[Establishment of the prediction model for ischemic cardiovascular disease of elderly male population under current health care program].

PubMed

Chen, Jin-hong; Wu, Hai-yun; He, Kun-lun; He, Yao; Qin, Yin-he

2010-10-01

To establish and verify the prediction model for ischemic cardiovascular disease (ICVD) among the elderly population who were under the current health care programs. Statistical analysis on data from physical examination, hospitalization of the past years, from questionnaire and telephone interview was carried out in May, 2003. Data was from a hospital which implementing a health care program. Baseline population with a proportion of 4:1 was randomly selected to generate both module group and verification group. Baseline data was induced to make the verification group into regression model of module group and to generate the predictive value. Distinguished ability with area under ROC curve and the predictive veracity were verified through comparing the predictive incidence rate and actual incidence rate of every deciles group by Hosmer-Lemeshow test. Predictive veracity of the prediction model at population level was verified through comparing the predictive 6-year incidence rates of ICVD with actual 6-year accumulative incidence rates of ICVD with error rate calculated. The samples included 2271 males over the age of 65 with 1817 people for modeling population and 454 for verified population. All of the samples were stratified into two layers to establish hierarchical Cox proportional hazard regression model, including one advanced age group (greater than or equal to 75 years old), and another elderly group (less than 75 years old). Data from the statically analysis showed that the risk factors in aged group were age, systolic blood pressure, serum creatinine level, fasting blood glucose level, while protective factor was high density lipoprotein;in advanced age group, the risk factors were body weight index, systolic blood pressure, serum total cholesterol level, serum creatinine level, fasting blood glucose level, while protective factor was HDL-C. The area under the ROC curve (AUC) and 95%CI were 0.723 and 0.687 - 0.759 respectively. Discriminating power was good. All individual predictive ICVD cumulative incidence and actual incidence were analyzed using Hosmer-Lemeshow test, χ(2) = 1.43, P = 0.786, showing that the predictive veracity was good. The stratified Cox Hazards Regression model was used to establish prediction model of the aged male population under a certain health care program. The common prediction factor of the two age groups were: systolic blood pressure, serum creatinine level, fasting blood glucose level and HDL-C. The area under the ROC curve of the verification group was 0.723, showing that the distinguished ability was good and the predict ability at the individual level and at the group level were also satisfactory. It was feasible to using Cox Proportional Hazards Regression Model for predicting the population groups.

Associations between cognitive abilities and life satisfaction in the oldest-old. Results from the longitudinal population study Good Aging in Skåne

PubMed Central

Enkvist, Åsa; Ekström, Henrik; Elmståhl, Sölve

2013-01-01

Introduction Studies on the associations between cognitive abilities and life satisfaction (LS) in the oldest-old are few. The aim of this study was to explore whether abilities in six different cognitive domains could predict LS in the oldest-old 3 years later. Methods The study population consisted of 681 individuals aged 78–98 years, drawn from the longitudinal population study “Good Aging in Skåne,” which is part of a national survey (The Swedish National Study on Aging and Care). Scores on 13 cognitive tests were related to scores on Neugartens’ LS index A (LSI-A) 3 years later. The cognitive tests were added into six different cognitive domains. A multiple regression analysis was constructed for each cognitive domain separately, with scores on the LSI-A as the dependent variable. The model was adjusted stepwise for sex, age, education, functional capacity, and depressive mood. Results Significant correlations were found between digit cancellation, word recall, verbal fluency (VF) A, VF animals, VF occupations, and mental rotations at baseline, as well as LSI-A at follow-up. The domains of spatial abilities (B = 0.453, P = 0.014) and processing speed (B = 0.118, P = 0.020) remained significantly associated with LSI-A 3 years later after adjustment. Conclusion The cognitive domains of spatial abilities and processing speed predicted LS 3 years later in the oldest-old. Clinical implications are discussed. PMID:23874091

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle.

PubMed

Ayres, D R; Pereira, R J; Boligon, A A; Silva, F F; Schenkel, F S; Roso, V M; Albuquerque, L G

2013-12-01

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

Collective action and the collaborative brain

PubMed Central

Gavrilets, Sergey

2015-01-01

Humans are unique both in their cognitive abilities and in the extent of cooperation in large groups of unrelated individuals. How our species evolved high intelligence in spite of various costs of having a large brain is perplexing. Equally puzzling is how our ancestors managed to overcome the collective action problem and evolve strong innate preferences for cooperative behaviour. Here, I theoretically study the evolution of social-cognitive competencies as driven by selection emerging from the need to produce public goods in games against nature or in direct competition with other groups. I use collaborative ability in collective actions as a proxy for social-cognitive competencies. My results suggest that collaborative ability is more likely to evolve first by between-group conflicts and then later be utilized and improved in games against nature. If collaborative abilities remain low, the species is predicted to become genetically dimorphic with a small proportion of individuals contributing to public goods and the rest free-riding. Evolution of collaborative ability creates conditions for the subsequent evolution of collaborative communication and cultural learning. PMID:25551149

Does Parsonnet scoring model predict mortality following adult cardiac surgery in India?

PubMed

Srilata, Moningi; Padhy, Narmada; Padmaja, Durga; Gopinath, Ramachandran

2015-01-01

To validate the Parsonnet scoring model to predict mortality following adult cardiac surgery in Indian scenario. A total of 889 consecutive patients undergoing adult cardiac surgery between January 2010 and April 2011 were included in the study. The Parsonnet score was determined for each patient and its predictive ability for in-hospital mortality was evaluated. The validation of Parsonnet score was performed for the total data and separately for the sub-groups coronary artery bypass grafting (CABG), valve surgery and combined procedures (CABG with valve surgery). The model calibration was performed using Hosmer-Lemeshow goodness of fit test and receiver operating characteristics (ROC) analysis for discrimination. Independent predictors of mortality were assessed from the variables used in the Parsonnet score by multivariate regression analysis. The overall mortality was 6.3% (56 patients), 7.1% (34 patients) for CABG, 4.3% (16 patients) for valve surgery and 16.2% (6 patients) for combined procedures. The Hosmer-Lemeshow statistic was <0.05 for the total data and also within the sub-groups suggesting that the predicted outcome using Parsonnet score did not match the observed outcome. The area under the ROC curve for the total data was 0.699 (95% confidence interval 0.62-0.77) and when tested separately, it was 0.73 (0.64-0.81) for CABG, 0.79 (0.63-0.92) for valve surgery (good discriminatory ability) and only 0.55 (0.26-0.83) for combined procedures. The independent predictors of mortality determined for the total data were low ejection fraction (odds ratio [OR] - 1.7), preoperative intra-aortic balloon pump (OR - 10.7), combined procedures (OR - 5.1), dialysis dependency (OR - 23.4), and re-operation (OR - 9.4). The Parsonnet score yielded a good predictive value for valve surgeries, moderate predictive value for the total data and for CABG and poor predictive value for combined procedures.

Is decision-making ability related to food choice and facets of eating behaviour in adolescents?

PubMed

Macchi, Rosemarie; MacKew, Laura; Davis, Caroline

2017-09-01

To test the prediction that poor decision-making would predict poor eating-related behaviours, which in turn would relate to elevated body mass index (BMI) percentile. Associations among decision-making ability, eating behaviours, and BMI percentile were examined in a sample of 311 healthy male and female adolescents, aged 14-18 years. Structural equation modelling was used to test the proposed relationships. The predicted model was a good fit to the data and all paths between latent and indicator variables were significant. Impulsive responding significantly predicted poor food choice and overeating. No significant relationships emerged between eating-related variables and BMI percentile. Findings from this study extend the existing research in adults and offer a more comprehensive understanding of factors that may contribute to eating behaviours and weight status in teenagers. Copyright © 2017 Elsevier Ltd. All rights reserved.

External validation of Vascular Study Group of New England risk predictive model of mortality after elective abdominal aorta aneurysm repair in the Vascular Quality Initiative and comparison against established models.

PubMed

Eslami, Mohammad H; Rybin, Denis V; Doros, Gheorghe; Siracuse, Jeffrey J; Farber, Alik

2018-01-01

The purpose of this study is to externally validate a recently reported Vascular Study Group of New England (VSGNE) risk predictive model of postoperative mortality after elective abdominal aortic aneurysm (AAA) repair and to compare its predictive ability across different patients' risk categories and against the established risk predictive models using the Vascular Quality Initiative (VQI) AAA sample. The VQI AAA database (2010-2015) was queried for patients who underwent elective AAA repair. The VSGNE cases were excluded from the VQI sample. The external validation of a recently published VSGNE AAA risk predictive model, which includes only preoperative variables (age, gender, history of coronary artery disease, chronic obstructive pulmonary disease, cerebrovascular disease, creatinine levels, and aneurysm size) and planned type of repair, was performed using the VQI elective AAA repair sample. The predictive value of the model was assessed via the C-statistic. Hosmer-Lemeshow method was used to assess calibration and goodness of fit. This model was then compared with the Medicare, Vascular Governance Northwest model, and Glasgow Aneurysm Score for predicting mortality in VQI sample. The Vuong test was performed to compare the model fit between the models. Model discrimination was assessed in different risk group VQI quintiles. Data from 4431 cases from the VSGNE sample with the overall mortality rate of 1.4% was used to develop the model. The internally validated VSGNE model showed a very high discriminating ability in predicting mortality (C = 0.822) and good model fit (Hosmer-Lemeshow P = .309) among the VSGNE elective AAA repair sample. External validation on 16,989 VQI cases with an overall 0.9% mortality rate showed very robust predictive ability of mortality (C = 0.802). Vuong tests yielded a significant fit difference favoring the VSGNE over then Medicare model (C = 0.780), Vascular Governance Northwest (0.774), and Glasgow Aneurysm Score (0.639). Across the 5 risk quintiles, the VSGNE model predicted observed mortality significantly with great accuracy. This simple VSGNE AAA risk predictive model showed very high discriminative ability in predicting mortality after elective AAA repair among a large external independent sample of AAA cases performed by a diverse array of physicians nationwide. The risk score based on this simple VSGNE model can reliably stratify patients according to their risk of mortality after elective AAA repair better than other established models. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Predicting location of recurrence using FDG, FLT, and Cu-ATSM PET in canine sinonasal tumors treated with radiotherapy

NASA Astrophysics Data System (ADS)

Bradshaw, Tyler; Fu, Rau; Bowen, Stephen; Zhu, Jun; Forrest, Lisa; Jeraj, Robert

2015-07-01

Dose painting relies on the ability of functional imaging to identify resistant tumor subvolumes to be targeted for additional boosting. This work assessed the ability of FDG, FLT, and Cu-ATSM PET imaging to predict the locations of residual FDG PET in canine tumors following radiotherapy. Nineteen canines with spontaneous sinonasal tumors underwent PET/CT imaging with radiotracers FDG, FLT, and Cu-ATSM prior to hypofractionated radiotherapy. Therapy consisted of 10 fractions of 4.2 Gy to the sinonasal cavity with or without an integrated boost of 0.8 Gy to the GTV. Patients had an additional FLT PET/CT scan after fraction 2, a Cu-ATSM PET/CT scan after fraction 3, and follow-up FDG PET/CT scans after radiotherapy. Following image registration, simple and multiple linear and logistic voxel regressions were performed to assess how well pre- and mid-treatment PET imaging predicted post-treatment FDG uptake. R2 and pseudo R2 were used to assess the goodness of fits. For simple linear regression models, regression coefficients for all pre- and mid-treatment PET images were significantly positive across the population (P < 0.05). However, there was large variability among patients in goodness of fits: R2 ranged from 0.00 to 0.85, with a median of 0.12. Results for logistic regression models were similar. Multiple linear regression models resulted in better fits (median R2 = 0.31), but there was still large variability between patients in R2. The R2 from regression models for different predictor variables were highly correlated across patients (R ≈ 0.8), indicating tumors that were poorly predicted with one tracer were also poorly predicted by other tracers. In conclusion, the high inter-patient variability in goodness of fits indicates that PET was able to predict locations of residual tumor in some patients, but not others. This suggests not all patients would be good candidates for dose painting based on a single biological target.

Predicting location of recurrence using FDG, FLT, and Cu-ATSM PET in canine sinonasal tumors treated with radiotherapy.

PubMed

Bradshaw, Tyler; Fu, Rau; Bowen, Stephen; Zhu, Jun; Forrest, Lisa; Jeraj, Robert

2015-07-07

Dose painting relies on the ability of functional imaging to identify resistant tumor subvolumes to be targeted for additional boosting. This work assessed the ability of FDG, FLT, and Cu-ATSM PET imaging to predict the locations of residual FDG PET in canine tumors following radiotherapy. Nineteen canines with spontaneous sinonasal tumors underwent PET/CT imaging with radiotracers FDG, FLT, and Cu-ATSM prior to hypofractionated radiotherapy. Therapy consisted of 10 fractions of 4.2 Gy to the sinonasal cavity with or without an integrated boost of 0.8 Gy to the GTV. Patients had an additional FLT PET/CT scan after fraction 2, a Cu-ATSM PET/CT scan after fraction 3, and follow-up FDG PET/CT scans after radiotherapy. Following image registration, simple and multiple linear and logistic voxel regressions were performed to assess how well pre- and mid-treatment PET imaging predicted post-treatment FDG uptake. R(2) and pseudo R(2) were used to assess the goodness of fits. For simple linear regression models, regression coefficients for all pre- and mid-treatment PET images were significantly positive across the population (P < 0.05). However, there was large variability among patients in goodness of fits: R(2) ranged from 0.00 to 0.85, with a median of 0.12. Results for logistic regression models were similar. Multiple linear regression models resulted in better fits (median R(2) = 0.31), but there was still large variability between patients in R(2). The R(2) from regression models for different predictor variables were highly correlated across patients (R ≈ 0.8), indicating tumors that were poorly predicted with one tracer were also poorly predicted by other tracers. In conclusion, the high inter-patient variability in goodness of fits indicates that PET was able to predict locations of residual tumor in some patients, but not others. This suggests not all patients would be good candidates for dose painting based on a single biological target.

The Eighth Industrial Fluids Properties Simulation Challenge

PubMed Central

Schultz, Nathan E.; Ahmad, Riaz; Brennan, John K.; Frankel, Kevin A.; Moore, Jonathan D.; Moore, Joshua D.; Mountain, Raymond D.; Ross, Richard B.; Thommes, Matthias; Shen, Vincent K.; Siderius, Daniel W.; Smith, Kenneth D.

2016-01-01

The goal of the eighth industrial fluid properties simulation challenge was to test the ability of molecular simulation methods to predict the adsorption of organic adsorbates in activated carbon materials. In particular, the eighth challenge focused on the adsorption of perfluorohexane in the activated carbon BAM-109. Entrants were challenged to predict the adsorption in the carbon at 273 K and relative pressures of 0.1, 0.3, and 0.6. The predictions were judged by comparison to a benchmark set of experimentally determined values. Overall good agreement and consistency were found between the predictions of most entrants. PMID:27840542

Predictive model for risk of cesarean section in pregnant women after induction of labor.

PubMed

Hernández-Martínez, Antonio; Pascual-Pedreño, Ana I; Baño-Garnés, Ana B; Melero-Jiménez, María R; Tenías-Burillo, José M; Molina-Alarcón, Milagros

2016-03-01

To develop a predictive model for risk of cesarean section in pregnant women after induction of labor. A retrospective cohort study was conducted of 861 induced labors during 2009, 2010, and 2011 at Hospital "La Mancha-Centro" in Alcázar de San Juan, Spain. Multivariate analysis was used with binary logistic regression and areas under the ROC curves to determine predictive ability. Two predictive models were created: model A predicts the outcome at the time the woman is admitted to the hospital (before the decision to of the method of induction); and model B predicts the outcome at the time the woman is definitely admitted to the labor room. The predictive factors in the final model were: maternal height, body mass index, nulliparity, Bishop score, gestational age, macrosomia, gender of fetus, and the gynecologist's overall cesarean section rate. The predictive ability of model A was 0.77 [95% confidence interval (CI) 0.73-0.80] and model B was 0.79 (95% CI 0.76-0.83). The predictive ability for pregnant women with previous cesarean section with model A was 0.79 (95% CI 0.64-0.94) and with model B was 0.80 (95% CI 0.64-0.96). For a probability of estimated cesarean section ≥80%, the models A and B presented a positive likelihood ratio (+LR) for cesarean section of 22 and 20, respectively. Also, for a likelihood of estimated cesarean section ≤10%, the models A and B presented a +LR for vaginal delivery of 13 and 6, respectively. These predictive models have a good discriminative ability, both overall and for all subgroups studied. This tool can be useful in clinical practice, especially for pregnant women with previous cesarean section and diabetes.

Bloc Concentration and Dispute Escalation among the Major Powers, 1830-1965.

ERIC Educational Resources Information Center

Stoll, Richard J.

1984-01-01

In the 1830-1914 era, when the major powers had a high level of political-military interdependence and alliance flexibility, changes in bloc concentration were a good predictor of dispute escalation. But bloc concentration had little predictive ability when this interdependence and alliance flexibility declined (1919-1965). (RM)

Assessing landscape vulnerability to wildfire in the USA

Treesearch

Nicole M. Vaillant; Crystal A. Kolden; Alistair M. S. Smith

2016-01-01

Wildfire is an ever present, natural process shaping landscapes. Having the ability to accurately measure and predict wildfire occurrence and impacts to ecosystem goods and services, both retrospectively and prospectively, is critical for adaptive management of landscapes. Landscape vulnerability is a concept widely utilized in the ecosystem management literature that...

Online Learners’ Reading Ability Detection Based on Eye-Tracking Sensors

PubMed Central

Zhan, Zehui; Zhang, Lei; Mei, Hu; Fong, Patrick S. W.

2016-01-01

The detection of university online learners’ reading ability is generally problematic and time-consuming. Thus the eye-tracking sensors have been employed in this study, to record temporal and spatial human eye movements. Learners’ pupils, blinks, fixation, saccade, and regression are recognized as primary indicators for detecting reading abilities. A computational model is established according to the empirical eye-tracking data, and applying the multi-feature regularization machine learning mechanism based on a Low-rank Constraint. The model presents good generalization ability with an error of only 4.9% when randomly running 100 times. It has obvious advantages in saving time and improving precision, with only 20 min of testing required for prediction of an individual learner’s reading ability. PMID:27626418

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

Shortened version of the work ability index to identify workers at risk of long-term sickness absence.

PubMed

Schouten, Lianne S; Bültmann, Ute; Heymans, Martijn W; Joling, Catelijne I; Twisk, Jos W R; Roelen, Corné A M

2016-04-01

The Work Ability Index (WAI) identifies non-sicklisted workers at risk of future long-term sickness absence (LTSA). The WAI is a complicated instrument and inconvenient for use in large-scale surveys. We investigated whether shortened versions of the WAI identify non-sicklisted workers at risk of LTSA. Prospective study including two samples of non-sicklisted workers participating in occupational health checks between 2010 and 2012. A heterogeneous development sample (N= 2899) was used to estimate logistic regression coefficients for the complete WAI, a shortened WAI version without the list of diseases, and single-item Work Ability Score (WAS). These three instruments were calibrated for predictions of different (≥2, ≥4 and ≥6 weeks) LTSA durations in a validation sample of non-sicklisted workers (N= 3049) employed at a steel mill, differentiating between manual (N= 1710) and non-manual (N= 1339) workers. The discriminative ability was investigated by receiver operating characteristic analysis. All three instruments under-predicted the LTSA risks in both manual and non-manual workers. The complete WAI discriminated between individuals at high and low risk of LTSA ≥2, ≥4 and ≥6 weeks in manual and non-manual workers. Risk predictions and discrimination by the shortened WAI without the list of diseases were as good as the complete WAI. The WAS showed poorer discrimination in manual and non-manual workers. The WAI without the list of diseases is a good alternative to the complete WAI to identify non-sicklisted workers at risk of future LTSA durations ≥2, ≥4 and ≥6 weeks. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Intertransaction Class Association Rule Mining Based on Genetic Network Programming and Its Application to Stock Market Prediction

NASA Astrophysics Data System (ADS)

Yang, Yuchen; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro

Intertransaction association rules have been reported to be useful in many fields such as stock market prediction, but still there are not so many efficient methods to dig them out from large data sets. Furthermore, how to use and measure these more complex rules should be considered carefully. In this paper, we propose a new intertransaction class association rule mining method based on Genetic Network Programming (GNP), which has the ability to overcome some shortages of Apriori-like based intertransaction association methods. Moreover, a general classifier model for intertransaction rules is also introduced. In experiments on the real world application of stock market prediction, the method shows its efficiency and ability to obtain good results and can bring more benefits with a suitable classifier considering larger interval span.

Development and validation of a predictive model for excessive postpartum blood loss: A retrospective, cohort study.

PubMed

Rubio-Álvarez, Ana; Molina-Alarcón, Milagros; Arias-Arias, Ángel; Hernández-Martínez, Antonio

2018-03-01

postpartum haemorrhage is one of the leading causes of maternal morbidity and mortality worldwide. Despite the use of uterotonics agents as preventive measure, it remains a challenge to identify those women who are at increased risk of postpartum bleeding. to develop and to validate a predictive model to assess the risk of excessive bleeding in women with vaginal birth. retrospective cohorts study. "Mancha-Centro Hospital" (Spain). the elaboration of the predictive model was based on a derivation cohort consisting of 2336 women between 2009 and 2011. For validation purposes, a prospective cohort of 953 women between 2013 and 2014 were employed. Women with antenatal fetal demise, multiple pregnancies and gestations under 35 weeks were excluded METHODS: we used a multivariate analysis with binary logistic regression, Ridge Regression and areas under the Receiver Operating Characteristic curves to determine the predictive ability of the proposed model. there was 197 (8.43%) women with excessive bleeding in the derivation cohort and 63 (6.61%) women in the validation cohort. Predictive factors in the final model were: maternal age, primiparity, duration of the first and second stages of labour, neonatal birth weight and antepartum haemoglobin levels. Accordingly, the predictive ability of this model in the derivation cohort was 0.90 (95% CI: 0.85-0.93), while it remained 0.83 (95% CI: 0.74-0.92) in the validation cohort. this predictive model is proved to have an excellent predictive ability in the derivation cohort, and its validation in a latter population equally shows a good ability for prediction. This model can be employed to identify women with a higher risk of postpartum haemorrhage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating the Predictive Validity of the Computerized Comprehension Task: Comprehension Predicts Production

PubMed Central

Friend, Margaret; Schmitt, Sara A.; Simpson, Adrianne M.

2017-01-01

Until recently, the challenges inherent in measuring comprehension have impeded our ability to predict the course of language acquisition. The present research reports on a longitudinal assessment of the convergent and predictive validity of the CDI: Words and Gestures and the Computerized Comprehension Task (CCT). The CDI: WG and the CCT evinced good convergent validity however the CCT better predicted subsequent parent reports of language production. Language sample data in the third year confirm this finding: the CCT accounted for 24% of the variance in unique word use. These studies provide evidence for the utility of a behavior-based approach to predicting the course of language acquisition into production. PMID:21928878

Static and transient performance prediction for CFB boilers using a Bayesian-Gaussian Neural Network

NASA Astrophysics Data System (ADS)

Ye, Haiwen; Ni, Weidou

1997-06-01

A Bayesian-Gaussian Neural Network (BGNN) is put forward in this paper to predict the static and transient performance of Circulating Fluidized Bed (CFB) boilers. The advantages of this network over Back-Propagation Neural Networks (BPNNs), easier determination of topology, simpler and time saving in training process as well as self-organizing ability, make this network more practical in on-line performance prediction for complicated processes. Simulation shows that this network is comparable to the BPNNs in predicting the performance of CFB boilers. Good and practical on-line performance predictions are essential for operation guide and model predictive control of CFB boilers, which are under research by the authors.

Predicting heavy episodic drinking using an extended temporal self-regulation theory.

PubMed

Black, Nicola; Mullan, Barbara; Sharpe, Louise

2017-10-01

Alcohol consumption contributes significantly to the global burden from disease and injury, and specific patterns of heavy episodic drinking contribute uniquely to this burden. Temporal self-regulation theory and the dual-process model describe similar theoretical constructs that might predict heavy episodic drinking. The aims of this study were to test the utility of temporal self-regulation theory in predicting heavy episodic drinking, and examine whether the theoretical relationships suggested by the dual-process model significantly extend temporal self-regulation theory. This was a predictive study with 149 Australian adults. Measures were questionnaires (self-report habit index, cues to action scale, purpose-made intention questionnaire, timeline follow-back questionnaire) and executive function tasks (Stroop, Tower of London, operation span). Participants completed measures of theoretical constructs at baseline and reported their alcohol consumption two weeks later. Data were analysed using hierarchical multiple linear regression. Temporal self-regulation theory significantly predicted heavy episodic drinking (R 2 =48.0-54.8%, p<0.001) and the hypothesised extension significantly improved the prediction of heavy episodic drinking frequency (ΔR 2 =4.5%, p=0.001) but not peak consumption (ΔR 2 =1.4%, p=0.181). Intention and behavioural prepotency directly predicted heavy episodic drinking (p<0.01). Planning ability moderated the intention-behaviour relationship and inhibitory control moderated the behavioural prepotency-behaviour relationship (p<0.05). Both temporal self-regulation theory and the extended temporal self-regulation theory provide good prediction of heavy episodic drinking. Intention, behavioural prepotency, planning ability and inhibitory control may be good targets for interventions designed to decrease heavy episodic drinking. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Causal Meaning of Genomic Predictors and How It Affects Construction and Comparison of Genome-Enabled Selection Models

PubMed Central

Valente, Bruno D.; Morota, Gota; Peñagaricano, Francisco; Gianola, Daniel; Weigel, Kent; Rosa, Guilherme J. M.

2015-01-01

The term “effect” in additive genetic effect suggests a causal meaning. However, inferences of such quantities for selection purposes are typically viewed and conducted as a prediction task. Predictive ability as tested by cross-validation is currently the most acceptable criterion for comparing models and evaluating new methodologies. Nevertheless, it does not directly indicate if predictors reflect causal effects. Such evaluations would require causal inference methods that are not typical in genomic prediction for selection. This suggests that the usual approach to infer genetic effects contradicts the label of the quantity inferred. Here we investigate if genomic predictors for selection should be treated as standard predictors or if they must reflect a causal effect to be useful, requiring causal inference methods. Conducting the analysis as a prediction or as a causal inference task affects, for example, how covariates of the regression model are chosen, which may heavily affect the magnitude of genomic predictors and therefore selection decisions. We demonstrate that selection requires learning causal genetic effects. However, genomic predictors from some models might capture noncausal signal, providing good predictive ability but poorly representing true genetic effects. Simulated examples are used to show that aiming for predictive ability may lead to poor modeling decisions, while causal inference approaches may guide the construction of regression models that better infer the target genetic effect even when they underperform in cross-validation tests. In conclusion, genomic selection models should be constructed to aim primarily for identifiability of causal genetic effects, not for predictive ability. PMID:25908318

The science of tobacco addiction and cessation.

PubMed

2014-01-01

Over the past decade, researchers have found genetic variations that affect how nicotine, the main addictive component of tobacco, interacts with cells in the brain and how fast the body metabolizes it. Carrying a high-risk variant predicts a person's ability to snuff out their cigarettes for good. Genetic testing could help predict which smokers might benefit from nicotine replacement therapy or other prescription medications, much like sequencing of malignant tumors can point to the most effective cancer treatment.

Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease.

PubMed

Abraham, Gad; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

2013-02-01

A central goal of medical genetics is to accurately predict complex disease from genotypes. Here, we present a comprehensive analysis of simulated and real data using lasso and elastic-net penalized support-vector machine models, a mixed-effects linear model, a polygenic score, and unpenalized logistic regression. In simulation, the sparse penalized models achieved lower false-positive rates and higher precision than the other methods for detecting causal SNPs. The common practice of prefiltering SNP lists for subsequent penalized modeling was examined and shown to substantially reduce the ability to recover the causal SNPs. Using genome-wide SNP profiles across eight complex diseases within cross-validation, lasso and elastic-net models achieved substantially better predictive ability in celiac disease, type 1 diabetes, and Crohn's disease, and had equivalent predictive ability in the rest, with the results in celiac disease strongly replicating between independent datasets. We investigated the effect of linkage disequilibrium on the predictive models, showing that the penalized methods leverage this information to their advantage, compared with methods that assume SNP independence. Our findings show that sparse penalized approaches are robust across different disease architectures, producing as good as or better phenotype predictions and variance explained. This has fundamental ramifications for the selection and future development of methods to genetically predict human disease. © 2012 WILEY PERIODICALS, INC.

[Spanish versions of the Simplified Motor Score and the Glasgow Coma Scale in out-of-hospital treatment of head injury in adults: a preliminary study of each scale's ability to predict adverse events].

PubMed

Roca, Guillem; Mayol, Sergi; García, Esteban; Casajuana, Edgar; Quintana, Salvador

2015-06-01

To determine the ability of the modified (Spanish) version of the Simplified Motor Score (mSMS) to predict adverse events during hospitalization and to compare its predictive ability to that of the Glasgow Coma Scale (GCS) in adults with head injuries treated outside the hospital. Observational study of retrospective cohorts including all patients over the age of 14 years attended for head injuries occurring within 24 hours of treatment by an advanced life-support unit staffed by nurses between May 1, 2013, and May 1, 2014. The mSMS was a translation of the English original, created through a process of discussions of direct and back translations to arrive at consensus. Out-of-hospital patient records were searched to find GCS and mSMS scores. To predict the ability of each scale to predict brain injuries, neurosurgery, intubation, and/or inhospital death, we calculated the area under the receiving operator characteristic curves (AUCs). Of the total of 115 head-injury patients attended, 64 met the inclusion criteria. The mean (SD) age was 47 (24) years. Twelve (18.8%) patients developed some form of adverse event during hospitalization; 91.6% had brain damage, 58.3% required intubation, 8.3% required surgery, and 41.6% died. The AUC for the GCS was 0.907 (95% CI, 0.81-1.00; P<.001); the AUC for the mSMS was 0.796 (95% CI, 0.64-0.95; P=.001). Although the ability of the mSMS to predict in-hospital adverse outcomes is good, it is inferior to the GCS in adults with head injuries attended outside the hospital.

Development and Validation of Discriminant Analysis Models for Student Loan Defaultees and Non-Defaultees.

ERIC Educational Resources Information Center

Myers, Greeley; Siera, Steven

1980-01-01

Default on guaranteed student loans has been increasing. The use of discriminant analysis as a technique to identify "good" v "bad" student loans based on information available from the loan application is discussed. Research to test the ability of models to such predictions is reported. (Author/MLW)

Theoretical investigation on the microstructure of triethylene glycol based deep eutectic solvents: COSMO-RS and TURBOMOLE prediction

NASA Astrophysics Data System (ADS)

Aissaoui, Tayeb; Benguerba, Yacine; AlNashef, Inas M.

2017-08-01

The in-silico combination mechanism of triethylene glycol based DESs has been studied. COSMO-RS and graphical user interface TmoleX software were used to predict the interaction mechanism of hydrogen bond donors (HBDs) with hydrogen bond acceptors (HBA) to form DESs. The predicted IR results were compared with the previously reported experimental FT-IR analysis for the same studied DESs. The sigma profiles for the HBD, HBAs and formed DESs were interpreted to identify qualitatively molecular properties like polarity or hydrogen bonding donor and acceptor abilities. The predicted physicochemical properties reported in this study were in good agreement with experimental ones.

An appraisal of the psychometric properties of the Clinician version of the Apathy Evaluation Scale (AES-C).

PubMed

Clarke, Diana E; Van Reekum, Robert; Patel, Jigisha; Simard, Martine; Gomez, Everlyne; Streiner, David L

2007-01-01

This article examines the psychometric properties of the clinician version of the Apathy Evaluation Scale (AES-C) to determine its ability to characterize, quantify and differentiate apathy. Critical appraisals of the item-reduction processes, effectiveness of the administration, coding and scoring procedures, and the reliability and validity of the scale were carried out. For training, administration and rating of the AES-C, clearer guidelines, including a more standardized list of verbal and non-verbal apathetic cues, are needed. There is evidence of high internal consistency for the scale across studies. In addition, the original study reported good test-retest and inter-rater reliability coefficients. However, there is a lack of replication on these more stable and informative measures of reliability and as such they warrant further investigation. The research evidence confirms that the AES-C shows good discriminant, convergent and criterion validity. However, evidence of its predictive validity is limited. As this aspect of validity refers to the scale's ability to predict future outcomes, which is important for treatment and rehabilitation planning, further assessment of the predictive validity of the AES-C is needed. In conclusion, the AES-C is a reliable and valid measure for the characterization and quantification of apathy. Copyright (c) 2007 John Wiley & Sons, Ltd.

DFT and 3D-QSAR Studies of Anti-Cancer Agents m-(4-Morpholinoquinazolin-2-yl) Benzamide Derivatives for Novel Compounds Design

NASA Astrophysics Data System (ADS)

Zhao, Siqi; Zhang, Guanglong; Xia, Shuwei; Yu, Liangmin

2018-06-01

As a group of diversified frameworks, quinazolin derivatives displayed a broad field of biological functions, especially as anticancer. To investigate the quantitative structure-activity relationship, 3D-QSAR models were generated with 24 quinazolin scaffold molecules. The experimental and predicted pIC50 values for both training and test set compounds showed good correlation, which proved the robustness and reliability of the generated QSAR models. The most effective CoMFA and CoMSIA were obtained with correlation coefficient r 2 ncv of 1.00 (both) and leave-one-out coefficient q 2 of 0.61 and 0.59, respectively. The predictive abilities of CoMFA and CoMSIA were quite good with the predictive correlation coefficients ( r 2 pred ) of 0.97 and 0.91. In addition, the statistic results of CoMFA and CoMSIA were used to design new quinazolin molecules.

Application of Molecular Interaction Volume Model for Phase Equilibrium of Sn-Based Binary System in Vacuum Distillation

NASA Astrophysics Data System (ADS)

Kong, Lingxin; Yang, Bin; Xu, Baoqiang; Li, Yifu

2014-09-01

Based on the molecular interaction volume model (MIVM), the activities of components of Sn-Sb, Sb-Bi, Sn-Zn, Sn-Cu, and Sn-Ag alloys were predicted. The predicted values are in good agreement with the experimental data, which indicate that the MIVM is of better stability and reliability due to its good physical basis. A significant advantage of the MIVM lies in its ability to predict the thermodynamic properties of liquid alloys using only two parameters. The phase equilibria of Sn-Sb and Sn-Bi alloys were calculated based on the properties of pure components and the activity coefficients, which indicates that Sn-Sb and Sn-Bi alloys can be separated thoroughly by vacuum distillation. This study extends previous investigations and provides an effective and convenient model on which to base refining simulations for Sn-based alloys.

Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences

PubMed Central

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-01-01

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate. PMID:25325356

Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences.

PubMed

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-10-16

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate.

QSAR modeling of acute toxicity on mammals caused by aromatic compounds: the case study using oral LD50 for rats.

PubMed

Rasulev, Bakhtiyor; Kusić, Hrvoje; Leszczynska, Danuta; Leszczynski, Jerzy; Koprivanac, Natalija

2010-05-01

The goal of the study was to predict toxicity in vivo caused by aromatic compounds structured with a single benzene ring and the presence or absence of different substituent groups such as hydroxyl-, nitro-, amino-, methyl-, methoxy-, etc., by using QSAR/QSPR tools. A Genetic Algorithm and multiple regression analysis were applied to select the descriptors and to generate the correlation models. The most predictive model is shown to be the 3-variable model which also has a good ratio of the number of descriptors and their predictive ability to avoid overfitting. The main contributions to the toxicity were shown to be the polarizability weighted MATS2p and the number of certain groups C-026 descriptors. The GA-MLRA approach showed good results in this study, which allows the building of a simple, interpretable and transparent model that can be used for future studies of predicting toxicity of organic compounds to mammals.

Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli

PubMed Central

Laback, Bernhard; Savel, Sophie; Ystad, Sølvi; Balazs, Peter; Meunier, Sabine; Kronland-Martinet, Richard

2016-01-01

Many audio applications perform perception-based time-frequency (TF) analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain) using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1) with standard model parameters (i.e. without efferents), (2) with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other) effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using maximally-compact stimuli. PMID:27875575

Auditory Time-Frequency Masking for Spectrally and Temporally Maximally-Compact Stimuli.

PubMed

Necciari, Thibaud; Laback, Bernhard; Savel, Sophie; Ystad, Sølvi; Balazs, Peter; Meunier, Sabine; Kronland-Martinet, Richard

2016-01-01

Many audio applications perform perception-based time-frequency (TF) analysis by decomposing sounds into a set of functions with good TF localization (i.e. with a small essential support in the TF domain) using TF transforms and applying psychoacoustic models of auditory masking to the transform coefficients. To accurately predict masking interactions between coefficients, the TF properties of the model should match those of the transform. This involves having masking data for stimuli with good TF localization. However, little is known about TF masking for mathematically well-localized signals. Most existing masking studies used stimuli that are broad in time and/or frequency and few studies involved TF conditions. Consequently, the present study had two goals. The first was to collect TF masking data for well-localized stimuli in humans. Masker and target were 10-ms Gaussian-shaped sinusoids with a bandwidth of approximately one critical band. The overall pattern of results is qualitatively similar to existing data for long maskers. To facilitate implementation in audio processing algorithms, a dataset provides the measured TF masking function. The second goal was to assess the potential effect of auditory efferents on TF masking using a modeling approach. The temporal window model of masking was used to predict present and existing data in two configurations: (1) with standard model parameters (i.e. without efferents), (2) with cochlear gain reduction to simulate the activation of efferents. The ability of the model to predict the present data was quite good with the standard configuration but highly degraded with gain reduction. Conversely, the ability of the model to predict existing data for long maskers was better with than without gain reduction. Overall, the model predictions suggest that TF masking can be affected by efferent (or other) effects that reduce cochlear gain. Such effects were avoided in the experiment of this study by using maximally-compact stimuli.

Predictive Validation of an Influenza Spread Model

PubMed Central

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 ability. PMID:23755236

Prognostic value of resident clinical performance ratings.

PubMed

Williams, Reed G; Dunnington, Gary L

2004-10-01

This study investigated the concurrent and predictive validity of end-of-rotation (EOR) clinical performance ratings. Surgeon EOR ratings of residents were collected and compared with end-of-year (EOY) progress decisions and to EOR and EOY confidential judgments of resident ability to provide patient care without direct supervision. Eighty percent to 85% of EOR ratings were Excellent or Very Good. Five percent or fewer were Fair or Poor. Almost all residents receiving Excellent or Very Good EOR ratings also received positive EOR judgments about ability to provide patient care without direct supervision. Residents rated Fair or Poor received negative EOR judgments about ability to provide patient care without direct supervision. As the cumulative percent of Good, Fair, and Poor EOR ratings increased, the number of residents promoted without stipulations at the end of the year decreased and the percentage of faculty members who judged the residents capable of providing effective patient care without direct supervision at the end of the year declined. All residents receiving 40% or more EOR ratings below Very Good had stipulations associated with their promotion. Despite use of descriptive anchors on the scale, clinical performance ratings have no direct meaning. Their meaning needs to be established in the same manner as is done in setting normal values for diagnostic tests, ie, by establishing the relationship between EOR ratings and practice outcomes.

Measurement and prediction of model-rotor flow fields

NASA Technical Reports Server (NTRS)

Owen, F. K.; Tauber, M. E.

1985-01-01

This paper shows that a laser velocimeter can be used to measure accurately the three-component velocities induced by a model rotor at transonic tip speeds. The measurements, which were made at Mach numbers from 0.85 to 0.95 and at zero advance ratio, yielded high-resolution, orthogonal velocity values. The measured velocities were used to check the ability of the ROT22 full-potential rotor code to predict accurately the transonic flow field in the crucial region around and beyond the tip of a high-speed rotor blade. The good agreement between the calculated and measured velocities established the code's ability to predict the off-blade flow field at transonic tip speeds. This supplements previous comparisons in which surface pressures were shown to be well predicted on two different tips at advance ratios to 0.45, especially at the critical 90 deg azimuthal blade position. These results demonstrate that the ROT22 code can be used with confidence to predict the important tip-region flow field, including the occurrence, strength, and location of shock waves causing high drag and noise.

Assessing Soldier Individual Differences to Enable Tailored Training

DTIC Science & Technology

2010-04-01

upon effective and efficient training. However, there is ample evidence that learning-related individual differences exist ( Thorndike , 1985; Jensen...in both civilian and military settings (Schmidt, Hunter, & Outerbridge, 1986; Thorndike , 1985). Prior knowledge or knowledge of facts and...predictive power ( Thorndike , 1985; Jensen, 1998). Further, there is a good deal of evidence that general mental ability impacts performance largely

Attitudes and Motivation of Poor and Good Spellers: Broadening Planned Behavior Theory

ERIC Educational Resources Information Center

Sideridis, Georgios D.

2005-01-01

The purpose of the present study was to broaden planned behavior theory and examine its applicability to predict the academic achievement of students of low and high spelling ability. Two hundred fifty seven students, 54 low spellers and 203 high spellers from thirty elementary schools in northern Greece, participated in the study. Between groups…

Remembering Mike at MacArthur

ERIC Educational Resources Information Center

Horwood, Bert; Raffan, James

2010-01-01

For Bert, Mike, like all good teachers, proved early that he had the ability to predict potential problems and also to look back recognizing problems not adequately controlled. He wrestled with these. He worried at them, not in the neurotic sense of worry, but in the sense of thoroughly examining every aspect of the matter. Mike also knew how to…

Thyroid-specific questions on work ability showed known-groups validity among Danes with thyroid diseases.

PubMed

Nexo, Mette Andersen; Watt, Torquil; Bonnema, Steen Joop; Hegedüs, Laszlo; Rasmussen, Åse Krogh; Feldt-Rasmussen, Ulla; Bjorner, Jakob Bue

2015-07-01

We aimed to identify the best approach to work ability assessment in patients with thyroid disease by evaluating the factor structure, measurement equivalence, known-groups validity, and predictive validity of a broad set of work ability items. Based on the literature and interviews with thyroid patients, 24 work ability items were selected from previous questionnaires, revised, or developed anew. Items were tested among 632 patients with thyroid disease (non-toxic goiter, toxic nodular goiter, Graves' disease (with or without orbitopathy), autoimmune hypothyroidism, and other thyroid diseases), 391 of which had participated in a study 5 years previously. Responses to select items were compared to general population data. We used confirmatory factor analyses for categorical data, logistic regression analyses and tests of differential item function, and head-to-head comparisons of relative validity in distinguishing known groups. Although all work ability items loaded on a common factor, the optimal factor solution included five factors: role physical, role emotional, thyroid-specific limitations, work limitations (without disease attribution), and work performance. The scale on thyroid-specific limitations showed the most power in distinguishing clinical groups and time since diagnosis. A global single item proved useful for comparisons with the general population, and a thyroid-specific item predicted labor market exclusion within the next 5 years (OR 5.0, 95 % CI 2.7-9.1). Items on work limitations with attribution to thyroid disease were most effective in detecting impact on work ability and showed good predictive validity. Generic work ability items remain useful for general population comparisons.

Predicting Noninsulin Antidiabetic Drug Adherence Using a Theoretical Framework Based on the Theory of Planned Behavior in Adults With Type 2 Diabetes

PubMed Central

Zomahoun, Hervé Tchala Vignon; Moisan, Jocelyne; Lauzier, Sophie; Guillaumie, Laurence; Grégoire, Jean-Pierre; Guénette, Line

2016-01-01

Abstract Understanding the process behind noninsulin antidiabetic drug (NIAD) nonadherence is necessary for designing effective interventions to resolve this problem. This study aimed to explore the ability of the theory of planned behavior (TPB), which is known as a good predictor of behaviors, to predict the future NIAD adherence in adults with type 2 diabetes. We conducted a prospective study of adults with type 2 diabetes. They completed a questionnaire on TPB variables and external variables. Linear regression was used to explore the TPB's ability to predict future NIAD adherence, which was prospectively measured as the proportion of days covered by at least 1 NIAD using pharmacy claims data. The interaction between past NIAD adherence and intention was tested. The sample included 340 people. There was an interaction between past NIAD adherence and intention to adhere to the NIAD (P = 0.032). Intention did not predict future NIAD adherence in the past adherers and nonadherers groups, but its association measure was high among past nonadherers (β = 5.686, 95% confidence interval [CI] −10.174, 21.546). In contrast, intention was mainly predicted by perceived behavioral control both in the past adherers (β = 0.900, 95% CI 0.796, 1.004) and nonadherers groups (β = 0.760, 95% CI 0.555, 0.966). The present study suggests that TPB is a good tool to predict intention to adhere and future NIAD adherence. However, there was a gap between intention to adhere and actual adherence to the NIAD, which is partly explained by the past adherence level in adults with type 2 diabetes. PMID:27082543

Predicting toxic effects of copper on aquatic biota in mineralized areas by using the Biotic Ligand Model

USGS Publications Warehouse

Smith, Kathleen S.; Ranville, James F.; Adams, M.; Choate, LaDonna M.; Church, Stan E.; Fey, David L.; Wanty, Richard B.; Crock, James G.

2006-01-01

The chemical speciation of metals influences their biological effects. The Biotic Ligand Model (BLM) is a computational approach to predict chemical speciation and acute toxicological effects of metals on aquatic biota. Recently, the U.S. Environmental Protection Agency incorporated the BLM into their regulatory water-quality criteria for copper. Results from three different laboratory copper toxicity tests were compared with BLM predictions for simulated test-waters. This was done to evaluate the ability of the BLM to accurately predict the effects of hardness and concentrations of dissolved organic carbon (DOC) and iron on aquatic toxicity. In addition, we evaluated whether the BLM and the three toxicity tests provide consistent results. Comparison of BLM predictions with two types of Ceriodaphnia dubia toxicity tests shows that there is fairly good agreement between predicted LC50 values computed by the BLM and LC50 values determined from the two toxicity tests. Specifically, the effect of increasing calcium concentration (and hardness) on copper toxicity appears to be minimal. Also, there is fairly good agreement between the BLM and the two toxicity tests for test solutions containing elevated DOC, for which the LC50 is 3-to-5 times greater (less toxic) than the LC50 for the lower-DOC test water. This illustrates the protective effects of DOC on copper toxicity and demonstrates the ability of the BLM to predict these protective effects. In contrast, for test solutions with added iron there is a decrease in LC50 values (increase in toxicity) in results from the two C. dubia toxicity tests, and the agreement between BLM LC50 predictions and results from these toxicity tests is poor. The inability of the BLM to account for competitive iron binding to DOC or DOC fractionation may be a significant shortcoming of the BLM for predicting site- specific water-quality criteria in streams affected by iron-rich acidic drainage in mined and mineralized areas.

Ventricular shunt tap as a predictor of proximal shunt malfunction in children: a prospective study.

PubMed

Rocque, Brandon G; Lapsiwala, Samir; Iskandar, Bermans J

2008-06-01

The clinical diagnosis of cerebrospinal fluid (CSF) shunt malfunction can be challenging. In this prospective study, the authors evaluated a common method of interrogating shunts: the shunt tap; specifically, its ability to predict proximal malfunction. The authors performed standardized shunt taps in a consecutive series of cases involving children with suspected or proven shunt malfunction, assessing flow and, when possible, opening pressure. Data were collected prospectively, and results analyzed in light of surgical findings. A shunt tap was performed prior to 68 operative explorations in 51 patients. Of the 68 taps, 28 yielded poor or no CSF flow on aspiration. After 26 of these 28 procedures, proximal catheter obstruction was identified. After 28 taps with good CSF return and normal or low opening pressure, 18 shunts were found to have a proximal obstruction, 8 had no obstruction, and 2 had a distal obstruction. Another 12 taps with good CSF flow had high opening pressure; subsequent surgery showed distal obstruction in 11 of the shunts, and proximal obstruction in 1. The positive predictive value of poor flow was 93%, while good flow on shunt tap predicted adequate proximal catheter function in only 55% of cases. Poor flow of CSF on shunt tap is highly predictive of obstruction of the proximal catheter. Because not all patients with good flow on shunt tap underwent surgical shunt exploration, the specificity of this test cannot be determined. Nonetheless, a shunt tap that reveals good flow with a normal opening pressure can be misleading, and management of such cases should be based on clinical judgment.

A-Priori Tuning of Modified Magnussen Combustion Model

NASA Technical Reports Server (NTRS)

Norris, A. T.

2016-01-01

In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for that particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor simulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for simulations.

Transonic Drag Prediction Using an Unstructured Multigrid Solver

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.; Levy, David W.

2001-01-01

This paper summarizes the results obtained with the NSU-3D unstructured multigrid solver for the AIAA Drag Prediction Workshop held in Anaheim, CA, June 2001. The test case for the workshop consists of a wing-body configuration at transonic flow conditions. Flow analyses for a complete test matrix of lift coefficient values and Mach numbers at a constant Reynolds number are performed, thus producing a set of drag polars and drag rise curves which are compared with experimental data. Results were obtained independently by both authors using an identical baseline grid and different refined grids. Most cases were run in parallel on commodity cluster-type machines while the largest cases were run on an SGI Origin machine using 128 processors. The objective of this paper is to study the accuracy of the subject unstructured grid solver for predicting drag in the transonic cruise regime, to assess the efficiency of the method in terms of convergence, cpu time, and memory, and to determine the effects of grid resolution on this predictive ability and its computational efficiency. A good predictive ability is demonstrated over a wide range of conditions, although accuracy was found to degrade for cases at higher Mach numbers and lift values where increasing amounts of flow separation occur. The ability to rapidly compute large numbers of cases at varying flow conditions using an unstructured solver on inexpensive clusters of commodity computers is also demonstrated.

Cerebral oxygenation in traumatic brain injury; Can a non-invasive frequency domain near-infrared spectroscopy device detect changes in brain tissue oxygen tension as well as the established invasive monitor?

PubMed

Davies, David James; Clancy, Michael; Dehghani, Hamid; Lucas, Samuel John Edwin; Forcione, Mario; Yakoub, Kamal Makram; Belli, Antonio

2018-06-07

The cost and highly invasive nature of brain monitoring modality in traumatic brain injury patients currently restrict its utility to specialist neurological intensive care settings. We aim to test the abilities of a frequency domain near-infrared spectroscopy (FD-NIRS) device in predicting changes in invasively measured brain tissue oxygen tension. Individuals admitted to a United Kingdom specialist major trauma centre were contemporaneously monitored with an FD-NIRS device and invasively measured brain tissue oxygen tension probe. Area under the curve receiver operating characteristic (AUROC) statistical analysis was utilised to assess the predictive power of FD-NIRS in detecting both moderate and severe hypoxia (20 and 10 mmHg, respectively), as measured invasively. 16 individuals were prospectively recruited to the investigation. Severe hypoxic episodes were detected in 9 of these individuals, with the NIRS demonstrating a broad range of predictive abilities (AUROC 0.68-0.88) from relatively poor to good. Moderate hypoxic episodes were detected in seven individuals with similar predictive performance (AUROC 0.576 - 0.905). A variable performance in the predictive powers of this FD-NIRS device to detect changes in brain tissue oxygen was demonstrated. Consequently, this enhanced NIRS technology has not demonstrated sufficient ability to replace the established invasive measurement.

A novel method for structure-based prediction of ion channel conductance properties.

PubMed Central

Smart, O S; Breed, J; Smith, G R; Sansom, M S

1997-01-01

A rapid and easy-to-use method of predicting the conductance of an ion channel from its three-dimensional structure is presented. The method combines the pore dimensions of the channel as measured in the HOLE program with an Ohmic model of conductance. An empirically based correction factor is then applied. The method yielded good results for six experimental channel structures (none of which were included in the training set) with predictions accurate to within an average factor of 1.62 to the true values. The predictive r2 was equal to 0.90, which is indicative of a good predictive ability. The procedure is used to validate model structures of alamethicin and phospholamban. Two genuine predictions for the conductance of channels with known structure but without reported conductances are given. A modification of the procedure that calculates the expected results for the effect of the addition of nonelectrolyte polymers on conductance is set out. Results for a cholera toxin B-subunit crystal structure agree well with the measured values. The difficulty in interpreting such studies is discussed, with the conclusion that measurements on channels of known structure are required. Images FIGURE 1 FIGURE 3 FIGURE 4 FIGURE 6 FIGURE 10 PMID:9138559

Diagnostic Accuracy of Somatosensory Evoked Potential Monitoring in Evaluating Neurological Complications During Endovascular Aneurysm Treatment.

PubMed

Ares, William J; Grandhi, Ramesh M; Panczykowski, David M; Weiner, Gregory M; Thirumala, Parthasarathy; Habeych, Miguel E; Crammond, Donald J; Horowitz, Michael B; Jankowitz, Brian T; Jadhav, Ashutosh; Jovin, Tudor G; Ducruet, Andrew F; Balzer, Jeffrey

2018-02-01

Somatosensory evoked potential (SSEP) monitoring is used extensively for early detection and prevention of neurological complications in patients undergoing many different neurosurgical procedures. However, the predictive ability of SSEP monitoring during endovascular treatment of cerebral aneurysms is not well detailed. To evaluate the performance of intraoperative SSEP in the prediction postprocedural neurological deficits (PPNDs) after coil embolization of intracranial aneurysms. This population-based cohort study included patients ≥18 years of age undergoing intracranial aneurysm embolization with concurrent SSEP monitoring between January 2006 and August 2012. The ability of SSEP to predict PPNDs was analyzed by multiple regression analyses and assessed by the area under the receiver operating characteristic curve. In a population of 888 patients, SSEP changes occurred in 8.6% (n = 77). Twenty-eight patients (3.1%) suffered PPNDs. A 50% to 99% loss in SSEP waveform was associated with a 20-fold increase in risk of PPND; a total loss of SSEP waveform, regardless of permanence, was associated with a greater than 200-fold risk of PPND. SSEPs displayed very good predictive ability for PPND, with an area under the receiver operating characteristic curve of 0.84 (95% CI 0.76-0.92). This study supports the predictive ability of SSEPs for the detection of PPNDs. The magnitude and persistence of SSEP changes is clearly associated with the development of PPNDs. The utility of SSEP monitoring in detecting ischemia may provide an opportunity for neurointerventionalists to respond to changes intraoperatively to mitigate the potential for PPNDs. Copyright © 2017 by the Congress of Neurological Surgeons

A Formula to Calculate Standard Liver Volume Using Thoracoabdominal Circumference.

