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  1. 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

  2. Development of a Predictive Model for Induction Success of Labour

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    Cristina Pruenza

    2018-03-01

    Full Text Available Induction of the labour process is an extraordinarily common procedure used in some pregnancies. Obstetricians face the need to end a pregnancy, for medical reasons usually (maternal or fetal requirements or less frequently, social (elective inductions for convenience. The success of induction procedure is conditioned by a multitude of maternal and fetal variables that appear before or during pregnancy or birth process, with a low predictive value. The failure of the induction process involves performing a caesarean section. This project arises from the clinical need to resolve a situation of uncertainty that occurs frequently in our clinical practice. Since the weight of clinical variables is not adequately weighted, we consider very interesting to know a priori the possibility of success of induction to dismiss those inductions with high probability of failure, avoiding unnecessary procedures or postponing end if possible. We developed a predictive model of induced labour success as a support tool in clinical decision making. Improve the predictability of a successful induction is one of the current challenges of Obstetrics because of its negative impact. The identification of those patients with high chances of failure, will allow us to offer them better care improving their health outcomes (adverse perinatal outcomes for mother and newborn, costs (medication, hospitalization, qualified staff and patient perceived quality. Therefore a Clinical Decision Support System was developed to give support to the Obstetricians. In this article, we had proposed a robust method to explore and model a source of clinical information with the purpose of obtaining all possible knowledge. Generally, in classification models are difficult to know the contribution that each attribute provides to the model. We had worked in this direction to offer transparency to models that may be considered as black boxes. The positive results obtained from both the

  3. Improving student success using predictive models and data visualisations

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    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. Developing a Model and Applications for Probabilities of Student Success: A Case Study of Predictive Analytics

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    Calvert, Carol Elaine

    2014-01-01

    This case study relates to distance learning students on open access courses. It demonstrates the use of predictive analytics to generate a model of the probabilities of success and retention at different points, or milestones, in a student journey. A core set of explanatory variables has been established and their varying relative importance at…

  5. Successful modeling?

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    Lomnitz, Cinna

    Tichelaar and Ruff [1989] propose to “estimate model variance in complicated geophysical problems,” including the determination of focal depth in earthquakes, by means of unconventional statistical methods such as bootstrapping. They are successful insofar as they are able to duplicate the results from more conventional procedures.

  6. Use the predictive models to explore the key factors affecting phytoplankton succession in Lake Erhai, China.

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    Zhu, Rong; Wang, Huan; Chen, Jun; Shen, Hong; Deng, Xuwei

    2018-01-01

    Increasing algae in Lake Erhai has resulted in frequent blooms that have not only led to water ecosystem degeneration but also seriously influenced the quality of the water supply and caused extensive damage to the local people, as the lake is a water resource for Dali City. Exploring the key factors affecting phytoplankton succession and developing predictive models with easily detectable parameters for phytoplankton have been proven to be practical ways to improve water quality. To this end, a systematic survey focused on phytoplankton succession was conducted over 2 years in Lake Erhai. The data from the first study year were used to develop predictive models, and the data from the second year were used for model verification. The seasonal succession of phytoplankton in Lake Erhai was obvious. The dominant groups were Cyanobacteria in the summer, Chlorophyta in the autumn and Bacillariophyta in the winter. The developments and verification of predictive models indicated that compared to phytoplankton biomass, phytoplankton density is more effective for estimating phytoplankton variation in Lake Erhai. CCA (canonical correlation analysis) indicated that TN (total nitrogen), TP (total phosphorus), DO (dissolved oxygen), SD (Secchi depth), Cond (conductivity), T (water temperature), and ORP (oxidation reduction potential) had significant influences (p < 0.05) on the phytoplankton community. The CCA of the dominant species found that Microcystis was significantly influenced by T. The dominant Chlorophyta, Psephonema aenigmaticum and Mougeotia, were significantly influenced by TN. All results indicated that TN and T were the two key factors driving phytoplankton succession in Lake Erhai.

  7. Predictive models of objective oropharyngeal OSA surgery outcomes: Success rate and AHI reduction ratio.

    Science.gov (United States)

    Choi, Ji Ho; Lee, Jae Yong; Cha, Jaehyung; Kim, Kangwoo; Hong, Seung-No; Lee, Seung Hoon

    2017-01-01

    The aim of this study was to develop a predictive model of objective oropharyngeal obstructive sleep apnea (OSA) surgery outcomes including success rate and apnea-hypopnea index (AHI) reduction ratio in adult OSA patients. Retrospective outcome research. All subjects with OSA who underwent oropharyngeal and/or nasal surgery and were followed for at least 3 months were enrolled in this study. Demographic, anatomical [tonsil size (TS) and palate-tongue position (PTP) grade (Gr)], and polysomnographic parameters were analyzed. The AHI reduction ratio (%) was defined as [(postoperative AHI-preoperative AHI) x 100 / postoperative AHI], and surgical success was defined as a ≥ 50% reduction in preoperative AHI with a postoperative AHI predictive equation by Forward Selection likelihood ratio (LR) logistic regression analysis was: [Formula: see text]The best predictive equation according to stepwise multiple linear regression analysis was: [Formula: see text] (TS/PTP Gr = 1 if TS/PTP Gr 3 or 4, TS/PTP Gr = 0 if TS/PTP Gr 1 or 2). The predictive models for oropharyngeal surgery described in this study may be useful for planning surgical treatments and improving objective outcomes in adult OSA patients.

  8. Predictive models of objective oropharyngeal OSA surgery outcomes: Success rate and AHI reduction ratio.

    Directory of Open Access Journals (Sweden)

    Ji Ho Choi

    Full Text Available The aim of this study was to develop a predictive model of objective oropharyngeal obstructive sleep apnea (OSA surgery outcomes including success rate and apnea-hypopnea index (AHI reduction ratio in adult OSA patients.Retrospective outcome research.All subjects with OSA who underwent oropharyngeal and/or nasal surgery and were followed for at least 3 months were enrolled in this study. Demographic, anatomical [tonsil size (TS and palate-tongue position (PTP grade (Gr], and polysomnographic parameters were analyzed. The AHI reduction ratio (% was defined as [(postoperative AHI-preoperative AHI x 100 / postoperative AHI], and surgical success was defined as a ≥ 50% reduction in preoperative AHI with a postoperative AHI < 20.A total of 156 consecutive OSAS adult patients (mean age ± SD = 38.9 ± 9.6, M / F = 149 / 7 were included in this study. The best predictive equation by Forward Selection likelihood ratio (LR logistic regression analysis was: [Formula: see text]The best predictive equation according to stepwise multiple linear regression analysis was: [Formula: see text] (TS/PTP Gr = 1 if TS/PTP Gr 3 or 4, TS/PTP Gr = 0 if TS/PTP Gr 1 or 2.The predictive models for oropharyngeal surgery described in this study may be useful for planning surgical treatments and improving objective outcomes in adult OSA patients.

  9. Importance of prediction outlier diagnostics in determining a successful inter-vendor multivariate calibration model transfer.

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    Guenard, Robert D; Wehlburg, Christine M; Pell, Randy J; Haaland, David M

    2007-07-01

    This paper reports on the transfer of calibration models between Fourier transform near-infrared (FT-NIR) instruments from four different manufacturers. The piecewise direct standardization (PDS) method is compared with the new hybrid calibration method known as prediction augmented classical least squares/partial least squares (PACLS/PLS). The success of a calibration transfer experiment is judged by prediction error and by the number of samples that are flagged as outliers that would not have been flagged as such if a complete recalibration were performed. Prediction results must be acceptable and the outlier diagnostics capabilities must be preserved for the transfer to be deemed successful. Previous studies have measured the success of a calibration transfer method by comparing only the prediction performance (e.g., the root mean square error of prediction, RMSEP). However, our study emphasizes the need to consider outlier detection performance as well. As our study illustrates, the RMSEP values for a calibration transfer can be within acceptable range; however, statistical analysis of the spectral residuals can show that differences in outlier performance can vary significantly between competing transfer methods. There was no statistically significant difference in the prediction error between the PDS and PACLS/PLS methods when the same subset sample selection method was used for both methods. However, the PACLS/PLS method was better at preserving the outlier detection capabilities and therefore was judged to have performed better than the PDS algorithm when transferring calibrations with the use of a subset of samples to define the transfer function. The method of sample subset selection was found to make a significant difference in the calibration transfer results using the PDS algorithm, while the transfer results were less sensitive to subset selection when the PACLS/PLS method was used.

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

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    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.

  11. Prediction Modeling for Academic Success in Professional Master's Athletic Training Programs

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    Bruce, Scott L.; Crawford, Elizabeth; Wilkerson, Gary B.; Rausch, David; Dale, R. Barry; Harris, Martina

    2016-01-01

    Context: A common goal of professional education programs is to recruit the students best suited for the professional career. Selection of students can be a difficult process, especially if the number of qualified candidates exceeds the number of available positions. The ability to predict academic success in any profession has been a challenging…

  12. Predicting Commissary Store Success

    Science.gov (United States)

    2014-12-01

    goods, such as butter, flour, meat and cheese. Commissary pricing for some stores (Offut Air Force Base, Travis Air Force Base and Fort Belvoir...maximum 200 words) What external factors affect a commissruy store ’ s success? This thesis analyzes the impact of demographics, local prices and...their dependents-Reservists and National Guru·d members had no impact. Equally important was the price differential between commercial grocety

  13. An excitable cortex and memory model successfully predicts new pseudopod dynamics.

    Directory of Open Access Journals (Sweden)

    Robert M Cooper

    Full Text Available Motile eukaryotic cells migrate with directional persistence by alternating left and right turns, even in the absence of external cues. For example, Dictyostelium discoideum cells crawl by extending distinct pseudopods in an alternating right-left pattern. The mechanisms underlying this zig-zag behavior, however, remain unknown. Here we propose a new Excitable Cortex and Memory (EC&M model for understanding the alternating, zig-zag extension of pseudopods. Incorporating elements of previous models, we consider the cell cortex as an excitable system and include global inhibition of new pseudopods while a pseudopod is active. With the novel hypothesis that pseudopod activity makes the local cortex temporarily more excitable--thus creating a memory of previous pseudopod locations--the model reproduces experimentally observed zig-zag behavior. Furthermore, the EC&M model makes four new predictions concerning pseudopod dynamics. To test these predictions we develop an algorithm that detects pseudopods via hierarchical clustering of individual membrane extensions. Data from cell-tracking experiments agrees with all four predictions of the model, revealing that pseudopod placement is a non-Markovian process affected by the dynamics of previous pseudopods. The model is also compatible with known limits of chemotactic sensitivity. In addition to providing a predictive approach to studying eukaryotic cell motion, the EC&M model provides a general framework for future models, and suggests directions for new research regarding the molecular mechanisms underlying directional persistence.

  14. Developing and validating a model to predict the success of an IHCS implementation: the Readiness for Implementation Model

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    Gustafson, David H; Hawkins, Robert P; Brennan, Patricia F; Dinauer, Susan; Johnson, Pauley R; Siegler, Tracy

    2010-01-01

    Objective To develop and validate the Readiness for Implementation Model (RIM). This model predicts a healthcare organization's potential for success in implementing an interactive health communication system (IHCS). The model consists of seven weighted factors, with each factor containing five to seven elements. Design Two decision-analytic approaches, self-explicated and conjoint analysis, were used to measure the weights of the RIM with a sample of 410 experts. The RIM model with weights was then validated in a prospective study of 25 IHCS implementation cases. Measurements Orthogonal main effects design was used to develop 700 conjoint-analysis profiles, which varied on seven factors. Each of the 410 experts rated the importance and desirability of the factors and their levels, as well as a set of 10 different profiles. For the prospective 25-case validation, three time-repeated measures of the RIM scores were collected for comparison with the implementation outcomes. Results Two of the seven factors, ‘organizational motivation’ and ‘meeting user needs,’ were found to be most important in predicting implementation readiness. No statistically significant difference was found in the predictive validity of the two approaches (self-explicated and conjoint analysis). The RIM was a better predictor for the 1-year implementation outcome than the half-year outcome. Limitations The expert sample, the order of the survey tasks, the additive model, and basing the RIM cut-off score on experience are possible limitations of the study. Conclusion The RIM needs to be empirically evaluated in institutions adopting IHCS and sustaining the system in the long term. PMID:20962135

  15. Collegiate Student-Athletes' Academic Success: Academic Communication Apprehension's Impact on Prediction Models

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    James, Kai'Iah A.

    2010-01-01

    This dissertation study examines the impact of traditional and non-cognitive variables on the academic prediction model for a sample of collegiate student-athletes. Three hundred and fifty-nine NCAA Division IA male and female student-athletes, representing 13 sports, including football and Men's and Women's Basketball provided demographic…

  16. Validation of prediction model for successful vaginal birth after Cesarean delivery based on sonographic assessment of hysterotomy scar.

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    Baranov, A; Salvesen, K Å; Vikhareva, O

    2018-02-01

    To validate a prediction model for successful vaginal birth after Cesarean delivery (VBAC) based on sonographic assessment of the hysterotomy scar, in a Swedish population. Data were collected from a prospective cohort study. We recruited non-pregnant women aged 18-35 years who had undergone one previous low-transverse Cesarean delivery at ≥ 37 gestational weeks and had had no other uterine surgery. Participants who subsequently became pregnant underwent transvaginal ultrasound examination of the Cesarean hysterotomy scar at 11 + 0 to 13 + 6 and at 19 + 0 to 21 + 6 gestational weeks. Thickness of the myometrium at the thinnest part of the scar area was measured. After delivery, information on pregnancy outcome was retrieved from hospital records. Individual probabilities of successful VBAC were calculated using a previously published model. Predicted individual probabilities were divided into deciles. For each decile, observed VBAC rates were calculated. To assess the accuracy of the prediction model, receiver-operating characteristics curves were constructed and the areas under the curves (AUC) were calculated. Complete sonographic data were available for 120 women. Eighty (67%) women underwent trial of labor after Cesarean delivery (TOLAC) with VBAC occurring in 70 (88%) cases. The scar was visible in all 80 women at the first-trimester scan and in 54 (68%) women at the second-trimester scan. AUC was 0.44 (95% CI, 0.28-0.60) among all women who underwent TOLAC and 0.51 (95% CI, 0.32-0.71) among those with the scar visible sonographically at both ultrasound examinations. The prediction model demonstrated poor accuracy for prediction of successful VBAC in our Swedish population. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

  17. Toward a Predictive Model of Community College Student Success in Blended Classes

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    Volchok, Edward

    2018-01-01

    This retrospective study evaluates early semester predictors of whether or not community college students will successfully complete blended or hybrid courses. These predictors are available to faculty by the fourth week of the semester. Success is defined as receiving a grade of C- or higher. Failure is defined as a grade below a C- or a…

  18. Long-term success and failure with SG is predictable by 3 months: a multivariate model using simple office markers.

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    Cottam, Austin; Billing, Josiah; Cottam, Daniel; Billing, Peter; Cottam, Samuel; Zaveri, Hinali; Surve, Amit

    2017-08-01

    Despite being the most common surgery in the United States, little is known about predicting weight loss success and failure with sleeve gastrectomy (SG). Papers that have been published are inconclusive. We decided to use multivariate analysis from 2 practices to design a model to predict weight loss outcomes using data widely available to any surgical practice at 3 months to determine weight loss outcomes at 1 year. Two private practices in the United States. A retrospective review of 613 patients from 2 bariatric institutions were included in this study. Co-morbidities and other preoperative characteristics were gathered, and %EWL was calculated for 1, 3, and 12 months. Excess weight loss (%EWL)failure. Multiple variate analysis was used to find factors that affect %EWL at 12 months. Preoperative sleep apnea, preoperative diabetes, %EWL at 1 month, and %EWL at 3 months all affect %EWL at 1 year. The positive predictive value and negative predictive value of our model was 72% and 91%, respectively. Sensitivity and specificity were 71% and 91%, respectively. One-year results of the SG can be predicted by diabetes, sleep apnea, and weight loss velocity at 3 months postoperatively. This can help surgeons direct surgical or medical interventions for patients at 3 months rather than at 1 year or beyond. Copyright © 2017 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  19. Testing a Model of Environmental Risk and Protective Factors to Predict Middle and High School Students' Academic Success

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    Peters, S. Colby; Woolley, Michael E.

    2015-01-01

    Data from the School Success Profile generated by 19,228 middle and high school students were organized into three broad categories of risk and protective factors--control, support, and challenge--to examine the relative and combined power of aggregate scale scores in each category so as to predict academic success. It was hypothesized that higher…

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

    NARCIS (Netherlands)

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

    2016-01-01

    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

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

    NARCIS (Netherlands)

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

    2016-01-01

    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

  2. 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

  3. Limited Sampling Strategy for Accurate Prediction of Pharmacokinetics of Saroglitazar: A 3-point Linear Regression Model Development and Successful Prediction of Human Exposure.

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    Joshi, Shuchi N; Srinivas, Nuggehally R; Parmar, Deven V

    2018-03-01

    Our aim was to develop and validate the extrapolative performance of a regression model using a limited sampling strategy for accurate estimation of the area under the plasma concentration versus time curve for saroglitazar. Healthy subject pharmacokinetic data from a well-powered food-effect study (fasted vs fed treatments; n = 50) was used in this work. The first 25 subjects' serial plasma concentration data up to 72 hours and corresponding AUC 0-t (ie, 72 hours) from the fasting group comprised a training dataset to develop the limited sampling model. The internal datasets for prediction included the remaining 25 subjects from the fasting group and all 50 subjects from the fed condition of the same study. The external datasets included pharmacokinetic data for saroglitazar from previous single-dose clinical studies. Limited sampling models were composed of 1-, 2-, and 3-concentration-time points' correlation with AUC 0-t of saroglitazar. Only models with regression coefficients (R 2 ) >0.90 were screened for further evaluation. The best R 2 model was validated for its utility based on mean prediction error, mean absolute prediction error, and root mean square error. Both correlations between predicted and observed AUC 0-t of saroglitazar and verification of precision and bias using Bland-Altman plot were carried out. None of the evaluated 1- and 2-concentration-time points models achieved R 2 > 0.90. Among the various 3-concentration-time points models, only 4 equations passed the predefined criterion of R 2 > 0.90. Limited sampling models with time points 0.5, 2, and 8 hours (R 2 = 0.9323) and 0.75, 2, and 8 hours (R 2 = 0.9375) were validated. Mean prediction error, mean absolute prediction error, and root mean square error were prediction of saroglitazar. The same models, when applied to the AUC 0-t prediction of saroglitazar sulfoxide, showed mean prediction error, mean absolute prediction error, and root mean square error model predicts the exposure of

  4. Predicting Success Study Using Students GPA Category

    Directory of Open Access Journals (Sweden)

    Awan Setiawan

    2015-06-01

    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

  5. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Lindemann, Stephen R.; Mobberley, Jennifer M.; Cole, Jessica K.; Markillie, L. M.; Taylor, Ronald C.; Huang, Eric; Chrisler, William B.; Wiley, H. S.; Lipton, Mary S.; Nelson, William C.; Fredrickson, James K.; Romine, Margaret F.

    2017-06-13

    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.

  7. 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.

  8. Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study).

    Science.gov (United States)

    Thomas, Diana M; Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

    2015-03-01

    Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing loss were also calculated. Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. © 2015 American Society for Nutrition.

  9. 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.

  10. 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...... 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...

  11. Prediction of Success of External Cephalic Version after 36 Weeks

    NARCIS (Netherlands)

    Kok, Marjolein; van der Steeg, Jan Willem; van der Post, Joris A. M.; Mol, Ben W. J.

    2011-01-01

    We aimed to develop a predictive model for the chance of a successful external cephalic version (ECV). We performed a prospective cohort study of women with a singleton fetus in breech presentation with a gestational age of 36 weeks or more. Data on parity, maternal age, body mass index, ethnicity,

  12. Predicting Succession under Conditions of Enrollment Decline.

    Science.gov (United States)

    Berger, Michael A.

    Three possible explanations for superintendent succession focus on poor administrative performance, district response strategies, and the politics of the chief executive's relationship with the school board. To analyze succession in the context of declining enrollment, a case study survey was conducted of 56 school districts whose peak enrollment…

  13. Evaluating supervised machine learning algorithms to predict recreational fishing success : A multiple species, multiple algorithms approach

    OpenAIRE

    Wikström, Johan

    2015-01-01

    This report examines three different machine learning algorithms and their effectiveness for predicting recreational fishing success. Recreational fishing is a huge pastime but reliable methods of predicting fishing success have largely been missing. This report compares random forest, linear regression and multilayer perceptron to a reasonable baseline model for predicting fishing success. Fishing success is defined as the expected weight of the fish caught. Previous reports have mainly focu...

  14. 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. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  15. 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.

  16. 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

  17. Predicting Success in a Graduate Psychology Program

    Science.gov (United States)

    Kordinak, S. Thomas; Kercher, Melanie; Harman, Marsha J.; Bruce, A. Jerry

    2009-01-01

    The Graduate Record Examination (GRE) General Tests and GRE advanced Psychology (PSYGRE) Test were correlated with several measures of success in our graduate program at Sam Houston State University including some specific courses. Significant correlations were obtained for several of these measures, but the PSYGRE provided incremental validity…

  18. Development of a nomogram for prediction of successful membrane sweeping.

    Science.gov (United States)

    Haj Yahya, Rani; Ezra, Yossef; Berghella, Vincenzo; Herzberg, Shmuel; Safrai, Myriam; Reuveni Salzman, Adi; Abu Ahmad, Wiessam; Kabiri, Doron

    2017-11-28

    To evaluate the association of obstetric, maternal, and fetal variables with successful membrane sweeping and to develop a calculator that can predict spontaneous delivery within 24 hours of membrane sweeping. This secondary analysis of the STRIP-G Study included all singleton term parturients who underwent membrane sweeping in a tertiary center in October 2011 to July 2013. Primary end point was a 24-hour time interval from sweeping to delivery. Women who delivered without formal induction within the 24-hour interval were included in the "successful sweeping group". Stepwise logistic regression was used to calculate the adjusted odds ratio (aOR) for successful membrane sweeping and to create the calculator. The predictive power of the calculator was evaluated by area under the curve (AUC) of the receiver operating characteristic (ROC) curve and by Nagelkerke R-square. The model was validated by the Hosmer-Lemeshow test and by these validation measures: sensitivity, specificity, and positive and negative predictive value. We analyzed data from 542 women. Parity (aOR = 1.66, 95% confidence interval [CI] 1.1-2.54), cervical dilation (aOR = 3.33, 95%CI 2.04-5.44), and gestational age (aOR = 1.44, 95%CI 1.21-1.72) were independent predictors of spontaneous delivery during the first 24 hours. A cross validation procedure showed that the calculator had a good accuracy (68%). A simple calculator based on maternal age, parity, gestational age, cervical dilatation, effacement and station, can accurately predict the chances of delivery within 24 hours of membrane sweeping. This may assist physicians better counseling of women regarding the likelihood of successful membrane sweeping.

  19. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    refining formal, inductive predictive models is the quality of the archaeological and environmental data. To build models efficiently, relevant...geomorphology, and historic information . Lessons Learned: The original model was focused on the identification of prehistoric resources. This...system but uses predictive modeling informally . For example, there is no probability for buried archaeological deposits on the Burton Mesa, but there is

  20. Altruism predicts mating success in humans.

    Science.gov (United States)

    Arnocky, Steven; Piché, Tina; Albert, Graham; Ouellette, Danielle; Barclay, Pat

    2017-05-01

    In order for non-kin altruism to evolve, altruists must receive fitness benefits for their actions that outweigh the costs. Several researchers have suggested that altruism is a costly signal of desirable qualities, such that it could have evolved by sexual selection. In two studies, we show that altruism is broadly linked with mating success. In Study 1, participants who scored higher on a self-report altruism measure reported they were more desirable to the opposite sex, as well as reported having more sex partners, more casual sex partners, and having sex more often within relationships. Sex moderated some of these relationships, such that altruism mattered more for men's number of lifetime and casual sex partners. In Study 2, participants who were willing to donate potential monetary winnings (in a modified dictator dilemma) reported having more lifetime sex partners, more casual sex partners, and more sex partners over the past year. Men who were willing to donate also reported having more lifetime dating partners. Furthermore, these patterns persisted, even when controlling for narcissism, Big Five personality traits, and socially desirable responding. These results suggest that altruists have higher mating success than non-altruists and support the hypothesis that altruism is a sexually selected costly signal of difficult-to-observe qualities. © 2016 The British Psychological Society.

  1. Predicting academic success among deaf college students.

    Science.gov (United States)

    Convertino, Carol M; Marschark, Marc; Sapere, Patricia; Sarchet, Thomastine; Zupan, Megan

    2009-01-01

    For both practical and theoretical reasons, educators and educational researchers seek to determine predictors of academic success for students at different levels and from different populations. Studies involving hearing students at the postsecondary level have documented significant predictors of success relating to various demographic factors, school experience, and prior academic attainment. Studies involving deaf and hard-of-hearing students have focused primarily on younger students and variables such as degree of hearing loss, use of cochlear implants, educational placement, and communication factors-although these typically are considered only one or two at a time. The present investigation utilizes data from 10 previous experiments, all using the same paradigm, in an attempt to discern significant predictors of readiness for college (utilizing college entrance examination scores) and classroom learning at the college level (utilizing scores from tests in simulated classrooms). Academic preparation was a clear and consistent predictor in both domains, but the audiological and communication variables examined were not. Communication variables that were significant reflected benefits of language flexibility over skills in either spoken language or American Sign Language.

  2. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  3. Predicting success in the tactical air combat party training pipeline.

    Science.gov (United States)

    Kalns, John; Baskin, Jonathan; Reinert, Andrew; Michael, Darren; Santos, Adrienne; Daugherty, Sheena; Wright, James K

    2011-04-01

    To develop a statistical model that predicts the likelihood of success or failure of military training candidates using tests administered before initial skill training as inputs. Data were acquired from candidates before the start of U.S. Air Force Tactical Air Control Party training, including (1) demographic, (2) psychological composition evaluated using Emotional Quotient Inventory, (3) physical performance capability, (4) a physical activity questionnaire, and (5) salivary fatigue biomarker index. A total of 126 candidates were tracked until they either passed or failed the training, and a total of 55 variables were used as inputs for creation of the model. Clustering analysis of the data revealed that only 4 of 55 variables were useful for predicting success or failure. The variables in the order of their importance are as follows: run time, number of miles run per week in the last year, level of salivary fatigue biomarker, and height. The results suggest that simple testing methods can identify candidates at high risk of failure.

  4. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  5. 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.

  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. 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…

  8. Zephyr - the prediction models

    DEFF Research Database (Denmark)

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

    2001-01-01

    utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obatined by state-of-the-art parametric models.......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 Danish...

  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. Disentangling the Predictive Validity of High School Grades for Academic Success in University

    Science.gov (United States)

    Vulperhorst, Jonne; Lutz, Christel; de Kleijn, Renske; van Tartwijk, Jan

    2018-01-01

    To refine selective admission models, we investigate which measure of prior achievement has the best predictive validity for academic success in university. We compare the predictive validity of three core high school subjects to the predictive validity of high school grade point average (GPA) for academic achievement in a liberal arts university…

  11. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-27

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  12. Using landscape disturbance and succession models to support forest management

    Science.gov (United States)

    Eric J. Gustafson; Brian R. Sturtevant; Anatoly S. Shvidenko; Robert M. Scheller

    2010-01-01

    Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and...

  13. Predicting Third Grade Reading Success from Kindergarten Phonological Awareness

    Science.gov (United States)

    Robinson, Stephanie J.

    2013-01-01

    Although phonological awareness (PA) is an essential preliteracy skill with well-established predictive validity for elementary school reading success, previous research indicates that PA intervention does not demonstrate long term effects on reading. The theory of automaticity was the underlying foundation used to understand the importance of…

  14. Predicting Student Success from the "LASSI for Learning Online" (LLO)

    Science.gov (United States)

    Carson, Andrew D.

    2011-01-01

    This study tested the degree to which subscales of the "LASSI for Learning Online" (LLO) (Weinstein & Palmer, 2006), a measure of learning strategies and study skills, predict student success in the form of passing grades, using a combination of large training (N = 4,409) and cross-validation (N = 3,203) samples. Discriminant function analysis…

  15. Use of Admissions Interview Comments to Predict Clinical Clerkship Success.

    Science.gov (United States)

    Baker, Helen Hicks; Dunlap, Margaret Reed

    The use of admission interview comments to predict clinical clerkship success of medical students was evaluated. Narrative comments made by admissions interviewers regarding an applicant's skills and attitudes were coded, as were narrative evaluations of these students during year III of required clerkships in pediatrics and internal medicine in…

  16. How Predictive Analytics and Choice Architecture Can Improve Student Success

    Science.gov (United States)

    Denley, Tristan

    2014-01-01

    This article explores the challenges that students face in navigating the curricular structure of post-secondary degree programs, and how predictive analytics and choice architecture can play a role. It examines Degree Compass, a course recommendation system that successfully pairs current students with the courses that best fit their talents and…

  17. 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.,…

  18. Diaphragmatic excursion: does it predict successful weaning from mechanical ventilation?

    International Nuclear Information System (INIS)

    Hayat, A.; Khalil, A.

    2017-01-01

    To measure the diaphragmatic excursion and its outcome on weani ng from mechanical ventilation. Study Design: Cross-sectional comparative study. Place and Duration of Study: Medical Intensive Care Unit (ICU), Military Hospital (MH), Rawalpindi, Pakistan, from January to December 2014. Methodology: Diaphragmatic excursion (DE) in cm was measured through ultrasound by marking liver and spleen displacement in patients who fulfilled the criteria of removal from ventilatory support. The patients were followed up for 48 hours and classified according to the outcome as successful weaning and weaning failure. Results: Out of 100 cases, 76 patients had a successful weaning while 24 had a failed weaning outcome. At a diaphragmatic excursion of 1.2 cm and more, out of 67 cases, 60 had a successful weaning (89.55%) while 7 cases (10.45%) had a weaning failure. At an excursion of less than 1. 2 cm, 17 out of 33 cases (51.5%) had successful weaning while 16 (48.48%) had weaning failure. At this cut off point (1.2 cm), the sensitivity and specificity for successful weaning were 78.95% and 70.83%, respectively. The positive and negative likelihood ratio (LR) for these values being 2.70 and 0.29, respectively. The positive predictive value was 82.35% and negative predictive value 60.00%. Conclusion: Ultrasonographic measurement of diaphragmatic excursion is a good method for predicting weaning outcome from mechanical ventilation. (author)

  19. Factors predicting successful discontinuation of continuous renal replacement therapy.

    Science.gov (United States)

    Katayama, S; Uchino, S; Uji, M; Ohnuma, T; Namba, Y; Kawarazaki, H; Toki, N; Takeda, K; Yasuda, H; Izawa, J; Tokuhira, N; Nagata, I

    2016-07-01

    This multicentre, retrospective observational study was conducted from January 2010 to December 2010 to determine the optimal time for discontinuing continuous renal replacement therapy (CRRT) by evaluating factors predictive of successful discontinuation in patients with acute kidney injury. Analysis was performed for patients after CRRT was discontinued because of renal function recovery. Patients were divided into two groups according to the success or failure of CRRT discontinuation. In multivariate logistic regression analysis, urine output at discontinuation, creatinine level and CRRT duration were found to be significant variables (area under the receiver operating characteristic curve for urine output, 0.814). In conclusion, we found that higher urine output, lower creatinine and shorter CRRT duration were significant factors to predict successful discontinuation of CRRT.

