislav; Szewczyk-Zakrzewska, Agnieszka

    2017-01-01

    This paper aims to investigate the predictive validity of learning styles on academic achievement and technological literacy (TL). For this purpose, secondary school students were recruited (n = 150). An empirical research design was followed where the TL test was used with a learning style inventory measuring learning orientation, processing…

  10. Testing a Model of Teaching for Anxiety and Success for English Language Teaching

    Science.gov (United States)

    Önem, Evrim; Ergenç, Iclal

    2013-01-01

    Much research has shown that there is a negative relationship between high levels of anxiety and success for English language teaching. This paper aimed to test a model of teaching for anxiety and success in English language teaching to affect anxiety and success levels at the same time in a control-experiment group with pre- and post-test study…

  11. A combination of dopamine genes predicts success by professional Wall Street traders.

    Directory of Open Access Journals (Sweden)

    Steve Sapra

    Full Text Available What determines success on Wall Street? This study examined if genes affecting dopamine levels of professional traders were associated with their career tenure. Sixty professional Wall Street traders were genotyped and compared to a control group who did not trade stocks. We found that distinct alleles of the dopamine receptor 4 promoter (DRD4P and catecholamine-O-methyltransferase (COMT that affect synaptic dopamine were predominant in traders. These alleles are associated with moderate, rather than very high or very low, levels of synaptic dopamine. The activity of these alleles correlated positively with years spent trading stocks on Wall Street. Differences in personality and trading behavior were also correlated with allelic variants. This evidence suggests there may be a genetic basis for the traits that make one a successful trader.

  12. A combination of dopamine genes predicts success by professional Wall Street traders.

    Science.gov (United States)

    Sapra, Steve; Beavin, Laura E; Zak, Paul J

    2012-01-01

    What determines success on Wall Street? This study examined if genes affecting dopamine levels of professional traders were associated with their career tenure. Sixty professional Wall Street traders were genotyped and compared to a control group who did not trade stocks. We found that distinct alleles of the dopamine receptor 4 promoter (DRD4P) and catecholamine-O-methyltransferase (COMT) that affect synaptic dopamine were predominant in traders. These alleles are associated with moderate, rather than very high or very low, levels of synaptic dopamine. The activity of these alleles correlated positively with years spent trading stocks on Wall Street. Differences in personality and trading behavior were also correlated with allelic variants. This evidence suggests there may be a genetic basis for the traits that make one a successful trader.

  13. A Model for Physician Leadership Development and Succession Planning.

    Science.gov (United States)

    Dubinsky, Isser; Feerasta, Nadia; Lash, Rick

    2015-01-01

    Although the presence of physicians in formal leadership positions has often been limited to roles of department chiefs, MAC chairs, etc., a growing number of organizations are recruiting physicians to other leadership positions (e.g., VP, CEO) where their involvement is being genuinely sought and valued. While physicians have traditionally risen to leadership positions based on clinical excellence or on a rotational basis, truly effective physician leadership that includes competencies such as strategic planning, budgeting, mentoring, network development, etc., is essential to support organizational goals, improve performance and overall efficiency as well as ensuring the quality of care. In this context, the authors have developed a physician leader development and succession planning matrix and supporting toolkit to assist hospitals in identifying and nurturing the next generation of physician leaders.

  14. Successful public-private partnerships: The NYPD shield model.

    Science.gov (United States)

    Amadeo, Vincent; Iannone, Stephen

    2017-12-01

    This article will identify the challenges that post 9/11 law enforcement faces regarding privatepublic partnerships and describe in detail the NYPD Shield programme, created to combat those challenges. Recommendations made by the 911 Commission included the incorporation of the private sector into future homeland security strategies. One such strategy is NYPD Shield. This programme is a nationally recognized award-winning public-private partnership dedicated to providing counterterrorism training and information sharing with government agencies, non-government organizations, private businesses, and the community. Information is shared through several platforms that include a dedicated website, instruction of counterterrorism training curricula, e-mail alerts, intelligence assessments and the hosting of quarterly conferences. This article also details how the NYPD Shield is providing its successful template to other law enforcement agencies enabling them to initiate similar programmes in their respective jurisdictions, and in doing so joining a National Shield Network.