PubMed

Shaw, Brian I; Burdine, Lyle J; Braun, Hillary J; Ascher, Nancy L; Roberts, John P

2017-12-01

With the use of split liver grafts as well as living donor liver transplantation (LDLT) it is imperative to know the minimum graft volume to avoid complications. Most current formulas to predict standard liver volume (SLV) rely on weight-based measures that are likely inaccurate in the setting of cirrhosis. Therefore, we sought to create a formula for estimating SLV without weight-based covariates. LDLT donors underwent computed tomography scan volumetric evaluation of their livers. An optimal formula for calculating SLV using the anthropomorphic measure thoracoabdominal circumference (TAC) was determined using leave-one-out cross-validation. The ability of this formula to correctly predict liver volume was checked against other existing formulas by analysis of variance. The ability of the formula to predict small grafts in LDLT was evaluated by exact logistic regression. The optimal formula using TAC was determined to be SLV = (TAC × 3.5816) - (Age × 3.9844) - (Sex × 109.7386) - 934.5949. When compared to historic formulas, the current formula was the only one which was not significantly different than computed tomography determined liver volumes when compared by analysis of variance with Dunnett posttest. When evaluating the ability of the formula to predict small for size syndrome, many (10/16) of the formulas tested had significant results by exact logistic regression, with our formula predicting small for size syndrome with an odds ratio of 7.94 (95% confidence interval, 1.23-91.36; P = 0.025). We report a formula for calculating SLV that does not rely on weight-based variables that has good ability to predict SLV and identify patients with potentially small grafts.

Screen Twice, Cut Once: Assessing the Predictive Validity of Teacher Selection Tools. Working Paper 120

ERIC Educational Resources Information Center

Goldhaber, Dan; Grout, Cyrus; Huntington-Klein, Nick

2014-01-01

Evidence suggests that teacher hiring in public schools is ad hoc and often fails to result in good selection among applicants. Some districts use structured selection instruments in the hiring process, but we know little about the efficacy of such tools. In this paper, we evaluate the ability of applicant selection tools used by the Spokane…

Frontoparietal Structural Connectivity in Childhood Predicts Development of Functional Connectivity and Reasoning Ability: A Large-Scale Longitudinal Investigation.

PubMed

Wendelken, Carter; Ferrer, Emilio; Ghetti, Simona; Bailey, Stephen K; Cutting, Laurie; Bunge, Silvia A

2017-08-30

Prior research points to a positive concurrent relationship between reasoning ability and both frontoparietal structural connectivity (SC) as measured by diffusion tensor imaging (Tamnes et al., 2010) and frontoparietal functional connectivity (FC) as measured by fMRI (Cocchi et al., 2014). Further, recent research demonstrates a link between reasoning ability and FC of two brain regions in particular: rostrolateral prefrontal cortex (RLPFC) and the inferior parietal lobe (IPL) (Wendelken et al., 2016). Here, we sought to investigate the concurrent and dynamic, lead-lag relationships among frontoparietal SC, FC, and reasoning ability in humans. To this end, we combined three longitudinal developmental datasets with behavioral and neuroimaging data from 523 male and female participants between 6 and 22 years of age. Cross-sectionally, reasoning ability was most strongly related to FC between RLPFC and IPL in adolescents and adults, but to frontoparietal SC in children. Longitudinal analysis revealed that RLPFC-IPL SC, but not FC, was a positive predictor of future changes in reasoning ability. Moreover, we found that RLPFC-IPL SC at one time point positively predicted future changes in RLPFC-IPL FC, whereas, in contrast, FC did not predict future changes in SC. Our results demonstrate the importance of strong white matter connectivity between RLPFC and IPL during middle childhood for the subsequent development of both robust FC and good reasoning ability. SIGNIFICANCE STATEMENT The human capacity for reasoning develops substantially during childhood and has a profound impact on achievement in school and in cognitively challenging careers. Reasoning ability depends on communication between lateral prefrontal and parietal cortices. Therefore, to understand how this capacity develops, we examined the dynamic relationships over time among white matter tracts connecting frontoparietal cortices (i.e., structural connectivity, SC), coordinated frontoparietal activation (functional connectivity, FC), and reasoning ability in a large longitudinal sample of subjects 6-22 years of age. We found that greater frontoparietal SC in childhood predicts future increases in both FC and reasoning ability, demonstrating the importance of white matter development during childhood for subsequent brain and cognitive functioning. Copyright © 2017 the authors 0270-6474/17/378549-10$15.00/0.

Frontoparietal Structural Connectivity in Childhood Predicts Development of Functional Connectivity and Reasoning Ability: A Large-Scale Longitudinal Investigation

PubMed Central

Ferrer, Emilio; Cutting, Laurie

2017-01-01

Prior research points to a positive concurrent relationship between reasoning ability and both frontoparietal structural connectivity (SC) as measured by diffusion tensor imaging (Tamnes et al., 2010) and frontoparietal functional connectivity (FC) as measured by fMRI (Cocchi et al., 2014). Further, recent research demonstrates a link between reasoning ability and FC of two brain regions in particular: rostrolateral prefrontal cortex (RLPFC) and the inferior parietal lobe (IPL) (Wendelken et al., 2016). Here, we sought to investigate the concurrent and dynamic, lead–lag relationships among frontoparietal SC, FC, and reasoning ability in humans. To this end, we combined three longitudinal developmental datasets with behavioral and neuroimaging data from 523 male and female participants between 6 and 22 years of age. Cross-sectionally, reasoning ability was most strongly related to FC between RLPFC and IPL in adolescents and adults, but to frontoparietal SC in children. Longitudinal analysis revealed that RLPFC–IPL SC, but not FC, was a positive predictor of future changes in reasoning ability. Moreover, we found that RLPFC–IPL SC at one time point positively predicted future changes in RLPFC–IPL FC, whereas, in contrast, FC did not predict future changes in SC. Our results demonstrate the importance of strong white matter connectivity between RLPFC and IPL during middle childhood for the subsequent development of both robust FC and good reasoning ability. SIGNIFICANCE STATEMENT The human capacity for reasoning develops substantially during childhood and has a profound impact on achievement in school and in cognitively challenging careers. Reasoning ability depends on communication between lateral prefrontal and parietal cortices. Therefore, to understand how this capacity develops, we examined the dynamic relationships over time among white matter tracts connecting frontoparietal cortices (i.e., structural connectivity, SC), coordinated frontoparietal activation (functional connectivity, FC), and reasoning ability in a large longitudinal sample of subjects 6–22 years of age. We found that greater frontoparietal SC in childhood predicts future increases in both FC and reasoning ability, demonstrating the importance of white matter development during childhood for subsequent brain and cognitive functioning. PMID:28821657

Salivary mRNA markers having the potential to detect oral squamous cell carcinoma segregated from oral leukoplakia with dysplasia.

PubMed

Michailidou, Evangelia; Tzimagiorgis, Georgios; Chatzopoulou, Fani; Vahtsevanos, Konstantinos; Antoniadis, Konstantinos; Kouidou, Sofia; Markopoulos, Anastasios; Antoniades, Dimitrios

2016-08-01

In the current study the presence of extracellular IL-1B, IL-8, OAZ and SAT mRNAs in the saliva was evaluated as a tool in the early detection of oral squamous cell carcinoma. 34 patients with primary oral squamous cell carcinoma stage T1N0M0/T2N0M0, 20 patients with oral leukoplakia and dysplasia (15 patients with mild dysplasia and 5 with severe dysplasia/in situ carcinoma) and 31 matched healthy-control subjects were included in the study. The presence of IL-1B, IL-8, OAZ and SAT mRNA was evaluated in extracellular RNA isolated from saliva samples using sequence-specific primers and real-time RT-PCR. ROC curve analysis was used to estimate the ability of the biomarkers to detect oral squamous cell carcinoma patients. The data reveal that the combination of these four biomarkers provides a good predictive probability of up to 80% (AUC=0.799, p=0.002) for patients with oral squamous cell carcinoma but not patients suffering from oral leukoplakia with dysplasia. Moreover, the combination of only the two biomarkers (SAT and IL-8) also raises a high predictive ability of 75.5% (AUC=0.755, p=0.007) approximately equal to the four biomarkers suggesting the use of the two biomarkers only in the prediction model for oral squamous cell carcinoma patients limiting the economic and health cost in half. SAT and IL-8 mRNAs are present in the saliva in high quality and quantity, with a good discriminatory ability for oral squamous cell carcinoma patients only but not for patients with oral leukoplakia and dysplasia an oral potentially malignant disorder. Copyright © 2016. Published by Elsevier Ltd.

Brain structure correlates of component reading processes: implications for reading disability.

PubMed

Phinney, Erin; Pennington, Bruce F; Olson, Richard; Filley, Christopher M; Filipek, Pauline A

2007-08-01

Brain structures implicated in developmental dyslexia (reading disability - RD) vary greatly across structural magnetic resonance imaging (MRI) studies due to methodological differences regarding the definition of RD and the exact measurements of a specific brain structure. The current study attempts to resolve some of those methodological concerns by examining brain volume as it relates to components of proposed RD subtypes. We performed individual regression analyses on total cerebral volume, neocortical volume, subcortical volume, 9 neo-cortical structures and 2 sub-cortical structures. These analyses used three dimensions of reading, phonemic ability (PA), orthographic ability, and rapid naming (RN) ability, while accounting for total cerebral volume, age, and performance IQ (PIQ). Primary analyses included membership to a group (poor reader vs. good reader) in the analysis. The result was a significant interaction between PA and reading ability as it predicts total cerebral volume. Analyses revealed that poor readers lacked a relationship between PA and brain size, but that good readers had a significant positive relationship. This pattern of interaction was not present for the other two reading component factors. These findings bring into question the general belief that individuals with RD are at the low end of a reading ability distribution and do not have a unique disorder. Additional analyses revealed only a few significant relationships between brain size and task performance, most notably a positive correlation between orthographic ability and the angular gyrus (AG), as well as a negative correlation between RN ability and the parietal operculum (PO).

Applicability of Monte Carlo cross validation technique for model development and validation using generalised least squares regression

NASA Astrophysics Data System (ADS)

Haddad, Khaled; Rahman, Ataur; A Zaman, Mohammad; Shrestha, Surendra

2013-03-01

SummaryIn regional hydrologic regression analysis, model selection and validation are regarded as important steps. Here, the model selection is usually based on some measurements of goodness-of-fit between the model prediction and observed data. In Regional Flood Frequency Analysis (RFFA), leave-one-out (LOO) validation or a fixed percentage leave out validation (e.g., 10%) is commonly adopted to assess the predictive ability of regression-based prediction equations. This paper develops a Monte Carlo Cross Validation (MCCV) technique (which has widely been adopted in Chemometrics and Econometrics) in RFFA using Generalised Least Squares Regression (GLSR) and compares it with the most commonly adopted LOO validation approach. The study uses simulated and regional flood data from the state of New South Wales in Australia. It is found that when developing hydrologic regression models, application of the MCCV is likely to result in a more parsimonious model than the LOO. It has also been found that the MCCV can provide a more realistic estimate of a model's predictive ability when compared with the LOO.

Establishment and validation of the scoring system for preoperative prediction of central lymph node metastasis in papillary thyroid carcinoma.

PubMed

Liu, Wen; Cheng, Ruochuan; Ma, Yunhai; Wang, Dan; Su, Yanjun; Diao, Chang; Zhang, Jianming; Qian, Jun; Liu, Jin

2018-05-03

Early preoperative diagnosis of central lymph node metastasis (CNM) is crucial to improve survival rates among patients with papillary thyroid carcinoma (PTC). Here, we analyzed clinical data from 2862 PTC patients and developed a scoring system using multivariable logistic regression and testified by the validation group. The predictive diagnostic effectiveness of the scoring system was evaluated based on consistency, discrimination ability, and accuracy. The scoring system considered seven variables: gender, age, tumor size, microcalcification, resistance index >0.7, multiple nodular lesions, and extrathyroid extension. The area under the receiver operating characteristic curve (AUC) was 0.742, indicating a good discrimination. Using 5 points as a diagnostic threshold, the validation results for validation group had an AUC of 0.758, indicating good discrimination and consistency in the scoring system. The sensitivity of this predictive model for preoperative diagnosis of CNM was 4 times higher than a direct ultrasound diagnosis. These data indicate that the CNM prediction model would improve preoperative diagnostic sensitivity for CNM in patients with papillary thyroid carcinoma.

A Numerical Analysis of Heat Transfer and Effectiveness on Film Cooled Turbine Blade Tip Models

NASA Technical Reports Server (NTRS)

Ameri, A. A.; Rigby, D. L.

1999-01-01

A computational study has been performed to predict the distribution of convective heat transfer coefficient on a simulated blade tip with cooling holes. The purpose of the examination was to assess the ability of a three-dimensional Reynolds-averaged Navier-Stokes solver to predict the rate of tip heat transfer and the distribution of cooling effectiveness. To this end, the simulation of tip clearance flow with blowing of Kim and Metzger was used. The agreement of the computed effectiveness with the data was quite good. The agreement with the heat transfer coefficient was not as good but improved away from the cooling holes. Numerical flow visualization showed that the uniformity of wetting of the surface by the film cooling jet is helped by the reverse flow due to edge separation of the main flow.

Turbine Vane External Heat Transfer. Volume 2. Numerical Solutions of the Navier-stokes Equations for Two- and Three-dimensional Turbine Cascades with Heat Transfer

NASA Technical Reports Server (NTRS)

Yang, R. J.; Weinberg, B. C.; Shamroth, S. J.; Mcdonald, H.

1985-01-01

The application of the time-dependent ensemble-averaged Navier-Stokes equations to transonic turbine cascade flow fields was examined. In particular, efforts focused on an assessment of the procedure in conjunction with a suitable turbulence model to calculate steady turbine flow fields using an O-type coordinate system. Three cascade configurations were considered. Comparisons were made between the predicted and measured surface pressures and heat transfer distributions wherever available. In general, the pressure predictions were in good agreement with the data. Heat transfer calculations also showed good agreement when an empirical transition model was used. However, further work in the development of laminar-turbulent transitional models is indicated. The calculations showed most of the known features associated with turbine cascade flow fields. These results indicate the ability of the Navier-Stokes analysis to predict, in reasonable amounts of computation time, the surface pressure distribution, heat transfer rates, and viscous flow development for turbine cascades operating at realistic conditions.

External validity of two nomograms for predicting distant brain failure after radiosurgery for brain metastases in a bi-institutional independent patient cohort.

PubMed

Prabhu, Roshan S; Press, Robert H; Boselli, Danielle M; Miller, Katherine R; Lankford, Scott P; McCammon, Robert J; Moeller, Benjamin J; Heinzerling, John H; Fasola, Carolina E; Patel, Kirtesh R; Asher, Anthony L; Sumrall, Ashley L; Curran, Walter J; Shu, Hui-Kuo G; Burri, Stuart H

2018-03-01

Patients treated with stereotactic radiosurgery (SRS) for brain metastases (BM) are at increased risk of distant brain failure (DBF). Two nomograms have been recently published to predict individualized risk of DBF after SRS. The goal of this study was to assess the external validity of these nomograms in an independent patient cohort. The records of consecutive patients with BM treated with SRS at Levine Cancer Institute and Emory University between 2005 and 2013 were reviewed. Three validation cohorts were generated based on the specific nomogram or recursive partitioning analysis (RPA) entry criteria: Wake Forest nomogram (n = 281), Canadian nomogram (n = 282), and Canadian RPA (n = 303) validation cohorts. Freedom from DBF at 1-year in the Wake Forest study was 30% compared with 50% in the validation cohort. The validation c-index for both the 6-month and 9-month freedom from DBF Wake Forest nomograms was 0.55, indicating poor discrimination ability, and the goodness-of-fit test for both nomograms was highly significant (p < 0.001), indicating poor calibration. The 1-year actuarial DBF in the Canadian nomogram study was 43.9% compared with 50.9% in the validation cohort. The validation c-index for the Canadian 1-year DBF nomogram was 0.56, and the goodness-of-fit test was also highly significant (p < 0.001). The validation accuracy and c-index of the Canadian RPA classification was 53% and 0.61, respectively. The Wake Forest and Canadian nomograms for predicting risk of DBF after SRS were found to have limited predictive ability in an independent bi-institutional validation cohort. These results reinforce the importance of validating predictive models in independent patient cohorts.

Women's fertility across the cycle increases the short-term attractiveness of creative intelligence.

PubMed

Haselton, Martie G; Miller, Geoffrey F

2006-03-01

Male provisioning ability may have evolved as a "good dad" indicator through sexual selection, whereas male creativity may have evolved partly as a "good genes" indicator. If so, women near peak fertility (midcycle) should prefer creativity over wealth, especially in short-term mating. Forty-one normally cycling women read vignettes describing creative but poor men vs. uncreative but rich men. Women's estimated fertility predicted their short-term (but not long-term) preference for creativity over wealth, in both their desirability ratings of individual men (r=.40, p<.01) and their forced-choice decisions between men (r=.46, p<.01). These preliminary results are consistent with the view that creativity evolved at least partly as a good genes indicator through mate choice.

[Construction of competency model of 'excellent doctor' in Chinese medicine].

PubMed

Jin, Aning; Tian, Yongquan; Zhao, Taiyang

2014-05-01

To evaluate outstanding and ordinary persons from personal characteristics using competency as the important criteria, which is the future direction of medical education reform. We carried on a behavior event interview about famous doctors of old traditional Chinese medicine, compiled competency dictionary, proceed control prediction test. SPSS and AMOS were used to be data analysis tools on statistics. We adopted the model of peer assessment and contrast to carry out empirical research. This project has carried on exploratory factor analysis and confirmatory factor analysis, established a "5A" competency model which include moral ability, thinking ability, communication ability, learning and practical ability. Competency model of "excellent doctor" in Chinese medicine has been validated, with good reliability and validity, and embodies the characteristics of traditional Chinese medicine personnel training, with theoretical and practical significance for excellence in medicine physician training.

Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates

USGS Publications Warehouse

Patino, Reynaldo; VanLandeghem, Matthew M.; Denny, Shawn

2016-01-01

Golden alga (Prymnesium parvum) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from ∼ 80% to ∼ 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.

Development of a Salmonella screening tool for consumer complaint-based foodborne illness surveillance systems.

PubMed

Li, John; Maclehose, Rich; Smith, Kirk; Kaehler, Dawn; Hedberg, Craig

2011-01-01

Foodborne illness surveillance based on consumer complaints detects outbreaks by finding common exposures among callers, but this process is often difficult. Laboratory testing of ill callers could also help identify potential outbreaks. However, collection of stool samples from all callers is not feasible. Methods to help screen calls for etiology are needed to increase the efficiency of complaint surveillance systems and increase the likelihood of detecting foodborne outbreaks caused by Salmonella. Data from the Minnesota Department of Health foodborne illness surveillance database (2000 to 2008) were analyzed. Complaints with identified etiologies were examined to create a predictive model for Salmonella. Bootstrap methods were used to internally validate the model. Seventy-one percent of complaints in the foodborne illness database with known etiologies were due to norovirus. The predictive model had a good discriminatory ability to identify Salmonella calls. Three cutoffs for the predictive model were tested: one that maximized sensitivity, one that maximized specificity, and one that maximized predictive ability, providing sensitivities and specificities of 32 and 96%, 100 and 54%, and 89 and 72%, respectively. Development of a predictive model for Salmonella could help screen calls for etiology. The cutoff that provided the best predictive ability for Salmonella corresponded to a caller reporting diarrhea and fever with no vomiting, and five or fewer people ill. Screening calls for etiology would help identify complaints for further follow-up and result in identifying Salmonella cases that would otherwise go unconfirmed; in turn, this could lead to the identification of more outbreaks.

Walking Performance: Correlation between Energy Cost of Walking and Walking Participation. New Statistical Approach Concerning Outcome Measurement

PubMed Central

Franceschini, Marco; Rampello, Anais; Agosti, Maurizio; Massucci, Maurizio; Bovolenta, Federica; Sale, Patrizio

2013-01-01

Walking ability, though important for quality of life and participation in social and economic activities, can be adversely affected by neurological disorders, such as Spinal Cord Injury, Stroke, Multiple Sclerosis or Traumatic Brain Injury. The aim of this study is to evaluate if the energy cost of walking (CW), in a mixed group of chronic patients with neurological diseases almost 6 months after discharge from rehabilitation wards, can predict the walking performance and any walking restriction on community activities, as indicated by Walking Handicap Scale categories (WHS). One hundred and seven subjects were included in the study, 31 suffering from Stroke, 26 from Spinal Cord Injury and 50 from Multiple Sclerosis. The multivariable binary logistical regression analysis has produced a statistical model with good characteristics of fit and good predictability. This model generated a cut-off value of.40, which enabled us to classify correctly the cases with a percentage of 85.0%. Our research reveal that, in our subjects, CW is the only predictor of the walking performance of in the community, to be compared with the score of WHS. We have been also identifying a cut-off value of CW cost, which makes a distinction between those who can walk in the community and those who cannot do it. In particular, these values could be used to predict the ability to walk in the community when discharged from the rehabilitation units, and to adjust the rehabilitative treatment to improve the performance. PMID:23468871

The “Dry-Run” Analysis: A Method for Evaluating Risk Scores for Confounding Control

PubMed Central

Wyss, Richard; Hansen, Ben B.; Ellis, Alan R.; Gagne, Joshua J.; Desai, Rishi J.; Glynn, Robert J.; Stürmer, Til

2017-01-01

Abstract A propensity score (PS) model's ability to control confounding can be assessed by evaluating covariate balance across exposure groups after PS adjustment. The optimal strategy for evaluating a disease risk score (DRS) model's ability to control confounding is less clear. DRS models cannot be evaluated through balance checks within the full population, and they are usually assessed through prediction diagnostics and goodness-of-fit tests. A proposed alternative is the “dry-run” analysis, which divides the unexposed population into “pseudo-exposed” and “pseudo-unexposed” groups so that differences on observed covariates resemble differences between the actual exposed and unexposed populations. With no exposure effect separating the pseudo-exposed and pseudo-unexposed groups, a DRS model is evaluated by its ability to retrieve an unconfounded null estimate after adjustment in this pseudo-population. We used simulations and an empirical example to compare traditional DRS performance metrics with the dry-run validation. In simulations, the dry run often improved assessment of confounding control, compared with the C statistic and goodness-of-fit tests. In the empirical example, PS and DRS matching gave similar results and showed good performance in terms of covariate balance (PS matching) and controlling confounding in the dry-run analysis (DRS matching). The dry-run analysis may prove useful in evaluating confounding control through DRS models. PMID:28338910

Prediction of pelvic organ prolapse using an artificial neural network.

PubMed

Robinson, Christopher J; Swift, Steven; Johnson, Donna D; Almeida, Jonas S

2008-08-01

The objective of this investigation was to test the ability of a feedforward artificial neural network (ANN) to differentiate patients who have pelvic organ prolapse (POP) from those who retain good pelvic organ support. Following institutional review board approval, patients with POP (n = 87) and controls with good pelvic organ support (n = 368) were identified from the urogynecology research database. Historical and clinical information was extracted from the database. Data analysis included the training of a feedforward ANN, variable selection, and external validation of the model with an independent data set. Twenty variables were used. The median-performing ANN model used a median of 3 (quartile 1:3 to quartile 3:5) variables and achieved an area under the receiver operator curve of 0.90 (external, independent validation set). Ninety percent sensitivity and 83% specificity were obtained in the external validation by ANN classification. Feedforward ANN modeling is applicable to the identification and prediction of POP.

Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

NASA Astrophysics Data System (ADS)

Li, Ziyu; Bi, Jun; Li, Zhiyin

2017-12-01

Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

It's Selective, but Is It Effective? Exploring the Predictive Validity of Teacher Selection Tools. CEDR Brief. Policy Brief No. 2014-­9

ERIC Educational Resources Information Center

Goldhaber, Dan; Grout, Cyrus; Huntington-Klein, Nick

2014-01-01

Evidence suggests teacher hiring in public schools is ad-hoc and often does not result in good selection amongst applicants. Some districts use structured selection instruments in the hiring process, but we know little about the efficacy of such tools. In this paper we evaluate the ability of applicant selection tools used by the Spokane Public…

Predictive value of flat-panel CT for haemorrhagic transformations in patients with acute stroke treated with thrombectomy.

PubMed

Rouchaud, Aymeric; Pistocchi, Silvia; Blanc, Raphaël; Engrand, Nicolas; Bartolini, Bruno; Piotin, Michel

2014-03-01

Haemorrhagic transformations are pejorative for patients with acute ischaemic stroke (AIS). We estimated flat-panel CT performances to detect brain parenchymal hyperdense lesions immediately after mechanical thrombectomy directly on the angiography table in patients with AIS, and its ability to predict haemorrhagic transformation. We also evaluated an easy-reading protocol for post-procedure flat-panel CT evaluation by clinicians to enable them to determine the potential risk of haemorrhage. Two neuroradiologists retrospectively reviewed post-procedural flat-panel CT and 24 h follow-up imaging. We evaluated hyperdense lesions on flat-panel CT to predict the occurrence of haemorrhagic transformation within 24 h detected with conventional imaging. Of 63 patients, 60.3% presented post-procedural parenchymal hyperdensity and 54.0% had haemorrhagic transformation. Significantly more patients with hyperdense lesions on post-thrombectomy flat-panel CT presented haemorrhagic transformation (84.2% vs 8.0%; p<0.0001). No significant haemorrhagic transformations were detected for patients without parenchymal hyperdensity. Sensitivity and specificity of hyperdense lesions on flat-panel CT for the prediction of haemorrhagic transformation were 94.1% (80.3-99.3%) and 79.3% (60.3-92.0%), respectively. The positive and negative predictive values for the occurrence of haemorrhage were 84.2% (68.8-94.0%) and 92.0% (74.0-99.0%), respectively. For significant parenchymal haemorrhage type 2, sensitivity and negative predictive values were 100%. We observed good homogeneity between the different readers. Hyperdensity on post-procedural flat-panel CT was associated with a tendency for higher risk of death and lower risk of good clinical outcome. Flat-panel CT appears to be a good tool to detect brain parenchymal hyperdensities after mechanical thrombectomy in patients with AIS and to predict haemorrhagic transformation.

The use of a panel code on high lift configurations of a swept forward wing

NASA Technical Reports Server (NTRS)

Scheib, J. S.; Sandlin, D. R.

1985-01-01

A study was done on high lift configurations of a generic swept forward wing using a panel code prediction method. A survey was done of existing codes available at Ames, frow which the program VSAERO was chosen. The results of VSAERO were compared with data obtained from the Ames 7- by 10-foot wind tunnel. The results of the comparison in lift were good (within 3.5%). The comparison of the pressure coefficients was also good. The pitching moment coefficients obtained by VSAERO were not in good agreement with experiment. VSAERO's ability to predict drag is questionable and cannot be counted on for accurate trends. Further studies were done on the effects of a leading edge glove, canards, leading edge sweeps and various wing twists on spanwise loading and trim lift with encouraging results. An unsuccessful attempt was made to model spanwise blowing and boundary layer control on the trailing edge flap. The potential results of VSAERO were compared with experimental data of flap deflections with boundary layer control to check the first order effects.

A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.

Application of SWAT-HS, a lumped hillslope model to simulate hydrology in the Cannonsville Reservoir watershed, New York

NASA Astrophysics Data System (ADS)

Hoang, Linh; Schneiderman, Elliot; Mukundan, Rajith; Moore, Karen; Owens, Emmet; Steenhuis, Tammo

2017-04-01

Surface runoff is the primary mechanism transporting substances such as sediments, agricultural chemicals, and pathogens to receiving waters. In order to predict runoff and pollutant fluxes, and to evaluate management practices, it is essential to accurately predict the areas generating surface runoff, which depend on the type of runoff: infiltration-excess runoff and saturation-excess runoff. The watershed of Cannonsville reservoir is part of the New York City water supply system that provides high quality drinking water to nine million people in New York City (NYC) and nearby communities. Previous research identified saturation-excess runoff as the dominant runoff mechanism in this region. The Soil and Water Assessment Tool (SWAT) is a promising tool to simulate the NYC watershed given its broad application and good performance in many watersheds with different scales worldwide, for its ability to model water quality responses, and to evaluate the effect of management practices on water quality at the watershed scale. However, SWAT predicts runoff based mainly on soil and land use characteristics, and implicitly considers only infiltration-excess runoff. Therefore, we developed a modified version of SWAT, referred to as SWAT-Hillslope (SWAT-HS), which explicitly simulates saturation-excess runoff by redefining Hydrological Response Units (HRUs) based on wetness classes with varying soil water storage capacities, and by introducing a surface aquifer with the ability to route interflow from "drier" to "wetter" wetness classes. SWAT-HS was first tested at Town Brook, a 37 km2 headwater watershed draining to the Cannonsville reservoir using a single sub-basin for the whole watershed. SWAT-HS performed well, and predicted streamflow yielded Nash-Sutcliffe Efficiencies of 0.68 and 0.87 at the daily and monthly time steps, respectively. More importantly, it predicted the spatial distribution of saturated areas accurately. Based on the good performance in the Town Brook watershed, we scale-up the application of SWAT-HS to the 1160 km2 Cannonsville watershed utilizing a setup of multiple sub-basins, and evaluate the model performance on flow simulation at different gauged locations in the watershed. Results from flow predictions will be used as a basis for evaluating the ability of SWAT-HS to make sediment and nutrient loading estimates.

Validation of the Canada Acute Coronary Syndrome Risk Score for Hospital Mortality in the Gulf Registry of Acute Coronary Events-2.

PubMed

AlFaleh, Hussam F; Alsheikh-Ali, Alawi A; Ullah, Anhar; AlHabib, Khalid F; Hersi, Ahmad; Suwaidi, Jassim Al; Sulaiman, Kadhim; Saif, Shukri Al; Almahmeed, Wael; Asaad, Nidal; Amin, Haitham; Al-Motarreb, Ahmed; Kashour, Tarek

2015-09-01

Several risk scores have been developed for acute coronary syndrome (ACS) patients, but their use is limited by their complexity. The new Canada Acute Coronary Syndrome (C-ACS) risk score is a simple risk-assessment tool for ACS patients. This study assessed the performance of the C-ACS risk score in predicting hospital mortality in a contemporary Middle Eastern ACS cohort. The C-ACS score accurately predicts hospital mortality in ACS patients. The baseline risk of 7929 patients from 6 Arab countries who were enrolled in the Gulf RACE-2 registry was assessed using the C-ACS risk score. The score ranged from 0 to 4, with 1 point assigned for the presence of each of the following variables: age ≥75 years, Killip class >1, systolic blood pressure <100 mm Hg, and heart rate >100 bpm. The discriminative ability and calibration of the score were assessed using C statistics and goodness-of-fit tests, respectively. The C-ACS score demonstrated good predictive values for hospital mortality in all ACS patients with a C statistic of 0.77 (95% confidence interval [CI]: 0.74-0.80) and in ST-segment elevation myocardial infarction and non-ST-segment elevation acute coronary syndrome patients (C statistic: 0.76, 95% CI: 0.73-0.79; and C statistic: 0.80, 95% CI: 0.75-0.84, respectively). The discriminative ability of the score was moderate regardless of age category, nationality, and diabetic status. Overall, calibration was optimal in all subgroups. The new C-ACS score performed well in predicting hospital mortality in a contemporary ACS population outside North America. © 2015 Wiley Periodicals, Inc.

Can maintaining cognitive function at 65 years old predict successful ageing 6 years later? The PROOF study.

PubMed

Castro-Lionard, Karine; Thomas-Antérion, Catherine; Crawford-Achour, Emilie; Rouch, Isabelle; Trombert-Paviot, Béatrice; Barthélémy, Jean-Claude; Laurent, Bernard; Roche, Frédéric; Gonthier, Régis

2011-03-01

preservation of cognitive abilities is required to have a good quality of life. The predictive value of cognitive functioning at 65 years old on successful ageing 6 years later is not established. nine hundred and seventy-six questionnaires were sent by mail to a sample of healthy and voluntary French pensioners. Successful ageing was defined through health status and well-being. Cognitive abilities had been assessed 6 years earlier according to an objective method (Free and Cued Selective Recall Reminding Test (FCSRT), the Benton visual retention test and the similarities subtest of the Wechsler Adult Intelligence Scale-Revised) and a subjective one (Goldberg's anxiety scale, Mac Nair's scale and a Visual Analogue Scale to evaluate memory abilities change in the last 5 years). six hundred and eighty-six questionnaires could be analysed. The mean age was 72.9 ± 1.2 years old with 59% of women and 99% lived at home. Well-being was negatively correlated with the FCSRT (r = -0.08, P = 0.0318) but positively related with the Benton (r = 0.09, P = 0.0125) and the similarities tests (r = 0.09, P = 0.0118). There is a negative correlation between anxious and cognitive complaints measured at baseline, and successful ageing indicators 6 years later. preservation of cognitive abilities at the age of retirement can predict a successful ageing 6 years later. ClinicalTrials.gov Identifier: NCT00759304.

Good work ability among unemployed individuals: Association of sociodemographic, work-related and well-being factors.

PubMed

Hult, Marja; Pietilä, Anna-Maija; Koponen, Päivikki; Saaranen, Terhi

2018-05-01

The aims of this study were to describe the perceived work ability of unemployed individuals and to explore the association between perceived good work ability and sociodemographic, work-related and well-being factors. The data were derived from the Finnish Regional Health and Well-being Study (ATH) collected by postal and Internet-based questionnaires in 2014-2015. The random sample was selected from the Finnish National Population Register. The present study includes data from unemployed or laid-off respondents ( n=1975) aged 20-65 years. Logistic regression was used in the statistical analysis. Perceived work ability was measured with the Work Ability Score. Factors significantly associated with good work ability were having young children living in the household, short-term unemployment, low or moderate physical strain in most recent job, moderate mental strain in most recent job, satisfaction with most recent job, good self-rated health and good quality of life. Good self-rated health (odds ratio=10.53, 95% confidence interval 5.90-18.80) was the most substantial factor in the multivariate model. The findings provide further evidence on the factors related to good work ability of the unemployed. These factors should be considered when designing interventions for promoting work ability and to minimise the harmful effects of long-term unemployment.

Estimating the Octanol/Water Partition Coefficient for Aliphatic Organic Compounds Using Semi-Empirical Electrotopological Index

PubMed Central

Souza, Erica Silva; Zaramello, Laize; Kuhnen, Carlos Alberto; Junkes, Berenice da Silva; Yunes, Rosendo Augusto; Heinzen, Vilma Edite Fonseca

2011-01-01

A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (ISET). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-contribution methods, as in the Ghose/Crippen approach and its later refinement, AlogP; using fragmental methods through the ClogP method; and employing an approach considering the whole molecule using topological indices with the MlogP method. The efficiency and the applicability of the ISET in terms of calculating log P were demonstrated through good statistical quality (r > 0.99; s < 0.18), high internal stability and good predictive ability for an external group of compounds in the same order as the widely used models based on the fragmental method, ClogP, and the atomic contribution method, AlogP, which are among the most used methods of predicting log P. PMID:22072945

Estimating the octanol/water partition coefficient for aliphatic organic compounds using semi-empirical electrotopological index.

PubMed

Souza, Erica Silva; Zaramello, Laize; Kuhnen, Carlos Alberto; Junkes, Berenice da Silva; Yunes, Rosendo Augusto; Heinzen, Vilma Edite Fonseca

2011-01-01

A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (I(SET)). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-contribution methods, as in the Ghose/Crippen approach and its later refinement, AlogP; using fragmental methods through the ClogP method; and employing an approach considering the whole molecule using topological indices with the MlogP method. The efficiency and the applicability of the I(SET) in terms of calculating log P were demonstrated through good statistical quality (r > 0.99; s < 0.18), high internal stability and good predictive ability for an external group of compounds in the same order as the widely used models based on the fragmental method, ClogP, and the atomic contribution method, AlogP, which are among the most used methods of predicting log P.

Implementation of algebraic stress models in a general 3-D Navier-Stokes method (PAB3D)

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.

1995-01-01

A three-dimensional multiblock Navier-Stokes code, PAB3D, which was developed for propulsion integration and general aerodynamic analysis, has been used extensively by NASA Langley and other organizations to perform both internal (exhaust) and external flow analysis of complex aircraft configurations. This code was designed to solve the simplified Reynolds Averaged Navier-Stokes equations. A two-equation k-epsilon turbulence model has been used with considerable success, especially for attached flows. Accurate predicting of transonic shock wave location and pressure recovery in separated flow regions has been more difficult. Two algebraic Reynolds stress models (ASM) have been recently implemented in the code that greatly improved the code's ability to predict these difficult flow conditions. Good agreement with Direct Numerical Simulation (DNS) for a subsonic flat plate was achieved with ASM's developed by Shih, Zhu, and Lumley and Gatski and Speziale. Good predictions were also achieved at subsonic and transonic Mach numbers for shock location and trailing edge boattail pressure recovery on a single-engine afterbody/nozzle model.

[Influence of sample surface roughness on mathematical model of NIR quantitative analysis of wood density].

PubMed

Huang, An-Min; Fei, Ben-Hua; Jiang, Ze-Hui; Hse, Chung-Yun

2007-09-01

Near infrared spectroscopy is widely used as a quantitative method, and the main multivariate techniques consist of regression methods used to build prediction models, however, the accuracy of analysis results will be affected by many factors. In the present paper, the influence of different sample roughness on the mathematical model of NIR quantitative analysis of wood density was studied. The result of experiments showed that if the roughness of predicted samples was consistent with that of calibrated samples, the result was good, otherwise the error would be much higher. The roughness-mixed model was more flexible and adaptable to different sample roughness. The prediction ability of the roughness-mixed model was much better than that of the single-roughness model.

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

PubMed

Peñagaricano, F; Urioste, J I; Naya, H; de los Campos, G; Gianola, D

2011-04-01

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep. © 2010 Blackwell Verlag GmbH.

Do the physical and environment PETTLEP elements predict sport imagery ability?

PubMed

Anuar, Nurwina; Williams, Sarah E; Cumming, Jennifer

2017-11-01

The present study aimed to examine whether physical and environment elements of PETTLEP imagery relate to the ability to image five types of sport imagery (i.e. skill, strategy, goal, affect and mastery). Two hundred and ninety participants (152 males, 148 females; M age  = 20.24 years, SD = 4.36) from various sports completed the Sport Imagery Ability Questionnaire (SIAQ), and a set of items designed specifically for the study to assess how frequently participants incorporate physical (e.g. 'I make small movements or gestures during the imagery') and environment (e.g. 'I image in the real training/competition environment') elements of PETTLEP imagery. Structural equation modelling tested a hypothesised model in which imagery priming (i.e. the best fitting physical and environment elements) significantly and positively predicted imagery ability of the different imagery types (skill, β = 0.38; strategy, β = 0.23; goal, β = 0.21; affect, β = 0.25; mastery, β = 0.22). The model was a good fit to the data: χ 2 (174) = 263.87, p < .001, CFI = .96, TLI = .95, SRMR = .09, RMSEA = 0.05 (90% CI = 0.03-0.05). Findings displayed that priming imagery with physical and environment elements is associated with better skill, strategy, goal, affect and mastery imagery ability. The findings extend models of imagery use by indicating that how athletes images may influence their imagery ability.

Coping self-efficacy of Chinese nursing undergraduates with their research projects.

PubMed

Zhang, Wei; Li, Kun; Zhang, XiuMin; Chen, Li

2016-10-01

Undergraduate nursing education includes both professional knowledge and research skills. With regard to training nursing professionals for future healthcare settings, the ability to conduct research is fundamental for nurses after they graduate from universities. However, how nursing students develop coping self-efficacy and scientific skills as a specific ability during their professional study has received little attention. We studied nursing undergraduates' scientific research ability and its associated factors in the Chinese context and evaluated their self-efficacy for coping with research tasks. A total of 134 nursing undergraduates participated in the study. A purposely designed 22-item questionnaire was used to quantify students' research ability in implementing their research projects and the associated factors. Coping self-efficacy was measured with a modified Chinese version. The mean total self-efficacy score was 50.78±6.604 (M±SD). The majority (63.4%) of the students' coping self-efficacy was at a moderate level. Having "the ability to write a manuscript before conducting research projects" (P=0.006) and "topics determined by instructors after discussion with group members" (P=0.005) were the two predictive factors of good coping self-efficacy in students. Nursing undergraduates' self-efficacy was high enough to cope with their scientific research projects, but the information on procedures needed for project application was not abundant, and new training programs might be needed to meet the needs of nursing undergraduates. We should make full use of the predictors of good coping self-efficacy and promote nursing undergraduates' research ability. Copyright © 2016 Elsevier Ltd. All rights reserved.

Establishing a Dynamic Self-Adaptation Learning Algorithm of the BP Neural Network and Its Applications

NASA Astrophysics Data System (ADS)

Li, Xiaofeng; Xiang, Suying; Zhu, Pengfei; Wu, Min

2015-12-01

In order to avoid the inherent deficiencies of the traditional BP neural network, such as slow convergence speed, that easily leading to local minima, poor generalization ability and difficulty in determining the network structure, the dynamic self-adaptive learning algorithm of the BP neural network is put forward to improve the function of the BP neural network. The new algorithm combines the merit of principal component analysis, particle swarm optimization, correlation analysis and self-adaptive model, hence can effectively solve the problems of selecting structural parameters, initial connection weights and thresholds and learning rates of the BP neural network. This new algorithm not only reduces the human intervention, optimizes the topological structures of BP neural networks and improves the network generalization ability, but also accelerates the convergence speed of a network, avoids trapping into local minima, and enhances network adaptation ability and prediction ability. The dynamic self-adaptive learning algorithm of the BP neural network is used to forecast the total retail sale of consumer goods of Sichuan Province, China. Empirical results indicate that the new algorithm is superior to the traditional BP network algorithm in predicting accuracy and time consumption, which shows the feasibility and effectiveness of the new algorithm.

Parenting by persons with intellectual disability: an explorative study in the Netherlands.

PubMed

Willems, D L; de Vries, J-N; Isarin, J; Reinders, J S

2007-07-01

As a sequel to a report by the Health Council of the Netherlands on contraception in persons with intellectual disabilities (IDs), a fierce debate about parenthood by such persons occurred, in which a lack of knowledge about parenting competences became clear. Therefore, the Ministry of Health commissioned a study investigating examples of 'successful parenthood' by persons with IDs. In conformity with the literature and with legal categories, we defined 'successful parenthood' as 'good enough parenthood', meaning no indications for child abuse and/or neglect, no dealings with child protection agencies and no legal custody. We combined a nationwide quantitative questionnaire study with a qualitative interview study. Questionnaires were sent to all institutions involved in caring for persons with ID, interviews were held with 'good enough' parents and their professional caregivers, selected on the basis of returned questionnaires. Parenthood occurs in around 1.5% of persons with ID in the Netherlands and is mostly restricted to those with mild handicaps. In total, 51% of the cases were regarded, by caregivers, as not-good-enough parenthood, 33% were clearly good enough and 16% were doubtful. Predicting factors included the ability and the willingness to follow advice, the quality of the social network and the acceptance of parenting in the community. However, there is not one decisive predicting factor; particularly, the predictive value of the IQ alone is small. A general policy of discouragement of parenthood, as advocated by the Dutch Ministry, is not supported by our results; moreover, it would probably be impossible and have negative effects on social acceptance of parents with ID. The overall conclusion from the study therefore is that some kind of balancing model, in which positive and negative factors are weighed, may be useful to predict success and need for support.

PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.

PubMed

Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H

2016-01-01

We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.

Predictive power of the grace score in population with diabetes.

PubMed

Baeza-Román, Anna; de Miguel-Balsa, Eva; Latour-Pérez, Jaime; Carrillo-López, Andrés

2017-12-01

Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score. The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model. Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement. The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model. The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Vision and night driving abilities of elderly drivers.

PubMed

Gruber, Nicole; Mosimann, Urs P; Müri, René M; Nef, Tobias

2013-01-01

In this article, we review the impact of vision on older people's night driving abilities. Driving is the preferred and primary mode of transport for older people. It is a complex activity where intact vision is seminal for road safety. Night driving requires mesopic rather than scotopic vision, because there is always some light available when driving at night. Scotopic refers to night vision, photopic refers to vision under well-lit conditions, and mesopic vision is a combination of photopic and scotopic vision in low but not quite dark lighting situations. With increasing age, mesopic vision decreases and glare sensitivity increases, even in the absence of ocular diseases. Because of the increasing number of elderly drivers, more drivers are affected by night vision difficulties. Vision tests, which accurately predict night driving ability, are therefore of great interest. We reviewed existing literature on age-related influences on vision and vision tests that correlate or predict night driving ability. We identified several studies that investigated the relationship between vision tests and night driving. These studies found correlations between impaired mesopic vision or increased glare sensitivity and impaired night driving, but no correlation was found among other tests; for example, useful field of view or visual field. The correlation between photopic visual acuity, the most commonly used test when assessing elderly drivers, and night driving ability has not yet been fully clarified. Photopic visual acuity alone is not a good predictor of night driving ability. Mesopic visual acuity and glare sensitivity seem relevant for night driving. Due to the small number of studies evaluating predictors for night driving ability, further research is needed.

Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

PubMed

Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

2016-08-11

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues.

PubMed

Perišić, Ognjen

2018-03-16

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM's weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol's ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner's interacting scaffold is more flexible and adaptable.

A Dynamic Speech Comprehension Test for Assessing Real-World Listening Ability.

PubMed

Best, Virginia; Keidser, Gitte; Freeston, Katrina; Buchholz, Jörg M

2016-07-01

Many listeners with hearing loss report particular difficulties with multitalker communication situations, but these difficulties are not well predicted using current clinical and laboratory assessment tools. The overall aim of this work is to create new speech tests that capture key aspects of multitalker communication situations and ultimately provide better predictions of real-world communication abilities and the effect of hearing aids. A test of ongoing speech comprehension introduced previously was extended to include naturalistic conversations between multiple talkers as targets, and a reverberant background environment containing competing conversations. In this article, we describe the development of this test and present a validation study. Thirty listeners with normal hearing participated in this study. Speech comprehension was measured for one-, two-, and three-talker passages at three different signal-to-noise ratios (SNRs), and working memory ability was measured using the reading span test. Analyses were conducted to examine passage equivalence, learning effects, and test-retest reliability, and to characterize the effects of number of talkers and SNR. Although we observed differences in difficulty across passages, it was possible to group the passages into four equivalent sets. Using this grouping, we achieved good test-retest reliability and observed no significant learning effects. Comprehension performance was sensitive to the SNR but did not decrease as the number of talkers increased. Individual performance showed associations with age and reading span score. This new dynamic speech comprehension test appears to be valid and suitable for experimental purposes. Further work will explore its utility as a tool for predicting real-world communication ability and hearing aid benefit. American Academy of Audiology.

Prediction of mortality rates using a model with stochastic parameters

NASA Astrophysics Data System (ADS)

Tan, Chon Sern; Pooi, Ah Hin

2016-10-01

Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been applied on mortality data from the United States for the years 1933 till 2000 to forecast the future mortality rates for the years 2001 till 2010. In this paper, a more dynamic approach based on the multivariate time series will be proposed where the model uses stochastic parameters that vary with time. The resulting prediction intervals obtained using the model with stochastic parameters perform better because apart from having good ability in covering the observed future mortality rates, they also tend to have distinctly shorter interval lengths.

Which employment interview skills best predict the employability of schizophrenic patients?

PubMed

Charisiou, J; Jackson, H J; Boyle, G J; Burgess, P M; Minas, I H; Joshua, S D

1989-06-01

To examine the effects of verbal and nonverbal interview microbehaviors and interview characteristics on employability, Simulated Employment Interviews were conducted with 46 psychiatric inpatients who each met the DSM-III criteria for a diagnosis of schizophrenia. Each interview was videotaped and shown to two raters, who generated independent ratings for six microbehaviors (eye-contact, facial gestures, body posture, verbal content, voice volume, and length of speech) and six subject characteristics (motivation, self-confidence, ability to communicate, manifest adjustment, manifest intelligence and overall interview skill). A panel of three Commonwealth Employment Service psychologists viewed the same videotaped interviews and generated employability ratings. Verbal and nonverbal microbehaviors were relatively independent while subject characteristics were highly interdependent. Microbehaviors and characteristics correlated at a high level. Of the 12 interview microbehaviors and characteristics, manifest adjustment and ability to communicate accounted for 64% of the total variance in predicting employability. Interviewees who were perceived as behaving in an adjusted manner and as being good communicators were rated as more employable.

Development and Psychometric Properties of the Standardized Assessment of Severity of Personality Disorder (SASPD).

PubMed

Olajide, Kike; Munjiza, Jasna; Moran, Paul; O'Connell, Lesley; Newton-Howes, Giles; Bassett, Paul; Akintomide, Gbolagade; Ng, Nicola; Tyrer, Peter; Mulder, Roger; Crawford, Mike J

2018-02-01

Personality disorder (PD) is increasingly categorized according to its severity, but there is no simple way to screen for severity according to ICD-11 criteria. We set out to develop the Standardized Assessment of Severity of Personality Disorder (SASPD). A total of 110 patients completed the SASPD together with a clinical assessment of the severity of personality disorder. We examined the predictive ability of the SASPD using the area under the ROC curve (AUC). Two to four weeks later, 43 patients repeated the SASPD to examine reliability. The SASPD had good predictive ability for determining mild (AUC = 0.86) and moderate (AUC = 0.84) PD at cut points of 8 and 10, respectively. Test-retest reliability of the SASPD was high (intraclass correlation coefficient = 0.93, 95% CI [0.88, 0.96]). The SASPD thus provides a simple, brief, and reliable indicator of the presence of mild or moderate PD according to ICD-11 criteria.

Computer-aided design, synthesis and biological assay of p-methylsulfonamido phenylethylamine analogues.

PubMed

Liu, H; Ji, M; Jiang, H; Liu, L; Hua, W; Chen, K; Ji, R

2000-10-02

Class III antiarrhythmic agents selectively delay the effective refractory period (ERP) and increase the transmembrance action potential duration (APD). Based on our previous studies, a set of 17 methylsulfonamido phenylethylamine analogues were investigated by 3D-QSAR techniques of CoMFA and CoMSIA. The 3D-QSAR models proved a good predictive ability, and could describe the steric, electrostatic and hydrophobic requirements for recognition forces of the receptor site. According to the clues provided by this 3D-QSAR analysis, we designed and synthesized a series of new analogues of methanesulfonamido phenylethylamine (VIa-i). Pharmacological assay indicated that the effective concentrations of delaying the functional refractory period (FRP) 10ms of these new compounds have a good correlation with the 3D-QSAR predicted values. It is remarkable that the maximal percent change of delaying FRP in microM of compound VIc is much higher than that of dofetilide. The results showed that the 3D-QSAR models are reliable.

Thermogravimetric analysis for rapid assessment of moisture diffusivity in polydisperse powder and thin film matrices.

PubMed

Thirunathan, Praveena; Arnz, Patrik; Husny, Joeska; Gianfrancesco, Alessandro; Perdana, Jimmy

2018-03-01

Accurate description of moisture diffusivity is key to precisely understand and predict moisture transfer behaviour in a matrix. Unfortunately, measuring moisture diffusivity is not trivial, especially at low moisture values and/or elevated temperatures. This paper presents a novel experimental procedure to accurately measure moisture diffusivity based on thermogravimetric approach. The procedure is capable to measure diffusivity even at elevated temperatures (>70°C) and low moisture values (>1%). Diffusivity was extracted from experimental data based on "regular regime approach". The approach was tailored to determine diffusivity from thin film and from poly-dispersed powdered samples. Subsequently, measured diffusivity was validated by comparing to available literature data, showing good agreement. Ability of this approach to accurately measure diffusivity at a wider range of temperatures provides better insight on temperature dependency of diffusivity. Thus, this approach can be crucial to ensure good accuracy of moisture transfer description/prediction especially when involving elevated temperatures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Construct validity of tests that measure kick performance for young soccer players based on cluster analysis: exploring the relationship between coaches rating and actual measures.

PubMed

Palucci Vieira, Luiz H; de Andrade, Vitor L; Aquino, Rodrigo L; Moraes, Renato; Barbieri, Fabio A; Cunha, Sérgio A; Bedo, Bruno L; Santiago, Paulo R

2017-12-01

The main aim of this study was to verify the relationship between the classification of coaches and actual performance in field tests that measure the kicking performance in young soccer players, using the K-means clustering technique. Twenty-three U-14 players performed 8 tests to measure their kicking performance. Four experienced coaches provided a rating for each player as follows: 1: poor; 2: below average; 3: average; 4: very good; 5: excellent as related to three parameters (i.e. accuracy, power and ability to put spin on the ball). The scores interval established from k-means cluster metric was useful to originating five groups of performance level, since ANOVA revealed significant differences between clusters generated (P<0.01). Accuracy seems to be moderately predicted by the penalty kick, free kick, kicking the ball rolling and Wall Volley Test (0.44≤r≤0.56), while the ability to put spin on the ball can be measured by the free kick and the corner kick tests (0.52≤r≤0.61). Body measurements, age and PHV did not systematically influence the performance. The Wall Volley Test seems to be a good predictor of other tests. Five tests showed reasonable construct validity and can be used to predict the accuracy (penalty kick, free kick, kicking a rolling ball and Wall Volley Test) and ability to put spin on the ball (free kick and corner kick tests) when kicking in soccer. In contrast, the goal kick, kicking the ball when airborne and the vertical kick tests exhibited low power of discrimination and using them should be viewed with caution.