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

    Science.gov (United States)

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

    2016-08-31

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

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

    Science.gov (United States)

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

    2018-01-01

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

  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. 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

  4. FUZZY MODELING BY SUCCESSIVE ESTIMATION OF RULES ...

    African Journals Online (AJOL)

    This paper presents an algorithm for automatically deriving fuzzy rules directly from a set of input-output data of a process for the purpose of modeling. The rules are extracted by a method termed successive estimation. This method is used to generate a model without truncating the number of fired rules, to within user ...

  5. Are traditional cognitive tests useful in predicting clinical success?

    Science.gov (United States)

    Gray, Sarah A; Deem, Lisa P; Straja, Sorin R

    2002-11-01

    The purpose of this research was to determine the predictive value of the Dental Admission Test (DAT) for clinical success using Ackerman's theory of ability determinants of skilled performance. The Ackerman theory is a valid, reliable schema in the applied psychology literature used to predict complex skill acquisition. Inconsistent stimulus-response skill acquisition depends primarily on determinants of cognitive ability. Consistent information-processing tasks have been described as "automatic," in which stimuli and responses are mapped in a manner that allows for complete certainty once the relationships have been learned. It is theorized that the skills necessary for success in the clinical component of dental schools involve a significant amount of automatic processing demands and, as such, student performance in the clinics should begin to converge as task practice is realized and tasks become more consistent. Subtest scores of the DAT of four classes were correlated with final grades in nine clinical courses. Results showed that the DAT subtest scores played virtually no role with regard to the final clinical grades. Based on this information, the DAT scores were determined to be of no predictive value in clinical achievement.

  6. 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...

  7. 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.

  8. Excellence in fleet combat replacement squadrons: predicting carrier qualification success

    OpenAIRE

    Smith, Martin P.

    1988-01-01

    This thesis presents a two-part analysis of excellence criteria for fleet combat replacement squadrons. Part one focuses on the qualitative issues and management techniques identified in outstanding fleet combat replacement squadrons. Part two develops and presents a regression model for predicting a fleet replacement squadron pilot's carrier qualification grade. The model was derived using standard linear regression techniques and the SPSSx software package of the Naval Postgraduate School. ...

  9. Mathematical Modeling Projects: Success for All Students

    Science.gov (United States)

    Shelton, Therese

    2018-01-01

    Mathematical modeling allows flexibility for a project-based experience. We share details of our regular capstone course, successful for virtually 100% of our math majors for almost two decades. Our research-like approach in this course accommodates a variety of student backgrounds and interests, and has produced some award-winning student…

  10. 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.

  11. 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. PMID:22496850

  12. 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.

  13. 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.

  14. Serial Diaphragm Ultrasonography to Predict Successful Discontinuation of Mechanical Ventilation.

    Science.gov (United States)

    Palkar, Atul; Mayo, Paul; Singh, Karan; Koenig, Seth; Narasimhan, Mangala; Singh, Anup; Darabaner, Rivkah; Greenberg, Harly; Gottesman, Eric

    2018-03-19

    Diaphragm excursion and contraction velocity measured using ultrasonography have been used to assess diaphragm function. We aimed to evaluate the performance of diaphragm ultrasonography during weaning from mechanical ventilation (MV). Diaphragm ultrasonography was performed on 73 mechanically ventilated patients who were being considered for extubation on three separate occasions: (1) on assist control mode (A/C) during consistent patient triggered ventilation, (2) following 30 min during a spontaneous breathing trial (SBT), (3) 4-24 h following extubation. Right hemidiaphragm excursion and contraction velocity were measured on A/C, during SBT, and following extubation. These measurements were correlated with the outcome of extubation. Twenty patients failed extubation: 6 of whom required re-intubation and 14 of whom required non-invasive ventilatory support. During SBT, the mean diaphragm excursions were 1.7 ± 0.82 cm in the group who failed extubation compared to 2.1 ± 0.9 cm in the group who were successfully extubated (p = 0.06). To predict successful extubation, a decrease in diaphragm excursion of < 16.4% between A/C and SBT had a sensitivity of 84.9% and a specificity of 65%. The area under curve (AUC) for receiver operative characteristics for above cut-off was 0.75. Diaphragm contraction velocity performed poorly in predicting weaning outcome. Diaphragm excursion measured during SBT is an imperfect predictor of the outcome of extubation. Maintenance of diaphragm excursion between A/C and SBT has good performance characteristics by AUC analysis. Diaphragm contraction velocity has poor ability to predict outcome of extubation.

  15. Induction of labour: clinical predictive factors for success and failure.

    Science.gov (United States)

    Batinelli, Laura; Serafini, Andrea; Nante, Nicola; Petraglia, Felice; Severi, Filiberto Maria; Messina, Gabriele

    2018-04-01

    Induction of labour (IOL) is a widely-used practice in obstetrics. Our aim was to evaluate predictors of vaginal delivery in postdate pregnancies induced with prostaglandins. We conducted a retrospective cross-sectional study with analytic component. A total of 145 women, admitted for IOL after the 41st week of gestation, were induced with a vaginal pessary releasing prostaglandins. Type of delivery, whether vaginal or caesarean, was the outcome. Several maternal and foetal variables were investigated. The Kaplan-Maier curves, monovariate and a multivariate logistic regression were carried out. In our population, 80.7% of women had vaginal delivery after the induction. Multiparity and a high Bishop score at the beginning of the IOL were protective factors for a vaginal delivery (respectively OR 0.16, p = .028 and OR 0.62, p = .034) while age >35 years, and the foetal birth weight >3500 g at the birth, resulted in being risk factors for caesarean section (respectively OR 4.20, p = .006 and OR 3.63, p = .013). IMPACT STATEMENT What is already known on this subject: Induction of labour (IOL) is a widely used practice in obstetrics. Scientific literature shows several predictors of successful induction, although there is no unanimity except for 'multiparity' and 'favourable Bishop score' which are associated with positive outcome of the induction. The main difficulty in finding other predictive factors is the heterogeneity of this field (different local protocols in each hospital, type of induction, populations and outcomes chosen in each study). In addition to that, populations are not always comparable due to the different gestation. For this reason, we decided to select a specific population of women, such as low risk postterm pregnancies induced with prostaglandins, in order to detect possible predictive factors for the success of the IOL for women with uncomplicated pregnancies. What the results of this study add: Our study agrees with existing

  16. 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.

  17. Successful External Cephalic Version: Factors Predicting Vaginal Birth

    Directory of Open Access Journals (Sweden)

    Pei Shan Lim

    2014-01-01

    Full Text Available Purpose. To determine the maternal and fetal outcomes of successful external cephalic version (ECV as well as factors predicting vaginal birth. Methods. The ECV data over a period of three years at Universiti Kebangsaan Malaysia Medical Centre (UKMMC between 1 September 2008 and 30 September 2010 was reviewed. Sixty-seven patients who had successful ECV were studied and reviewed for maternal, fetal, and labour outcomes. The control group comprised patients with cephalic singletons of matching parity who delivered following the index cases. Results. The mean gestational age at ECV was 263±6.52 days (37.5 weeks ± 6.52 days. Spontaneous labour and transient cardiotocographic (CTG changes were the commonest early adverse effects following ECV. The reversion rate was 7.46%. The mean gestational age at delivery of the two groups was significantly different (P=0.000 with 277.9±8.91 days and 269.9±9.68 days in the study group and control groups, respectively. The study group needed significantly more inductions of labour. They required more operative deliveries, had more blood loss at delivery, a higher incidence of meconium-stained liquor, and more cord around the neck. Previous flexed breeches had a threefold increase in caesarean section rate compared to previous extended breeches (44.1% versus 15.2%, P=0.010. On the contrary, an amniotic fluid index (AFI of 13 or more is significantly associated with a higher rate of vaginal birth (86.8% versus 48.3%, P=0.001. Conclusions. Patients with successful ECV were at higher risk of carrying the pregnancy beyond 40 weeks and needing induction of labour, with a higher rate of caesarean section and higher rates of obstetrics complications. Extended breech and AFI 13 or more were significantly more likely to deliver vaginally postsuccessful ECV. This additional information may be useful to caution a patient with breech that ECV does not bring them to behave exactly like a normal cephalic, so that they

  18. 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.

  19. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation......, then rival strategies can still be compared based on repeated bootstraps of the same data. Often, however, the overall performance of rival strategies is similar and it is thus difficult to decide for one model. Here, we investigate the variability of the prediction models that results when the same...... 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...

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

    Science.gov (United States)

    Sponsler, D B; Johnson, R M

    2015-01-01

    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.

  1. 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.

  2. Predicting success on the Advanced Placement Biology Examination

    Science.gov (United States)

    Shepherd, Lesa Hanlin

    Four hundred sixty students in four public high schools were used as subjects to determine which of eleven academic and demographic factors studied were significant predictors of success for the Advanced Placement Biology Examination. Factors studied were attendance, class rank, gender, grade level at the time of the examination, grade point average, level of prerequisite biology course, number of Advanced Placement Examinations taken in the year prior to the Advanced Placement Biology Examination, number of Advanced Placement Examinations taken in the same year as the Advanced Placement Biology Examination, proposed major in college, race, and SAT mathematics, verbal, and combined score. Significant relationships were found to exist between the Advanced Placement Biology Examination score and attendance, class rank, gender, grade level at the time of the Advanced Placement Biology Examination, grade point average, number of Advanced Placement Examinations taken in the year prior to the Advanced Placement Biology Examination, number of Advanced Placement Examinations taken in the same year as the Advanced Placement Biology Examination, race, and SAT scores. Significant relationships were not found to exist between Advanced Placement Biology Examination score and level prerequisite biology course and Advanced Placement Biology Examination score and proposed major in college. A multiple regression showed the best combination of predictors to be attendance, SAT verbal score, and SAT mathematics score. Discriminant analysis showed the variables in this study to be good predictors of whether the student would pass the Advanced Placement Biology Examination (score a 3, 4, or 5) or fail the Advanced Placement Biology Examination (score a 1 or 2). These results demonstrated that significant predictors for the Advanced Placement Biology Examination do exist and can be used to assist in the prediction of scores, prediction of passing or failing, the identification of

  3. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  4. 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

  5. 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...... the performance of HIRLAM in particular with respect to wind predictions. To estimate the performance of the model two spatial resolutions (0,5 Deg. and 0.2 Deg.) and different sets of HIRLAM variables were used to predict wind speed and energy production. The predictions of energy production for the wind farms...... 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...

  6. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... Linear MPC. 1. Uses linear model: ˙x = Ax + Bu. 2. Quadratic cost function: F = xT Qx + uT Ru. 3. Linear constraints: Hx + Gu < 0. 4. Quadratic program. Nonlinear MPC. 1. Nonlinear model: ˙x = f(x, u). 2. Cost function can be nonquadratic: F = (x, u). 3. Nonlinear constraints: h(x, u) < 0. 4. Nonlinear program.

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

    Science.gov (United States)

    Mestyán, Márton; Yasseri, Taha; Kertész, János

    2013-01-01

    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.

  8. 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.

  9. Spatial succession modeling of biological communities: a multi-model approach.

    Science.gov (United States)

    Zhang, WenJun; Wei, Wu

    2009-11-01

    Strong spatial correlation may exist in the spatial succession of biological communities, and the spatial succession can be mathematically described. It was confirmed by our study on spatial succession of both plant and arthropod communities along a linear transect of natural grassland. Both auto-correlation and cross-correlation analyses revealed that the succession of plant and arthropod communities exhibited a significant spatial correlation, and the spatial correlation for plant community succession was stronger than arthropod community succession. Theoretically it should be reasonable to infer a site's community composition from the last site in the linear transect. An artificial neural network for state space modeling (ANNSSM) was developed in present study. An algorithm (i.e., Importance Detection Method (IDM)) for determining the relative importance of input variables was proposed. The relative importance for plant families Gramineae, Compositae and Leguminosae, and arthropod orders Homoptera, Diptera and Orthoptera, were detected and analyzed using IDM. ANNSSM performed better than multivariate linear regression and ordinary differential equation, while ordinary differential equation exhibited the worst performance in the simulation and prediction of spatial succession of biological communities. A state transition probability model (STPM) was proposed to simulate the state transition process of biological communities. STPM performed better than multinomial logistic regression in the state transition modeling. We suggested a novel multi-model framework, i.e., the joint use of ANNSSM and STPM, to predict the spatial succession of biological communities. In this framework, ANNSSM and STPM can be separately used to simulate the continuous and discrete dynamics.

  10. Modelling bankruptcy prediction models in Slovak companies

    Directory of Open Access Journals (Sweden)

    Kovacova Maria

    2017-01-01

    Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

  11. Predicting the breeding success of large raptors in arid southern ...

    African Journals Online (AJOL)

    Raptors are often priorities for conservation efforts and breeding success is a target measure for assessing their conservation status. The breeding success of large raptors in arid southern Africa is thought to be higher in years of high rainfall. While this correlation has been found in several studies, it has not yet been shown ...

  12. 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.

  13. Predictive models of moth development

    Science.gov (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  14. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  15. Using the Sixteen Personality Factor Questionnaire to Predict Teacher Success

    Science.gov (United States)

    Watts, Rebecca S.; Cage, Bob N.; Batley, Valerie S.; Davis, Debrah

    2011-01-01

    Faculty involved in pre-service teacher education often debate whether individual characteristics can predict effective teachers. Research is inconclusive with respect to the factors being capable of predicting effective teaching. This paper reports the results of a longitudinal study that identified self-reported characteristics of pre-service…

  16. Predictions models with neural nets

    Directory of Open Access Journals (Sweden)

    Vladimír Konečný

    2008-01-01

    Full Text Available The contribution is oriented to basic problem trends solution of economic pointers, using neural networks. Problems include choice of the suitable model and consequently configuration of neural nets, choice computational function of neurons and the way prediction learning. The contribution contains two basic models that use structure of multilayer neural nets and way of determination their configuration. It is postulate a simple rule for teaching period of neural net, to get most credible prediction.Experiments are executed with really data evolution of exchange rate Kč/Euro. The main reason of choice this time series is their availability for sufficient long period. In carry out of experiments the both given basic kind of prediction models with most frequent use functions of neurons are verified. Achieve prediction results are presented as in numerical and so in graphical forms.

  17. 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).

  18. 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…

  19. Predictive Variables of Success for Latino Enrollment in Higher Education

    Science.gov (United States)

    Sanchez, Jafeth E.; Usinger, Janet; Thornton, Bill W.

    2015-01-01

    It is necessary to better understand the unique variables that serve as predictors of Latino students' postsecondary enrollment and success. Impacts of various variables were examined among 850 Latino and Caucasian students (76% and 24% of the sample, respectively). Gender, ethnicity, perceived affordability, high school grade point average, and…

  20. Student nurse selection and predictability of academic success: The Multiple Mini Interview project.

    Science.gov (United States)

    Gale, Julia; Ooms, Ann; Grant, Robert; Paget, Kris; Marks-Maran, Di

    2016-05-01

    With recent reports of public enquiries into failure to care, universities are under pressure to ensure that candidates selected for undergraduate nursing programmes demonstrate academic potential as well as characteristics and values such as compassion, empathy and integrity. The Multiple Mini Interview (MMI) was used in one university as a way of ensuring that candidates had the appropriate numeracy and literacy skills as well as a range of communication, empathy, decision-making and problem-solving skills as well as ethical insights and integrity, initiative and team-work. To ascertain whether there is evidence of bias in MMIs (gender, age, nationality and location of secondary education) and to determine the extent to which the MMI is predictive of academic success in nursing. A longitudinal retrospective analysis of student demographics, MMI data and the assessment marks for years 1, 2 and 3. One university in southwest London. One cohort of students who commenced their programme in September 2011, including students in all four fields of nursing (adult, child, mental health and learning disability). Inferential statistics and a Bayesian Multilevel Model. MMI in conjunction with MMI numeracy test and MMI literacy test shows little or no bias in terms of ages, gender, nationality or location of secondary school education. Although MMI in conjunction with numeracy and literacy testing is predictive of academic success, it is only weakly predictive. The MMI used in conjunction with literacy and numeracy testing appears to be a successful technique for selecting candidates for nursing. However, other selection methods such as psychological profiling or testing of emotional intelligence may add to the extent to which selection methods are predictive of academic success on nursing. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. 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…

  2. Can brain responses to movie trailers predict success?

    NARCIS (Netherlands)

    M.A.S. Boksem (Maarten)

    2015-01-01

    textabstractDecades of research have shown that much of our mental processing occurs at the subconscious level, including the decisions we make as consumers. These subconscious processes explain why we so often fail to accurately predict our own future choices. Often what we think we want has

  3. A Success Prediction Equation for the Intern Training Center.

    Science.gov (United States)

    A multiple regression equation predicting Intern Training Center grade point average was developed using a sample of sixty-two trainees from the ... Intern Training Center at Red River Army Depot. Possible predictor variables were taken as age, number of dependents, undergraduate college grades

  4. Successful emotion regulation is predicted by amygdala activity and aspects of personality: A latent variable approach.

    Science.gov (United States)

    Morawetz, Carmen; Alexandrowicz, Rainer W; Heekeren, Hauke R

    2017-04-01

    The experience of emotions and their cognitive control are based upon neural responses in prefrontal and subcortical regions and could be affected by personality and temperamental traits. Previous studies established an association between activity in reappraisal-related brain regions (e.g., inferior frontal gyrus and amygdala) and emotion regulation success. Given these relationships, we aimed to further elucidate how individual differences in emotion regulation skills relate to brain activity within the emotion regulation network on the one hand, and personality/temperamental traits on the other. We directly examined the relationship between personality and temperamental traits, emotion regulation success and its underlying neuronal network in a large sample (N = 82) using an explicit emotion regulation task and functional MRI (fMRI). We applied a multimethodological analysis approach, combing standard activation-based analyses with structural equation modeling. First, we found that successful downregulation is predicted by activity in key regions related to emotion processing. Second, the individual ability to successfully upregulate emotions is strongly associated with the ability to identify feelings, conscientiousness, and neuroticism. Third, the successful downregulation of emotion is modulated by openness to experience and habitual use of reappraisal. Fourth, the ability to regulate emotions is best predicted by a combination of brain activity and personality as well temperamental traits. Using a multimethodological analysis approach, we provide a first step toward a causal model of individual differences in emotion regulation ability by linking biological systems underlying emotion regulation with descriptive constructs. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  5. Prediction of successful shock wave lithotripsy with CT: a phantom study using texture analysis.

    Science.gov (United States)

    Mannil, Manoj; von Spiczak, Jochen; Hermanns, Thomas; Alkadhi, Hatem; Fankhauser, Christian D

    2017-08-24

    To apply texture analysis (TA) in computed tomography (CT) of urinary stones and to correlate TA findings with the number of required shockwaves for successful shock wave lithotripsy (SWL). CT was performed on thirty-four urinary stones in an in vitro setting. Urinary stones underwent SWL and the number of required shockwaves for disintegration was recorded. TA was performed after post-processing for pixel spacing and image normalization. Feature selection and dimension reduction were performed according to inter- and intrareader reproducibility and by evaluating the predictive ability of the number of shock waves with the degree of redundancy between TA features. Three regression models were tested: (1) linear regression with elimination of colinear attributes (2), sequential minimal optimization regression (SMOreg) employing machine learning, and (3) simple linear regression model of a single TA feature with lowest squared error. Highest correlations with the absolute number of required SWL shockwaves were found for the linear regression model (r = 0.55, p = 0.005) using two weighted TA features: Histogram 10th Percentile, and Gray-Level Co-Occurrence Matrix (GLCM) S(3, 3) SumAverg. Using the median number of required shockwaves (n = 72) as a threshold, receiver-operating characteristic analysis showed largest area-under-the-curve values for the SMOreg model (AUC = 0.84, r = 0.51, p predicting the success of stone disintegration with SWL.

  6. What do saliency models predict?

    Science.gov (United States)

    Koehler, Kathryn; Guo, Fei; Zhang, Sheng; Eckstein, Miguel P.

    2014-01-01

    Saliency models have been frequently used to predict eye movements made during image viewing without a specified task (free viewing). Use of a single image set to systematically compare free viewing to other tasks has never been performed. We investigated the effect of task differences on the ability of three models of saliency to predict the performance of humans viewing a novel database of 800 natural images. We introduced a novel task where 100 observers made explicit perceptual judgments about the most salient image region. Other groups of observers performed a free viewing task, saliency search task, or cued object search task. Behavior on the popular free viewing task was not best predicted by standard saliency models. Instead, the models most accurately predicted the explicit saliency selections and eye movements made while performing saliency judgments. Observers' fixations varied similarly across images for the saliency and free viewing tasks, suggesting that these two tasks are related. The variability of observers' eye movements was modulated by the task (lowest for the object search task and greatest for the free viewing and saliency search tasks) as well as the clutter content of the images. Eye movement variability in saliency search and free viewing might be also limited by inherent variation of what observers consider salient. Our results contribute to understanding the tasks and behavioral measures for which saliency models are best suited as predictors of human behavior, the relationship across various perceptual tasks, and the factors contributing to observer variability in fixational eye movements. PMID:24618107

  7. Predicting the establishment success of introduced target species in grassland restoration by functional traits.

    Science.gov (United States)

    Engst, Karina; Baasch, Annett; Bruelheide, Helge

    2017-09-01

    Species-rich semi-natural grasslands are highly endangered habitats in Central Europe and numerous restoration efforts have been made to compensate for the losses in the last decades. However, some plant species could become more easily established than others. The establishment success of 37 species was analyzed over 6 years at two study sites of a restoration project in Germany where hay transfer and sowing of threshing material in combination with additional sowing were applied. The effects of the restoration method applied, time since the restoration took place, traits related to germination, dispersal, and reproduction, and combinations of these traits on the establishment were analyzed. While the specific restoration method of how seeds were transferred played a subordinate role, the establishment success depended in particular on traits such as flower season or the lifeform. Species flowering in autumn, such as Pastinaca sativa and Serratula tinctoria , became established better than species flowering in other seasons, probably because they could complete their life cycle, resulting in increasingly stronger seed pressure with time. Geophytes, like Allium angulosum and Galium boreale , became established very poorly, but showed an increase with study duration. For various traits, we found significant trait by method and trait by year interactions, indicating that different traits promoted establishment under different conditions. Using a multi-model approach, we tested whether traits acted in combination. For the first years and the last year, we found that models with three traits explained establishment success better than models with a single trait or two traits. While traits had only an additive effect on the establishment success in the first years, trait interactions became important thereafter. The most important trait was the season of flowering, which occurred in all best models from the third year onwards. Overall, our approach revealed the

  8. FORMATIVE ASSESSMENT MODEL OF LEARNING SUCCESS ACHIEVEMENTS

    Directory of Open Access Journals (Sweden)

    Mikhailova Elena Konstantinovna

    2013-05-01

    Full Text Available The paper is devoted to the problem of assessment of the school students’ learning success achievements. The problem is investigated from the viewpoint of assessing the students’ learning outcomes that is aimed to ensure the teachers and students with the means and conditions to improve the educational process and results.

  9. Model predictive control of a 3-DOF helicopter system using ...

    African Journals Online (AJOL)

    ... by simulation, and its performance is compared with that achieved by linear model predictive control (LMPC). Keywords: nonlinear systems, helicopter dynamics, MIMO systems, model predictive control, successive linearization. International Journal of Engineering, Science and Technology, Vol. 2, No. 10, 2010, pp. 9-19 ...

  10. 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

  11. 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.

  12. The Personal Marketing Pyramid: A Model for Secretarial Success.

    Science.gov (United States)

    Caudill, Donald W.

    1988-01-01

    The author describes his model of a synergistic approach to achieving success. His Personal Marketing Pyramid consists of four sciences: physiology, psychology, sociology, and philosophy. He uses examples related to success in a secretarial career. (CH)

  13. 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

    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 <0.001). When compared to the J-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

  14. 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.

  15. 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.

  16. 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)

  17. 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.

  18. Hydronephrosis Predicts Successful Catheter Removal after Painful Urinary Retention - Preliminary Results of a Prospective Single Center Study.

    Science.gov (United States)

    Heidegger, Isabel; Fritz, Josef; Steiner, Hannes; Bektic, Jasmin; Pichler, Renate

    2016-01-01

    The study aims to identify candidates who can be managed conservatively after the first episode of spontaneous painful acute urinary retention (AUR). A total of 20 patients with primary spontaneous painful AUR were prospectively included in the study. Twenty-four hours after AUR, the catheter was removed. When residual urinary volume was <100 ml, patients were referred without catheter, when residual urinary volume was ≥100 ml, the catheter was replaced and removed again at day 4, 7 or 10 after AUR, respectively. Receiver operating characteristic curves, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated to assess predictors for successful catheter removal. Thirteen out of 20 (65%) patients had a successful catheter removal until day 10 after AUR. Among them 12 of 13 (93.2%) had a successful catheter removal until day 4 of AUR. Hydronephrosis urinary volume and Qmax at the time of AUR were significant numeric predictors for failure of successful catheter removal. In addition, we calculated a prediction model combing age + prostate volume + urinary volume + Qmax that highly predicts successful catheter removal (sensitivity 100%, specificity 69%, PPV 64%, NPV 100%). We found for the first time a significant association between hydronephrosis and successful catheter removal. Successful catheter removal until day 4 after AUR can safely be managed without immediate transurethral resection of the prostate. © 2015 S. Karger AG, Basel.

  19. Brain activation during fear extinction predicts exposure success.

    Science.gov (United States)

    Ball, Tali Manber; Knapp, Sarah E; Paulus, Martin P; Stein, Murray B

    2017-03-01

    Exposure therapy, a gold-standard treatment for anxiety disorders, is assumed to work via extinction learning, but this has never been tested. Anxious individuals demonstrate extinction learning deficits, likely related to less ventromedial prefrontal cortex (vmPFC) and more amygdala activation, but the relationship between these deficits and exposure outcome is unknown. We tested whether anxious individuals who demonstrate better extinction learning report greater anxiety reduction following brief exposure. Twenty-four adults with public speaking anxiety completed (1) functional magnetic resonance imaging during a conditioning paradigm, (2) a speech exposure session, and (3) anxiety questionnaires before and two weeks postexposure. Extinction learning was assessed by comparing ratings to a conditioned stimulus (neutral image) that was previously paired with an aversive noise against a stimulus that had never been paired. Robust regression analyses examined whether brain activation during extinction learning predicted anxiety reduction two weeks postexposure. On average, the conditioning paradigm resulted in acquisition and extinction effects on stimulus ratings, and the exposure session resulted in reduced anxiety two weeks post-exposure. Consistent with our hypothesis, individuals with better extinction learning (less negative stimulus ratings), greater activation in vmPFC, and less activation in amygdala, insula, and periaqueductal gray reported greater anxiety reduction two weeks postexposure. To our knowledge, this is the first time that the theoretical link between extinction learning and exposure outcome has been demonstrated. Future work should examine whether extinction learning can be used as a prognostic test to determine who is most likely to benefit from exposure therapy. © 2016 Wiley Periodicals, Inc.

  20. Stress and success: individual differences in the glucocorticoid stress response predict behavior and reproductive success under high predation risk.

    Science.gov (United States)

    Vitousek, Maren N; Jenkins, Brittany R; Safran, Rebecca J

    2014-11-01

    A fundamental element of how vertebrates respond to stressors is by rapidly elevating circulating glucocorticoid hormones. Individual variation in the magnitude of the glucocorticoid stress response has been linked with reproductive success and survival. But while the adaptive value of this response is believed to stem in part from changes in the expression of hormone-mediated behaviors, it is not clear how the behavior of stronger and weaker glucocorticoid responders differs during reproduction, or during exposure to ecologically relevant stressors. Here we report that in a population of barn swallows (Hirundo rustica erythrogaster) experiencing high rates of nest predation, circulating levels of corticosterone (the primary avian glucocorticoid) during exposure to a standardized stressor predict aspects of subsequent behavior and fitness. Individuals that mounted a stronger corticosterone stress response during the early reproductive period did not differ in clutch size, but fledged fewer offspring. Parents with higher stress-induced corticosterone during the early reproductive period later provisioned their nestlings at lower rates. Additionally, in the presence of a model predator stress-induced corticosterone was positively associated with the latency to return to the nest, but only among birds that were observed to return. Model comparisons revealed that stress-induced hormones were better predictors of the behavioral and fitness effects of exposure to transient, ecologically relevant stressors than baseline corticosterone. These findings are consistent with functional links between individual variation in the hormonal and behavioral response to stressors. If such links occur, then selection on the heritable components of the corticosterone stress response could promote adaptation to novel environments or predation regimes. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Regional cost and experience, not size or hospital inclusion, helps predict ACO success.

    Science.gov (United States)

    Schulz, John; DeCamp, Matthew; Berkowitz, Scott A

    2017-06-01

    The Medicare Shared Savings Program (MSSP) continues to expand and now includes 434 accountable care organizations (ACOs) serving more than 7 million beneficiaries. During 2014, 86 of these ACOs earned over $300 million in shared savings payments by promoting higher-quality patient care at a lower cost.Whether organizational characteristics, regional cost of care, or experience in the MSSP are associated with the ability to achieve shared savings remains uncertain.Using financial results from 2013 and 2014, we examined all 339 MSSP ACOs with a 2012, 2013, or 2014 start-date. We used a cross-sectional analysis to examine all ACOs and used a multivariate logistic model to predict probability of achieving shared savings.Experience, as measured by years in the MSSP program, was associated with success and the ability to earn shared savings varied regionally. This variation was strongly associated with differences in regional Medicare fee-for-service per capita costs: ACOs in high cost regions were more likely to earn savings. In the multivariate model, the number of ACO beneficiaries, inclusion of a hospital or involvement of an academic medical center, was not associated with likelihood of earning shared savings, after accounting for regional baseline cost variation.These results suggest ACOs are learning and improving from their experience. Additionally, the results highlight regional differences in ACO success and the strong association with variation in regional per capita costs, which can inform CMS policy to help promote ACO success nationwide.

  2. 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.

  3. Can we predict foraging success in a marine predator from dive patterns only? Validation with prey capture attempt data.

    Directory of Open Access Journals (Sweden)

    Morgane Viviant

    Full Text Available Predicting how climatic variations will affect marine predator populations relies on our ability to assess foraging success, but evaluating foraging success in a marine predator at sea is particularly difficult. Dive metrics are commonly available for marine mammals, diving birds and some species of fish. Bottom duration or dive duration are usually used as proxies for foraging success. However, few studies have tried to validate these assumptions and identify the set of behavioral variables that best predict foraging success at a given time scale. The objective of this study was to assess if foraging success in Antarctic fur seals could be accurately predicted from dive parameters only, at different temporal scales. For this study, 11 individuals were equipped with either Hall sensors or accelerometers to record dive profiles and detect mouth-opening events, which were considered prey capture attempts. The number of prey capture attempts was best predicted by descent and ascent rates at the dive scale; bottom duration and descent rates at 30-min, 1-h, and 2-h scales; and ascent rates and maximum dive depths at the all-night scale. Model performances increased with temporal scales, but rank and sign of the factors varied according to the time scale considered, suggesting that behavioral adjustment in response to prey distribution could occur at certain scales only. The models predicted the foraging intensity of new individuals with good accuracy despite high inter-individual differences. Dive metrics that predict foraging success depend on the species and the scale considered, as verified by the literature and this study. The methodology used in our study is easy to implement, enables an assessment of model performance, and could be applied to any other marine predator.

  4. Achieving Success in Measurement and Reliability Modeling

    OpenAIRE

    Keller, Ted; Munson, John C.; Schneidewind, Norman; Stark, George

    1993-01-01

    Panel Session at the International Symposium on Software Reliability Engineering 1993, Saturday: 6 November 1993, 0830-1000 and 1030-1200 The NASA Space Shuttle on-board software is one of the nation’s most safety-critical software systems. The process which produces this software has been rated at maturity level five. Among the quality assurance methods that are used to ensure the software is free of safetycritical faults is the use of reliability modelling and predi...