  15. Model for predicting mountain wave field uncertainties

    Science.gov (United States)

    Damiens, Florentin; Lott, François; Millet, Christophe; Plougonven, Riwal

    2017-04-01

    Studying the propagation of acoustic waves throughout troposphere requires knowledge of wind speed and temperature gradients from the ground up to about 10-20 km. Typical planetary boundary layers flows are known to present vertical low level shears that can interact with mountain waves, thereby triggering small-scale disturbances. Resolving these fluctuations for long-range propagation problems is, however, not feasible because of computer memory/time restrictions and thus, they need to be parameterized. When the disturbances are small enough, these fluctuations can be described by linear equations. Previous works by co-authors have shown that the critical layer dynamics that occur near the ground produces large horizontal flows and buoyancy disturbances that result in intense downslope winds and gravity wave breaking. While these phenomena manifest almost systematically for high Richardson numbers and when the boundary layer depth is relatively small compare to the mountain height, the process by which static stability affects downslope winds remains unclear. In the present work, new linear mountain gravity wave solutions are tested against numerical predictions obtained with the Weather Research and Forecasting (WRF) model. For Richardson numbers typically larger than unity, the mesoscale model is used to quantify the effect of neglected nonlinear terms on downslope winds and mountain wave patterns. At these regimes, the large downslope winds transport warm air, a so called "Foehn" effect than can impact sound propagation properties. The sensitivity of small-scale disturbances to Richardson number is quantified using two-dimensional spectral analysis. It is shown through a pilot study of subgrid scale fluctuations of boundary layer flows over realistic mountains that the cross-spectrum of mountain wave field is made up of the same components found in WRF simulations. The impact of each individual component on acoustic wave propagation is discussed in terms of

  16. Specification of variables predictive of victories in the sport of boxing: II. Further characterization of previous success.

    Science.gov (United States)

    Warnick, Jason E; Warnick, Kyla

    2009-02-01

    Previous success, i.e., performance in the preceding bout and total number of wins and losses, was predictive of victory. Clarification of this effect was sought in examining whether the prior performance against a particular opponent or in a common location would be predictive of a victory in a bout against that opponent or in that locale. The career records of 739 male professional boxers who participated in contests held in the USA in November 2007 were collected from the BoxRec online database. Chi-squared tests and logistic regression analyses indicated that performance in the preceding bout, prior performance against the same opponent, and prior performance in a particular location were predictive of the outcome in a current bout.

  17. Problematic healthcare insurance: a comparison with successful models.

    Science.gov (United States)

    Matusitz, Jonathan

    2014-01-01

    This article analyzes the experiences of problematic health insurance models in Canada, France, Germany, and Spain, based on news reports, facts, and data. Those nations were selected because they represent typical socialist economies with nationalized health insurance systems. Major findings are that (a) these health insurance systems are not cheap, (b) they sometimes contribute to governments' own financial deficits, (c) there are significant restrictions for access to private health care, (d) many services are not covered, and (e) the insurance plans create conflict as to what treatment options are offered. The author also provides a description of the current U.S. health care insurance model and compares it with the European socialist model. What comes subsequently is an examination of two ideal models of efficient health care insurance: the ones of Switzerland and the Netherlands. This analysis ends with a discussion section that provides implications for U.S. health care and offers suggestions for future research.

  18. Cross-Paradigm Simulation Modeling: Challenges and Successes

    Science.gov (United States)

    2011-12-01

    This paper addresses the broad topic area of cross-paradigm simulation modeling with a focus on the discrete-event, system dynamics and agent-based...used in simulation modeling are also discussed, and the implications of these mechanisms for each paradigm is explored....and definitions are presented. The difference between the process-oriented worldview and the event-oriented worldview within discrete-event simulation

  19. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  20. RFI modeling and prediction approach for SATOP applications: RFI prediction models

    Science.gov (United States)

    Nguyen, Tien M.; Tran, Hien T.; Wang, Zhonghai; Coons, Amanda; Nguyen, Charles C.; Lane, Steven A.; Pham, Khanh D.; Chen, Genshe; Wang, Gang