Experimental verification of a progressive damage model for composite laminates based on continuum damage mechanics. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Coats, Timothy William

1994-01-01

Progressive failure is a crucial concern when using laminated composites in structural design. Therefore the ability to model damage and predict the life of laminated composites is vital. The purpose of this research was to experimentally verify the application of the continuum damage model, a progressive failure theory utilizing continuum damage mechanics, to a toughened material system. Damage due to tension-tension fatigue was documented for the IM7/5260 composite laminates. Crack density and delamination surface area were used to calculate matrix cracking and delamination internal state variables, respectively, to predict stiffness loss. A damage dependent finite element code qualitatively predicted trends in transverse matrix cracking, axial splits and local stress-strain distributions for notched quasi-isotropic laminates. The predictions were similar to the experimental data and it was concluded that the continuum damage model provided a good prediction of stiffness loss while qualitatively predicting damage growth in notched laminates.

Comparison of calculated and measured velocities near the tip of a model rotor blade at transonic speeds

NASA Technical Reports Server (NTRS)

Tauber, M. E.; Owen, F. K.; Langhi, R. G.; Palmer, G. E.

1985-01-01

The ability of the ROT22 code to predict accurately the transonic flow field in the crucial region around and beyond the tip of a high speed rotor blade was assessed. The computations were compared with extensive laser velocimetry measurements made at zero advance ratio and tip Mach numbers of 0.85, 0.88, 0.90, and 0.95. The comparison between theory and experiment was made using 300 scans for the three orthogonal velocity components covering a volume having a height of over one blade chord, a width of nearly two chords, and a length ranging from about 1 to 1.6 chords, depending on the tip speeds. The good agreement between the calculated and measured velocities established the ability of the code to predict the off blade flow field at high tip speeds. This supplements previous comparisons where surface pressures were shown to be well predicted on two different tips at advance ratios to 0.45, especially at the critical 90 deg azimuth blade position. These results demonstrate that the ROT22 code can be used with confidence to predict the important tip region flow field including the occurrence, strength, and location of shock waves causing high drag and noise.

Development of a prognostic scale for severely hemiplegic stroke patients in a rehabilitation hospital.

PubMed

Hirano, Yoshitake; Nitta, Osamu; Hayashi, Takeshi; Takahashi, Hidetoshi; Miyazaki, Yasuhiro; Kigawa, Hiroshi

2017-07-01

For patients with severe hemiplegia in a rehabilitation hospital, early prediction of the functional prognosis and outcomes is challenging. The purpose of this study was to create and verify a prognostic scale in severely hemiplegic stroke patients and allowing for prediction of (1) the ability to walk at the time of hospital discharge, (2) the ability to carry out activities of daily living (ADL), and (3) feasibility of home discharge. The study was conducted on 80 severely hemiplegic stroke patients. A prognostic scale was created as an analysis method using the following items: mini-mental state examination (MMSE) at the time of admission, modified NIH stroke scale (m-NIHSS); trunk control test (TCT); and the ratio of the knee extensor strength on the non-paralyzed side to the body weight (KES/BW-US). We verified the reliability and validity of this scale. We established a prognostic scale using the MMSE, m-NIHSS, TCT, and KES/BW-US. A score of 56.8 or higher on the prognostic scale suggested that the patient would be able to walk and that assistance with ADL would be unnecessary at the time of hospital discharge. In addition, a score of 41.3 points indicated that the patient's return home was feasible. The reliability and the results were in good agreement. These findings showed that the ability or inability to walk was predictable in 85%, the need of assistance with ADL in 82.5%, and the feasibility of home return in 76.3% of cases. At the time of admission, four evaluation items permitted the prediction of three outcomes at time of discharge. Our formula predicts three outcomes with an accuracy of more than 76%. Copyright © 2017 Elsevier B.V. All rights reserved.

Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

PubMed

Ingo, Elisabeth; Brännström, K Jonas; Andersson, Gerhard; Lunner, Thomas; Laplante-Lévesque, Ariane

2016-07-01

Acceptance and readiness to seek professional help have shown to be important factors for favourable audiological rehabilitation outcomes. Theories from health psychology such as the transtheoretical (stages-of-change) model could help understand behavioural change in people with hearing impairment. In recent studies, the University of Rhode Island change assessment (URICA) has been found to have good predictive validity. In a previous study, 224 Swedish adults who had failed an online hearing screening completed URICA and two other measures of stages of change. This follow-up aimed to: (1) determine prevalence of help-seeking at a hearing clinic and hearing aid uptake, and (2) explore the predictive validity of the stages of change measures by a follow-up on the 224 participants who had failed a hearing screening 18 months previously. A total of 122 people (54%) completed the follow-up online questionnaire, including the three measures and questions regarding experience with hearing help-seeking and hearing aid uptake. Since failing the online hearing screening, 61% of participants had sought help. A good predictive validity for a one-item measure of stages of change was reported. The Staging algorithm was the stages of change measure with the best ability to predict help-seeking 18 months later.

Serum HBV RNA as a Predictor of Peginterferon Alfa-2a (40KD) Response in Patients With HBeAg-Positive Chronic Hepatitis B.

PubMed

van Bömmel, Florian; van Bömmel, Alena; Krauel, Alexander; Wat, Cynthia; Pavlovic, Vedran; Yang, Lei; Deichsel, Danilo; Berg, Thomas; Böhm, Stephan

2018-05-08

Hepatitis B virus (HBV) RNA is a novel serum biomarker that has the potential to predict treatment response in patients with chronic hepatitis B. We explored whether HBV RNA serum levels can predict hepatitis B e antigen (HBeAg) seroconversion in patients treated with peginterferon alfa-2a. Serum samples from HBeAg-positive patients previously treated with peginterferon alfa-2a in two large randomized controlled trials were retrospectively analyzed. HBV RNA levels were measured using a real-time polymerase chain reaction assay. Ability of individual biomarkers to predict HBeAg seroconversion at 24 weeks post-treatment was evaluated using receiver operating characteristics (ROC) analyses. The study included 131 subjects (70% male, 96% Asians, 35% HBV genotypes B and 61% C), 76 treated with peginterferon alfa-2a alone and 55 in combination with LAM. Median HBV RNA levels were significantly lower, at all time points, in patients achieving HBeAg seroconversion. Levels of HBV RNA at treatment weeks 12 and 24 showed good ability to predict HBeAg seroconversion (AUROC scores >0.75, p<0.001). A HBV RNA cutoff of >5.5 log10 copies/mL identified 30% of non-responders at week 12 (negative predictive value >90%). Serum HBV RNA is an early predictor of HBeAg seroconversion in patients treated with peginterferon alfa-2a.

Adaptive Neuro-Fuzzy Determination of the Effect of Experimental Parameters on Vehicle Agent Speed Relative to Vehicle Intruder.

PubMed

Shamshirband, Shahaboddin; Banjanovic-Mehmedovic, Lejla; Bosankic, Ivan; Kasapovic, Suad; Abdul Wahab, Ainuddin Wahid Bin

2016-01-01

Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.

Risk and protective factors as predictors of outcome in adolescents with psychiatric disorder and aggression.

PubMed

Vance, J Eric; Bowen, Natasha K; Fernandez, Gustavo; Thompson, Shealy

2002-01-01

To identify predictors of behavioral outcomes in high-risk adolescents with aggression and serious emotional disturbance (SED). Three hundred thirty-seven adolescents from a statewide North Carolina treatment program for aggressive youths with SED were followed between July 1995 and June 1999 from program entry (T1) to approximately 1 year later (T2). Historical and current psychosocial risk and protective factors as well as psychiatric symptom severity at T1 were tested as predictors of high and low behavioral functioning at T2. Behavioral functioning was a composite based on the frequency of risk-taking, self-injurious, threatening, and assaultive behavior. Eleven risk and protective factors were predictive of T2 behavioral functioning, while none of the measured T1 psychiatric symptoms was predictive. A history of aggression and negative parent-child relationships in childhood was predictive of worse T2 behavior, as was lower IQ. Better T2 behavioral outcomes were predicted by a history of consistent parental employment and positive parent-child relations, higher levels of current family support, contact with prosocial peers, higher reading level, good problem-solving abilities, and superior interpersonal skills. Among high-risk adolescents with aggression and SED, psychiatric symptom severity may be a less important predictor of behavioral outcomes than certain risk and protective factors. Several factors predictive of good behavioral functioning represent feasible intervention targets.

Comparing Pre- and Post-Operative Fontan Hemodynamic Simulations: Implications for the Reliability of Surgical Planning

PubMed Central

Haggerty, Christopher M.; de Zélicourt, Diane A.; Restrepo, Maria; Rossignac, Jarek; Spray, Thomas L.; Kanter, Kirk R.; Fogel, Mark A.; Yoganathan, Ajit P.

2012-01-01

Background Virtual modeling of cardiothoracic surgery is a new paradigm that allows for systematic exploration of various operative strategies and uses engineering principles to predict the optimal patient-specific plan. This study investigates the predictive accuracy of such methods for the surgical palliation of single ventricle heart defects. Methods Computational fluid dynamics (CFD)-based surgical planning was used to model the Fontan procedure for four patients prior to surgery. The objective for each was to identify the operative strategy that best distributed hepatic blood flow to the pulmonary arteries. Post-operative magnetic resonance data were acquired to compare (via CFD) the post-operative hemodynamics with predictions. Results Despite variations in physiologic boundary conditions (e.g., cardiac output, venous flows) and the exact geometry of the surgical baffle, sufficient agreement was observed with respect to hepatic flow distribution (90% confidence interval-14 ± 4.3% difference). There was also good agreement of flow-normalized energetic efficiency predictions (19 ± 4.8% error). Conclusions The hemodynamic outcomes of prospective patient-specific surgical planning of the Fontan procedure are described for the first time with good quantitative comparisons between preoperatively predicted and postoperative simulations. These results demonstrate that surgical planning can be a useful tool for single ventricle cardiothoracic surgery with the ability to deliver significant clinical impact. PMID:22777126

What is the Ability Emotional Intelligence Test (MSCEIT) good for? An evaluation using item response theory.

PubMed

Fiori, Marina; Antonietti, Jean-Philippe; Mikolajczak, Moira; Luminet, Olivier; Hansenne, Michel; Rossier, Jérôme

2014-01-01

The ability approach has been indicated as promising for advancing research in emotional intelligence (EI). However, there is scarcity of tests measuring EI as a form of intelligence. The Mayer Salovey Caruso Emotional Intelligence Test, or MSCEIT, is among the few available and the most widespread measure of EI as an ability. This implies that conclusions about the value of EI as a meaningful construct and about its utility in predicting various outcomes mainly rely on the properties of this test. We tested whether individuals who have the highest probability of choosing the most correct response on any item of the test are also those who have the strongest EI ability. Results showed that this is not the case for most items: The answer indicated by experts as the most correct in several cases was not associated with the highest ability; furthermore, items appeared too easy to challenge individuals high in EI. Overall results suggest that the MSCEIT is best suited to discriminate persons at the low end of the trait. Results are discussed in light of applied and theoretical considerations.

Clinical utility of urine neutrophil gelatinase-associated lipocalin measured at admission to predict outcomes in heterogeneous population of critically ill patients.

PubMed

Nayak, N M; Madhumitha, S; Annigeri, R A; Venkataraman, R; Balasubramaian, S; Seshadri, R; Vadamalai, V; Rao, B S; Kowdle, P C; Ramakrishnan, N; Mani, M K

2016-01-01

Urine neutrophil gelatinase-associated lipocalin (uNGAL) is a reliable early biomarker of acute kidney injury (AKI) in a homogeneous patient population. However, its utility in a heterogeneous population of critically ill, in whom the time of onset of renal insult is often unclear, is not clearly established. We evaluated the ability of a single measurement of uNGAL in a heterogeneous adult population, on admission to intensive care unit (ICU), to predict the occurrence of AKI and hospital mortality. One hundred and two consecutive adult patients had uNGAL measured within 8 h of admission to ICU. The demographic and laboratory data were collected at admission. The diagnosis of AKI was based on AKI Network (AKIN) criteria. The primary outcome was the development of AKI, and the secondary outcome was hospital mortality. The mean age was 54 ± 16.4 years and 65% were males. Urine NGAL (ng/ml) was 69 ± 42 in patients with AKI (n = 42) and 30.4 ± 41.7 in those without AKI (P < 0.001). The area under the receiver operating characteristic (ROC) curve for prediction of AKI was 0.79 and for serum creatinine (SCr) was 0.88. The sensitivity and specificity for a cut-off value of uNGAL of 75 ng/ml to predict AKI were 0.5 and 0.85 respectively. uNGAL > 75 ng/ml was a strong (odd ratio = 5.17, 95% confidence interval: 1.39-19.3) and independent predictor of hospital mortality. A single measurement of uNGAL at admission to ICU exhibited good predictive ability for AKI though the sensitivity was low. The predictive ability of uNGAL was inferior to simultaneously measured SCr at admission, hence limited its clinical utility to predict AKI. However, admission uNGAL was a strong, independent predictor of hospital mortality.

Clinical utility of urine neutrophil gelatinase-associated lipocalin measured at admission to predict outcomes in heterogeneous population of critically ill patients

PubMed Central

Nayak, N. M.; Madhumitha, S.; Annigeri, R. A.; Venkataraman, R.; Balasubramaian, S.; Seshadri, R.; Vadamalai, V.; Rao, B. S.; Kowdle, P. C.; Ramakrishnan, N.; Mani, M. K.

2016-01-01

Urine neutrophil gelatinase-associated lipocalin (uNGAL) is a reliable early biomarker of acute kidney injury (AKI) in a homogeneous patient population. However, its utility in a heterogeneous population of critically ill, in whom the time of onset of renal insult is often unclear, is not clearly established. We evaluated the ability of a single measurement of uNGAL in a heterogeneous adult population, on admission to intensive care unit (ICU), to predict the occurrence of AKI and hospital mortality. One hundred and two consecutive adult patients had uNGAL measured within 8 h of admission to ICU. The demographic and laboratory data were collected at admission. The diagnosis of AKI was based on AKI Network (AKIN) criteria. The primary outcome was the development of AKI, and the secondary outcome was hospital mortality. The mean age was 54 ± 16.4 years and 65% were males. Urine NGAL (ng/ml) was 69 ± 42 in patients with AKI (n = 42) and 30.4 ± 41.7 in those without AKI (P < 0.001). The area under the receiver operating characteristic (ROC) curve for prediction of AKI was 0.79 and for serum creatinine (SCr) was 0.88. The sensitivity and specificity for a cut-off value of uNGAL of 75 ng/ml to predict AKI were 0.5 and 0.85 respectively. uNGAL > 75 ng/ml was a strong (odd ratio = 5.17, 95% confidence interval: 1.39–19.3) and independent predictor of hospital mortality. A single measurement of uNGAL at admission to ICU exhibited good predictive ability for AKI though the sensitivity was low. The predictive ability of uNGAL was inferior to simultaneously measured SCr at admission, hence limited its clinical utility to predict AKI. However, admission uNGAL was a strong, independent predictor of hospital mortality. PMID:27051136

Self-Assessed Kyphosis and Chewing Disorders Predict Disability and Mortality in Community-Dwelling Older Adults.

PubMed

Okura, Mika; Ogita, Mihoko; Yamamoto, Miki; Nakai, Toshimi; Numata, Tomoko; Arai, Hidenori

2017-06-01

It is clear that each trend of kyphosis with increased age and the ability to eat firm foods with the back teeth (chewing ability) has a strong influence on both the physical and mental condition of older people. Thus, this study aimed to examine whether the combination of kyphosis and chewing disorders was associated with mortality or the need for care under the new long-term care insurance (LTCI) service requirement, over 3 years in community-dwelling older Japanese adults. A prospective cohort study. We analyzed the cohort data for older adults (65 years or older) from a prospective study in Kami town. The response rate was 94.3%, and we followed 5094 older individuals for 3 years. Thus, we analyzed 5083 older adults using multiple imputation to manage missing data. The outcomes were mortality or new certifications for LTCI services in a 3-year period. We developed 3 groups by asking 2 self-reported questions on both "no kyphosis" and "good chewing ability." The groups were no kyphosis and good chewing ability (GG), kyphosis and poor chewing ability (BB), and kyphosis and good chewing ability or no kyphosis and poor chewing ability (GB/BG). The prevalence of BB, BG/GB, and GG were 8.9%, 40.3%, and 50.8%, respectively, in our survey. During the 3-year follow-up period, 5.2% (n = 262) died and 13.9% (n = 708) individuals were newly certified as needing LTCI services. As determined by multivariate analyses, BG/GB older adults (adjusted hazard ratio: 1.3 [95% CI 1.1-1.6]) and BB older adults (adjusted hazard ratio: 2.0 [95% CI 1.5-2.4]) had a significantly higher risk of needing LTCI services than GG older adults. Similarly, BG/GB older adults (adjusted hazard ratio: 1.5 [95% CI 1.1-2.0]) and BB older adults (adjusted hazard ratio: 2.3 [95% CI 1.5-3.3]) had a significantly higher risk of mortality than GG older adults did. The presence of kyphosis or poor chewing ability was related to mortality and new certifications for LTCI services, and we found an additive effect of these 2 factors related to frailty. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory

PubMed Central

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities. PMID:28082941

A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory.

PubMed

Asakura, Nobuhiko; Inui, Toshio

2016-01-01

Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities.

Prediction models for clustered data: comparison of a random intercept and standard regression model

PubMed Central

2013-01-01

Background When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Methods Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. Results The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. Conclusion The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters. PMID:23414436

Prediction models for clustered data: comparison of a random intercept and standard regression model.

PubMed

Bouwmeester, Walter; Twisk, Jos W R; Kappen, Teus H; van Klei, Wilton A; Moons, Karel G M; Vergouwe, Yvonne

2013-02-15

When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters.

Work-related stress, education and work ability among hospital nurses.

PubMed

Golubic, Rajna; Milosevic, Milan; Knezevic, Bojana; Mustajbegovic, Jadranka

2009-10-01

This paper is a report of a study conducted to determine which occupational stressors are present in nurses' working environment; to describe and compare occupational stress between two educational groups of nurses; to estimate which stressors and to what extent predict nurses' work ability; and to determine if educational level predicts nurses' work ability. Nurses' occupational stress adversely affects their health and nursing quality. Higher educational level has been shown to have positive effects on the preservation of good work ability. A cross-sectional study was conducted in 2006-2007. Questionnaires were distributed to a convenience sample of 1392 (59%) nurses employed at four university hospitals in Croatia (n = 2364). The response rate was 78% (n = 1086). Data were collected using the Occupational Stress Assessment Questionnaire and Work Ability Index Questionnaire. We identified six major groups of occupational stressors: 'Organization of work and financial issues', 'public criticism', 'hazards at workplace', 'interpersonal conflicts at workplace', 'shift work' and 'professional and intellectual demands'. Nurses with secondary school qualifications perceived Hazards at workplace and Shift work as statistically significantly more stressful than nurses a with college degree. Predictors statistically significantly related with low work ability were: Organization of work and financial issues (odds ratio = 1.69, 95% confidence interval 122-236), lower educational level (odds ratio = 1.69, 95% confidence interval 122-236) and older age (odds ratio = 1.07, 95% confidence interval 1.05-1.09). Hospital managers should develop strategies to address and improve the quality of working conditions for nurses in Croatian hospitals. Providing educational and career prospects can contribute to decreasing nurses' occupational stress levels, thus maintaining their work ability.

Relapse Risk Assessment for Schizophrenia Patients (RASP): A New Self-Report Screening Tool.

PubMed

Velligan, Dawn; Carpenter, William; Waters, Heidi C; Gerlanc, Nicole M; Legacy, Susan N; Ruetsch, Charles

2018-01-01

The Relapse Assessment for Schizophrenia Patients (RASP) was developed as a six-question self-report screener that measures indicators of Increased Anxiety and Social Isolation to assess patient stability and predict imminent relapse. This paper describes the development and psychometric characteristics of the RASP. The RASP and Positive and Negative Syndrome Scale (PANSS) were administered to patients with schizophrenia (n=166) three separate times. Chart data were collected on a subsample of patients (n=81). Psychometric analyses of RASP included tests of reliability, construct validity, and concurrent validity of items. Factors from RASP were correlated with subscales from PANSS (sensitivity to change and criterion validity [agreement between RASP and evidence of relapse]). Test-retest reliability returned modest to strong agreement at the item level and strong agreement at the questionnaire level. RASP showed good item response curves and internal consistency for the total instrument and within each of the two subscales (Increased Anxiety and Social Isolation). RASP Total Score and subscales showed good concurrent validity when correlated with PANSS Total Score, Positive, Excitement, and Anxiety subscales. RASP correctly predicted relapse in 67% of cases, with good specificity and negative predictive power and acceptable positive predictive power and sensitivity. The reliability and validity data presented support the use of RASP in settings where addition of a brief self-report assessment of relapse risk among patients with schizophrenia may be of benefit. Ease of use and scoring, and the ability to administer without clinical supervision allows for routine administration and assessment of relapse risk.

Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water.

PubMed

Ding, H; Chen, C; Zhang, X

2016-01-01

The linear solvation energy relationship (LSER) was applied to predict the adsorption coefficient (K) of synthetic organic compounds (SOCs) on single-walled carbon nanotubes (SWCNTs). A total of 40 log K values were used to develop and validate the LSER model. The adsorption data for 34 SOCs were collected from 13 published articles and the other six were obtained in our experiment. The optimal model composed of four descriptors was developed by a stepwise multiple linear regression (MLR) method. The adjusted r(2) (r(2)adj) and root mean square error (RMSE) were 0.84 and 0.49, respectively, indicating good fitness. The leave-one-out cross-validation Q(2) ([Formula: see text]) was 0.79, suggesting the robustness of the model was satisfactory. The external Q(2) ([Formula: see text]) and RMSE (RMSEext) were 0.72 and 0.50, respectively, showing the model's strong predictive ability. Hydrogen bond donating interaction (bB) and cavity formation and dispersion interactions (vV) stood out as the two most influential factors controlling the adsorption of SOCs onto SWCNTs. The equilibrium concentration would affect the fitness and predictive ability of the model, while the coefficients varied slightly.

Validation of the CRASH model in the prediction of 18-month mortality and unfavorable outcome in severe traumatic brain injury requiring decompressive craniectomy.

PubMed

Honeybul, Stephen; Ho, Kwok M; Lind, Christopher R P; Gillett, Grant R

2014-05-01

The goal in this study was to assess the validity of the corticosteroid randomization after significant head injury (CRASH) collaborators prediction model in predicting mortality and unfavorable outcome at 18 months in patients with severe traumatic brain injury (TBI) requiring decompressive craniectomy. In addition, the authors aimed to assess whether this model was well calibrated in predicting outcome across a wide spectrum of severity of TBI requiring decompressive craniectomy. This prospective observational cohort study included all patients who underwent a decompressive craniectomy following severe TBI at the two major trauma hospitals in Western Australia between 2004 and 2012 and for whom 18-month follow-up data were available. Clinical and radiological data on initial presentation were entered into the Web-based model and the predicted outcome was compared with the observed outcome. In validating the CRASH model, the authors used area under the receiver operating characteristic curve to assess the ability of the CRASH model to differentiate between favorable and unfavorable outcomes. The ability of the CRASH 6-month unfavorable prediction model to differentiate between unfavorable and favorable outcomes at 18 months after decompressive craniectomy was good (area under the receiver operating characteristic curve 0.85, 95% CI 0.80-0.90). However, the model's calibration was not perfect. The slope and the intercept of the calibration curve were 1.66 (SE 0.21) and -1.11 (SE 0.14), respectively, suggesting that the predicted risks of unfavorable outcomes were not sufficiently extreme or different across different risk strata and were systematically too high (or overly pessimistic), respectively. The CRASH collaborators prediction model can be used as a surrogate index of injury severity to stratify patients according to injury severity. However, clinical decisions should not be based solely on the predicted risks derived from the model, because the number of patients in each predicted risk stratum was still relatively small and hence the results were relatively imprecise. Notwithstanding these limitations, the model may add to a clinician's ability to have better-informed conversations with colleagues and patients' relatives about prognosis.

The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model.

PubMed

Klemans, Rob J B; Otte, Dianne; Knol, Mirjam; Knol, Edward F; Meijer, Yolanda; Gmelig-Meyling, Frits H J; Bruijnzeel-Koomen, Carla A F M; Knulst, André C; Pasmans, Suzanne G M A

2013-01-01

A diagnostic prediction model for peanut allergy in children was recently published, using 6 predictors: sex, age, history, skin prick test, peanut specific immunoglobulin E (sIgE), and total IgE minus peanut sIgE. To validate this model and update it by adding allergic rhinitis, atopic dermatitis, and sIgE to peanut components Ara h 1, 2, 3, and 8 as candidate predictors. To develop a new model based only on sIgE to peanut components. Validation was performed by testing discrimination (diagnostic value) with an area under the receiver operating characteristic curve and calibration (agreement between predicted and observed frequencies of peanut allergy) with the Hosmer-Lemeshow test and a calibration plot. The performance of the (updated) models was similarly analyzed. Validation of the model in 100 patients showed good discrimination (88%) but poor calibration (P < .001). In the updating process, age, history, and additional candidate predictors did not significantly increase discrimination, being 94%, and leaving only 4 predictors of the original model: sex, skin prick test, peanut sIgE, and total IgE minus sIgE. When building a model with sIgE to peanut components, Ara h 2 was the only predictor, with a discriminative ability of 90%. Cutoff values with 100% positive and negative predictive values could be calculated for both the updated model and sIgE to Ara h 2. In this way, the outcome of the food challenge could be predicted with 100% accuracy in 59% (updated model) and 50% (Ara h 2) of the patients. Discrimination of the validated model was good; however, calibration was poor. The discriminative ability of Ara h 2 was almost comparable to that of the updated model, containing 4 predictors. With both models, the need for peanut challenges could be reduced by at least 50%. Copyright © 2012 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field.

PubMed

Krupa, Paweł; Mozolewska, Magdalena A; Joo, Keehyoung; Lee, Jooyoung; Czaplewski, Cezary; Liwo, Adam

2015-06-22

A new approach to the prediction of protein structures that uses distance and backbone virtual-bond dihedral angle restraints derived from template-based models and simulations with the united residue (UNRES) force field is proposed. The approach combines the accuracy and reliability of template-based methods for the segments of the target sequence with high similarity to those having known structures with the ability of UNRES to pack the domains correctly. Multiplexed replica-exchange molecular dynamics with restraints derived from template-based models of a given target, in which each restraint is weighted according to the accuracy of the prediction of the corresponding section of the molecule, is used to search the conformational space, and the weighted histogram analysis method and cluster analysis are applied to determine the families of the most probable conformations, from which candidate predictions are selected. To test the capability of the method to recover template-based models from restraints, five single-domain proteins with structures that have been well-predicted by template-based methods were used; it was found that the resulting structures were of the same quality as the best of the original models. To assess whether the new approach can improve template-based predictions with incorrectly predicted domain packing, four such targets were selected from the CASP10 targets; for three of them the new approach resulted in significantly better predictions compared with the original template-based models. The new approach can be used to predict the structures of proteins for which good templates can be found for sections of the sequence or an overall good template can be found for the entire sequence but the prediction quality is remarkably weaker in putative domain-linker regions.

Performance of Several Density Functional Theory Methods on Describing Hydrogen-Bond Interactions.

PubMed

Rao, Li; Ke, Hongwei; Fu, Gang; Xu, Xin; Yan, Yijing

2009-01-13

We have investigated eleven density functionals, including LDA, PBE, mPWPW91, TPSS, B3LYP, X3LYP, PBE0, O3LYP, B97-1, MPW1K, and TPSSh, for their performances on describing hydrogen bond (HB) interactions. The emphasis has been laid not only on their abilities to calculate the intermolecular hydrogen bonding energies but also on their performances in predicting the relative energies of intermolecular H-bonded complexes and the conformer stabilities due to intramolecular hydrogen bondings. As compared to the best theoretical values, we found that although PBE and PBE0 gave the best estimation of HB strengths, they might fail to predict the correct order of relative HB energies, which might lead to a wrong prediction of the global minimum for different conformers. TPSS and TPSSh did not always improve over PBE and PBE0. B3LYP was found to underestimate the intermolecular HB strengths but was among the best performers in calculating the relative HB energies. We showed here that X3LYP and B97-1 were able to give good values for both absolute HB strengths and relative HB energies, making these functionals good candidates for HB description.

Porous Molecular Solids and Liquids

PubMed Central

2017-01-01

Until recently, porous molecular solids were isolated curiosities with properties that were eclipsed by porous frameworks, such as metal–organic frameworks. Now molecules have emerged as a functional materials platform that can have high levels of porosity, good chemical stability, and, uniquely, solution processability. The lack of intermolecular bonding in these materials has also led to new, counterintuitive states of matter, such as porous liquids. Our ability to design these materials has improved significantly due to advances in computational prediction methods. PMID:28691065

A Preliminary Study of the Ability of the 4Kscore test, the Prostate Cancer Prevention Trial-Risk Calculator and the European Research Screening Prostate-Risk Calculator for Predicting High-Grade Prostate Cancer.

PubMed

Borque-Fernando, Á; Esteban-Escaño, L M; Rubio-Briones, J; Lou-Mercadé, A C; García-Ruiz, R; Tejero-Sánchez, A; Muñoz-Rivero, M V; Cabañuz-Plo, T; Alfaro-Torres, J; Marquina-Ibáñez, I M; Hakim-Alonso, S; Mejía-Urbáez, E; Gil-Fabra, J; Gil-Martínez, P; Ávarez-Alegret, R; Sanz, G; Gil-Sanz, M J

2016-04-01

To prevent the overdiagnosis and overtreatment of prostate cancer (PC), therapeutic strategies have been established such as active surveillance and focal therapy, as well as methods for clarifying the diagnosis of high-grade prostate cancer (HGPC) (defined as a Gleason score ≥7), such as multiparametric magnetic resonance imaging and new markers such as the 4Kscore test (4KsT). By means of a pilot study, we aim to test the ability of the 4KsT to identify HGPC in prostate biopsies (Bx) and compare the test with other multivariate prognostic models such as the Prostate Cancer Prevention Trial Risk Calculator 2.0 (PCPTRC 2.0) and the European Research Screening Prostate Cancer Risk Calculator 4 (ERSPC-RC 4). Fifty-one patients underwent a prostate Bx according to standard clinical practice, with a minimum of 10 cores. The diagnosis of HGPC was agreed upon by 4 uropathologists. We compared the predictions from the various models by using the Mann-Whitney U test, area under the ROC curve (AUC) (DeLong test), probability density function (PDF), box plots and clinical utility curves. Forty-three percent of the patients had PC, and 23.5% had HGPC. The medians of probability for the 4KsT, PCPTRC 2.0 and ERSPC-RC 4 were significantly different between the patients with HGPC and those without HGPC (p≤.022) and were more differentiated in the case of 4KsT (51.5% for HGPC [25-75 percentile: 25-80.5%] vs. 16% [P 25-75: 8-26.5%] for non-HGPC; p=.002). All models presented AUCs above 0.7, with no significant differences between any of them and 4KsT (p≥.20). The PDF and box plots showed good discriminative ability, especially in the ERSPC-RC 4 and 4KsT models. The utility curves showed how a cutoff of 9% for 4KsT identified all cases of HGPC and provided a 22% savings in biopsies, which is similar to what occurs with the ERSPC-RC 4 models and a cutoff of 3%. The assessed predictive models offer good discriminative ability for HGPCs in Bx. The 4KsT is a good classification model as a whole, followed by ERSPC-RC 4 and PCPTRC 2.0. The clinical utility curves help suggest cutoff points for clinical decisions: 9% for 4KsT and 3% for ERSPC-RC 4. This preliminary study should be interpreted with caution due to its limited sample size. Copyright © 2015 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

The Work Ability Index as a screening tool to identify the need for rehabilitation: longitudinal findings from the Second German Sociomedical Panel of Employees.

PubMed

Bethge, Matthias; Radoschewski, Friedrich Michael; Gutenbrunner, Christoph

2012-11-01

To evaluate the predictive value of the Work Ability Index (WAI) for different indicators of the need for rehabilitation at 1-year follow-up. Cohort study. Data were obtained from the Second German Sociomedical Panel of Employees, a large-scale cohort study with postal surveys in 2009 and 2010. A total of 457 women and 579 men were included. Confirmatory factor analysis confirmed the one-dimensionality of the WAI. Regression analyses showed that poor and moderate baseline WAI scores were associated with lower health-related quality of life and more frequent use of primary healthcare 1 year later. Subjects with poor baseline work ability had 4.6 times higher odds of unemployment and 12.2 times higher odds of prolonged sick leave than the reference group with good or excellent baseline work ability. Moreover, the odds of subjectively perceived need for rehabilitation, intention to request rehabilitation and actual use of rehabilitation services were 9.7, 5.7 and 3 times higher in the poor baseline WAI group and 5.5, 4 and 1.8 times higher in the moderate baseline WAI group, respectively. A WAI score ≤ 37 was identified as the optimal cut-off to predict the need for rehabilitation. The WAI is a valid screening tool for identifying the need for rehabilitation.

Posterior Predictive Bayesian Phylogenetic Model Selection

PubMed Central

Lewis, Paul O.; Xie, Wangang; Chen, Ming-Hui; Fan, Yu; Kuo, Lynn

2014-01-01

We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand–Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior predictive variance (GGp) and goodness-of-fit (GGg), which distinguishes this method from the posterior predictive P-value approach. The conditional predictive ordinate (CPO) method provides a site-specific measure of model fit useful for exploratory analyses and can be combined over sites yielding the log pseudomarginal likelihood (LPML) which is useful as an overall measure of model fit. CPO provides a useful cross-validation approach that is computationally efficient, requiring only a sample from the posterior distribution (no additional simulation is required). Both GG and CPO add new perspectives to Bayesian phylogenetic model selection based on the predictive abilities of models and complement the perspective provided by the marginal likelihood (including Bayes Factor comparisons) based solely on the fit of competing models to observed data. [Bayesian; conditional predictive ordinate; CPO; L-measure; LPML; model selection; phylogenetics; posterior predictive.] PMID:24193892

Understanding phylogenies in biology: the influence of a Gestalt Perceptual Principle.

PubMed

Novick, Laura R; Catley, Kefyn M

2007-12-01

Cladograms, hierarchical diagrams depicting evolutionary histories among (groups of) species, are commonly drawn in 2 informationally equivalent formats--tree and ladder. The authors hypothesize that these formats are not computationally equivalent because the Gestalt principle of good continuation obscures the hierarchical structure of ladders. Experimental results confirmed that university students (N = 44) prefer to subdivide ladders in accordance with good continuation rather than with the underlying hierarchical structure. Two subsequent experiments (N = 164) investigated cladogram understanding by examining students' ability to translate between formats (e.g., from tree to ladder). As predicted, students had greater difficulty understanding ladders than trees. This effect was larger for students with weaker backgrounds in biology. These results have important implications for evolution education reform.

Selfing ability and dispersal are positively related, but not affected by range position: a multispecies study on southern African Asteraceae.

PubMed

de Waal, C; Rodger, J G; Anderson, B; Ellis, A G

2014-05-01

Dispersal and breeding system traits are thought to affect colonization success. As species have attained their present distribution ranges through colonization, these traits may vary geographically. Although several theories predict associations between dispersal ability, selfing ability and the relative position of a population within its geographic range, there is little theoretical or empirical consensus on exactly how these three variables are related. We investigated relationships between dispersal ability, selfing ability and range position across 28 populations of 13 annual, wind-dispersed Asteraceae species from the Namaqualand region of South Africa. Controlling for phylogeny, relative dispersal ability--assessed from vertical fall time of fruits--was positively related to an index of autofertility--determined from hand-pollination experiments. These findings support the existence of two discrete syndromes: high selfing ability associated with good dispersal and obligate outcrossing associated with lower dispersal ability. This is consistent with the hypothesis that selection for colonization success drives the evolution of an association between these traits. However, no general effect of range position on dispersal or breeding system traits was evident. This suggests selection on both breeding system and dispersal traits acts consistently across distribution ranges. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Pulmonary hypertension due to left heart disease: diagnostic and prognostic value of CT in chronic systolic heart failure.

PubMed

Colin, Geoffrey C; Gerber, Bernhard L; de Meester de Ravenstein, Christophe; Byl, David; Dietz, Anna; Kamga, Michele; Pasquet, Agnes; Vancraeynest, David; Vanoverschelde, Jean-Louis; D'Hondt, Anne-Marie; Ghaye, Benoit; Pouleur, Anne-Catherine

2018-05-14

To evaluate the ability of chest computed tomography (CT) to predict pulmonary hypertension (PH) and outcome in chronic heart failure with reduced ejection fraction (HFrEF). We reviewed 119 consecutive patients with HFrEF by CT, transthoracic echocardiography (TTE) and right heart catheterization (RHC). CT-derived pulmonary artery (PA) diameter and PA to ascending aorta diameter ratio (PA:A ratio), left atrial, right atrial, right ventricular (RV) and left ventricular volumes were correlated with RHC mean pulmonary arterial pressure (mPAP) . Diagnostic accuracy to predict PH and ability to predict primary composite endpoint of all-cause mortality and HF events were evaluated. RV volume was significantly higher in 81 patients with PH compared to 38 patients without PH (133 ml/m 2 vs. 79 ml/m 2 , p < 0.001) and was moderately correlated with mPAP (r=0.55, p < 0.001). Also, RV volume had higher ability to predict PH (area under the curve: 0.88) than PA diameter (0.79), PA:A ratio (0.76) by CT and tricuspid regurgitation gradient (0.83) and RV basal diameter by TTE (0.84, all p < 0.001). During the follow-up period (median: 3.4 years), 51 patients (43%) had HF events or died. After correction for important clinical, TTE and RHC parameters, RV volume (adjusted hazard ratio [HR]: 1.71, 95% CI 1.31-2.23, p < 0.001) and PA diameter (HR: 1.61, 95% CI 1.18-2.22, p = 0.003) were independent predictors of the primary endpoint. In patients with HFrEF, measurement of RV volume and PA diameter on ungated CT are non-invasive markers of PH and may help to predict the patient outcome. • Right ventricular (RV) volume measured by chest CT has good ability to identify pulmonary hypertension (PH) in patients with chronic heart failure (HF) and reduced ejection fraction (HFrEF). • The accuracy of pulmonary artery (PA) diameter and PA to ascending aorta diameter ratio (PA:A ratio) to predict PH was similar to previous studies, however, with lower cut-offs (28.1 mm and 0.92, respectively). • Chest CT-derived PA diameter and RV volume independently predict all-cause mortality and HF events and improve outcome prediction in patients with advanced HFrEF.

A novel and simple test of gait adaptability predicts gold standard measures of functional mobility in stroke survivors.

PubMed

Hollands, K L; Pelton, T A; van der Veen, S; Alharbi, S; Hollands, M A

2016-01-01

Although there is evidence that stroke survivors have reduced gait adaptability, the underlying mechanisms and the relationship to functional recovery are largely unknown. We explored the relationships between walking adaptability and clinical measures of balance, motor recovery and functional ability in stroke survivors. Stroke survivors (n=42) stepped to targets, on a 6m walkway, placed to elicit step lengthening, shortening and narrowing on paretic and non-paretic sides. The number of targets missed during six walks and target stepping speed was recorded. Fugl-Meyer (FM), Berg Balance Scale (BBS), self-selected walking speed (SWWS) and single support (SS) and step length (SL) symmetry (using GaitRite when not walking to targets) were also assessed. Stepwise multiple-linear regression was used to model the relationships between: total targets missed, number missed with paretic and non-paretic legs, target stepping speed, and each clinical measure. Regression revealed a significant model for each outcome variable that included only one independent variable. Targets missed by the paretic limb, was a significant predictor of FM (F(1,40)=6.54, p=0.014,). Speed of target stepping was a significant predictor of each of BBS (F(1,40)=26.36, p<0.0001), SSWS (F(1,40)=37.00, p<0.0001). No variables were significant predictors of SL or SS asymmetry. Speed of target stepping was significantly predictive of BBS and SSWS and paretic targets missed predicted FM, suggesting that fast target stepping requires good balance and accurate stepping demands good paretic leg function. The relationships between these parameters indicate gait adaptability is a clinically meaningful target for measurement and treatment of functionally adaptive walking ability in stroke survivors. Copyright © 2015 Elsevier B.V. All rights reserved.

Ability of preoperative 3.0-Tesla magnetic resonance imaging to predict the absence of side-specific extracapsular extension of prostate cancer.

PubMed

Hara, Tomohiko; Nakanishi, Hiroyuki; Nakagawa, Tohru; Komiyama, Motokiyo; Kawahara, Takashi; Manabe, Tomoko; Miyake, Mototaka; Arai, Eri; Kanai, Yae; Fujimoto, Hiroyuki

2013-10-01

Recent studies have shown an improvement in prostate cancer diagnosis with the use of 3.0-Tesla magnetic resonance imaging. We retrospectively assessed the ability of this imaging technique to predict side-specific extracapsular extension of prostate cancer. From October 2007 to August 2011, prostatectomy was carried out in 396 patients after preoperative 3.0-Tesla magnetic resonance imaging. Among these, 132 (primary sample) and 134 patients (validation sample) underwent 12-core prostate biopsy at the National Cancer Center Hospital of Tokyo, Japan, and at other institutions, respectively. In the primary dataset, univariate and multivariate analyses were carried out to predict side-specific extracapsular extension using variables determined preoperatively, including 3.0-Tesla magnetic resonance imaging findings (T2-weighted and diffusion-weighted imaging). A prediction model was then constructed and applied to the validation study sample. Multivariate analysis identified four significant independent predictors (P < 0.05), including a biopsy Gleason score of ≥8, positive 3.0-Tesla diffusion-weighted magnetic resonance imaging findings, ≥2 positive biopsy cores on each side and a maximum percentage of positive cores ≥31% on each side. The negative predictive value was 93.9% in the combination model with these four predictors, meanwhile the positive predictive value was 33.8%. Good reproducibility of these four significant predictors and the combination model was observed in the validation study sample. The side-specific extracapsular extension prediction by the biopsy Gleason score and factors associated with tumor location, including a positive 3.0-Tesla diffusion-weighted magnetic resonance imaging finding, have a high negative predictive value, but a low positive predictive value. © 2013 The Japanese Urological Association.

Predicting pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review.

PubMed

Ryan, J E; Warrier, S K; Lynch, A C; Ramsay, R G; Phillips, W A; Heriot, A G

2016-03-01

Approximately 20% of patients treated with neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer achieve a pathological complete response (pCR) while the remainder derive the benefit of improved local control and downstaging and a small proportion show a minimal response. The ability to predict which patients will benefit would allow for improved patient stratification directing therapy to those who are likely to achieve a good response, thereby avoiding ineffective treatment in those unlikely to benefit. A systematic review of the English language literature was conducted to identify pathological factors, imaging modalities and molecular factors that predict pCR following chemoradiotherapy. PubMed, MEDLINE and Cochrane Database searches were conducted with the following keywords and MeSH search terms: 'rectal neoplasm', 'response', 'neoadjuvant', 'preoperative chemoradiation', 'tumor response'. After review of title and abstracts, 85 articles addressing the prediction of pCR were selected. Clear methods to predict pCR before chemoradiotherapy have not been defined. Clinical and radiological features of the primary cancer have limited ability to predict response. Molecular profiling holds the greatest potential to predict pCR but adoption of this technology will require greater concordance between cohorts for the biomarkers currently under investigation. At present no robust markers of the prediction of pCR have been identified and the topic remains an area for future research. This review critically evaluates existing literature providing an overview of the methods currently available to predict pCR to nCRT for locally advanced rectal cancer. The review also provides a comprehensive comparison of the accuracy of each modality. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.

Structural parameterization and functional prediction of antigenic polypeptome sequences with biological activity through quantitative sequence-activity models (QSAM) by molecular electronegativity edge-distance vector (VMED).

PubMed

Li, ZhiLiang; Wu, ShiRong; Chen, ZeCong; Ye, Nancy; Yang, ShengXi; Liao, ChunYang; Zhang, MengJun; Yang, Li; Mei, Hu; Yang, Yan; Zhao, Na; Zhou, Yuan; Zhou, Ping; Xiong, Qing; Xu, Hong; Liu, ShuShen; Ling, ZiHua; Chen, Gang; Li, GenRong

2007-10-01

Only from the primary structures of peptides, a new set of descriptors called the molecular electronegativity edge-distance vector (VMED) was proposed and applied to describing and characterizing the molecular structures of oligopeptides and polypeptides, based on the electronegativity of each atom or electronic charge index (ECI) of atomic clusters and the bonding distance between atom-pairs. Here, the molecular structures of antigenic polypeptides were well expressed in order to propose the automated technique for the computerized identification of helper T lymphocyte (Th) epitopes. Furthermore, a modified MED vector was proposed from the primary structures of polypeptides, based on the ECI and the relative bonding distance of the fundamental skeleton groups. The side-chains of each amino acid were here treated as a pseudo-atom. The developed VMED was easy to calculate and able to work. Some quantitative model was established for 28 immunogenic or antigenic polypeptides (AGPP) with 14 (1-14) A(d) and 14 other restricted activities assigned as "1"(+) and "0"(-), respectively. The latter comprised 6 A(b)(15-20), 3 A(k)(21-23), 2 E(k)(24-26), 2 H-2(k)(27 and 28) restricted sequences. Good results were obtained with 90% correct classification (only 2 wrong ones for 20 training samples) and 100% correct prediction (none wrong for 8 testing samples); while contrastively 100% correct classification (none wrong for 20 training samples) and 88% correct classification (1 wrong for 8 testing samples). Both stochastic samplings and cross validations were performed to demonstrate good performance. The described method may also be suitable for estimation and prediction of classes I and II for major histocompatibility antigen (MHC) epitope of human. It will be useful in immune identification and recognition of proteins and genes and in the design and development of subunit vaccines. Several quantitative structure activity relationship (QSAR) models were developed for various oligopeptides and polypeptides including 58 dipeptides and 31 pentapeptides with angiotensin converting enzyme (ACE) inhibition by multiple linear regression (MLR) method. In order to explain the ability to characterize molecular structure of polypeptides, a molecular modeling investigation on QSAR was performed for functional prediction of polypeptide sequences with antigenic activity and heptapeptide sequences with tachykinin activity through quantitative sequence-activity models (QSAMs) by the molecular electronegativity edge-distance vector (VMED). The results showed that VMED exhibited both excellent structural selectivity and good activity prediction. Moreover, the results showed that VMED behaved quite well for both QSAR and QSAM of poly-and oligopeptides, which exhibited both good estimation ability and prediction power, equal to or better than those reported in the previous references. Finally, a preliminary conclusion was drawn: both classical and modified MED vectors were very useful structural descriptors. Some suggestions were proposed for further studies on QSAR/QSAM of proteins in various fields.

Neuronal prediction of opponent's behavior during cooperative social interchange in primates.

PubMed

Haroush, Keren; Williams, Ziv M

2015-03-12

A cornerstone of successful social interchange is the ability to anticipate each other's intentions or actions. While generating these internal predictions is essential for constructive social behavior, their single neuronal basis and causal underpinnings are unknown. Here, we discover specific neurons in the primate dorsal anterior cingulate that selectively predict an opponent's yet unknown decision to invest in their common good or defect and distinct neurons that encode the monkey's own current decision based on prior outcomes. Mixed population predictions of the other was remarkably near optimal compared to behavioral decoders. Moreover, disrupting cingulate activity selectively biased mutually beneficial interactions between the monkeys but, surprisingly, had no influence on their decisions when no net-positive outcome was possible. These findings identify a group of other-predictive neurons in the primate anterior cingulate essential for enacting cooperative interactions and may pave a way toward the targeted treatment of social behavioral disorders. Copyright © 2015 Elsevier Inc. All rights reserved.

Dynamical systems proxies of atmospheric predictability and mid-latitude extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Faranda, Davide; Caballero, Rodrigo; Yiou, Pascal

2017-04-01

Extreme weather ocurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. Many extremes (for e.g. storms, heatwaves, cold spells, heavy precipitation) are tied to specific patterns of midlatitude atmospheric circulation. The ability to identify these patterns and use them to enhance the predictability of the extremes is therefore a topic of crucial societal and economic value. We propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We use two simple dynamical systems metrics - local dimension and persistence - to identify sets of similar large-scale atmospheric flow patterns which present a coherent temporal evolution. When these patterns correspond to weather extremes, they therefore afford a particularly good forward predictability. We specifically test this technique on European winter temperatures, whose variability largely depends on the atmospheric circulation in the North Atlantic region. We find that our dynamical systems approach provides predictability of large-scale temperature extremes up to one week in advance.

Experimental Verification of a Progressive Damage Model for IM7/5260 Laminates Subjected to Tension-Tension Fatigue

NASA Technical Reports Server (NTRS)

Coats, Timothy W.; Harris, Charles E.

1995-01-01

The durability and damage tolerance of laminated composites are critical design considerations for airframe composite structures. Therefore, the ability to model damage initiation and growth and predict the life of laminated composites is necessary to achieve structurally efficient and economical designs. The purpose of this research is to experimentally verify the application of a continuum damage model to predict progressive damage development in a toughened material system. Damage due to monotonic and tension-tension fatigue was documented for IM7/5260 graphite/bismaleimide laminates. Crack density and delamination surface area were used to calculate matrix cracking and delamination internal state variables to predict stiffness loss in unnotched laminates. A damage dependent finite element code predicted the stiffness loss for notched laminates with good agreement to experimental data. It was concluded that the continuum damage model can adequately predict matrix damage progression in notched and unnotched laminates as a function of loading history and laminate stacking sequence.

Intelligent Monitoring? Assessing the ability of the Care Quality Commission's statistical surveillance tool to predict quality and prioritise NHS hospital inspections.

PubMed

Griffiths, Alex; Beaussier, Anne-Laure; Demeritt, David; Rothstein, Henry

2017-02-01

The Care Quality Commission (CQC) is responsible for ensuring the quality of the health and social care delivered by more than 30 000 registered providers in England. With only limited resources for conducting on-site inspections, the CQC has used statistical surveillance tools to help it identify which providers it should prioritise for inspection. In the face of planned funding cuts, the CQC plans to put more reliance on statistical surveillance tools to assess risks to quality and prioritise inspections accordingly. To evaluate the ability of the CQC's latest surveillance tool, Intelligent Monitoring (IM), to predict the quality of care provided by National Health Service (NHS) hospital trusts so that those at greatest risk of providing poor-quality care can be identified and targeted for inspection. The predictive ability of the IM tool is evaluated through regression analyses and χ 2 testing of the relationship between the quantitative risk score generated by the IM tool and the subsequent quality rating awarded following detailed on-site inspection by large expert teams of inspectors. First, the continuous risk scores generated by the CQC's IM statistical surveillance tool cannot predict inspection-based quality ratings of NHS hospital trusts (OR 0.38 (0.14 to 1.05) for Outstanding/Good, OR 0.94 (0.80 to -1.10) for Good/Requires improvement, and OR 0.90 (0.76 to 1.07) for Requires improvement/Inadequate). Second, the risk scores cannot be used more simply to distinguish the trusts performing poorly-those subsequently rated either 'Requires improvement' or 'Inadequate'-from the trusts performing well-those subsequently rated either 'Good' or 'Outstanding' (OR 1.07 (0.91 to 1.26)). Classifying CQC's risk bandings 1-3 as high risk and 4-6 as low risk, 11 of the high risk trusts were performing well and 43 of the low risk trusts were performing poorly, resulting in an overall accuracy rate of 47.6%. Third, the risk scores cannot be used even more simply to distinguish the worst performing trusts-those subsequently rated 'Inadequate'-from the remaining, better performing trusts (OR 1.11 (0.94 to 1.32)). Classifying CQC's risk banding 1 as high risk and 2-6 as low risk, the highest overall accuracy rate of 72.8% was achieved, but still only 6 of the 13 Inadequate trusts were correctly classified as being high risk. Since the IM statistical surveillance tool cannot predict the outcome of NHS hospital trust inspections, it cannot be used for prioritisation. A new approach to inspection planning is therefore required. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Risk prediction models for major adverse cardiac event (MACE) following percutaneous coronary intervention (PCI): A review

NASA Astrophysics Data System (ADS)

Manan, Norhafizah A.; Abidin, Basir

2015-02-01

Five percent of patients who went through Percutaneous Coronary Intervention (PCI) experienced Major Adverse Cardiac Events (MACE) after PCI procedure. Risk prediction of MACE following a PCI procedure therefore is helpful. This work describes a review of such prediction models currently in use. Literature search was done on PubMed and SCOPUS database. Thirty literatures were found but only 4 studies were chosen based on the data used, design, and outcome of the study. Particular emphasis was given and commented on the study design, population, sample size, modeling method, predictors, outcomes, discrimination and calibration of the model. All the models had acceptable discrimination ability (C-statistics >0.7) and good calibration (Hosmer-Lameshow P-value >0.05). Most common model used was multivariate logistic regression and most popular predictor was age.

The Added Value of Collecting Information on Pain Experience When Predicting Time on Benefits for Injured Workers with Back Pain.

PubMed

Steenstra, Ivan A; Franche, Renée-Louise; Furlan, Andrea D; Amick, Ben; Hogg-Johnson, Sheilah

2016-06-01

Objectives Some injured workers with work-related, compensated back pain experience a troubling course in return to work. A prediction tool was developed in an earlier study, using administrative data only. This study explored the added value of worker reported data in identifying those workers with back pain at higher risk of being on benefits for a longer period of time. Methods This was a cohort study of workers with compensated back pain in 2005 in Ontario. Workplace Safety and Insurance Board (WSIB) data was used. As well, we examined the added value of patient-reported prognostic factors obtained from a prospective cohort study. Improvement of model fit was determined by comparing area under the curve (AUC) statistics. The outcome measure was time on benefits during a first workers' compensation claim for back pain. Follow-up was 2 years. Results Among 1442 workers with WSIB data still on full benefits at 4 weeks, 113 were also part of the prospective cohort study. Model fit of an established rule in the smaller dataset of 113 workers was comparable to the fit previously established in the larger dataset. Adding worker rating of pain at baseline improved the rule substantially (AUC = 0.80, 95 % CI 0.68, 0.91 compared to benefit status at 180 days, AUC = 0.88, 95 % CI 0.74, 1.00 compared to benefits status at 360 days). Conclusion Although data routinely collected by workers' compensation boards show some ability to predict prolonged time on benefits, adding information on experienced pain reported by the worker improves the predictive ability of the model from 'fairly good' to 'good'. In this study, a combination of prognostic factors, reported by multiple stakeholders, including the worker, could identify those at high risk of extended duration on disability benefits and in potentially in need of additional support at the individual level.