  5. Predictive Models for Carcinogenicity and Mutagenicity ...

    Science.gov (United States)

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include VitotoxTM, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-t

  6. Modelling the effect of food availability on recruitment success of ...

    African Journals Online (AJOL)

    The results show the importance of food (especially diatoms and copepods) dynamics on the spatial and temporal patterns of recruitment success, and also confirm the importance of the spawning area, timing and water depth on the recruitment success of Cape anchovy larvae. Keywords: 3-D modelling, IBM model, pelagic ...

  7. 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.

  8. Model approach brings multi-level success.

    Science.gov (United States)

    Howell, Mark

    2012-08-01

    n an article that first appeared in US magazine, Medical Construction & Design, Mark Howell, senior vice-president of Skanska USA Building, based in Seattle, describes the design and construction of a new nine-storey, 350,000 ft2 extension to the Good Samaritan Hospital in Puyallup, Washington state. He explains how the use of an Integrated Project Delivery (IPD) approach by the key players, and extensive use of building information modelling (BIM), combined to deliver a healthcare facility that he believes should meet the needs of patients, families, and the clinical care team, 'well into the future'.

  9. Threat-related selective attention predicts treatment success in childhood anxiety disorders

    NARCIS (Netherlands)

    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

    The present study examined whether threat-related selective attention was predictive of treatment success in children with anxiety disorders and whether age moderated this association. Specific components of selective attention were examined in treatment responders and nonresponders. Participants

  10. Brain Imaging Predicts Psychotherapy Success in Patients with Social Anxiety Disorder

    Science.gov (United States)

    ... Brain Imaging Predicts Psychotherapy Success in Patients with Social Anxiety Disorder February 1, 2013 • Science Update Treatment for social anxiety disorder or social phobia has entered the personalized ...

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

    Directory of Open Access Journals (Sweden)

    Parisa Azimi

    Full Text Available 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 < 0.001. Post-surgical success was 76.0% (n = 117. The patients' rating on surgical success assessments by the ODI discriminated well between sub-groups of patients who differed with respect to the Finneson-Cooper 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.

  12. 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.

  13. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird

    OpenAIRE

    Milenkaya, Olga; Catlin, Daniel H.; Legge, Sarah; Walters, Jeffrey R.

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival ove...

  14. 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.

  15. Most Likely to Achieve: Predicting Early Success of the Practical Nurse Student

    Science.gov (United States)

    Cline, April P.

    2013-01-01

    It is important that practical nurse (PN) educators be able to identify which students are likely to be successful in their programs. However, the majority of literature related to predicting success of nursing students has been done on baccalaureate nursing students in the university setting. This study sought to determine whether the same…

  16. 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)…

  17. 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.

  18. 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…

  19. 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…

  20. 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…

  1. 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.

  2. 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.

  3. A Labor Market Success Model of Young Male Hispanic Americans.

    Science.gov (United States)

    Seidenstat, Paul

    The study develops a labor market success model of young male inner-city Hispanics and examines several variables influencing labor market success. A sample of inner-city Puerto Ricans who attended the eighth grade in two schools in Wilmington, Delaware, in the 1966-1971 period was chosen and interviewed. Small control groups of blacks and whites…

  4. End Users and ERP Systems� Success. Three Models

    Directory of Open Access Journals (Sweden)

    Gianina MIHAI

    2017-06-01

    Full Text Available Information systems (IS have an enormous impact on organizations, individual work, and performance in general. As a result, many research works in the field of IS are focused on the interrelationship between individual performance and IS performance. During the last 20 to 30 years many models have been developed and tested by researchers. Their main objective was to investigate IS success and user performance in different environments. Therefore, a number of models appeared, their goal being the studying of the success, usefulness, end user adoption and utilization of IS, and other user and IS-related aspects in different organizations. This research paper presents three of the most important models developed in specialized literature, which deal with measuring IS success and end user adoption of the IS: the TAM model, the D&M model, and the TTF model. The research also provides an overview of some studies that have applied these models in the field of ERP systems.

  5. 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.

  6. 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.

  7. Web tools for predictive toxicology model building.

    Science.gov (United States)

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  8. Predicting, deciding, learning: can one evaluate the 'success' of national climate scenarios?

    International Nuclear Information System (INIS)

    Hulme, Mike; Dessai, Suraje

    2008-01-01

    Scenarios may be understood as products and/or processes. Viewing scenario exercises as productive tends to emphasize their tangibility: scenario products may acquire value unrelated to the processes of their creation. Viewing scenario exercises as procedural tends to emphasize their modes of formation: the process of constructing scenarios may have benefits irrespective of the value of ensuing products. These two framings yield different expectations about how one might evaluate the 'success' or otherwise of scenario exercises. We illustrate three approaches to evaluating the success or otherwise of scenarios using the example of the series of national UK climate scenarios published between 1991 and 2002. These are: predictive success (has the future turned out as envisaged?), decision success (have 'good' decisions subsequently been made?) and learning success (have scenarios proved engaging and enabled learning?). We reflect on the different ways the 'success' of national climate scenarios might be evaluated and on the relationship between the productive and procedural dimensions of scenario exercises.

  9. Serum biomarkers may help predict successful misoprostol management of early pregnancy failure.

    Science.gov (United States)

    Schreiber, Courtney A; Ratcliffe, Sarah J; Quinley, Kelly E; Miller, Carrie; Sammel, Mary D

    2015-06-01

    In order to simplify management of early pregnancy loss, our goal was to elucidate predictors of successful medical management of miscarriage with a single dose of misoprostol. In this secondary analysis of data from a multicenter randomized controlled trial, candidate biomarkers were compared between 49 women with missed abortion who succeeded in passing their pregnancy with a single dose of misoprostol and 46 women who did not pass their pregnancy with a misoprostol single dose. We computed the precision of trophoblastic protein and hormone concentrations to discriminate between women who succeed or fail single dose misoprostol management. We also included demographic factors in our analyses. We found overlap in the concentrations of the individual markers between women who succeeded and failed single-dose misoprostol. However, hCG levels ≥ 4000 mIU/mL and ADAM-12 levels ≥ 2500 pg/mL were independently associated with complete uterine expulsion after one dose of misoprostol in our population. A multivariable logistic model for success included non-Hispanic ethnicity and parity <2 in addition to hCG ≥ 4000 mIU/mL and ADAM-12 ≥ 2500 pg/mL and had an area under the receiver operating characteristic (ROC) of 0.81 (95% confidence interval: 72-90%). Categorizing women with a predicted probability of ≥ 0.65 resulted in a sensitivity of 75.0%, specificity 77.1% and positive predictive value of 81.8%. While preliminary, our data suggest that serum biomarkers, especially when combined with demographic characteristics, may be helpful in guiding patient decision-making regarding the management of early pregnancy failure (EPF). Further study is warranted. Copyright © 2015 Society for Biology of Reproduction & the Institute of Animal Reproduction and Food Research of Polish Academy of Sciences in Olsztyn. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  10. Launch Hard or Go Home! Predicting the Success of Kickstarter Campaigns

    OpenAIRE

    Etter, Vincent; Grossglauser, Matthias; Thiran, Patrick

    2013-01-01

    Crowdfunding websites such as Kickstarter are becoming increasingly popular, allowing project creators to raise hundreds of millions of dollars every year. However, only one out of two Kickstarter campaigns reaches its funding goal and is successful. It is therefore of prime importance, both for project creators and backers, to be able to know which campaigns are likely to succeed. We propose a method for predicting the success of Kickstarter campaigns by using both direct information and so...

  11. Prediction of successful treatment by extracorporeal shock wave lithotripsy based on crystalluriacomposition correlations of urinary calculi

    Directory of Open Access Journals (Sweden)

    Nadia Messaoudi

    2015-12-01

    Full Text Available Objective: To provide correlations between crystalluria and chemical structure of calculi in situ to help making decision in the use of the extracorporeal shock wave lithotripsy (ESWL. Methods: A crystalluria study was carried out on 644 morning urines of 172 nephrolithiasis patients (111 males and 61 females, and 235 of them were in situ stone carriers. After treating by ESWL, the recovered calculi have been analyzed by Fourier transform infrared spectroscopy and their compositions were correlated to the nature of urinary crystals. Results: We obtained successful treatment for 109 patients out of 157 and 63 patients out of 78 with stones had a treatment failure (33.2%. The correlations showed that for the overwhelming crystalluria containing calcium oxalate dihydrate (COD with mixed crystals without calcium oxalate monohydrate, we should have 68% to 88 % success rate. However, the obtained result was 79%. Similarly, for crystalluria with COD + calcium oxalate monohydrate ± carbapatite, the prediction was 11% to 45% and the result was approximately 39%. When the majority of crystalluria was calcium phosphate, the prediction of 50% to 80% was confirmed by 71% success rate. For those majority containing magnesium ammonium phosphate hexahydrate (struvite ± diammonium urate ± COD, we predicted between 80% to 100%, and the result gave a success rate of 84%. Conclusions: The analysis of crystalluria of morning urine can help to know the composition of calculi in situ and can predict the success rate of ESWL for maximum efficiency.

  12. Comparison of clinical utility between diaphragm excursion and thickening change using ultrasonography to predict extubation success

    Science.gov (United States)

    Yoo, Jung-Wan; Lee, Seung Jun; Lee, Jong Deog; Kim, Ho Cheol

    2018-01-01

    Background/Aims Both diaphragmatic excursion and change in muscle thickening are measured using ultrasonography (US) to assess diaphragm function and mechanical ventilation weaning outcomes. However, which parameter can better predict successful extubation remains to be determined. The aim of this study was to compare the clinical utility of these two diaphragmatic parameters to predict extubation success. Methods This study included patients subjected to extubation trial in the medical or surgical intensive care unit of a university-affiliated hospital from May 2015 through February 2016. Diaphragm excursion and percent of thickening change (Δtdi%) were measured using US within 24 hours before extubation. Results Sixty patients were included, and 78.3% (47/60) of these patients were successfully extubated, whereas 21.7% (13/60) were not. The median degree of excursion was greater in patients with extubation success than in those with extubation failure (1.65 cm vs. 0.8 cm, p success had a greater Δtdi% than those with extubation failure (42.1% vs. 22.5%, p = 0.03). The areas under the receiver operating curve for excursion and Δtdi% were 0.836 (95% confidence interval [CI], 0.717 to 0.919) and 0.698 (95% CI, 0.566 to 0.810), respectively (p = 0.017). Conclusions Diaphragm excursion seems more accurate than a change in the diaphragm thickness to predict extubation success. PMID:29050461

  13. 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…

  14. Empirical evaluation of a forecasting model for successful facilitation ...

    African Journals Online (AJOL)

    The forecasting model identified 8 key attributes for facilitation success based on performance measures from the 1999 Facilitator Customer Service Survey. During 2000 the annual Facilitator Customer Satisfaction Survey was employed to validate the findings of the forecasting model. A total of 1910 questionnaires were ...

  15. An internally validated prognostic model for success in revision stapes surgery for otosclerosis.

    Science.gov (United States)

    Wegner, Inge; Vincent, Robert; Derks, Laura S M; Rauh, Simone P; Heymans, Martijn W; Stegeman, Inge; Grolman, Wilko

    2018-03-09

    To develop a prediction model that can accurately predict the chance of success following revision stapes surgery in patients with recurrent or persistent otosclerosis at 2- to 6-months follow-up and to validate this model internally. A retrospective cohort study of prospectively gathered data in a tertiary referral center. The associations of 11 prognostic factors with treatment success were tested in 705 cases using multivariable logistic regression analysis with backward selection. Success was defined as a mean air-bone gap closure to 10 dB or less. The most relevant predictors were used to derive a clinical prediction rule to determine the probability of success. Internal validation by means of bootstrapping was performed. Model performance indices, including the Hosmer-Lemeshow test, the area under the receiver operating characteristics curve (AUC), and the explained variance were calculated. Success was achieved in 57.7% of cases at 2- to 6-months follow-up. Certain previous surgical techniques, primary causes of failure leading up to revision stapes surgery, and positions of the prosthesis placed during revision surgery were associated with higher success percentages. The clinical prediction rule performed moderately well in the original dataset (Hosmer-Lemeshow P = .78; AUC = 0.73; explained variance = 22%), which slightly decreased following internal validation by means of bootstrapping (AUC = 0.69; explained variance = 13%). Our study established the importance of previous surgical technique, primary cause of failure, and type of the prosthesis placed during the revision surgery in predicting the probability of success following stapes surgery at 2- to 6-months follow-up. 2b. Laryngoscope, 2018. © 2018 The American Laryngological, Rhinological and Otological Society, Inc.

  16. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

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

  17. Machine learning algorithms for the prediction of conception success to a given insemination in lactating dairy cows.

    Science.gov (United States)

    Hempstalk, K; McParland, S; Berry, D P

    2015-08-01

    The ability to accurately predict the conception outcome for a future mating would be of considerable benefit for producers in deciding what mating plan (i.e., expensive semen or less expensive semen) to implement for a given cow. The objective of the present study was to use herd- and cow-level factors to predict the likelihood of conception success to a given insemination (i.e., conception outcome not including embryo loss); of particular interest in the present study was the usefulness of milk mid-infrared (MIR) spectral data in augmenting the accuracy of the prediction model. A total of 4,341 insemination records with conception outcome information from 2,874 lactations on 1,789 cows from 7 research herds for the years 2009 to 2014 were available. The data set was separated into a calibration data set and a validation data set using either of 2 approaches: (1) the calibration data set contained records from all 7 farms for the years 2009 to 2011, inclusive, and the validation data set included data from the 7 farms for the years 2012 to 2014, inclusive, or (2) the calibration data set contained records from 5 farms for all 6 yr and the validation data set contained information from the other 2 farms for all 6 yr. The prediction models were developed with 8 different machine learning algorithms in the calibration data set using standard 10-times 10-fold cross-validation and also by evaluating in the validation data set. The area under curve (AUC) for the receiver operating curve varied from 0.487 to 0.675 across the different algorithms and scenarios investigated. Logistic regression was generally the best-performing algorithm. The AUC was generally inferior for the external validation data sets compared with the calibration data sets. The inclusion of milk MIR in the prediction model generally did not improve the accuracy of prediction. Despite the fair AUC for predicting conception outcome under the different scenarios investigated, the model provided a

  18. Predicting Success in Product Development: The Application of Principal Component Analysis to Categorical Data and Binomial Logistic Regression

    Directory of Open Access Journals (Sweden)

    Glauco H.S. Mendes

    2013-09-01

    Full Text Available Critical success factors in new product development (NPD in the Brazilian small and medium enterprises (SMEs are identified and analyzed. Critical success factors are best practices that can be used to improve NPD management and performance in a company. However, the traditional method for identifying these factors is survey methods. Subsequently, the collected data are reduced through traditional multivariate analysis. The objective of this work is to develop a logistic regression model for predicting the success or failure of the new product development. This model allows for an evaluation and prioritization of resource commitments. The results will be helpful for guiding management actions, as one way to improve NPD performance in those industries.

  19. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  20. 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.

  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 for Program Success from Engineering and Manufacturing Development Performance Trends

    National Research Council Canada - National Science Library

    Gailey, Charles

    2002-01-01

    ...; they were descriptive rather than predictive. It was also found that the Selective Acquisition Reporting system had succeeded in identifying the "bad" programs; but corrective measures, if any, were ineffective. Additional research indicated that the contract type most likely to lead to success in EMD was Cost Plus Incentive Fee.

  3. 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…

  4. Olympic medals: Success predictions for Río-2016 | Sánchez ...

    African Journals Online (AJOL)

    Medals are the maximum exponent of successful sporting events. One of the most relevant of these sporting events is the Olympic Games, which gathers major athletes and teams from across the world every four years. Predicting the distribution of the medals at these Games is nothing new. As a matter of fact, this practice ...

  5. Egg quality in fish: pH of stripped eggs can predict catfish hatching success

    Science.gov (United States)

    This study was conducted to determine the feasibility of measuring the pH of stripped unfertilized channel catfish eggs to predict the hatching success of channel x blue hybrid catfish eggs. A significant correlation was established between the ovarian fluid pH of stripped eggs and subsequent hatch...

  6. 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-…

  7. Predicting Successful Completion Using Student Delay Indicators in Undergraduate Self-Paced Online Courses

    Science.gov (United States)

    Lim, Janine M.

    2016-01-01

    Self-paced online courses meet flexibility and learning needs of many students, but skepticism persists regarding the quality and the tendency for students to procrastinate in self-paced courses. Research is needed to understand procrastination and delay patterns of students in online self-paced courses to predict successful completion and…

  8. 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…

  9. Noncognitive Variables to Predict Academic Success among Junior Year Baccalaureate Nursing Students

    Science.gov (United States)

    Smith, Ellen M. T.

    2017-01-01

    An equitable predictor of academic success is needed as nursing education strives toward comprehensive preparation of diverse nursing students. The purpose of this study was to discover how Sedlacek's (2004a) Noncognitive Questionnaire (NCQ) and Duckworth & Quinn's (2009) Grit-S predicted baccalaureate nursing student academic performance and…

  10. Predicting College Success: Achievement, Demographic, and Psychosocial Predictors of First-Semester College Grade Point Average

    Science.gov (United States)

    Saltonstall, Margot

    2013-01-01

    This study seeks to advance and expand research on college student success. Using multinomial logistic regression analysis, the study investigates the contribution of psychosocial variables above and beyond traditional achievement and demographic measures to predicting first-semester college grade point average (GPA). It also investigates if…

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

    Science.gov (United States)

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

    2012-10-01

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

  12. 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.

  13. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  14. Individual differences in episodic memory abilities predict successful prospective memory output monitoring.

    Science.gov (United States)

    Hunter Ball, B; Pitães, Margarida; Brewer, Gene A

    2018-02-07

    Output monitoring refers to memory for one's previously completed actions. In the context of prospective memory (PM) (e.g., remembering to take medication), failures of output monitoring can result in repetitions and omissions of planned actions (e.g., over- or under-medication). To be successful in output monitoring paradigms, participants must flexibly control attention to detect PM cues as well as engage controlled retrieval of previous actions whenever a particular cue is encountered. The current study examined individual differences in output monitoring abilities in a group of younger adults differing in attention control (AC) and episodic memory (EM) abilities. The results showed that AC ability uniquely predicted successful cue detection on the first presentation, whereas EM ability uniquely predicted successful output monitoring on the second presentation. The current study highlights the importance of examining external correlates of PM abilities and contributes to the growing body of research on individual differences in PM.

  15. Predicting individuals' learning success from patterns of pre-learning MRI activity.

    Science.gov (United States)

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

    2011-01-14

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

  16. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

    Science.gov (United States)

    Milenkaya, Olga; Catlin, Daniel H; Legge, Sarah; Walters, Jeffrey R

    2015-01-01

    Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch), a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage) such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous interpretation of

  17. Body Condition Indices Predict Reproductive Success but Not Survival in a Sedentary, Tropical Bird.

    Directory of Open Access Journals (Sweden)

    Olga Milenkaya

    Full Text Available Body condition may predict individual fitness because those in better condition have more resources to allocate towards improving their fitness. However, the hypothesis that condition indices are meaningful proxies for fitness has been questioned. Here, we ask if intraspecific variation in condition indices predicts annual reproductive success and survival. We monitored a population of Neochmia phaeton (crimson finch, a sedentary, tropical passerine, for reproductive success and survival over four breeding seasons, and sampled them for commonly used condition indices: mass adjusted for body size, muscle and fat scores, packed cell volume, hemoglobin concentration, total plasma protein, and heterophil to lymphocyte ratio. Our study population is well suited for this research because individuals forage in common areas and do not hold territories such that variation in condition between individuals is not confounded by differences in habitat quality. Furthermore, we controlled for factors that are known to impact condition indices in our study population (e.g., breeding stage such that we assessed individual condition relative to others in the same context. Condition indices that reflect energy reserves predicted both the probability of an individual fledging young and the number of young produced that survived to independence, but only during some years. Those that were relatively heavy for their body size produced about three times more independent young compared to light individuals. That energy reserves are a meaningful predictor of reproductive success in a sedentary passerine supports the idea that energy reserves are at least sometimes predictors of fitness. However, hematological indices failed to predict reproductive success and none of the indices predicted survival. Therefore, some but not all condition indices may be informative, but because we found that most indices did not predict any component of fitness, we question the ubiquitous

  18. 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.

  19. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    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 is a r...

  20. 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

  1. Leader Succession: A Model and Review for School Settings.

    Science.gov (United States)

    Miskel, Cecil; Cosgrove, Dorothy

    Recent research casts doubt on the commonly held notions that administrators affect student learning through instructional leadership and that changing administrators will improve school performance. To help construct a model for examining the process of leader succession that specifies a number of major school process and outcome variables…

  2. 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…

  3. A Competitive Success Model in the Hotel Industry

    OpenAIRE

    González Rodríguez, María Rosario; Martín Samper, Rosario del Carmen; Jiménez Caballero, José Luis

    2015-01-01

    The aim of the paper focus on identifying those factors involved in the competitive success of hotel companies and the interrelations between them, taking into account the socio-economic influence that these companies might have on Andalusian region and the few studies carried out in tourism sector so far. The study tries to specify an econometric model that may include factors that appear as mechanisms for the generation of competitive advantage. The research model allows us t...

  4. [Predicting the success of a benzodiazepine discontinuation programme: myths or clinical wisdom?].

    Science.gov (United States)

    Knoop, H; Kan, C C; Mickers, F C; Barnhoorn, D

    2006-01-01

    After successful completion of a benzodiazepine withdrawal programme it nevertheless is hard to remain abstinent in the long term. To determine to what extent the success of a benzodiazepine discontinuation programme for psychiatric patients with chronic benzodiazepine use (> or = 3 months) can be predicted from the severity of the anxiety, sleep disorders and depressive symptoms, and from the level of benzodiazepine dependence. The predictive values of coping style and personality characteristics were also studied. A prognostic cohort study with patients of the Radboud University Nijmegen Medical Centre was conducted. Before entering the programme 92 patients were given a psychological assessment. Anxiety level, benzodiazepine dependence, coping style and personality traits were measured by means of psychological questionnaires. The DSM-IV axis I classification for each patient was known. Patients who had stopped their medication immediately after the discontinuation programme ended (n = 6o) were compared with patients who had not been successful in completing the programme (n = 32). Thereafter, patients who were still abstinent at the follow-up about 2 years later (n = 25) were compared with patients who at that time /used benzodiazepine (n = 43). Of all the variables examined, it was only a specific coping style whereby patients expressed their (negative) emotions which was associated with the short- and long-term success of the discontinuation programme. The more patients expressed their negative emotions, the greater the chance of a successful outcome and permanent abstinence. Coping style, however, predicted for only a small proportion of the variance in the success of the discontinuation programme. The psychological characteristics and the DSM-IV axis I classifications should not exert undue influence on the clinician's decision to advise the patient to stop or continue taking benzodiazepines.

  5. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

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

  6. Predictive Model Assessment for Count Data

    National Research Council Canada - National Science Library

    Czado, Claudia; Gneiting, Tilmann; Held, Leonhard

    2007-01-01

    .... In case studies, we critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. Key words: Calibration...

  7. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

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

    2016-01-01

    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......) for modeling and forecasting. It is argued that this gives models and predictions which better reflect reality. The SDE approach also offers a more adequate framework for modeling and a number of efficient tools for model building. A software package (CTSM-R) for SDE-based modeling is briefly described....... 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...

  8. 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

  9. 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.

  10. 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.

  11. Predictive models for arteriovenous fistula maturation.

    Science.gov (United States)

    Al Shakarchi, Julien; McGrogan, Damian; Van der Veer, Sabine; Sperrin, Matthew; Inston, Nicholas

    2016-05-07

    Haemodialysis (HD) is a lifeline therapy for patients with end-stage renal disease (ESRD). A critical factor in the survival of renal dialysis patients is the surgical creation of vascular access, and international guidelines recommend arteriovenous fistulas (AVF) as the gold standard of vascular access for haemodialysis. Despite this, AVFs have been associated with high failure rates. Although risk factors for AVF failure have been identified, their utility for predicting AVF failure through predictive models remains unclear. The objectives of this review are to systematically and critically assess the methodology and reporting of studies developing prognostic predictive models for AVF outcomes and assess them for suitability in clinical practice. Electronic databases were searched for studies reporting prognostic predictive models for AVF outcomes. Dual review was conducted to identify studies that reported on the development or validation of a model constructed to predict AVF outcome following creation. Data were extracted on study characteristics, risk predictors, statistical methodology, model type, as well as validation process. We included four different studies reporting five different predictive models. Parameters identified that were common to all scoring system were age and cardiovascular disease. This review has found a small number of predictive models in vascular access. The disparity between each study limits the development of a unified predictive model.

  12. Model Predictive Control Fundamentals | Orukpe | Nigerian Journal ...

    African Journals Online (AJOL)

    Model Predictive Control (MPC) has developed considerably over the last two decades, both within the research control community and in industries. MPC strategy involves the optimization of a performance index with respect to some future control sequence, using predictions of the output signal based on a process model, ...

  13. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

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

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optim...

  14. 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.

  15. Optimal Futility Interim Design: A Predictive Probability of Success Approach with Time-to-Event Endpoint.

    Science.gov (United States)

    Tang, Zhongwen

    2015-01-01

    An analytical way to compute predictive probability of success (PPOS) together with credible interval at interim analysis (IA) is developed for big clinical trials with time-to-event endpoints. The method takes account of the fixed data up to IA, the amount of uncertainty in future data, and uncertainty about parameters. Predictive power is a special type of PPOS. The result is confirmed by simulation. An optimal design is proposed by finding optimal combination of analysis time and futility cutoff based on some PPOS criteria.

  16. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  17. Hybrid approaches to physiologic modeling and prediction

    Science.gov (United States)

    Olengü, Nicholas O.; Reifman, Jaques

    2005-05-01

    This paper explores how the accuracy of a first-principles physiological model can be enhanced by integrating data-driven, "black-box" models with the original model to form a "hybrid" model system. Both linear (autoregressive) and nonlinear (neural network) data-driven techniques are separately combined with a first-principles model to predict human body core temperature. Rectal core temperature data from nine volunteers, subject to four 30/10-minute cycles of moderate exercise/rest regimen in both CONTROL and HUMID environmental conditions, are used to develop and test the approach. The results show significant improvements in prediction accuracy, with average improvements of up to 30% for prediction horizons of 20 minutes. The models developed from one subject's data are also used in the prediction of another subject's core temperature. Initial results for this approach for a 20-minute horizon show no significant improvement over the first-principles model by itself.

  18. Youth's Causal Beliefs About Success: Socioeconomic Differences and Prediction of Early Career Development.

    Science.gov (United States)

    Kay, Joseph S; Shane, Jacob; Heckhausen, Jutta

    2017-10-01

    Youth's career attainment is associated with socioeconomic background, but may also be related to their beliefs about causes of success. Relationships between 17-year-olds' socioeconomic status (SES) and causal beliefs about success, and whether these beliefs predict career attainment after completing a vocational or university degree were examined using data from the German Socio-Economic Panel Study (n = 997, 48.5% female). Youth with higher SES parents and those who attended higher levels of high schools were less likely to believe that success in society is due to external causes, but SES was unrelated to the belief that success is due to personal merit or ability. Youth who believe that success is due to external causes attained lower income, occupational prestige, and job autonomy, and slower increases in income over time. There were also significant indirect effects of youth's parents' SES and their own high school levels on career attainment through such external causal beliefs; merit beliefs, by contrast, were largely unrelated to career attainment. These results suggest that beliefs about external causes of success may uniquely contribute to the transmission and maintenance of SES across generations and over time.

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

    Science.gov (United States)

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

    2014-01-01

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

  20. Hope of Success and Fear of Failure Predicting Academic Procrastination Students Who Working on a Thesis

    Directory of Open Access Journals (Sweden)

    Sari Zakiah Akmal

    2017-08-01

    Full Text Available Students, who are working on the thesis, have some difficulties caused by internal and external factors. Those problems can disrupt the completion of their thesis, such as the tendency to do academic procrastination. Increasing achievement motivation can reduce academic procrastination. This study aims to look at the role of achievement motivation (hope of success and fear of failure in predicting academic procrastination. The study used a quantitative approach by distributing academic procrastination and achievement motivation questionnaires. The study involved 182 students who were working on a thesis as samples, which were obtained by using accidental sampling technique. Data were analyzed using multiple regressions. It showed that the hope of success and fear of failure have a significant role in predicting academic procrastination (R2 = 13.8%, F = 14,356, p <0.05. The hope of success can decrease academic procrastination, while fear of failure can improve it. Thus, interventions to reduce academic procrastination can be delivered by increasing students hope of success.

  1. Evaluating the Predictive Value of Growth Prediction Models

    Science.gov (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.

    2014-01-01

    This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

  2. 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...

  3. 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

  4. A Global Model for Bankruptcy Prediction.

    Science.gov (United States)

    Alaminos, David; Del Castillo, Agustín; Fernández, Manuel Ángel

    2016-01-01

    The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world. The objective is to construct a global model with a high capacity for predicting bankruptcy in any region of the world. The results obtained have allowed us to confirm the superiority of the global model in comparison to regional models over periods of up to three years prior to bankruptcy.

  5. 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.

  6. [Predictive value of ultrasonic diaphragm thickening fraction on successful weaning for patients with myasthenia gravis crisis].

    Science.gov (United States)

    Sun, Qiang; Shan, Feng; Dong, Hai; Jiang, Yan; Sun, Yongmei; Sun, Yunbo

    2017-07-01

    To confirm the predictive value of diaphragm thickening fraction (DTF) on successful weaning by bedside ultrasound in patients with myasthenia gravis crisis. A prospective study was conducted. The patients with myasthenia gravis crisis undergoing mechanical ventilation admitted to Department of Critical Care Medicine of the Affiliated Hospital of Qingdao University from March 2015 to February 2017 were enrolled. All patients underwent a low level pressure support mode of spontaneous breathing test (SBT), and rapid shallow breathing index (RSBI) was recorded. The indicators of right diaphragm thickness at the end of inspiration (DTei) and expiration (DTee) were determined by bedside ultrasound at 5 minutes and 60 minutes of SBT, and DTF was calculated, the changes in above parameters were observed during SBT. The patients were divided into successful weaning group and failure weaning group, and the differences in above indexes were compared between the two groups. Receiver operating characteristic curve (ROC) was used to evaluate the predictive value of DTF and RSBI at 60 minutes of SBT on successful weaning. A total of 37 patients were enrolled in the study. Ultrasonic measurement data of 63 person-times at 5 minutes of SBT and 50 at 60 minutes of SBT were obtained. There were no statistical differences in RSBI, DTei, DTee, and DTF at 5 minutes of SBT between successful weaning group (n = 33) and failure weaning group (n = 30). At 60 minutes of SBT, compared with successful weaning group (n = 33), the patients in failure weaning group (n = 17) had a higher RSBI (times×min -1 ×L -1 : 80.41±29.08 vs. 63.94±23.84, t = 2.146, P = 0.037), and lower DTee, DTei and DTF [DTee (mm): 22.00±6.25 vs. 25.45±4.99, t = 2.127, P = 0.039; DTei (mm): 27.94±6.19 vs. 38.48±6.15, t = 5.731, P = 0.000; DTF: (24.46±14.11)% vs. (62.04±30.21)%, t = 4.845, P = 0.000]. There were no statistical differences in RSBI, DTei, DTee, and DTF between 5 minutes and 60 minutes of SBT in 33

  7. Predicting success of metabolic surgery: age, body mass index, C-peptide, and duration score.

    Science.gov (United States)

    Lee, Wei-Jei; Hur, Kyung Yul; Lakadawala, Muffazal; Kasama, Kazunori; Wong, Simon K H; Chen, Shu-Chun; Lee, Yi-Chih; Ser, Kong-Han

    2013-01-01

    Surgery is the most effective treatment of morbid obesity and leads to dramatic improvements in type 2 diabetes mellitus (T2DM). Gastrointestinal metabolic surgery has been proposed as a treatment option for T2DM. However, a grading system to categorize and predict the outcome of metabolic surgery is lacking. The study setting was a tertiary referral hospital (Taoyuan City, Taoyuan County, Taiwan). We first evaluated 63 patients and identified 4 factors that predicted the success of T2DM remission after bariatric surgery in this cohort: body mass index, C-peptide level, T2DM duration, and patient age. We used these variables to construct the Diabetes Surgery Score, a multidimensional 10-point scale along which greater scores indicate a better chance of T2DM remission. We then validated the index in a prospective collected cohort of 176 patients, using remission of T2DM at 1 year after surgery as the outcome variable. A total of 48 T2DM remissions occurred among the 63 patients and 115 remissions (65.3%) in the validation cohort. Patients with T2DM remission after surgery had a greater Diabetes Surgery Score than those without (8 ± 4 versus 4 ± 4, P Surgery Score also had a greater rate of success with T2DM remission (from 33% at score 0 to 100% at score 10); A 1-point increase in the Diabetes Surgery Score translated to an absolute 6.7% in the success rate. The Diabetes Surgery Score is a simple multidimensional grading system that can predict the success of T2DM treatment using bariatric surgery among patients with inadequately controlled T2DM. Copyright © 2013 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  8. Fingerprint verification prediction model in hand dermatitis.