    2016-05-01

    This paper describes a technical approach for the development of RFI prediction models using carrier synchronization loop when calculating Bit or Carrier SNR degradation due to interferences for (i) detecting narrow-band and wideband RFI signals, and (ii) estimating and predicting the behavior of the RFI signals. The paper presents analytical and simulation models and provides both analytical and simulation results on the performance of USB (Unified S-Band) waveforms in the presence of narrow-band and wideband RFI signals. The models presented in this paper will allow the future USB command systems to detect the RFI presence, estimate the RFI characteristics and predict the RFI behavior in real-time for accurate assessment of the impacts of RFI on the command Bit Error Rate (BER) performance. The command BER degradation model presented in this paper also allows the ground system operator to estimate the optimum transmitted SNR to maintain a required command BER level in the presence of both friendly and un-friendly RFI sources.

  1. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to unders

  2. Predictive Power of Primary and Secondary School Success Criterion on Transition to Higher Education Examination Scores

    Directory of Open Access Journals (Sweden)

    Atilla ÖZDEMİR

    2016-12-01

    Full Text Available It is seen that education has a significant effect that changes an individual’s life in our country in which education is a way of moving up the social ladder. In order to continue to a higher education program after graduating from high school, students have to succeed in transition to higher education examination. Thus, the entrance exam is an important factor to determine the future of the students. In our country, middle school grades and high school grade point average that is added to university placement score are also determinants. When spiral structure of our curriculum is considered, it is expected that related courses’ grades at middle school will predict the scores obtained from the first stage of transition to higher education exam (YGS. Since high school grade point average forms university placement score, being aware of how related courses’ achievement scores at secondary school predict raw scores of YGS subtests is significant in terms of our education system’s feedback and integrity. As a result, observing students’ achievement scores in related courses during their middle and high school education longitudinally and predicting raw scores on the subtests of the first stage of university entrance exam, YGS, from middle school and high scool achievement scores are substantial with regards to provide feedback to our education system. Because of those reasons, the predictive power of 7th - 12th grade year-end grade point averages ofstudents who took YGS in 2013 on their 2013 YGS subtests’ raw scvores is examined. Students who took YGS exam in Ankara province at 2012-2013 school year formed the aimed population of this study and 533 students who took YGS exam in 2013 in Altındağ district of Ankara formed target population of the study. Data was obtained from 533 students at three different schools in Altındağ district of Ankara province. Stepwise multiple regression analysis was used to answer research questions

  3. Successful Aging: A Psychosocial Resources Model for Very Old Adults

    Directory of Open Access Journals (Sweden)

    G. Kevin Randall

    2012-01-01

    Full Text Available Objectives. Using data from the first two phases of the Georgia Centenarian Study, we proposed a latent factor structure for the Duke OARS domains: Economic Resources, Mental Health, Activities of Daily Living, Physical Health, and Social Resources. Methods. Exploratory and confirmatory factor analyses were conducted on two waves of the Georgia Centenarian Study to test a latent variable measurement model of the five resources; nested model testing was employed to assess the final measurement model for equivalency of factor structure over time. Results. The specified measurement model fit the data well at Time 1. However, at Time 2, Social Resources only had one indicator load significantly and substantively. Supplemental analyses demonstrated that a model without Social Resources adequately fit the data. Factorial invariance over time was confirmed for the remaining four latent variables. Discussion. This study’s findings allow researchers and clinicians to reduce the number of OARS questions asked of participants. This has practical implications because increased difficulties with hearing, vision, and fatigue in older adults may require extended time or multiple interviewer sessions to complete the battery of OARS questions.

  4. PREDICTING MOVIE SUCCESS FROM SEARCH QUERY USING SUPPORT VECTOR REGRESSION METHOD

    Directory of Open Access Journals (Sweden)

    Chanseung Lee

    2016-01-01

    Full Text Available Query data from search engines can provide many insights about the human behavior. Therefore, massive data resulting from human interactions may offer a new perspective on the behavior of the market. By analyzing Google query database for search terms, we present a method of analyzing large numbers of search queries to predict outcomes such as movie incomes. Our results illustrate the potential of combining extensive behavioral data sets that offer a better understanding of collective human behavior.