Ability to Reach Orgasm in Patients With Prostate Cancer Treated With Robot-assisted Laparoscopic Prostatectomy.

PubMed

Østby-Deglum, Marie; Axcrona, Karol; Brennhovd, Bjørn; Dahl, Alv A

2016-06-01

To study the ability to reach orgasm after robot-assisted laparoscopic prostatectomy (RALP) in relation to demographic, cancer-related, and surgical variables, and the use of erectile aids. In this cross-sectional study at a mean of 3 years after RALP at Oslo University Hospital, 982 men were invited to complete a mailed questionnaire, and 777 responded. Respondents who reported postoperative radiotherapy or hormone treatment, or did not report on orgasm were omitted, leaving 609 patients for analysis. Ability to reach orgasm was rated on 1 question from The Expanded Prostate Cancer Index Composite 26-item version, and dichotomized into "good" or "poor." Overall, 27% of the men reported good ability to reach orgasm: 22% among those did not use erectile aids and 34% among those did (P = .001). Univariate analysis of men with good versus poor ability to reach orgasm showed many significant differences. In multivariate analysis, being older, having a reduced physical quality of life, and erectile dysfunction were significantly associated with poor ability to reach orgasm. Erectile dysfunction showed an odds ratio of 4.86 for poor orgasmic ability. The 48% of men who used erectile aids had significantly better orgasmic ability than the nonusers. In our sample, 27% had good ability to reach orgasm at a mean of 3 years after RALP. Poor orgasmic ability was associated with being older, poor erectile function, and a reduced physical quality of life. Using erectile aids increased the rate of good ability to reach orgasm. Copyright © 2016 Elsevier Inc. All rights reserved.

The Reliability and Predictive Ability of a Biomarker of Oxidative DNA Damage on Functional Outcomes after Stroke Rehabilitation

PubMed Central

Hsieh, Yu-Wei; Lin, Keh-Chung; Korivi, Mallikarjuna; Lee, Tsong-Hai; Wu, Ching-Yi; Wu, Kuen-Yuh

2014-01-01

We evaluated the reliability of 8-hydroxy-2′-deoxyguanosine (8-OHdG), and determined its ability to predict functional outcomes in stroke survivors. The rehabilitation effect on 8-OHdG and functional outcomes were also assessed. Sixty-one stroke patients received a 4-week rehabilitation. Urinary 8-OHdG levels were determined by liquid chromatography–tandem mass spectrometry. The test-retest reliability of 8-OHdG was good (interclass correlation coefficient = 0.76). Upper-limb motor function and muscle power determined by the Fugl-Meyer Assessment (FMA) and Medical Research Council (MRC) scales before rehabilitation showed significant negative correlation with 8-OHdG (r = −0.38, r = −0.30; p < 0.05). After rehabilitation, we found a fair and significant correlation between 8-OHdG and FMA (r = −0.34) and 8-OHdG and pain (r = 0.26, p < 0.05). Baseline 8-OHdG was significantly correlated with post-treatment FMA, MRC, and pain scores (r = −0.34, −0.31, and 0.25; p < 0.05), indicating its ability to predict functional outcomes. 8-OHdG levels were significantly decreased, and functional outcomes were improved after rehabilitation. The exploratory study findings conclude that 8-OHdG is a reliable and promising biomarker of oxidative stress and could be a valid predictor of functional outcomes in patients. Monitoring of behavioral indicators along with biomarkers may have crucial benefits in translational stroke research. PMID:24743892

Heterodimer Binding Scaffolds Recognition via the Analysis of Kinetically Hot Residues

PubMed Central

Perišić, Ognjen

2018-01-01

Physical interactions between proteins are often difficult to decipher. The aim of this paper is to present an algorithm that is designed to recognize binding patches and supporting structural scaffolds of interacting heterodimer proteins using the Gaussian Network Model (GNM). The recognition is based on the (self) adjustable identification of kinetically hot residues and their connection to possible binding scaffolds. The kinetically hot residues are residues with the lowest entropy, i.e., the highest contribution to the weighted sum of the fastest modes per chain extracted via GNM. The algorithm adjusts the number of fast modes in the GNM’s weighted sum calculation using the ratio of predicted and expected numbers of target residues (contact and the neighboring first-layer residues). This approach produces very good results when applied to dimers with high protein sequence length ratios. The protocol’s ability to recognize near native decoys was compared to the ability of the residue-level statistical potential of Lu and Skolnick using the Sternberg and Vakser decoy dimers sets. The statistical potential produced better overall results, but in a number of cases its predicting ability was comparable, or even inferior, to the prediction ability of the adjustable GNM approach. The results presented in this paper suggest that in heterodimers at least one protein has interacting scaffold determined by the immovable, kinetically hot residues. In many cases, interacting proteins (especially if being of noticeably different sizes) either behave as a rigid lock and key or, presumably, exhibit the opposite dynamic behavior. While the binding surface of one protein is rigid and stable, its partner’s interacting scaffold is more flexible and adaptable. PMID:29547506

Online and offline inferential and textual processing of poor comprehenders: Evidence from a probing method.

PubMed

Yeari, Menahem; Elentok, Shiri; Schiff, Rachel

2017-03-01

Numerous studies have demonstrated that poor inferential processing underlies the specific deficit of poor comprehenders. However, it is still not clear why poor comprehenders have difficulties in generating inferences while reading and whether this impairment is general or specific to one or more types of inferences. The current study employed an online probing method to examine the spontaneous immediate activation of two inference types-forward-predictive inferences and backward-explanatory inferences-during reading. In addition, we examined the ability of poor comprehenders to retain, suppress, and reactivate text information (relevant for inferencing) in working memory. The participants, 10- to 12-year-old good and poor comprehenders, read short narratives and name inference or text word probes following a predictive, intervening, or bridging sentence. Comparing the size of probe-naming facilitations revealed that poor comprehenders generate predictive inferences, albeit more slowly than good comprehenders, and generate explanatory inferences to a lesser extent than good comprehenders. Moreover, we found that this inferior inferential processing is presumably a result of poor retention and reactivation of inference-evoking text information during reading. Finally, poorer reading comprehension was associated with higher activation of information when it was less relevant following the intervening sentences. Taken together, the current findings demonstrate the manner in which poor regulation of relevant and less relevant information during reading underlies the specific comprehension difficulties experienced by poor comprehenders. Copyright © 2016 Elsevier Inc. All rights reserved.

Off-Ice Anaerobic Power Does Not Predict On-Ice Repeated Shift Performance in Hockey.

PubMed

Peterson, Ben J; Fitzgerald, John S; Dietz, Calvin C; Ziegler, Kevin S; Baker, Sarah E; Snyder, Eric M

2016-09-01

Peterson, BJ, Fitzgerald, JS, Dietz, CC, Ziegler, KS, Baker, SE, and Snyder, EM. Off-ice anaerobic power does not predict on-ice repeated shift performance in hockey. J Strength Cond Res 30(9): 2375-2381, 2016-Anaerobic power is a significant predictor of acceleration and top speed in team sport athletes. Historically, these findings have been applied to ice hockey although recent research has brought their validity for this sport into question. As ice hockey emphasizes the ability to repeatedly produce power, single bout anaerobic power tests should be examined to determine their ability to predict on-ice performance. We tested whether conventional off-ice anaerobic power tests could predict on-ice acceleration, top speed, and repeated shift performance. Forty-five hockey players, aged 18-24 years, completed anthropometric, off-ice, and on-ice tests. Anthropometric and off-ice testing included height, weight, body composition, vertical jump, and Wingate tests. On-ice testing consisted of acceleration, top speed, and repeated shift fatigue tests. Vertical jump (VJ) (r = -0.42; r = -0.58), Wingate relative peak power (WRPP) (r = -0.32; r = -0.43), and relative mean power (WRMP) (r = -0.34; r = -0.48) were significantly correlated (p ≤ 0.05) to on-ice acceleration and top speed, respectively. Conversely, none of the off-ice tests correlated with on-ice repeated shift performance, as measured by first gate, second gate, or total course fatigue; VJ (r = 0.06; r = 0.13; r = 0.09), WRPP (r = 0.06; r = 0.14; r = 0.10), or WRMP (r = -0.10; r = -0.01; r = -0.01). Although conventional off-ice anaerobic power tests predict single bout on-ice acceleration and top speed, they neither predict the repeated shift ability of the player, nor are good markers for performance in ice hockey.

Age and Preoperative Knee Society Score Are Significant Predictors of Outcomes Among Asians Following Total Knee Arthroplasty.

PubMed

Bin Abd Razak, Hamid Rahmatullah; Tan, Chuen-Seng; Chen, Yongqiang Jerry Delphi; Pang, Hee-Nee; Tay, Keng-Jin Darren; Chin, Pak-Lin; Chia, Shi-Lu; Lo, Ngai-Nung; Yeo, Seng-Jin

2016-05-04

The ability to predict patients' functional outcomes will add value to preoperative counseling. The purpose of this study was to evaluate predictors of good outcomes following total knee arthroplasty (TKA) among Asian patients. Registry data from 2006 to 2010 were extracted. The Oxford Knee Score (OKS) and the Short Form (SF)-36 physical component summary (PCS) were used to evaluate outcomes. A "good outcome" was defined as an improvement in scores of greater than or equal to the minimal clinically important difference (MCID) in the primary analysis. The MCID for the OKS was 5, and the MCID for the PCS was 10. For the sensitivity analyses, a "good outcome" was defined as an OKS of <30 and a PCS score of >50. Clinical variables were used to develop a multiple logistic regression model for a good outcome following total knee arthroplasty at 5 years. Follow-up data were available for 3,062 patients who underwent primary TKA (mean age of 66.4 years; 79.5% female). Eighty-five percent had a good outcome on the basis of the OKS and 83%, on the basis of the SF-36 PCS. Age and preoperative Knee Society score (KSS) were found to be significant predictors. When outcomes were assessed by the MCID, lesser age and lower (worse) preoperative KSS predicted a good outcome at 5 years. When outcomes were assessed by absolute criteria (postoperative scores measured against OKS and PCS thresholds), a higher (better) preoperative KSS predicted a good outcome at 5 years. Body mass index, preoperative flexion range, SF-36 mental component summary (MCS) score, mechanical alignment, sex, education level, ethnicity, operative side, number of comorbidities, type of anesthesia, and type of implant were found not to be significant predictors. The majority of Asian patients with osteoarthritis had good outcomes according to the MCID criterion and benefitted from primary TKA. On the basis of our findings, we believe that older patients with a lower (worse) preoperative KSS can be informed that they have a high likelihood of improvement but a lower likelihood of achieving as good a functional outcome as those with better scores. Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

PubMed

Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

2013-09-01

The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Self-Reported Work Ability Predicts Rehabilitation Measures, Disability Pensions, Other Welfare Benefits, and Work Participation: Longitudinal Findings from a Sample of German Employees.

PubMed

Bethge, Matthias; Spanier, Katja; Peters, Elke; Michel, Elliot; Radoschewski, Michael

2017-09-27

Purpose The study examined the performance of the Work Ability Index in predicting rehabilitation measures and disability pensions, sickness absence and unemployment benefits, and work participation among a sample of workers previously receiving sickness absence benefits. Methods Workers aged 40 to 54 years who received sickness absence benefits in 2012 completed the Work Ability Index in 2013. Outcomes were extracted from administrative data records. Results Data for 2149 participants were included (mean age: 47.8 years; 54.4% women). Mean follow-up was 19 months. Work Ability Index scores were poor (7-27 points) in 21% of the participants, and moderate (28-36 points) in 38.4%. In all, 224 rehabilitation measures and 35 disability pensions were approved. Fully adjusted analyses showed increased risk of rehabilitation measures in workers with poor (HR 4.55; 95% CI 3.14-6.60) and moderate scores (HR 2.08; 95% CI 1.43-3.01) compared to workers with good or excellent scores (37-49 points). The risk of a disability pension increased significantly for workers with poor scores (HR 7.78; 95% CI 2.59-23.35). In addition, poor scores were prospectively associated with a longer duration of sickness absence and employment benefits, and fewer employment days and less income from regular employment. Conclusions The Work Ability Index is a potential tool for following up workers who already have an increased risk of permanent work disability due to previous long-term sickness absence.

Measurement properties of a screening questionnaire of obstructive sleep apnea risk: Little information, great prediction?(☆).

PubMed

Sargento, Paulo; Perea, Victoria; Ladera, Valentina; Lopes, Paulo; Oliveira, Jorge

2014-06-01

Previous research had shown the suitability of several questionnaires predicting the obstructive sleep apnea syndrome. Measurement properties of an online screening questionnaire were studied. The sample consisted of 184 Portuguese adults (89 men and 95 women); 46 of them were polysomnographically diagnosed with the untreated obstructive sleep apnea syndrome. The participants were assessed with an online questionnaire of sleep apnea risk, from University of Maryland. A principal component factor analysis was performed, revealing a single factor (49.24% of the total variance). Internal consistency was minimally adequate (α=0.74). The mean of inter-item correlation was of 0.35 (0.120.61), whereas the item-total correlations were considered good (0.520.81). The total score for patients was significantly higher than for healthy participants (p<0.000), but no significant statistical differences between severity groups of patients were found (p>0.05). Furthermore, the ability of the measure in discriminating between healthy subjects and OSA subjects was good. Overall data from the Rasch analysis was consistent with the guidelines of Linacre, scores show good model fit and psychometric adequacy. The measure showed an adequate structural, internal and criterion validity, suggesting this as a useful and effective screening for sleep apnea risk in Portuguese adults.

Alphabet Writing and Allograph Selection as Predictors of Spelling in Sentences Written by Spanish-Speaking Children Who Are Poor or Good Keyboarders.

PubMed

Peake, Christian; Diaz, Alicia; Artiles, Ceferino

This study examined the relationship and degree of predictability that the fluency of writing the alphabet from memory and the selection of allographs have on measures of fluency and accuracy of spelling in a free-writing sentence task when keyboarding. The Test Estandarizado para la Evaluación de la Escritura con Teclado ("Spanish Keyboarding Writing Test"; Jiménez, 2012) was used as the assessment tool. A sample of 986 children from Grades 1 through 3 were classified according to transcription skills measured by keyboard ability (poor vs. good) across the grades. Results demonstrated that fluency in writing the alphabet and selecting allographs mediated the differences in spelling between good and poor keyboarders in the free-writing task. Execution in the allograph selection task and writing alphabet from memory had different degrees of predictability in each of the groups in explaining the level of fluency and spelling in the free-writing task sentences, depending on the grade. These results suggest that early assessment of writing by means of the computer keyboard can provide clues and guidelines for intervention and training to strengthen specific skills to improve writing performance in the early primary grades in transcription skills by keyboarding.

Modeling the growth of Lactobacillus viridescens under non-isothermal conditions in vacuum-packed sliced ham.

PubMed

Silva, Nathália Buss da; Longhi, Daniel Angelo; Martins, Wiaslan Figueiredo; Laurindo, João Borges; Aragão, Gláucia Maria Falcão de; Carciofi, Bruno Augusto Mattar

2017-01-02

Lactic acid bacteria (LAB) are responsible for spoiling vacuum-packed meat products, such as ham. Since the temperature is the main factor affecting the microbial dynamic, the use of mathematical models describing the microbial behavior into a non-isothermal environment can be very useful for predicting food shelf life. In this study, the growth of Lactobacillus viridescens was measured in vacuum-packed sliced ham under non-isothermal conditions, and the predictive ability of primary (Baranyi and Roberts, 1994) and secondary (Square Root) models were assessed using parameters estimated in MRS culture medium under isothermal conditions (between 4 and 30°C). Fresh ham piece was sterilized, sliced, inoculated, vacuum-packed, and stored in a temperature-controlled incubator at five different non-isothermal conditions (between 4 and 25°C) and one isothermal condition (8°C). The mathematical models obtained in MRS medium were assessed by comparing predicted values with L. viridescens growth data in vacuum-packed ham. Its predictive ability was assessed through statistical indexes, with good results (bias factor between 0.95 and 1.03; accuracy factor between 1.04 and 1.07, and RMSE between 0.76 and 1.33), especially in increasing temperature, which predictions were safe. The model parameters obtained from isothermal growth data in MRS medium enabled to estimate the shelf life of a commercial ham under non-isothermal conditions in the temperature range analyzed. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2012-02-01

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.

Predicting DPP-IV inhibitors with machine learning approaches

NASA Astrophysics Data System (ADS)

Cai, Jie; Li, Chanjuan; Liu, Zhihong; Du, Jiewen; Ye, Jiming; Gu, Qiong; Xu, Jun

2017-04-01

Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain, edema, and hypoglycemia. However, the marketed DPP-IV inhibitors have adverse effects such as nasopharyngitis, headache, nausea, hypersensitivity, skin reactions and pancreatitis. Therefore, it is still expected for novel DPP-IV inhibitors with minimal adverse effects. The scaffolds of existing DPP-IV inhibitors are structurally diversified. This makes it difficult to build virtual screening models based upon the known DPP-IV inhibitor libraries using conventional QSAR approaches. In this paper, we report a new strategy to predict DPP-IV inhibitors with machine learning approaches involving naïve Bayesian (NB) and recursive partitioning (RP) methods. We built 247 machine learning models based on 1307 known DPP-IV inhibitors with optimized molecular properties and topological fingerprints as descriptors. The overall predictive accuracies of the optimized models were greater than 80%. An external test set, composed of 65 recently reported compounds, was employed to validate the optimized models. The results demonstrated that both NB and RP models have a good predictive ability based on different combinations of descriptors. Twenty "good" and twenty "bad" structural fragments for DPP-IV inhibitors can also be derived from these models for inspiring the new DPP-IV inhibitor scaffold design.

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

PubMed

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

2012-05-01

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

I believe I'm good at orienting myself… But is that true?

PubMed

Nori, Raffaella; Piccardi, Laura

2015-08-01

The present study aimed to analyse beliefs that men and women have with respect to their sense of direction (SOD) and whether they correlate with spatial environmental task performance. Eighty-four students filled in the short version of the Familiarity and Spatial Cognitive Style Scale to evaluate beliefs on their SOD, knowledge of the city (TK), spatial ability (SA) and wayfinding (WA) and performed three spatial environmental tasks. Results showed that gender did not predict the performance on the spatial environmental tasks, whereas it can be predicted by participants' beliefs related to their SOD and TK. The findings point out the need to identify specific training aimed at improving women's metacognitive skills in order to delete or reduce gender differences in SA.

No question about exciting questions in cell biology.

PubMed

Pollard, Thomas D

2013-12-01

Although we have a good grasp of many important processes in cell biology, including knowledge of many molecules involved and how they interact with each other, we still do not understand most of the dynamical features that are the essence of living systems. Fortunately, we now have the ability to dissect biological systems in enough detail to understand their dynamics, including the use of mathematical models to account for past observations and predict future experiments. This deep level of mechanistic understanding should be our goal—not simply to satisfy our scientific curiosity, but also to understand the causes of disease well enough to predict risks, make early diagnoses, and treat effectively. Many big questions remain to be answered before we reach this goal of understanding cellular dynamics.

The relation between children's reading comprehension level and their comprehension of idioms.

PubMed

Cain, Kate; Oakhill, Jane; Lemmon, Kate

2005-01-01

We report an investigation of 9-year-olds' ability to interpret idioms in relation to their reading comprehension level. We manipulated whether the idioms were transparent or opaque, whether they were real or novel, whether they were presented in isolation or in a supportive narrative context. As predicted, children were better able to explain the meanings of idioms in context than in isolation. The good and poor comprehenders did not differ in their abilities to interpret transparent idioms in context, but the poor comprehenders were significantly worse at using context to work out the meanings of opaque idioms. The explanation task revealed the source of information used by the children to derive nontarget interpretations. We discuss these findings in relation to idiom processing strategies and Levorato and Cacciari's global elaboration model.

A study on the applicability of in-line measurements in the monitoring of the pellet coating process.

PubMed

Hudovornik, Grega; Korasa, Klemen; Vrečer, Franc

2015-07-30

Special populations including paediatric and elderly patients often need advanced approaches in treatment, such as one-a-day dosing, which is achieved with modified release formulations or alternative routes of applications such as nasogastric route. Pellets are a dosage form that is frequently used in such formulations. The aim of the present work was to study the applicability of two in-line techniques, namely, Near Infrared Spectroscopy (NIR) and Spatial Filtering Technique (SFT) in the pellet coating process. The first objective of our work was to develop a prediction model for moisture content determination with the in-line NIR and to test its robustness in terms of sensitivity to changes in composition of the pellets and performance in wide range of moisture content. Secondly, the in-line SFT measurement was correlated with different off-line particle size methods. The third objective was to evaluate the ability of both in-line techniques for the detection of undesired deviations during the process, such as pellet attrition and agglomeration. Finally, the ability to predict coating thickness with the in-line NIR probe was evaluated. Results suggested that NIR prediction model for moisture content was less robust outside the calibration range and was also sensitive to changes in composition of the film coating. Nevertheless, satisfactory prediction was achieved in the case when coating composition was partially altered and adequate calibration range was used. The SFT probe results were in good correlation with off-line particle size measurement methods and proved to be an effective tool for coating thickness determination during the coating, however, the probe failed to accurately show the actual amount of the agglomerates formed during the process. In experiment when pellet attrition was initiated, both probes successfully detected abrasion of the pellet surface in real time. Furthermore, a predictive NIR model for coating thickness was made and showed a good potential to measure coating thickness in-line, suggesting that the NIR probe can be used as a single tool to monitor water content, coating thickness, and deviations in the coating process. Copyright © 2015 Elsevier B.V. All rights reserved.

Intellectual Abilities That Discriminate Good and Poor Problem Solvers.

ERIC Educational Resources Information Center

Meyer, Ruth Ann

1981-01-01

This study compared good and poor fourth-grade problem solvers on a battery of 19 "reference" tests for verbal, induction, numerical, word fluency, memory, perceptual speed, and simple visualization abilities. Results suggest verbal, numerical, and especially induction abilities are important to successful mathematical problem solving.…

Toward link predictability of complex networks

PubMed Central

Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H. Eugene

2015-01-01

The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners. PMID:25659742

Prediction of high temperature metal matrix composite ply properties

NASA Technical Reports Server (NTRS)

Caruso, J. J.; Chamis, C. C.

1988-01-01

The application of the finite element method (superelement technique) in conjunction with basic concepts from mechanics of materials theory is demonstrated to predict the thermomechanical behavior of high temperature metal matrix composites (HTMMC). The simulated behavior is used as a basis to establish characteristic properties of a unidirectional composite idealized an as equivalent homogeneous material. The ply properties predicted include: thermal properties (thermal conductivities and thermal expansion coefficients) and mechanical properties (moduli and Poisson's ratio). These properties are compared with those predicted by a simplified, analytical composite micromechanics model. The predictive capabilities of the finite element method and the simplified model are illustrated through the simulation of the thermomechanical behavior of a P100-graphite/copper unidirectional composite at room temperature and near matrix melting temperature. The advantage of the finite element analysis approach is its ability to more precisely represent the composite local geometry and hence capture the subtle effects that are dependent on this. The closed form micromechanics model does a good job at representing the average behavior of the constituents to predict composite behavior.

An evaluation of the predictive performance of distributional models for flora and fauna in north-east New South Wales.

PubMed

Pearce, J; Ferrier, S; Scotts, D

2001-06-01

To use models of species distributions effectively in conservation planning, it is important to determine the predictive accuracy of such models. Extensive modelling of the distribution of vascular plant and vertebrate fauna species within north-east New South Wales has been undertaken by linking field survey data to environmental and geographical predictors using logistic regression. These models have been used in the development of a comprehensive and adequate reserve system within the region. We evaluate the predictive accuracy of models for 153 small reptile, arboreal marsupial, diurnal bird and vascular plant species for which independent evaluation data were available. The predictive performance of each model was evaluated using the relative operating characteristic curve to measure discrimination capacity. Good discrimination ability implies that a model's predictions provide an acceptable index of species occurrence. The discrimination capacity of 89% of the models was significantly better than random, with 70% of the models providing high levels of discrimination. Predictions generated by this type of modelling therefore provide a reasonably sound basis for regional conservation planning. The discrimination ability of models was highest for the less mobile biological groups, particularly the vascular plants and small reptiles. In the case of diurnal birds, poor performing models tended to be for species which occur mainly within specific habitats not well sampled by either the model development or evaluation data, highly mobile species, species that are locally nomadic or those that display very broad habitat requirements. Particular care needs to be exercised when employing models for these types of species in conservation planning.

Cortical Measures of Binaural Processing Predict Spatial Release from Masking Performance

PubMed Central

Papesh, Melissa A.; Folmer, Robert L.; Gallun, Frederick J.

2017-01-01

Binaural sensitivity is an important contributor to the ability to understand speech in adverse acoustical environments such as restaurants and other social gatherings. The ability to accurately report on binaural percepts is not commonly measured, however, as extensive training is required before reliable measures can be obtained. Here, we investigated the use of auditory evoked potentials (AEPs) as a rapid physiological indicator of detection of interaural phase differences (IPDs) by assessing cortical responses to 180° IPDs embedded in amplitude-modulated carrier tones. We predicted that decrements in encoding of IPDs would be evident in middle age, with further declines found with advancing age and hearing loss. Thus, participants in experiment #1 were young to middle-aged adults with relatively good hearing thresholds while participants in experiment #2 were older individuals with typical age-related hearing loss. Results revealed that while many of the participants in experiment #1 could encode IPDs in stimuli up to 1,000 Hz, few of the participants in experiment #2 had discernable responses to stimuli above 750 Hz. These results are consistent with previous studies that have found that aging and hearing loss impose frequency limits on the ability to encode interaural phase information present in the fine structure of auditory stimuli. We further hypothesized that AEP measures of binaural sensitivity would be predictive of participants' ability to benefit from spatial separation between sound sources, a phenomenon known as spatial release from masking (SRM) which depends upon binaural cues. Results indicate that not only were objective IPD measures well correlated with and predictive of behavioral SRM measures in both experiments, but that they provided much stronger predictive value than age or hearing loss. Overall, the present work shows that objective measures of the encoding of interaural phase information can be readily obtained using commonly available AEP equipment, allowing accurate determination of the degree to which binaural sensitivity has been reduced in individual listeners due to aging and/or hearing loss. In fact, objective AEP measures of interaural phase encoding are actually better predictors of SRM in speech-in-speech conditions than are age, hearing loss, or the combination of age and hearing loss. PMID:28377706

Cortical Measures of Binaural Processing Predict Spatial Release from Masking Performance.

PubMed

Papesh, Melissa A; Folmer, Robert L; Gallun, Frederick J

2017-01-01

Binaural sensitivity is an important contributor to the ability to understand speech in adverse acoustical environments such as restaurants and other social gatherings. The ability to accurately report on binaural percepts is not commonly measured, however, as extensive training is required before reliable measures can be obtained. Here, we investigated the use of auditory evoked potentials (AEPs) as a rapid physiological indicator of detection of interaural phase differences (IPDs) by assessing cortical responses to 180° IPDs embedded in amplitude-modulated carrier tones. We predicted that decrements in encoding of IPDs would be evident in middle age, with further declines found with advancing age and hearing loss. Thus, participants in experiment #1 were young to middle-aged adults with relatively good hearing thresholds while participants in experiment #2 were older individuals with typical age-related hearing loss. Results revealed that while many of the participants in experiment #1 could encode IPDs in stimuli up to 1,000 Hz, few of the participants in experiment #2 had discernable responses to stimuli above 750 Hz. These results are consistent with previous studies that have found that aging and hearing loss impose frequency limits on the ability to encode interaural phase information present in the fine structure of auditory stimuli. We further hypothesized that AEP measures of binaural sensitivity would be predictive of participants' ability to benefit from spatial separation between sound sources, a phenomenon known as spatial release from masking (SRM) which depends upon binaural cues. Results indicate that not only were objective IPD measures well correlated with and predictive of behavioral SRM measures in both experiments, but that they provided much stronger predictive value than age or hearing loss. Overall, the present work shows that objective measures of the encoding of interaural phase information can be readily obtained using commonly available AEP equipment, allowing accurate determination of the degree to which binaural sensitivity has been reduced in individual listeners due to aging and/or hearing loss. In fact, objective AEP measures of interaural phase encoding are actually better predictors of SRM in speech-in-speech conditions than are age, hearing loss, or the combination of age and hearing loss.

Capillary Rise: Validity of the Dynamic Contact Angle Models.

PubMed

Wu, Pingkeng; Nikolov, Alex D; Wasan, Darsh T

2017-08-15

The classical Lucas-Washburn-Rideal (LWR) equation, using the equilibrium contact angle, predicts a faster capillary rise process than experiments in many cases. The major contributor to the faster prediction is believed to be the velocity dependent dynamic contact angle. In this work, we investigated the dynamic contact angle models for their ability to correct the dynamic contact angle effect in the capillary rise process. We conducted capillary rise experiments of various wetting liquids in borosilicate glass capillaries and compared the model predictions with our experimental data. The results show that the LWR equations modified by the molecular kinetic theory and hydrodynamic model provide good predictions on the capillary rise of all the testing liquids with fitting parameters, while the one modified by Joos' empirical equation works for specific liquids, such as silicone oils. The LWR equation modified by molecular self-layering model predicts well the capillary rise of carbon tetrachloride, octamethylcyclotetrasiloxane, and n-alkanes with the molecular diameter or measured solvation force data. The molecular self-layering model modified LWR equation also has good predictions on the capillary rise of silicone oils covering a wide range of bulk viscosities with the same key parameter W(0), which results from the molecular self-layering. The advantage of the molecular self-layering model over the other models reveals the importance of the layered molecularly thin wetting film ahead of the main meniscus in the energy dissipation associated with dynamic contact angle. The analysis of the capillary rise of silicone oils with a wide range of bulk viscosities provides new insights into the capillary dynamics of polymer melts.

Modeling and sliding mode predictive control of the ultra-supercritical boiler-turbine system with uncertainties and input constraints.

PubMed

Tian, Zhen; Yuan, Jingqi; Zhang, Xiang; Kong, Lei; Wang, Jingcheng

2018-05-01

The coordinated control system (CCS) serves as an important role in load regulation, efficiency optimization and pollutant reduction for coal-fired power plants. The CCS faces with tough challenges, such as the wide-range load variation, various uncertainties and constraints. This paper aims to improve the load tacking ability and robustness for boiler-turbine units under wide-range operation. To capture the key dynamics of the ultra-supercritical boiler-turbine system, a nonlinear control-oriented model is developed based on mechanism analysis and model reduction techniques, which is validated with the history operation data of a real 1000 MW unit. To simultaneously address the issues of uncertainties and input constraints, a discrete-time sliding mode predictive controller (SMPC) is designed with the dual-mode control law. Moreover, the input-to-state stability and robustness of the closed-loop system are proved. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves good tracking performance, disturbance rejection ability and compatibility to input constraints. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Time to first cigarette in the morning as an index of ability to quit smoking: Implications for nicotine dependence

PubMed Central

Baker, Timothy B.; Piper, Megan E.; McCarthy, Danielle E.; Bolt, Daniel M.; Smith, Stevens S.; Kim, Su-Young; Colby, Suzanne; Conti, David; Giovino, Gary A.; Hatsukami, Dorothy; Hyland, Andrew; Krishnan-Sarin, Suchitra; Niaura, Raymond; Perkins, Kenneth A.; Toll, Benjamin A.

2010-01-01

An inability to maintain abstinence is a key indicator of tobacco dependence. Unfortunately, little evidence exists regarding the ability of the major tobacco dependence measures to predict smoking cessation outcome. This paper used data from four placebo-controlled smoking cessation trials and one international epidemiologic study to determine relations between the Fagerström Test for Nicotine Dependence (FTND; Heatherton et al., 1991), the Heaviness of Smoking Index (HSI; Kozlowski et al., 1994), the Nicotine Dependence Syndrome Scale (NDSS; Shiffman et al., 2004) and the Wisconsin Inventory of Smoking Dependence Motives (WISDM; Piper et al. 2004) with cessation success. Results showed that much of the predictive validity of the FTND could be attributed to its first item, time to first cigarette in the morning, and this item had greater validity than any other single measure. Thus, the time to first cigarette item appears to tap a pattern of heavy, uninterrupted, and automatic smoking and may be a good single-item measure of nicotine dependence. PMID:18067032

Experimental and analytical study of loss-of-flow transients in EBR-II occurring at decay power levels

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

Chang, L.K.; Mohr, D.; Feldman, E.E.

A series of eight loss-of-flow (LOF) tests have been conducted in EBR-II to study the transition between forced and natural convective flows following a variety of loss-of-primary-pumping power conditions from decay heat levels. Comparisons of measurements and pretest/posttest predictions were made on a selected test. Good agreements between measurements and predictions was found prior to and just after the flow reaching its minimum, but the agreement is not as good after that point. The temperatures are consistent with the flow response and the assumed decay power. The measured results indicate that the flows of driver and the instrumented subassemblies aremore » too much in the analytical model in the natural convective region. Although a parametric study on secondary flow, turbulent-laminar flow transition, heat transfer ability of the intermediate heat exchange at low flow and flow mixing in the primary tank has been performed to determine their effects on the flow, the cause of the discrepancy at very low flow level is still unknown.« less

Computer-aided design of negative allosteric modulators of metabotropic glutamate receptor 5 (mGluR5): Comparative molecular field analysis of aryl ether derivatives.

PubMed

Selvam, Chelliah; Thilagavathi, Ramasamy; Narasimhan, Balasubramanian; Kumar, Pradeep; Jordan, Brian C; Ranganna, Kasturi

2016-02-15

The metabotropic glutamate receptors (mGlu receptors) have emerged as attractive targets for number of neurological and psychiatric disorders. Recently, mGluR5 negative allosteric modulators (NAMs) have gained considerable attention in pharmacological research. Comparative molecular field analysis (CoMFA) was performed on 73 analogs of aryl ether which were reported as mGluR5 NAMs. The study produced a statistically significant model with high correlation coefficient and good predictive abilities. Published by Elsevier Ltd.

Analogue based design of MMP-13 (Collagenase-3) inhibitors.

PubMed

Sarma, J A R P; Rambabu, G; Srikanth, K; Raveendra, D; Vithal, M

2002-10-07

3D-QSAR studies using MFA and RSA methods were performed on a series of 39MMP-13 inhibitors. Model developed by MFA method has a r(2)(cv) (cross-validated) of 0.616 while its r(2) (conventional) value is 0.822. For the RSA model r(2)(cv) and r(2) are 0.681 and 0.847, respectively. Both the models indicate good internal as well as external predictive abilities. These models provide crucial information about the field descriptors for the design of potential inhibitors of MMP-13.

Control your inventory in a world of lean retailing.

PubMed

Abernathy, F H; Dunlop, J T; Hammond, J H; Weil, D

2000-01-01

As retailers adopt lean retailing practices, manufacturers are feeling the pinch. Retailers no longer place large seasonal orders for goods in advance-instead, they require ongoing replenishment of stock, forcing manufacturers to predict demand and then hold substantial inventories indefinitely. Manufacturers now carry the cost of inventory risk--the possibility that demand will dry up and goods will have to be sold below cost. And as product proliferation increases, customer demand becomes harder to predict. Most manufacturers apply one inventory policy for all stock-keeping units in a product line. But the inventory demand for SKUs within the same product line can vary significantly. SKUs with high volume typically have little variation in weekly sales, while slow-selling SKUs can vary enormously in weekly sales. The greater the variation, the larger the inventory the manufacturer must hold relative to an SKU's expected weekly sales. By differentiating inventory policies at the SKU level, manufacturers can reduce inventories for the high-volume SKUs and increase them for the low-volume ones--and thereby improve the profit-ability of the entire line. SKU-level differentiation can also be applied to sourcing strategies. Instead of producing all the SKUs for a product line at a single location, either offshore at low cost or close to market at higher cost, manufacturers can typically do better by going for a mixed allocation. Low-variation goods should be produced mainly offshore, while high-variation goods are best made close to markets.

Computational modeling of in vitro biological responses on polymethacrylate surfaces

PubMed Central

Ghosh, Jayeeta; Lewitus, Dan Y; Chandra, Prafulla; Joy, Abraham; Bushman, Jared; Knight, Doyle; Kohn, Joachim

2011-01-01

The objective of this research was to examine the capabilities of QSPR (Quantitative Structure Property Relationship) modeling to predict specific biological responses (fibrinogen adsorption, cell attachment and cell proliferation index) on thin films of different polymethacrylates. Using 33 commercially available monomers it is theoretically possible to construct a library of over 40,000 distinct polymer compositions. A subset of these polymers were synthesized and solvent cast surfaces were prepared in 96 well plates for the measurement of fibrinogen adsorption. NIH 3T3 cell attachment and proliferation index were measured on spin coated thin films of these polymers. Based on the experimental results of these polymers, separate models were built for homo-, co-, and terpolymers in the library with good correlation between experiment and predicted values. The ability to predict biological responses by simple QSPR models for large numbers of polymers has important implications in designing biomaterials for specific biological or medical applications. PMID:21779132

Development of a recursion RNG-based turbulence model

NASA Technical Reports Server (NTRS)

Zhou, YE; Vahala, George; Thangam, S.

1993-01-01

Reynolds stress closure models based on the recursion renormalization group theory are developed for the prediction of turbulent separated flows. The proposed model uses a finite wavenumber truncation scheme to account for the spectral distribution of energy. In particular, the model incorporates effects of both local and nonlocal interactions. The nonlocal interactions are shown to yield a contribution identical to that from the epsilon-renormalization group (RNG), while the local interactions introduce higher order dispersive effects. A formal analysis of the model is presented and its ability to accurately predict separated flows is analyzed from a combined theoretical and computational stand point. Turbulent flow past a backward facing step is chosen as a test case and the results obtained based on detailed computations demonstrate that the proposed recursion -RNG model with finite cut-off wavenumber can yield very good predictions for the backstep problem.

Mathematical modeling of ethanol production in solid-state fermentation based on solid medium' dry weight variation.

PubMed

Mazaheri, Davood; Shojaosadati, Seyed Abbas; Zamir, Seyed Morteza; Mousavi, Seyyed Mohammad

2018-04-21

In this work, mathematical modeling of ethanol production in solid-state fermentation (SSF) has been done based on the variation in the dry weight of solid medium. This method was previously used for mathematical modeling of enzyme production; however, the model should be modified to predict the production of a volatile compound like ethanol. The experimental results of bioethanol production from the mixture of carob pods and wheat bran by Zymomonas mobilis in SSF were used for the model validation. Exponential and logistic kinetic models were used for modeling the growth of microorganism. In both cases, the model predictions matched well with the experimental results during the exponential growth phase, indicating the good ability of solid medium weight variation method for modeling a volatile product formation in solid-state fermentation. In addition, using logistic model, better predictions were obtained.

Analysis of moment structures for assessing relationships among perceived chewing ability, dentition status, muscle strength, and balance in community-dwelling older adults.

PubMed

Moriya, Shingo; Notani, Kenji; Murata, Ayumi; Inoue, Nobuo; Miura, Hiroko

2014-12-01

The aim of this study was to assess relationships among perceived chewing ability, dentition status, muscle strength and balance in community-dwelling older adults using analysis of moment structures (Amos). Physical performance parameters such as muscle strength and balance can predict the future onset of disabilities in activities of daily living among older adults. In this context, elucidation of the relationships among oral conditions and physical performance parameters is necessary. Data on occlusal contact patterns of natural teeth (OPNT), self-assessed masticatory ability (mastication), body mass index (BMI), handgrip strength (HG) and one-leg standing time with eyes open (OLST) were collected from 501 independently living adults aged 65-74 years. The relationships among these parameters were analysed using Spearman's rank correlation coefficients and Amos. Subjects of both genders showed significant correlations among OPNT, mastication, HG and OLST, evaluated using Spearman's rank correlation coefficients. For each Amos model, the goodness-of-fit statistic indicated a good level of fit. In both men and women, OPNT was significantly related to mastication, and mastication was related to HG but not to OLST. OPNT was related to neither HG nor OLST in women and was related to OLST but not HG in men. The findings observed in this study present a possible importance of dental status and perceived chewing ability for the onset of disability by influencing physical performance in community-dwelling older adults. © 2012 The Gerodontology Society and John Wiley & Sons A/S.

Evaluating the ability of artificial neural network and PCA-M5P models in predicting leachate COD load in landfills.

PubMed

Azadi, Sama; Amiri, Hamid; Rakhshandehroo, G Reza

2016-09-01

Waste burial in uncontrolled landfills can cause serious environmental damages and unpleasant consequences. Leachates produced in landfills have the potential to contaminate soil and groundwater resources. Leachate management is one of the major issues with respect to landfills environmental impacts. Improper design of landfills can lead to leachate spread in the environment, and hence, engineered landfills are required to have leachate monitoring programs. The high cost of such programs may be greatly reduced and cost efficiency of the program may be optimized if one can predict leachate contamination level and foresee management and treatment strategies. The aim of this study is to develop two expert systems consisting of Artificial Neural Network (ANN) and Principal Component Analysis-M5P (PCA-M5P) models to predict Chemical Oxygen Demand (COD) load in leachates produced in lab-scale landfills. Measured data from three landfill lysimeters, including rainfall depth, number of days after waste deposition, thickness of top and bottom Compacted Clay Liners (CCLs), and thickness of top cover over the lysimeter, were utilized to develop, train, validate, and test the expert systems and predict the leachate COD load. Statistical analysis of the prediction results showed that both models possess good prediction ability with a slight superiority for ANN over PCA-M5P. Based on test datasets, the mean absolute percentage error for ANN and PCA-M5P models were 4% and 12%, respectively, and the correlation coefficient for both models was greater than 0.98. Developed models may be used as a rough estimate for leachate COD load prediction in primary landfill designs, where the effect of a top and/or bottom liner is disputed. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Non-invasive fibrosis indexes in predicting acute liver function deterioration after transcatheter arterial chemoembolization].

PubMed

Song, Y P; Zhao, Q Y; Li, S; Wang, H; Wu, P H

2016-03-08

To investigate the ability of two non-invasive fibrosis indexes-APRI, i. e. aspartate transaminase (AST) to platelet (PLT) ratio index, and fibrosis index based on the 4 factors (FIB-4)score in predicting ALFD in patients with unresectable primary HCC and underwent TACE. Clinical data of those patients treated with TACE in Department of Interventional Radiology of the Center from Jan 2010 to Aug 2014 were investigated retrospectively. A total of 366 cases were enrolled after randomized selection, 62 (18.5%) of which developed ALFD after TACE. Child-Pugh score, APRI and FIB-4 score in every case were calculated, receiver operating characteristic (ROC) curve of each model were performed and the predictive abilities of them were assessed by area under the curve (AUC), positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity. The AUC of Child-Pugh score, APRI and FIB-4 score were 0.783, 0.752 and 0.758 respectively, while the difference had no significance in statistics, indicating that predictive accuracies of them were similar. APRI≤1.15 and FIB-4≤3.08 had better NPV (90.6% and 93.6%) and sensitivity (65.6% and 80.0%) than Child-Pugh score>6 (NPV=85.8%, sensitivity=27.4%), PPV and specificity of them are 35.7%, 32.9%, 89.5% and 73.7%, 64.2%, 99.3% respectively. Comparing to Child-Pugh score, APRI and FIB-4 score have similar accuracy but better NPV and sensitivity in predicting post-TACE ALFD. Thereafter they are good for selection of low-risk patients for TACE treatment. Candidates with an APRI≤1.15 or a FIB-4≤3.08 or in Child-Pugh a stage are unlikely to develop ALFD thus could receive TACE safely.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

NASA Astrophysics Data System (ADS)

Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

2012-08-01

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

An Empiric HIV Risk Scoring Tool to Predict HIV-1 Acquisition in African Women.

PubMed

Balkus, Jennifer E; Brown, Elizabeth; Palanee, Thesla; Nair, Gonasagrie; Gafoor, Zakir; Zhang, Jingyang; Richardson, Barbra A; Chirenje, Zvavahera M; Marrazzo, Jeanne M; Baeten, Jared M

2016-07-01

To develop and validate an HIV risk assessment tool to predict HIV acquisition among African women. Data were analyzed from 3 randomized trials of biomedical HIV prevention interventions among African women (VOICE, HPTN 035, and FEM-PrEP). We implemented standard methods for the development of clinical prediction rules to generate a risk-scoring tool to predict HIV acquisition over the course of 1 year. Performance of the score was assessed through internal and external validations. The final risk score resulting from multivariable modeling included age, married/living with a partner, partner provides financial or material support, partner has other partners, alcohol use, detection of a curable sexually transmitted infection, and herpes simplex virus 2 serostatus. Point values for each factor ranged from 0 to 2, with a maximum possible total score of 11. Scores ≥5 were associated with HIV incidence >5 per 100 person-years and identified 91% of incident HIV infections from among only 64% of women. The area under the curve (AUC) for predictive ability of the score was 0.71 (95% confidence interval [CI]: 0.68 to 0.74), indicating good predictive ability. Risk score performance was generally similar with internal cross-validation (AUC = 0.69; 95% CI: 0.66 to 0.73) and external validation in HPTN 035 (AUC = 0.70; 95% CI: 0.65 to 0.75) and FEM-PrEP (AUC = 0.58; 95% CI: 0.51 to 0.65). A discrete set of characteristics that can be easily assessed in clinical and research settings was predictive of HIV acquisition over 1 year. The use of a validated risk score could improve efficiency of recruitment into HIV prevention research and inform scale-up of HIV prevention strategies in women at highest risk.

Using the Johns Hopkins' Aggregated Diagnosis Groups (ADGs) to predict 1-year mortality in population-based cohorts of patients with diabetes in Ontario, Canada.

PubMed

Austin, P C; Shah, B R; Newman, A; Anderson, G M

2012-09-01

There are limited validated methods to ascertain comorbidities for risk adjustment in ambulatory populations of patients with diabetes using administrative health-care databases. The objective was to examine the ability of the Johns Hopkins' Aggregated Diagnosis Groups to predict mortality in population-based ambulatory samples of both incident and prevalent subjects with diabetes. Retrospective cohorts constructed using population-based administrative data. The incident cohort consisted of all 346,297 subjects diagnosed with diabetes between 1 April 2004 and 31 March 2008. The prevalent cohort consisted of all 879,849 subjects with pre-existing diabetes on 1 January, 2007. The outcome was death within 1 year of the subject's index date. A logistic regression model consisting of age, sex and indicator variables for 22 of the 32 Johns Hopkins' Aggregated Diagnosis Group categories had excellent discrimination for predicting mortality in incident diabetes patients: the c-statistic was 0.87 in an independent validation sample. A similar model had excellent discrimination for predicting mortality in prevalent diabetes patients: the c-statistic was 0.84 in an independent validation sample. Both models demonstrated very good calibration, denoting good agreement between observed and predicted mortality across the range of predicted mortality in which the large majority of subjects lay. For comparative purposes, regression models incorporating the Charlson comorbidity index, age and sex, age and sex, and age alone had poorer discrimination than the model that incorporated the Johns Hopkins' Aggregated Diagnosis Groups. Logistical regression models using age, sex and the John Hopkins' Aggregated Diagnosis Groups were able to accurately predict 1-year mortality in population-based samples of patients with diabetes. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

The Implementation of "The n-term" Formula to Improve Student Ability in Determining the Rules of a Numeric Sequence

ERIC Educational Resources Information Center

In'am, Akhsanul; Hajar, Siti

2013-01-01

A good-quality teacher may determines a good-quality learning, thus good-quality students will be the results. In order to have a good-quality learning, a lot of strategies and methods can be adopted. The objective of this research is to improve students' ability in determining the rules of a numeric sequence and analysing the effectiveness of the…

Estimated glomerular filtration rate is an early biomarker of cardiac surgery-associated acute kidney injury.

PubMed

Candela-Toha, Ángel; Pardo, María Carmen; Pérez, Teresa; Muriel, Alfonso; Zamora, Javier

2018-04-20

and objective Acute kidney injury (AKI) diagnosis is still based on serum creatinine and diuresis. However, increases in creatinine are typically delayed 48h or longer after injury. Our aim was to determine the utility of routine postoperative renal function blood tests, to predict AKI one or 2days in advance in a cohort of cardiac surgery patients. Using a prospective database, we selected a sample of patients who had undergone major cardiac surgery between January 2002 and December 2013. The ability of the parameters to predict AKI was based on Acute Kidney Injury Network serum creatinine criteria. A cohort of 3,962 cases was divided into 2groups of similar size, one being exploratory and the other a validation sample. The exploratory group was used to show primary objectives and the validation group to confirm results. The ability to predict AKI of several kidney function parameters measured in routine postoperative blood tests, was measured with time-dependent ROC curves. The primary endpoint was time from measurement to AKI diagnosis. AKI developed in 610 (30.8%) and 623 (31.4%) patients in the exploratory and validation samples, respectively. Estimated glomerular filtration rate using the MDRD-4 equation showed the best AKI prediction capacity, with values for the AUC ROC curves between 0.700 and 0.946. We obtained different cut-off values for estimated glomerular filtration rate depending on the degree of AKI severity and on the time elapsed between surgery and parameter measurement. Results were confirmed in the validation sample. Postoperative estimated glomerular filtration rate using the MDRD-4 equation showed good ability to predict AKI following cardiac surgery one or 2days in advance. Copyright © 2018 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

External validation of the simple clinical score and the HOTEL score, two scores for predicting short-term mortality after admission to an acute medical unit.

PubMed

Stræde, Mia; Brabrand, Mikkel

2014-01-01

Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Pre-planned prospective observational cohort study. Danish 460-bed regional teaching hospital. We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774-0.879) for 30-day mortality, and goodness-of-fit test, χ(2) = 2.68 (10 degrees of freedom), P = 0.998 and χ(2) = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901-0.962) for 24-hours mortality and goodness-of-fit test, χ(2) = 5.56 (10 degrees of freedom), P = 0.234. We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision.

A valid model for predicting responsible nerve roots in lumbar degenerative disease with diagnostic doubt.

PubMed

Li, Xiaochuan; Bai, Xuedong; Wu, Yaohong; Ruan, Dike

2016-03-15

To construct and validate a model to predict responsible nerve roots in lumbar degenerative disease with diagnostic doubt (DD). From January 2009-January 2013, 163 patients with DD were assigned to the construction (n = 106) or validation sample (n = 57) according to different admission times to hospital. Outcome was assessed according to the Japanese Orthopedic Association (JOA) recovery rate as excellent, good, fair, and poor. The first two results were considered as effective clinical outcome (ECO). Baseline patient and clinical characteristics were considered as secondary variables. A multivariate logistic regression model was used to construct a model with the ECO as a dependent variable and other factors as explanatory variables. The odds ratios (ORs) of each risk factor were adjusted and transformed into a scoring system. Area under the curve (AUC) was calculated and validated in both internal and external samples. Moreover, calibration plot and predictive ability of this scoring system were also tested for further validation. Patients with DD with ECOs in both construction and validation models were around 76 % (76.4 and 75.5 % respectively). more preoperative visual analog pain scale (VAS) score (OR = 1.56, p < 0.01), stenosis levels of L4/5 or L5/S1 (OR = 1.44, p = 0.04), stenosis locations with neuroforamen (OR = 1.95, p = 0.01), neurological deficit (OR = 1.62, p = 0.01), and more VAS improvement of selective nerve route block (SNRB) (OR = 3.42, p = 0.02). the internal area under the curve (AUC) was 0.85, and the external AUC was 0.72, with a good calibration plot of prediction accuracy. Besides, the predictive ability of ECOs was not different from the actual results (p = 0.532). We have constructed and validated a predictive model for confirming responsible nerve roots in patients with DD. The associated risk factors were preoperative VAS score, stenosis levels of L4/5 or L5/S1, stenosis locations with neuroforamen, neurological deficit, and VAS improvement of SNRB. A tool such as this is beneficial in the preoperative counseling of patients, shared surgical decision making, and ultimately improving safety in spine surgery.

The Theory of Planned Behavior as a Model of Heavy Episodic Drinking Among College Students

PubMed Central

Collins, Susan E.; Carey, Kate B.

2008-01-01

This study provided a simultaneous, confirmatory test of the theory of planned behavior (TPB) in predicting heavy episodic drinking (HED) among college students. It was hypothesized that past HED, drinking attitudes, subjective norms and drinking refusal self-efficacy would predict intention, which would in turn predict future HED. Participants consisted of 131 college drinkers (63% female) who reported having engaged in HED in the previous two weeks. Participants were recruited and completed questionnaires within the context of a larger intervention study (see Collins & Carey, 2005). Latent factor structural equation modeling was used to test the ability of the TPB to predict HED. Chi-square tests and fit indices indicated good fit for the final structural models. Self-efficacy and attitudes but not subjective norms significantly predicted baseline intention, and intention and past HED predicted future HED. Contrary to hypotheses, however, a structural model excluding past HED provided a better fit than a model including it. Although further studies must be conducted before a definitive conclusion is reached, a TPB model excluding past behavior, which is arguably more parsimonious and theory driven, may provide better prediction of HED among college drinkers than a model including past behavior. PMID:18072832

Elastic properties of graphene: A pseudo-beam model with modified internal bending moment and its application

NASA Astrophysics Data System (ADS)

Xia, Z. M.; Wang, C. G.; Tan, H. F.