    Science.gov (United States)

    Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah

    2015-07-01

    Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

  9. Massive Predictive Modeling using Oracle R Enterprise

    CERN Multimedia

    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...

  10. Real-time index for predicting successful golf putting motion using multichannel EEG.

    Science.gov (United States)

    Muangjaroen, Piyachat; Wongsawat, Yodchanan

    2012-01-01

    A skill in goal-directed sport performance is an ability involving with many factors of both external and internal concernment. External factors are still developed while internal factors are challenged topic to understand for improving the performance. Internal concernment is explained an effective performance as estimation, solving strategy, planning and decision on the brain. These conjunctions are relevant to somatosensory information, focus attention and fine motor control of cortical activity. Five skilled right-handed golfers were recruited to be subjected of studying the criteria on how to predict golf putt success. Each of their putts was calculated in power spectral analysis by comparing to the pre-movement period. Successful and unsuccessful putt were classified by focusing on the frontal-midline(Fz), parietal-midline(Pz), central midline(Cz), left central(C3) and right central(C4) which supported by few consistency studies that they are related to a primary sensory motor area, focus attention and working memory processing. Results were shown that high alpha power on C4, theta power on Fz, theta power and high alpha power on Pz can be calculated to use as index of predicting golf putt success. Real-time monitoring system with friendly GUI was proposed in this study as promising preliminary study. Expected goal in the future is to apply this real-time golf putting prediction system into a biofeedback system to increase the golf putting's accuracy. However, it still needs more subjects to increase credibility and accuracy of the prediction.

  11. Predictability of successful trans-arterial embolization in pelvic fracture bleeding based on patient initial presentation.

    Science.gov (United States)

    Tung, Cheng-Cheng; Yu, Jei-Feng; Lan, Shou-Jen

    2017-12-24

    Pelvic fracture bleeding generally leads to hemorrhagic shock. Trans-arterial embolization (TAE) is regarded as the most useful treatment; however, the initial presentation of the patient can impact the effectiveness of TAE for pelvic fracture bleeding. The aim of this retrospective study is to explore whether the patient data at the initial presentation can predict the success of TAE for pelvic fracture bleeding. Twenty-seven charts were retrospectively reviewed. TAE failure was defined as any patient who eventually received an exigent laparotomy or who died due to uncontrolled bleeding after TAE. For patients who received TAE, we analyzed factors recorded at the initial presentation, including age, gender, systolic blood pressure, heart rate, respiratory rate, body temperature, Glasgow coma scale (GCS) score, injury severity score (ISS) and associated injuries, using Pearson's correlation and independent t-tests. The odds ratio was used to determine the cut-off values for the patient presentation findings related to successful TAE and thus was used to assess congruity. Successful TAE was not correlated with age or gender. The hierarchical order of statistically significant associations between successful TAE and initial presentation data was as follows: the patient's body temperature, associated injury, respiratory rate, systolic blood pressure, GCS score, and ISS. The odds ratios for all statistically significant initial presentation factors were within a 95% confidence interval. The findings upon initial presentation of a patient with pelvic fracture bleeding that were related to the predictability of successful TAE include the following: hypothermia prevention with maintenance of the body temperature above 36°C, associated injuries limited to two organ systems, maintenance of the respiratory rate at approximately twenty-two breaths per minute, a sustained systolic blood pressure of approximately 90mmHg, maintenance of a heart rate of approximately one hundred

  12. Predictive Model of Systemic Toxicity (SOT)

    Science.gov (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Risk Prediction Models for Oral Clefts Allowing for Phenotypic Heterogeneity

    Directory of Open Access Journals (Sweden)

    Yalu eWen

    2015-08-01

    Full Text Available Oral clefts are common birth defects that have a major impact on the affected individual, their family and society. World-wide, the incidence of oral clefts is 1/700 live births, making them the most common craniofacial birth defects. The successful prediction of oral clefts may help identify sub-population at high risk, and promote new diagnostic and therapeutic strategies. Nevertheless, developing a clinically useful oral clefts risk prediction model remains a great challenge. Compelling evidences suggest the etiologies of oral clefts are highly heterogeneous, and the development of a risk prediction model with consideration of phenotypic heterogeneity may potentially improve the accuracy of a risk prediction model. In this study, we applied a previously developed statistical method to investigate the risk prediction on sub-phenotypes of oral clefts. Our results suggested subtypes of cleft lip and palate have similar genetic etiologies (AUC=0.572 with subtypes of cleft lip only (AUC=0.589, while the subtypes of cleft palate only (CPO have heterogeneous underlying mechanisms (AUCs for soft CPO and hard CPO are 0.617 and 0.623, respectively. This highlighted the potential that the hard and soft forms of CPO have their own mechanisms despite sharing some of the genetic risk factors. Comparing with conventional methods for risk prediction modeling, our method considers phenotypic heterogeneity of a disease, which potentially improves the accuracy for predicting each sub-phenotype of oral clefts.

  5. 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…

  6. 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......). 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...... visualization to improve our understanding of the different attained performances, effectively compiling all the conducted experiments in a meaningful way. We complete our study with an entropy-based analysis that highlights the uncertainty handling properties provided by the GP, crucial for prediction tasks...

  7. Predictive fine granularity successive elimination for fast optimal block-matching motion estimation.

    Science.gov (United States)

    Zhu, Ce; Qi, Wei-Song; Ser, Wee

    2005-02-01

    Given the number of checking points, the speed of block motion estimation depends on how fast the block matching is. In this paper, a new framework, fine granularity successive elimination (FGSE), is proposed for fast optimal block matching in motion estimation. The FGSE features providing a sequence of nondecreasing fine-grained boundary levels to reject a checking point using as little computation as possible, where block complexity is utilized to determine the order of partitioning larger sub-blocks into smaller subblocks in the creation of the fine-grained boundary levels. It is shown that the well-known successive elimination algorithm (SEA) and multilevel successive elimination algorithm (MSEA) are just two special cases in the FGSE framework. Moreover, in view that two adjacent checking points (blocks) share most of the block pixels with just one pixel shifting horizontally or vertically, we develop a scheme to predict the rejection level for a candidate by exploiting the correlation of matching errors between two adjacent checking points. The resulting predictive FGSE algorithm can further reduce computation load by skipping some redundant boundary levels. Experimental results are presented to verify substantial computational savings of the proposed algorithm in comparison with the SEA/MSEA.

  8. 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%; pbike 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.

  9. Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models.

    Science.gov (United States)

    Liu, Bowen; Ramsundar, Bharath; Kawthekar, Prasad; Shi, Jade; Gomes, Joseph; Luu Nguyen, Quang; Ho, Stephen; Sloane, Jack; Wender, Paul; Pande, Vijay

    2017-10-25

    We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder-decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis.

  10. 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.

  11. Predicting and Modeling RNA Architecture

    Science.gov (United States)

    Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

    2011-01-01

    SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

  12. Multiple Steps Prediction with Nonlinear ARX Models

    OpenAIRE

    Zhang, Qinghua; Ljung, Lennart

    2007-01-01

    NLARX (NonLinear AutoRegressive with eXogenous inputs) models are frequently used in black-box nonlinear system identication. Though it is easy to make one step ahead prediction with such models, multiple steps prediction is far from trivial. The main difficulty is that in general there is no easy way to compute the mathematical expectation of an output conditioned by past measurements. An optimal solution would require intensive numerical computations related to nonlinear filltering. The pur...

  13. 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.

  14. Model complexity control for hydrologic prediction

    Science.gov (United States)

    Schoups, G.; van de Giesen, N. C.; Savenije, H. H. G.

    2008-12-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore needed. We compare three model complexity control methods for hydrologic prediction, namely, cross validation (CV), Akaike's information criterion (AIC), and structural risk minimization (SRM). Results show that simulation of water flow using non-physically-based models (polynomials in this case) leads to increasingly better calibration fits as the model complexity (polynomial order) increases. However, prediction uncertainty worsens for complex non-physically-based models because of overfitting of noisy data. Incorporation of physically based constraints into the model (e.g., storage-discharge relationship) effectively bounds prediction uncertainty, even as the number of parameters increases. The conclusion is that overparameterization and equifinality do not lead to a continued increase in prediction uncertainty, as long as models are constrained by such physical principles. Complexity control of hydrologic models reduces parameter equifinality and identifies the simplest model that adequately explains the data, thereby providing a means of hydrologic generalization and classification. SRM is a promising technique for this purpose, as it (1) provides analytic upper bounds on prediction uncertainty, hence avoiding the computational burden of CV, and (2) extends the applicability of classic methods such as AIC to finite data. The main hurdle in applying SRM is the need for an a priori estimation of the complexity of the hydrologic model, as measured by its Vapnik-Chernovenkis (VC) dimension. Further research is needed in this area.

  15. Predicting success of methotrexate treatment by pretreatment HCG level and 24-hour HCG increment.

    Science.gov (United States)

    Levin, Gabriel; Saleh, Narjes A; Haj-Yahya, Rani; Matan, Liat S; Avi, Benshushan

    2018-04-01

    To evaluate β-human chorionic gonadotropin (β-HCG) level and its 24-hour increment as predictors of successful methotrexate treatment for ectopic pregnancy. Data were retrospectively reviewed from women with ectopic pregnancy who were treated by single-dose methotrexate (50 mg/m 2 ) at a university hospital in Jerusalem, Israel, between January 1, 2000, and June 30, 2015. Serum β-HCG before treatment and its percentage increment in the 24 hours before treatment were compared between treatment success and failure groups. Sixty-nine women were included in the study. Single-dose methotrexate treatment was successful for 44 (63.8%) women. Both mean β-HCG level and its 24-hour increment were lower for women with successful treatment than for those with failed treatment (respectively, 1224 IU\\L vs 2362 IU\\L, P=0.018; and 13.5% vs 29.6%, P=0.009). Receiver operator characteristic curve analysis yielded cutoff values of 1600 IU\\L and 14% increment with a positive predictive value of 75% and 82%, respectively, for treatment success. β-HCG level and its 24-hour increment were independent predictors of treatment outcome by logistic regression (both PHCG increment of less than 14% in the 24 hours before single-dose methotrexate and serum β-HCG of less than 1600 IU\\L were found to be good predictors of treatment success. © 2017 International Federation of Gynecology and Obstetrics.

  16. 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.

  17. 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.

  18. Quantifying predictive accuracy in survival models.

    Science.gov (United States)

    Lirette, Seth T; Aban, Inmaculada

    2017-12-01

    For time-to-event outcomes in medical research, survival models are the most appropriate to use. Unlike logistic regression models, quantifying the predictive accuracy of these models is not a trivial task. We present the classes of concordance (C) statistics and R 2 statistics often used to assess the predictive ability of these models. The discussion focuses on Harrell's C, Kent and O'Quigley's R 2 , and Royston and Sauerbrei's R 2 . We present similarities and differences between the statistics, discuss the software options from the most widely used statistical analysis packages, and give a practical example using the Worcester Heart Attack Study dataset.

  19. Predictive power of nuclear-mass models

    Directory of Open Access Journals (Sweden)

    Yu. A. Litvinov

    2013-12-01

    Full Text Available Ten different theoretical models are tested for their predictive power in the description of nuclear masses. Two sets of experimental masses are used for the test: the older set of 2003 and the newer one of 2011. The predictive power is studied in two regions of nuclei: the global region (Z, N ≥ 8 and the heavy-nuclei region (Z ≥ 82, N ≥ 126. No clear correlation is found between the predictive power of a model and the accuracy of its description of the masses.

  20. 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...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

  1. 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.

  2. Accuracy assessment of landslide prediction models

    International Nuclear Information System (INIS)

    Othman, A N; Mohd, W M N W; Noraini, S

    2014-01-01

    The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones

  3. A model for successful use of student response systems.

    Science.gov (United States)

    Klein, Kathleen; Kientz, Mary

    2013-01-01

    This article presents a model developed to assist teachers in selecting, implementing, and assessing student response system (SRS) use in the classroom. Research indicates that SRS technology is effective in achieving desired outcomes in higher education settings. Studies indicate that effective SRS use promotes greater achievement of learning outcomes, increased student attention, improved class participation, and active engagement. The model offered in this article is based on best practices described in the literature and several years of SRS use in a traditional higher education classroom setting. Student feedback indicates increased class participation and engagement with SRS technology. Teacher feedback indicates opportunities for contingent teaching. The model described in this article provides a process to assist teachers in the successful selection, implementation, and assessment of SRS technology in the classroom.

  4. Successes and failures of the constituent quark model

    International Nuclear Information System (INIS)

    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

  5. Can terrestrial laser scanners (TLSs) and hemispherical photographs predict tropical dry forest succession with liana abundance?

    Science.gov (United States)

    Sánchez-Azofeifa, Gerardo Arturo; Guzmán-Quesada, J. Antonio; Vega-Araya, Mauricio; Campos-Vargas, Carlos; Milena Durán, Sandra; D'Souza, Nikhil; Gianoli, Thomas; Portillo-Quintero, Carlos; Sharp, Iain

    2017-03-01

    Tropical dry forests (TDFs) are ecosystems with long drought periods, a mean temperature of 25 °C, a mean annual precipitation that ranges from 900 to 2000 mm, and that possess a high abundance of deciduous species (trees and lianas). What remains of the original extent of TDFs in the Americas remains highly fragmented and at different levels of ecological succession. It is estimated that one of the main fingerprints left by global environmental and climate change in tropical environments is an increase in liana coverage. Lianas are non-structural elements of the forest canopy that eventually kill their host trees. In this paper we evaluate the use of a terrestrial laser scanner (TLS) in combination with hemispherical photographs (HPs) to characterize changes in forest structure as a function of ecological succession and liana abundance. We deployed a TLS and HP system in 28 plots throughout secondary forests of different ages and with different levels of liana abundance. Using a canonical correlation analysis (CCA), we addressed how the VEGNET, a terrestrial laser scanner, and HPs could predict TDF structure. Likewise, using univariate analyses of correlations, we show how the liana abundance could affect the prediction of the forest structure. Our results suggest that TLSs and HPs can predict the differences in the forest structure at different successional stages but that these differences disappear as liana abundance increases. Therefore, in well known ecosystems such as the tropical dry forest of Costa Rica, these biases of prediction could be considered as structural effects of liana presence. This research contributes to the understanding of the potential effects of lianas in secondary dry forests and highlights the role of TLSs combined with HPs in monitoring structural changes in secondary TDFs.

  6. 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.

  7. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  8. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  9. 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

  10. Using Empirical Models for Communication Prediction of Spacecraft

    Science.gov (United States)

    Quasny, Todd

    2015-01-01

    A viable communication path to a spacecraft is vital for its successful operation. For human spaceflight, a reliable and predictable communication link between the spacecraft and the ground is essential not only for the safety of the vehicle and the success of the mission, but for the safety of the humans on board as well. However, analytical models of these communication links are challenged by unique characteristics of space and the vehicle itself. For example, effects of radio frequency during high energy solar events while traveling through a solar array of a spacecraft can be difficult to model, and thus to predict. This presentation covers the use of empirical methods of communication link predictions, using the International Space Station (ISS) and its associated historical data as the verification platform and test bed. These empirical methods can then be incorporated into communication prediction and automation tools for the ISS in order to better understand the quality of the communication path given a myriad of variables, including solar array positions, line of site to satellites, position of the sun, and other dynamic structures on the outside of the ISS. The image on the left below show the current analytical model of one of the communication systems on the ISS. The image on the right shows a rudimentary empirical model of the same system based on historical archived data from the ISS.

  11. Joint modeling of success and treatment discontinuation in in vitro fertilization programs: a retrospective cohort study

    Directory of Open Access Journals (Sweden)

    Troude Pénélope

    2012-08-01

    Full Text Available Abstract Background As discontinuation in in vitro fertilization (IVF programs has been associated with a poor prognosis, one hypothesis is that some couple-specific predictive factors in IVF may be shared with opposite effect by both success (i.e. live birth and treatment discontinuation processes. Our objective was to perform a joint analysis of these two processes to examine the hypothesis of a link between the two processes. Methods Analyses were conducted on a retrospective cohort of 3,002 women who began IVF between 1998 and 2002 in two French IVF centers: a Parisian center and a center in a medium-sized city in central France. A shared random effects model based on a joint modelization of IVF treatment success and discontinuation was used to study the link between the two processes. Results Success and discontinuation processes were significantly linked in the medium-sized city center, whereas they were not linked in the Parisian center. The center influenced risk of treatment discontinuation but not chance of success. The well-known inverse-J relation between the woman’s age and chance of success was observed, as expected. Risk of discontinuation globally increased as the woman’s age increased. Conclusions The link between success and discontinuation processes could depend on the fertility center. In particular, the woman’s decision to pursue or to discontinue IVF in a particular center could depend on the presence of other IVF centers in the surrounding area.

  12. Developing entrepreneurial competencies for successful business model canvas

    Science.gov (United States)

    Sundah, D. I. E.; Langi, C.; Maramis, D. R. S.; Tawalujan, L. dan

    2018-01-01

    We explore the competencies of entrepreneurship that contribute to business model canvas. This research conducted at smoked fish industries in Province of North Sulawesi, Indonesia. This research used a mixed method which integrating both quantitative and qualitative approaches in a sequential design. The technique of snowball sampling and questionnaire has been used in collecting data from 44 entrepreneurs. Structural equation modeling with SmartPLS application program has been used in analyzing this data to determine the effect of entrepreneurial competencies on business model canvas. We also investigate 3 entrepreneurs who conducted smoked fish business and analyzed their business by using business model canvas. Focus Group Discussion is used in collecting data from 2 groups of entrepreneurs from 2 different locations. The empirical results show that entrepreneurial competencies which consists of managerial competencies, technical competencies, marketing competencies, financial competencies, human relations competencies, and the specific working attitude of entrepreneur has a positive and significantly effect on business model canvas. Additionally, the empirical cases and discussion with 2 groups of entrepreneurs support the quantitative result and it found that human relations competencies have greater influence in achieving successful business model canvas.

  13. Posterior predictive checking of multiple imputation models.

    Science.gov (United States)

    Nguyen, Cattram D; Lee, Katherine J; Carlin, John B

    2015-07-01

    Multiple imputation is gaining popularity as a strategy for handling missing data, but there is a scarcity of tools for checking imputation models, a critical step in model fitting. Posterior predictive checking (PPC) has been recommended as an imputation diagnostic. PPC involves simulating "replicated" data from the posterior predictive distribution of the model under scrutiny. Model fit is assessed by examining whether the analysis from the observed data appears typical of results obtained from the replicates produced by the model. A proposed diagnostic measure is the posterior predictive "p-value", an extreme value of which (i.e., a value close to 0 or 1) suggests a misfit between the model and the data. The aim of this study was to evaluate the performance of the posterior predictive p-value as an imputation diagnostic. Using simulation methods, we deliberately misspecified imputation models to determine whether posterior predictive p-values were effective in identifying these problems. When estimating the regression parameter of interest, we found that more extreme p-values were associated with poorer imputation model performance, although the results highlighted that traditional thresholds for classical p-values do not apply in this context. A shortcoming of the PPC method was its reduced ability to detect misspecified models with increasing amounts of missing data. Despite the limitations of posterior predictive p-values, they appear to have a valuable place in the imputer's toolkit. In addition to automated checking using p-values, we recommend imputers perform graphical checks and examine other summaries of the test quantity distribution. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. 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...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

  15. 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...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  16. Comparative Study of Bancruptcy Prediction Models

    Directory of Open Access Journals (Sweden)

    Isye Arieshanti

    2013-09-01

    Full Text Available Early indication of bancruptcy is important for a company. If companies aware of  potency of their bancruptcy, they can take a preventive action to anticipate the bancruptcy. In order to detect the potency of a bancruptcy, a company can utilize a a model of bancruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully. Because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for bancruptcy prediction. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP, Hybrid of MLP + Multiple Linear Regression, it can be showed that fuzzy k-NN method achieve the best performance with accuracy 77.5%

  17. 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

  18. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  19. Are animal models predictive for humans?

    Directory of Open Access Journals (Sweden)

    Greek Ray

    2009-01-01

    Full Text Available Abstract It is one of the central aims of the philosophy of science to elucidate the meanings of scientific terms and also to think critically about their application. The focus of this essay is the scientific term predict and whether there is credible evidence that animal models, especially in toxicology and pathophysiology, can be used to predict human outcomes. Whether animals can be used to predict human response to drugs and other chemicals is apparently a contentious issue. However, when one empirically analyzes animal models using scientific tools they fall far short of being able to predict human responses. This is not surprising considering what we have learned from fields such evolutionary and developmental biology, gene regulation and expression, epigenetics, complexity theory, and comparative genomics.

  20. Human Factors Predicting Failure and Success in Hospital Information System Implementations in Sub-Saharan Africa.

    Science.gov (United States)

    Verbeke, Frank; Karara, Gustave; Nyssen, Marc

    2015-01-01

    From 2007 through 2014, the authors participated in the implementation of open source hospital information systems (HIS) in 19 hospitals in Rwanda, Burundi, DR Congo, Congo-Brazzaville, Gabon, and Mali. Most of these implementations were successful, but some failed. At the end of a seven-year implementation effort, a number of risk factors, facilitators, and pragmatic approaches related to the deployment of HIS in Sub-Saharan health facilities have been identified. Many of the problems encountered during the HIS implementation process were not related to technical issues but human, cultural, and environmental factors. This study retrospectively evaluates the predictive value of 14 project failure factors and 15 success factors in HIS implementation in the Sub-Saharan region. Nine of the failure factors were strongly correlated with project failure, three were moderately correlated, and one weakly correlated. Regression analysis also confirms that eight factors were strongly correlated with project success, four moderately correlated, and two weakly correlated. The study results may help estimate the expedience of future HIS projects.

  1. Botulinum toxin injection for restrictive myopathy of thyroid-associated orbitopathy: success rate and predictive factors.

    Science.gov (United States)

    Akbari, Mohammad Reza; Ameri, Ahmad; Keshtkar Jaafari, Ali Reza; Mirmohammadsadeghi, Arash

    2016-04-01

    To evaluate the rate of and predictive factors for successful treatment of restrictive myopathy in thyroid-associated orbitopathy (TAO) using botulinum toxin injection. Twenty patients with restrictive myopathy of TAO were enrolled in the study. Abnormal thyroid function test results were not a prerequisite for inclusion. In each extraocular muscle 25 units of botulinum toxinA were injected. The success rate, calculated at 2 years or last follow-up before surgery, was defined as proportion of the cases with esotropia of extorsion (P = 0.01). In the multivariate logistic regression, only lower amount of hypotropia was significantly associated with the success (P = 0.09, OR = 1.36). Botulinum toxin injection can be an effective alternative for the treatment of the restrictive myopathy in TAO. The best candidates for injection of the toxin are patients with esotropia, smaller angle of horizontal and vertical deviations, and lower degree of extorsion. Copyright © 2016 American Association for Pediatric Ophthalmology and Strabismus. Published by Elsevier Inc. All rights reserved.

  2. 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

  3. 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.

  4. Cephalometric variables predicting the long-term success or failure of combined rapid maxillary expansion and facial mask therapy.

    Science.gov (United States)

    Baccetti, Tiziano; Franchi, Lorenzo; McNamara, James A

    2004-07-01

    The aim of this study was to select a model of cephalometric variables to predict the results of early treatment of Class III malocclusion with rapid maxillary expansion and facemask therapy followed by comprehensive treatment with fixed appliances. Lateral cephalograms of 42 patients (20 boys, 22 girls) with Class III malocclusion were analyzed at the start of treatment (mean age 8 years 6 months +/- 2 years, at stage I in cervical vertebral maturation). All patients were reevaluated after a mean period of 6 years 6 months (at stage IV or V in cervical vertebral maturation) that included active treatment plus retention. At this time, the sample was divided into 2 groups according to occlusal criteria: a successful group (30 patients) and an unsuccessful group (12 patients). Discriminant analysis was applied to select pretreatment predictive variables of long-term treatment outcome. Stepwise variable selection of the cephalometric measurements at the first observation identified 3 predictive variables. Orthopedic treatment of Class III malocclusion might be unfavorable over the long term when a patient's pretreatment cephalometric records exhibit a long mandibular ramus (ie, increased posterior facial height), an acute cranial base angle, and a steep mandibular plane angle. On the basis of the equation generated by the multivariate statistical method, the outcome of interceptive orthopedic treatment for each new patient with Class III malocclusion can be predicted with a probability error of 16.7%.

  5. A Model for Predicting Student Performance on High-Stakes Assessment

    Science.gov (United States)

    Dammann, Matthew Walter

    2010-01-01

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

  6. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2014-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  7. 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.

  8. A Case of Vertebral Artery Fusiform Aneurysm Treated by Flow Alteration: Successful Prediction of Therapeutic Effects Using Computational Fluid Dynamics.

    Science.gov (United States)

    Miura, Yoichi; Ishida, Fujimaro; Kamei, Yusuke; Tsuji, Masanori; Shiba, Masato; Tanemura, Hiroshi; Umeda, Yasuyuki; Shimosaka, Shinichi; Suzuki, Hidenori

    2017-10-01

    The treatment of intracranial complicated aneurysms remains challenging. In patients with complicated aneurysms that are neither clippable nor coilable, flow alteration treatment (FAT) with a combined procedure of proximal/distal occlusion or trapping of an aneurysm with bypass surgery has been reported. However, it is difficult to predict whatever FAT can achieve aneurysmal obliteration without ischemic complications. A 69-year-old female was incidentally diagnosed with a left vertebral artery (VA) fusiform aneurysm distal to the left posterior inferior cerebellar artery (PICA). Because one-year follow-up three-dimensional computed tomography angiography showed that the aneurysm grew significantly, surgical management was considered the therapy of choice. For determining treatment strategies, we assumed left VA occlusion at the proximal to the left PICA as a FAT model and performed computational fluid dynamics (CFD) analyses. The FAT model had much lower wall shear stress and shear rate at the aneurysm dome than presumed thresholds necessary to thrombus formation, while those at the PICA were obviously higher than the thresholds, and streamlines into the left PICA from the distal VA were preserved. These findings theoretically meant that surgical occlusion of the left VA proximal to the left PICA and aneurysm would induce intra-aneurysmal thrombus formation with preservation of the left PICA flow. The treatment was performed successfully and achieved the predicted results. CFD simulations may be useful to predict effects of FAT for complicated aneurysms.

  9. 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. © 2010 The Author. Journal of Personality © 2010, Wiley Periodicals, Inc.

  10. Value of routine investigations to predict loop diuretic down-titration success in stable heart failure.

    Science.gov (United States)

    Martens, Pieter; Verbrugge, Frederik H; Boonen, Levinia; Nijst, Petra; Dupont, Matthias; Mullens, Wilfried

    2018-01-01

    Guidelines advocate down-titration of loop diuretics in chronic heart failure (CHF) when patients have no signs of volume overload. Limited data are available on the expected success rate of this practice or how routine diagnostic tests might help steering this process. Fifty ambulatory CHF-patients on stable neurohumoral blocker/diuretic therapy for at least 3months without any clinical sign of volume overload were prospectively included to undergo loop diuretic down-titration. All patients underwent a similar pre-down-titration evaluation consisting of a dyspnea scoring, physical examination, transthoracic echocardiography (diastolic function, right ventricular function, cardiac filling pressures and valvular disease), blood sample (serum creatinine, plasma NT-pro-BNP and neurohormones). Loop diuretic maintenance dose was subsequently reduced by 50% or stopped if dose was ≤40mg furosemide equivalents. Successful down-titration was defined as a persistent dose reduction after 30days without weight increase >1.5kg or new-onset symptoms of worsening heart failure. At 30-day follow-up, down-titration was successful in 62% (n=31). In 12/19 patients exhibiting down-titration failure, this occurred within the first week. Physical examination, transthoracic echocardiography and laboratory analysis had limited predictive capability to detect patients with down-titration success/failure (positive likelihood-ratios below 1.5, or area under the curve [AUC] non-statically different from AUC=0.5). Loop diuretic down-titration is feasible in a majority of stable CHF patients in which the treating clinician felt continuation of loops was unnecessary to sustain euvolemia. Importantly, routine diagnostics which suggest euvolemia, have limited diagnostic impact on the post-test probability. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  12. 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.…

  13. Thermodynamic modeling of activity coefficient and prediction of solubility: Part 1. Predictive models.

    Science.gov (United States)

    Mirmehrabi, Mahmoud; Rohani, Sohrab; Perry, Luisa

    2006-04-01

    A new activity coefficient model was developed from excess Gibbs free energy in the form G(ex) = cA(a) x(1)(b)...x(n)(b). The constants of the proposed model were considered to be function of solute and solvent dielectric constants, Hildebrand solubility parameters and specific volumes of solute and solvent molecules. The proposed model obeys the Gibbs-Duhem condition for activity coefficient models. To generalize the model and make it as a purely predictive model without any adjustable parameters, its constants were found using the experimental activity coefficient and physical properties of 20 vapor-liquid systems. The predictive capability of the proposed model was tested by calculating the activity coefficients of 41 binary vapor-liquid equilibrium systems and showed good agreement with the experimental data in comparison with two other predictive models, the UNIFAC and Hildebrand models. The only data used for the prediction of activity coefficients, were dielectric constants, Hildebrand solubility parameters, and specific volumes of the solute and solvent molecules. Furthermore, the proposed model was used to predict the activity coefficient of an organic compound, stearic acid, whose physical properties were available in methanol and 2-butanone. The predicted activity coefficient along with the thermal properties of the stearic acid were used to calculate the solubility of stearic acid in these two solvents and resulted in a better agreement with the experimental data compared to the UNIFAC and Hildebrand predictive models.

  14. 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.