  5. Achievement goals and championship performance: Predicting absolute performance and qualification success

    OpenAIRE

    Stoeber, Joachim; Crombie, Rosanna

    2010-01-01

    Objectives: Research on athletes’ achievement goals has suggested that the contrast between performance approach and performance avoidance goals (performance approach-avoidance contrast) is a significant predictor of sports performance. However, so far only two studies investigating triathletes found that performance approach-avoidance contrast predicted sports performance in competitions. The present study aims to replicate and expand on these findings with a diverse sample of track and fiel...

  6. Human experts' and a fuzzy model's predictions of outcomes of scoliosis treatment: a comparative analysis.

    Science.gov (United States)

    Chalmers, Eric; Pedrycz, Witold; Lou, Edmond

    2015-03-01

    Brace treatment is the most commonly used nonsurgical treatment for adolescents with idiopathic scoliosis. However, brace treatment is not always successful and the factors influencing its success are not completely clear. This makes treatment outcome difficult to predict. A computer model which can accurately predict treatment outcomes could potentially provide valuable treatment recommendations. This paper describes a fuzzy system that includes a prediction model and a decision support engine. The model was constructed using conditional fuzzy c-means clustering to discover patterns in retrospective patient data. The model's ability to predict treatment outcome was compared to the ability of eight Scoliosis experts. The model and experts each predicted treatment outcome retrospectively for 28 braced patients, and these predictions were compared to the actual outcomes. The model outperformed all but one expert individually and performed similarly to the experts as a group. These results suggest that the fuzzy model is capable of providing meaningful treatment recommendations. This study offers the first model for this application whose performance has been shown to be at or above the human expert level.

  7. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  8. Predictability of the Indian Ocean Dipole in the coupled models

    Science.gov (United States)

    Liu, Huafeng; Tang, Youmin; Chen, Dake; Lian, Tao

    2017-03-01

    In this study, the Indian Ocean Dipole (IOD) predictability, measured by the Indian Dipole Mode Index (DMI), is comprehensively examined at the seasonal time scale, including its actual prediction skill and potential predictability, using the ENSEMBLES multiple model ensembles and the recently developed information-based theoretical framework of predictability. It was found that all model predictions have useful skill, which is normally defined by the anomaly correlation coefficient larger than 0.5, only at around 2-3 month leads. This is mainly because there are more false alarms in predictions as leading time increases. The DMI predictability has significant seasonal variation, and the predictions whose target seasons are boreal summer (JJA) and autumn (SON) are more reliable than that for other seasons. All of models fail to predict the IOD onset before May and suffer from the winter (DJF) predictability barrier. The potential predictability study indicates that, with the model development and initialization improvement, the prediction of IOD onset is likely to be improved but the winter barrier cannot be overcome. The IOD predictability also has decadal variation, with a high skill during the 1960s and the early 1990s, and a low skill during the early 1970s and early 1980s, which is very consistent with the potential predictability. The main factors controlling the IOD predictability, including its seasonal and decadal variations, are also analyzed in this study.

  9. [AIDS prevention in Germany - a successful model in crisis].

    Science.gov (United States)

    Rosenbrock, R

    2007-04-01

    The rising number of new HIV infections in Germany, particularly among men who have sex with men, raises the question whether the previously successful prevention strategy should be revised. This strategy has been based on a New Public Health approach which arose from the specific historical context in Europe at the start of the epidemic. The hallmarks of this approach are: the active involvement of the target groups; the central role of non-governmental organizations; the combination of population level and targeted, context specific interventions; and an emphasis on social integration and voluntary participation in the work with target group members. Current challenges include: changes in risk perception (at least in part due to the availability of more effective treatments); a diversification of prevention behavioral strategies among target group members; the formation of new sexual subcultures and target groups; as well as changes in hard-to-reach populations such as immigrants and people of lower socioeconomic status. In order to meet these challenges the following measures are necessary: an increased investment in prevention research (with a particular focus on interventions specific to social contexts in which risk behavior is increasing); further development of the institutional infrastructure for prevention, including the full implementation of UNAIDS guidelines for national prevention strategies; and improving the prevention work of local AIDS service organizations and public health authorities through an increase in funding and the implementation of quality assurance measures based on participatory action research.