2018-04-01

A pseudo-beam model with modified internal bending moment is presented to predict elastic properties of graphene, including the Young's modulus and Poisson's ratio. In order to overcome a drawback in existing molecular structural mechanics models, which only account for pure bending (constant bending moment), the presented model accounts for linear bending moments deduced from the balance equations. Based on this pseudo-beam model, an analytical prediction is accomplished to predict the Young's modulus and Poisson's ratio of graphene based on the equation of the strain energies by using Castigliano second theorem. Then, the elastic properties of graphene are calculated compared with results available in literature, which verifies the feasibility of the pseudo-beam model. Finally, the pseudo-beam model is utilized to study the twisting wrinkling characteristics of annular graphene. Due to modifications of the internal bending moment, the wrinkling behaviors of graphene sheet are predicted accurately. The obtained results show that the pseudo-beam model has a good ability to predict the elastic properties of graphene accurately, especially the out-of-plane deformation behavior.

Development of polyparameter linear free energy relationship models for octanol-air partition coefficients of diverse chemicals.

PubMed

Jin, Xiaochen; Fu, Zhiqiang; Li, Xuehua; Chen, Jingwen

2017-03-22

The octanol-air partition coefficient (K OA ) is a key parameter describing the partition behavior of organic chemicals between air and environmental organic phases. As the experimental determination of K OA is costly, time-consuming and sometimes limited by the availability of authentic chemical standards for the compounds to be determined, it becomes necessary to develop credible predictive models for K OA . In this study, a polyparameter linear free energy relationship (pp-LFER) model for predicting K OA at 298.15 K and a novel model incorporating pp-LFERs with temperature (pp-LFER-T model) were developed from 795 log K OA values for 367 chemicals at different temperatures (263.15-323.15 K), and were evaluated with the OECD guidelines on QSAR model validation and applicability domain description. Statistical results show that both models are well-fitted, robust and have good predictive capabilities. Particularly, the pp-LFER model shows a strong predictive ability for polyfluoroalkyl substances and organosilicon compounds, and the pp-LFER-T model maintains a high predictive accuracy within a wide temperature range (263.15-323.15 K).

Thinking and feeling in the People's Republic of China: testing the generality of the "laws of emotion".

PubMed

Brown, Jonathon D; Cai, Huajian

2010-04-01

Cognitive theories of emotion assert that emotional reactions to events depend on the manner in which events are interpreted and appraised. From this perspective, the same outcome can produce different emotions. For example, a score of 85% on a test can evoke positive feelings if it is considered a success or negative feelings if it is considered a failure. Among the various appraisal dimensions that have been identified, causal attributions are thought to play a particularly influential role in shaping emotional reactions to various events. For example, success can evoke pride if it is attributed to high ability, gratitude if it is attributed to help from others, relief if it is attributed to a stroke of good fortune, or guilt if it is attained fraudulently or at the expense of others. These cognitive-affective linkages are thought to be universal. In this paper, we report two studies that tested the cross-cultural generality of some of these assumptions. In Study 1, participants from the People's Republic of China were led to succeed or fail on an (alleged) test of their intelligence and creativity. Consistent with previous findings with Western samples, attributions to ability predicted participants' emotional reactions to their test performance, with high ability attributions linked to greater pride following success. In Study 2, we extended these findings with American and Chinese participants, using a different experimental manipulation of success and failure, and a measure of attributions to effort. For both cultural groups, attributions to ability (but not attributions to effort) predicted greater emotional reactions to success. We conclude that attribution-emotion linkages have cross-cultural validity, and that pride is maximized when success is attributed to high ability.

"Are the Good Beautiful or the Beautiful Good?" The Relationship between Children's Perceptions of Ability and Perceptions of Physical Attractiveness.

ERIC Educational Resources Information Center

Felson, Richard B.; Bohrnstedt, George W.

1979-01-01

Children's ratings were obtained, examining reciprocal feedback between perceptions of physical attractiveness and ability. Data supported the conclusion that perceptions of ability affect those of physical attractiveness but not vice versa. The role of the relative ambiguity of stimuli associated with physical attractiveness may explain the…

Breastfeeding Self-Efficacy Scale: Validation of the Italian Version and Correlation With Breast-feeding at 3 Months.

PubMed

Petrozzi, Angela; Gagliardi, Luigi

2016-01-01

Psychological factors can influence breast-feeding. We translated into Italian and validated the Breastfeeding Self-Efficacy Scale Short Form (BSES-SF) and investigated its predictive ability and its relation with postpartum depression symptoms.BSES-SF and Edinburgh Postnatal Depression Scale (EPDS) were administered 2 to 3 days after delivery to 122 mothers. Breast-feeding was assessed at 3 months.The BSES-SF displayed good validity (receiver operating characteristic area = 0.69) for predicting full breast-feeding at 3 months. In multivariate analysis, the probability of full breast-feeding increased 2.4% for 1-point increase of BSES-SF. The BSES-SF and EPDS scores were inversely correlated. BSES-SF is a useful tool to identify the risk of early breast-feeding attrition.

Electrodermal reactivity and its association to substance use disorders.

PubMed

Taylor, Jeanette

2004-11-01

Poor electrodermal response modulation is associated with substance use disorders, but the specificity of the relationship has not been tested. To test this, 112 college students were assessed for psychiatric symptoms using structured interviews and for ability to modulate skin conductance responses to 2-s 92- or 110-dB white noise blasts that varied in temporal predictability. Twenty-eight good and 28 poor modulators were compared on symptoms of alcohol and illicit drug use disorders, personality disorders (antisocial, borderline, histrionic, and narcissistic), social and specific phobia, and depression. As expected, poor modulators had significantly more symptoms of substance use disorders than good modulators. Groups did not differ in symptoms of anxiety disorder, depression, or personality disorders marked by disinhibition. Poor electrodermal response modulation may reflect a biological risk factor for substance use disorders in particular.

SOX9 as a Predictor for Neurogenesis Potentiality of Amniotic Fluid Stem Cells

PubMed Central

Wei, Pei-Cih; Chao, Angel; Peng, Hsiu-Huei; Chao, An-Shine; Chang, Yao-Lung; Chang, Shuenn-Dyh; Wang, Hsin-Shih; Chang, Yu-Jen; Tsai, Ming-Song; Sieber, Martin; Chen, Hua-Chien; Chen, Shu-Jen; Lee, Yun-Shien

2014-01-01

Preclinical studies of amniotic fluid-derived cell therapy have been successful in the research of neurodegenerative diseases, peripheral nerve injury, spinal cord injury, and brain ischemia. Transplantation of human amniotic fluid stem cells (AFSCs) into rat brain ventricles has shown improvement in symptoms of Parkinson's disease and also highlighted the minimal immune rejection risk of AFSCs, even between species. Although AFSCs appeared to be a promising resource for cell-based regenerative therapy, AFSCs contain a heterogeneous pool of distinct cell types, rendering each preparation of AFSCs unique. Identification of predictive markers for neuron-prone AFSCs is necessary before such stem cell-based therapeutics can become a reality. In an attempt to identify markers of AFSCs to predict their ability for neurogenesis, we performed a two-phase study. In the discovery phase of 23 AFSCs, we tested ZNF521/Zfp521, OCT6, SOX1, SOX2, SOX3, and SOX9 as predictive markers of AFSCs for neural differentiation. In the validation phase, the efficacy of these predictive markers was tested in independent sets of 18 AFSCs and 14 dental pulp stem cells (DPSCs). We found that high expression of SOX9 in AFSCs is associated with good neurogenetic ability, and these positive correlations were confirmed in independent sets of AFSCs and DPSCs. Furthermore, knockdown of SOX9 in AFSCs inhibited their neuronal differentiation. In conclusion, the discovery of SOX9 as a predictive marker for neuron-prone AFSCs could expedite the selection of useful clones for regenerative medicine, in particular, in neurological diseases and injuries. PMID:25154783

Ability-performance relationships in education and employment settings: critical tests of the more-is-better and the good-enough hypotheses.

PubMed

Arneson, Justin J; Sackett, Paul R; Beatty, Adam S

2011-10-01

The nature of the relationship between ability and performance is of critical importance for admission decisions in the context of higher education and for personnel selection. Although previous research has supported the more-is-better hypothesis by documenting linearity of ability-performance relationships, such research has not been sensitive enough to detect deviations at the top ends of the score distributions. An alternative position receiving considerable attention is the good-enough hypothesis, which suggests that although higher levels of ability may result in better performance up to a threshold, above this threshold greater ability does not translate to better performance. In this study, the nature of the relationship between cognitive ability and performance was examined throughout the score range in four large-scale data sets. Monotonicity was maintained in all instances. Contrary to the good-enough hypothesis, the ability-performance relationship was commonly stronger at the top end of the score distribution than at the bottom end.

Prediction of acute kidney injury within 30 days of cardiac surgery.

PubMed

Ng, Shu Yi; Sanagou, Masoumeh; Wolfe, Rory; Cochrane, Andrew; Smith, Julian A; Reid, Christopher Michael

2014-06-01

To predict acute kidney injury after cardiac surgery. The study included 28,422 cardiac surgery patients who had had no preoperative renal dialysis from June 2001 to June 2009 in 18 hospitals. Logistic regression analyses were undertaken to identify the best combination of risk factors for predicting acute kidney injury. Two models were developed, one including the preoperative risk factors and another including the pre-, peri-, and early postoperative risk factors. The area under the receiver operating characteristic curve was calculated, using split-sample internal validation, to assess model discrimination. The incidence of acute kidney injury was 5.8% (1642 patients). The mortality for patients who experienced acute kidney injury was 17.4% versus 1.6% for patients who did not. On validation, the area under the curve for the preoperative model was 0.77, and the Hosmer-Lemeshow goodness-of-fit P value was .06. For the postoperative model area under the curve was 0.81 and the Hosmer-Lemeshow P value was .6. Both models had good discrimination and acceptable calibration. Acute kidney injury after cardiac surgery can be predicted using preoperative risk factors alone or, with greater accuracy, using pre-, peri-, and early postoperative risk factors. The ability to identify high-risk individuals can be useful in preoperative patient management and for recruitment of appropriate patients to clinical trials. Prediction in the early stages of postoperative care can guide subsequent intensive care of patients and could also be the basis of a retrospective performance audit tool. Copyright © 2014 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

Diet Quality Scores and Prediction of All-Cause, Cardiovascular and Cancer Mortality in a Pan-European Cohort Study

PubMed Central

Lassale, Camille; Gunter, Marc J.; Romaguera, Dora; Peelen, Linda M.; Van der Schouw, Yvonne T.; Beulens, Joline W. J.; Freisling, Heinz; Muller, David C.; Ferrari, Pietro; Huybrechts, Inge; Fagherazzi, Guy; Boutron-Ruault, Marie-Christine; Affret, Aurélie; Overvad, Kim; Dahm, Christina C.; Olsen, Anja; Roswall, Nina; Tsilidis, Konstantinos K.; Katzke, Verena A.; Kühn, Tilman; Buijsse, Brian; Quirós, José-Ramón; Sánchez-Cantalejo, Emilio; Etxezarreta, Nerea; Huerta, José María; Barricarte, Aurelio; Bonet, Catalina; Khaw, Kay-Tee; Key, Timothy J.; Trichopoulou, Antonia; Bamia, Christina; Lagiou, Pagona; Palli, Domenico; Agnoli, Claudia; Tumino, Rosario; Fasanelli, Francesca; Panico, Salvatore; Bueno-de-Mesquita, H. Bas; Boer, Jolanda M. A.; Sonestedt, Emily; Nilsson, Lena Maria; Renström, Frida; Weiderpass, Elisabete; Skeie, Guri; Lund, Eiliv; Moons, Karel G. M.; Riboli, Elio; Tzoulaki, Ioanna

2016-01-01

Scores of overall diet quality have received increasing attention in relation to disease aetiology; however, their value in risk prediction has been little examined. The objective was to assess and compare the association and predictive performance of 10 diet quality scores on 10-year risk of all-cause, CVD and cancer mortality in 451,256 healthy participants to the European Prospective Investigation into Cancer and Nutrition, followed-up for a median of 12.8y. All dietary scores studied showed significant inverse associations with all outcomes. The range of HRs (95% CI) in the top vs. lowest quartile of dietary scores in a composite model including non-invasive factors (age, sex, smoking, body mass index, education, physical activity and study centre) was 0.75 (0.72–0.79) to 0.88 (0.84–0.92) for all-cause, 0.76 (0.69–0.83) to 0.84 (0.76–0.92) for CVD and 0.78 (0.73–0.83) to 0.91 (0.85–0.97) for cancer mortality. Models with dietary scores alone showed low discrimination, but composite models also including age, sex and other non-invasive factors showed good discrimination and calibration, which varied little between different diet scores examined. Mean C-statistic of full models was 0.73, 0.80 and 0.71 for all-cause, CVD and cancer mortality. Dietary scores have poor predictive performance for 10-year mortality risk when used in isolation but display good predictive ability in combination with other non-invasive common risk factors. PMID:27409582

The relationship between wisdom and abstinence behaviors in women in recovery from substance abuse.

PubMed

Digangi, Julia A; Jason, Leonard A; Mendoza, Leslie; Miller, Steve A; Contreras, Richard

2013-01-01

Wisdom is theorized to be an important construct in recovery from substance abuse. In order to explore the role of wisdom in substance abuse recovery behaviors, the present study had two goals. First, it sought to examine the factor structure of a wisdom scale, the Foundational Value Scale (FVS) in a community sample of women in recovery from substance abuse. Second, the study examined how wisdom predicted the women's beliefs about their ability to abstain from future substance use. 116 women in recovery from substance abuse disorders were recruited from self-run recovery homes and a substance abuse recovery convention. Results from an exploratory factor analysis indicated that a modified version of the FVS has good internal consistency reliability and is composed of three wisdom-related dimensions. The three factors were then used to create a higher-order wisdom factor in a structural equation model (SEM) that was used to predict abstinence self-efficacy behaviors. Results from the SEM showed that the wisdom factor was predictive of greater abstinence self-efficacy behaviors. The FVS was found to be a reliable measure with women in recovery from substance abuse. In addition, wisdom predicted beliefs about self-efficacy such that those who reported higher levels of wisdom felt more confident in their abilities to abstain from alcohol. The results of this study indicate that wisdom is an important construct in the abstinence behaviors of women who are in recovery from substance abuse disorders.

A novel risk score model for prediction of contrast-induced nephropathy after emergent percutaneous coronary intervention.

PubMed

Lin, Kai-Yang; Zheng, Wei-Ping; Bei, Wei-Jie; Chen, Shi-Qun; Islam, Sheikh Mohammed Shariful; Liu, Yong; Xue, Lin; Tan, Ning; Chen, Ji-Yan

2017-03-01

A few studies developed simple risk model for predicting CIN with poor prognosis after emergent PCI. The study aimed to develop and validate a novel tool for predicting the risk of contrast-induced nephropathy (CIN) in patients undergoing emergent percutaneous coronary intervention (PCI). 692 consecutive patients undergoing emergent PCI between January 2010 and December 2013 were randomly (2:1) assigned to a development dataset (n=461) and a validation dataset (n=231). Multivariate logistic regression was applied to identify independent predictors of CIN, and established CIN predicting model, whose prognostic accuracy was assessed using the c-statistic for discrimination and the Hosmere Lemeshow test for calibration. The overall incidence of CIN was 55(7.9%). A total of 11 variables were analyzed, including age >75years old, baseline serum creatinine (SCr)>1.5mg/dl, hypotension and the use of intra-aortic balloon pump(IABP), which were identified to enter risk score model (Chen). The incidence of CIN was 32(6.9%) in the development dataset (in low risk (score=0), 1.0%, moderate risk (score:1-2), 13.4%, high risk (score≥3), 90.0%). Compared to the classical Mehran's and ACEF CIN risk score models, the risk score (Chen) across the subgroup of the study population exhibited similar discrimination and predictive ability on CIN (c-statistic:0.828, 0.776, 0.853, respectively), in-hospital mortality, 2, 3-years mortality (c-statistic:0.738.0.750, 0.845, respectively) in the validation population. Our data showed that this simple risk model exhibited good discrimination and predictive ability on CIN, similar to Mehran's and ACEF score, and even on long-term mortality after emergent PCI. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Analysis of students’ incorrect answers at triangle materials in the fifth-grade of primary school

NASA Astrophysics Data System (ADS)

Shintawati, E.; Jupri, Al

2018-05-01

This research aims to analyse the comparison of the predictions made by the author between learning methods with the reality that occur in the class and to analyse students' responses toward questions given by teachers at triangle materials. The method used in this research is the descriptive-qualitative method. The subjects of this research are all fifth-grade students from a primary school in the city of Bandung. The results of this research indicated that there are some influences between learning methods and students' responses shown by the way students answer the question. In reality, there are many students’ responses produced beyond the predictions of the author. It shows that as the good teachers, besides setting up learning methods, they should also make predictions toward the responses of the students in answering the questions given. The results of the predictions could be used as a lesson for teachers to run the learning processes as good as possible so the students' responses could being accordance with the concept of materials presented and could also achieve the expected learning goals. Based on this research’s results, as a teacher must have techniques and strategies to overcome things that are not expected during the learning so that learning can be conducive so that students can focus on learning and enjoy learning so that learning outcomes is the ability of students to increase in understanding the material and can construct the concept of material provided.

Measurement of historical cliff-top changes and estimation of future trends using GIS data between Bridlington and Hornsea - Holderness Coast (UK)

NASA Astrophysics Data System (ADS)

Castedo, Ricardo; de la Vega-Panizo, Rogelio; Fernández-Hernández, Marta; Paredes, Carlos

2015-02-01

A key requirement for effective coastal zone management is good knowledge of historical rates of change and the ability to predict future shoreline evolution, especially for rapidly eroding areas. Historical shoreline recession analysis was used for the prediction of future cliff shoreline positions along a section of 9 km between Bridlington and Hornsea, on the northern area of the Holderness Coast, UK. The analysis was based on historical maps and aerial photographs dating from 1852 to 2011 using the Digital Shoreline Analysis System (DSAS) 4.3, extension of ESRI's ArcInfo 10.×. The prediction of future shorelines was performed for the next 40 years using a variety of techniques, ranging from extrapolation from historical data, geometric approaches like the historical trend analysis, to a process-response numerical model that incorporates physically-based equations and geotechnical stability analysis. With climate change and sea-level rise implying that historical rates of change may not be a reliable guide for the future, enhanced visualization of the evolving coastline has the potential to improve awareness of these changing conditions. Following the IPCC, 2013 report, two sea-level rise rates, 2 mm/yr and 6 mm/yr, have been used to estimate future shoreline conditions. This study illustrated that good predictive models, once their limitations are estimated or at least defined, are available for use by managers, planners, engineers, scientists and the public to make better decisions regarding coastal management, development, and erosion-control strategies.

Predicting risk and outcomes for frail older adults: an umbrella review of frailty screening tools

PubMed Central

Apóstolo, João; Cooke, Richard; Bobrowicz-Campos, Elzbieta; Santana, Silvina; Marcucci, Maura; Cano, Antonio; Vollenbroek-Hutten, Miriam; Germini, Federico; Holland, Carol

2017-01-01

EXECUTIVE SUMMARY Background A scoping search identified systematic reviews on diagnostic accuracy and predictive ability of frailty measures in older adults. In most cases, research was confined to specific assessment measures related to a specific clinical model. Objectives To summarize the best available evidence from systematic reviews in relation to reliability, validity, diagnostic accuracy and predictive ability of frailty measures in older adults. Inclusion criteria Population Older adults aged 60 years or older recruited from community, primary care, long-term residential care and hospitals. Index test Available frailty measures in older adults. Reference test Cardiovascular Health Study phenotype model, the Canadian Study of Health and Aging cumulative deficit model, Comprehensive Geriatric Assessment or other reference tests. Diagnosis of interest Frailty defined as an age-related state of decreased physiological reserves characterized by an increased risk of poor clinical outcomes. Types of studies Quantitative systematic reviews. Search strategy A three-step search strategy was utilized to find systematic reviews, available in English, published between January 2001 and October 2015. Methodological quality Assessed by two independent reviewers using the Joanna Briggs Institute critical appraisal checklist for systematic reviews and research synthesis. Data extraction Two independent reviewers extracted data using the standardized data extraction tool designed for umbrella reviews. Data synthesis Data were only presented in a narrative form due to the heterogeneity of included reviews. Results Five reviews with a total of 227,381 participants were included in this umbrella review. Two reviews focused on reliability, validity and diagnostic accuracy; two examined predictive ability for adverse health outcomes; and one investigated validity, diagnostic accuracy and predictive ability. In total, 26 questionnaires and brief assessments and eight frailty indicators were analyzed, most of which were applied to community-dwelling older people. The Frailty Index was examined in almost all these dimensions, with the exception of reliability, and its diagnostic and predictive characteristics were shown to be satisfactory. Gait speed showed high sensitivity, but only moderate specificity, and excellent predictive ability for future disability in activities of daily living. The Tilburg Frailty Indicator was shown to be a reliable and valid measure for frailty screening, but its diagnostic accuracy was not evaluated. Screening Letter, Timed-up-and-go test and PRISMA 7 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) demonstrated high sensitivity and moderate specificity for identifying frailty. In general, low physical activity, variously measured, was one of the most powerful predictors of future decline in activities of daily living. Conclusion Only a few frailty measures seem to be demonstrably valid, reliable and diagnostically accurate, and have good predictive ability. Among them, the Frailty Index and gait speed emerged as the most useful in routine care and community settings. However, none of the included systematic reviews provided responses that met all of our research questions on their own and there is a need for studies that could fill this gap, covering all these issues within the same study. Nevertheless, it was clear that no suitable tool for assessing frailty appropriately in emergency departments was identified. PMID:28398987

The synergistic use of models and observations: understanding the mechanisms behind observed biomass dynamics at 14 Amazonian field sites and the implications for future biomass change

NASA Astrophysics Data System (ADS)

Levine, N. M.; Galbraith, D.; Christoffersen, B. J.; Imbuzeiro, H. A.; Restrepo-Coupe, N.; Malhi, Y.; Saleska, S. R.; Costa, M. H.; Phillips, O.; Andrade, A.; Moorcroft, P. R.

2011-12-01

The Amazonian rainforests play a vital role in global water, energy and carbon cycling. The sensitivity of this system to natural and anthropogenic disturbances therefore has important implications for the global climate. Some global models have predicted large-scale forest dieback and the savannization of Amazonia over the next century [Meehl et al., 2007]. While several studies have demonstrated the sensitivity of dynamic global vegetation models to changes in temperature, precipitation, and dry season length [e.g. Galbraith et al., 2010; Good et al., 2011], the ability of these models to accurately reproduce ecosystem dynamics of present-day transitional or low biomass tropical forests has not been demonstrated. A model-data intercomparison was conducted with four state-of-the-art terrestrial ecosystem models to evaluate the ability of these models to accurately represent structure, function, and long-term biomass dynamics over a range of Amazonian ecosystems. Each modeling group conducted a series of simulations for 14 sites including mature forest, transitional forest, savannah, and agricultural/pasture sites. All models were run using standard physical parameters and the same initialization procedure. Model results were compared against forest inventory and dendrometer data in addition to flux tower measurements. While the models compared well against field observations for the mature forest sites, significant differences were observed between predicted and measured ecosystem structure and dynamics for the transitional forest and savannah sites. The length of the dry season and soil sand content were good predictors of model performance. In addition, for the big leaf models, model performance was highest for sites dominated by late successional trees and lowest for sites with predominantly early and mid-successional trees. This study provides insight into tropical forest function and sensitivity to environmental conditions that will aid in predictions of the response of the Amazonian rainforest to future anthropogenically induced changes.

Risk prediction model for knee pain in the Nottingham community: a Bayesian modelling approach.

PubMed

Fernandes, G S; Bhattacharya, A; McWilliams, D F; Ingham, S L; Doherty, M; Zhang, W

2017-03-20

Twenty-five percent of the British population over the age of 50 years experiences knee pain. Knee pain can limit physical ability and cause distress and bears significant socioeconomic costs. The objectives of this study were to develop and validate the first risk prediction model for incident knee pain in the Nottingham community and validate this internally within the Nottingham cohort and externally within the Osteoarthritis Initiative (OAI) cohort. A total of 1822 participants from the Nottingham community who were at risk for knee pain were followed for 12 years. Of this cohort, two-thirds (n = 1203) were used to develop the risk prediction model, and one-third (n = 619) were used to validate the model. Incident knee pain was defined as pain on most days for at least 1 month in the past 12 months. Predictors were age, sex, body mass index, pain elsewhere, prior knee injury and knee alignment. A Bayesian logistic regression model was used to determine the probability of an OR >1. The Hosmer-Lemeshow χ 2 statistic (HLS) was used for calibration, and ROC curve analysis was used for discrimination. The OAI cohort from the United States was also used to examine the performance of the model. A risk prediction model for knee pain incidence was developed using a Bayesian approach. The model had good calibration, with an HLS of 7.17 (p = 0.52) and moderate discriminative ability (ROC 0.70) in the community. Individual scenarios are given using the model. However, the model had poor calibration (HLS 5866.28, p < 0.01) and poor discriminative ability (ROC 0.54) in the OAI cohort. To our knowledge, this is the first risk prediction model for knee pain, regardless of underlying structural changes of knee osteoarthritis, in the community using a Bayesian modelling approach. The model appears to work well in a community-based population but not in individuals with a higher risk for knee osteoarthritis, and it may provide a convenient tool for use in primary care to predict the risk of knee pain in the general population.

Is the admission test for a course in medicine a good predictor of academic performance? A case-control experience at the school of medicine of Turin.

PubMed

Migliaretti, Giuseppe; Bozzaro, Salvatore; Siliquini, Roberta; Stura, Ilaria; Costa, Giuseppe; Cavallo, Franco

2017-12-01

The usefulness of university admission tests to medical schools has been discussed in recent years. In the academic year 2014-15 in Italy, several students who failed the admission test appealed to the regional administrative court ('Tribunale Amministrativo Regionale'-TAR) requesting to be included, despite their test results, and all were admitted to their respective courses. The existence of this population of students generated a control group, in order to evaluate the predictive capacity of the admission test. The aim of the present work is to discuss the ability of university admission tests to predict subsequent academic success. The study involved 683 students who enrolled onto the first year of the degree course in medicine in the academic year 2014-15 at the University of Turin (Molinette and San Luigi Gonzaga colleges). The students were separated into two categories: those who passed the admission test (n1=531) and those who did not pass the admission test but won their appeal in the TAR (n2=152). The validity of the admission test was analysed using specificity, sensitivity, positive and negative likelihood ratios (LH+, LH-), receiver operating characteristic (ROC) curves, area under the ROC curve (AUC), and relative (95% CI). The results showed that the admission test appeared to be a good tool for predicting the academic performances in the first year of the course (AUC=0.70, 95% CI 0.64 to 0.76). Moreover, some subject areas seemed to have a greater discriminating capacity than others. In general, students who obtained a high score in scientific questions were more likely to obtain the required standards during the first year (LH+ 1.22, 95% CI 1.14 to 1.25). Based on a consistent statistical approach, our study seems to confirm the ability of the admission test to predict academic success in the first year at the school of medicine of Turin. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Nuclear charge radii: density functional theory meets Bayesian neural networks

NASA Astrophysics Data System (ADS)

Utama, R.; Chen, Wei-Chia; Piekarewicz, J.

2016-11-01

The distribution of electric charge in atomic nuclei is fundamental to our understanding of the complex nuclear dynamics and a quintessential observable to validate nuclear structure models. The aim of this study is to explore a novel approach that combines sophisticated models of nuclear structure with Bayesian neural networks (BNN) to generate predictions for the charge radii of thousands of nuclei throughout the nuclear chart. A class of relativistic energy density functionals is used to provide robust predictions for nuclear charge radii. In turn, these predictions are refined through Bayesian learning for a neural network that is trained using residuals between theoretical predictions and the experimental data. Although predictions obtained with density functional theory provide a fairly good description of experiment, our results show significant improvement (better than 40%) after BNN refinement. Moreover, these improved results for nuclear charge radii are supplemented with theoretical error bars. We have successfully demonstrated the ability of the BNN approach to significantly increase the accuracy of nuclear models in the predictions of nuclear charge radii. However, as many before us, we failed to uncover the underlying physics behind the intriguing behavior of charge radii along the calcium isotopic chain.

Molecular surface area based predictive models for the adsorption and diffusion of disperse dyes in polylactic acid matrix.

PubMed

Xu, Suxin; Chen, Jiangang; Wang, Bijia; Yang, Yiqi

2015-11-15

Two predictive models were presented for the adsorption affinities and diffusion coefficients of disperse dyes in polylactic acid matrix. Quantitative structure-sorption behavior relationship would not only provide insights into sorption process, but also enable rational engineering for desired properties. The thermodynamic and kinetic parameters for three disperse dyes were measured. The predictive model for adsorption affinity was based on two linear relationships derived by interpreting the experimental measurements with molecular structural parameters and compensation effect: ΔH° vs. dye size and ΔS° vs. ΔH°. Similarly, the predictive model for diffusion coefficient was based on two derived linear relationships: activation energy of diffusion vs. dye size and logarithm of pre-exponential factor vs. activation energy of diffusion. The only required parameters for both models are temperature and solvent accessible surface area of the dye molecule. These two predictive models were validated by testing the adsorption and diffusion properties of new disperse dyes. The models offer fairly good predictive ability. The linkage between structural parameter of disperse dyes and sorption behaviors might be generalized and extended to other similar polymer-penetrant systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Digital-computer model of ground-water flow in Tooele Valley, Utah

USGS Publications Warehouse

Razem, Allan C.; Bartholoma, Scott D.

1980-01-01

A two-dimensional, finite-difference digital-computer model was used to simulate the ground-water flow in the principal artesian aquifer in Tooele Valley, Utah. The parameters used in the model were obtained through field measurements and tests, from historical records, and by trial-and-error adjustments. The model was calibrated against observed water-level changes that occurred during 1941-50, 1951-60, 1961-66, 1967-73, and 1974-78. The reliability of the predictions is good in most parts of the valley, as is shown by the ability of the model to match historical water-level changes.

Using an interview guide to identify effective nurse managers: phase II, outcomes.

PubMed

Fosbinder, D; Everson-Bates, S; Hendrix, L

2000-01-01

The investigators report validation of a survey tool called the Interview Guide to assist in the selection of nurses who will be effective as managers. Nurse administrators rated nurse managers at six months and two years after hire. The Interview Guide rated the management qualities "seeing the big picture" and potential for "rehire" as the best predictors of managerial success. After two years, a good "self-concept" or a "flexible attitude" was the best predictor. The ability to manage conflict was the most significant competency for predicting rehire at both six months and two years.

Multi-scale modelling of supercapacitors: From molecular simulations to a transmission line model

NASA Astrophysics Data System (ADS)

Pean, C.; Rotenberg, B.; Simon, P.; Salanne, M.

2016-09-01

We perform molecular dynamics simulations of a typical nanoporous-carbon based supercapacitor. The organic electrolyte consists in 1-ethyl-3-methylimidazolium and hexafluorophosphate ions dissolved in acetonitrile. We simulate systems at equilibrium, for various applied voltages. This allows us to determine the relevant thermodynamic (capacitance) and transport (in-pore resistivities) properties. These quantities are then injected in a transmission line model for testing its ability to predict the charging properties of the device. The results from this macroscopic model are in good agreement with non-equilibrium molecular dynamics simulations, which validates its use for interpreting electrochemical impedance experiments.

Modeling Scramjet Flows with Variable Turbulent Prandtl and Schmidt Numbers

NASA Technical Reports Server (NTRS)

Xiao, X.; Hassan, H. A.; Baurle, R. A.

2006-01-01

A complete turbulence model, where the turbulent Prandtl and Schmidt numbers are calculated as part of the solution and where averages involving chemical source terms are modeled, is presented. The ability of avoiding the use of assumed or evolution Probability Distribution Functions (PDF's) results in a highly efficient algorithm for reacting flows. The predictions of the model are compared with two sets of experiments involving supersonic mixing and one involving supersonic combustion. The results demonstrate the need for consideration of turbulence/chemistry interactions in supersonic combustion. In general, good agreement with experiment is indicated.

Deception and false belief in paranoia: modelling theory of mind stories.

PubMed

Shryane, Nick M; Corcoran, Rhiannon; Rowse, Georgina; Moore, Rosanne; Cummins, Sinead; Blackwood, Nigel; Howard, Robert; Bentall, Richard P

2008-01-01

This study used Item Response Theory (IRT) to model the psychometric properties of a Theory of Mind (ToM) stories task. The study also aimed to determine whether the ability to understand states of false belief in others and the ability to understand another's intention to deceive are separable skills, and to establish which is more sensitive to the presence of paranoia. A large and diverse clinical and nonclinical sample differing in levels of depression and paranoid ideation performed a ToM stories task measuring false belief and deception at first and second order. A three-factor IRT model was found to best fit the data, consisting of first- and second-order deception factors and a single false-belief factor. The first-order deception and false-belief factors had good measurement properties at low trait levels, appropriate for samples with reduced ToM ability. First-order deception and false beliefs were both sensitive to paranoid ideation with IQ predicting performance on false belief items. Separable abilities were found to underlie performance on verbal ToM tasks. However, paranoia was associated with impaired performance on both false belief and deception understanding with clear impairment at the simplest level of mental state attribution.

Predictors of long-term renal outcome in lupus nephritis trials: lessons learned from the Euro-Lupus Nephritis cohort.

PubMed

Dall'Era, Maria; Cisternas, Miriam G; Smilek, Dawn E; Straub, Laura; Houssiau, Frédéric A; Cervera, Ricard; Rovin, Brad H; Mackay, Meggan

2015-05-01

There is a need to determine which response measures in lupus nephritis trials are most predictive of good long-term renal function. We used data from the Euro-Lupus Nephritis Trial to evaluate the performance of proteinuria, serum creatinine (Cr), and urinary red blood cells (RBCs) as predictors of good long-term renal outcome. Patients from the Euro-Lupus Nephritis Trial with proteinuria, serum Cr, and urinary RBC measurements at 3, 6, or 12 months and with a minimum of 7 years of followup were included (n = 76). We assessed the ability of these clinical biomarkers at 3, 6, and 12 months after randomization to predict good long-term renal outcome (defined as a serum Cr value ≤1.0 mg/dl) at 7 years. Receiver operating characteristic curves were generated to assess parameter performance at these time points and to select the best cutoff for individual parameters. Sensitivity and specificity were calculated for the parameters alone and in combination. A proteinuria value of <0.8 gm/day at 12 months after randomization was the single best predictor of good long-term renal function (sensitivity 81% and specificity 78%). The addition of serum Cr to proteinuria as a composite predictor did not improve the performance of the outcome measure; addition of urinary RBCs as a predictor significantly decreased the sensitivity to 47%. This study demonstrates that the level of proteinuria at 12 months is the individual best predictor of long-term renal outcome in patients with lupus nephritis. Inclusion of urinary RBCs as part of a composite outcome measure actually undermined the predictive value of the trial data. We therefore suggest that urinary RBCs should not be included as a component of clinical trial response criteria in lupus nephritis. © 2015, American College of Rheumatology.

The status and challenge of global fire modelling

DOE PAGES

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...

2016-06-09

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

The status and challenge of global fire modelling

NASA Astrophysics Data System (ADS)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

The status and challenge of global fire modelling

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

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

[Gaussian process regression and its application in near-infrared spectroscopy analysis].

PubMed

Feng, Ai-Ming; Fang, Li-Min; Lin, Min

2011-06-01

Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.

Rodentia and lagomorpha

USGS Publications Warehouse

Sheffield, S.R.; Sawicka-Kapusta, K.; Cohen, J.B.; Rattner, B.A.; Shore, Richard F.; Rattner, Barnett A.

2001-01-01

This comprehensive review examines the extensive literature on wild rodents and lagomorphs as biomonitors of environmental contamination. This chapter covers studies dealing with exposure and effects of environmental contaminants on rodent and lagomorph species, including pesticides (organochlorines, organophosphorus and carbamate compounds, herbicides, plant growth regulators, fungicides, and rodenticides), other organic chemicals, metals, radionuclides, and other miscellaneous contaminants. Many research needs become evident when reviewing ecotoxicological data for rodents and lagomorphs, the most striking being the paucity of information on rodent families other than Muridae (mice and rats). While our ability to qualitatively extrapolate effects observed in laboratory studies to field situations is good for a variety of contaminants, quantitative predictions of dose-response relationships are poor because inter-specific variation and differences in exposure patterns between laboratory and wild species to toxicants are for the most part unknown. More sophisticated comparative toxicity studies need to be undertaken that build on previous work in order to develop a database of information, to account for and model differences in exposure pathways, to document interactions among multiple stressors, to generate data establishing thresholds, critical concentrations, and diagnostic guidelines, and even to develop physiologically-based toxicokinetic models. Such efforts may enhance our ability to predict effects on wild populations, including threatened and endangered species.

Is there a link between writing ability, drawing aptitude and manual skills of dental students?

PubMed

Gillet, Dominique; Quinton, André; Jeannel, Alain

2002-05-01

In France, students have to choose between medical or dental courses, according to their rank, after a competitive examination at the end of their first year of study. Intellectual ability is evaluated, while manual competence is not, and this is a paradox. The purpose of the present study is to investigate whether it is possible to predict the manual aptitude of a dental student through tests that allow the qualities of reflection and organization to be judged. We administered writing tests and drawing tests to 45 students of the Bordeaux dental school to ascertain whether there was a correlation between the competitive examination, the criterion examined (reflection, organization, aesthetics em leader) and the results of the dental practical assessments during the first year of dental study. The results showed that although manual competence in dental practical work, graphic qualities and writing skills are connected, it is difficult to correlate them directly with competitive examination performance. In view of the number of uncontrolled variables influencing the students' outcome, is it useful to be able to predict who will become a good practitioner? One indication may be found in the moral reasoning of candidates.

An automated workflow for patient-specific quality control of contour propagation

NASA Astrophysics Data System (ADS)

Beasley, William J.; McWilliam, Alan; Slevin, Nicholas J.; Mackay, Ranald I.; van Herk, Marcel

2016-12-01

Contour propagation is an essential component of adaptive radiotherapy, but current contour propagation algorithms are not yet sufficiently accurate to be used without manual supervision. Manual review of propagated contours is time-consuming, making routine implementation of real-time adaptive radiotherapy unrealistic. Automated methods of monitoring the performance of contour propagation algorithms are therefore required. We have developed an automated workflow for patient-specific quality control of contour propagation and validated it on a cohort of head and neck patients, on which parotids were outlined by two observers. Two types of error were simulated—mislabelling of contours and introducing noise in the scans before propagation. The ability of the workflow to correctly predict the occurrence of errors was tested, taking both sets of observer contours as ground truth, using receiver operator characteristic analysis. The area under the curve was 0.90 and 0.85 for the observers, indicating good ability to predict the occurrence of errors. This tool could potentially be used to identify propagated contours that are likely to be incorrect, acting as a flag for manual review of these contours. This would make contour propagation more efficient, facilitating the routine implementation of adaptive radiotherapy.

Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

USGS Publications Warehouse

Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.

2015-08-24

Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

Geoscience technology application to optimize field development, Seligi Field, Malay Basin

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

Ahmed, M.S.; Wiggins, B.D.

1994-07-01

Integration of well log, core, 3-D seismic, and engineering data within a sequence stratigraphic framework, has enabled prediction of reservoir distribution and optimum development of Seligi field. Seligi is the largest field in the Malay Basin, with half of the reserves within lower Miocene Group J reservoirs. These reservoirs consist of shallow marine sandstones and estuarine sandstones predominantly within an incised valley. Variation in reservoir quality has been a major challenge in developing Seligi. Recognizing and mapping four sequences within the Group J incised valley fill has resulted in a geologic model for predicting the distribution of good quality estuarinemore » reservoir units and intercalated low-permeability sand/shale units deposited during marine transgressions. These low-permeability units segregate the reservoir fluids, causing differential contact movement in response to production thus impacting completion strategy and well placement. Seismic calibration shows that a large impedance contrast exists between the low-permeability rock and adjacent good quality oil sand. Application of sequence stratigraphic/facies analysis coupled with the ability to identify the low-permeability units seismically is enabling optimum development of each of the four sequences at Seligi.« less

Molecular docking, 3D QSAR and dynamics simulation studies of imidazo-pyrrolopyridines as janus kinase 1 (JAK 1) inhibitors.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2016-10-01

Janus kinase 1 (JAK 1) plays a critical role in initiating responses to cytokines by the JAK-signal transducer and activator of transcription (JAK-STAT). This controls survival, proliferation and differentiation of a variety of cells. Docking, 3D quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) studies were performed on a series of Imidazo-pyrrolopyridine derivatives reported as JAK 1 inhibitors. QSAR model was generated using 30 molecules in the training set; developed model showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r 2 Pred ) values. Finally, molecular dynamics simulation was performed to validate docking results and MM/GBSA calculations. This facilitated us to compare binding free energies of cocrystal ligand and newly designed molecule R1. The good concordance between the docking results and CoMFA/CoMSIA contour maps afforded obliging clues for the rational modification of molecules to design more potent JAK 1 inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting No-Shows in Radiology Using Regression Modeling of Data Available in the Electronic Medical Record.

PubMed

Harvey, H Benjamin; Liu, Catherine; Ai, Jing; Jaworsky, Cristina; Guerrier, Claude Emmanuel; Flores, Efren; Pianykh, Oleg

2017-10-01

To test whether data elements available in the electronic medical record (EMR) can be effectively leveraged to predict failure to attend a scheduled radiology examination. Using data from a large academic medical center, we identified all patients with a diagnostic imaging examination scheduled from January 1, 2016, to April 1, 2016, and determined whether the patient successfully attended the examination. Demographic, clinical, and health services utilization variables available in the EMR potentially relevant to examination attendance were recorded for each patient. We used descriptive statistics and logistic regression models to test whether these data elements could predict failure to attend a scheduled radiology examination. The predictive accuracy of the regression models were determined by calculating the area under the receiver operator curve. Among the 54,652 patient appointments with radiology examinations scheduled during the study period, 6.5% were no-shows. No-show rates were highest for the modalities of mammography and CT and lowest for PET and MRI. Logistic regression indicated that 16 of the 27 demographic, clinical, and health services utilization factors were significantly associated with failure to attend a scheduled radiology examination (P ≤ .05). Stepwise logistic regression analysis demonstrated that previous no-shows, days between scheduling and appointments, modality type, and insurance type were most strongly predictive of no-show. A model considering all 16 data elements had good ability to predict radiology no-shows (area under the receiver operator curve = 0.753). The predictive ability was similar or improved when these models were analyzed by modality. Patient and examination information readily available in the EMR can be successfully used to predict radiology no-shows. Moving forward, this information can be proactively leveraged to identify patients who might benefit from additional patient engagement through appointment reminders or other targeted interventions to avoid no-shows. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Latitudinal variation in carbon storage can help predict changes in swamps affected by global warming

USGS Publications Warehouse

Middleton, Beth A.; McKee, Karen

2004-01-01

Plants may offer our best hope of removing greenhouse gases (gases that contribute to global warming) emitted to the atmosphere from the burning of fossil fuels. At the same time, global warming could change environments so that natural plant communities will either need to shift into cooler climate zones, or become extirpated (Prasad and Iverson, 1999; Crumpacker and others, 2001; Davis and Shaw, 2001). It is impossible to know the future, but studies combining field observation of production and modeling can help us make predictions about what may happen to these wetland communities in the future. Widespread wetland types such as baldcypress (Taxodium distichum) swamps in the southeastern portion of the United States could be especially good at carbon sequestration (amount of CO2 stored by forests) from the atmosphere. They have high levels of production and sometimes store undecomposed dead plant material in wet conditions with low oxygen, thus keeping gases stored that would otherwise be released into the atmosphere (fig. 1). To study the ability of baldcypress swamps to store carbon, our project has taken two approaches. The first analysis looked at published data to develop an idea (hypothesis) of how production levels change across a temperature gradient in the baldcypress region (published data study). The second study tested this idea by comparing production levels across a latitudinal range by using swamps in similar field conditions (ongoing carbon storage study). These studies will help us make predictions about the future ability of baldcypress swamps to store carbon in soil and plant biomass, as well as the ability of these forests to shift northward with global warming.

Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.

PubMed

Jeunet, Camille; N'Kaoua, Bernard; Subramanian, Sriram; Hachet, Martin; Lotte, Fabien

2015-01-01

Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants' BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants' performance with a mean error of less than 3 points. This study determined how users' profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user.

Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns

PubMed Central

Jeunet, Camille; N’Kaoua, Bernard; Subramanian, Sriram; Hachet, Martin; Lotte, Fabien

2015-01-01

Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy—EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants’ BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants’ performance with a mean error of less than 3 points. This study determined how users’ profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user. PMID:26625261

External Validation of the Simple Clinical Score and the HOTEL Score, Two Scores for Predicting Short-Term Mortality after Admission to an Acute Medical Unit

PubMed Central

Stræde, Mia; Brabrand, Mikkel

2014-01-01

Background Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Methods Pre-planned prospective observational cohort study. Setting Danish 460-bed regional teaching hospital. Findings We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774–0.879) for 30-day mortality, and goodness-of-fit test, χ2 = 2.68 (10 degrees of freedom), P = 0.998 and χ2 = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901–0.962) for 24-hours mortality and goodness-of-fit test, χ2 = 5.56 (10 degrees of freedom), P = 0.234. Conclusion We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision. PMID:25144186

Dental status and self-assessed chewing ability in 70- and 80-year-old subjects in Sweden.

PubMed

Unell, L; Johansson, A; Ekbäck, G; Ordell, S; Carlsson, G E

2015-09-01

The objective was to compare two cohorts of elderly people, 70 and 80 years old, with respect to dental status and self-assessed chewing ability. The hypotheses were as follows: (i) dental status is associated with self-assessed chewing ability; (ii) chewing ability is poorer among the 80- than the 70-year-old subjects. Identical questionnaires were in 2012 sent to all subjects born in 1942 and 1932, living in two Swedish counties. The response rate was 70.1% resulting in samples of 5697 70- and 2922 80-year-old subjects. Answers to questions on self-assessed chewing ability, dental status and some other factors have been analysed. Dental status varied but was in general good; 72% of the 70- and 60% of the 80-year-old subjects reported that they had all or only few missing teeth. Rate of edentulism was 3% and 7%, respectively. Removable partial dentures were reported by 6% and 10%, respectively, implant treatment by 13% in both cohorts. Self-assessed chewing ability was mostly good and correlated with the number of teeth (Spearman rho = 0.46). A majority of the edentulous subjects assessed their chewing ability as very or fairly good. Logistic regression showed that self-assessed chewing ability was significantly associated with a number of dental variables but also with general health. In conclusion, dental status was relatively good at both ages but somewhat poorer in the older cohort. Dental status, some other dental variables and being healthy were in both age groups significantly associated with self-assessed chewing ability. © 2015 John Wiley & Sons Ltd.

Mapping environmental dimensions of dengue fever transmission risk in the Aburrá Valley, Colombia.

PubMed

Arboleda, Sair; Jaramillo-O, Nicolas; Peterson, A Townsend

2009-12-01

Dengue fever (DF) is endemic in Medellín, the second largest Colombian city, and surrounding municipalities. We used DF case and satellite environmental data to investigate conditions associated with suitable areas for DF occurrence in 2008 in three municipalities (Bello, Medellín and Itagüí). We develop spatially stratified tests of ecological niche models, and found generally good predictive ability, with all model tests yielding results significantly better than random expectations. We concluded that Bello and Medellín present ecological conditions somewhat different from, and more suitable for DF than, those of Itagüí. We suggest that areas predicted by our models as suitable for DF could be considered as at-risk, and could be used to guide campaigns for DF prevention in these municipalities.

Mapping Environmental Dimensions of Dengue Fever Transmission Risk in the Aburrá Valley, Colombia

PubMed Central

Arboleda, Sair; Nicolas, Jaramillo-O.; Peterson, A. Townsend

2009-01-01

Dengue fever (DF) is endemic in Medellín, the second largest Colombian city, and surrounding municipalities. We used DF case and satellite environmental data to investigate conditions associated with suitable areas for DF occurrence in 2008 in three municipalities (Bello, Medellín and Itagüí). We develop spatially stratified tests of ecological niche models, and found generally good predictive ability, with all model tests yielding results significantly better than random expectations. We concluded that Bello and Medellín present ecological conditions somewhat different from, and more suitable for DF than, those of Itagüí. We suggest that areas predicted by our models as suitable for DF could be considered as at-risk, and could be used to guide campaigns for DF prevention in these municipalities. PMID:20049244

Effect of Tutorial Giving on The Topic of Special Theory of Relativity in Modern Physics Course Towards Students’ Problem-Solving Ability

NASA Astrophysics Data System (ADS)

Hartatiek; Yudyanto; Haryoto, Dwi

2017-05-01

A Special Theory of Relativity handbook has been successfully arranged to guide students tutorial activity in the Modern Physics course. The low of students’ problem-solving ability was overcome by giving the tutorial in addition to the lecture class. It was done due to the limited time in the class during the course to have students do some exercises for their problem-solving ability. The explicit problem-solving based tutorial handbook was written by emphasizing to this 5 problem-solving strategies: (1) focus on the problem, (2) picture the physical facts, (3) plan the solution, (4) solve the problem, and (5) check the result. This research and development (R&D) consisted of 3 main steps: (1) preliminary study, (2) draft I. product development, and (3) product validation. The developed draft product was validated by experts to measure the feasibility of the material and predict the effect of the tutorial giving by means of questionnaires with scale 1 to 4. The students problem-solving ability in Special Theory of Relativity showed very good qualification. It implied that the tutorial giving with the help of tutorial handbook increased students problem-solving ability. The empirical test revealed that the developed handbook was significantly affected in improving students’ mastery concept and problem-solving ability. Both students’ mastery concept and problem-solving ability were in middle category with gain of 0.31 and 0.41, respectively.

Individualization of controlled ovarian stimulation in vitro fertilization using ovarian reserve markers.

PubMed

Grisendi, Valentina; La Marca, Antonio

2017-06-01

In assisted reproduction technologies (ART) the controlled ovarian stimulation (COS) therapy is the starting point from which a good oocytes retrieval depends. Treatment individualization is based on ovarian response prediction, which largely depends on a woman's ovarian reserve. Anti-Müllerian hormone (AMH) and antral follicle count (AFC) are considered the most accurate and reliable markers of ovarian reserve. A literature search was carried out for studies that addressed the ability of AMH and AFC to predict poor and/or excessive ovarian response in IVF cycles. According to the predicted response to ovarian stimulation (poor- normal- or high-response) is today possible not only to personalize pre-treatment counseling with the couple, but also to individualize the ovarian stimulation protocol, choosing among GnRH-agonists or antagonists for endogenous follicle-stimulating hormone (FSH) suppression and formulating the FSH starting dose most adequate for the single patients. In this review we discuss how to choose the best COS therapy for the single patient, on the basis of the markers-guided ovarian response prediction.

Physical re-examination of parameters on a molecular collisions-based diffusion model for diffusivity prediction in polymers.

PubMed

Ohashi, Hidenori; Tamaki, Takanori; Yamaguchi, Takeo

2011-12-29

Molecular collisions, which are the microscopic origin of molecular diffusive motion, are affected by both the molecular surface area and the distance between molecules. Their product can be regarded as the free space around a penetrant molecule defined as the "shell-like free volume" and can be taken as a characteristic of molecular collisions. On the basis of this notion, a new diffusion theory has been developed. The model can predict molecular diffusivity in polymeric systems using only well-defined single-component parameters of molecular volume, molecular surface area, free volume, and pre-exponential factors. By consideration of the physical description of the model, the actual body moved and which neighbor molecules are collided with are the volume and the surface area of the penetrant molecular core. In the present study, a semiempirical quantum chemical calculation was used to calculate both of these parameters. The model and the newly developed parameters offer fairly good predictive ability. © 2011 American Chemical Society

Detection of Tetracycline in Milk using NIR Spectroscopy and Partial Least Squares

NASA Astrophysics Data System (ADS)

Wu, Nan; Xu, Chenshan; Yang, Renjie; Ji, Xinning; Liu, Xinyuan; Yang, Fan; Zeng, Ming

2018-02-01

The feasibility of measuring tetracycline in milk was investigated by near infrared (NIR) spectroscopic technique combined with partial least squares (PLS) method. The NIR transmittance spectra of 40 pure milk samples and 40 tetracycline adulterated milk samples with different concentrations (from 0.005 to 40 mg/L) were obtained. The pure milk and tetracycline adulterated milk samples were properly assigned to the categories with 100% accuracy in the calibration set, and the rate of correct classification of 96.3% was obtained in the prediction set. For the quantitation of tetracycline in adulterated milk, the root mean squares errors for calibration and prediction models were 0.61 mg/L and 4.22 mg/L, respectively. The PLS model had good fitting effect in calibration set, however its predictive ability was limited, especially for low tetracycline concentration samples. Totally, this approach can be considered as a promising tool for discrimination of tetracycline adulterated milk, as a supplement to high performance liquid chromatography.

Simulations of a binary-sized mixture of inelastic grains in rapid shear flow.

PubMed

Clelland, R; Hrenya, C M

2002-03-01

In an effort to explore the rapid flow behavior associated with a binary-sized mixture of grains and to assess the predictive ability of the existing theory for such systems, molecular-dynamic simulations have been carried out. The system under consideration is composed of inelastic, smooth, hard disks engaged in rapid shear flow. The simulations indicate that nondimensional stresses decrease with an increase in d(L)/d(S) (ratio of large particle diameter to small particle diameter) or a decrease in nu(L)/nu(S) (area fraction ratio), as is also predicted by the kinetic theory of Willits and Arnarson [Phys. Fluids 11, 3116 (1999)]. Furthermore, the level of quantitative agreement between the theoretical stress predictions and simulation data is good over the entire range of parameters investigated. Nonetheless, the molecular-dynamic simulations also show that the assumption of an equipartition of energy rapidly deteriorates as the coefficient of restitution is decreased. The magnitude of this energy difference is found to increase with the difference in particle sizes.

Personality traits measured at baseline can predict academic performance in upper secondary school three years late.