  15. A revised prediction model for natural conception.

    Science.gov (United States)

    Bensdorp, Alexandra J; van der Steeg, Jan Willem; Steures, Pieternel; Habbema, J Dik F; Hompes, Peter G A; Bossuyt, Patrick M M; van der Veen, Fulco; Mol, Ben W J; Eijkemans, Marinus J C

    2017-06-01

    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 was to assess whether additional predictors can refine the Hunault model and extend its applicability. Consecutive subfertile couples with unexplained and mild male subfertility presenting in fertility clinics were asked to participate in a prospective cohort study. We constructed a multivariable prediction model with the predictors from the Hunault model and new potential predictors. The primary outcome, natural conception leading to an ongoing pregnancy, was observed in 1053 women of the 5184 included couples (20%). All predictors of the Hunault model were selected into the revised model plus an additional seven (woman's body mass index, cycle length, basal FSH levels, tubal status,history of previous pregnancies in the current relationship (ongoing pregnancies after natural conception, fertility treatment or miscarriages), semen volume, and semen morphology. Predictions from the revised model seem to concur better with observed pregnancy rates compared with the Hunault model; c-statistic of 0.71 (95% CI 0.69 to 0.73) compared with 0.59 (95% CI 0.57 to 0.61). Copyright © 2017. Published by Elsevier Ltd.

  16. 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…

  17. A structural equation model to integrate changes in functional strategies during old-field succession.

    Science.gov (United States)

    Vile, Denis; Shipley, Bill; Garnier, Eric

    2006-02-01

    From a functional perspective, changes in abundance, and ultimately species replacement, during succession are a consequence of integrated suites of traits conferring different relative ecological advantages as the environment changes over time. Here we use structural equations to model the interspecific relationships between these integrated functional traits using 34 herbaceous species from a Mediterranean old-field succession and thus quantify the notion of a plant strategy. We measured plant traits related to plant vegetative and reproductive size, leaf functioning, reproductive phenology, seed mass, and production on 15 individuals per species monitored during one growing season. The resulting structural equation model successfully accounts for the pattern of trait covariation during the first 45 years post-abandonment using just two forcing variables: time since site abandonment and seed mass; no association between time since field abandonment and seed mass was observed over these herbaceous stages of secondary succession. All other predicted traits values are determined by these two variables and the cause-effect linkage between them. Adding pre-reproductive vegetative mass as a third forcing variable noticeably increased the predictive power of the model. Increasing the time after abandonment favors species with increasing life span and pre-reproductive biomass and decreasing specific leaf area. Allometric coefficients relating vegetative and reproductive components of plant size were in accordance with allometry theory. The model confirmed the trade-off between seed mass and seed number. Maximum plant height and seed mass were major determinants of reproductive phenology. Our results show that beyond verbal conceptualization, plant ecological strategies can be quantified and modeled.

  18. Fire spread in chaparral – a comparison of laboratory data and model predictions in burning live fuels

    Science.gov (United States)

    David R. Weise; Eunmo Koo; Xiangyang Zhou; Shankar Mahalingam; Frédéric Morandini; Jacques-Henri Balbi

    2016-01-01

    Fire behaviour data from 240 laboratory fires in high-density live chaparral fuel beds were compared with model predictions. Logistic regression was used to develop a model to predict fire spread success in the fuel beds and linear regression was used to predict rate of spread. Predictions from the Rothermel equation and three proposed changes as well as two physically...

  19. Therapeutic effects and predictive factors for successful intravesical hyaluronic acid instillation in patients with interstitial cystitis/bladder pain syndrome

    Directory of Open Access Journals (Sweden)

    Cheng-Ling Lee

    2015-06-01

    Conclusion: Intravesical HA administrations improved IC symptoms, decreased bladder pain, and decreased frequency after four instillations, and decreased nocturia and increased bladder capacity after completion of all nine instillations. Low-grade glomerulation predicts successful outcome.

  20. New models for success emerge for US natural gas industry

    International Nuclear Information System (INIS)

    Addy, W.M.; Hutchinson, R.A.

    1994-01-01

    Very few companies in the US natural gas industry are confident in their ability to compete effectively in the brave new world of deregulation. Boston Consulting Group recently conducted an internal study to help the industry think about its future and identify models for success in this new environment. The authors examined the historical performance of 800 companies using several shareholder-value indicators, including cash-flow returns on investment, a measure of cash returns on cash invested that correlates closely to share price. Based on that review and discussions with investment managers and industry analysts, the authors were able to focus on a handful of companies that actually have thrived and created value against the difficult landscape of the past decade. Interviews with their senior executives provided important strategic and operational insights

  1. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

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

  2. 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.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Vaniel Fogli

    2014-01-01

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

  5. Laparoscopic sleeve gastrectomy for type 2 diabetes mellitus: predicting the success by ABCD score.

    Science.gov (United States)

    Lee, Wei-Jei; Almulaifi, Abdullah; Tsou, Ju Juin; Ser, Kong-Han; Lee, Yi-Chih; Chen, Shu-Chun

    2015-01-01

    Laparoscopic sleeve gastrectomy (LSG) is becoming a primary bariatric surgery for obesity and related diseases. This study presents the outcome of LSG with regard to the remission of type 2 diabetes mellitus (T2 DM) and the usefulness of a grading system to categorize and predict outcome of T2 DM remission. A total of 157 patients with T2 DM (82 women and 75 men) with morbid obesity (mean body mass index 39.0±7.4 kg/m(2)) who underwent LSG from 2006 to 2013 were selected for the present study. The ABCD score is composed of the patient's age, body mass index, C-peptide level, and duration of T2 DM (yr). The remission of T2 DM after LSG was evaluated using the ABCD score. At 12 months after surgery, 85 of the patients had complete follow-up data. The weight loss was 26.5% and the mean HbA1c decreased from 8.1% to 6.1%. A significant number of patients had improvement in their glycemic control, including 45 (52.9%) patients who had complete remission (HbA1csurgery had a higher ABCD score than those who did not (7.3±1.7 versus 5.2±2.1, Prate of success in T2 DM remission (from 0% in score 0 to 100% in score 10). LSG is an effective and well-tolerated procedure for achieving weight loss and T2 DM remission. The ABCD score, a simple multidimensional grading system, can predict the success of T2 DM treatment by LSG. Copyright © 2015 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  6. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    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 cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....... and controlled have thus become essential factors for efficient 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...

  7. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

    Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior......One of the major challenges with the increase in wind power generation is the uncertain nature of wind speed. So far the uncertainty about wind speed has been presented through probability distributions. Also the existing models that consider the uncertainty of the wind speed primarily view...

  8. Recent Successes and Remaining Challenges in Predicting Phosphorus Loading to Surface Waters at Large Scales

    Science.gov (United States)

    Harrison, J.; Metson, G.; Beusen, A.

    2017-12-01

    Over the past century humans have greatly accelerated phosphorus (P) flows from land to aquatic ecosystems, causing eutrophication and associated effects such as harmful algal blooms and hypoxia. Effectively addressing this challenge requires understanding geographic and temporal distribution of aquatic P loading, knowledge of major controls on P loading, and the relative importance of various potential P sources. The Global (N)utrient (E)xport from (W)ater(S)heds) NEWS model and recent improvements and extensions of this modeling system can be used to generate this understanding. This presentation will focus on insights global NEWS models grant into past, present, and potential future P sources and sinks, with a focus on the world's large rivers. Early results suggest: 1) that while aquatic P loading is globally dominated by particulate forms, dissolved P can be locally dominant; 2) that P loading has increased substantially at the global scale, but unevenly between world regions, with hotspots in South and East Asia; 3) that P loading is likely to continue to increase globally, but decrease in certain regions that are actively pursuing proactive P management; and 4) that point sources, especially in urban centers, play an important (even dominant) role in determining loads of dissolved inorganic P. Despite these insights, substantial unexplained variance remains when model predictions and measurements are compared at global and regional scales, for example within the U.S. Disagreements between model predictions and measurements suggest opportunities for model improvement. In particular, explicit inclusion of soil characteristics and the concept of temporal P legacies in future iterations of NEWS (and other) models may help improve correspondence between models and measurements.

  9. Comparison of two ordinal prediction models

    DEFF Research Database (Denmark)

    Kattan, Michael W; Gerds, Thomas A

    2015-01-01

    system (i.e. old or new), such as the level of evidence for one or more factors included in the system or the general opinions of expert clinicians. However, given the major objective of estimating prognosis on an ordinal scale, we argue that the rival staging system candidates should be compared...... on their ability to predict outcome. We sought to outline an algorithm that would compare two rival ordinal systems on their predictive ability. RESULTS: We devised an algorithm based largely on the concordance index, which is appropriate for comparing two models in their ability to rank observations. We...... demonstrate our algorithm with a prostate cancer staging system example. CONCLUSION: We have provided an algorithm for selecting the preferred staging system based on prognostic accuracy. It appears to be useful for the purpose of selecting between two ordinal prediction models....

  10. Somatologic characteristics of biathlon students’ body constitution in predicting of their successfulness

    Directory of Open Access Journals (Sweden)

    S. G. Priymak

    2017-08-01

    Full Text Available Purpose: determination of somatologic characteristics of biathlon students’ body constitution in predicting of their successfulness. Material: in the research the following students participated (n=27, age19-21 years, boys n=17, girls n=10. Quetelet’s, Erisman’s and Piniet’s anthropometric indices were calculated as well as life index. Results: the greatest distinctions between boys and girls were observed by the following absolute indicators: body, trunk and torso lengths; body mass. The least distinctions were by the length of upper and lower limbs, which prevail in boys. In girls we observed noticeable realization of diaphragm breathing. It permits to increase alveolar surface at the cost of lungs’ stretching in longitudinal direction. With it, there was no visible change of chest excursion. Relatively high level of women’s physical fitness conditions asthenia (dolymorphia. It results in approximation of girls’ chest shape to men’s. In boys formation of somatic type is realized at the cost of chest circumferential sizes but directly depends on the strength of hands’ and back’s muscles. Conclusions: for some sport-pedagogic activities (in our case - biathlon certain type of body constitution is intrinsic, which conditions successfulness of professional program realization. Somatic type characterizes compliance and correlation of separated body links. These criteria permit to reduce costly part of future specialist’s training and achieve high results in professional activity.

  11. Short-term test for predicting the potential of xenobiotics to impair reproductive success in fish

    Energy Technology Data Exchange (ETDEWEB)

    Landner, L.; Neilson, A.H.; Soerensen, L.T.; Taernholm, A.V.; Viktor, T.

    1985-06-01

    Short-term screening tests with the zebra fish (Brachydanio rerio) have been developed for predicting the potential of xenobiotics to impair reproductive success in fish. The aim was to find simple and sensitive test parameters and to simulate exposure situations typical for anadromous fish species (salmonids), which generally cross heavily polluted coastal areas or estuaries before they reach uncontaminated upstream spawning areas. Therefore, particular attention was directed to tests designed to assess adverse effects induced during gametogenesis in adult fish. The test protocol involves exposure of adults prior to, but not during, spawning and the effects are measured in the offspring as alterations in hatching frequency and hatching rate of eggs, and survival and stress tolerance of embryos and larvae. Some representative examples of the application of these tests are given, and it is shown that impairment of reproductive success can be induced by exposure of parent fish prior to spawning at concentrations of xenobiotics at least five times lower than those yielding effects during direct exposure of embryos and larvae. It is suggested that, in hazard assessment programs, tests of the effect of xenobiotics on the offspring of preexposed adults be routinely incorporated.

  12. Immobilized metal-affinity chromatography protein-recovery screening is predictive of crystallographic structure success.

    Science.gov (United States)

    Choi, Ryan; Kelley, Angela; Leibly, David; Hewitt, Stephen Nakazawa; Napuli, Alberto; Van Voorhis, Wesley

    2011-09-01

    The recombinant expression of soluble proteins in Escherichia coli continues to be a major bottleneck in structural genomics. The establishment of reliable protocols for the performance of small-scale expression and solubility testing is an essential component of structural genomic pipelines. The SSGCID Protein Production Group at the University of Washington (UW-PPG) has developed a high-throughput screening (HTS) protocol for the measurement of protein recovery from immobilized metal-affinity chromatography (IMAC) which predicts successful purification of hexahistidine-tagged proteins. The protocol is based on manual transfer of samples using multichannel pipettors and 96-well plates and does not depend on the use of robotic platforms. This protocol has been applied to evaluate the expression and solubility of more than 4000 proteins expressed in E. coli. The UW-PPG also screens large-scale preparations for recovery from IMAC prior to purification. Analysis of these results show that our low-cost non-automated approach is a reliable method for the HTS demands typical of large structural genomic projects. This paper provides a detailed description of these protocols and statistical analysis of the SSGCID screening results. The results demonstrate that screening for proteins that yield high recovery after IMAC, both after small-scale and large-scale expression, improves the selection of proteins that can be successfully purified and will yield a crystal structure.

  13. Predictive analytics can support the ACO model.

    Science.gov (United States)

    Bradley, Paul

    2012-04-01

    Predictive analytics can be used to rapidly spot hard-to-identify opportunities to better manage care--a key tool in accountable care. When considering analytics models, healthcare providers should: Make value-based care a priority and act on information from analytics models. Create a road map that includes achievable steps, rather than major endeavors. Set long-term expectations and recognize that the effectiveness of an analytics program takes time, unlike revenue cycle initiatives that may show a quick return.

  14. Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction.

    Science.gov (United States)

    López, Yosvany; Sharma, Alok; Dehzangi, Abdollah; Lal, Sunil Pranit; Taherzadeh, Ghazaleh; Sattar, Abdul; Tsunoda, Tatsuhiko

    2018-01-19

    Post-translational modification is considered an important biological mechanism with critical impact on the diversification of the proteome. Although a long list of such modifications has been studied, succinylation of lysine residues has recently attracted the interest of the scientific community. The experimental detection of succinylation sites is an expensive process, which consumes a lot of time and resources. Therefore, computational predictors of this covalent modification have emerged as a last resort to tackling lysine succinylation. In this paper, we propose a novel computational predictor called 'Success', which efficiently uses the structural and evolutionary information of amino acids for predicting succinylation sites. To do this, each lysine was described as a vector that combined the above information of surrounding amino acids. We then designed a support vector machine with a radial basis function kernel for discriminating between succinylated and non-succinylated residues. We finally compared the Success predictor with three state-of-the-art predictors in the literature. As a result, our proposed predictor showed a significant improvement over the compared predictors in statistical metrics, such as sensitivity (0.866), accuracy (0.838) and Matthews correlation coefficient (0.677) on a benchmark dataset. The proposed predictor effectively uses the structural and evolutionary information of the amino acids surrounding a lysine. The bigram feature extraction approach, while retaining the same number of features, facilitates a better description of lysines. A support vector machine with a radial basis function kernel was used to discriminate between modified and unmodified lysines. The aforementioned aspects make the Success predictor outperform three state-of-the-art predictors in succinylation detection.

  15. Predictive modeling in homogeneous catalysis: a tutorial

    NARCIS (Netherlands)

    Maldonado, A.G.; Rothenberg, G.

    2010-01-01

    Predictive modeling has become a practical research tool in homogeneous catalysis. It can help to pinpoint ‘good regions’ in the catalyst space, narrowing the search for the optimal catalyst for a given reaction. Just like any other new idea, in silico catalyst optimization is accepted by some

  16. Model predictive control of smart microgrids

    DEFF Research Database (Denmark)

    Hu, Jiefeng; Zhu, Jianguo; Guerrero, Josep M.

    2014-01-01

    required to realise high-performance of distributed generations and will realise innovative control techniques utilising model predictive control (MPC) to assist in coordinating the plethora of generation and load combinations, thus enable the effective exploitation of the clean renewable energy sources...

  17. Feedback model predictive control by randomized algorithms

    NARCIS (Netherlands)

    Batina, Ivo; Stoorvogel, Antonie Arij; Weiland, Siep

    2001-01-01

    In this paper we present a further development of an algorithm for stochastic disturbance rejection in model predictive control with input constraints based on randomized algorithms. The algorithm presented in our work can solve the problem of stochastic disturbance rejection approximately but with

  18. A Robustly Stabilizing Model Predictive Control Algorithm

    Science.gov (United States)

    Ackmece, A. Behcet; Carson, John M., III

    2007-01-01

    A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

  19. 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...

  20. 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.

  1. 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 ...

  2. [Succession caused by beaver (Castor fiber L.) life activity: II. A refined Markov model].

    Science.gov (United States)

    Logofet; Evstigneev, O I; Aleinikov, A A; Morozova, A O

    2015-01-01

    The refined Markov model of cyclic zoogenic successions caused by beaver (Castor fiber L.) life activity represents a discrete chain of the following six states: flooded forest, swamped forest, pond, grassy swamp, shrubby swamp, and wet forest, which correspond to certain stages of succession. Those stages are defined, and a conceptual scheme of probable transitions between them for one time step is constructed from the knowledge of beaver behaviour in small river floodplains of "Bryanskii Les" Reserve. We calibrated the corresponding matrix of transition probabilities according to the optimization principle: minimizing differences between the model outcome and reality; the model generates a distribution of relative areas corresponding to the stages of succession, that has to be compared to those gained from case studies in the Reserve during 2002-2006. The time step is chosen to equal 2 years, and the first-step data in the sum of differences are given various weights, w (between 0 and 1). The value of w = 0.2 is selected due to its optimality and for some additional reasons. By the formulae of finite homogeneous Markov chain theory, we obtained the main results of the calibrated model, namely, a steady-state distribution of stage areas, indexes of cyclicity, and the mean durations (M(j)) of succession stages. The results of calibration give an objective quantitative nature to the expert knowledge of the course of succession and get a proper interpretation. The 2010 data, which are not involved in the calibration procedure, enabled assessing the quality of prediction by the homogeneous model in short-term (from the 2006 situation): the error of model area distribution relative to the distribution observed in 2010 falls into the range of 9-17%, the best prognosis being given by the least optimal matrices (rejected values of w). This indicates a formally heterogeneous nature of succession processes in time. Thus, the refined version of the homogeneous Markov chain

  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. 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

  5. Using plural modeling for predicting decisions made by adaptive adversaries

    International Nuclear Information System (INIS)

    Buede, Dennis M.; Mahoney, Suzanne; Ezell, Barry; Lathrop, John

    2012-01-01

    Incorporating an appropriate representation of the likelihood of terrorist decision outcomes into risk assessments associated with weapons of mass destruction attacks has been a significant problem for countries around the world. Developing these likelihoods gets at the heart of the most difficult predictive problems: human decision making, adaptive adversaries, and adversaries about which very little is known. A plural modeling approach is proposed that incorporates estimates of all critical uncertainties: who is the adversary and what skills and resources are available to him, what information is known to the adversary and what perceptions of the important facts are held by this group or individual, what does the adversary know about the countermeasure actions taken by the government in question, what are the adversary's objectives and the priorities of those objectives, what would trigger the adversary to start an attack and what kind of success does the adversary desire, how realistic is the adversary in estimating the success of an attack, how does the adversary make a decision and what type of model best predicts this decision-making process. A computational framework is defined to aggregate the predictions from a suite of models, based on this broad array of uncertainties. A validation approach is described that deals with a significant scarcity of data.

  6. An Early Warning System: Predicting 10th Grade FCAT Success from 6th Grade FCAT Performance. Research Brief. Volume 0711

    Science.gov (United States)

    Froman, Terry; Brown, Shelly; Lapadula, Maria

    2008-01-01

    This Research Brief presents a method for predicting 10th grade Florida Comprehensive Assessment Test (FCAT) success from 6th grade FCAT performance. A simple equation provides the most probable single score prediction, and give-or-take error margins define high and low probability zones for expected 10th grade scores. In addition, a double-entry…

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

    Science.gov (United States)

    Hannon, Brenda

    2014-01-01

    To-date, studies have examined simultaneously the relative predictive powers of two or three factors on GPA. The present study examines the relative powers of five social/personality factors, five cognitive/learning factors, and SAT scores to predict freshmen and non-freshmen (sophomores, juniors, seniors) academic success (i.e., GPA). The results…

  8. Testing predictions of forest succession using long-term measurements: 100 yrs of observations in the Oregon Cascades

    Science.gov (United States)

    Mark E. Harmon; Robert J. Pabst

    2015-01-01

    Question: Many predictions about forest succession have been based on chronosequences. Are these predictions – at the population, community and ecosystemlevel – consistent with long-termmeasurements in permanent plots? Location: Pseudotsuga menziesii (Mirb.) Franco dominated forest in western Oregon, US.Methods: Over a 100-yr period,...

  9. Link Prediction via Sparse Gaussian Graphical Model

    Directory of Open Access Journals (Sweden)

    Liangliang Zhang

    2016-01-01

    Full Text Available Link prediction is an important task in complex network analysis. Traditional link prediction methods are limited by network topology and lack of node property information, which makes predicting links challenging. In this study, we address link prediction using a sparse Gaussian graphical model and demonstrate its theoretical and practical effectiveness. In theory, link prediction is executed by estimating the inverse covariance matrix of samples to overcome information limits. The proposed method was evaluated with four small and four large real-world datasets. The experimental results show that the area under the curve (AUC value obtained by the proposed method improved by an average of 3% and 12.5% compared to 13 mainstream similarity methods, respectively. This method outperforms the baseline method, and the prediction accuracy is superior to mainstream methods when using only 80% of the training set. The method also provides significantly higher AUC values when using only 60% in Dolphin and Taro datasets. Furthermore, the error rate of the proposed method demonstrates superior performance with all datasets compared to mainstream methods.

  10. Modeling N Cycling during Succession after Forest Disturbance: an Analysis of N Mining and Retention Hypothesis

    Science.gov (United States)

    Zhou, Z.; Ollinger, S. V.; Ouimette, A.; Lovett, G. M.; Fuss, C. B.; Goodale, C. L.

    2017-12-01

    Dissolved inorganic nitrogen losses at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA, have declined in recent decades, a pattern that counters expectations based on prevailing theory. An unbalanced ecosystem nitrogen (N) budget implies there is a missing component for N sink. Hypotheses to explain this discrepancy include increasing rates of denitrification and accumulation of N in mineral soil pools following N mining by plants. Here, we conducted a modeling analysis fused with field measurements of N cycling, specifically examining the hypothesis relevant to N mining and retention in mineral soils. We included simplified representations of both mechanisms, N mining and retention, in a revised ecosystem process model, PnET-SOM, to evaluate the dynamics of N cycling during succession after forest disturbance at the HBEF. The predicted N mining during the early succession was regulated by a metric representing a potential demand of extra soil N for large wood growth. The accumulation of nitrate in mineral soil pools was a function of the net aboveground biomass accumulation and soil N availability and parameterized based on field 15N tracer incubation data. The predicted patterns of forest N dynamics were consistent with observations. The addition of the new algorithms also improved the predicted DIN export in stream water with an R squared of 0.35 (Psuccession, and soil retention about 35% at the current forest stage at the HBEF.

  11. 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.)

  12. 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.

  13. Genetic models of homosexuality: generating testable predictions

    Science.gov (United States)

    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 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. PMID:17015344

  14. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

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

  15. 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

  16. 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.

  17. 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.

  18. 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…

  19. The Influence of Quality on E-Commerce Success: An Empirical Application of the Delone and Mclean IS Success Model

    OpenAIRE

    Ultan Sharkey; Murray Scott; Thomas Acton

    2010-01-01

    This research addresses difficulties in measuring e-commerce success by implementing the DeLone and McLean (D&M) model of IS success (1992, 2003) in an e-commerce environment. This research considers the influence of quality on e-commerce success by measuring the information quality and system quality attributes of an e-commerce system and the intention to use, user satisfaction and intention to transact from a sample of respondents. This research provides an empirical e-commerce application ...

  20. Immobilized metal-affinity chromatography protein-recovery screening is predictive of crystallographic structure success

    International Nuclear Information System (INIS)

    Choi, Ryan; Kelley, Angela; Leibly, David; Nakazawa Hewitt, Stephen; Napuli, Alberto; Van Voorhis, Wesley

    2011-01-01

    An overview of the methods used for high-throughput cloning and protein-expression screening of SSGCID hexahistidine recombinant proteins is provided. It is demonstrated that screening for recombinant proteins that are highly recoverable from immobilized metal-affinity chromatography improves the likelihood that a protein will produce a structure. The recombinant expression of soluble proteins in Escherichia coli continues to be a major bottleneck in structural genomics. The establishment of reliable protocols for the performance of small-scale expression and solubility testing is an essential component of structural genomic pipelines. The SSGCID Protein Production Group at the University of Washington (UW-PPG) has developed a high-throughput screening (HTS) protocol for the measurement of protein recovery from immobilized metal-affinity chromatography (IMAC) which predicts successful purification of hexahistidine-tagged proteins. The protocol is based on manual transfer of samples using multichannel pipettors and 96-well plates and does not depend on the use of robotic platforms. This protocol has been applied to evaluate the expression and solubility of more than 4000 proteins expressed in E. coli. The UW-PPG also screens large-scale preparations for recovery from IMAC prior to purification. Analysis of these results show that our low-cost non-automated approach is a reliable method for the HTS demands typical of large structural genomic projects. This paper provides a detailed description of these protocols and statistical analysis of the SSGCID screening results. The results demonstrate that screening for proteins that yield high recovery after IMAC, both after small-scale and large-scale expression, improves the selection of proteins that can be successfully purified and will yield a crystal structure

  1. A multifocal electroretinogram model predicting the development of diabetic retinopathy.

    Science.gov (United States)

    Bearse, Marcus A; Adams, Anthony J; Han, Ying; Schneck, Marilyn E; Ng, Jason; Bronson-Castain, Kevin; Barez, Shirin

    2006-09-01

    The prevalence of diabetes has been accelerating at an alarming rate in the last decade; some describe it as an epidemic. Diabetic eye complications are the leading cause of blindness in adults aged 25-74 in the United States. Early diagnosis and development of effective preventatives and treatments of diabetic retinopathy are essential to save sight. We describe efforts to establish functional indicators of retinal health and predictors of diabetic retinopathy. These indicators and predictors will be needed as markers of the efficacy of new therapies. Clinical trials aimed at either prevention or early treatments will rely heavily on the discovery of sensitive methods to identify patients and retinal locations at risk, as well as to evaluate treatment effects. We report on recent success in revealing local functional changes of the retina with the multifocal electroretinogram (mfERG). This objective measure allows the simultaneous recording of responses from over 100 small retinal patches across the central 45 degrees field. We describe the sensitivity of mfERG implicit time measurement for revealing functional alterations of the retina in diabetes, the local correspondence between functional (mfERG) and structural (vascular) abnormalities in eyes with early nonproliferative retinopathy, and longitudinal studies to formulate models to predict the retinal sites of future retinopathic signs. A multivariate model including mfERG implicit time delays and 'person' risk factors achieved 86% sensitivity and 84% specificity for prediction of new retinopathy development over one year at specific locations in eyes with some retinopathy at baseline. A preliminary test of the model yielded very positive results. This model appears to be the first to predict, quantitatively, the retinal locations of new nonproliferative diabetic retinopathy development over a one-year period. In a separate study, the predictive power of a model was assessed over one- and two-year follow

  2. 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

  3. 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.

  4. 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.

  5. 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...

  6. ON THE UTILITY OF SORNETTE’S CRASH PREDICTION MODEL

    Directory of Open Access Journals (Sweden)

    IOAN ROXANA

    2015-10-01

    Full Text Available Stock market crashes have been a constant subject of interest among capital market researchers. Crashes’ behavior has been largely studied, but the problem that remained unsolved until recently, was that of a prediction algorithm. Stock market crashes are complex and global events, rarely taking place on a singular national capital market. They usually occur simultaneously on several if not most capital markets, implying important losses among the investors. Investments made within various stock markets have an extremely important role within the global economy, influencing people’s lives in many ways. Presently, stock market crashes are being studied with great interest, not only because of the necessity of a deep understanding of the phenomenon, but also because of the fact that these crashes belong to the so-called category of “extreme phenomena”. Those are the main reasons that determined scientists to try building mathematical models for crashes prediction. Such a model was built by Professor Didier Sornette, inspired and adapted from an earthquake detection model. Still, the model keeps many characteristics of its predecessor, not being fully adapted to the economic realities and demands, or to the stock market’s characteristics. This paper attempts to test the utility of the model in predicting Bucharest Stock Exchange’s price falls, as well as the possibility of it being successfully used by investors.

  7. A predictive model for indoor radon occurrences - A first approximation

    International Nuclear Information System (INIS)

    LeGrand, H.E.

    1987-01-01

    Knowledge of how radon gas is transmitted in the shallow ground environment and how it emanates into buildings is grossly incomplete. Admittedly, some excellent research studies have been made and some general associations between certain aspects of the environment and radon occurrences in buildings are recognized. Yet, a technique for precisely predicting the radon concentrations indoors is not likely to be developed soon. As knowledge increases, successive approximations toward a final predictive model may be required. An early approximation of a predictive model for indoor radon is presented in this paper. It applies specifically to the crystalline rock region of the eastern United States, but it should have some application on a broader basis. The predictive model described focuses on understanding the wide-ranging permeability characteristics in the soil and rock fracture system. Radon is thought to accrete in confined subsurface air and moves under ground to low-pressure places, such as house niched in hill sloped. Driving forces for the air-laden and entrapped radon gas are considered to be a rising water table and infiltrating moisture from the land surface

  8. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  9. 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...... values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  10. 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.

  11. Predictive modelling of evidence informed teaching

    OpenAIRE

    Zhang, Dell; Brown, C.

    2017-01-01

    In this paper, we analyse the questionnaire survey data collected from 79 English primary schools about the situation of evidence informed teaching, where the evidences could come from research journals or conferences. Specifically, we build a predictive model to see what external factors could help to close the gap between teachers’ belief and behaviour in evidence informed teaching, which is the first of its kind to our knowledge. The major challenge, from the data mining perspective, is th...

  12. A Predictive Model for Cognitive Radio

    Science.gov (United States)

    2006-09-14

    response in a given situation. Vadde et al. interest and produce a model for prediction of the response. have applied response surface methodology and...34 2000. [3] K. K. Vadde and V. R. Syrotiuk, "Factor interaction on service configurations to those that best meet our communication delivery in mobile ad...resulting set of configurations randomly or apply additional 2004. screening criteria. [4] K. K. Vadde , M.-V. R. Syrotiuk, and D. C. Montgomery

  13. Tectonic predictions with mantle convection models

    Science.gov (United States)

    Coltice, Nicolas; Shephard, Grace E.

    2018-04-01

    Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough

  14. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert F.; Knox, James C.

    2016-01-01

    As part of NASA's Advanced Exploration Systems (AES) program and the Life Support Systems Project (LSSP), fully predictive models of the Four Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) on the International Space Station (ISS) 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.

  15. 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

  16. Predicting the ungauged basin: Model validation and realism assessment

    Directory of Open Access Journals (Sweden)

    Tim evan Emmerik

    2015-10-01

    Full Text Available The hydrological decade on Predictions in Ungauged Basins (PUB 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 paper 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. This paper does not present a generic approach that can be transferred to other ungauged catchments, but it aims to show how clever model design and alternative data acquisition can result in a valuable hydrological model for an ungauged catchment.

  17. Conceptual models of coronary perfusion pressure and their relationship to defibrillation success in a porcine model of prolonged out-of-hospital cardiac arrest

    Science.gov (United States)

    Reynolds, Joshua C.; Salcido, David D.; Menegazzi, James J.