  10. Predicting Success at Marine Security Guard (MSG) School Utilizing the Headquarters Master File (HMF)

    Science.gov (United States)

    1993-03-01

    omander or HQM assessing the probability of success That any varticula Marine would have at the school. Examples were jiven detailing how to do this...Electronics Schools," CRC 362-Vol.1, Center for Naval Analyses, Arlington, Virginia, October 1978. Shelton, David L., "The Marine Security Guard Program...34 vol.74, no.6, p.73- 7 7, Marine Corps Gazette, Quantico, Virginia, June 1990. 108 Shelton, David L., ’"Thoughts on The MSG roqr.," no.6, p.15-i

  11. Teaching Modeling with Partial Differential Equations: Several Successful Approaches

    Science.gov (United States)

    Myers, Joseph; Trubatch, David; Winkel, Brian

    2008-01-01

    We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…

  12. Successively refined models for crack tip plasticity in polymer blends

    NARCIS (Netherlands)

    Pijnenburg, KGW; Seelig, T; van der Giessen, E

    2005-01-01

    This paper is concerned with a comparative study of different, partly complementary micromechanical models for crack tip plasticity in polymer-rubber blends. It is experimentally well established that interspersion of micron-scale rubber particles into a polymer matrix can lead to a significantly en

  13. e-Learning Success Model: An Information Systems Perspective

    Science.gov (United States)

    Lee-Post, Anita

    2009-01-01

    This paper reports the observations made and experience gained from developing and delivering an online quantitative methods course for Business undergraduates. Inspired by issues and challenges experienced in developing the online course, a model is advanced to address the question of how to guide the design, development, and delivery of…

  14. Teaching Modeling with Partial Differential Equations: Several Successful Approaches

    Science.gov (United States)

    Myers, Joseph; Trubatch, David; Winkel, Brian

    2008-01-01

    We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…

  15. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  16. Leptogenesis in minimal predictive seesaw models

    Energy Technology Data Exchange (ETDEWEB)

    Björkeroth, Fredrik [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom); Anda, Francisco J. de [Departamento de Física, CUCEI, Universidad de Guadalajara,Guadalajara (Mexico); Varzielas, Ivo de Medeiros; King, Stephen F. [School of Physics and Astronomy, University of Southampton,Southampton, SO17 1BJ (United Kingdom)

    2015-10-15

    We estimate the Baryon Asymmetry of the Universe (BAU) arising from leptogenesis within a class of minimal predictive seesaw models involving two right-handed neutrinos and simple Yukawa structures with one texture zero. The two right-handed neutrinos are dominantly responsible for the “atmospheric” and “solar” neutrino masses with Yukawa couplings to (ν{sub e},ν{sub μ},ν{sub τ}) proportional to (0,1,1) and (1,n,n−2), respectively, where n is a positive integer. The neutrino Yukawa matrix is therefore characterised by two proportionality constants with their relative phase providing a leptogenesis-PMNS link, enabling the lightest right-handed neutrino mass to be determined from neutrino data and the observed BAU. We discuss an SU(5) SUSY GUT example, where A{sub 4} vacuum alignment provides the required Yukawa structures with n=3, while a ℤ{sub 9} symmetry fixes the relatives phase to be a ninth root of unity.

  17. QSPR Models for Octane Number Prediction

    Directory of Open Access Journals (Sweden)

    Jabir H. Al-Fahemi

    2014-01-01

    Full Text Available Quantitative structure-property relationship (QSPR is performed as a means to predict octane number of hydrocarbons via correlating properties to parameters calculated from molecular structure; such parameters are molecular mass M, hydration energy EH, boiling point BP, octanol/water distribution coefficient logP, molar refractivity MR, critical pressure CP, critical volume CV, and critical temperature CT. Principal component analysis (PCA and multiple linear regression technique (MLR were performed to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The results of PCA explain the interrelationships between octane number and different variables. Correlation coefficients were calculated using M.S. Excel to examine the relationship between multiple variables of the above parameters and the octane number of hydrocarbons. The data set was split into training of 40 hydrocarbons and validation set of 25 hydrocarbons. The linear relationship between the selected descriptors and the octane number has coefficient of determination (R2=0.932, statistical significance (F=53.21, and standard errors (s =7.7. The obtained QSPR model was applied on the validation set of octane number for hydrocarbons giving RCV2=0.942 and s=6.328.