PubMed

Rosander, Pia; Bäckström, Martin

2014-12-01

The aim of the present study was to explore the ability of personality to predict academic performance in a longitudinal study of a Swedish upper secondary school sample. Academic performance was assessed throughout a three-year period via final grades from the compulsory school and upper secondary school. The Big Five personality factors (Costa & McCrae, ) - particularly Conscientiousness and Neuroticism - were found to predict overall academic performance, after controlling for general intelligence. Results suggest that Conscientiousness, as measured at the age of 16, can explain change in academic performance at the age of 19. The effect of Neuroticism on Conscientiousness indicates that, as regarding getting good grades, it is better to be a bit neurotic than to be stable. The study extends previous work by assessing the relationship between the Big Five and academic performance over a three-year period. The results offer educators avenues for improving educational achievement. © 2014 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

DOE PAGES

Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

2015-04-02

The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K 1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO 2 2+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K 1 values are significantly overestimated. Accurate predictions of the absolute log K 1 values (root mean square deviation from experiment < 1.0 for logmore » K 1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

Antibacterial Effects and Biocompatibility of Titania Nanotubes with Octenidine Dihydrochloride/Poly(lactic-co-glycolic acid).

PubMed

Xu, Zhiqiang; Lai, Yingzhen; Wu, Dong; Huang, Wenxiu; Huang, Sijia; Zhou, Lin; Chen, Jiang

2015-01-01

Titanium (Ti) implants with long-term antibacterial ability and good biocompatibility are highly desirable materials that can be used to prevent implant-associated infections. In this study, titania nanotubes (TNTs) were synthesized on Ti surfaces through electrochemical anodization. Octenidine dihydrochloride (OCT)/poly(lactic-co-glycolic acid) (PLGA) was infiltrated into TNTs using a simple solvent-casting technique. OCT/PLGA-TNTs demonstrated sustained drug release and maintained the characteristic hollow structures of TNTs. TNTs (200 nm in diameter) alone exhibited slight antibacterial effect and good osteogenic activity but also evidently impaired adhesion and proliferation of bone marrow mesenchymal stem cells (BMSCs). OCT/PLGA-TNTs (100 nm in diameter) supported BMSC adhesion and proliferation and showed good osteogenesis-inducing ability. OCT/PLGA-TNTs also exhibited good long-term antibacterial ability within the observation period of 7 d. The synthesized drug carrier with relatively long-term antibacterial ability and enhanced excellent biocompatibility demonstrated significant potential in bone implant applications.

Antibacterial Effects and Biocompatibility of Titania Nanotubes with Octenidine Dihydrochloride/Poly(lactic-co-glycolic acid)

PubMed Central

Xu, Zhiqiang; Lai, Yingzhen; Wu, Dong; Huang, Wenxiu; Huang, Sijia; Zhou, Lin; Chen, Jiang

2015-01-01

Titanium (Ti) implants with long-term antibacterial ability and good biocompatibility are highly desirable materials that can be used to prevent implant-associated infections. In this study, titania nanotubes (TNTs) were synthesized on Ti surfaces through electrochemical anodization. Octenidine dihydrochloride (OCT)/poly(lactic-co-glycolic acid) (PLGA) was infiltrated into TNTs using a simple solvent-casting technique. OCT/PLGA-TNTs demonstrated sustained drug release and maintained the characteristic hollow structures of TNTs. TNTs (200 nm in diameter) alone exhibited slight antibacterial effect and good osteogenic activity but also evidently impaired adhesion and proliferation of bone marrow mesenchymal stem cells (BMSCs). OCT/PLGA-TNTs (100 nm in diameter) supported BMSC adhesion and proliferation and showed good osteogenesis-inducing ability. OCT/PLGA-TNTs also exhibited good long-term antibacterial ability within the observation period of 7 d. The synthesized drug carrier with relatively long-term antibacterial ability and enhanced excellent biocompatibility demonstrated significant potential in bone implant applications. PMID:26090449

Theory of Mind is Related to Children’s Resource Allocations in Gender Stereotypic Contexts

PubMed Central

Rizzo, Michael T.; Killen, Melanie

2017-01-01

The present study investigated the relations between 4- to 6-year-old children’s (N = 67) gender stereotypes, resource allocations, and mental state knowledge in gender stereotypic contexts. Participants were told vignettes about female and male characters completing gender-stereotyped activities (making dolls or trucks). Children held stereotypic expectations regarding doll- and truck-making abilities, and these expectations predicted the degree of bias in their allocations of resources to the characters. Critically, children’s performance on a ToM scale (Diverse Desires, Contents False-Belief, Belief-Emotion) was significantly related to their allocations of resources to individuals whose effort did not fit existing gender stereotypes (e.g., a boy who was good at making dolls). With increasing ToM competence, children allocated resources based on merit (even when the character’s effort did not fit existing gender stereotypes) rather than based on stereotypes. The present results provide novel information regarding the emergence of gender stereotypes about abilities, the influence of stereotypes on children’s resource allocations, and the role of ToM in children’s ability to challenge gender stereotypes when allocating resources. PMID:29083217

Imitated Prosodic Fluency Predicts Reading Comprehension Ability in Good and Poor High School Readers

PubMed Central

Breen, Mara; Kaswer, Lianne; Van Dyke, Julie A.; Krivokapić, Jelena; Landi, Nicole

2016-01-01

Researchers have established a relationship between beginning readers' silent comprehension ability and their prosodic fluency, such that readers who read aloud with appropriate prosody tend to have higher scores on silent reading comprehension assessments. The current study was designed to investigate this relationship in two groups of high school readers: Specifically Poor Comprehenders (SPCs), who have adequate word level and phonological skills but poor reading comprehension ability, and a group of age- and decoding skill-matched controls. We compared the prosodic fluency of the two groups by determining how effectively they produced prosodic cues to syntactic and semantic structure in imitations of a model speaker's production of syntactically and semantically varied sentences. Analyses of pitch and duration patterns revealed that speakers in both groups produced the expected prosodic patterns; however, controls provided stronger durational cues to syntactic structure. These results demonstrate that the relationship between prosodic fluency and reading comprehension continues past the stage of early reading instruction. Moreover, they suggest that prosodically fluent speakers may also generate more fluent implicit prosodic representations during silent reading, leading to more effective comprehension. PMID:27486409

Evaluation of pneumonia severity and acute physiology scores to predict ICU admission and mortality in patients hospitalized for influenza.

PubMed

Muller, Matthew P; McGeer, Allison J; Hassan, Kazi; Marshall, John; Christian, Michael

2010-03-05

The demand for inpatient medical services increases during influenza season. A scoring system capable of identifying influenza patients at low risk death or ICU admission could help clinicians make hospital admission decisions. Hospitalized patients with laboratory confirmed influenza were identified over 3 influenza seasons at 25 Ontario hospitals. Each patient was assigned a score for 6 pneumonia severity and 2 sepsis scores using the first data available following their registration in the emergency room. In-hospital mortality and ICU admission were the outcomes. Score performance was assessed using the area under the receiver operating characteristic curve (AUC) and the sensitivity and specificity for identifying low risk patients (risk of outcome <5%). The cohort consisted of 607 adult patients. Mean age was 76 years, 12% of patients died (71/607) and 9% required ICU care (55/607). None of the scores examined demonstrated good discriminatory ability (AUC>or=0.80). The Pneumonia Severity Index (AUC 0.78, 95% CI 0.72-0.83) and the Mortality in Emergency Department Sepsis score (AUC 0.77, 95% 0.71-0.83) demonstrated fair predictive ability (AUC>or=0.70) for in-hospital mortality. The best predictor of ICU admission was SMART-COP (AUC 0.73, 95% CI 0.67-0.79). All other scores were poor predictors (AUC <0.70) of either outcome. If patients classified as low risk for in-hospital mortality using the PSI were discharged, 35% of admissions would have been avoided. None of the scores studied were good predictors of in-hospital mortality or ICU admission. The PSI and MEDS score were fair predictors of death and if these results are validated, their use could reduce influenza admission rates significantly.

Prediction of transfer among multiple states of blood pressure based on Markov model: an 18-year cohort study.

PubMed

Wang, Yunfeng; Ma, Zhimin; Xu, Chaonan; Wang, ZiKun; Yang, Xinghua

2018-05-15

This study aimed to identify the rules of transition between normotension, prehypertension and hypertension states and to establish a prediction model for the incidence of prehypertension and hypertension. Data from the China Health and Nutrition Survey from 1991 to 2009 were used as training data to develop the model. Data of the year 2011 were used for model validation. The multistate Markov model was developed using the msm package in R software. A total of 5265 participants were included at baseline, with an average follow-up of 8.05 ± 5.27 years and 17 640 observations. The ratio of men to women was 1 : 1.17, and the mean age was 37.54 ± 13.80 years. Within 10 years, in men, from normotension, the average probability to prehypertension and hypertension are 34.5 and 35.25%, respectively; from prehypertension, the average probability of recovering to normotension and developing to hypertension are 17.78 and 43.85%, respectively. In women, the average probabilities are 27.49, 28.09, 29.11 and 39.05%. Fat consumption increasing was found to be a protective factor, with 4.5% lower rate of transferring from normotension to prehypertension for a quarter percentage increasing. The model showed a very good prediction ability within 10 years and provided good prediction of blood pressure in the 2011 cohort (χ = 0.781, P = 0.676). The multistate Markov model can be a useful tool to identify the rules of transition among multiple states of blood pressure and predict well prevalence of the normotension, prehypertension and hypertension in cohort populations.

Predicting the risk for hospital-onset Clostridium difficile infection (HO-CDI) at the time of inpatient admission: HO-CDI risk score.

PubMed

Tabak, Ying P; Johannes, Richard S; Sun, Xiaowu; Nunez, Carlos M; McDonald, L Clifford

2015-06-01

To predict the likelihood of hospital-onset Clostridium difficile infection (HO-CDI) based on patient clinical presentations at admission Retrospective data analysis Six US acute care hospitals Adult inpatients We used clinical data collected at the time of admission in electronic health record (EHR) systems to develop and validate a HO-CDI predictive model. The outcome measure was HO-CDI cases identified by a nonduplicate positive C. difficile toxin assay result with stool specimens collected >48 hours after inpatient admission. We fit a logistic regression model to predict the risk of HO-CDI. We validated the model using 1,000 bootstrap simulations. Among 78,080 adult admissions, 323 HO-CDI cases were identified (ie, a rate of 4.1 per 1,000 admissions). The logistic regression model yielded 14 independent predictors, including hospital community onset CDI pressure, patient age ≥65, previous healthcare exposures, CDI in previous admission, admission to the intensive care unit, albumin ≤3 g/dL, creatinine >2.0 mg/dL, bands >32%, platelets ≤150 or >420 109/L, and white blood cell count >11,000 mm3. The model had a c-statistic of 0.78 (95% confidence interval [CI], 0.76-0.81) with good calibration. Among 79% of patients with risk scores of 0-7, 19 HO-CDIs occurred per 10,000 admissions; for patients with risk scores >20, 623 HO-CDIs occurred per 10,000 admissions (P<.0001). Using clinical parameters available at the time of admission, this HO-CDI model demonstrated good predictive ability, and it may have utility as an early risk identification tool for HO-CDI preventive interventions and outcome comparisons.

Back to the Future with the Uniform Code of Military Justice: The Need to Recalibrate the Relationship Between the Military Justice System, Due Process, and Good Order and Discipline

DTIC Science & Technology

2014-04-01

successes against the Roman army, Plutarch focused on Sertorius’ ability to bring good order and discipline to the seemingly barbaric tribes of the...Roman frontier.161 Plutarch noted that after the campaigns against Rome, Sertorius was “highly honored for his introducing discipline and good order...Sertorius’ ability to achieve good order and discipline within his troops, Plutarch did not mention discipline or fear; instead, he noted that Sertorius

The creation and evaluation of a model to simulate the probability of conception in seasonal-calving pasture-based dairy heifers.

PubMed

Fenlon, Caroline; O'Grady, Luke; Butler, Stephen; Doherty, Michael L; Dunnion, John

2017-01-01

Herd fertility in pasture-based dairy farms is a key driver of farm economics. Models for predicting nulliparous reproductive outcomes are rare, but age, genetics, weight, and BCS have been identified as factors influencing heifer conception. The aim of this study was to create a simulation model of heifer conception to service with thorough evaluation. Artificial Insemination service records from two research herds and ten commercial herds were provided to build and evaluate the models. All were managed as spring-calving pasture-based systems. The factors studied were related to age, genetics, and time of service. The data were split into training and testing sets and bootstrapping was used to train the models. Logistic regression (with and without random effects) and generalised additive modelling were selected as the model-building techniques. Two types of evaluation were used to test the predictive ability of the models: discrimination and calibration. Discrimination, which includes sensitivity, specificity, accuracy and ROC analysis, measures a model's ability to distinguish between positive and negative outcomes. Calibration measures the accuracy of the predicted probabilities with the Hosmer-Lemeshow goodness-of-fit, calibration plot and calibration error. After data cleaning and the removal of services with missing values, 1396 services remained to train the models and 597 were left for testing. Age, breed, genetic predicted transmitting ability for calving interval, month and year were significant in the multivariate models. The regression models also included an interaction between age and month. Year within herd was a random effect in the mixed regression model. Overall prediction accuracy was between 77.1% and 78.9%. All three models had very high sensitivity, but low specificity. The two regression models were very well-calibrated. The mean absolute calibration errors were all below 4%. Because the models were not adept at identifying unsuccessful services, they are not suggested for use in predicting the outcome of individual heifer services. Instead, they are useful for the comparison of services with different covariate values or as sub-models in whole-farm simulations. The mixed regression model was identified as the best model for prediction, as the random effects can be ignored and the other variables can be easily obtained or simulated.

Learning a Markov Logic network for supervised gene regulatory network inference

PubMed Central

2013-01-01

Background Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. Results We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate “regulates”, starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a pairwise SVM while providing relevant insights on the predictions. Conclusions The numerical studies show that MLN achieves very good predictive performance while opening the door to some interpretability of the decisions. Besides the ability to suggest new regulations, such an approach allows to cross-validate experimental data with existing knowledge. PMID:24028533

Rationale of the Spanish FRAX model in decision-making for predicting osteoporotic fractures: an update of FRIDEX cohort of Spanish women.

PubMed

Azagra, Rafael; Zwart, Marta; Encabo, Gloria; Aguyé, Amada; Martin-Sánchez, Juan Carlos; Puchol-Ruiz, Nuria; Gabriel-Escoda, Paula; Ortiz-Alinque, Sergio; Gené, Emilio; Iglesias, Milagros; Moriña, David; Diaz-Herrera, Miguel Angel; Utzet, Mireia; Manresa, Josep Maria

2016-06-17

The FRAX® tool estimates the risk of a fragility fracture among the population and many countries have been evaluating its performance among their populations since its creation in 2007. The purpose of this study is to update the first FRIDEX cohort analysis comparing FRAX with the bone mineral density (BMD) model, and its predictive abilities. The discriminatory ability of the FRAX was assessed using the 'area under curve' of the receiver operating characteristic (AUC-ROC). Predictive ability was assessed by comparing estimated risk fractures with incidence fractures after a 10-year follow up period. One thousand three hundred eight women ≥ 40 and ≤ 90 years followed up during a 10-year period. The AUC for major osteoporotic fractures using FRAX without DXA was 0.686 (95 % CI 0.630-0.742) and using FN T-score of DXA 0.714 (95 % CI 0.661-0.767). Using only the traditional parameters of DXA (FN T-score), the AUC was 0.706 (95 % CI 0.652-0.760). The AUC for hip osteoporotic fracture was 0.883 (95 % CI 0.827-0.938), 0.857 (95 % CI 0.773-0.941), and 0.814 (95 % CI 0.712-0.916) respectively. For major osteoporotic fractures, the overall predictive value using the ratio Observed fractures/Expected fractures calculated with FRAX without T-score of DXA was 2.29 and for hip fractures 2.28 and with the inclusion of the T-score 2.01 and 1.83 respectively. However, for hip fracture in women < 65 years was 1.53 and 1.24 respectively. The FRAX tool has been found to show a good discriminatory capacity for detecting women at high risk of fragility fracture, and is better for hip fracture than major fracture. The test of sensibility shows that it is, at least, not inferior than when using BMD model alone. The predictive capacity of FRAX tool needs some adjustment. This capacity is better for hip fracture prediction and better for women < 65 years. Further studies in Catalonia and other regions of Spain are needed to fine tune the FRAX tool's predictive capability.

Learning a Markov Logic network for supervised gene regulatory network inference.

PubMed

Brouard, Céline; Vrain, Christel; Dubois, Julie; Castel, David; Debily, Marie-Anne; d'Alché-Buc, Florence

2013-09-12

Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate "regulates", starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a pairwise SVM while providing relevant insights on the predictions. The numerical studies show that MLN achieves very good predictive performance while opening the door to some interpretability of the decisions. Besides the ability to suggest new regulations, such an approach allows to cross-validate experimental data with existing knowledge.

Prediction of Air Pollutants Concentration Based on an Extreme Learning Machine: The Case of Hong Kong

PubMed Central

Zhang, Jiangshe; Ding, Weifu

2017-01-01

With the development of the economy and society all over the world, most metropolitan cities are experiencing elevated concentrations of ground-level air pollutants. It is urgent to predict and evaluate the concentration of air pollutants for some local environmental or health agencies. Feed-forward artificial neural networks have been widely used in the prediction of air pollutants concentration. However, there are some drawbacks, such as the low convergence rate and the local minimum. The extreme learning machine for single hidden layer feed-forward neural networks tends to provide good generalization performance at an extremely fast learning speed. The major sources of air pollutants in Hong Kong are mobile, stationary, and from trans-boundary sources. We propose predicting the concentration of air pollutants by the use of trained extreme learning machines based on the data obtained from eight air quality parameters in two monitoring stations, including Sham Shui Po and Tap Mun in Hong Kong for six years. The experimental results show that our proposed algorithm performs better on the Hong Kong data both quantitatively and qualitatively. Particularly, our algorithm shows better predictive ability, with R2 increased and root mean square error values decreased respectively. PMID:28125034

Applicability of a panel method, which includes nonlinear effects, to a forward-swept-wing aircraft

NASA Technical Reports Server (NTRS)

Ross, J. C.

1984-01-01

The ability of a lower order panel method VSAERO, to accurately predict the lift and pitching moment of a complete forward-swept-wing/canard configuration was investigated. The program can simulate nonlinear effects including boundary-layer displacement thickness, wake roll up, and to a limited extent, separated wakes. The predictions were compared with experimental data obtained using a small-scale model in the 7- by 10- Foot Wind Tunnel at NASA Ames Research Center. For the particular configuration under investigation, wake roll up had only a small effect on the force and moment predictions. The effect of the displacement thickness modeling was to reduce the lift curve slope slightly, thus bringing the predicted lift into good agreement with the measured value. Pitching moment predictions were also improved by the boundary-layer simulation. The separation modeling was found to be sensitive to user inputs, but appears to give a reasonable representation of a separated wake. In general, the nonlinear capabilities of the code were found to improve the agreement with experimental data. The usefullness of the code would be enhanced by improving the reliability of the separated wake modeling and by the addition of a leading edge separation model.

The relationship between two visual communication systems: reading and lipreading.

PubMed

Williams, A

1982-12-01

To explore the relationship between reading and lipreading and to determine whether readers and lipreaders use similar strategies to comprehend verbal messages, 60 female junior and sophomore high school students--30 good and 30 poor readers--were given a filmed lipreading test, a test to measure eye-voice span, a test of cloze ability, and a test of their ability to comprehend printed material presented one word at a time in the absence of an opportunity to regress or scan ahead. The results of this study indicated that (a) there is a significant relationship between reading and lipreading ability; (b) although good readers may be either good or poor lipreaders, poor readers are more likely to be poor than good lipreaders; (c) there are similarities in the strategies used by readers and lipreaders in their approach to comprehending spoken and written material; (d) word-by-word reading of continuous prose appears to be a salient characteristic of both poor reading and poor lipreading ability; and (c) good readers and lipreaders do not engage in word-by-word reading but rather use a combination of visual and linguistic cues to interpret written and spoken messages.

The use of presurgical psychological screening to predict the outcome of spine surgery.

PubMed

Block, A R; Ohnmeiss, D D; Guyer, R D; Rashbaum, R F; Hochschuler, S H

2001-01-01

Several previous studies have shown that psychosocial factors can influence the outcome of elective spine surgery. The purpose of the current study was to determine how well a presurgical screening instrument could predict surgical outcome. The study was conducted by staff of a psychologist's office. They performed preoperative screening for spine surgery candidates and collected the follow-up data. Presurgical screening and follow-up data collection was performed on 204 patients who underwent laminectomy/discectomy (n=118) or fusion (n=86) of the lumbar spine. The outcome measures used in the study were visual analog pain scales, the Oswestry Disability Questionnaire, and medication use. A semi-structured interview and psychometric testing were used to identify specific, quantifiable psychological, and "medical" risk factors for poor surgical outcome. A presurgical psychological screening (PPS) scorecard was completed for each patient, assessing whether the patient had a high or low level of risk on these psychological and medical dimensions. Based on the scorecard, an overall surgical prognosis of "good," "fair," or "poor" was generated. Results showed spine surgery led to significant overall improvements in pain, functional ability, and medication use. Medical and psychological risk levels were significantly related to outcome, with the poorest results obtained by patients having both high psychological and medical risk. Further, the accuracy of PPS surgical prognosis in predicting overall outcome was 82%. Only 9 of 53 patients predicted to have poor outcome achieved fair or good results from spine surgery. These findings suggest that PPS should become a more routine part of the evaluation of chronic pain patients in whom spine surgery is being considered.

Melanoma-specific mortality and competing mortality in patients with non-metastatic malignant melanoma: a population-based analysis.

PubMed

Shen, Weidong; Sakamoto, Naoko; Yang, Limin

2016-07-07

The objectives of this study were to evaluate and model the probability of melanoma-specific death and competing causes of death for patients with melanoma by competing risk analysis, and to build competing risk nomograms to provide individualized and accurate predictive tools. Melanoma data were obtained from the Surveillance Epidemiology and End Results program. All patients diagnosed with primary non-metastatic melanoma during the years 2004-2007 were potentially eligible for inclusion. The cumulative incidence function (CIF) was used to describe the probability of melanoma mortality and competing risk mortality. We used Gray's test to compare differences in CIF between groups. The proportional subdistribution hazard approach by Fine and Gray was used to model CIF. We built competing risk nomograms based on the models that we developed. The 5-year cumulative incidence of melanoma death was 7.1 %, and the cumulative incidence of other causes of death was 7.4 %. We identified that variables associated with an elevated probability of melanoma-specific mortality included older age, male sex, thick melanoma, ulcerated cancer, and positive lymph nodes. The nomograms were well calibrated. C-indexes were 0.85 and 0.83 for nomograms predicting the probability of melanoma mortality and competing risk mortality, which suggests good discriminative ability. This large study cohort enabled us to build a reliable competing risk model and nomogram for predicting melanoma prognosis. Model performance proved to be good. This individualized predictive tool can be used in clinical practice to help treatment-related decision making.

Longitudinal change in the BODE index predicts mortality in severe emphysema.

PubMed

Martinez, Fernando J; Han, Meilan K; Andrei, Adin-Cristian; Wise, Robert; Murray, Susan; Curtis, Jeffrey L; Sternberg, Alice; Criner, Gerard; Gay, Steven E; Reilly, John; Make, Barry; Ries, Andrew L; Sciurba, Frank; Weinmann, Gail; Mosenifar, Zab; DeCamp, Malcolm; Fishman, Alfred P; Celli, Bartolome R

2008-09-01

The predictive value of longitudinal change in BODE (Body mass index, airflow Obstruction, Dyspnea, and Exercise capacity) index has received limited attention. We hypothesized that decrease in a modified BODE (mBODE) would predict survival in National Emphysema Treatment Trial (NETT) patients. To determine how the mBODE score changes in patients with lung volume reduction surgery versus medical therapy and correlations with survival. Clinical data were recorded using standardized instruments. The mBODE was calculated and patient-specific mBODE trajectories during 6, 12, and 24 months of follow-up were estimated using separate regressions for each patient. Patients were classified as having decreasing, stable, increasing, or missing mBODE based on their absolute change from baseline. The predictive ability of mBODE change on survival was assessed using multivariate Cox regression models. The index of concordance was used to directly compare the predictive ability of mBODE and its separate components. The entire cohort (610 treated medically and 608 treated surgically) was characterized by severe airflow obstruction, moderate breathlessness, and increased mBODE at baseline. A wide distribution of change in mBODE was seen at follow-up. An increase in mBODE of more than 1 point was associated with increased mortality in surgically and medically treated patients. Surgically treated patients were less likely to experience death or an increase greater than 1 in mBODE. Indices of concordance showed that mBODE change predicted survival better than its separate components. The mBODE demonstrates short- and intermediate-term responsiveness to intervention in severe chronic obstructive pulmonary disease. Increase in mBODE of more than 1 point from baseline to 6, 12, and 24 months of follow-up was predictive of subsequent mortality. Change in mBODE may prove a good surrogate measure of survival in therapeutic trials in severe chronic obstructive pulmonary disease. Clinical trial registered with www.clinicaltrials.gov (NCT 00000606).

Nice Voices Are a Dime a Dozen.

ERIC Educational Resources Information Center

Hollahan, Patricia Welting

1979-01-01

To succeed in today's competitive opera world, a singer needs--in addition to a good voice--personality, acting ability, good appearance, musicianship, language facility, versatility, and experience. Especially important are sight reading skills, care of the voice, and the ability to express emotion. Part of a theme issue on opera. (Author/SJL)

Beyond Climate and Weather Science: Expanding the Forecasting Family to Serve Societal Needs

NASA Astrophysics Data System (ADS)

Barron, E. J.

2009-05-01

The ability to "anticipate" the future is what makes information from the Earth sciences valuable to society - whether it is the prediction of severe weather or the future availability of water resources in response to climate change. An improved ability to anticipate or forecast has the potential to serve society by simultaneously improving our ability to (1) promote economic vitality, (2) enable environmental stewardship, (3) protect life and property, as well as (4) improve our fundamental knowledge of the earth system. The potential is enormous, yet many appear ready to move quickly toward specific mitigation and adaptation strategies assuming that the science is settled. Five important weakness must be addressed first: (1) the formation of a true "climate services" function and capability, (2) the deliberate investment in expanding the family of forecasting elements to incorporate a broader array of environmental factors and impacts, (3) the investment in the sciences that connect climate to society, (4) a deliberate focus on the problems associated with scale, in particular the difference between the scale of predictive models and the scale associated with societal decisions, and (5) the evolution from climate services and model predictions to the equivalent of "environmental intelligence centers." The objective is to bring the discipline of forecasting to a broader array of environmental challenges. Assessments of the potential impacts of global climate change on societal sectors such as water, human health, and agriculture provide good examples of this challenge. We have the potential to move from a largely reactive mode in addressing adverse health outcomes, for example, to one in which the ties between climate, land cover, infectious disease vectors, and human health are used to forecast and predict adverse human health conditions. The potential exists for a revolution in forecasting, that entrains a much broader set of societal needs and solutions. The argument is made that (for example) the current capabilities in the prediction of environmental health is similar to the capabilities (and potential) of weather forecasting in the 1960's.

Not equal in the face of habitat change: closely related fishes differ in their ability to use predation-related information in degraded coral

PubMed Central

2017-01-01

Coral reefs are biodiversity hotpots that are under significant threat due to the degradation and death of hard corals. When obligate coral-dwelling species die, the remaining species must either move or adjust to the altered conditions. Our goal was to investigate the effect of coral degradation on the ability of coral reef fishes to assess their risk of predation using alarm cues from injured conspecifics. Here, we tested the ability of six closely related species of juvenile damselfish (Pomacentridae) to respond to risk cues in both live coral or dead-degraded coral environments. Of those six species, two are exclusively associated with live coral habitats, two are found mostly on dead-degraded coral rubble, while the last two are found in both habitat types. We found that the two live coral associates failed to respond appropriately to the cues in water from degraded habitats. In contrast, the cue response of the two rubble associates was unaffected in the same degraded habitat. Interestingly, we observed a mixed response from the species found in both habitat types, with one species displaying an appropriate cue response while the other did not. Our second experiment suggested that the lack of responses stemmed from deactivation of the alarm cues, rather than the inability of the species to smell. Habitat preference (live coral versus dead coral associates) and phylogeny are good candidates for future work aimed at predicting which species are affected by coral degradation. Our results point towards a surprising level of variation in the ability of congeneric species to fare in altered habitats and hence underscores the difficulty of predicting community change in degraded habitats. PMID:28404773

Ability to Categorize Food Predicts Hypothetical Food Choices in Head Start Preschoolers.

PubMed

Nicholson, Jody S; Barton, Jennifer M; Simons, Ali L

2018-03-01

To investigate whether preschoolers are able to identify and categorize foods, and whether their ability to classify food as healthy predicts their hypothetical food choice. Structured interviews and body measurements with preschoolers, and teacher reports of classroom performance. Six Head Start centers in a large southeastern region. A total of 235 preschoolers (mean age [SD], 4.73 [0.63] years; 45.4% girls). Teachers implemented a nutrition education intervention across the 2014-2015 school year in which children were taught to identify and categorize food as sometimes (ie, unhealthy) and anytime (ie, healthy). Preschooler responses to a hypothetical snack naming, classifying, and selection scenario. Hierarchical regression analyses to examine predictors of child hypothetical food selection. While controlling for child characteristics and cognitive functioning, preschoolers who were better at categorizing food as healthy or unhealthy were more likely to say they would choose the healthy food. Low-contrast food pairs in which food had to be classified based on multiple dimensions were outside the cognitive abilities of the preschoolers. Nutrition interventions may be more effective in helping children make healthy food choices if developmental limitations in preschoolers' abilities to categorize food is addressed in their curriculum. Classification of food into evaluative categories is challenging for this age group. Categorizing on multiple dimensions is difficult, and dichotomous labeling of food as good or bad is not always accurate in directing children toward making food choices. Future research could evaluate further preschoolers' developmental potential for food categorization and nutrition decision making and consider factors that influence healthy food choices at both snack and mealtime. Copyright © 2017 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Not equal in the face of habitat change: closely related fishes differ in their ability to use predation-related information in degraded coral.

PubMed

Ferrari, Maud C O; McCormick, Mark I; Allan, Bridie J M; Chivers, Douglas P

2017-04-12

Coral reefs are biodiversity hotpots that are under significant threat due to the degradation and death of hard corals. When obligate coral-dwelling species die, the remaining species must either move or adjust to the altered conditions. Our goal was to investigate the effect of coral degradation on the ability of coral reef fishes to assess their risk of predation using alarm cues from injured conspecifics. Here, we tested the ability of six closely related species of juvenile damselfish (Pomacentridae) to respond to risk cues in both live coral or dead-degraded coral environments. Of those six species, two are exclusively associated with live coral habitats, two are found mostly on dead-degraded coral rubble, while the last two are found in both habitat types. We found that the two live coral associates failed to respond appropriately to the cues in water from degraded habitats. In contrast, the cue response of the two rubble associates was unaffected in the same degraded habitat. Interestingly, we observed a mixed response from the species found in both habitat types, with one species displaying an appropriate cue response while the other did not. Our second experiment suggested that the lack of responses stemmed from deactivation of the alarm cues, rather than the inability of the species to smell. Habitat preference (live coral versus dead coral associates) and phylogeny are good candidates for future work aimed at predicting which species are affected by coral degradation. Our results point towards a surprising level of variation in the ability of congeneric species to fare in altered habitats and hence underscores the difficulty of predicting community change in degraded habitats. © 2017 The Authors.

Clinical and genetic correlates of decision making in anorexia nervosa.

PubMed

Tenconi, Elena; Degortes, Daniela; Clementi, Maurizio; Collantoni, Enrico; Pinato, Claudia; Forzan, Monica; Cassina, Matteo; Santonastaso, Paolo; Favaro, Angela

2016-01-01

Decision-making (DM) abilities have been found to be impaired in anorexia nervosa (AN), but few data are available about the characteristics and correlates of this cognitive function. The aim of the present study was to provide data on DM functioning in AN using both veridical and adaptive paradigms. While in veridical DM tasks, the individual's ability to predict a true/false response is measured, adaptive DM is the ability to consider both internal and external demands in order to make a good choice, in the absence of a single true "correct" answer. The participants were 189 women, of whom 91 were eating-disordered patients with a lifetime diagnosis of anorexia nervosa, and 98 were healthy women. All the participants underwent clinical, neuropsychological, and genetic assessment. The cognitive evaluation included a set of neuropsychological tasks and two decision-making tests: The Iowa Gambling Task and the Cognitive Bias Task. Anorexia nervosa patients showed significantly poorer performances on both decision-making tasks than healthy women. The Cognitive Bias Task revealed that anorexia nervosa patients employed significantly more context-independent decision-making strategies, which were independent from diagnostic subtype, handedness, education, and psychopathology. In the whole sample (patients and controls), Cognitive Bias Task performance was independently predicted by lifetime anorexia nervosa diagnosis, body mass index at assessment, and 5-HTTLPR genotype. Patients displayed poor decision-making functioning in both veridical and adaptive situations. The difficulties detected in anorexia nervosa individuals may affect not only the ability to consider the future outcomes of their actions (leading to "myopia for the future"), but also the capacity to update and review one's own mindset according to new environmental stimuli.

Genetic improvement of mastitis resistance: validation of somatic cell score and clinical mastitis as selection criteria.

PubMed

Odegård, J; Klemetsdal, G; Heringstad, B

2003-12-01

Mean daughter deviations for clinical mastitis among second-crop daughters were regressed on predicted transmitting abilities for clinical mastitis and lactation mean somatic cell score in first-crop daughters to validate the predictive ability of these traits as selection criteria for reduced incidence of clinical mastitis. A total of 321 sires had 684,897 second-crop daughters, while predicted transmitting abilities were calculated for 2159 sires, based on 495,681 records of first-crop daughters. Predictive ability, as a measure of efficiency of selection, was 23 to 43% higher for clinical mastitis than for lactation mean somatic cell score. Compared to single-trait selection, predictive ability improved 8 to 13% from utilizing information on both traits. The relative weight that should be assigned to standardized predicted transmitting abilities from univariate genetic analyses were 60 to 67% for clinical mastitis and 33 to 40% for lactation mean somatic cell score. No significant nonlinear genetic relationship between the two traits was found.

Quantification of hazard prediction ability at hazard prediction training (Kiken-Yochi Training: KYT) by free-response receiver-operating characteristic (FROC) analysis.

PubMed

Hashida, Masahiro; Kamezaki, Ryousuke; Goto, Makoto; Shiraishi, Junji

2017-03-01

The ability to predict hazards in possible situations in a general X-ray examination room created for Kiken-Yochi training (KYT) is quantified by use of free-response receiver-operating characteristics (FROC) analysis for determining whether the total number of years of clinical experience, involvement in general X-ray examinations, occupation, and training each have an impact on the hazard prediction ability. Twenty-three radiological technologists (RTs) (years of experience: 2-28), four nurses (years of experience: 15-19), and six RT students observed 53 scenes of KYT: 26 scenes with hazardous points (hazardous points are those that might cause injury to patients) and 27 scenes without points. Based on the results of these observations, we calculated the alternative free-response receiver-operating characteristic (AFROC) curve and the figure of merit (FOM) to quantify the hazard prediction ability. The results showed that the total number of years of clinical experience did not have any impact on hazard prediction ability, whereas recent experience with general X-ray examinations greatly influenced this ability. In addition, the hazard prediction ability varied depending on the occupations of the observers while they were observing the same scenes in KYT. The hazard prediction ability of the radiologic technology students was improved after they had undergone patient safety training. This proposed method with FROC observer study enabled the quantification and evaluation of the hazard prediction capability, and the application of this approach to clinical practice may help to ensure the safety of examinations and treatment in the radiology department.

Predicting functional ability in mild cognitive impairment with the Dementia Rating Scale-2.

PubMed

Greenaway, Melanie C; Duncan, Noah L; Hanna, Sherrie; Smith, Glenn E

2012-06-01

We examined the utility of cognitive evaluation to predict instrumental activities of daily living (IADLs) and decisional ability in Mild Cognitive Impairment (MCI). Sixty-seven individuals with single-domain amnestic MCI were administered the Dementia Rating Scale-2 (DRS-2) as well as the Everyday Cognition assessment form to assess functional ability. The DRS-2 Total Scores and Initiation/Perseveration and Memory subscales were found to be predictive of IADLs, with Total Scores accounting for 19% of the variance in IADL performance on average. In addition, the DRS-2 Initiation/Perseveration and Total Scores were predictive of ability to understand information, and the DRS-2 Conceptualization helped predict ability to communicate with others, both key variables in decision-making ability. These findings suggest that performance on the DRS-2, and specific subscales related to executive function and memory, is significantly related to IADLs in individuals with MCI. These cognitive measures are also associated with decision-making-related abilities in MCI.

Experimental investigation of elastic mode control on a model of a transport aircraft

NASA Technical Reports Server (NTRS)

Abramovitz, M.; Heimbaugh, R. M.; Nomura, J. K.; Pearson, R. M.; Shirley, W. A.; Stringham, R. H.; Tescher, E. L.; Zoock, I. E.

1981-01-01

A 4.5 percent DC-10 derivative flexible model with active controls is fabricated, developed, and tested to investigate the ability to suppress flutter and reduce gust loads with active controlled surfaces. The model is analyzed and tested in both semispan and complete model configuration. Analytical methods are refined and control laws are developed and successfully tested on both versions of the model. A 15 to 25 percent increase in flutter speed due to the active system is demonstrated. The capability of an active control system to significantly reduce wing bending moments due to turbulence is demonstrated. Good correlation is obtained between test and analytical prediction.

An analytical and experimental evaluation of shadow shields and their support members

NASA Technical Reports Server (NTRS)

Stochl, R. J.; Boyle, R. J.

1972-01-01

Experimental tests were performed on a model shadow shield thermal protection system to examine the effect of certain configuration variables. The experimental results were used to verify the ability of an analytical program to predict the shadow shield performance including the shield-support interaction. In general, the analysis (assuming diffuse surfaces) agreed well with the experimental support temperature profiles. The agreement for the shield profiles was not as good. The results demonstrated: (1) shadow shields can be effective in reducing the heat transfer into cryogenic propellant tanks, and (2) the conductive heat transfer through supports can be reduced by selective surface coatings.

Nomogram Prediction of Overall Survival After Curative Irradiation for Uterine Cervical Cancer

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

Seo, YoungSeok; Yoo, Seong Yul; Kim, Mi-Sook

Purpose: The purpose of this study was to develop a nomogram capable of predicting the probability of 5-year survival after radical radiotherapy (RT) without chemotherapy for uterine cervical cancer. Methods and Materials: We retrospectively analyzed 549 patients that underwent radical RT for uterine cervical cancer between March 1994 and April 2002 at our institution. Multivariate analysis using Cox proportional hazards regression was performed and this Cox model was used as the basis for the devised nomogram. The model was internally validated for discrimination and calibration by bootstrap resampling. Results: By multivariate regression analysis, the model showed that age, hemoglobin levelmore » before RT, Federation Internationale de Gynecologie Obstetrique (FIGO) stage, maximal tumor diameter, lymph node status, and RT dose at Point A significantly predicted overall survival. The survival prediction model demonstrated good calibration and discrimination. The bootstrap-corrected concordance index was 0.67. The predictive ability of the nomogram proved to be superior to FIGO stage (p = 0.01). Conclusions: The devised nomogram offers a significantly better level of discrimination than the FIGO staging system. In particular, it improves predictions of survival probability and could be useful for counseling patients, choosing treatment modalities and schedules, and designing clinical trials. However, before this nomogram is used clinically, it should be externally validated.« less

Prediction of p38 map kinase inhibitory activity of 3, 4-dihydropyrido [3, 2-d] pyrimidone derivatives using an expert system based on principal component analysis and least square support vector machine

PubMed Central

Shahlaei, M.; Saghaie, L.

2014-01-01

A quantitative structure–activity relationship (QSAR) study is suggested for the prediction of biological activity (pIC50) of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors. Modeling of the biological activities of compounds of interest as a function of molecular structures was established by means of principal component analysis (PCA) and least square support vector machine (LS-SVM) methods. The results showed that the pIC50 values calculated by LS-SVM are in good agreement with the experimental data, and the performance of the LS-SVM regression model is superior to the PCA-based model. The developed LS-SVM model was applied for the prediction of the biological activities of pyrimidone derivatives, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.460 for LS-SVM. The study provided a novel and effective approach for predicting biological activities of 3, 4-dihydropyrido [3,2-d] pyrimidone derivatives as p38 inhibitors and disclosed that LS-SVM can be used as a powerful chemometrics tool for QSAR studies. PMID:26339262

Effects and detection of raw material variability on the performance of near-infrared calibration models for pharmaceutical products.

PubMed

Igne, Benoit; Shi, Zhenqi; Drennen, James K; Anderson, Carl A

2014-02-01

The impact of raw material variability on the prediction ability of a near-infrared calibration model was studied. Calibrations, developed from a quaternary mixture design comprising theophylline anhydrous, lactose monohydrate, microcrystalline cellulose, and soluble starch, were challenged by intentional variation of raw material properties. A design with two theophylline physical forms, three lactose particle sizes, and two starch manufacturers was created to test model robustness. Further challenges to the models were accomplished through environmental conditions. Along with full-spectrum partial least squares (PLS) modeling, variable selection by dynamic backward PLS and genetic algorithms was utilized in an effort to mitigate the effects of raw material variability. In addition to evaluating models based on their prediction statistics, prediction residuals were analyzed by analyses of variance and model diagnostics (Hotelling's T(2) and Q residuals). Full-spectrum models were significantly affected by lactose particle size. Models developed by selecting variables gave lower prediction errors and proved to be a good approach to limit the effect of changing raw material characteristics. Hotelling's T(2) and Q residuals provided valuable information that was not detectable when studying only prediction trends. Diagnostic statistics were demonstrated to be critical in the appropriate interpretation of the prediction of quality parameters. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

Semi-supervised protein subcellular localization.

PubMed

Xu, Qian; Hu, Derek Hao; Xue, Hong; Yu, Weichuan; Yang, Qiang

2009-01-30

Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data. In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions. Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.

Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

PubMed

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

How Good Are Statistical Models at Approximating Complex Fitness Landscapes?

PubMed Central

du Plessis, Louis; Leventhal, Gabriel E.; Bonhoeffer, Sebastian

2016-01-01

Fitness landscapes determine the course of adaptation by constraining and shaping evolutionary trajectories. Knowledge of the structure of a fitness landscape can thus predict evolutionary outcomes. Empirical fitness landscapes, however, have so far only offered limited insight into real-world questions, as the high dimensionality of sequence spaces makes it impossible to exhaustively measure the fitness of all variants of biologically meaningful sequences. We must therefore revert to statistical descriptions of fitness landscapes that are based on a sparse sample of fitness measurements. It remains unclear, however, how much data are required for such statistical descriptions to be useful. Here, we assess the ability of regression models accounting for single and pairwise mutations to correctly approximate a complex quasi-empirical fitness landscape. We compare approximations based on various sampling regimes of an RNA landscape and find that the sampling regime strongly influences the quality of the regression. On the one hand it is generally impossible to generate sufficient samples to achieve a good approximation of the complete fitness landscape, and on the other hand systematic sampling schemes can only provide a good description of the immediate neighborhood of a sequence of interest. Nevertheless, we obtain a remarkably good and unbiased fit to the local landscape when using sequences from a population that has evolved under strong selection. Thus, current statistical methods can provide a good approximation to the landscape of naturally evolving populations. PMID:27189564

Predicting Gender-Role Attitudes in Adolescent Females: Ability, Agency, and Parental Factors.

ERIC Educational Resources Information Center

Ahrens, Julia A.; O'Brien, Karen M.

1996-01-01

Investigated the contribution of ability, agency, and parental factors to the prediction of gender-role attitudes of 409 adolescent females in a private, college-preparatory high school. Findings indicate that ability and agency were predictive of gender-role attitudes, whereas parental factors were not significant contributors. Recommendations…

Copula Entropy coupled with Wavelet Neural Network Model for Hydrological Prediction

NASA Astrophysics Data System (ADS)

Wang, Yin; Yue, JiGuang; Liu, ShuGuang; Wang, Li

2018-02-01

Artificial Neural network(ANN) has been widely used in hydrological forecasting. in this paper an attempt has been made to find an alternative method for hydrological prediction by combining Copula Entropy(CE) with Wavelet Neural Network(WNN), CE theory permits to calculate mutual information(MI) to select Input variables which avoids the limitations of the traditional linear correlation(LCC) analysis. Wavelet analysis can provide the exact locality of any changes in the dynamical patterns of the sequence Coupled with ANN Strong non-linear fitting ability. WNN model was able to provide a good fit with the hydrological data. finally, the hybrid model(CE+WNN) have been applied to daily water level of Taihu Lake Basin, and compared with CE ANN, LCC WNN and LCC ANN. Results showed that the hybrid model produced better results in estimating the hydrograph properties than the latter models.

Evaluation of a novel electronic eigenvalue (EEVA) molecular descriptor for QSAR/QSPR studies: validation using a benchmark steroid data set.

PubMed

Tuppurainen, Kari; Viisas, Marja; Laatikainen, Reino; Peräkylä, Mikael

2002-01-01

A novel electronic eigenvalue (EEVA) descriptor of molecular structure for use in the derivation of predictive QSAR/QSPR models is described. Like other spectroscopic QSAR/QSPR descriptors, EEVA is also invariant as to the alignment of the structures concerned. Its performance was tested with respect to the CBG (corticosteroid binding globulin) affinity of 31 benchmark steroids. It appeared that the electronic structure of the steroids, i.e., the "spectra" derived from molecular orbital energies, is directly related to the CBG binding affinities. The predictive ability of EEVA is compared to other QSAR approaches, and its performance is discussed in the context of the Hammett equation. The good performance of EEVA is an indication of the essential quantum mechanical nature of QSAR. The EEVA method is a supplement to conventional 3D QSAR methods, which employ fields or surface properties derived from Coulombic and van der Waals interactions.

Measuring Student Effort and Engagement in an Introductory Physics Course

NASA Astrophysics Data System (ADS)

Bonham, Scott

2007-11-01

Multiple scales reflecting student effort were developed using factor and scale analysis on data from an introductory physics course. This data included interactions with an on-line homework system. One of the scales displays many characteristics of a metric of the individual level of engagement in the course. This scale is shown to be a good predictor of performance on class exams and the Force Concept Inventory (FCI). Furthermore, normalized learning gains on the FCI are well predicted by this scale while pre-instructional FCI scores provide no additional predictive ability, agreeing with observations by Richard Hake. This scale also correlates strongly with epistemological beliefs that learning is related to effort and is the responsibility of the student. The factors that enter into this scale, writing and mastering expert-like problem-solving, are consistent with this being a measure of individual levels of class engagement.

Is Approximate Number Precision a Stable Predictor of Math Ability?

ERIC Educational Resources Information Center

Libertus, Melissa E.; Feigenson, Lisa; Halberda, Justin

2013-01-01

Previous research shows that children's ability to estimate numbers of items using their Approximate Number System (ANS) predicts later math ability. To more closely examine the predictive role of early ANS acuity on later abilities, we assessed the ANS acuity, math ability, and expressive vocabulary of preschoolers twice, six months apart. We…

Predicting Arithmetic Abilities: The Role of Preparatory Arithmetic Markers and Intelligence

ERIC Educational Resources Information Center

Stock, Pieter; Desoete, Annemie; Roeyers, Herbert

2009-01-01

Arithmetic abilities acquired in kindergarten are found to be strong predictors for later deficient arithmetic abilities. This longitudinal study (N = 684) was designed to examine if it was possible to predict the level of children's arithmetic abilities in first and second grade from their performance on preparatory arithmetic abilities in…

SOLAR FLARE PREDICTION USING SDO/HMI VECTOR MAGNETIC FIELD DATA WITH A MACHINE-LEARNING ALGORITHM

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

Bobra, M. G.; Couvidat, S., E-mail: couvidat@stanford.edu

2015-01-10

We attempt to forecast M- and X-class solar flares using a machine-learning algorithm, called support vector machine (SVM), and four years of data from the Solar Dynamics Observatory's Helioseismic and Magnetic Imager, the first instrument to continuously map the full-disk photospheric vector magnetic field from space. Most flare forecasting efforts described in the literature use either line-of-sight magnetograms or a relatively small number of ground-based vector magnetograms. This is the first time a large data set of vector magnetograms has been used to forecast solar flares. We build a catalog of flaring and non-flaring active regions sampled from a databasemore » of 2071 active regions, comprised of 1.5 million active region patches of vector magnetic field data, and characterize each active region by 25 parameters. We then train and test the machine-learning algorithm and we estimate its performances using forecast verification metrics with an emphasis on the true skill statistic (TSS). We obtain relatively high TSS scores and overall predictive abilities. We surmise that this is partly due to fine-tuning the SVM for this purpose and also to an advantageous set of features that can only be calculated from vector magnetic field data. We also apply a feature selection algorithm to determine which of our 25 features are useful for discriminating between flaring and non-flaring active regions and conclude that only a handful are needed for good predictive abilities.« less

A model for autumn pelagic distribution of adult female polar bears in the Chukchi Seas, 1987-1994

USGS Publications Warehouse

Durner, George M.; Douglas, David C.; Nielson, R.M.; Amstrup, Steven C.

2006-01-01

We made predictions of polar bear (Ursus maritimus) autumn distribution in the Chukchi Sea with a Resource Selection Function (RSF) developed from 1198 satellite radio-collar locations on 124 adult female polar bears, 1987 – 1994. The RSF was created to assist in an aerial survey design for polar bears proposed by the U.S. Fish and Wildlife Service. The RSF was based on bathymetry and daily sea ice covariates extracted from passive microwave satellite imagery within the pelagic region > 25 km from shore. The RSF indicated that polar bears selected habitats with intermediate amounts (~50%) of ice cover in close proximity to higher ice concentrations, and over relatively shallow waters. The RSF showed good predictive abilities for the years of its construct, worked best in October, and was robust to inter-annual variability. When evaluated with recent (1997 – 2005) data, the RSF performed well for October and November but poorly in September. This loss of predictive abilities appeared to be related to recent changes in habitat due to longer melt seasons and younger sea ice, and testing the retrospective model with a small sample of recent polar bears locations from a limited region of the Chukchi Sea. Contemporary applications of this RSF must consider three factors that could limit its utility: 1) 2 different sea ice phenology; 2) distributions of males and sub-adults; and 3) occupancy in nearshore habitats.

Design, synthesis, antiviral bioactivity and three-dimensional quantitative structure-activity relationship study of novel ferulic acid ester derivatives containing quinazoline moiety.

PubMed

Wu, Zengxue; Zhang, Jian; Chen, Jixiang; Pan, Jianke; Zhao, Lei; Liu, Dengyue; Zhang, Awei; Chen, Jin; Hu, Deyu; Song, Baoan

2017-10-01

Ferulic acid and quinazoline derivatives possess good antiviral activities. In order to develop novel compounds with high antiviral activities, a series of ferulic acid ester derivatives containing quinazoline were synthesized and evaluated for their antiviral activities. Bioassays indicated that some of the compounds exhibited good antiviral activities in vivo against tobacco mosaic virus (TMV) and cucumber mosaic virus (CMV). One of the compounds demonstrated significant curative and protective activities against TMV and CMV, with EC 50 values of 162.14, 114.61 and 255.49, 138.81 mg L -1 , respectively, better than those of ningnanmycin (324.51, 168.84 and 373.88, 272.70 mg L -1 ). The values of q 2 and r 2 for comparative molecular field analysis and comparative molecular similarity index analysis in the TMV (0.508, 0.663 and 0.992, 0.930) and CMV (0.530, 0.626 and 0.997, 0.981) models presented good predictive abilities. Some of the title compounds demonstrated good antiviral activities. Three-dimensional quantitative structure-activity relationship models revealed that the antiviral activities depend on steric and electrostatic properties. These results could provide significant structural insights for the design of highly active ferulic acid derivatives. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Benchmarking test of empirical root water uptake models

NASA Astrophysics Data System (ADS)

dos Santos, Marcos Alex; de Jong van Lier, Quirijn; van Dam, Jos C.; Freire Bezerra, Andre Herman

2017-01-01

Detailed physical models describing root water uptake (RWU) are an important tool for the prediction of RWU and crop transpiration, but the hydraulic parameters involved are hardly ever available, making them less attractive for many studies. Empirical models are more readily used because of their simplicity and the associated lower data requirements. The purpose of this study is to evaluate the capability of some empirical models to mimic the RWU distribution under varying environmental conditions predicted from numerical simulations with a detailed physical model. A review of some empirical models used as sub-models in ecohydrological models is presented, and alternative empirical RWU models are proposed. All these empirical models are analogous to the standard Feddes model, but differ in how RWU is partitioned over depth or how the transpiration reduction function is defined. The parameters of the empirical models are determined by inverse modelling of simulated depth-dependent RWU. The performance of the empirical models and their optimized empirical parameters depends on the scenario. The standard empirical Feddes model only performs well in scenarios with low root length density R, i.e. for scenarios with low RWU compensation. For medium and high R, the Feddes RWU model cannot mimic properly the root uptake dynamics as predicted by the physical model. The Jarvis RWU model in combination with the Feddes reduction function (JMf) only provides good predictions for low and medium R scenarios. For high R, it cannot mimic the uptake patterns predicted by the physical model. Incorporating a newly proposed reduction function into the Jarvis model improved RWU predictions. Regarding the ability of the models to predict plant transpiration, all models accounting for compensation show good performance. The Akaike information criterion (AIC) indicates that the Jarvis (2010) model (JMII), with no empirical parameters to be estimated, is the best model. The proposed models are better in predicting RWU patterns similar to the physical model. The statistical indices point to them as the best alternatives for mimicking RWU predictions of the physical model.