    2012-01-01

    Introduction The amount of myocardial perfusion required for successful defibrillation after cardiac arrest is unknown. Coronary perfusion pressure (CPP) is a surrogate for myocardial perfusion. One limited clinical study identifies a threshold of 15 mmHg required for return of spontaneous circulation (ROSC). Our exploration of threshold and dose models of CPP during the initial bout of CPR indicates higher levels than previously demonstrated are required. CPP required for shock success throughout on-going resuscitation is unknown and other conceptual models of CPP have not been explored. Hypothesis An array of conceptual models of CPP is associated with and predicts defibrillation success throughout resuscitation. Methods Data from 6 porcine cardiac arrest studies were pooled. Mean and area under the curve (AUC) CPP were derived for 30-second epochs. Five conceptual models of CPP were analyzed: threshold, delta, cumulative delta, dose, and cumulative dose. Comparative statistics were performed with one-way ANOVA and two-tailed t-test. Regression models assessed CPP trends and prediction of ROSC. Results For 316 defibrillation attempts in 124 animals, those resulting in ROSC (n=75) had significantly higher threshold, delta, cumulative delta, dose, and cumulative dose CPP than those without. All conceptual models except delta CPP had significantly different values across successive defibrillation attempts and all five models were significant predictors of ROSC, along with experimental design. Conclusions Threshold, delta, cumulative delta, dose, and cumulative dose CPP predict individual defibrillation success throughout resuscitation. PMID:22266069

  18. 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

  19. 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.

  20. 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

  1. Predictive Modeling by the Cerebellum Improves Proprioception

    Science.gov (United States)

    Bhanpuri, Nasir H.; Okamura, Allison M.

    2013-01-01

    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. PMID:24005283

  2. Prediction of Chemical Function: Model Development and ...

    Science.gov (United States)

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

  3. 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...

  4. Evaluating predictive models of software quality

    International Nuclear Information System (INIS)

    Ciaschini, V; Canaparo, M; Ronchieri, E; Salomoni, D

    2014-01-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  5. 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

  6. PREDICTION MODELS OF GRAIN YIELD AND CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    Narciso Ysac Avila Serrano

    2009-06-01

    Full Text Available With the objective to characterize the grain yield of five cowpea cultivars and to find linear regression models to predict it, a study was developed in La Paz, Baja California Sur, Mexico. A complete randomized blocks design was used. Simple and multivariate analyses of variance were carried out using the canonical variables to characterize the cultivars. The variables cluster per plant, pods per plant, pods per cluster, seeds weight per plant, seeds hectoliter weight, 100-seed weight, seeds length, seeds wide, seeds thickness, pods length, pods wide, pods weight, seeds per pods, and seeds weight per pods, showed significant differences (P≤ 0.05 among cultivars. Paceño and IT90K-277-2 cultivars showed the higher seeds weight per plant. The linear regression models showed correlation coefficients ≥0.92. In these models, the seeds weight per plant, pods per cluster, pods per plant, cluster per plant and pods length showed significant correlations (P≤ 0.05. In conclusion, the results showed that grain yield differ among cultivars and for its estimation, the prediction models showed determination coefficients highly dependable.

  7. Predictive Models for Normal Fetal Cardiac Structures.

    Science.gov (United States)

    Krishnan, Anita; Pike, Jodi I; McCarter, Robert; Fulgium, Amanda L; Wilson, Emmanuel; Donofrio, Mary T; Sable, Craig A

    2016-12-01

    Clinicians rely on age- and size-specific measures of cardiac structures to diagnose cardiac disease. No universally accepted normative data exist for fetal cardiac structures, and most fetal cardiac centers do not use the same standards. The aim of this study was to derive predictive models for Z scores for 13 commonly evaluated fetal cardiac structures using a large heterogeneous population of fetuses without structural cardiac defects. The study used archived normal fetal echocardiograms in representative fetuses aged 12 to 39 weeks. Thirteen cardiac dimensions were remeasured by a blinded echocardiographer from digitally stored clips. Studies with inadequate imaging views were excluded. Regression models were developed to relate each dimension to estimated gestational age (EGA) by dates, biparietal diameter, femur length, and estimated fetal weight by the Hadlock formula. Dimension outcomes were transformed (e.g., using the logarithm or square root) as necessary to meet the normality assumption. Higher order terms, quadratic or cubic, were added as needed to improve model fit. Information criteria and adjusted R 2 values were used to guide final model selection. Each Z-score equation is based on measurements derived from 296 to 414 unique fetuses. EGA yielded the best predictive model for the majority of dimensions; adjusted R 2 values ranged from 0.72 to 0.893. However, each of the other highly correlated (r > 0.94) biometric parameters was an acceptable surrogate for EGA. In most cases, the best fitting model included squared and cubic terms to introduce curvilinearity. For each dimension, models based on EGA provided the best fit for determining normal measurements of fetal cardiac structures. Nevertheless, other biometric parameters, including femur length, biparietal diameter, and estimated fetal weight provided results that were nearly as good. Comprehensive Z-score results are available on the basis of highly predictive models derived from gestational

  8. Fuzzy subtractive clustering based prediction model for brand association analysis

    Directory of Open Access Journals (Sweden)

    Widodo Imam Djati

    2018-01-01

    Full Text Available The brand is one of the crucial elements that determine the success of a product. Consumers in determining the choice of a product will always consider product attributes (such as features, shape, and color, however consumers are also considering the brand. Brand will guide someone to associate a product with specific attributes and qualities. This study was designed to identify the product attributes and predict brand performance with those attributes. A survey was run to obtain the attributes affecting the brand. Subtractive Fuzzy Clustering was used to classify and predict product brand association based aspects of the product under investigation. The result indicates that the five attributes namely shape, ease, image, quality and price can be used to classify and predict the brand. Training step gives best FSC model with radii (ra = 0.1. It develops 70 clusters/rules with MSE (Training is 9.7093e-016. By using 14 data testing, the model can predict brand very well (close to the target with MSE is 0.6005 and its’ accuracy rate is 71%.

  9. Does inhibitory control capacity in overweight and obese children and adolescents predict success in a weight-reduction program?

    OpenAIRE

    Pauli-Pott , Ursula; Albayrak , Özgür; Hebebrand , Johannes; Pott , Wilfried

    2009-01-01

    Abstract It has been assumed that inhibitory control capacity might influence the success of overweight or obese subjects in reducing weight. However, empirical research on this association is scarce. The present study, therefore, examines whether success in an outpatient weight-reduction program for children and adolescents can be predicted by pre-intervention inhibitory control capacity. The study sample consisted of 111 overweight and obese children and adolescents (7.5?15 years...

  10. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  11. An Anisotropic Hardening Model for Springback Prediction

    International Nuclear Information System (INIS)

    Zeng, Danielle; Xia, Z. Cedric

    2005-01-01

    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

  12. Predictive model for ice formation on superhydrophobic surfaces.

    Science.gov (United States)

    Bahadur, Vaibhav; Mishchenko, Lidiya; Hatton, Benjamin; Taylor, J Ashley; Aizenberg, Joanna; Krupenkin, Tom

    2011-12-06

    The prevention and control of ice accumulation has important applications in aviation, building construction, and energy conversion devices. One area of active research concerns the use of superhydrophobic surfaces for preventing ice formation. The present work develops a physics-based modeling framework to predict ice formation on cooled superhydrophobic surfaces resulting from the impact of supercooled water droplets. This modeling approach analyzes the multiple phenomena influencing ice formation on superhydrophobic surfaces through the development of submodels describing droplet impact dynamics, heat transfer, and heterogeneous ice nucleation. These models are then integrated together to achieve a comprehensive understanding of ice formation upon impact of liquid droplets at freezing conditions. The accuracy of this model is validated by its successful prediction of the experimental findings that demonstrate that superhydrophobic surfaces can fully prevent the freezing of impacting water droplets down to surface temperatures of as low as -20 to -25 °C. The model can be used to study the influence of surface morphology, surface chemistry, and fluid and thermal properties on dynamic ice formation and identify parameters critical to achieving icephobic surfaces. The framework of the present work is the first detailed modeling tool developed for the design and analysis of surfaces for various ice prevention/reduction strategies. © 2011 American Chemical Society

  13. Prediction of strong earthquake motions on rock surface using evolutionary process models

    International Nuclear Information System (INIS)

    Kameda, H.; Sugito, M.

    1984-01-01

    Stochastic process models are developed for prediction of strong earthquake motions for engineering design purposes. Earthquake motions with nonstationary frequency content are modeled by using the concept of evolutionary processes. Discussion is focused on the earthquake motions on bed rocks which are important for construction of nuclear power plants in seismic regions. On this basis, two earthquake motion prediction models are developed, one (EMP-IB Model) for prediction with given magnitude and epicentral distance, and the other (EMP-IIB Model) to account for the successive fault ruptures and the site location relative to the fault of great earthquakes. (Author) [pt

  14. 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.

  15. Predictions of the most minimal see-saw model

    CERN Document Server

    Raidal, Martti

    2003-01-01

    We derive the most minimal see-saw texture from an extra-dimensional dynamics. If LMA is the solution to the solar neutrino problem, it predicts $\\theta_{13} = 0.07\\pm0.02$ and $m_{ee} = 2.5\\pm0.7 \\meV.$ Assuming thermal leptogenesis, the sign of the CP-phase measurable in neutrino oscillations, together with the sign of baryon asymmetry, determines the order of heavy neutrino masses. Unless heavy neutrinos are almost degenerate, successful leptogenesis fixes the lightest mass. Depending on the sign of the neutrino CP-phase, the supersymmetric version of the model with universal soft terms at high scale predicts BR($\\mu\\to e \\gamma$) or BR($\\tau\\to \\mu \\gamma$), and gives a lower bound on the other process.

  16. PREDICTABILITY OF FINANCIAL CRISES: TESTING K.R.L. MODEL IN THE CASE OF TURKEY

    Directory of Open Access Journals (Sweden)

    Zeynep KARACOR

    2012-06-01

    Full Text Available The aim of this study is to test predictability of 2007 Global Economic Crisis which hit Turkey by the help of macroeconomic data of Turkey. K.R.L. model is used to test the predictability. By the method of analyzing various leading early warning indicators, the success of the model in forecasting the crises is surveyed. The findings do not support K.R.L. models. Possible reasons for this are stated at the article.

  17. [Endometrial cancer: Predictive models and clinical impact].

    Science.gov (United States)

    Bendifallah, Sofiane; Ballester, Marcos; Daraï, Emile

    2017-12-01

    In France, in 2015, endometrial cancer (CE) is the first gynecological cancer in terms of incidence and the fourth cause of cancer of the woman. About 8151 new cases and nearly 2179 deaths have been reported. Treatments (surgery, external radiotherapy, brachytherapy and chemotherapy) are currently delivered on the basis of an estimation of the recurrence risk, an estimation of lymph node metastasis or an estimate of survival probability. This risk is determined on the basis of prognostic factors (clinical, histological, imaging, biological) taken alone or grouped together in the form of classification systems, which are currently insufficient to account for the evolutionary and prognostic heterogeneity of endometrial cancer. For endometrial cancer, the concept of mathematical modeling and its application to prediction have developed in recent years. These biomathematical tools have opened a new era of care oriented towards the promotion of targeted therapies and personalized treatments. Many predictive models have been published to estimate the risk of recurrence and lymph node metastasis, but a tiny fraction of them is sufficiently relevant and of clinical utility. The optimization tracks are multiple and varied, suggesting the possibility in the near future of a place for these mathematical models. The development of high-throughput genomics is likely to offer a more detailed molecular characterization of the disease and its heterogeneity. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  18. Application of two forest succession models at sites in Northeast Germany

    International Nuclear Information System (INIS)

    Lasch, P.; Lindner, M.

    1995-06-01

    In order to simulate potential impacts of climate change on forests, two succession models were applied to sites in the Northeast German lowlands. The models, which had been developed for Alpine (FORECE) and Boreal (FORSKA) forests differ from each other in the way they represent tree growth processes and the impact of environmental factors on establishment and growth. Both models were adjusted and compared with each other at sites that are situated along an ecological gradient from maritime to subcontinental climate. These sites are extending the former environmental space of model application towards water limited conditions, which under a predicted climatic change may have increasing importance for European forests. First results showed that FORECE was unrealistically sensitive to changes in soil moisture. On the other hand, FORSKA generally simulated very low biomasses. Since the structure of FORSKA seemed to be better suited for the simulation of changing environmental conditions, this model was chosen for further model development, applications and sensitivity analyses. Among other changes, establishment rates were increased and some environmental response factors were analysed. The function of account for resource depletion was modified. After the modifications for Central European conditions were made, there was a decrease in performance for the Boreal site. Both simulated total biomasses and species composition had changed. We conclude, that with currently available models, realistic forest dynamics within different climatic zones of Europe cannot be simulated without more substantial model modifications. (orig.)

  19. 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.

  20. Predictions of models for environmental radiological assessment

    International Nuclear Information System (INIS)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa; Mahler, Claudio Fernando

    2011-01-01

    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 137 Cs and 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)

  1. 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

  2. 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.

  3. Sustaining a successful RN compensation model through transparency and communication.

    Science.gov (United States)

    Reid, Karmen R; Attlesey-Pries, Jacqueline M; Syverson, Renae C; Uthke, Lorraine D; Wottreng, Diane M; Muehlenbein, Michael J

    2011-02-01

    In the March 2005 issue of The Journal of Nursing Administration, authors from an academic medical center outlined a new RN salary program that addressed recruitment and retention of valued resources and established an approach for pay and pay practices for staff RNs across an integrated practice. This follow-up article describes experiences in implementing the program and the successful outcomes achieved.

  4. Two-Year Apprenticeships--A Successful Model of Training?

    Science.gov (United States)

    Kammermann, Marlise; Stalder, Barbara E.; Hattich, Achim

    2011-01-01

    Educational policy is asked to support young people in their successful transition from education to employment. In Switzerland, a two-year apprenticeship with Federal VET Certificate was established in 2002 aimed at increasing the employability of low-achieving school leavers. It is a low-threshold VET programme offering standardised vocational…

  5. Combining GPS measurements and IRI model predictions

    International Nuclear Information System (INIS)

    Hernandez-Pajares, M.; Juan, J.M.; Sanz, J.; Bilitza, D.

    2002-01-01

    The free electrons distributed in the ionosphere (between one hundred and thousands of km in height) produce a frequency-dependent effect on Global Positioning System (GPS) signals: a delay in the pseudo-orange and an advance in the carrier phase. These effects are proportional to the columnar electron density between the satellite and receiver, i.e. the integrated electron density along the ray path. Global ionospheric TEC (total electron content) maps can be obtained with GPS data from a network of ground IGS (international GPS service) reference stations with an accuracy of few TEC units. The comparison with the TOPEX TEC, mainly measured over the oceans far from the IGS stations, shows a mean bias and standard deviation of about 2 and 5 TECUs respectively. The discrepancies between the STEC predictions and the observed values show an RMS typically below 5 TECUs (which also includes the alignment code noise). he existence of a growing database 2-hourly global TEC maps and with resolution of 5x2.5 degrees in longitude and latitude can be used to improve the IRI prediction capability of the TEC. When the IRI predictions and the GPS estimations are compared for a three month period around the Solar Maximum, they are in good agreement for middle latitudes. An over-determination of IRI TEC has been found at the extreme latitudes, the IRI predictions being, typically two times higher than the GPS estimations. Finally, local fits of the IRI model can be done by tuning the SSN from STEC GPS observations

  6. Mathematical models for indoor radon prediction

    International Nuclear Information System (INIS)

    Malanca, A.; Pessina, V.; Dallara, G.

    1995-01-01

    It is known that the indoor radon (Rn) concentration can be predicted by means of mathematical models. The simplest model relies on two variables only: the Rn source strength and the air exchange rate. In the Lawrence Berkeley Laboratory (LBL) model several environmental parameters are combined into a complex equation; besides, a correlation between the ventilation rate and the Rn entry rate from the soil is admitted. The measurements were carried out using activated carbon canisters. Seventy-five measurements of Rn concentrations were made inside two rooms placed on the second floor of a building block. One of the rooms had a single-glazed window whereas the other room had a double pane window. During three different experimental protocols, the mean Rn concentration was always higher into the room with a double-glazed window. That behavior can be accounted for by the simplest model. A further set of 450 Rn measurements was collected inside a ground-floor room with a grounding well in it. This trend maybe accounted for by the LBL model

  7. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    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......). Five technical and economic aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality...... 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...

  8. An Operational Model for the Prediction of Jet Blast

    Science.gov (United States)

    2012-01-09

    This paper presents an operational model for the prediction of jet blast. The model was : developed based upon three modules including a jet exhaust model, jet centerline decay : model and aircraft motion model. The final analysis was compared with d...

  9. 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…

  10. 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…

  11. 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…

  12. 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…

  13. 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

  14. 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

    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...... 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...

  15. Validation and Generalizability of Preoperative PROMIS Scores to Predict Postoperative Success in Foot and Ankle Patients.

    Science.gov (United States)

    Anderson, Michael R; Houck, Jeff R; Saltzman, Charles L; Hung, Man; Nickisch, Florian; Barg, Alexej; Beals, Timothy; Baumhauer, Judith F

    2018-04-01

    A recent publication reported preoperative Patient-Reported Outcomes Measurement Instrumentation System (PROMIS) scores to be highly predictive in identifying patients who would and would not benefit from foot and ankle surgery. Their applicability to other patient populations is unknown. The aim of this study was to assess the validation and generalizability of previously published preoperative PROMIS physical function (PF) and pain interference (PI) threshold t scores as predictors of postoperative clinically meaningful improvement in foot and ankle patients from a geographically unique patient population. Prospective PROMIS PF and PI scores of consecutive patient visits to a tertiary foot and ankle clinic were obtained between January 2014 and November 2016. Patients undergoing elective foot and ankle surgery were identified and PROMIS values obtained at initial and follow-up visits (average, 7.9 months). Analysis of variance was used to assess differences in PROMIS scores before and after surgery. The distributive method was used to estimate a minimal clinically important difference (MCID). Receiver operating characteristic curve analysis was used to determine thresholds for achieving and failing to achieve MCID. To assess the validity and generalizability of these threshold values, they were compared with previously published threshold values for accuracy using likelihood ratios and pre- and posttest probabilities, and the percentages of patients identified as achieving and failing to achieve MCID were evaluated using χ 2 analysis. There were significant improvements in PF ( P < .001) and PI ( P < .001) after surgery. The area under the curve for PF (0.77) was significant ( P < .01), and the thresholds for achieving MCID and not achieving MCID were similar to those in the prior study. A significant proportion of patients (88.9%) identified as not likely to achieve MCID failed to achieve MCID ( P = .03). A significant proportion of patients (84.2%) identified

  16. Reproductive success is predicted by social dynamics and kinship in managed animal populations [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Saul J. Newman

    2016-05-01

    Full Text Available 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.

  17. 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)

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

    African Journals Online (AJOL)

    No significant association was found between transvaginal measurement of cervical length and the success of labour induction (p=0.201). We found no statistically significant difference between failure of labour induction and successful labour induction in terms of transvaginal measurement of cervical length (area under ...

  19. Mathematical modeling and computational prediction of cancer drug resistance.

    Science.gov (United States)

    Sun, Xiaoqiang; Hu, Bin

    2017-06-23

    Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of

  20. Anticipatory brain activity predicts the success or failure of subsequent emotion regulation.

    Science.gov (United States)

    Denny, Bryan T; Ochsner, Kevin N; Weber, Jochen; Wager, Tor D

    2014-04-01

    Expectations about an upcoming emotional event have the power to shape one's subsequent affective response for better or worse. Here, we used mediation analyses to examine the relationship between brain activity when anticipating the need to cognitively reappraise aversive images, amygdala responses to those images and subsequent success in diminishing negative affect. We found that anticipatory activity in right rostrolateral prefrontal cortex was associated with greater subsequent left amygdala responses to aversive images and decreased regulation success. In contrast, anticipatory ventral anterior insula activity was associated with reduced amygdala responses and greater reappraisal success. In both cases, left amygdala responses mediated the relationship between anticipatory activity and reappraisal success. These results suggest that anticipation facilitates successful reappraisal via reduced anticipatory prefrontal 'cognitive' elaboration and better integration of affective information in paralimbic and subcortical systems.

  1. 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.

  2. 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. PMID:20885919

  3. 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.

  4. 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.

    2018-02-01

    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.

  5. 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

  6. Predictive modeling: potential application in prevention services.

    Science.gov (United States)

    Wilson, Moira L; Tumen, Sarah; Ota, Rissa; Simmers, Anthony G

    2015-05-01

    In 2012, the New Zealand Government announced a proposal to introduce predictive risk models (PRMs) to help professionals identify and assess children at risk of abuse or neglect as part of a preventive early intervention strategy, subject to further feasibility study and trialing. The purpose of this study is to examine technical feasibility and predictive validity of the proposal, focusing on a PRM that would draw on population-wide linked administrative data to identify newborn children who are at high priority for intensive preventive services. Data analysis was conducted in 2013 based on data collected in 2000-2012. A PRM was developed using data for children born in 2010 and externally validated for children born in 2007, examining outcomes to age 5 years. Performance of the PRM in predicting administratively recorded substantiations of maltreatment was good compared to the performance of other tools reviewed in the literature, both overall, and for indigenous Māori children. Some, but not all, of the children who go on to have recorded substantiations of maltreatment could be identified early using PRMs. PRMs should be considered as a potential complement to, rather than a replacement for, professional judgment. Trials are needed to establish whether risks can be mitigated and PRMs can make a positive contribution to frontline practice, engagement in preventive services, and outcomes for children. Deciding whether to proceed to trial requires balancing a range of considerations, including ethical and privacy risks and the risk of compounding surveillance bias. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

  7. Scaling Student Success with Predictive Analytics: Reflections after Four Years in the Data Trenches

    Science.gov (United States)

    Wagner, Ellen; Longanecker, David

    2016-01-01

    The metrics used in the US to track students do not include adults and part-time students. This has led to the development of a massive data initiative--the Predictive Analytics Reporting (PAR) framework--that uses predictive analytics to trace the progress of all types of students in the system. This development has allowed actionable,…

  8. Heuristic Modeling for TRMM Lifetime Predictions

    Science.gov (United States)

    Jordan, P. S.; Sharer, P. J.; DeFazio, R. L.

    1996-01-01

    Analysis time for computing the expected mission lifetimes of proposed frequently maneuvering, tightly altitude constrained, Earth orbiting spacecraft have been significantly reduced by means of a heuristic modeling method implemented in a commercial-off-the-shelf spreadsheet product (QuattroPro) running on a personal computer (PC). The method uses a look-up table to estimate the maneuver frequency per month as a function of the spacecraft ballistic coefficient and the solar flux index, then computes the associated fuel use by a simple engine model. Maneuver frequency data points are produced by means of a single 1-month run of traditional mission analysis software for each of the 12 to 25 data points required for the table. As the data point computations are required only a mission design start-up and on the occasion of significant mission redesigns, the dependence on time consuming traditional modeling methods is dramatically reduced. Results to date have agreed with traditional methods to within 1 to 1.5 percent. The spreadsheet approach is applicable to a wide variety of Earth orbiting spacecraft with tight altitude constraints. It will be particularly useful to such missions as the Tropical Rainfall Measurement Mission scheduled for launch in 1997, whose mission lifetime calculations are heavily dependent on frequently revised solar flux predictions.

  9. A Computational Model for Predicting Gas Breakdown

    Science.gov (United States)

    Gill, Zachary

    2017-10-01

    Pulsed-inductive discharges are a common method of producing a plasma. They provide a mechanism for quickly and efficiently generating a large volume of plasma for rapid use and are seen in applications including propulsion, fusion power, and high-power lasers. However, some common designs see a delayed response time due to the plasma forming when the magnitude of the magnetic field in the thruster is at a minimum. New designs are difficult to evaluate due to the amount of time needed to construct a new geometry and the high monetary cost of changing the power generation circuit. To more quickly evaluate new designs and better understand the shortcomings of existing designs, a computational model is developed. This model uses a modified single-electron model as the basis for a Mathematica code to determine how the energy distribution in a system changes with regards to time and location. By analyzing this energy distribution, the approximate time and location of initial plasma breakdown can be predicted. The results from this code are then compared to existing data to show its validity and shortcomings. Missouri S&T APLab.

  10. 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.

  11. 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 ...

  12. 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…

  13. Predicting landscape vegetation dynamics using state-and-transition simulation models

    Science.gov (United States)

    Colin J. Daniel; Leonardo. Frid

    2012-01-01

    This paper outlines how state-and-transition simulation models (STSMs) can be used to project changes in vegetation over time across a landscape. STSMs are stochastic, empirical simulation models that use an adapted Markov chain approach to predict how vegetation will transition between states over time, typically in response to interactions between succession,...

  14. Which method predicts recidivism best?: A comparison of statistical, machine learning, and data mining predictive models

    OpenAIRE

    Tollenaar, N.; van der Heijden, P.G.M.

    2012-01-01

    Using criminal population conviction histories of recent offenders, prediction mod els are developed that predict three types of criminal recidivism: general recidivism, violent recidivism and sexual recidivism. The research question is whether prediction techniques from modern statistics, data mining and machine learning provide an improvement in predictive performance over classical statistical methods, namely logistic regression and linear discrim inant analysis. These models are compared ...

  15. 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...

  16. 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…

  17. Sialylated Fetuin-A as a candidate predictive biomarker for successful grass pollen allergen immunotherapy.

    Science.gov (United States)

    Caillot, Noémie; Bouley, Julien; Jain, Karine; Mariano, Sandrine; Luce, Sonia; Horiot, Stéphane; Airouche, Sabi; Beuraud, Chloé; Beauvallet, Christian; Devillier, Philippe; Chollet-Martin, Sylvie; Kellenberger, Christine; Mascarell, Laurent; Chabre, Henri; Batard, Thierry; Nony, Emmanuel; Lombardi, Vincent; Baron-Bodo, Véronique; Moingeon, Philippe

    2017-09-01

    Eligibility to immunotherapy is based on the determination of IgE reactivity to a specific allergen by means of skin prick or in vitro testing. Biomarkers predicting the likelihood of clinical improvement during immunotherapy would significantly improve patient selection. Proteins were differentially assessed by using 2-dimensional differential gel electrophoresis and label-free mass spectrometry in pretreatment sera obtained from clinical responders and nonresponders within a cohort of 82 patients with grass pollen allergy receiving sublingual immunotherapy or placebo. Functional studies of Fetuin-A (FetA) were conducted by using gene silencing in a mouse asthma model, human dendritic cell in vitro stimulation assays, and surface plasmon resonance. Analysis by using quantitative proteomics of pretreatment sera from patients with grass pollen allergy reveals that high levels of O-glycosylated sialylated FetA isoforms are found in patients exhibiting a strong decrease in rhinoconjunctivitis symptoms after sublingual immunotherapy. Although FetA is involved in numerous inflammatory conditions, its potential role in allergy is unknown. In vivo silencing of the FETUA gene in BALB/c mice results in a dramatic upregulation of airway hyperresponsiveness, lung resistance, and T H 2 responses after allergic sensitization to ovalbumin. Both sialylated and nonsialytated FetA bind to LPS, but only the former synergizes with LPS and grass pollen or mite allergens to enhance the Toll-like receptor 4-mediated proallergic properties of human dendritic cells. As a reflection of the patient's inflammatory status, pretreatment levels of sialylated FetA in the blood are indicative of the likelihood of clinical responses during grass pollen immunotherapy. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  18. Cut-Off Value for Pain Sensitivity Questionnaire in Predicting Surgical Success in Patients with Lumbar Disc Herniation.

    Directory of Open Access Journals (Sweden)

    Parisa Azimi

    Full Text Available Various factors related to predict surgical success were studied; however, a standard cut-off point for the Pain Sensitivity Questionnaire (PSQ measure has not yet been established for a favorable surgical outcome for lumbar disc herniation (LDH. This study was to find the optimal cut-off point on the PSQ to distinguish surgical success in patients with LDH. A total of 154 patients with LDH consecutively referred to our clinic were enrolled into this prospective study between February 2011 and January 2014. All participants completed the PSQ. Patients completed the Oswestry Disability Index (ODI score before surgery, and at 2 years after surgery. Surgical success was defined as a 13-point improvement from the baseline ODI scores. The cut-off value for PSQ was determined by the receiver-operating characteristic curve (ROC. The mean age of patients was 49.3±9.6 years, and there were 80 women. The mean time for follow-up assessment was 31±5 months (range 24-35. Post-surgical success was 79.9% (n = 123 at 2 years follow up. The mean score for the total PSQ, PSQ-minor, and PSQ-moderate were 6.0 (SD = 1.6, 5.4 (SD = 1.9 and 6.5 (SD = 1.7, respectively. Total PSQ score was also significantly correlated with the total scores of the ODI. The optimal total PSQ cut-off point was determined as > 5.2 to predict surgical success in LDH patients, with 80.0% sensitivity and 75.6% specificity (AUC-0.814, 95% CI 0.703-0.926. This study showed that the PSQ could be considered a parameter for predicting surgical success in patients with LDH, and can be useful in clinical practice.

  19. 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.

  20. 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.

  1. Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization...

  2. Business Model Innovation in Incumbent Organizations: : Challenges and Success Routes

    OpenAIRE

    Salama, Ahmad; Parvez, Khawar

    2015-01-01

    In this thesis major challenges of creating business models at incumbents within mature industries are identified along with a mitigation plan. Pressure is upon incumbent organizations in order to keep up with the latest rapid technological advancements, the launching of startups that almost cover every field of business and the continuous change in customers’ tastes and needs. That along with various factors either forced organizations to continually reevaluate their current business models ...

  3. 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…

  4. Indexed left atrial volume predicts the recurrence of non-valvular atrial fibrillation after successful cardioversion.

    Science.gov (United States)

    Marchese, Procolo; Bursi, Francesca; Delle Donne, Grazia; Malavasi, Vincenzo; Casali, Edoardo; Barbieri, Andrea; Melandri, Francesco; Modena, Maria Grazia

    2011-03-01

    Atrial fibrillation (AFib) induces remodelling of the left atrium (LA). Indexed LA volume (iLAV) as more accurate measure of LA size has not been evaluated as predictor of recurrence of AFib after cardioversion. We identified 411 adults (mean age 64.1 ± 11.4 years, 34.5% women) who underwent successful cardioversion and with no history of other atrial arrhythmia, stroke, congenital heart disease, valvular dysfunction, surgery, thyroid dysfunction, acute or chronic inflammatory disease, and pacemaker. All echocardiographic data were retrieved from the laboratory database. iLAV was measured off-line using Simpson's method. Clinical characteristics and recurrence of clinical AFib were determined by review of medical records. Patients with scheduled follow-up of at least 6 months were included. About 250 patients (60.8%) developed AFib recurrence after a median (25th-75th percentile) follow-up of 345.0 (210.0-540.0) days. Patients with AFib recurrence had significantly greater iLAV than patients without AFib recurrence (39.7 ± 8.4 vs. 31.4 ± 4.6, P < 0.001). Each mL/m(2) increase in iLAV was associated with a 30% increased risk of AFib recurrence [odds ratio (OR) 1.30, confidence interval (CI) 1.23-1.38, P < 0.001]. In a multivariable model, each mL/m(2) increase in iLAV was independently associated with a 21% increase in the risk of AFib recurrence (OR 1.21, CI 1.11-1.30, P < 0.001). The areas under receiver operating characteristic curves, generated to compare LA diameter and iLAV as predictors of AFib recurrence, were 0.59 ± 0.3 and 0.85 ± 0.2, respectively (P < 0.001). The present study is the first to show that larger iLAV before cardioversion, as a more accurate measure of LA remodelling than LA diameter, is strongly and independently associated with higher risks of AFib recurrence.