  18. Usefulness of the presenting electrocardiogram in predicting successful reperfusion with streptokinase in acute myocardial infarction.

    Science.gov (United States)

    Wong, C K; French, J K; Aylward, P E; Frey, M J; Adgey, A A; White, H D

    1999-01-15

    The presenting electrocardiogram may contain information indicating the probability of successful reperfusion. The relation between 3 parameters in the presenting electrocardiogram (pathologic Q waves, T-wave inversion, and the slope of ST elevation) and Thrombolysis in Myocardial Infarction trial (TIMI) grade 3 flow in the infarct-related artery was assessed angiographically 90 minutes after beginning streptokinase in 362 patients. TIMI grade 3 flow was more common in patients without Q waves (55%) than in those with Q waves (35%; p wave inversion (50%) than in those with T-wave inversion (30%; p waves and T-wave inversion had TIMI grade 3 flow, compared with 50% of the remaining patients (p waves (p wave inversion (p = 0.06). Among patients treated after 3 hours, TIMI grade 3 flow was seen in 38% of those without versus 30% of those with Q waves (p = NS), and in 38% of those without versus 23% of those with T-wave inversion (p waves, the time from the onset of chest pain to treatment, and age were independent predictors of TIMI grade 3 flow. Pathologic Q waves in the presenting electrocardiogram provide valuable information as to the probability of achieving successful reperfusion following administration of streptokinase, and may be helpful for triage of patients to alternative reperfusion strategies, including percutaneous revascularization.

  19. Prediction of pregnancy success rate through in vitro fertilization based on maternal age

    Directory of Open Access Journals (Sweden)

    Soegiharto Soebijanto

    2009-12-01

    Full Text Available Aim To evaluate the correlation between the success of pregnancy through in vitro fertilization and maternal age. Methods Assessment of pregnancy was performed in eight in vitro fertilization centers in Indonesia: Harapan Kita Pediatric and Obstetric Hospital from 1997 to 2001, and seven in vitro fertilization centers in Indonesia. Follicular induction was performed through the long protocol, short protocol and natural cycle. Insemination was performed through ICSI (intra cytoplasmic sperm injection on petri dish. Spermatozoa were obtained through masturbation, testicular biopsy and epididimical biopsy. A successful pregnancy was indicated chemically, with the presence of fetal heart beat and the birth of a baby (take home baby. Results There was a 34% pregnancy rate for the age group below 30 years, 33.75% for those between 31 and 35 years olds, and 26% for the age group 36 to 40 years old, and 8% for the age group above 40 years. Conclusion The higher the maternal age, the lower pregnancy rate. In other words, the higher the maternal age, the higher the rate of miscarriage. (Med J Indones 2009; 18: 244-8Keywords: pregnancy, in vitro fertilization

  20. Adaptation to stroke using a model of successful aging.

    Science.gov (United States)

    Donnellan, C; Hevey, D; Hickey, A; O'Neill, D

    2012-01-01

    The process of adaptation to the physical and psychosocial consequences after stroke is a major challenge for many individuals affected. The aim of this study was to examine if stroke patients within 1 month of admission (n = 153) and followed up at 1 year (n = 107) engage in selection, optimization, and compensation (SOC) adaptive strategies and the relationship of these strategies with functional ability, health-related quality of life (HRQOL) and depression 1 year later. Adaptive strategies were measured using a 15-item SOC questionnaire. Internal and external resources were assessed including recovery locus of control, stroke severity, and socio-demographics. Outcome measures were the Stroke Specific Quality of Life Questionnaire (SS-QoL), the Nottingham Extended Activities of Daily Living Scale and the Depression Subscale of the Hospital Anxiety and Depression Scale. Findings indicated that stroke patients engaged in the use of SOC strategies but the use of these strategies were not predictive of HRQOL, functional ability or depression 1 year after stroke. The use of SOC strategies were not age specific and were consistent over time, with the exception of the compensation subscale. Results indicate that SOC strategies may potentially be used in response to loss regulation after stroke and that an individual's initial HRQOL functional ability, levels of depression and socio-economic status that are important factors in determining outcome 1 year after stroke. A stroke-specific measure of SOC may be warranted in order to detect significant differences in determining outcomes for a stroke population.