Brain Activation during Sentence Comprehension among Good and Poor Readers

PubMed Central

Keller, Timothy A.; Cherkassky, Vladimir L.; Lee, Donghoon; Hoeft, Fumiko; Whitfield-Gabrieli, Susan; Gabrieli, John D. E.; Just, Marcel Adam

2008-01-01

This study sought to increase current understanding of the neuro-psychological basis of poor reading ability by using fMRI to examine brain activation during a visual sentence comprehension task among good and poor readers in the third (n = 32) and fifth (n = 35) grades. Reading ability, age, and the combination of both factors made unique contributions to cortical activation. The main finding was of parietotemporal underactivation (less activation than controls) among poor readers at the 2 grade levels. A positive linear relationship (spanning both the poor and good readers) was found between reading ability and activation in the left posterior middle temporal and postcentral gyri and in the right inferior parietal lobule such that activation increased with reading ability. Different developmental trajectories characterized good and poor readers in the left angular gyrus: activation increased with age among good readers, a change that failed to occur among poor readers. The parietotemporal cortex is discussed in terms of its role in reading acquisition, with the left angular gyrus playing a key role. It is proposed that the functioning of the cortical network underlying reading is dependent on a combination of interacting factors, including physiological maturation, neural integrity, skill level, and the nature of the task. PMID:17317678

Predictive validity of the Work Ability Index and its individual items in the general population.

PubMed

Lundin, Andreas; Leijon, Ola; Vaez, Marjan; Hallgren, Mats; Torgén, Margareta

2017-06-01

This study assesses the predictive ability of the full Work Ability Index (WAI) as well as its individual items in the general population. The Work, Health and Retirement Study (WHRS) is a stratified random national sample of 25-75-year-olds living in Sweden in 2000 that received a postal questionnaire ( n = 6637, response rate = 53%). Current and subsequent sickness absence was obtained from registers. The ability of the WAI to predict long-term sickness absence (LTSA; ⩾ 90 consecutive days) during a period of four years was analysed by logistic regression, from which the Area Under the Receiver Operating Characteristic curve (AUC) was computed. There were 313 incident LTSA cases among 1786 employed individuals. The full WAI had acceptable ability to predict LTSA during the 4-year follow-up (AUC = 0.79; 95% CI 0.76 to 0.82). Individual items were less stable in their predictive ability. However, three of the individual items: current work ability compared with lifetime best, estimated work impairment due to diseases, and number of diagnosed current diseases, exceeded AUC > 0.70. Excluding the WAI item on number of days on sickness absence did not result in an inferior predictive ability of the WAI. The full WAI has acceptable predictive validity, and is superior to its individual items. For public health surveys, three items may be suitable proxies of the full WAI; current work ability compared with lifetime best, estimated work impairment due to diseases, and number of current diseases diagnosed by a physician.

Comparison of four staging systems of lymph node metastasis in gastric cancer.

PubMed

Zhang, Ming; Zhu, Guanyu; Ma, Yan; Xue, Yingwei

2009-11-01

The classification of lymph node metastasis in patients with gastric cancer is still controversial. Our aim was to evaluate the relative merits of four staging systems of lymph node metastasis. In our study, the nodal status was classified according to the 5th edition of the tumor node metastasis (TNM) system, the Japanese Classification of Gastric Carcinoma (JCGC), the ratio of metastatic lymph nodes, and the size of the largest metastatic lymph node. Each staging system was scored as good (+2), fair (+1), or poor (0) with respect to the theoretical value (extent of the anatomical lymphatic tumor spread), convenience (simplicity), surgical applicability (extent of lymph node dissection), and prognostic value (ability to predict survival rate). In the multivariate analysis including the four staging systems and other potential prognostic factors, stepwise Cox regression revealed that the ratio of metastatic lymph nodes was the most independent prognostic factor. The TNM, ratio, and size systems were convenient because they had no consideration for the location of the tumor and lymph node. Although the JCGC system had advantages in theoretical value and surgical application, it was most optional due to the complexity of the system. Although all different staging systems are comparable, the metastatic lymph node ratio system is convenient, reproducible, and has the highest ability to predict survival.

Experience with a mouse intranasal test for the predictive identification of respiratory sensitization potential of proteins.

PubMed

Blaikie, L; Basketter, D A

1999-08-01

The predictive identification of respiratory allergenic potential is an important primary step in the safety evaluation of (novel) proteins, such as the enzymes used in a range of consumer laundry products. In the past this has been achieved by assessing the relative ability of proteins to give rise to the formation of anaphylactic antibody in the guinea pig. Recently, an alternative model has been proposed which assesses the formation of specific IgG1 antibody in a mouse intranasal test (MINT), the assumption being that specific IgG1 antibody is a surrogate for anaphylactic antibody in the mouse. This procedure has undergone successful initial intralaboratory and interlaboratory assessment. In the present work, the MINT has been evaluated in a more thorough intralaboratory study using eight enzymes plus ovalbumin. While the data generated with a reference enzyme protein, Alcalase, showed good reproducibility, results with the remaining eight proteins led to estimates of their relative antigenic or sensitization potential several of which were at variance from those derived from the guinea pig/ human experience. In consequence, it is concluded that the MINT requires substantial further investigation before it can be adopted as a model for the assessment of the relative ability of proteins to behave as respiratory allergens.

The Joint Contribution of Activation and Inhibition in Moderating Carryover Effects of Anger on Social Judgment

PubMed Central

Fiori, Marina; Shuman, Vera

2017-01-01

Carryover effects of emotions that lead to biases in social judgments are commonly observed. We suggest that such effects may be influenced by the ability to engage or disengage attention from emotional stimuli. We assessed the ability to activate and inhibit attention to anger stimuli, experimentally induced anger in a demanding task, and measured social judgment toward an ambiguous target. Results show that higher activation and higher inhibition of anger-related information predicted more biased evaluations of the ambiguous target when individuals were experiencing anger, but not in an emotionally neutral condition. Interestingly, the effect of activation and inhibition in the anger condition emerged only when such variables were entered simultaneously in the regression model, indicating that they had an additive effect in predicting carryover effects of anger on social judgement. Results are consistent with a cooperative suppression effect (Conger, 1974) of activation and inhibition and may be explained by either an increased accessibility of anger-related cues leading to more biased social judgments, or by an instance in which being good at engaging in and disengaging attention from emotional cues might have depleted participants’ resources making carryover effects of anger more likely to occur. Ultimately, the finding highlight that individual differences in attentional processes are important moderators for carryover effects of emotions. PMID:28993743

Biaxial experimental and analytical characterization of a dielectric elastomer

NASA Astrophysics Data System (ADS)

Helal, Alexander; Doumit, Marc; Shaheen, Robert

2018-01-01

Electroactive polymers (EAPs) have emerged as a strong contender for use in low-cost efficient actuators in multiple applications especially related to biomimetic and mobile-assistive devices. Dielectric elastomers (DE), a subcategory of these smart materials, have been of particular interest due to their large achievable deformation and favourable mechanical and electro-mechanical properties. Previous work has been completed to understand the behaviour of these materials; however, their properties require further investigation to properly integrate them into real-world applications. In this study, a biaxial tensile experimental evaluation of 3M™ VHB 4905 and VHB 4910 is presented with the purpose of illustrating the elastomers' transversely isotropic mechanical behaviours. These tests were applied to both tapes for equibiaxial stretch rates ranging between 0.025 and 0.300 s-1. Subsequently, a dynamic planar biaxial visco-hyperelastic constitutive relationship was derived from a Kelvin-Voigt rheological model and the general Hooke's law for transversely isotropic materials. The model was then fitted to the experimental data to obtain three general material parameters for either tapes. The model's ability to predict tensile stress response and internal energy dissipation, with respect to experimental data, is evaluated with good agreement. The model's ability to predict variations in mechanical behaviour due to changes in kinematic variables is then illustrated for different conditions.

Absence without leave or leave without absence: Examining the interrelations among mind wandering, metacognition and cognitive control.

PubMed

Drescher, Leonhard Hakon; Van den Bussche, Eva; Desender, Kobe

2018-01-01

Despite the abundance of recent publications about mind wandering (i.e., off-task thought), its interconnection with metacognition and cognitive control has not yet been examined. In the current study, we hypothesized that these three constructs would show clear interrelations. Metacognitive capacity was predicted to correlate positively with cognitive control ability, which in turn was predicted to be positively related to resistance to mind wandering during sustained attention. Moreover, it was expected that participants with good metacognitive capacity would be better at the subjective recognition of behaviorally present mind wandering. Three tasks were used: The Sustained Attention to Response Task (SART) to measure mind wandering, a perceptual decision task with confidence ratings to measure metacognitive efficiency, and a conflict task to measure cognitive control. Structural Equation Modelling was used to test the interrelations among the three constructs. As expected, metacognitive efficiency was positively related to cognitive control ability. Surprisingly, there was a negative relation between metacognitive efficiency and the degree to which subjective mind wandering reports tracked the behavioral index of mind wandering. No relation was found between cognitive control and behavioral mind wandering. The results of the current work are the first to shed light on the interrelations among these three constructs.

Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Muldoon, Timothy J.; Thekkek, Nadhi; Roblyer, Darren; Maru, Dipen; Harpaz, Noam; Potack, Jonathan; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2010-03-01

Early detection of neoplasia in patients with Barrett's esophagus is essential to improve outcomes. The aim of this ex vivo study was to evaluate the ability of high-resolution microendoscopic imaging and quantitative image analysis to identify neoplastic lesions in patients with Barrett's esophagus. Nine patients with pathologically confirmed Barrett's esophagus underwent endoscopic examination with biopsies or endoscopic mucosal resection. Resected fresh tissue was imaged with fiber bundle microendoscopy; images were analyzed by visual interpretation or by quantitative image analysis to predict whether the imaged sites were non-neoplastic or neoplastic. The best performing pair of quantitative features were chosen based on their ability to correctly classify the data into the two groups. Predictions were compared to the gold standard of histopathology. Subjective analysis of the images by expert clinicians achieved average sensitivity and specificity of 87% and 61%, respectively. The best performing quantitative classification algorithm relied on two image textural features and achieved a sensitivity and specificity of 87% and 85%, respectively. This ex vivo pilot trial demonstrates that quantitative analysis of images obtained with a simple microendoscope system can distinguish neoplasia in Barrett's esophagus with good sensitivity and specificity when compared to histopathology and to subjective image interpretation.

Versatile and efficient pore network extraction method using marker-based watershed segmentation

NASA Astrophysics Data System (ADS)

Gostick, Jeff T.

2017-08-01

Obtaining structural information from tomographic images of porous materials is a critical component of porous media research. Extracting pore networks is particularly valuable since it enables pore network modeling simulations which can be useful for a host of tasks from predicting transport properties to simulating performance of entire devices. This work reports an efficient algorithm for extracting networks using only standard image analysis techniques. The algorithm was applied to several standard porous materials ranging from sandstone to fibrous mats, and in all cases agreed very well with established or known values for pore and throat sizes, capillary pressure curves, and permeability. In the case of sandstone, the present algorithm was compared to the network obtained using the current state-of-the-art algorithm, and very good agreement was achieved. Most importantly, the network extracted from an image of fibrous media correctly predicted the anisotropic permeability tensor, demonstrating the critical ability to detect key structural features. The highly efficient algorithm allows extraction on fairly large images of 5003 voxels in just over 200 s. The ability for one algorithm to match materials as varied as sandstone with 20% porosity and fibrous media with 75% porosity is a significant advancement. The source code for this algorithm is provided.

Absence without leave or leave without absence: Examining the interrelations among mind wandering, metacognition and cognitive control

PubMed Central

Van den Bussche, Eva; Desender, Kobe

2018-01-01

Despite the abundance of recent publications about mind wandering (i.e., off-task thought), its interconnection with metacognition and cognitive control has not yet been examined. In the current study, we hypothesized that these three constructs would show clear interrelations. Metacognitive capacity was predicted to correlate positively with cognitive control ability, which in turn was predicted to be positively related to resistance to mind wandering during sustained attention. Moreover, it was expected that participants with good metacognitive capacity would be better at the subjective recognition of behaviorally present mind wandering. Three tasks were used: The Sustained Attention to Response Task (SART) to measure mind wandering, a perceptual decision task with confidence ratings to measure metacognitive efficiency, and a conflict task to measure cognitive control. Structural Equation Modelling was used to test the interrelations among the three constructs. As expected, metacognitive efficiency was positively related to cognitive control ability. Surprisingly, there was a negative relation between metacognitive efficiency and the degree to which subjective mind wandering reports tracked the behavioral index of mind wandering. No relation was found between cognitive control and behavioral mind wandering. The results of the current work are the first to shed light on the interrelations among these three constructs. PMID:29425205

75 FR 80354 - Satellite Television Extension and Localism Act of 2010 and Satellite Home Viewer Extension and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-22

... Commission, adopts a point-to-point predictive model for determining the ability of individual locations to... predictive model for reliably and presumptively determining the ability of individual locations, through the... adopted a point-to-point predictive model for determining the ability of individual locations to receive...

Numerical predictors of arithmetic success in grades 1-6.

PubMed

Lyons, Ian M; Price, Gavin R; Vaessen, Anniek; Blomert, Leo; Ansari, Daniel

2014-09-01

Math relies on mastery and integration of a wide range of simpler numerical processes and concepts. Recent work has identified several numerical competencies that predict variation in math ability. We examined the unique relations between eight basic numerical skills and early arithmetic ability in a large sample (N = 1391) of children across grades 1-6. In grades 1-2, children's ability to judge the relative magnitude of numerical symbols was most predictive of early arithmetic skills. The unique contribution of children's ability to assess ordinality in numerical symbols steadily increased across grades, overtaking all other predictors by grade 6. We found no evidence that children's ability to judge the relative magnitude of approximate, nonsymbolic numbers was uniquely predictive of arithmetic ability at any grade. Overall, symbolic number processing was more predictive of arithmetic ability than nonsymbolic number processing, though the relative importance of symbolic number ability appears to shift from cardinal to ordinal processing. © 2014 John Wiley & Sons Ltd.

Detection of Organophosphorus Pesticides with Colorimetry and Computer Image Analysis.

PubMed

Li, Yanjie; Hou, Changjun; Lei, Jincan; Deng, Bo; Huang, Jing; Yang, Mei

2016-01-01

Organophosphorus pesticides (OPs) represent a very important class of pesticides that are widely used in agriculture because of their relatively high-performance and moderate environmental persistence, hence the sensitive and specific detection of OPs is highly significant. Based on the inhibitory effect of acetylcholinesterase (AChE) induced by inhibitors, including OPs and carbamates, a colorimetric analysis was used for detection of OPs with computer image analysis of color density in CMYK (cyan, magenta, yellow and black) color space and non-linear modeling. The results showed that there was a gradually weakened trend of yellow intensity with the increase of the concentration of dichlorvos. The quantitative analysis of dichlorvos was achieved by Artificial Neural Network (ANN) modeling, and the results showed that the established model had a good predictive ability between training sets and predictive sets. Real cabbage samples containing dichlorvos were detected by colorimetry and gas chromatography (GC), respectively. The results showed that there was no significant difference between colorimetry and GC (P > 0.05). The experiments of accuracy, precision and repeatability revealed good performance for detection of OPs. AChE can also be inhibited by carbamates, and therefore this method has potential applications in real samples for OPs and carbamates because of high selectivity and sensitivity.

Structural insights of Staphylococcus aureus FtsZ inhibitors through molecular docking, 3D-QSAR and molecular dynamics simulations.

PubMed

Ballu, Srilata; Itteboina, Ramesh; Sivan, Sree Kanth; Manga, Vijjulatha

2018-02-01

Filamentous temperature-sensitive protein Z (FtsZ) is a protein encoded by the FtsZ gene that assembles into a Z-ring at the future site of the septum of bacterial cell division. Structurally, FtsZ is a homolog of eukaryotic tubulin but has low sequence similarity; this makes it possible to obtain FtsZ inhibitors without affecting the eukaryotic cell division. Computational studies were performed on a series of substituted 3-arylalkoxybenzamide derivatives reported as inhibitors of FtsZ activity in Staphylococcus aureus. Quantitative structure-activity relationship models (QSAR) models generated showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of these models was determined and an acceptable predictive correlation (r 2 Pred ) values were obtained. Finally, we performed molecular dynamics simulations in order to examine the stability of protein-ligand interactions. This facilitated us to compare free binding energies of cocrystal ligand and newly designed molecule B1. The good concordance between the docking results and comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) contour maps afforded obliging clues for the rational modification of molecules to design more potent FtsZ inhibitors.

Comparison and relationship of thyroid hormones, IL-6, IL-10 and albumin as mortality predictors in case-mix critically ill patients.

PubMed

Quispe E, Álvaro; Li, Xiang-Min; Yi, Hong

2016-05-01

To compare the ability of thyroid hormones, IL-6, IL-10, and albumin to predict mortality, and to assess their relationship in case-mix acute critically ill patients. APACHE II scores and serum thyroid hormones (FT3, FT4, and TSH), IL-6, IL-10, and albumin were obtained at EICU admission for 79 cases of mix acute critically ill patients without previous history of thyroid disease. Patients were followed for 28 days with patient's death as the primary outcome. All mean values were compared, correlations assessed with Pearson' test, and mortality prediction assessed by multivariate logistic regression and ROC. Non survivors were older, with higher APACHE II score (p=0.000), IL-6 (p<0.05), IL-10 (p=0.000) levels, and lower albumin (p=0.000) levels compared to survivors at 28 days. IL-6 and IL-10 had significant negative correlation with albumin (p=0.001) and FT3 (p ⩽ 0.05) respectively, while low albumin had a direct correlation with FT3 (p<0.05). In the mortality prediction assessment, IL-10, albumin and APACHE II were independent morality predictors and showed to have a good (0.70-0.79) AUC-ROC (p<0.05). Despite that the entire cohort showed low FT3 serum levels (p=0.000), there was not statistical difference between survivors and non-survivors; neither showed any significance as mortality predictor. IL-6 and IL-10 are correlated with Low FT3 and hypoalbuminemia. Thyroid hormones assessed at EICU admission did not have any predictive value in our study. And finally, high levels of IL-6 and IL-10 in conjunction with albumin could improve our ability to evaluate disease's severity and predict mortality in the critically ill patients. When use in combination with APACHE II scores, our model showed improved mortality prediction. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Predicting space telerobotic operator training performance from human spatial ability assessment

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

A Comparison of Three Job Engagement Measures: Examining their Factorial and Criterion-Related Validity.

PubMed

Wefald, Andrew J; Mills, Maura J; Smith, Michael R; Downey, Ronald G

2012-03-01

Engagement is an emerging job attitude that purports to measure employees' psychological presence at and involvement in their work. This research compares three academic approaches to engagement, and makes recommendations regarding the most appropriate conceptualisation and measurement of the construct in future research. The current research also investigates whether any of these three approaches to engagement contribute unique variance to the prediction of turnover intentions above and beyond the predictive capacity of alternative constructs. An online survey was taken by 382 employees and managers from a mid-sized financial institution. Results failed to support either a multi- or unidimensional factor structure for the Utrecht Work Engagement Scale (UWES) engagement measure. For the Shirom-Melamed Vigor Measure (SMVM), a multi-dimensional structure was identified as a good fit, while a unidimensional structure fit poorly. The uni-factorial structure of Britt's engagement measure was confirmed. The Schaufeli measure of engagement was a strong predictor of work outcomes; however, when controlling for job satisfaction and affective commitment, that measure lost its ability to predict intentions to leave. Two components of the Shirom vigor measure held their predictive validity. Collectively, these findings suggest that the Shirom vigor measure may provide better insight into whether and how much a person is 'into' his or her job. The Schaufeli measure was a good predictor of important work outcomes, but when job satisfaction and affective commitment were controlled, it lost its predictive validity. We were not able to confirm the three-factor structure of the Schaufeli measure. Two components of the Shirom vigor measure predicted turnover intentions after controlling for job satisfaction and affective commitment, suggesting less overlap with those constructs than the Schaufeli measure of engagement. This research adds important information on the nature of engagement and is expected to contribute toward a better understanding of the construct itself, as well as its measurement. © 2011 The Authors. Applied Psychology: Health and Well-Being © 2011 The International Association of Applied Psychology.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

PubMed

Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

2017-03-01

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

A Comparison of the Intellectual Abilities of Good and Poor Problem Solvers: An Exploratory Study.

ERIC Educational Resources Information Center

Meyer, Ruth Ann

This study examined a selected sample of fourth-grade students who had been previously identified as good or poor problem solvers. The pupils were compared on variables considered as "reference tests" for Verbal, Induction, Numerical, Word Fluency, Memory, Spatial Visualization, and Perceptual Speed abilities. The data were compiled to…

Work load and individual factors affecting work ability among aging municipal employees.

PubMed

Tuomi, K; Eskelinen, L; Toikkanen, J; Jarvinen, E; Ilmarinen, J; Klockars, M

1991-01-01

The effects of work stressors, individual characteristics, symptoms, and diseases on work ability were studied among 4255 municipal employees. Work ability was assessed by a work ability index in two cross-sectional inquiries, one in 1981 and the other in 1985. The most impairing for work ability were mental symptoms and musculoskeletal disease. Among the work stressors, high physical demands at work, poor physical work environment, and lack of freedom were associated with impaired work ability. Muscular work, disturbing temperatures at the workplace, and lack of freedom particularly affected employees with disease, whereas poor work postures and role conflicts at work were particularly injurious for healthy employees. The worst situation was observed when a worker with many symptoms and disease was exposed to many different work stressors. Life satisfaction, sitting work posture, a good basic education, and physical exercise during leisure time were associated with good work ability.

Genomic selection in a commercial winter wheat population.

PubMed

He, Sang; Schulthess, Albert Wilhelm; Mirdita, Vilson; Zhao, Yusheng; Korzun, Viktor; Bothe, Reiner; Ebmeyer, Erhard; Reif, Jochen C; Jiang, Yong

2016-03-01

Genomic selection models can be trained using historical data and filtering genotypes based on phenotyping intensity and reliability criterion are able to increase the prediction ability. We implemented genomic selection based on a large commercial population incorporating 2325 European winter wheat lines. Our objectives were (1) to study whether modeling epistasis besides additive genetic effects results in enhancement on prediction ability of genomic selection, (2) to assess prediction ability when training population comprised historical or less-intensively phenotyped lines, and (3) to explore the prediction ability in subpopulations selected based on the reliability criterion. We found a 5 % increase in prediction ability when shifting from additive to additive plus epistatic effects models. In addition, only a marginal loss from 0.65 to 0.50 in accuracy was observed using the data collected from 1 year to predict genotypes of the following year, revealing that stable genomic selection models can be accurately calibrated to predict subsequent breeding stages. Moreover, prediction ability was maximized when the genotypes evaluated in a single location were excluded from the training set but subsequently decreased again when the phenotyping intensity was increased above two locations, suggesting that the update of the training population should be performed considering all the selected genotypes but excluding those evaluated in a single location. The genomic prediction ability was substantially higher in subpopulations selected based on the reliability criterion, indicating that phenotypic selection for highly reliable individuals could be directly replaced by applying genomic selection to them. We empirically conclude that there is a high potential to assist commercial wheat breeding programs employing genomic selection approaches.

Preoperative prediction of intensive care unit stay following cardiac surgery.

PubMed

De Cocker, Jeroen; Messaoudi, Nouredin; Stockman, Bernard A; Bossaert, Leo L; Rodrigus, Inez E R

2011-01-01

Following cardiac surgery, a great variety in intensive care unit (ICU) stay is observed, making it often difficult to adequately predict ICU stay preoperatively. Therefore, a study was conducted to investigate, which preoperative variables are independent risk factors for a prolonged ICU stay and whether a patient's risk of experiencing an extended ICU stay can be estimated from these predictors. The records of 1566 consecutive adult patients who underwent cardiac surgery at our institution were analysed retrospectively over a 2-year period. Procedures included in the analyses were coronary artery bypass grafting, valve replacement or repair, ascending and aortic arch surgery, ventricular rupture and aneurysm repair, septal myectomy and cardiac tumour surgery. For this patient group, ICU stay was registered and 57 preoperative variables were collected for analysis. Descriptives and log-rank tests were calculated and Kaplan-Meier curves drawn for all variables. Significant predictors in the univariate analyses were included in a Cox proportional hazards model. The definitive model was validated on an independent sample of 395 consecutive adult patients who underwent cardiac surgery at our institution over an additional 6-month period. In this patient group, the accuracy and discriminative abilities of the model were evaluated. Twelve independent preoperative predictors of prolonged ICU stay were identified: age at surgery>75 years, female gender, dyspnoea status>New York Heart Association class II (NYHA II), unstable symptoms, impaired kidney function (estimated glomerular filtration rate (eGFR)<60 ml min(-1)), extracardiac arterial disease, presence of arrhythmias, mitral insufficiency>colour flow mapping (CFM) grade II, inotropic support, intra-aortic balloon pumping (IABP), non-elective procedures and aortic surgery. The individual effect of every predictor on ICU stay was quantified and inserted into a mathematical algorithm (called the Morbidity Defining Cardiosurgical (MDC) index), making it possible to calculate a patient's risk of having an extended ICU stay. The model showed very good calibration and very good to excellent discriminative ability in predicting ICU stay >2, >5 and >7 days (C-statistic of 0.78; 0.82 and 0.85, respectively). Twelve independent preoperative risk factors for a prolonged ICU stay following cardiac surgery were identified and constructed into a proportional hazards model. Using this risk model, one can predict whether a patient will have a prolonged ICU stay or not. Copyright © 2010 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

PubMed

James, Katherine A; Meliker, Jaymie R; Buttenfield, Barbara E; Byers, Tim; Zerbe, Gary O; Hokanson, John E; Marshall, Julie A

2014-08-01

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83-0.92 for samples collected from the same well 15-25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.

Factors predicting recovery from suicide in attempted suicide patients.

PubMed

Sun, Fan-Ko; Lu, Chu-Yun; Tseng, Yun Shan; Chiang, Chun-Ying

2017-12-01

The aim of this study was to explore the factors predicting suicide recovery and to provide guidance for healthcare professionals when caring for individuals who have attempted suicide. The high rate of suicide is a global health problem. Suicide prevention has become an important issue in contemporary mental health. Most suicide research has focused on suicidal prevention and care. There is a lack of research on the factors predicting suicidal recovery. A cross-sectional design was adopted. A correlational study with a purposive sample of 160 individuals from a suicide prevention centre in southern Taiwan was conducted. The questionnaires included the Brief Symptom Rating Scale-5, Suicidal Recovery Assessment Scale and Beck Hopelessness Scale. Descriptive statistics and linear regressions were used for the analysis. The mean age of the participants was 40.2 years. Many participants were striving to make changes to create a more stable and fulfilling life, had an improved recovery from suicide and had a good ability to adapt or solve problems. The linear regression showed that the Beck Hopelessness Scale scores (ß = -.551, p < .001) and Brief Symptom Rating Scale-5 (ß = -.218, p = .003) and past suicidal behaviour (ß = -.145, p = .008) were significant predictors of individuals' recovery from suicide. They accounted for 57.1% of the variance. Suicidal individuals who have a lower level of hopelessness, a better ability to cope with their mental condition and fewer past suicidal behaviours may better recover from suicide attempts. The nurses could use the results of this study to predict recovery from suicide in patients with attempted suicide. © 2017 John Wiley & Sons Ltd.

[Evaluation of the capacity of the APR-DRG classification system to predict hospital mortality].

PubMed

De Marco, Maria Francesca; Lorenzoni, Luca; Addari, Piero; Nante, Nicola

2002-01-01

Inpatient mortality has increasingly been used as an hospital outcome measure. Comparing mortality rates across hospitals requires adjustment for patient risks before making inferences about quality of care based on patient outcomes. Therefore it is essential to dispose of well performing severity measures. The aim of this study is to evaluate the ability of the All Patient Refined DRG system to predict inpatient mortality for congestive heart failure, myocardial infarction, pneumonia and ischemic stroke. Administrative records were used in this analysis. We used two statistics methods to assess the ability of the APR-DRG to predict mortality: the area under the receiver operating characteristics curve (referred to as the c-statistic) and the Hosmer-Lemeshow test. The database for the study included 19,212 discharges for stroke, pneumonia, myocardial infarction and congestive heart failure from fifteen hospital participating in the Italian APR-DRG Project. A multivariate analysis was performed to predict mortality for each condition in study using age, sex and APR-DRG risk mortality subclass as independent variables. Inpatient mortality rate ranges from 9.7% (pneumonia) to 16.7% (stroke). Model discrimination, calculated using the c-statistic, was 0.91 for myocardial infarction, 0.68 for stroke, 0.78 for pneumonia and 0.71 for congestive heart failure. The model calibration assessed using the Hosmer-Leme-show test was quite good. The performance of the APR-DRG scheme when used on Italian hospital activity records is similar to that reported in literature and it seems to improve by adding age and sex to the model. The APR-DRG system does not completely capture the effects of these variables. In some cases, the better performance might be due to the inclusion of specific complications in the risk-of-mortality subclass assignment.

Evaluation of the suitability of chromatographic systems to predict human skin permeation of neutral compounds.

PubMed

Hidalgo-Rodríguez, Marta; Soriano-Meseguer, Sara; Fuguet, Elisabet; Ràfols, Clara; Rosés, Martí

2013-12-18

Several chromatographic systems (three systems of high-performance liquid chromatography and two micellar electrokinetic chromatography systems) besides the reference octanol-water partition system are evaluated by a systematic procedure previously proposed in order to know their ability to model human skin permeation. The precision achieved when skin-water permeability coefficients are correlated against chromatographic retention factors is predicted within the framework of the solvation parameter model. It consists in estimating the contribution of error due to the biological and chromatographic data, as well as the error coming from the dissimilarity between the human skin permeation and the chromatographic systems. Both predictions and experimental tests show that all correlations are greatly affected by the considerable uncertainty of the skin permeability data and the error associated to the dissimilarity between the systems. Correlations with much better predictive abilities are achieved when the volume of the solute is used as additional variable, which illustrates the main roles of both lipophilicity and size of the solute to penetrate through the skin. In this way, the considered systems are able to give precise estimations of human skin permeability coefficients. In particular, the HPLC systems with common C18 columns provide the best performances in emulating the permeation of neutral compounds from aqueous solution through the human skin. As a result, a methodology based on easy, fast, and economical HPLC measurements in a common C18 column has been developed. After a validation based on training and test sets, the method has been applied with good results to the estimation of skin permeation of several hormones and pesticides. Copyright © 2013 Elsevier B.V. All rights reserved.

Numerical simulation of damage and progressive failures in composite laminates using the layerwise plate theory

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

Reddy, Y.S.

1992-01-01

The failure behavior of composite laminates is modeled numerically using the Generalized Layerwise Plate Theory (GLPT) of Reddy and a progressive failure algorithm. The Layerwise Theory of Reddy assumes a piecewise continuous displacement field through the thickness of the laminate and therefore has the ability to capture the interlaminar stress fields near the free edges and cut outs more accurately. The progressive failure algorithm is based on the assumption that the material behaves like a stable progressively fracturing solid. A three-dimensional stiffness reduction scheme is developed and implemented to study progressive failures in composite laminates. The effect of various parametersmore » such as out-of-plane material properties, boundary conditions, and stiffness reduction methods on the failure stresses and strains of a quasi-isotropic composite laminate with free edges subjected to tensile loading is studied. The ultimate stresses and strains predicted by the Generalized Layerwise Plate Theory (GLPT) and the more widely used First Order Shear Deformation Theory (FSDT) are compared with experimental results. The predictions of the GLPT are found to be in good agreement with the experimental results both qualitatively and quantitatively, while the predictions of FSDT are found to be different from experimental results both qualitatively and quantitatively. The predictive ability of various phenomenological failure criteria is evaluated with reference to the experimental results available in the literature. The effect of geometry of the test specimen and the displacement boundary conditions at the grips on the ultimate stresses and strains of a composite laminate under compressive loading is studied. The ultimate stresses and strains are found to be quite sensitive to the geometry of the test specimen and the displacement boundary conditions at the grips. The degree of sensitivity is observed to depend strongly on the lamination sequence.« less

Self-concept and quality of object relations as predictors of outcome in short- and long-term psychotherapy.

PubMed

Lindfors, Olavi; Knekt, Paul; Heinonen, Erkki; Virtala, Esa

2014-01-01

Quality of object relations and self-concept reflect clinically relevant aspects of personality functioning, but their prediction as suitability factors for psychotherapies of different lengths has not been compared. This study compared their prediction on psychiatric symptoms and work ability in short- and long-term psychotherapy. Altogether 326 patients, 20-46 years of age, with mood and/or anxiety disorder, were randomized to short-term (solution-focused or short-term psychodynamic) psychotherapy and long-term psychodynamic psychotherapy. The Quality of Object Relations Scale (QORS) and the Structural Analysis of Social Behavior (SASB) self-concept questionnaire were measured at baseline, and their prediction on outcome during the 3-year follow-up was assessed by the Symptom Check List Global Severity Index and the Anxiety Scale, the Beck Depression Inventory and by the Work Ability Index, Social Adjustment Scale work subscale and the Perceived Psychological Functioning scale. Negative self-concept strongly and self-controlling characteristics modestly predicted better 3-year outcomes in long-term therapy, after faster early gains in short-term therapy. Patients with a more positive or self-emancipating self-concept, or more mature object relations, experienced more extensive benefits after long-term psychotherapy. The importance of length vs. long-term therapy technique on the differences found is not known. Patients with mild to moderate personality pathology, indicated by poor self-concept, seem to benefit more from long-term than short-term psychotherapy, in reducing risk of depression. Long-term therapy may also be indicated for patients with relatively good psychological functioning. More research is needed on the relative importance of these characteristics in comparison with other patient-related factors. © 2013 Published by Elsevier B.V.

Usefulness of a simple self-administered joint condition assessment sheet to predict the need for orthopaedic intervention in the management of haemophilic arthropathy.

PubMed

Masaoka, T; Amano, K; Takedani, H; Suzuki, T; Otaki, M; Seita, I; Tateiwa, T; Shishido, T; Yamamoto, K; Fukutake, K

2017-03-01

Detecting signs of joint deterioration is important for early effective orthopaedic intervention in managing haemophilic arthropathy. We developed a simple, patient self-administered sheet to evaluate the joint condition, and assessed the predictive ability of this assessment sheet for the need for an orthopaedic intervention. This was a single-centre, cross-sectional study. The association between the score of each of the four items of the assessment sheet (bleeding, swelling, pain and physical impairment) and the results of radiological findings and physical examinations based on Haemophilia Joint Health Score 2.1 was assessed. An optimal scoring system was explored by the area under the curve (AUC). The cut-off value for the need for surgery or physiotherapy was determined using the receiver operating characteristic curve procedure. Forty-two patients were included. The 'physical impairment' item showed the highest correlation coefficient with the results of radiographic and physical examinations (range: 0.57-0.76). The AUC of finally adjusted scoring indicates good ability to discriminate between patients with and without a need for orthopaedic intervention. The positive predictive value was the highest at a cut-off value of 4 points for knees (63.0%) and ankles (70.0%), at 5 points for elbows (66.7%) and the highest predictive accuracy at the cut-off value of 4 points for all the joints. The linear trend of the need for an orthopaedic intervention was observed with an increasing score. The joint condition assessment sheet can help clinicians assess the need for orthopaedic intervention for haemophilic arthropathy in Japanese patients with haemophilia. © 2016 John Wiley & Sons Ltd.

CFD-RANS prediction of individual exposure from continuous release of hazardous airborne materials in complex urban environments

NASA Astrophysics Data System (ADS)

Efthimiou, G. C.; Andronopoulos, S.; Bartzis, J. G.; Berbekar, E.; Harms, F.; Leitl, B.

2017-02-01

One of the key issues of recent research on the dispersion inside complex urban environments is the ability to predict individual exposure (maximum dosages) of an airborne material which is released continuously from a point source. The present work addresses the question whether the computational fluid dynamics (CFD)-Reynolds-averaged Navier-Stokes (RANS) methodology can be used to predict individual exposure for various exposure times. This is feasible by providing the two RANS concentration moments (mean and variance) and a turbulent time scale to a deterministic model. The whole effort is focused on the prediction of individual exposure inside a complex real urban area. The capabilities of the proposed methodology are validated against wind-tunnel data (CUTE experiment). The present simulations were performed 'blindly', i.e. the modeller had limited information for the inlet boundary conditions and the results were kept unknown until the end of the COST Action ES1006. Thus, a high uncertainty of the results was expected. The general performance of the methodology due to this 'blind' strategy is good. The validation metrics fulfil the acceptance criteria. The effect of the grid and the turbulence model on the model performance is examined.

Predicting the shock compression response of heterogeneous powder mixtures

NASA Astrophysics Data System (ADS)

Fredenburg, D. A.; Thadhani, N. N.

2013-06-01

A model framework for predicting the dynamic shock-compression response of heterogeneous powder mixtures using readily obtained measurements from quasi-static tests is presented. Low-strain-rate compression data are first analyzed to determine the region of the bulk response over which particle rearrangement does not contribute to compaction. This region is then fit to determine the densification modulus of the mixture, σD, an newly defined parameter describing the resistance of the mixture to yielding. The measured densification modulus, reflective of the diverse yielding phenomena that occur at the meso-scale, is implemented into a rate-independent formulation of the P-α model, which is combined with an isobaric equation of state to predict the low and high stress dynamic compression response of heterogeneous powder mixtures. The framework is applied to two metal + metal-oxide (thermite) powder mixtures, and good agreement between the model and experiment is obtained for all mixtures at stresses near and above those required to reach full density. At lower stresses, rate-dependencies of the constituents, and specifically those of the matrix constituent, determine the ability of the model to predict the measured response in the incomplete compaction regime.

Development of a 3D numerical methodology for fast prediction of gun blast induced loading

NASA Astrophysics Data System (ADS)

Costa, E.; Lagasco, F.

2014-05-01

In this paper, the development of a methodology based on semi-empirical models from the literature to carry out 3D prediction of pressure loading on surfaces adjacent to a weapon system during firing is presented. This loading is consequent to the impact of the blast wave generated by the projectile exiting the muzzle bore. When exceeding a pressure threshold level, loading is potentially capable to induce unwanted damage to nearby hard structures as well as frangible panels or electronic equipment. The implemented model shows the ability to quickly predict the distribution of the blast wave parameters over three-dimensional complex geometry surfaces when the weapon design and emplacement data as well as propellant and projectile characteristics are available. Considering these capabilities, the use of the proposed methodology is envisaged as desirable in the preliminary design phase of the combat system to predict adverse effects and then enable to identify the most appropriate countermeasures. By providing a preliminary but sensitive estimate of the operative environmental loading, this numerical means represents a good alternative to more powerful, but time consuming advanced computational fluid dynamics tools, which use can, thus, be limited to the final phase of the design.

Narrative Fiction and Expository Nonfiction Differentially Predict Verbal Ability

ERIC Educational Resources Information Center

Mar, Raymond A.; Rain, Marina

2015-01-01

Although reading is known to be an important contributor to language abilities, it is not yet well established whether different text genres are uniquely associated with verbal abilities. We examined how exposure to narrative fiction and expository nonfiction predict language ability among university students. Exposure was measured both with…

Comparison of Speed-Up Over Hills Derived from Wind-Tunnel Experiments, Wind-Loading Standards, and Numerical Modelling

NASA Astrophysics Data System (ADS)

Safaei Pirooz, Amir A.; Flay, Richard G. J.

2018-03-01

We evaluate the accuracy of the speed-up provided in several wind-loading standards by comparison with wind-tunnel measurements and numerical predictions, which are carried out at a nominal scale of 1:500 and full-scale, respectively. Airflow over two- and three-dimensional bell-shaped hills is numerically modelled using the Reynolds-averaged Navier-Stokes method with a pressure-driven atmospheric boundary layer and three different turbulence models. Investigated in detail are the effects of grid size on the speed-up and flow separation, as well as the resulting uncertainties in the numerical simulations. Good agreement is obtained between the numerical prediction of speed-up, as well as the wake region size and location, with that according to large-eddy simulations and the wind-tunnel results. The numerical results demonstrate the ability to predict the airflow over a hill with good accuracy with considerably less computational time than for large-eddy simulation. Numerical simulations for a three-dimensional hill show that the speed-up and the wake region decrease significantly when compared with the flow over two-dimensional hills due to the secondary flow around three-dimensional hills. Different hill slopes and shapes are simulated numerically to investigate the effect of hill profile on the speed-up. In comparison with more peaked hill crests, flat-topped hills have a lower speed-up at the crest up to heights of about half the hill height, for which none of the standards gives entirely satisfactory values of speed-up. Overall, the latest versions of the National Building Code of Canada and the Australian and New Zealand Standard give the best predictions of wind speed over isolated hills.

Watching novice action degrades expert motor performance: Causation between action production and outcome prediction of observed actions by humans

PubMed Central

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2014-01-01

Our social skills are critically determined by our ability to understand and appropriately respond to actions performed by others. However despite its obvious importance, the mechanisms enabling action understanding in humans have remained largely unclear. A popular but controversial belief is that parts of the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral paradigm, we investigated this belief by examining a causal relation between action production, and a component of action understanding - outcome prediction, the ability of a person to predict the outcome of observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert's ability to predict watched actions while controlling the other experimental factors, and exhibited that a change (improvement) in their outcome prediction ability results in a progressive and proportional deterioration in the expert's own darts performance. This causal relationship supports involvement of the motor system in outcome prediction by humans of actions observed in others. PMID:25384755

Women in mathematics, science, and engineering college majors: A model predicting career aspirations based on ability, self-efficacy, role model influence, and role conflict

NASA Astrophysics Data System (ADS)

Nauta, Margaret Mary

1997-09-01

This study investigated a model of predictors of career aspirations among two groups of women: students in mathematics, physical science, and engineering majors and students in biological science majors. Based on theories of women's career development and social-cognitive theories, it was hypothesized that ability, self-efficacy, positivity of role model influence, and role conflict would influence the career aspirations of these women. It was further hypothesized that the students' year in school would contribute to this model as a predictor variable. Five hundred forty-six students (representing a 71% response rate) from Iowa State University were surveyed by mail to evaluate the fit of this model. The structural equation modeling procedure revealed that the career aspirations of the two groups of women were directly predicted by self-efficacy and role conflict and indirectly predicted by year in school, academic ability, and positivity of role model influence. The model for this combined group of students represented a good overall fit, explaining 94% of the covariation among the measured variables. When the two groups of students were compared, identical models for women in the two groups revealed different relationships among the variables. In contrast to the women in math, physical science, and engineering majors, the relationships between ability and self-efficacy and between positivity of role model influence and self-efficacy were significantly lower in magnitude for women in the biological sciences group. In addition to providing a parsimonious model for conceptualizing the experiences of women in traditionally male fields, this study's findings have implications for increasing the number of women who aspire to advanced careers in these occupations. Primarily, this study suggests that interventions designed to increase the degree to which students are influenced positively by role models may increase their self-efficacy expectations and may decrease the amount of conflict they perceive between the roles of worker and spouse or parent. In turn, increasing self-efficacy and decreasing role conflict may increase the degree to which students aspire to leadership and top-level careers within mathematics, the physical sciences, and engineering.

Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding

PubMed Central

Patael, Smadar Z.; Farris, Emily A.; Black, Jessica M.; Hancock, Roeland; Gabrieli, John D. E.; Cutting, Laurie E.; Hoeft, Fumiko

2018-01-01

Objective The ultimate goal of reading is to understand written text. To accomplish this, children must first master decoding, the ability to translate printed words into sounds. Although decoding and reading comprehension are highly interdependent, some children struggle to decode but comprehend well, whereas others with good decoding skills fail to comprehend. The neural basis underlying individual differences in this discrepancy between decoding and comprehension abilities is virtually unknown. Methods We investigated the neural basis underlying reading discrepancy, defined as the difference between reading comprehension and decoding skills, in a three-part study: 1) The neuroanatomical basis of reading discrepancy in a cross-sectional sample of school-age children with a wide range of reading abilities (Experiment-1; n = 55); 2) Whether a discrepancy-related neural signature is present in beginning readers and predictive of future discrepancy (Experiment-2; n = 43); and 3) Whether discrepancy-related regions are part of a domain-general or a language specialized network, utilizing the 1000 Functional Connectome data and large-scale reverse inference from Neurosynth.org (Experiment-3). Results Results converged onto the left dorsolateral prefrontal cortex (DLPFC), as related to having discrepantly higher reading comprehension relative to decoding ability. Increased gray matter volume (GMV) was associated with greater discrepancy (Experiment-1). Region-of-interest (ROI) analyses based on the left DLPFC cluster identified in Experiment-1 revealed that regional GMV within this ROI in beginning readers predicted discrepancy three years later (Experiment-2). This region was associated with the fronto-parietal network that is considered fundamental for working memory and cognitive control (Experiment-3). Interpretation Processes related to the prefrontal cortex might be linked to reading discrepancy. The findings may be important for understanding cognitive resilience, which we operationalize as those individuals with greater higher-order reading skills such as reading comprehension compared to lower-order reading skills such as decoding skills. Our study provides insights into reading development, existing theories of reading, and cognitive processes that are potentially significant to a wide range of reading disorders. PMID:29902208

Masking ability of bi- and tri- laminate all-ceramic veneers on tooth-colored ceramic discs.

PubMed

Farhan, Daniel; Sukumar, Smitha; von Stein-Lausnitz, Axel; Aarabi, Ghazal; Alawneh, Ahmad; Reissmann, Daniel R

2014-01-01

A predictable esthetic outcome is imperative when placing ceramic veneers. Discolored teeth pose a major challenge as sufficient material thickness is required to achieve a good esthetic result. There is limited evidence in the literature that compares the masking ability of multi-laminate veneers. The aim of this in-vitro study was to compare the masking ability of bi-laminate (BL) and tri-laminate (TL) all-ceramic veneers cemented on tooth-colored ceramic discs. A total of 40 veneers (shade A1, 10-mm diameter, 0.8-mm thick) were manufactured-20 BL veneers (0.4-mm pressable ceramic coping veneered with 0.4-mm thick enamel layer) and 20 TL veneers (0.4-mm coping veneered with 0.2-mm thick opaque interlayer and 0.2-mm thick enamel layer). A bonding apparatus was utilized to adhesively cement all veneers on the ceramic discs (shade A1), simulating teeth of light and dark color. The resulting groups (N = 10 each) were the reference groups (shade A1 ceramic base) BL-1 and TL-1 veneers, and the test groups (shade A4 ceramic base) BL-4 and TL-4 veneers. The color of the cemented veneers was measured using a spectrophotometer. The data were converted to CIE L*a*b* coordinates, and ΔE* were calculated to allow for statistical analysis. The color differences between the samples with the A1 and A4 ceramic bases were significantly lower when covered with TL veneers (mean ΔE*: 3.2 units) than with BL veneers (mean ΔE*: 4.0 units: p < 0.001), indicating a better masking ability of the TL veneers. The 0.8-mm thick TL veneer was able to mask darker tooth-colored ceramic disc within clinically acceptable limits. Increased understanding of the masking ability of ceramics and of color science is necessary in these esthetically aware times. Providing tri-laminate veneers for darker colored teeth seems to result in more predictable esthetical results than when using bi-laminate veneers. Patients with discolored/darker teeth may benefit from a more predictable esthetic result when teeth restored with tri-laminate rather than bi-laminate veneers. © 2014 Wiley Periodicals, Inc.

Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: diagnostic study

PubMed Central

Nijman, Ruud G; Vergouwe, Yvonne; Thompson, Matthew; van Veen, Mirjam; van Meurs, Alfred H J; van der Lei, Johan; Steyerberg, Ewout W; Moll, Henriette A

2013-01-01

Objective To derive, cross validate, and externally validate a clinical prediction model that assesses the risks of different serious bacterial infections in children with fever at the emergency department. Design Prospective observational diagnostic study. Setting Three paediatric emergency care units: two in the Netherlands and one in the United Kingdom. Participants Children with fever, aged 1 month to 15 years, at three paediatric emergency care units: Rotterdam (n=1750) and the Hague (n=967), the Netherlands, and Coventry (n=487), United Kingdom. A prediction model was constructed using multivariable polytomous logistic regression analysis and included the predefined predictor variables age, duration of fever, tachycardia, temperature, tachypnoea, ill appearance, chest wall retractions, prolonged capillary refill time (>3 seconds), oxygen saturation <94%, and C reactive protein. Main outcome measures Pneumonia, other serious bacterial infections (SBIs, including septicaemia/meningitis, urinary tract infections, and others), and no SBIs. Results Oxygen saturation <94% and presence of tachypnoea were important predictors of pneumonia. A raised C reactive protein level predicted the presence of both pneumonia and other SBIs, whereas chest wall retractions and oxygen saturation <94% were useful to rule out the presence of other SBIs. Discriminative ability (C statistic) to predict pneumonia was 0.81 (95% confidence interval 0.73 to 0.88); for other SBIs this was even better: 0.86 (0.79 to 0.92). Risk thresholds of 10% or more were useful to identify children with serious bacterial infections; risk thresholds less than 2.5% were useful to rule out the presence of serious bacterial infections. External validation showed good discrimination for the prediction of pneumonia (0.81, 0.69 to 0.93); discriminative ability for the prediction of other SBIs was lower (0.69, 0.53 to 0.86). Conclusion A validated prediction model, including clinical signs, symptoms, and C reactive protein level, was useful for estimating the likelihood of pneumonia and other SBIs in children with fever, such as septicaemia/meningitis and urinary tract infections. PMID:23550046

Working Memory and Speech Comprehension in Older Adults With Hearing Impairment.

PubMed

Nagaraj, Naveen K

2017-10-17

This study examined the relationship between working memory (WM) and speech comprehension in older adults with hearing impairment (HI). It was hypothesized that WM would explain significant variance in speech comprehension measured in multitalker babble (MTB). Twenty-four older (59-73 years) adults with sensorineural HI participated. WM capacity (WMC) was measured using 3 complex span tasks. Speech comprehension was assessed using multiple passages, and speech identification ability was measured using recall of sentence final-word and key words. Speech measures were performed in quiet and in the presence of MTB at + 5 dB signal-to-noise ratio. Results suggested that participants' speech identification was poorer in MTB, but their ability to comprehend discourse in MTB was at least as good as in quiet. WMC did not explain significant variance in speech comprehension before and after controlling for age and audibility. However, WMC explained significant variance in low-context sentence key words identification in MTB. These results suggest that WMC plays an important role in identifying low-context sentences in MTB, but not when comprehending semantically rich discourse passages. In general, data did not support individual variability in WMC as a factor that predicts speech comprehension ability in older adults with HI.

A multifunctional targeting probe with dual-mode imaging and photothermal therapy used in vivo.

PubMed

Zhang, Xiao-Shuai; Xuan, Yang; Yang, Xiao-Quan; Cheng, Kai; Zhang, Ruo-Yun; Li, Cheng; Tan, Fang; Cao, Yuan-Cheng; Song, Xian-Lin; An, Jie; Hou, Xiao-Lin; Zhao, Yuan-Di

2018-04-19

Ag 2 S has the characteristics of conventional quantum dot such as broad excitation spectrum, narrow emission spectrum, long fluorescence lifetime, strong anti-bleaching ability, and other optical properties. Moreover, since its fluorescence emission is located in the NIR-II region, has stronger penetrating ability for tissue. Ag 2 S quantum dot has strong absorption during the visible and NIR regions, it has good photothermal and photoacoustic response under certain wavelength excitation. 200 nm aqueous probe Ag 2 S@DSPE-PEG 2000 -FA (Ag 2 S@DP-FA) with good dispersibility and stability was prepared by coating hydrophobic Ag 2 S with the mixture of folic acid (FA) modified DSPE-PEG 2000 (DP) and other polymers, it was found the probe had good fluorescent, photoacoustic and photothermal responses, and a low cell cytotoxicity at 50 μg/mL Ag concentration. Blood biochemical analysis, liver enzyme and tissue histopathological test showed that no significant influence was observed on blood and organs within 15 days after injection of the probe. In vivo and in vitro fluorescence and photoacoustic imaging of the probe further demonstrated that the Ag 2 S@DP-FA probe had good active targeting ability for tumor. In vivo and in vitro photothermal therapy experiments confirmed that the probe also had good ability of killing tumor by photothermal. Ag 2 S@DP-FA was a safe, integrated diagnosis and treatment probe with multi-mode imaging, photothermal therapy and active targeting ability, which had a great application prospect in the early diagnosis and treatment of tumor.

Dispositional hope and life satisfaction among older adults attending lifelong learning programs.

PubMed

Oliver, A; Tomás, J M; Montoro-Rodriguez, J

2017-09-01

The aim of this study is to explore the indirect effects of dispositional hope in the life satisfaction of older adults attending a lifelong learning program at the University of Valencia, Spain. We examine the mediating impact of dispositional hope regarding its ability to impact life satisfaction while considering affective and confidant social support, perceived health and leisure activities, consciousness and spirituality as predictors. Analysis were based on survey data (response rate 77.4%) provided by 737 adults 55 years old or more (Mean age=65.41, SD=6.60; 69% woman). A structural model with latent variables was specified and estimated in Mplus. The results show the ability of just a few variables to sum up a reasonable model to apply to successful aging population. All these variables are correlated and significantly predict hope with the exception of health. The model additionally includes significant positive indirect effects from spirituality, affective support and consciousness on satisfaction. The model has a good fit in terms of both the measurement and structural model. Regarding predictive power, these comprehensive four main areas of successful aging account for 42% of hope and finally for one third of the life satisfaction variance. Results support the mediating role of dispositional hope on the life satisfaction among older adults attending lifelong learning programs. These findings also support the MacArthur model of successful aging adapted to older adults with high levels of functional, social and cognitive ability. Dispositional hope, perceived health, and social support were the strongest predictors of satisfaction with life. Copyright © 2017 Elsevier B.V. All rights reserved.

CoMFA and CoMSIA 3D-QSAR studies on S(6)-(4-nitrobenzyl)mercaptopurine riboside (NBMPR) analogs as inhibitors of human equilibrative nucleoside transporter 1 (hENT1).