  5. Effective amygdala-prefrontal connectivity predicts individual differences in successful emotion regulation.

    Science.gov (United States)

    Morawetz, Carmen; Bode, Stefan; Baudewig, Juergen; Heekeren, Hauke R

    2017-04-01

    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 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. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

    OpenAIRE

    Mestyán, Márton; Yasseri, Taha; Kertész, János

    2012-01-01

    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...

  7. Developing a theoretical model and questionnaire survey instrument to measure the success of electronic health records in residential aged care

    Science.gov (United States)

    Yu, Ping; Qian, Siyu

    2018-01-01

    Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables—training, self-efficacy, system quality and information quality—on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time. PMID:29315323

  8. Developing a theoretical model and questionnaire survey instrument to measure the success of electronic health records in residential aged care.

    Science.gov (United States)

    Yu, Ping; Qian, Siyu

    2018-01-01

    Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables-training, self-efficacy, system quality and information quality-on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time.

  9. A predictive coding account of bistable perception - a model-based fMRI study.

    Science.gov (United States)

    Weilnhammer, Veith; Stuke, Heiner; Hesselmann, Guido; Sterzer, Philipp; Schmack, Katharina

    2017-05-01

    In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model's predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants' perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together, our current work

  10. A predictive coding account of bistable perception - a model-based fMRI study.

    Directory of Open Access Journals (Sweden)

    Veith Weilnhammer

    2017-05-01

    Full Text Available In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model's predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants' perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together

  11. 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.

  12. Analysis of syntax and word use to predict successful participation in guided self-help for anxiety and depression

    DEFF Research Database (Denmark)

    Zinken, Jörg; Zinken, Katarzyna; Wilson, J. Clare

    2010-01-01

    with a primary care mental health service were analysed. Outcome measures were completion of the guided self-help programme, and change in symptoms assessed by a standardised scale (CORE-OM). Regression analyses indicated that some aspects of participants' syntax helped to predict completion of the programme...... of causation words and complex syntax (adverbial clauses) predicted improvement, accounting for 50% of the variation in well-being benefit. These results suggest that the analysis of narrative style can provide useful information for assessing the likelihood of success of individuals participating in a mental...... health guided self-help programme....

  13. 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

  14. A fusion model used in subsidence prediction in Taiwan

    Directory of Open Access Journals (Sweden)

    S.-J. Wang

    2015-11-01

    Full Text Available The Taiwan Water Resources Agency uses four techniques to monitor subsidence in Taiwan, namely data from leveling, global positioning system (GPS, multi-level compaction monitoring wells (MCMWs, and interferometry synthetic aperture radar (InSAR. Each data type has advantages and disadvantages and is suitable for different analysis tools. Only MCMW data provide compaction information at different depths in an aquifer system, thus they are adopted in this study. However, the cost of MCMW is high and the number of MCMW is relatively low. Leveling data are thus also adopted due to its high resolution and accuracy. MCMW data provide compaction information at different depths and the experimental data from the wells provide the physical properties. These data are suitable for a physical model. Leveling data have high monitoring density in spatial domain but lack in temporal domain due to the heavy field work. These data are suitable for a black- or grey-box model. Poroelastic theory, which is known to be more conscientious than Terzaghi's consolidation theory, is adopted in this study with the use of MCMW data. Grey theory, which is a widely used grey-box model, is adopted in this study with the use of leveling data. A fusion technique is developed to combine the subsidence predicted results from poroelastic and grey models to obtain a spatially and temporally connected two-dimensional subsidence distribution. The fusion model is successfully applied to subsidence predictions in Changhua, Yunlin, Tainan, and Kaohsiung of Taiwan and obtains good results. A good subsidence model can help the government to make the accurate strategies for land and groundwater resource management.

  15. Supporting Sophomore Success through a New Learning Community Model

    Science.gov (United States)

    Virtue, Emily E.; Wells, Gayle; Virtue, Andrew D.

    2013-01-01

    The creation of a Sophomore Learning Community (SLC) model can help address concerns about the "sophomore slump" and sophomore attrition. While managing the logistics of a sophomore LC can be difficult, with proper faculty, staff, and administrative support, positive results can be produced. This article outlines the need for Sophomore…

  16. Carsharing Business Models in Germany: Characteristics, Success and Future Prospects

    NARCIS (Netherlands)

    Munzel, K.L.; Boon, W.P.C.; Frenken, K.; Vaskelainen, T.

    2017-01-01

    Carsharing provides an alternative to private car ownership by allowing car use temporarily on an ondemand basis. Operators provide carsharing services using different business models and ownership structures. We distinguish between cooperative, business-to-consumer (B2C) roundtrip and one-way, as

  17. Can magnetic resonance imaging predict the success of parturition in oxytocin-induced pregnant women?

    International Nuclear Information System (INIS)

    Sabir, N.; Akkemik, B.; Dicle, O.; Yurdakul, B.

    2000-01-01

    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.)

  18. 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…

  19. Do planning and preparation relate predict success in SME-transfers?

    NARCIS (Netherlands)

    Lex van Teeffelen

    2007-01-01

    This study (re)tests the relationship between planning and transfer success. Previous studies show that planning increases satisfaction, but find no or only weak relations to transfer effectiveness. 76 Dutch SME business owners, who succeeded in the transfer, were surveyed. To improve on previous

  20. 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…

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

    African Journals Online (AJOL)

    Eighty-four patients induced with prostaglandin E2 (dinoprostone) for medical indications were included in the study. Results. No significant association was found between transvaginal measurement of cervical length and the success of labour induction. (p=0.201). We found no statistically significant difference between ...

  2. 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…

  3. 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…

  4. 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.

  5. Model Predictive Control for an Industrial SAG Mill

    DEFF Research Database (Denmark)

    Ohan, Valeriu; Steinke, Florian; Metzger, Michael

    2012-01-01

    We discuss Model Predictive Control (MPC) based on ARX models and a simple lower order disturbance model. The advantage of this MPC formulation is that it has few tuning parameters and is based on an ARX prediction model that can readily be identied using standard technologies from system identic...

  6. Uncertainties in spatially aggregated predictions from a logistic regression model

    NARCIS (Netherlands)

    Horssen, P.W. van; Pebesma, E.J.; Schot, P.P.

    2002-01-01

    This paper presents a method to assess the uncertainty of an ecological spatial prediction model which is based on logistic regression models, using data from the interpolation of explanatory predictor variables. The spatial predictions are presented as approximate 95% prediction intervals. The

  7. Dealing with missing predictor values when applying clinical prediction models.

    NARCIS (Netherlands)

    Janssen, K.J.; Vergouwe, Y.; Donders, A.R.T.; Harrell Jr, F.E.; Chen, Q.; Grobbee, D.E.; Moons, K.G.

    2009-01-01

    BACKGROUND: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with

  8. 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.

  9. A Model of Social Selection and Successful Altruism

    Science.gov (United States)

    1989-10-07

    D., The evolution of social behavior. Annual Reviews of Ecological Systems, 5:325-383 (1974). 2. Dawkins , R., The selfish gene . Oxford: Oxford...alive and well. it will be important to re- examine this striking historical experience,-not in terms o, oversimplified models of the " selfish gene ," but...Darwinian Analysis The acceptance by many modern geneticists of the axiom that the basic unit of selection Is the " selfish gene " quickly led to the

  10. Observational constraints on successful model of quintessential Inflation

    Energy Technology Data Exchange (ETDEWEB)

    Geng, Chao-Qiang [Chongqing University of Posts and Telecommunications, Chongqing, 400065 (China); Lee, Chung-Chi [DAMTP, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Sami, M. [Centre for Theoretical Physics, Jamia Millia Islamia, New Delhi 110025 (India); Saridakis, Emmanuel N. [Physics Division, National Technical University of Athens, 15780 Zografou Campus, Athens (Greece); Starobinsky, Alexei A., E-mail: geng@phys.nthu.edu.tw, E-mail: lee.chungchi16@gmail.com, E-mail: sami@iucaa.ernet.in, E-mail: Emmanuel_Saridakis@baylor.edu, E-mail: alstar@landau.ac.ru [L. D. Landau Institute for Theoretical Physics RAS, Moscow 119334 (Russian Federation)

    2017-06-01

    We study quintessential inflation using a generalized exponential potential V (φ)∝ exp(−λ φ {sup n} / M {sub Pl} {sup n} ), n >1, the model admits slow-roll inflation at early times and leads to close-to-scaling behaviour in the post inflationary era with an exit to dark energy at late times. We present detailed investigations of the inflationary stage in the light of the Planck 2015 results, study post-inflationary dynamics and analytically confirm the existence of an approximately scaling solution. Additionally, assuming that standard massive neutrinos are non-minimally coupled, makes the field φ dominant once again at late times giving rise to present accelerated expansion of the Universe. We derive observational constraints on the field and time-dependent neutrino masses. In particular, for n =6 (8), the parameter λ is constrained to be, log λ > −7.29 (−11.7); the model produces the spectral index of the power spectrum of primordial scalar (matter density) perturbations as n {sub s} = 0.959 ± 0.001 (0.961 ± 0.001) and tiny tensor-to-scalar ratio, r <1.72 × 10{sup −2} (2.32 × 10{sup −2}) respectively. Consequently, the upper bound on possible values of the sum of neutrino masses Σ m {sub ν} ∼< 2.5 eV significantly enhances compared to that in the standard ΛCDM model.

  11. 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.

  12. 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.

  13. Predictive capabilities of various constitutive models for arterial tissue.

    Science.gov (United States)

    Schroeder, Florian; Polzer, Stanislav; Slažanský, Martin; Man, Vojtěch; Skácel, Pavel

    2018-02-01

    Aim of this study is to validate some constitutive models by assessing their capabilities in describing and predicting uniaxial and biaxial behavior of porcine aortic tissue. 14 samples from porcine aortas were used to perform 2 uniaxial and 5 biaxial tensile tests. Transversal strains were furthermore stored for uniaxial data. The experimental data were fitted by four constitutive models: Holzapfel-Gasser-Ogden model (HGO), model based on generalized structure tensor (GST), Four-Fiber-Family model (FFF) and Microfiber model. Fitting was performed to uniaxial and biaxial data sets separately and descriptive capabilities of the models were compared. Their predictive capabilities were assessed in two ways. Firstly each model was fitted to biaxial data and its accuracy (in term of R 2 and NRMSE) in prediction of both uniaxial responses was evaluated. Then this procedure was performed conversely: each model was fitted to both uniaxial tests and its accuracy in prediction of 5 biaxial responses was observed. Descriptive capabilities of all models were excellent. In predicting uniaxial response from biaxial data, microfiber model was the most accurate while the other models showed also reasonable accuracy. Microfiber and FFF models were capable to reasonably predict biaxial responses from uniaxial data while HGO and GST models failed completely in this task. HGO and GST models are not capable to predict biaxial arterial wall behavior while FFF model is the most robust of the investigated constitutive models. Knowledge of transversal strains in uniaxial tests improves robustness of constitutive models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Comparing National Water Model Inundation Predictions with Hydrodynamic Modeling

    Science.gov (United States)

    Egbert, R. J.; Shastry, A.; Aristizabal, F.; Luo, C.

    2017-12-01

    The National Water Model (NWM) simulates the hydrologic cycle and produces streamflow forecasts, runoff, and other variables for 2.7 million reaches along the National Hydrography Dataset for the continental United States. NWM applies Muskingum-Cunge channel routing which is based on the continuity equation. However, the momentum equation also needs to be considered to obtain better estimates of streamflow and stage in rivers especially for applications such as flood inundation mapping. Simulation Program for River NeTworks (SPRNT) is a fully dynamic model for large scale river networks that solves the full nonlinear Saint-Venant equations for 1D flow and stage height in river channel networks with non-uniform bathymetry. For the current work, the steady-state version of the SPRNT model was leveraged. An evaluation on SPRNT's and NWM's abilities to predict inundation was conducted for the record flood of Hurricane Matthew in October 2016 along the Neuse River in North Carolina. This event was known to have been influenced by backwater effects from the Hurricane's storm surge. Retrospective NWM discharge predictions were converted to stage using synthetic rating curves. The stages from both models were utilized to produce flood inundation maps using the Height Above Nearest Drainage (HAND) method which uses the local relative heights to provide a spatial representation of inundation depths. In order to validate the inundation produced by the models, Sentinel-1A synthetic aperture radar data in the VV and VH polarizations along with auxiliary data was used to produce a reference inundation map. A preliminary, binary comparison of the inundation maps to the reference, limited to the five HUC-12 areas of Goldsboro, NC, yielded that the flood inundation accuracies for NWM and SPRNT were 74.68% and 78.37%, respectively. The differences for all the relevant test statistics including accuracy, true positive rate, true negative rate, and positive predictive value were found

  15. Success/Failure Prediction of Noninvasive Mechanical Ventilation in Intensive Care Units. Using Multiclassifiers and Feature Selection Methods.

    Science.gov (United States)

    Martín-González, Félix; González-Robledo, Javier; Sánchez-Hernández, Fernando; Moreno-García, María N

    2016-05-17

    This paper addresses the problem of decision-making in relation to the administration of noninvasive mechanical ventilation (NIMV) in intensive care units. Data mining methods were employed to find out the factors influencing the success/failure of NIMV and to predict its results in future patients. These artificial intelligence-based methods have not been applied in this field in spite of the good results obtained in other medical areas. Feature selection methods provided the most influential variables in the success/failure of NIMV, such as NIMV hours, PaCO2 at the start, PaO2 / FiO2 ratio at the start, hematocrit at the start or PaO2 / FiO2 ratio after two hours. These methods were also used in the preprocessing step with the aim of improving the results of the classifiers. The algorithms provided the best results when the dataset used as input was the one containing the attributes selected with the CFS method. Data mining methods can be successfully applied to determine the most influential factors in the success/failure of NIMV and also to predict NIMV results in future patients. The results provided by classifiers can be improved by preprocessing the data with feature selection techniques.

  16. The social networking application success model : An empirical study of Facebook and Twitter

    NARCIS (Netherlands)

    Ou, Carol; Davison, R.M.; Huang, Q.

    2016-01-01

    Social networking applications (SNAs) are among the fastest growing web applications of recent years. In this paper, we propose a causal model to assess the success of SNAs, grounded on DeLone and McLean’s updated information systems (IS) success model. In addition to their original three dimensions

  17. Predictive models for moving contact line flows

    Science.gov (United States)

    Rame, Enrique; Garoff, Stephen

    2003-01-01

    Modeling flows with moving contact lines poses the formidable challenge that the usual assumptions of Newtonian fluid and no-slip condition give rise to a well-known singularity. This singularity prevents one from satisfying the contact angle condition to compute the shape of the fluid-fluid interface, a crucial calculation without which design parameters such as the pressure drop needed to move an immiscible 2-fluid system through a solid matrix cannot be evaluated. Some progress has been made for low Capillary number spreading flows. Combining experimental measurements of fluid-fluid interfaces very near the moving contact line with an analytical expression for the interface shape, we can determine a parameter that forms a boundary condition for the macroscopic interface shape when Ca much les than l. This parameter, which plays the role of an "apparent" or macroscopic dynamic contact angle, is shown by the theory to depend on the system geometry through the macroscopic length scale. This theoretically established dependence on geometry allows this parameter to be "transferable" from the geometry of the measurement to any other geometry involving the same material system. Unfortunately this prediction of the theory cannot be tested on Earth.

  18. 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.…

  19. Predicting Academic Success with Early, Middle, and Late Semester Assessment of Student-Instructor Rapport

    Science.gov (United States)

    Lammers, William J.; Gillaspy, J. Arthur, Jr.; Hancock, Felecia

    2017-01-01

    We used a brief scale to measure student-instructor rapport and assessed the degree to which student's perceived rapport at the beginning, middle, and end of the semester predicted final course grades in a traditional course. Results showed a positive correlation between rapport scores and final grades such that rapport at each of the time points…

  20. 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…

  1. Predicting Student Success in a Psychological Statistics Course Emphasizing Collaborative Learning

    Science.gov (United States)

    Gorvine, Benjamin J.; Smith, H. David

    2015-01-01

    This study describes the use of a collaborative learning approach in a psychological statistics course and examines the factors that predict which students benefit most from such an approach in terms of learning outcomes. In a course format with a substantial group work component, 166 students were surveyed on their preference for individual…

  2. Predicting academic success in higher education: what’s more important than being smart?

    NARCIS (Netherlands)

    Kappe, F.R.; van der Flier, H.

    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 (N0137) completed a survey that measured intelligence, the Big Five personality traits,

  3. Light's Retention Scale Does Not Predict Success in First-Grade Retainees.

    Science.gov (United States)

    Sandoval, Jonathan

    1982-01-01

    Used Light's Retention Scale totals, along with measures of achievement, and self-concept to predict academic, emotional, and social status at the end of the repeated first grade. Results suggest that Light's Retention Scale is neither reliable nor valid as a psychometric device. (Author/JAC)

  4. Developmental prediction model for early alcohol initiation in Dutch adolescents

    NARCIS (Netherlands)

    Geels, L.M.; Vink, J.M.; Beijsterveldt, C.E.M. van; Bartels, M.; Boomsma, D.I.

    2013-01-01

    Objective: Multiple factors predict early alcohol initiation in teenagers. Among these are genetic risk factors, childhood behavioral problems, life events, lifestyle, and family environment. We constructed a developmental prediction model for alcohol initiation below the Dutch legal drinking age

  5. 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.

  6. 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.

  7. On the successful use of a simplified model to simulate the succession of toxic cyanobacteria in a hypereutrophic reservoir with a highly fluctuating water level.

    Science.gov (United States)

    Fadel, Ali; Lemaire, Bruno J; Vinçon-Leite, Brigitte; Atoui, Ali; Slim, Kamal; Tassin, Bruno

    2017-09-01

    Many freshwater bodies worldwide that suffer from harmful algal blooms would benefit for their management from a simple ecological model that requires few field data, e.g. for early warning systems. Beyond a certain degree, adding processes to ecological models can reduce model predictive capabilities. In this work, we assess whether a simple ecological model without nutrients is able to describe the succession of cyanobacterial blooms of different species in a hypereutrophic reservoir and help understand the factors that determine these blooms. In our study site, Karaoun Reservoir, Lebanon, cyanobacteria Aphanizomenon ovalisporum and Microcystis aeruginosa alternatively bloom. A simple configuration of the model DYRESM-CAEDYM was used; both cyanobacteria were simulated, with constant vertical migration velocity for A. ovalisporum, with vertical migration velocity dependent on light for M. aeruginosa and with growth limited by light and temperature and not by nutrients for both species. The model was calibrated on two successive years with contrasted bloom patterns and high variations in water level. It was able to reproduce the measurements; it showed a good performance for the water level (root-mean-square error (RMSE) lower than 1 m, annual variation of 25 m), water temperature profiles (RMSE of 0.22-1.41 °C, range 13-28 °C) and cyanobacteria biomass (RMSE of 1-57 μg Chl a L -1 , range 0-206 μg Chl a L -1 ). The model also helped understand the succession of blooms in both years. The model results suggest that the higher growth rate of M. aeruginosa during favourable temperature and light conditions allowed it to outgrow A. ovalisporum. Our results show that simple model configurations can be sufficient not only for theoretical works when few major processes can be identified but also for operational applications. This approach could be transposed on other hypereutrophic lakes and reservoirs to describe the competition between dominant phytoplankton

  8. Initial species composition predicts the progress in the spontaneous succession on post-mining sites

    Czech Academy of Sciences Publication Activity Database

    Mudrák, Ondřej; Doležal, Jiří; Frouz, J.

    2016-01-01

    Roč. 95, č. 11 (2016), s. 665-670 ISSN 0925-8574 R&D Projects: GA ČR GA13-13368S; GA ČR GA13-10377S; GA ČR(CZ) GAP505/11/0256 Institutional support: RVO:67985939 Keywords : Spontaneous succession * Ecological restoration * Calamagrostis epigejos Subject RIV: EH - Ecology, Behaviour Impact factor: 2.914, year: 2016

  9. Computed tomography findings predicting the success of silodosin for medical expulsive therapy of ureteral stones

    Directory of Open Access Journals (Sweden)

    Serdar Celik

    2017-06-01

    Full Text Available Aim of the study is to investigate the relationship between non-contrast computed tomography (NCCT findings and stone expulsion rate with medical expulsive therapy (MET using silodosin for ureteral stones in male adults. Between January 2014 and June 2015, we retrospectively reviewed the patient charts with uncomplicated ureteral stones on NCCT images, who were treated with silodosin for MET. Stone diameter, volume and hounsfield units (HU measured by NCCT and treatment findings were noted at the end of treatment. Patients were divided into three groups according to the localization as distal, mid and proximal ureteral stones. NCCT and treatment findings were compared between MET success and failure groups in different localizations. Stone expulsion rate was 81.3% for 134 distal, 45.5% for 22 mid and 27.7% for 47 proximal stones. Stone diameter, volume, and HU were significantly lower for success groups with distal and proximal stones (p < 0.05. In ROC analysis the cut-off values for stone volume and HU were detected as 48.7 mm3 and 598 HU for success group with proximal stones. Stone expulsion rate was found to be 24 times more (OR = 24; p = 0.001 in patients with <598 HU and 14 times more (OR = 14; p = 0.002 in patients with <48.7 mm3 proximal stones. Lower stone diameter, volume and HU were significant predictors of success with silodosin for MET for ureteral stones. Patients with <598 HU and/or <48.7 mm3 proximal stones may be prescribed silodosin for MET.

  10. Human and canine personality assessment instruments to predict successful adoptions with shelter dogs

    OpenAIRE

    Walker, Sheryl Lynn

    2014-01-01

    Animal shelters are often over-crowded with animals, and efforts to match potential adopters with shelter dogs, to improve the quality of adoptions, are increasing. However, a lack of evidence-based practices makes matching difficult. This research was conducted to investigate the role of dog and human personality, using questionnaire-based measurements, on adoption success in two Indiana shelters, Clinton County Humane Society and the Humane Society of Indianapolis. Ultimately, the aim of th...

  11. A Combination of Dopamine Genes Predicts Success by Professional Wall Street Traders

    OpenAIRE

    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, r...

  12. Anticipatory brain activity predicts the success or failure of subsequent emotion regulation

    OpenAIRE

    Denny, Bryan T.; Ochsner, Kevin N.; Weber, Jochen; Wager, Tor D.

    2013-01-01

    Expectations about an upcoming emotional event have the power to shape one’s subsequent affective response for better or worse. Here, we used mediation analyses to examine the relationship between brain activity when anticipating the need to cognitively reappraise aversive images, amygdala responses to those images and subsequent success in diminishing negative affect. We found that anticipatory activity in right rostrolateral prefrontal cortex was associated with greater subsequent left amyg...

  13. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  14. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  15. A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

    NARCIS (Netherlands)

    Yamamoto, Yumi; Valitalo, Pyry A.; van den Berg, Dirk-Jan; Hartman, Robin; van den Brink, Willem; Wong, Yin Cheong; Huntjens, Dymphy R.; Proost, Johannes H.; Vermeulen, An; Krauwinkel, Walter; Bakshi, Suruchi; Aranzana-Climent, Vincent; Marchand, Sandrine; Dahyot-Fizelier, Claire; Couet, William; Danhof, Meindert; van Hasselt, Johan G. C.; de lange, Elizabeth C. M.

    Purpose Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human

  16. Climate modelling, uncertainty and responses to predictions of change

    International Nuclear Information System (INIS)

    Henderson-Sellers, A.

    1996-01-01

    Article 4.1(F) of the Framework Convention on Climate Change commits all parties to take climate change considerations into account, to the extent feasible, in relevant social, economic and environmental policies and actions and to employ methods such as impact assessments to minimize adverse effects of climate change. This could be achieved by, inter alia, incorporating climate change risk assessment into development planning processes, i.e. relating climatic change to issues of habitability and sustainability. Adaptation is an ubiquitous and beneficial natural and human strategy. Future adaptation (adjustment) to climate is inevitable at the least to decrease the vulnerability to current climatic impacts. An urgent issue is the mismatch between the predictions of global climatic change and the need for information on local to regional change in order to develop adaptation strategies. Mitigation efforts are essential since the more successful mitigation activities are, the less need there will be for adaptation responses. And, mitigation responses can be global (e.g. a uniform percentage reduction in greenhouse gas emissions) while adaptation responses will be local to regional in character and therefore depend upon confident predictions of regional climatic change. The dilemma facing policymakers is that scientists have considerable confidence in likely global climatic changes but virtually zero confidence in regional changes. Mitigation and adaptation strategies relevant to climatic change can most usefully be developed in the context of sound understanding of climate, especially the near-surface continental climate, permitting discussion of societally relevant issues. But, climate models can't yet deliver this type of regionally and locationally specific prediction and some aspects of current research even seem to indicate increased uncertainty. These topics are explored in this paper using the specific example of the prediction of land-surface climate changes

  17. 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

  18. Successful immunization against Acanthamoeba keratitis in a pig model.

    Science.gov (United States)

    Alizadeh, H; He, Y; McCulley, J P; Ma, D; Stewart, G L; Via, M; Haehling, E; Niederkorn, J Y

    1995-03-01

    The feasibility of inducing protective immunity to Acanthamoeba keratitis was tested in a pig model. Experiments were designed to determine if ocular infection with Acanthamoeba trophozoites would elicit protection against reinfection. Additional experiments examined whether injection of parasite antigens either intramuscularly, subconjunctivally, or by both routes would induce immunity. Therefore, four groups of animals were examined: (a) pigs that had resolved a primary corneal infection with Acanthamoeba; (b) pigs immunized intramuscularly; (c) pigs immunized subconjunctivally; and (d) pigs immunized intramuscularly and subconjunctivally. Animals were subsequently challenged with parasite-laden soft contact lenses and observed clinically for the appearance of Acanthamoeba keratitis. Acanthamoeba-specific serum antibody titers and blastogenic responses of peripheral blood lymphocytes were determined weekly. The results indicated that intramuscular injection of Acanthamoeba antigens failed to protect against ocular infection even though hosts developed high titers of IgG antibodies and displayed lymphocyte blastogenic responses to parasite antigens. Ocular infection alone failed to stimulate immunity in any of the animals. By contrast, 50% of the hosts immunized subconjunctivally were protected against corneal disease, and 100% of the animals immunized by a combination of intramuscular and subconjunctival administration of parasite antigens were completely protected against two separate ocular challenges with infectious parasites. Protection did not correlate with either IgG antibody titers or blastogenic potentials of peripheral blood lymphocytes. Interestingly, ocular infection alone failed to stimulate immunity to subsequent ocular challenge with infectious parasites. Thus, administration of parasite antigen via the subconjunctival route can protect against Acanthamoeba keratitis.

  19. The predictive success and profitability of chart patterns in the Euro/Dollar foreign exchange market

    OpenAIRE

    BEN OMRANE, Walid; VAN OPPEN, Hervé

    2004-01-01

    We investigate the existence of chart patterns in the Euro/Dollar intra-daily foreign exchange market. We use two identification methods of the different chart patterns: one built on close prices only, and one based on low and high prices. We look for twelve types of chart patterns and we study the detected patterns through two criteria : predictability and profitability. We run a Monte Carlo simulation to compute the statistical significance of the obtained results. We find an apparent exist...

  20. Sialylated Fetuin-A as a candidate predictive biomarker for successful grass pollen allergen immunotherapy

    OpenAIRE

    Caillot, Noemie; Bouley, Julien; Jain, Karine; Mariano, Sandrine; Luce, Sonia; Horiot, Stéphane; Airouche, Sabi; Beuraud, Chloe; Beauvallet, Christian; Devillier, Philippe; Chollet-Martin, Sylvie; Kellenberger, Christine; Mascarell, Laurent; Chabre, Henri; Batard, Thierry

    2017-01-01

    Background: Eligibility to immunotherapy is based on the determination of IgE reactivity to a specific allergen by means of skin prick or in vitro testing. Biomarkers predicting the likelihood of clinical improvement during immunotherapy would significantly improve patient selection. Methods: Proteins were differentially assessed by using 2-dimensional differential gel electrophoresis and label-free mass spectrometry in pretreatment sera obtained from clinical responders and nonresponders wit...

  1. Predictability in models of the atmospheric circulation

    NARCIS (Netherlands)

    Houtekamer, P.L.

    1992-01-01

    It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error

  2. Oxidative stress predicts long-term resight probability and reproductive success in Scopoli's shearwater (Calonectris diomedea).

    Science.gov (United States)

    Costantini, David; Dell'Omo, Giacomo

    2015-01-01

    A major challenge in conservation physiology is to find out biomarkers that reliably reflect individual variation in wear and tear. Recent work has suggested that biomarkers of oxidative stress may provide an additional tool to assess the health state of individuals and to predict fitness perspectives. In this study, we assessed whether three biomarkers of plasma oxidative status predicted the following factors: (i) the resight probability as breeder in the next seasons; and (ii) the cumulative reproductive output over multiple years in Scopoli's shearwaters (Calonectris diomedea) using a 7 year individual-based data set. Our results show that shearwaters having higher levels of a marker of oxidative damage (reactive oxygen metabolites) in 2008 had a lower resight probability in the next years and a lower number of chicks raised from 2008 to 2014. In contrast, two biomarkers of antioxidant defences (non-enzymatic antioxidant capacity of plasma and thiols) did not have any predictive value. Increased concentrations of plasma reactive oxygen metabolites, together with the significant individual repeatability over time in this metric of oxidative stress found in numerous studies, suggest that this metric might serve as a blood-derived biomarker for health and fitness perspectives in birds and, possibly, also in other taxa.

  3. Plant physiological models of heat, water and photoinhibition stress for climate change modelling and agricultural prediction

    Science.gov (United States)

    Nicolas, B.; Gilbert, M. E.; Paw U, K. T.

    2015-12-01

    Soil-Vegetation-Atmosphere Transfer (SVAT) models are based upon well understood steady state photosynthetic physiology - the Farquhar-von Caemmerer-Berry model (FvCB). However, representations of physiological stress and damage have not been successfully integrated into SVAT models. Generally, it has been assumed that plants will strive to conserve water at higher temperatures by reducing stomatal conductance or adjusting osmotic balance, until potentially damaging temperatures and the need for evaporative cooling become more important than water conservation. A key point is that damage is the result of combined stresses: drought leads to stomatal closure, less evaporative cooling, high leaf temperature, less photosynthetic dissipation of absorbed energy, all coupled with high light (photosynthetic photon flux density; PPFD). This leads to excess absorbed energy by Photosystem II (PSII) and results in photoinhibition and damage, neither are included in SVAT models. Current representations of photoinhibition are treated as a function of PPFD, not as a function of constrained photosynthesis under heat or water. Thus, it seems unlikely that current models can predict responses of vegetation to climate variability and change. We propose a dynamic model of damage to Rubisco and RuBP-regeneration that accounts, mechanistically, for the interactions between high temperature, light, and constrained photosynthesis under drought. Further, these predictions are illustrated by key experiments allowing model validation. We also integrated this new framework within the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). Preliminary results show that our approach can be used to predict reasonable photosynthetic dynamics. For instances, a leaf undergoing one day of drought stress will quickly decrease its maximum quantum yield of PSII (Fv/Fm), but it won't recover to unstressed levels for several days. Consequently, cumulative effect of photoinhibition on photosynthesis can cause

  4. Impulsivity, perceived self-regulatory success in dieting, and body mass in children and adolescents: A moderated mediation model.

    Science.gov (United States)

    Meule, Adrian; Hofmann, Johannes; Weghuber, Daniel; Blechert, Jens

    2016-12-01

    Impulsivity has been suggested to contribute to overeating and obesity. However, findings are inconsistent and it appears that only specific facets of impulsivity are related to eating-related variables and to body mass. In the current study, relationships between self-reported impulsivity, perceived self-regulatory success in dieting, and objectively measured body mass were examined in N = 122 children and adolescents. Scores on attentional and motor impulsivity interactively predicted perceived self-regulatory success in dieting, but not body mass: Higher attentional impulsivity was associated with lower perceived self-regulatory success at high levels of motor impulsivity, but not at low levels of motor impulsivity. A moderated mediation model revealed an indirect effect of attentional and motor impulsivity on body mass, which was mediated by perceived self-regulatory success in dieting. Thus, results show that only specific facets of impulsivity are relevant in eating- and weight-regulation and interact with each other in the prediction of these variables. These facets of impulsivity, however, are not directly related to higher body mass, but indirectly via lower success in eating-related self-regulation in children and adolescents. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Required Collaborative Work in Online Courses: A Predictive Modeling Approach

    Science.gov (United States)

    Smith, Marlene A.; Kellogg, Deborah L.

    2015-01-01

    This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…

  6. Models for predicting compressive strength and water absorption of ...

    African Journals Online (AJOL)

    This work presents a mathematical model for predicting the compressive strength and water absorption of laterite-quarry dust cement block using augmented Scheffe's simplex lattice design. The statistical models developed can predict the mix proportion that will yield the desired property. The models were tested for lack of ...

  7. A model for estimating the minimum number of offspring to sample in studies of reproductive success.

    Science.gov (United States)

    Anderson, Joseph H; Ward, Eric J; Carlson, Stephanie M

    2011-01-01

    Molecular parentage permits studies of selection and evolution in fecund species with cryptic mating systems, such as fish, amphibians, and insects. However, there exists no method for estimating the number of offspring that must be assigned parentage to achieve robust estimates of reproductive success when only a fraction of offspring can be sampled. We constructed a 2-stage model that first estimated the mean (μ) and variance (v) in reproductive success from published studies on salmonid fishes and then sampled offspring from reproductive success distributions simulated from the μ and v estimates. Results provided strong support for modeling salmonid reproductive success via the negative binomial distribution and suggested that few offspring samples are needed to reject the null hypothesis of uniform offspring production. However, the sampled reproductive success distributions deviated significantly (χ(2) goodness-of-fit test p value reproductive success distribution at rates often >0.05 and as high as 0.24, even when hundreds of offspring were assigned parentage. In general, reproductive success patterns were less accurate when offspring were sampled from cohorts with larger numbers of parents and greater variance in reproductive success. Our model can be reparameterized with data from other species and will aid researchers in planning reproductive success studies by providing explicit sampling targets required to accurately assess reproductive success.

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

    Science.gov (United States)

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

    2017-05-01

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

  9. 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

  10. Cognitive function predicts 24-month weight loss success after bariatric surgery.

    Science.gov (United States)

    Spitznagel, Mary Beth; Alosco, Michael; Strain, Gladys; Devlin, Michael; Cohen, Ronald; Paul, Robert; Crosby, Ross D; Mitchell, James E; Gunstad, John

    2013-01-01

    Clinically significant cognitive impairment, particularly in attention/executive and memory function, is found in many patients undergoing bariatric surgery. These difficulties have previously been linked to decreased weight loss 12 months after surgery, but more protracted examination of this relationship has not yet been conducted. The present study prospectively examined the independent contribution of cognitive function to weight loss 24 months after bariatric surgery. Given the rapid rate of cognitive improvement observed after surgery, postoperative cognitive function (i.e., cognition 12 weeks after surgery, controlling for baseline cognition) was expected to predict lower body mass index (BMI) and higher percent total weight loss (%WL) at 24-month follow-up. Data were collected by 3 sites of the Longitudinal Assessment of Bariatric Surgery (LABS) parent project. Fifty-seven individuals enrolled in the LABS project who were undergoing bariatric surgery completed cognitive evaluation at baseline, 12 weeks, and 24 months. BMI and %WL were calculated for 24-month postoperative follow-up. Better cognitive function 12 weeks after surgery predicted higher %WL and lower BMI at 24 months, and specific domains of attention/executive and memory function were robustly related to decreased BMI and greater %WL at 24 months. Results show that cognitive performance shortly after bariatric surgery predicts greater long-term %WL and lower BMI 24 months after bariatric surgery. Further work is needed to clarify the degree to which this relationship is mediated by adherence to postoperative guidelines. Copyright © 2013 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  11. The prediction of success in kickboxing based on the analysis of morphofunctional, physiological, biomechanical and psychophysiological indicators

    Directory of Open Access Journals (Sweden)

    L.V. Podrigalo

    2018-02-01

    Full Text Available Purpose: To substantiate and develop a methodology for predicting success in kickboxing on the basis of analysis of morphofunctional, physiological, biomechanical and psychophysiological indicators. Material: it was examined athletes of kickboxing (n=185, age 18.58 +- 0.46 years. It was studied the features of physical development (n = 18. The main biomechanical parameters (n=45 were determined. Goniometric indices of limb joints (n=29 were studied. It was studied the features of psychophysiological reactions (n =76. The adaptive capabilities of the cardiovascular system were studied (n=17. The prognostication is carried out by means of a sequential Wald procedure. Prognostic coefficients and their informativity were calculated. Results: a prognostic table was developed containing the indicators of the functional state of kickboxing athletes. The table includes 31 criteria, the informativeness of which varied within 115,45 - 2,23. The content of the forecast consists in: an evaluation of the results; determination of the corresponding prognostic coefficient; summation of coefficients. The threshold was set at the level +- 13, which corresponds to a probability of 95% (p<0,05. Exceeding the positive threshold means a high level of success for the athlete. When the negative threshold is reached, the probability of success is low. Conclusions: The proposed methodology is based on a sequential analysis of Wald. The technique is a simple, informative and objective tool for monitoring and predicting the status of athletes.

  12. Predictive value of early serum beta-human chorionic gonadotrophin for the successful outcome in women undergoing in vitro fertilization

    Directory of Open Access Journals (Sweden)

    Neeta Singh

    2013-01-01

    Full Text Available Aims: Pregnancies achieved by in vitro fertilization (IVF are at increased risk of adverse outcome. The main objective of this study was to evaluate the predictive value of β-human chorionic gonadotrophin (β-HCG and age of the patient for the successful outcome in IVF. Materials and Methods: A retrospective study was done in 139 pregnancies after IVF at single IVF center from June 2007 to July 2012. The age of the patient and initial serum values of β-HCG on day 14 of embryo transfer were correlated with ongoing pregnancy (>12 weeks gestation. Results: The β-HCG level on day 14 of more than 347 mIU/ml has a sensitivity of 72.2% and specificity of 73.6% in prediction of pregnancy beyond 12 weeks period of gestation. Positive likelihood ratio (LR is 2.74 and negative LR is 0.37, (receiver operating characteristic area = 0.79. Discussion: In IVF cycles, there is a lot of stress on the couples while the cycle is going on. There was a positive correlation between the higher values of early serum β-HCG levels and ongoing pregnancy. Hence, it can be used as an independent predictor of a successful outcome of IVF cycle. Conclusion: We concluded from our study that early serum β-HCG can be used as a predictor of a successful outcome in IVF.

  13. Personality traits of pair members predict pair compatibility and reproductive success in a socially monogamous parrot breeding in captivity.

    Science.gov (United States)

    Fox, Rebecca A; Millam, James R

    2014-01-01

    While pair behavioral compatibility seems to be a determinant of reproductive success in at least some species of monogamous birds, the specific factors underlying among-pair variation in behavioral compatibility remain poorly understood. However, recent research on the relationship between personality traits and reproductive success in several species of socially monogamous birds suggests that the fit between mates' personality traits might play a role in determining behavioral compatibility. To test this hypothesis, we used ten pairs formed by free choice from a captive population of cockatiels (Nymphicus hollandicus) to investigate whether personality ratings could be used to predict pair compatibility and reproductive success in pairs breeding for the first time. We found that pairs that ultimately hatched eggs paired disassortatively for agreeableness (an aggregate measure of social style which measures birds' tendency to be aggressive vs. gentle, submissive, and tolerant of others' behavior), and, as predicted, showed lower intrapair aggression and better coordination during incubation. Conversely, unsuccessful pairs paired assortatively for agreeableness, showed higher levels of intrapair aggression, and showed poorer coordination during incubation. Our results suggest that personality measurements may provide a useful adjunct to other information currently used in selecting mates for birds breeding in captivity. © 2014 Wiley Periodicals, Inc.

  14. Modeling movie success when "nobody knows anything": Conditional stable distribution analysis of film returns

    OpenAIRE

    W David Walls

    2004-01-01

    In this paper we apply a recently-developed statistical model that explicitly accounts for the extreme uncertainty surrounding film returns. The conditional distribution of box-office returns is analyzed using the stable distribution regression model. The regression coefficients in this model represent what is known about the correlates of film success while at the same time permitting the variance of film success at the box office to be infinite. The empirical analysis shows that the conditi...

  15. Predicting success of oligomerized pool engineering (OPEN for zinc finger target site sequences

    Directory of Open Access Journals (Sweden)

    Goodwin Mathew J

    2010-11-01

    Full Text Available Abstract Background Precise and efficient methods for gene targeting are critical for detailed functional analysis of genomes and regulatory networks and for potentially improving the efficacy and safety of gene therapies. Oligomerized Pool ENgineering (OPEN is a recently developed method for engineering C2H2 zinc finger proteins (ZFPs designed to bind specific DNA sequences with high affinity and specificity in vivo. Because generation of ZFPs using OPEN requires considerable effort, a computational method for identifying the sites in any given gene that are most likely to be successfully targeted by this method is desirable. Results Analysis of the base composition of experimentally validated ZFP target sites identified important constraints on the DNA sequence space that can be effectively targeted using OPEN. Using alternate encodings to represent ZFP target sites, we implemented Naïve Bayes and Support Vector Machine classifiers capable of distinguishing "active" targets, i.e., ZFP binding sites that can be targeted with a high rate of success, from those that are "inactive" or poor targets for ZFPs generated using current OPEN technologies. When evaluated using leave-one-out cross-validation on a dataset of 135 experimentally validated ZFP target sites, the best Naïve Bayes classifier, designated ZiFOpT, achieved overall accuracy of 87% and specificity+ of 90%, with an ROC AUC of 0.89. When challenged with a completely independent test set of 140 newly validated ZFP target sites, ZiFOpT performance was comparable in terms of overall accuracy (88% and specificity+ (92%, but with reduced ROC AUC (0.77. Users can rank potentially active ZFP target sites using a confidence score derived from the posterior probability returned by ZiFOpT. Conclusion ZiFOpT, a machine learning classifier trained to identify DNA sequences amenable for targeting by OPEN-generated zinc finger arrays, can guide users to target sites that are most likely to function

  16. Regression models for predicting anthropometric measurements of ...

    African Journals Online (AJOL)

    measure anthropometric dimensions to predict difficult-to-measure dimensions required for ergonomic design of school furniture. A total of 143 students aged between 16 and 18 years from eight public secondary schools in Ogbomoso, Nigeria ...

  17. FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL ...

    African Journals Online (AJOL)

    direction (σx) had a maximum value of 375MPa (tensile) and minimum value of ... These results shows that the residual stresses obtained by prediction from the finite element method are in fair agreement with the experimental results.

  18. Relevance of Self-reported Behavioral Changes Before Bariatric Surgery to Predict Success After Surgery.

    Science.gov (United States)

    Ledoux, Séverine; Sami, Ouidad; Breuil, Marie-Christine; Delapierre, Marie; Calabrese, Daniela; Msika, Simon; Coupaye, Muriel

    2017-06-01

    International guidelines emphasize the need for multidisciplinary preparation to improve the safety and effectiveness of bariatric surgery (BS), but whether the patient is ready for surgery is difficult to assess. The objective of this study was to explore whether inquiries on dietary habits and physical activity before surgery are predictive of postoperative weight loss. We prospectively assessed in 78 candidates for BS (age, 43 ± 12 years; M/F, 15/63; weight, 122 ± 17 kg; IMC, 44 ± 5 kg/m 2 ) anthropometric parameters, food intake, and physical activity (Baecke questionnaire) at the beginning and the end of a systematized preoperative preparation (7 ± 2 months) including consultations (mean number 7 ± 2) with a nutritionist, dietician, psychologist, and sports coach. During the preparation, weight change was zero (±5 kg). In contrast, self-reported caloric intake decreased from 2143 ± 640 to 1906 ± 564 kcal/24 h (p bariatric surgery, as illustrated by the absence of weight changes on average during the preoperative preparation. In contrast to dietary inquiry, self-reported changes in physical activity are predictive of postoperative weight loss after bariatric surgery.

  19. Prediction for Major Adverse Outcomes in Cardiac Surgery: Comparison of Three Prediction Models

    Directory of Open Access Journals (Sweden)

    Cheng-Hung Hsieh

    2007-09-01

    Conclusion: The Parsonnet score performed as well as the logistic regression models in predicting major adverse outcomes. The Parsonnet score appears to be a very suitable model for clinicians to use in risk stratification of cardiac surgery.

  20. Initial Sleep Time Predicts Success in Manual-Guided Cognitive Behavioral Therapy for Insomnia.

    Science.gov (United States)

    Bothelius, Kristoffer; Kyhle, Kicki; Broman, Jan-Erik; Gordh, Torsten; Fredrikson, Mats

    2016-01-01

    Cognitive behavioral therapy produces significant and long-lasting improvement for individuals with insomnia, but treatment resources are scarce. A "stepped care" approach has therefore been proposed, but knowledge is limited on how to best allocate patients to different treatment steps. In this study, 66 primary-care patients with insomnia attended a low-end treatment step: manual-guided cognitive behavioral therapy (CBT) for insomnia delivered by ordinary primary-care personnel. Based on clinically significant treatment effects, subjects were grouped into treatment responders or nonresponders. Baseline data were analyzed to identify predictors for treatment success. Long total sleep time at baseline assessment was the only statistically significant predictor for becoming a responder, and sleep time may thus be important to consider before enrolling patients in low-end treatments.

  1. Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

    Science.gov (United States)

    He, Yuning

    2015-01-01

    Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

  2. Follicular size predicts success in artificial insemination with frozen-thawed sperm in donkeys.

    Science.gov (United States)

    Saragusty, Joseph; Lemma, Alemayehu; Hildebrandt, Thomas Bernd; Göritz, Frank

    2017-01-01

    In asses, semen collection, cryopreservation, and artificial insemination (AI) with frozen-thawed semen have been scarcely described and success rate, particularly following AI, is reportedly low. In the absence of reliable protocols, assisted reproductive technologies cannot support the conservation efforts aimed at endangered wild ass species and domestic donkey breeds. Two experiments were conducted in this study. In experiment 1 we evaluated freezing Abyssinian donkey (N = 5, 4 ejaculates each) spermatozoa using three freezing extenders (Berliner Cryomedium + glycerol, BC+G; BotuCrio, BOTU; INRAFreeze, INRA) and two cryopreservation techniques (liquid nitrogen vapour, LNV; directional freezing, DF). Post-thaw evaluation indicated that BOTU and INRA were similar and both superior to BC+G (P ≤ 0.004 for all motility tests), and that DF was superior to LNV (P < 0.002 for all evaluation parameters). In experiment 2, relying on these results, we used Abyssinian donkey sperm frozen in BOTU and INRA by DF for AI (N = 20). Prior to AI, thawed samples were diluted in corresponding centrifugation media or autologous seminal fluids at 1:1 ratio. No difference was found between BOTU and INRA or between the addition of seminal fluids or media, all resulting in ~50% pregnancy, and no differences were noted between males (N = 4). The size of pre-ovulatory follicle was a significant (P = 0.001) predictor for AI success with 9/10 pregnancies occurring when follicular size ranged between 33.1-37.4 mm, no pregnancy when it was smaller, and only one when larger. A number of ass species face the risk of extinction. Knowledge gained in this study on the Abyssinian donkey can be customised and transferred to its closely related endangered species and breeds.

  3. Combined individual scrummaging kinetics and muscular power predict competitive team scrum success.

    Science.gov (United States)

    Green, Andrew; Dafkin, Chloe; Kerr, Samantha; McKinon, Warrick

    2017-09-01

    Scrummaging is a major component of Rugby Union gameplay. Successful scrummaging is dependent on the coordination of the forward players and the strength of the eight individuals. The study aim was to determine whether individual scrummaging kinetics and other candidate factors associated with scrummaging performance discriminate team scrum performances. Sixteen club-level forwards (stature: 1.80 ± 0.1 m; mass: 99.0 ± 18.2 kg) were initially divided into two scrummaging packs. A total of 10 various scrum permutations were tested, where players were randomly swapped between the two packs. Winning scrums were determined by two observers on opposite sides of the scrum. Fatigue (100 mm visual analogue scale (VAS)) and scrummaging effort (6-20 rating of perceived exertion (RPE)) were assessed following each scrum contest. Individual scrummaging kinetics were acquired through an instrumented scrum ergometer and muscular power indicated through vertical jump heights. Student's t-tests were used to differentiate between winning and losing scrum packs. VAS and RPE were assessed using repeated measures ANOVAs. Winning scrum packs had significantly larger combined force magnitudes (p scrum packs. While perceived VAS and RPE values progressively increased (p scrum magnitudes were observed between the 1st and 10th scrum (p = .418). The results indicated that the combination of individual forces, variation in movement and factors related to scrummaging performance, such as vertical jump height, were associated with team scrummaging success.

  4. From Predictive Models to Instructional Policies

    Science.gov (United States)

    Rollinson, Joseph; Brunskill, Emma

    2015-01-01

    At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…

  5. Predicting factors of medical treatment success with single dose methotrexate in tubal ectopic pregnancy: a retrospective study

    Directory of Open Access Journals (Sweden)

    Fariba Mirbolouk

    2015-06-01

    Full Text Available Background: Nowadays, The first step in treatment of ectopic pregnancy (EP is medical treatment. Medical treatment with methotrexate (MTX for EP is safe and effective method without the risks associated with the surgical procedure. But there are controversies between studies for which patients will respond better to medical treatment. Objective: The aim of the present study was to investigate the predictive factors of success or failure of treatment of EP with single dose MTX. Materials and Methods: In this retrospective study, records of 370 patients who were treated for tubal EP with single dose of MTX were reviewed during four years. Patients were divided into two groups; the first group or “success group” are the patients who were successfully treated with MTX. The second group or “failure group” consist the patients who did not respond to the MTX therapy. The week of gestation, size and location of EP and β-hCG level were compared between groups. Results: Of 370 patients, 285 (77.1% were successfully treated with MTX. 85 patients (22.9% required surgery after a mean of 5.4 (range 2-15 days. Day-1 beta- human chorionic gonadotropin (β-hCG and fall in β-hCG between day 1 and day 4 were the best predictors for single dose MTX treatment success. The cutoff value of initial β-hCG with the success treatment results was found to be 1375 IU/mL there was no statistical difference between groups about week of gestation, size and location of EP. Conclusion: The results showed that patients who have β-hCG levels below 1375 and the number of cases with decreasing β-hCG level on day 4 are the good candidates for medical treatment.

  6. Measuring online learning systems success: applying the updated DeLone and McLean model.

    Science.gov (United States)

    Lin, Hsiu-Fen

    2007-12-01

    Based on a survey of 232 undergraduate students, this study used the updated DeLone and McLean information systems success model to examine the determinants for successful use of online learning systems (OLS). The results provided an expanded understanding of the factors that measure OLS success. The results also showed that system quality, information quality, and service quality had a significant effect on actual OLS use through user satisfaction and behavioral intention to use OLS.

  7. Seizure freedom score: a new simple method to predict success of epilepsy surgery.

    Science.gov (United States)

    Garcia Gracia, Camilo; Yardi, Ruta; Kattan, Michael W; Nair, Dileep; Gupta, Ajay; Najm, Imad; Bingaman, William; Gonzalez-Martinez, Jorge; Jehi, Lara

    2015-03-01

    We aim to develop a new scale that predicts seizure outcomes after resective epilepsy surgery. We retrospectively reviewed patients who underwent surgery for medically refractory epilepsy at our center between 1999 and 2012. Four predictive outcome indicators were selected: preoperative seizure frequency, history of generalized tonic-clonic seizures, brain magnetic resonance imaging (MRI), and epilepsy duration. A score of 0 or 1 was given if the indicator was associated with poor or good outcome, respectively. A seizure freedom score (SFS) was calculated by adding these four categories (total score ranged from 0 to 4). A modified SFS (m-SFS) was then calculated with two additional outcome indicators: invasive electroencephalography (EEG) evaluation (IEI) (performed or not performed) and lobe of resection (temporal vs. extratemporal), for a score ranging from 0 to 6. Kaplan-Meier survival analysis was used to calculate the probability of seizure freedom in the overall group. Statistical significance was tested using the log-rank test and comparison of 95% confidence intervals (CIs). The study population included 466 patients with 244 (52%) male. Seizure freedom rates were directly correlated with the SFS score: at 10 years, 36.9% of patients with SFS of 0 were seizure-free, as opposed to 45% for SFS = 1, 60% for SFS = 2, 72% for SFS 3 or above (p = 0.002). When calculated including the IEI and the localization, the score's performance improved: 24% of patients with a m-SFS of 0 were seizure-free at 10 years, as opposed to 38-59% for m-SFS = 1-3, and 75-79% for m-SFS of 4-6 (p < 0.001). An easily measurable seizure freedom score could be a reliable tool to synthesize multiple seizure outcome predictors into a single simple score to predict postoperative seizure freedom. This tool will help with patient and family counseling and estimation of surgical candidacy at both early (SFS) and advanced (m-SFS) stages of a surgical evaluation. Wiley Periodicals, Inc. © 2014

  8. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

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

  9. Evaluation of computed tomography findings for success prediction after extracorporeal shock wave lithotripsy for urinary tract stone disease.

    Science.gov (United States)

    Celik, Serdar; Bozkurt, Ozan; Kaya, Fatih Gulbey; Egriboyun, Sedat; Demir, Omer; Secil, Mustafa; Celebi, Ilhan

    2015-01-01

    Currently, the most widely used method of treatment of urinary tract stones is extracorporeal shock wave lithotripsy (SWL). Patient and stone characteristics are important for SWL success. We evaluated noncontrast computed tomography (NCCT) characteristics of urinary tract stones for the prediction of SWL success. Records of patients who underwent NCCT before SWL treatment between January 2008 and June 2012 were retrospectively evaluated. Demographic data were recruited from patient files. Hounsfield units (HU), stone size and skin-to-stone distance (SSD) were measured on NCCT. After serial measurements of the highest HU value (HUmax) and lowest HU value (HUmin), HU value was calculated as the average of these two values (HUave). These parameters were compared between successful [stone-free (SF) group] and unsuccessful [residual fragment (RF) group] cases after SWL. A total of 254 patients, 113 kidney stones and 141 ureteral stones, were evaluated. Mean age was 51.0±14.6 (18-87) years, and mean stone size was 10.9±3.7 mm. Stone diameter, HUmax, HUmin and HUave were significantly lower in SF group when compared with RF group for both kidney and ureteral stones (pHUmin and HUave values are significant predictors of SWL success for both kidney and ureteral stones. They might be used in daily clinical practice for patient counselling.

  10. Greater hunger and less restraint predict weight loss success with phentermine treatment.

    Science.gov (United States)

    Thomas, Elizabeth A; Mcnair, Bryan; Bechtell, Jamie L; Ferland, Annie; Cornier, Marc-Andre; Eckel, Robert H

    2016-01-01

    Phentermine is thought to cause weight loss through a reduction in hunger. It was hypothesized that higher hunger ratings would predict greater weight loss with phentermine. This is an observational pilot study in which all subjects were treated with phentermine for 8 weeks and appetite and eating behaviors were measured at baseline and week 8. Outcomes were compared in subjects with ≥5% vs. hunger (P = 0.017), desire to eat (P =0.003), and prospective food consumption (0.006) and lower baseline cognitive restraint (P = 0.01). In addition, higher baseline home prospective food consumption (P = 0.002) and lower baseline cognitive restraint (P hunger and less restraint are more likely to achieve significant weight loss with phentermine. This information can be used clinically to determine who might benefit most from phentermine treatment. © 2015 The Obesity Society.

  11. Individual brain structure and modelling predict seizure propagation.

    Science.gov (United States)

    Proix, Timothée; Bartolomei, Fabrice; Guye, Maxime; Jirsa, Viktor K

    2017-03-01

    See Lytton (doi:10.1093/awx018) for a scientific commentary on this article.Neural network oscillations are a fundamental mechanism for cognition, perception and consciousness. Consequently, perturbations of network activity play an important role in the pathophysiology of brain disorders. When structural information from non-invasive brain imaging is merged with mathematical modelling, then generative brain network models constitute personalized in silico platforms for the exploration of causal mechanisms of brain function and clinical hypothesis testing. We here demonstrate with the example of drug-resistant epilepsy that patient-specific virtual brain models derived from diffusion magnetic resonance imaging have sufficient predictive power to improve diagnosis and surgery outcome. In partial epilepsy, seizures originate in a local network, the so-called epileptogenic zone, before recruiting other close or distant brain regions. We create personalized large-scale brain networks for 15 patients and simulate the individual seizure propagation patterns. Model validation is performed against the presurgical stereotactic electroencephalography data and the standard-of-care clinical evaluation. We demonstrate that the individual brain models account for the patient seizure propagation patterns, explain the variability in postsurgical success, but do not reliably augment with the use of patient-specific connectivity. Our results show that connectome-based brain network models have the capacity to explain changes in the organization of brain activity as observed in some brain disorders, thus opening up avenues towards discovery of novel clinical interventions. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain.

  12. Generating a robust prediction model for stage I lung adenocarcinoma recurrence after surgical resection.

    Science.gov (United States)

    Wu, Yu-Chung; Wei, Nien-Chih; Hung, Jung-Jyh; Yeh, Yi-Chen; Su, Li-Jen; Hsu, Wen-Hu; Chou, Teh-Ying

    2017-10-03

    Lung cancer mortality remains high even after successful resection. Adjuvant treatment benefits stage II and III patients, but not stage I patients, and most studies fail to predict recurrence in stage I patients. Our study included 211 lung adenocarcinoma patients (stages I-IIIA; 81% stage I) who received curative resections at Taipei Veterans General Hospital between January 2001 and December 2012. We generated a prediction model using 153 samples, with validation using an additional 58 clinical outcome-blinded samples. Gene expression profiles were generated using formalin-fixed, paraffin-embedded tissue samples and microarrays. Data analysis was performed using a supervised clustering method. The prediction model generated from mixed stage samples successfully separated patients at high vs. low risk for recurrence. The validation tests hazard ratio (HR = 4.38) was similar to that of the training tests (HR = 4.53), indicating a robust training process. Our prediction model successfully distinguished high- from low-risk stage IA and IB patients, with a difference in 5-year disease-free survival between high- and low-risk patients of 42% for stage IA and 45% for stage IB ( p model for identifying lung adenocarcinoma patients at high risk for recurrence who may benefit from adjuvant therapy. Our prediction performance of the difference in disease free survival between high risk and low risk groups demonstrates more than two fold improvement over earlier published results.

  13. Robust human body model injury prediction in simulated side impact crashes.

    Science.gov (United States)

    Golman, Adam J; Danelson, Kerry A; Stitzel, Joel D

    2016-01-01

    This study developed a parametric methodology to robustly predict occupant injuries sustained in real-world crashes using a finite element (FE) human body model (HBM). One hundred and twenty near-side impact motor vehicle crashes were simulated over a range of parameters using a Toyota RAV4 (bullet vehicle), Ford Taurus (struck vehicle) FE models and a validated human body model (HBM) Total HUman Model for Safety (THUMS). Three bullet vehicle crash parameters (speed, location and angle) and two occupant parameters (seat position and age) were varied using a Latin hypercube design of Experiments. Four injury metrics (head injury criterion, half deflection, thoracic trauma index and pelvic force) were used to calculate injury risk. Rib fracture prediction and lung strain metrics were also analysed. As hypothesized, bullet speed had the greatest effect on each injury measure. Injury risk was reduced when bullet location was further from the B-pillar or when the bullet angle was more oblique. Age had strong correlation to rib fractures frequency and lung strain severity. The injuries from a real-world crash were predicted using two different methods by (1) subsampling the injury predictors from the 12 best crush profile matching simulations and (2) using regression models. Both injury prediction methods successfully predicted the case occupant's low risk for pelvic injury, high risk for thoracic injury, rib fractures and high lung strains with tight confidence intervals. This parametric methodology was successfully used to explore crash parameter interactions and to robustly predict real-world injuries.

  14. Successful aging as a continuum of functional independence: lessons from physical disability models of aging.

    NARCIS (Netherlands)

    Lowry, K.A.; Vallejo, A.N.; Studenski, S.A.

    2012-01-01

    Successful aging is a multidimensional construct that could be viewed as a continuum of achievement. Based on the disability model proposed by the WHO International Classification of Functioning, Disability and Health, successful aging includes not only the presence or absence of disease, but also

  15. A model to predict the beginning of the pollen season

    DEFF Research Database (Denmark)

    Toldam-Andersen, Torben Bo

    1991-01-01

    In order to predict the beginning of the pollen season, a model comprising the Utah phenoclirnatography Chill Unit (CU) and ASYMCUR-Growing Degree Hour (GDH) submodels were used to predict the first bloom in Alms, Ulttirrs and Berirln. The model relates environmental temperatures to rest completion...... and bud development. As phenologic parameter 14 years of pollen counts were used. The observed datcs for the beginning of the pollen seasons were defined from the pollen counts and compared with the model prediction. The CU and GDH submodels were used as: 1. A fixed day model, using only the GDH model...... for fruit trees are generally applicable, and give a reasonable description of the growth processes of other trees. This type of model can therefore be of value in predicting the start of the pollen season. The predicted dates were generally within 3-5 days of the observed. Finally the possibility of frost...

  16. Risk prediction model: Statistical and artificial neural network approach

    Science.gov (United States)

    Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

    2017-04-01

    Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

  17. United States Medical Licensing Examination Step 1 and 2 Scores Predict Neuroradiology Fellowship Success.

    Science.gov (United States)

    Yousem, Ilyssa J; Liu, Li; Aygun, Nafi; Yousem, David M

    2016-04-01

    Many neuroradiology programs use United States Medical Licensing Examination (USMLE) scores to assess fellowship candidates. The authors hypothesized that because they are taken several years before fellowship, USMLE scores would correlate poorly with success in fellowship training as measured by faculty evaluations. USMLE scores from 10 years of neuroradiology fellows (n = 73) were compared with their cumulative mean E*Value scores from their fellowship years and their best-to-worst rankings within their fellowship years. If available, subspecialty certification scores were also factored as an outcome. Linear correlation and regression analyses were performed adjusting for gender, medical school site, and practice setting after fellowship. USMLE Step 1, 2, and 3 scores were available for 69, 64, and 56 fellows, respectively. Fellowship E*Value scores and rankings showed statistically significant (P neuroradiology fellowship, measured by faculty assessments of the six core competencies. Using the scores as a means of assessing candidates for positions is justified. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  18. Evaluation of the US Army fallout prediction model

    International Nuclear Information System (INIS)

    Pernick, A.; Levanon, I.

    1987-01-01

    The US Army fallout prediction method was evaluated against an advanced fallout prediction model--SIMFIC (Simplified Fallout Interpretive Code). The danger zone areas of the US Army method were found to be significantly greater (up to a factor of 8) than the areas of corresponding radiation hazard as predicted by SIMFIC. Nonetheless, because the US Army's method predicts danger zone lengths that are commonly shorter than the corresponding hot line distances of SIMFIC, the US Army's method is not reliably conservative

  19. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of ...

  20. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of cowpea yield-water use and weather data were collected.