PubMed

Gupte, Amol; Buolamwini, John K

2009-01-15

3D-QSAR (CoMFA and CoMSIA) studies were performed on human equlibrative nucleoside transporter (hENT1) inhibitors displaying K(i) values ranging from 10,000 to 0.7nM. Both CoMFA and CoMSIA analysis gave reliable models with q2 values >0.50 and r2 values >0.92. The models have been validated for their stability and robustness using group validation and bootstrapping techniques and for their predictive abilities using an external test set of nine compounds. The high predictive r2 values of the test set (0.72 for CoMFA model and 0.74 for CoMSIA model) reveals that the models can prove to be a useful tool for activity prediction of newly designed nucleoside transporter inhibitors. The CoMFA and CoMSIA contour maps identify features important for exhibiting good binding affinities at the transporter, and can thus serve as a useful guide for the design of potential equilibrative nucleoside transporter inhibitors.

MELCOR Analysis of OSU Multi-Application Small Light Water Reactor (MASLWR) Experiment

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

Yoon, Dhongik S.; Jo, HangJin; Fu, Wen

A multi-application small light water reactor (MASLWR) conceptual design was developed by Oregon State University (OSU) with emphasis on passive safety systems. The passive containment safety system employs condensation and natural circulation to achieve the necessary heat removal from the containment in case of postulated accidents. Containment condensation experiments at the MASLWR test facility at OSU are modeled and analyzed with MELCOR, a system-level reactor accident analysis computer code. The analysis assesses its ability to predict condensation heat transfer in the presence of noncondensable gas for accidents where high-energy steam is released into the containment. This work demonstrates MELCOR’s abilitymore » to predict the pressure-temperature response of the scaled containment. Our analysis indicates that the heat removal rates are underestimated in the experiment due to the limited locations of the thermocouples and applies corrections to these measurements by conducting integral energy analyses along with CFD simulation for confirmation. Furthermore, the corrected heat removal rate measurements and the MELCOR predictions on the heat removal rate from the containment show good agreement with the experimental data.« less

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Predictive Capacity of Cloninger's temperament and character inventory (TCI-R) in alcohol use disorder outcomes.

PubMed

Ávila Escribano, José Juan; Sánchez Barba, Mercedes; Álvarez Pedrero, Aida; López Villarreal, Ana; Recio Pérez, Joaquina; Rodríguez Rodilla, Manuela; Fraile García, Eulalia

2016-06-14

to investigate the ability to predict the outcome of alcohol use disorders through Cloninger's temperament and character inventory (TCI-R). this is a prospective study consisting of 237 outpatients with alcohol use disorders who underwent follow-up treatment for 6 months and whose personality traits were studied using TCI-R. At the end of that period, the scores of each TCI-R trait were analyzed in terms of those who remained in treatment and those who dropped out. The whole group scored highly in novelty seeking (NS) and harm avoidance (HA) and produced low scores in self-directedness (SD), these last traits are considered prominent. The drop-out group scored significantly (p=.004) higher in novelty seeking (NS) than the follow-up group. Also, when the score was higher than the 67 percentile the likelihood of abandoning the treatment was 1.07 times higher. Cloninger's temperament and character inventory is a good instrument to predict the outcome of treatment of patients with alcohol use disorders and the novelty seeking (NS) dimension is strongly related to therapeutic drop-out.

MELCOR Analysis of OSU Multi-Application Small Light Water Reactor (MASLWR) Experiment

DOE PAGES

Yoon, Dhongik S.; Jo, HangJin; Fu, Wen; ...

2017-05-23

A multi-application small light water reactor (MASLWR) conceptual design was developed by Oregon State University (OSU) with emphasis on passive safety systems. The passive containment safety system employs condensation and natural circulation to achieve the necessary heat removal from the containment in case of postulated accidents. Containment condensation experiments at the MASLWR test facility at OSU are modeled and analyzed with MELCOR, a system-level reactor accident analysis computer code. The analysis assesses its ability to predict condensation heat transfer in the presence of noncondensable gas for accidents where high-energy steam is released into the containment. This work demonstrates MELCOR’s abilitymore » to predict the pressure-temperature response of the scaled containment. Our analysis indicates that the heat removal rates are underestimated in the experiment due to the limited locations of the thermocouples and applies corrections to these measurements by conducting integral energy analyses along with CFD simulation for confirmation. Furthermore, the corrected heat removal rate measurements and the MELCOR predictions on the heat removal rate from the containment show good agreement with the experimental data.« less

Predicting individual fusional range from optometric data

NASA Astrophysics Data System (ADS)

Endrikhovski, Serguei; Jin, Elaine; Miller, Michael E.; Ford, Robert W.

2005-03-01

A model was developed to predict the range of disparities that can be fused by an individual user from optometric measurements. This model uses parameters, such as dissociated phoria and fusional reserves, to calculate an individual user"s fusional range (i.e., the disparities that can be fused on stereoscopic displays) when the user views a stereoscopic stimulus from various distances. This model is validated by comparing its output with data from a study in which the individual fusional range of a group of users was quantified while they viewed a stereoscopic display from distances of 0.5, 1.0, and 2.0 meters. Overall, the model provides good data predictions for the majority of the subjects and can be generalized for other viewing conditions. The model may, therefore, be used within a customized stereoscopic system, which would render stereoscopic information in a way that accounts for the individual differences in fusional range. Because the comfort of an individual user also depends on the user"s ability to fuse stereo images, such a system may, consequently, improve the comfort level and viewing experience for people with different stereoscopic fusional capabilities.

Coupling of Markov chains and cellular automata spatial models to predict land cover changes (case study: upper Ci Leungsi catchment area)

NASA Astrophysics Data System (ADS)

Marko, K.; Zulkarnain, F.; Kusratmoko, E.

2016-11-01

Land cover changes particular in urban catchment area has been rapidly occur. Land cover changes occur as a result of increasing demand for built-up area. Various kinds of environmental and hydrological problems e.g. floods and urban heat island can happen if the changes are uncontrolled. This study aims to predict land cover changes using coupling of Markov chains and cellular automata. One of the most rapid land cover changes is occurs at upper Ci Leungsi catchment area that located near Bekasi City and Jakarta Metropolitan Area. Markov chains has a good ability to predict the probability of change statistically while cellular automata believed as a powerful method in reading the spatial patterns of change. Temporal land cover data was obtained by remote sensing satellite imageries. In addition, this study also used multi-criteria analysis to determine which driving factor that could stimulate the changes such as proximity, elevation, and slope. Coupling of these two methods could give better prediction model rather than just using it separately. The prediction model was validated using existing 2015 land cover data and shown a satisfactory kappa coefficient. The most significant increasing land cover is built-up area from 24% to 53%.

Prediction of blood-brain partitioning: a model based on molecular electronegativity distance vector descriptors.

PubMed

Zhang, Yong-Hong; Xia, Zhi-Ning; Qin, Li-Tang; Liu, Shu-Shen

2010-09-01

The objective of this paper is to build a reliable model based on the molecular electronegativity distance vector (MEDV) descriptors for predicting the blood-brain barrier (BBB) permeability and to reveal the effects of the molecular structural segments on the BBB permeability. Using 70 structurally diverse compounds, the partial least squares regression (PLSR) models between the BBB permeability and the MEDV descriptors were developed and validated by the variable selection and modeling based on prediction (VSMP) technique. The estimation ability, stability, and predictive power of a model are evaluated by the estimated correlation coefficient (r), leave-one-out (LOO) cross-validation correlation coefficient (q), and predictive correlation coefficient (R(p)). It has been found that PLSR model has good quality, r=0.9202, q=0.7956, and R(p)=0.6649 for M1 model based on the training set of 57 samples. To search the most important structural factors affecting the BBB permeability of compounds, we performed the values of the variable importance in projection (VIP) analysis for MEDV descriptors. It was found that some structural fragments in compounds, such as -CH(3), -CH(2)-, =CH-, =C, triple bond C-, -CH<, =C<, =N-, -NH-, =O, and -OH, are the most important factors affecting the BBB permeability. (c) 2010. Published by Elsevier Inc.

QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

PubMed

Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-06-15

The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step. Copyright © 2011 Elsevier B.V. All rights reserved.

Estimation of work capacity and work ability among plantation workers in South India.

PubMed

Anbazhagan, Suguna; Ramesh, Naveen; Surekha, A; Fathima, Farah N; Melina; Anjali

2016-01-01

Work capacity is the ability to perform real physical work, and work ability is a result of interaction of worker to his or her work that is how good a worker is at present, in near future, and how able is he or she to do his or her work with respect to work demands and health and mental resources. To assess the work capacity and work ability and to study the factors associated with work capacity and work ability of workers at a tea plantation in South India. A cross-sectional study was conducted at a tea plantation in Annamalai, South India, from March to May 2015. Data were collected using a structured interview schedule comprising of three parts as follows: sociodemographic data, work ability questionnaire, and work capacity assessment. Of the 199 subjects participated in the study, majority [90 (45.3%)] were in the age group of 46-55 years, and 128 (64.3%) were females. Of the 199 workers, 12.6% had poor aerobic capacity (by Harvard Step test), 88.4% had an endurance of more than 1 h, 70.9% had better work productivity and energetic efficiency, and the voluntary activity workers spent most time on household chores. Of the 199 workers assessed, only 9.6% had good work ability. There is negative correlation between work ability and body mass index (BMI). Our study found 12.6% workers with poor aerobic capacity and 9.6% of workers with good work ability. Periodic health examinations and other screening procedures should be made as routine in workplace to improve work ability and capacity.

Flux balance analysis of different carbon source fermentation with hydrogen producing Clostridium butyricum using Cell Net Analyzer.

PubMed

Rafieenia, Razieh; Chaganti, Subba Rao

2015-01-01

A metabolic network model for Clostridium butyricum was developed using six different carbon sources (sucrose, fructose, galactose, mannose, trehalose and ribose) to study the fermentative H2 production. The model was used for investigation of H2 production and the ability of growth on different substrates to predict the maximum abilities for fermentative H2 production that each substrate can support. NADH fluxes were calculated by the model as an important cofactor affecting on H2 production. Butyrate and acetate production were used as model assumptions and biomass formation was chosen as the objective function for flux analysis calculations. Among the substrates selected, sucrose and trehalose supported the maximum growth and H2 yields. The Cell Net Analyzer metabolic network model developed for H2 estimation revealed good correlation with experimental data and could be further used to study the effect of environmental conditions and substrates concentration on H2 yield. Copyright © 2014 Elsevier Ltd. All rights reserved.

What Are You Measuring? Dimensionality and Reliability Analysis of Ability and Speed in Medical School Didactic Examinations.

PubMed

Thompson, James J

2016-01-01

Summative didactic evaluation often involves multiple choice questions which are then aggregated into exam scores, course scores, and cumulative grade point averages. To be valid, each of these levels should have some relationship to the topic tested (dimensionality) and be sufficiently reproducible between persons (reliability) to justify student ranking. Evaluation of dimensionality is difficult and is complicated by the classic observation that didactic performance involves a generalized component (g) in addition to subtest specific factors. In this work, 183 students were analyzed over two academic years in 13 courses with 44 exams and 3352 questions for both accuracy and speed. Reliability at all levels was good (>0.95). Assessed by bifactor analysis, g effects dominated most levels resulting in essential unidimensionality. Effect sizes on predicted accuracy and speed due to nesting in exams and courses was small. There was little relationship between person ability and person speed. Thus, the hierarchical grading system appears warrented because of its g-dependence.

Neurocognitive ability in adults coping with alcohol and drug relapse temptations.

PubMed

Tapert, Susan F; Ozyurt, Saba Senses; Myers, Mark G; Brown, Sandra A

2004-05-01

Coping is important for preventing relapse, but may be utilized differently depending on the individual's level of cognitive functioning. Impaired reasoning, attention, and memory are commonly observed in alcohol-dependent individuals. This study describes the prospective relationship between neuropsychological functioning and utilization of coping strategies in predicting outcome one year after discharge from an inpatient alcohol treatment program. Male veterans (n = 43) hospitalized in an alcohol treatment facility were given structured interviews, coping questionnaires, and neuropsychological testing, and were followed three and 12 months after discharge. Neuropsychological ability moderated the relationship between coping and drinking outcomes one year after treatment. This was particularly true for patients with better neurocognitive functioning. Specifically, patients with higher neurocognitive performances and more maladaptive coping responses, such as self-blame, had a greater percentage of drinking days at follow-up. Alcohol-dependent adults with good neuropsychological functioning may be able to benefit more from coping skills training. For those with neuropsychological deficits, coping skills training may need to take cognitive limitations into consideration.

Mycotoxin Production in Liquid Culture and on Plants Infected with Alternaria spp. Isolated from Rocket and Cabbage

PubMed Central

Siciliano, Ilenia; Ortu, Giuseppe; Gilardi, Giovanna; Gullino, Maria Lodovica; Garibaldi, Angelo

2015-01-01

Fungi belonging to the genus Alternaria are common pathogens of fruit and vegetables with some species able to produce secondary metabolites dangerous to human health. Twenty-eight Alternaria isolates from rocket and cabbage were investigated for their mycotoxin production. Five different Alternaria toxins were extracted from synthetic liquid media and from plant material (cabbage, cultivated rocket, cauliflower). A modified Czapek-Dox medium was used for the in vitro assay. Under these conditions, more than 80% of the isolates showed the ability to produce at least one mycotoxin, generally with higher levels for tenuazonic acid. However, the same isolates analyzed in vivo seemed to lose their ability to produce tenuazonic acid. For the other mycotoxins; alternariol, alternariol monomethyl ether, altenuene and tentoxin a good correlation between in vitro and in vivo production was observed. In vitro assay is a useful tool to predict the possible mycotoxin contamination under field and greenhouse conditions. PMID:25751147

Mycotoxin production in liquid culture and on plants infected with Alternaria spp. isolated from rocket and cabbage.

PubMed

Siciliano, Ilenia; Ortu, Giuseppe; Gilardi, Giovanna; Gullino, Maria Lodovica; Garibaldi, Angelo

2015-03-05

Fungi belonging to the genus Alternaria are common pathogens of fruit and vegetables with some species able to produce secondary metabolites dangerous to human health. Twenty-eight Alternaria isolates from rocket and cabbage were investigated for their mycotoxin production. Five different Alternaria toxins were extracted from synthetic liquid media and from plant material (cabbage, cultivated rocket, cauliflower). A modified Czapek-Dox medium was used for the in vitro assay. Under these conditions, more than 80% of the isolates showed the ability to produce at least one mycotoxin, generally with higher levels for tenuazonic acid. However, the same isolates analyzed in vivo seemed to lose their ability to produce tenuazonic acid. For the other mycotoxins; alternariol, alternariol monomethyl ether, altenuene and tentoxin a good correlation between in vitro and in vivo production was observed. In vitro assay is a useful tool to predict the possible mycotoxin contamination under field and greenhouse conditions.

Azolium analogues as CDK4 inhibitors: Pharmacophore modeling, 3D QSAR study and new lead drug discovery

NASA Astrophysics Data System (ADS)

Rondla, Rohini; Padma Rao, Lavanya Souda; Ramatenki, Vishwanath; Vadija, Rajender; Mukkera, Thirupathi; Potlapally, Sarita Rajender; Vuruputuri, Uma

2017-04-01

The cyclin-dependent kinase 4 (CDK4) enzyme is a key regulator in cell cycle G1 phase progression. It is often overexpressed in variety of cancer cells, which makes it an attractive therapeutic target for cancer treatment. A number of chemical scaffolds have been reported as CDK4 inhibitors in the literature, and in particular azolium scaffolds as potential inhibitors. Here, a ligand based pharmacophore modeling and an atom based 3D-QSAR analyses for a series of azolium based CDK4 inhibitors are presented. A five point pharmacophore hypothesis, i.e. APRRR with one H-bond acceptor (A), one positive cationic feature (P) and three ring aromatic sites (R) is developed, which yielded an atom based 3D-QSAR model that shows an excellent correlation coefficient value- R2 = 0.93, fisher ratio- F = 207, along with good predictive ability- Q2 = 0.79, and Pearson R value = 0.89. The visual inspection of the 3D-QSAR model, with the most active and the least active ligands, demonstrates the favorable and unfavorable structural regions for the activity towards CDK4. The roles of positively charged nitrogen, the steric effect, ligand flexibility, and the substituents on the activity are in good agreement with the previously reported experimental results. The generated 3D QSAR model is further applied as query for a 3D database screening, which identifies 23 lead drug candidates with good predicted activities and diverse scaffolds. The ADME analysis reveals that, the pharmacokinetic parameters of all the identified new leads are within the acceptable range.

Application of Taguchi L16 design method for comparative study of ability of 3A zeolite in removal of Rhodamine B and Malachite green from environmental water samples.

PubMed

Rahmani, Mashaallah; Kaykhaii, Massoud; Sasani, Mojtaba

2018-01-05

This study aimed to investigate the efficiency of 3A zeolite as a novel adsorbent for removal of Rhodamine B and Malachite green dyes from water samples. To increase the removal efficiency, effecting parameters on adsorption process were investigated and optimized by adopting Taguchi design of experiments approach. The percentage contribution of each parameter on the removal of Rhodamine B and Malachite green dyes determined using ANOVA and showed that the most effective parameters in removal of RhB and MG by 3A zeolite are initial concentration of dye and pH, respectively. Under optimized condition, the amount predicted by Taguchi design method and the value obtained experimentally, showed good closeness (more than 94.86%). Good adsorption efficiency obtained for proposed methods indicates that, the 3A zeolite is capable to remove the significant amounts of Rhodamine B and Malachite green from environmental water samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence of personality and neuropsychological ability on social functioning and self-management in bipolar disorder.

PubMed

Vierck, Esther; Joyce, Peter R

2015-10-30

A majority of bipolar patients (BD) show functional difficulties even in remission. In recent years cognitive functions and personality characteristics have been associated with occupational and psychosocial outcomes, but findings are not consistent. We assessed personality and cognitive functioning through a range of tests in BD and control participants. Three cognitive domains-verbal memory, facial-executive, and spatial memory-were extracted by principal component analysis. These factors and selected personality dimensions were included in hierarchical regression analysis to predict psychosocial functioning and the use of self-management strategies while controlling for mood status. The best determinants of good psychosocial functioning were good verbal memory and high self-directedness. The use of self-management techniques was associated with a low level of harm-avoidance. Our findings indicate that strategies to improve memory and self-directedness may be useful for increasing functioning in individuals with bipolar disorder. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Application of Taguchi L16 design method for comparative study of ability of 3A zeolite in removal of Rhodamine B and Malachite green from environmental water samples

NASA Astrophysics Data System (ADS)

Rahmani, Mashaallah; Kaykhaii, Massoud; Sasani, Mojtaba

2018-01-01

This study aimed to investigate the efficiency of 3A zeolite as a novel adsorbent for removal of Rhodamine B and Malachite green dyes from water samples. To increase the removal efficiency, effecting parameters on adsorption process were investigated and optimized by adopting Taguchi design of experiments approach. The percentage contribution of each parameter on the removal of Rhodamine B and Malachite green dyes determined using ANOVA and showed that the most effective parameters in removal of RhB and MG by 3A zeolite are initial concentration of dye and pH, respectively. Under optimized condition, the amount predicted by Taguchi design method and the value obtained experimentally, showed good closeness (more than 94.86%). Good adsorption efficiency obtained for proposed methods indicates that, the 3A zeolite is capable to remove the significant amounts of Rhodamine B and Malachite green from environmental water samples.

Creating your own leadership brand.

PubMed

Kerfoot, Karlene

2002-01-01

Building equity in a brand happens through many encounters. The initial attraction must be followed by the meeting of expectations. This creates a loyalty that is part of an emotional connection to that brand. This is the same process people go through when they first meet a leader and decide if this is a person they want to buy into. People will examine your style, your competence, and your standards. If you fail on any of these fronts, your ability to lead will be severely compromised. People expect more of leaders now, because they know and recognize good leaders. And, predictably, people are now more cynical of leaders because of the well-publicized excess of a few leaders who advanced their own causes at the expense of their people and their financial future. This will turn out to be a good thing, because it will create a higher standard of leadership that all must aspire to achieve. When the bar is raised for us, our standards of performance are also raised.

Effect of sample preparation on the measurement of sugars, organic acids, and polyphenols in apple fruit by mid-infrared spectroscopy.

PubMed

Bureau, Sylvie; Scibisz, Iwona; Le Bourvellec, Carine; Renard, Catherine M G C

2012-04-11

The objectives of this study were (i) to test different conditions of freezing, thawing, and grinding during sample preparation and (ii) to evaluate the possibility of using mid-infrared spectroscopy for analyzing the composition of sugars, organic acids, and polyphenols in apples. Seven commercial apple cultivars were chosen for their large variability in composition (total polyphenols from 406 to 1033 mg kg(-1) fresh weight). The different conditions of sample preparation affected only the phenolic compounds and not sugars or organic acids. The regression models of the mid-infrared spectra showed a good ability to estimate sugar and organic acid contents (R(2) ≥ 0.96), except for citric acid. Good predictions were obtained for total phenolic, flavan-3-ols, and procyanidins (R(2) ≥ 0.94) provided oxidation was avoided during sample preparation. A rapid and simple procedure was then proposed for phenolic compounds using sodium fluoride during sample homogenization at ambient temperature and freeze-drying before spectra acquisition.

Sustained modelling ability of artificial neural networks in the analysis of two pharmaceuticals (dextropropoxyphene and dipyrone) present in unequal concentrations.

PubMed

Cámara, María S; Ferroni, Félix M; De Zan, Mercedes; Goicoechea, Héctor C

2003-07-01

An improvement is presented on the simultaneous determination of two active ingredients present in unequal concentrations in injections. The analysis was carried out with spectrophotometric data and non-linear multivariate calibration methods, in particular artificial neural networks (ANNs). The presence of non-linearities caused by the major analyte concentrations which deviate from Beer's law was confirmed by plotting actual vs. predicted concentrations, and observing curvatures in the residuals for the estimated concentrations with linear methods. Mixtures of dextropropoxyphene and dipyrone have been analysed by using linear and non-linear partial least-squares (PLS and NPLSs) and ANNs. Notwithstanding the high degree of spectral overlap and the occurrence of non-linearities, rapid and simultaneous analysis has been achieved, with reasonably good accuracy and precision. A commercial sample was analysed by using the present methodology, and the obtained results show reasonably good agreement with those obtained by using high-performance liquid chromatography (HPLC) and a UV-spectrophotometric comparative methods.

Validation of a Spanish-language version of the ADHD Rating Scale IV in a Spanish sample.

PubMed

Vallejo-Valdivielso, M; Soutullo, C A; de Castro-Manglano, P; Marín-Méndez, J J; Díez-Suárez, A

2017-07-14

The purpose of this study is to validate a Spanish-language version of the 18-item ADHD Rating Scale-IV (ADHD-RS-IV.es) in a Spanish sample. From a total sample of 652 children and adolescents aged 6 to 17 years (mean age was 11.14±3.27), we included 518 who met the DSM-IV-TR criteria for ADHD and 134 healthy controls. To evaluate the factorial structure, validity, and reliability of the scale, we performed a confirmatory factor analysis (CFA) using structural equation modelling on a polychoric correlation matrix and maximum likelihood estimation. The scale's discriminant validity and predictive value were estimated using ROC (receiver operating characteristics) curve analysis. Both the full scale and the subscales of the Spanish-language version of the ADHD-RS-IV showed good internal consistency. Cronbach's alpha was 0.94 for the full scale and ≥ 0.90 for the subscales, and ordinal alpha was 0.95 and ≥ 0.90, respectively. CFA showed that a two-factor model (inattention and hyperactivity/impulsivity) provided the best fit for the data. ADHD-RS-IV.es offered good discriminant ability to distinguish between patients with ADHD and controls (AUC=0.97). The two-factor structure of the Spanish-language version of the ADHD-RS-IV (ADHD-RS-IV.es) is consistent with those of the DSM-IV-TR and DSM-5 as well as with the model proposed by the author of the original scale. Furthermore, it has good discriminant ability. ADHD-RS-IV.es is therefore a valid and reliable tool for determining presence and severity of ADHD symptoms in the Spanish population. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Modelling of a holographic interferometry based calorimeter for radiation dosimetry

NASA Astrophysics Data System (ADS)

Beigzadeh, A. M.; Vaziri, M. R. Rashidian; Ziaie, F.

2017-08-01

In this research work, a model for predicting the behaviour of holographic interferometry based calorimeters for radiation dosimetry is introduced. Using this technique for radiation dosimetry via measuring the variations of refractive index due to energy deposition of radiation has several considerable advantages such as extreme sensitivity and ability of working without normally used temperature sensors that disturb the radiation field. We have shown that the results of our model are in good agreement with the experiments performed by other researchers under the same conditions. This model also reveals that these types of calorimeters have the additional and considerable merits of transforming the dose distribution to a set of discernible interference fringes.

Post-1500 Population Flows and the Long Run Determinants of Economic Growth and Inequality

PubMed Central

Putterman, Louis; Weil, David N.

2013-01-01

We construct a matrix showing the share of the year 2000 population in every country that is descended from people in different source countries in the year 1500. Using the matrix to adjust indicators of early development so they reflect the history of a population’s ancestors rather than the history of the place they live today greatly improves the ability of those indicators to predict current GDP. The variance of early development history of a country’s inhabitants is a good predictor for current inequality, with ethnic groups originating in regions having longer histories of organized states tending to be at the upper end of a country’s income distribution. PMID:24478530

Post-1500 Population Flows and the Long Run Determinants of Economic Growth and Inequality.

PubMed

Putterman, Louis; Weil, David N

2010-01-01

We construct a matrix showing the share of the year 2000 population in every country that is descended from people in different source countries in the year 1500. Using the matrix to adjust indicators of early development so they reflect the history of a population's ancestors rather than the history of the place they live today greatly improves the ability of those indicators to predict current GDP. The variance of early development history of a country's inhabitants is a good predictor for current inequality, with ethnic groups originating in regions having longer histories of organized states tending to be at the upper end of a country's income distribution.

A points-based algorithm for prognosticating clinical outcome of Chiari malformation Type I with syringomyelia: results from a predictive model analysis of 82 surgically managed adult patients.

PubMed

Thakar, Sumit; Sivaraju, Laxminadh; Jacob, Kuruthukulangara S; Arun, Aditya Atal; Aryan, Saritha; Mohan, Dilip; Sai Kiran, Narayanam Anantha; Hegde, Alangar S

2018-01-01

OBJECTIVE Although various predictors of postoperative outcome have been previously identified in patients with Chiari malformation Type I (CMI) with syringomyelia, there is no known algorithm for predicting a multifactorial outcome measure in this widely studied disorder. Using one of the largest preoperative variable arrays used so far in CMI research, the authors attempted to generate a formula for predicting postoperative outcome. METHODS Data from the clinical records of 82 symptomatic adult patients with CMI and altered hindbrain CSF flow who were managed with foramen magnum decompression, C-1 laminectomy, and duraplasty over an 8-year period were collected and analyzed. Various preoperative clinical and radiological variables in the 57 patients who formed the study cohort were assessed in a bivariate analysis to determine their ability to predict clinical outcome (as measured on the Chicago Chiari Outcome Scale [CCOS]) and the resolution of syrinx at the last follow-up. The variables that were significant in the bivariate analysis were further analyzed in a multiple linear regression analysis. Different regression models were tested, and the model with the best prediction of CCOS was identified and internally validated in a subcohort of 25 patients. RESULTS There was no correlation between CCOS score and syrinx resolution (p = 0.24) at a mean ± SD follow-up of 40.29 ± 10.36 months. Multiple linear regression analysis revealed that the presence of gait instability, obex position, and the M-line-fourth ventricle vertex (FVV) distance correlated with CCOS score, while the presence of motor deficits was associated with poor syrinx resolution (p ≤ 0.05). The algorithm generated from the regression model demonstrated good diagnostic accuracy (area under curve 0.81), with a score of more than 128 points demonstrating 100% specificity for clinical improvement (CCOS score of 11 or greater). The model had excellent reliability (κ = 0.85) and was validated with fair accuracy in the validation cohort (area under the curve 0.75). CONCLUSIONS The presence of gait imbalance and motor deficits independently predict worse clinical and radiological outcomes, respectively, after decompressive surgery for CMI with altered hindbrain CSF flow. Caudal displacement of the obex and a shorter M-line-FVV distance correlated with good CCOS scores, indicating that patients with a greater degree of hindbrain pathology respond better to surgery. The proposed points-based algorithm has good predictive value for postoperative multifactorial outcome in these patients.

Super-recognizers: People with extraordinary face recognition ability

PubMed Central

Russell, Richard; Duchaine, Brad; Nakayama, Ken

2014-01-01

We tested four people who claimed to have significantly better than ordinary face recognition ability. Exceptional ability was confirmed in each case. On two very different tests of face recognition, all four experimental subjects performed beyond the range of control subject performance. They also scored significantly better than average on a perceptual discrimination test with faces. This effect was larger with upright than inverted faces, and the four subjects showed a larger ‘inversion effect’ than control subjects, who in turn showed a larger inversion effect than developmental prosopagnosics. This indicates an association between face recognition ability and the magnitude of the inversion effect. Overall, these ‘super-recognizers’ are about as good at face recognition and perception as developmental prosopagnosics are bad. Our findings demonstrate the existence of people with exceptionally good face recognition ability, and show that the range of face recognition and face perception ability is wider than previously acknowledged. PMID:19293090

Super-recognizers: people with extraordinary face recognition ability.

PubMed

Russell, Richard; Duchaine, Brad; Nakayama, Ken

2009-04-01

We tested 4 people who claimed to have significantly better than ordinary face recognition ability. Exceptional ability was confirmed in each case. On two very different tests of face recognition, all 4 experimental subjects performed beyond the range of control subject performance. They also scored significantly better than average on a perceptual discrimination test with faces. This effect was larger with upright than with inverted faces, and the 4 subjects showed a larger "inversion effect" than did control subjects, who in turn showed a larger inversion effect than did developmental prosopagnosics. This result indicates an association between face recognition ability and the magnitude of the inversion effect. Overall, these "super-recognizers" are about as good at face recognition and perception as developmental prosopagnosics are bad. Our findings demonstrate the existence of people with exceptionally good face recognition ability and show that the range of face recognition and face perception ability is wider than has been previously acknowledged.

Pain, fatigue and hand function closely correlated to work ability and employment status in systemic sclerosis.

PubMed

Sandqvist, Gunnel; Scheja, Agneta; Hesselstrand, Roger

2010-09-01

To identify factors, individual and work related, influencing work ability, and to assess the association between work ability and employment status, activities of daily life (ADLs) and quality of life in patients with SSc. Fifty-seven consecutive patients (53 females/4 males) with SSc (47 lcSSc/10 dcSSc) were included. Median age was 58 [interquartile range (IQR) 47-62] years and disease duration 14 (9-19) years. The patients were assessed for socio-demographic characteristics, disease parameters, symptoms, work ability, empowerment and adaptations in a workplace, social support, ADLs and quality of life. Work ability, assessed with the Work Ability Index (WAI) could be evaluated in 48 of 57 patients. The correlation between employment status and WAI was good (r(s) = 0.79, P < 0.001). Thirteen patients had good or excellent WAI, 15 had less good and 20 had poor WAI. There were no significant differences between subgroups of WAI and socio-demographic characteristics, disease duration or degree of skin and lung involvement. However, patients with good WAI expressed milder perceived symptoms (pain, fatigue and impaired hand function; P < 0.001). Patients with better WAI had better competence (P < 0.001), better possibility of adaptations at work (P < 0.01) and impact at work (P < 0.01) than those with poorer WAI. In SSc, pain, fatigue and impaired hand function have a dominant impact on the WAI. Employment interventions should include support in job adaptations as well as self-management strategies to help patients deal with pain and fatigue and to enhance the confidence to perform their work.

Dose-response association between leisure time physical activity and work ability: Cross-sectional study among 3000 workers.

PubMed

Calatayud, Joaquin; Jakobsen, Markus D; Sundstrup, Emil; Casaña, Jose; Andersen, Lars L

2015-12-01

Regular physical activity is important for longevity and health, but knowledge about the optimal dose of physical activity for maintaining good work ability is unknown. This study investigates the association between intensity and duration of physical activity during leisure time and work ability in relation to physical demands of the job. From the 2010 round of the Danish Work Environment Cohort Study, currently employed wage earners with physically demanding work (n = 2952) replied to questions about work, lifestyle and health. Excellent (100 points), very good (75 points), good (50 points), fair (25 points) and poor (0 points) work ability in relation to the physical demands of the job was experienced by 18%, 40%, 30%, 10% and 2% of the respondents, respectively. General linear models that controlled for gender, age, physical and psychosocial work factors, lifestyle and chronic disease showed that the duration of high-intensity physical activity during leisure was positively associated with work ability, in a dose-response fashion (p < 0.001). Those performing ⩾ 5 hours of high-intensity physical activity per week had on average 8 points higher work ability than those not performing such activities. The duration of low-intensity leisure-time physical activity was not associated with work ability (p = 0.5668). The duration of high-intensity physical activity during leisure time is associated in a dose-response fashion with work ability, in workers with physically demanding jobs. © 2015 the Nordic Societies of Public Health.

Recent development of risk-prediction models for incident hypertension: An updated systematic review

PubMed Central

Xiao, Lei; Liu, Ya; Wang, Zuoguang; Li, Chuang; Jin, Yongxin; Zhao, Qiong

2017-01-01

Background Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative. Methods Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc. Results From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%. Conclusions The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment. PMID:29084293

Nonstandard Lumbar Region in Predicting Fracture Risk.

PubMed

Alajlouni, Dima; Bliuc, Dana; Tran, Thach; Pocock, Nicholas; Nguyen, Tuan V; Eisman, John A; Center, Jacqueline R

Femoral neck (FN) bone mineral density (BMD) is the most commonly used skeletal site to estimate fracture risk. The role of lumbar spine (LS) BMD in fracture risk prediction is less clear due to osteophytes that spuriously increase LS BMD, particularly at lower levels. The aim of this study was to compare fracture predictive ability of upper L1-L2 BMD with standard L2-L4 BMD and assess whether the addition of either LS site could improve fracture prediction over FN BMD. This study comprised a prospective cohort of 3016 women and men over 60 yr from the Dubbo Osteoporosis Epidemiology Study followed up for occurrence of minimal trauma fractures from 1989 to 2014. Dual-energy X-ray absorptiometry was used to measure BMD at L1-L2, L2-L4, and FN at baseline. Fracture risks were estimated using Cox proportional hazards models separately for each site. Predictive performances were compared using receiver operating characteristic curve analyses. There were 565 women and 179 men with a minimal trauma fracture during a mean of 11 ± 7 yr. L1-L2 BMD T-score was significantly lower than L2-L4 T-score in both genders (p < 0.0001). L1-L2 and L2-L4 BMD models had a similar fracture predictive ability. LS BMD was better than FN BMD in predicting vertebral fracture risk in women [area under the curve 0.73 (95% confidence interval, 0.68-0.79) vs 0.68 (95% confidence interval, 0.62-0.74), but FN was superior for hip fractures prediction in both women and men. The addition of L1-L2 or L2-L4 to FN BMD in women increased overall and vertebral predictive power compared with FN BMD alone by 1% and 4%, respectively (p < 0.05). In an elderly population, L1-L2 is as good as but not better than L2-L4 site in predicting fracture risk. The addition of LS BMD to FN BMD provided a modest additional benefit in overall fracture risk. Further studies in individuals with spinal degenerative disease are needed. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2018-02-01

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

The effect of age, gender, TG/HDL-C ratio and behavioral lifestyles on the metabolic syndrome in the high risk Mediterranean Island population of Malta.

PubMed

Cuschieri, Sarah; Vassallo, Josanne; Calleja, Neville; Pace, Nikolai; Mamo, Julian

2017-11-01

Metabolic syndrome (MetS) is a public health epidemic, typically with female predominance. The aim was to analyse the effect of gender and age on MetS and its components; analyse effects of lifestyle, diabetes mellitus and identify predictors for MetS including TG/HDL ratio, on a national level in a Mediterranean island. Findings will provide evidence-based data for neighboring countries to aid in combat of this epidemic. A cross-sectional survey was conducted in Malta (2014-2016) on a randomized adults population sample. Various components of MetS were measured along with lifestyle habits (smoking, alcohol and physical activity) and family history (cardiovascular and diabetes). Both descriptive and statistical analyses were performed. A total of 80,788 Maltese adults estimated to suffer from MetS. Males were predominantly affected with significant difference from females. All MetS components were found to be significant predictors along with alcohol habits but not smoking. Neither physical inactivity nor family history of cardiovascular disease, showed any predictive ability for MetS even after adjustment. Elevated triglyceride levels exhibited highest predictive effect on MetS. TG/HDL ratio showed predictive ability in the Maltese population. Males were at higher risk for MetS in Malta. A number of predictors were established but not sedentary lifestyle. TG/HDL ratio may provide to be a good indicator for development of MetS. Copyright © 2017 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Decision-support models for empiric antibiotic selection in Gram-negative bloodstream infections.

PubMed

MacFadden, D R; Coburn, B; Shah, N; Robicsek, A; Savage, R; Elligsen, M; Daneman, N

2018-04-25

Early empiric antibiotic therapy in patients can improve clinical outcomes in Gram-negative bacteraemia. However, the widespread prevalence of antibiotic-resistant pathogens compromises our ability to provide adequate therapy while minimizing use of broad antibiotics. We sought to determine whether readily available electronic medical record data could be used to develop predictive models for decision support in Gram-negative bacteraemia. We performed a multi-centre cohort study, in Canada and the USA, of hospitalized patients with Gram-negative bloodstream infection from April 2010 to March 2015. We analysed multivariable models for prediction of antibiotic susceptibility at two empiric windows: Gram-stain-guided and pathogen-guided treatment. Decision-support models for empiric antibiotic selection were developed based on three clinical decision thresholds of acceptable adequate coverage (80%, 90% and 95%). A total of 1832 patients with Gram-negative bacteraemia were evaluated. Multivariable models showed good discrimination across countries and at both Gram-stain-guided (12 models, areas under the curve (AUCs) 0.68-0.89, optimism-corrected AUCs 0.63-0.85) and pathogen-guided (12 models, AUCs 0.75-0.98, optimism-corrected AUCs 0.64-0.95) windows. Compared to antibiogram-guided therapy, decision-support models of antibiotic selection incorporating individual patient characteristics and prior culture results have the potential to increase use of narrower-spectrum antibiotics (in up to 78% of patients) while reducing inadequate therapy. Multivariable models using readily available epidemiologic factors can be used to predict antimicrobial susceptibility in infecting pathogens with reasonable discriminatory ability. Implementation of sequential predictive models for real-time individualized empiric antibiotic decision-making has the potential to both optimize adequate coverage for patients while minimizing overuse of broad-spectrum antibiotics, and therefore requires further prospective evaluation. Readily available epidemiologic risk factors can be used to predict susceptibility of Gram-negative organisms among patients with bacteraemia, using automated decision-making models. Copyright © 2018 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Prediction of ENSO episodes using canonical correlation analysis

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

Barnston, A.G.; Ropelewski, C.F.

Canonical correlation analysis (CCA) is explored as a multivariate linear statistical methodology with which to forecast fluctuations of the El Nino/Southern Oscillation (ENSO) in real time. CCA is capable of identifying critical sequences of predictor patterns that tend to evolve into subsequent pattern that can be used to form a forecast. The CCA model is used to forecast the 3-month mean sea surface temperature (SST) in several regions of the tropical Pacific and Indian oceans for projection times of 0 to 4 seasons beyond the immediately forthcoming season. The predictor variables, representing the climate situation in the four consecutive 3-monthmore » periods ending at the time of the forecast, are (1) quasi-global seasonal mean sea level pressure (SLP) and (2) SST in the predicted regions themselves. Forecast skill is estimated using cross-validation, and persistence is used as the primary skill control measure. Results indicate that a large region in the eastern equatorial Pacific (120[degrees]-170[degrees] W longitude) has the highest overall predictability, with excellent skill realized for winter forecasts made at the end of summer. CCA outperforms persistence in this region under most conditions, and does noticeably better with the SST included as a predictor in addition to the SLP. It is demonstrated that better forecast performance at the longer lead times would be obtained if some significantly earlier (i.e., up to 4 years) predictor data were included, because the ability to predict the lower-frequency ENSO phase changes would increase. The good performance of the current system at shorter lead times appears to be based largely on the ability to predict ENSO evolution for events already in progress. The forecasting of the eastern tropical Pacific SST using CCA is now done routinely on a monthly basis for a O-, 1-, and 2-season lead at the Climate Analysis Center.« less

Simple Scoring System and Artificial Neural Network for Knee Osteoarthritis Risk Prediction: A Cross-Sectional Study

PubMed Central

Yoo, Tae Keun; Kim, Deok Won; Choi, Soo Beom; Oh, Ein; Park, Jee Soo

2016-01-01

Background Knee osteoarthritis (OA) is the most common joint disease of adults worldwide. Since the treatments for advanced radiographic knee OA are limited, clinicians face a significant challenge of identifying patients who are at high risk of OA in a timely and appropriate way. Therefore, we developed a simple self-assessment scoring system and an improved artificial neural network (ANN) model for knee OA. Methods The Fifth Korea National Health and Nutrition Examination Surveys (KNHANES V-1) data were used to develop a scoring system and ANN for radiographic knee OA. A logistic regression analysis was used to determine the predictors of the scoring system. The ANN was constructed using 1777 participants and validated internally on 888 participants in the KNHANES V-1. The predictors of the scoring system were selected as the inputs of the ANN. External validation was performed using 4731 participants in the Osteoarthritis Initiative (OAI). Area under the curve (AUC) of the receiver operating characteristic was calculated to compare the prediction models. Results The scoring system and ANN were built using the independent predictors including sex, age, body mass index, educational status, hypertension, moderate physical activity, and knee pain. In the internal validation, both scoring system and ANN predicted radiographic knee OA (AUC 0.73 versus 0.81, p<0.001) and symptomatic knee OA (AUC 0.88 versus 0.94, p<0.001) with good discriminative ability. In the external validation, both scoring system and ANN showed lower discriminative ability in predicting radiographic knee OA (AUC 0.62 versus 0.67, p<0.001) and symptomatic knee OA (AUC 0.70 versus 0.76, p<0.001). Conclusions The self-assessment scoring system may be useful for identifying the adults at high risk for knee OA. The performance of the scoring system is improved significantly by the ANN. We provided an ANN calculator to simply predict the knee OA risk. PMID:26859664

Validation of an approach to predict total-tract fiber digestibility using a standardized in vitro technique for different diets fed to high-producing dairy cows.

PubMed

Lopes, F; Ruh, K; Combs, D K

2015-04-01

The experimental objective was to validate an in vitro model to predict total-tract neutral detergent fiber (NDF) digestibility in dairy cattle. Twenty-one diets from 7 studies conducted at University of Wisconsin-Madison were analyzed for in vitro fiber digestibility. Forages varied among diets (corn, alfalfa, tall and meadow fescue, and wheat straw silages) and nutrient composition (ranges: NDF = 22.5 to 33.8%; crude protein = 15.8 to 18.9%; nonfiber carbohydrates = 38.0 to 51.0%). Total-tract NDF digestibility (TTNDFD) observed in in vivo trials was determined using different markers as described in the individual studies. The in vitro TTNDFD model predicted total-tract fiber digestibility from the proportion of total NDF potentially digestible (pdNDF), rate of pdNDF degradation, and rate of passage of pdNDF. The model predicted TTNDFD similar to in vivo measurements. The relationship between TTNDFD measured in vivo and TTNDFD predicted by the in vitro assay was significant (R(2) = 0.68). The relationship between in vitro 30-h NDF digestibility values and in vivo total-tract NDF digestibility values was not significant, whereas in vitro 48-h NDF digestibility values were correlated (R(2) = 0.30) with in vivo TTNDFD measurements. Indigestible NDF (iNDF) showed a negative relationship (R(2) = 0.40) with TTNDFD in vivo. Each 1-percentage-unit increase of iNDF resulted in a decrease of 0.96 percentage units of total-tract NDF digestibility; however, iNDF by itself was not a good predictor of TTNDFD because of the difference among the means. This study showed that an in vitro TTNDFD model that uses iNDF, pdNDF, and rates of pdNDF digestion and passage can predict (R(2) = 0.68) total-tract NDF digestibility. Most importantly, we demonstrated the ability to predict total-tract fiber digestibility from a model based on in vitro NDF degradation, which could improve our ability to optimize forage utilization and milk production. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Exploring the motivation jungle: predicting performance on a novel task by investigating constructs from different motivation perspectives in tandem.

PubMed

Van Nuland, Hanneke J C; Dusseldorp, Elise; Martens, Rob L; Boekaerts, Monique

2010-08-01

Different theoretical viewpoints on motivation make it hard to decide which model has the best potential to provide valid predictions on classroom performance. This study was designed to explore motivation constructs derived from different motivation perspectives that predict performance on a novel task best. Motivation constructs from self-determination theory, self-regulation theory, and achievement goal theory were investigated in tandem. Performance was measured by systematicity (i.e. how systematically students worked on a problem-solving task) and test score (i.e. score on a multiple-choice test). Hierarchical regression analyses on data from 259 secondary school students showed a quadratic relation between a performance avoidance orientation and both performance outcomes, indicating that extreme high and low performance avoidance resulted in the lowest performance. Furthermore, two three-way interaction effects were found. Intrinsic motivation seemed to play a key role in test score and systematicity performance, provided that effort regulation and metacognitive skills were both high. Results indicate that intrinsic motivation in itself is not enough to attain a good performance. Instead, a moderate score on performance avoidance, together with the ability to remain motivated and effectively regulate and control task behavior, is needed to attain a good performance. High time management skills also contributed to higher test score and systematicity performance and a low performance approach orientation contributed to higher systematicity performance. We concluded that self-regulatory skills should be trained in order to have intrinsically motivated students perform well on novel tasks in the classroom.

Psychological model of ART adherence behaviors in persons living with HIV/AIDS in Mexico: a structural equation analysis.

PubMed

Sagarduy, José Luis Ybarra; López, Julio Alfonso Piña; Ramírez, Mónica Teresa González; Dávila, Luis Enrique Fierros

2017-09-04

The objective of this study has been to test the ability of variables of a psychological model to predict antiretroviral therapy medication adherence behavior. We have conducted a cross-sectional study among 172 persons living with HIV/AIDS (PLWHA), who completed four self-administered assessments: 1) the Psychological Variables and Adherence Behaviors Questionnaire, 2) the Stress-Related Situation Scale to assess the variable of Personality, 3) The Zung Depression Scale, and 4) the Duke-UNC Functional Social Support Questionnaire. Structural equation modeling was used to construct a model to predict medication adherence behaviors. Out of all the participants, 141 (82%) have been considered 100% adherent to antiretroviral therapy. Structural equation modeling has confirmed the direct effect that personality (decision-making and tolerance of frustration) has on motives to behave, or act accordingly, which was in turn directly related to medication adherence behaviors. In addition, these behaviors have had a direct and significant effect on viral load, as well as an indirect effect on CD4 cell count. The final model demonstrates the congruence between theory and data (x2/df. = 1.480, goodness of fit index = 0.97, adjusted goodness of fit index = 0.94, comparative fit index = 0.98, root mean square error of approximation = 0.05), accounting for 55.7% of the variance. The results of this study support our theoretical model as a conceptual framework for the prediction of medication adherence behaviors in persons living with HIV/AIDS. Implications for designing, implementing, and evaluating intervention programs based on the model are to be discussed.

A nomogram to predict brain metastasis as the first relapse in curatively resected non-small cell lung cancer patients.

PubMed

Won, Young-Woong; Joo, Jungnam; Yun, Tak; Lee, Geon-Kook; Han, Ji-Youn; Kim, Heung Tae; Lee, Jin Soo; Kim, Moon Soo; Lee, Jong Mog; Lee, Hyun-Sung; Zo, Jae Ill; Kim, Sohee

2015-05-01

Development of brain metastasis results in a significant reduction in overall survival. However, there is no an effective tool to predict brain metastasis in non-small cell lung cancer (NSCLC) patients. We conducted this study to develop a feasible nomogram that can predict metastasis to the brain as the first relapse site in patients with curatively resected NSCLC. A retrospective review of NSCLC patients who had received curative surgery at National Cancer Center (Goyang, South Korea) between 2001 and 2008 was performed. We chose metastasis to the brain as the first relapse site after curative surgery as the primary endpoint of the study. A nomogram was modeled using logistic regression. Among 1218 patients, brain metastasis as the first relapse developed in 87 patients (7.14%) during the median follow-up of 43.6 months. Occurrence rates of brain metastasis were higher in patients with adenocarcinoma or those with a high pT and pN stage. Younger age appeared to be associated with brain metastasis, but this result was not statistically significant. The final prediction model included histology, smoking status, pT stage, and the interaction between adenocarcinoma and pN stage. The model showed fairly good discriminatory ability with a C-statistic of 69.3% and 69.8% for predicting brain metastasis within 2 years and 5 years, respectively. Internal validation using 2000 bootstrap samples resulted in C-statistics of 67.0% and 67.4% which still indicated good discriminatory performances. The nomogram presented here provides the individual risk estimate of developing metastasis to the brain as the first relapse site in patients with NSCLC who have undergone curative surgery. Surveillance programs or preventive treatment strategies for brain metastasis could be established based on this nomogram. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Work ability and associated factors of Brazilian technical-administrative workers in education.

PubMed

Godinho, Marluce Rodrigues; Greco, Rosangela Maria; Teixeira, Maria Teresa Bustamante; Teixeira, Liliane Reis; Guerra, Maximiliano Ribeiro; Chaoubah, Alfredo

2016-01-02

Studies about work ability have grown in importance owing to the worldwide aging of active populations. Research has shown that measuring work ability has a predictive value in cases of long-term sickness absence and early retirement. Our goal was to analyze the work ability and associated factors of civil servants from a higher education institution in Brazil. The participants in this cross-sectional study were 600 technical-administrative workers at a public university. Work ability was measured using the work ability index. The participants were as follows: 51.8% male; mean age of 45 years (SD = ±11); married or in a stable union (61.5%); holding a graduate degree (56.7%); having only one job (83.3%), working 40 h a week or less (78.6%); not working evenings (79.8%); and having direct contact with the public (58.3%). The prevalence of reduced work ability was 13.9%. The following factors were found to be associated with reduced work ability: age 50 years old or above (PR = 2.58; 95% CI 1.25-5.09); female (PR = 2.77; 95% CI 1.25-3.60); education up to secondary school (PR = 2.37; 95% CI 1.13-3.59); overall poor self-assessed health (PR = 2.96; 95% CI 1.32-3.93); signs and symptoms of depression (PR = 4.86; 95% CI 2.23-6.55); sedentariness (PR = 3.00; 95% CI 1.38-4.68) and poor social support at work (PR = 4.01; 95% CI 1.66-4.37). Most of the participants showed good work ability, but some subjects had reduced work ability. This study makes a contribution to expanding the discussion about the factors associated with work ability toward proposing actions for maintaining that ability or helping recovery in the case of diminished ability. Such actions can help reduce work absenteeism and early retirement, both of which have a social and economic impact in Brazil. Studying the determinants of work ability and recommendations to address those determinants will help efforts to improve the quality of life of individuals, both at work and personally, and promote healthy aging.

[Keeping company in an emotional trip. Emotional intelligence applied to the help relationship].

PubMed

Conangla Marín, M Mercè

2004-03-01

In order to be a good professional and caretaker, it is essential to work on one's capacity to manage one's own feelings and emotions in an adaptable, intelligent manner. This set of abilities form part of the concept known as Emotional Intelligence. One can only give to another what one is and one knows how to give to oneself. The five ability groups which make up affective or emotional intelligence are: self-knowledge, self-control, self-motivation, empathy and relationship abilities. All are necessary in order to carry out good management of our feelings and emotions.

Inhibition and Updating, but Not Switching, Predict Developmental Dyslexia and Individual Variation in Reading Ability

PubMed Central

Doyle, Caoilainn; Smeaton, Alan F.; Roche, Richard A. P.; Boran, Lorraine

2018-01-01

To elucidate the core executive function profile (strengths and weaknesses in inhibition, updating, and switching) associated with dyslexia, this study explored executive function in 27 children with dyslexia and 29 age matched controls using sensitive z-mean measures of each ability and controlled for individual differences in processing speed. This study found that developmental dyslexia is associated with inhibition and updating, but not switching impairments, at the error z-mean composite level, whilst controlling for processing speed. Inhibition and updating (but not switching) error composites predicted both dyslexia likelihood and reading ability across the full range of variation from typical to atypical. The predictive relationships were such that those with poorer performance on inhibition and updating measures were significantly more likely to have a diagnosis of developmental dyslexia and also demonstrate poorer reading ability. These findings suggest that inhibition and updating abilities are associated with developmental dyslexia and predict reading ability. Future studies should explore executive function training as an intervention for children with dyslexia as core executive functions appear to be modifiable with training and may transfer to improved reading ability. PMID:29892245

Do Teachers' Perceptions of Children's Math and Reading Related Ability and Effort Predict Children's Self-Concept of Ability in Math and Reading?

ERIC Educational Resources Information Center

Upadyaya, Katja; Eccles, Jacquelynne

2015-01-01

This study investigated to what extent primary school teachers' perceptions of their students' ability and effort predict developmental changes in children's self-concepts of ability in math and reading after controlling for students' academic performance and general intelligence. Three cohorts (N?=?849) of elementary school children and their…

Loewenstein communication scale for the minimally responsive patient.

PubMed

Borer-Alafi, Nurit; Gil, Mali; Sazbon, Leon; Korn, Cecilia

2002-07-01

Any sign of communicative ability in patients in vegetative state can provide information about regain of consciousness and conservation of cognitive abilities. The aim of this study was to test the reliability and validity of an instrument designed to measure the degree of communication in minimally responsive patients. The Loewenstein Communication Scale (LCS) measures five hierarchical functions - mobility, respiration, visual responsiveness, auditory comprehension and linguistic skills (verbal or alternative) - which are divided into five parameters and rated in developmental order on a 5-point scale by level of difficulty. Scores for each function are summed to obtain a quantitative communication profile. Forty-two adult patients in vegetative state, as a result of acquired brain injury, were examined with the proposed LCS for the minimally responsive patients by two speech and language clinicians at admission to the Intensive Care Unit (ICU) for brain injured patients and, thereafter, at least once weekly. At the end of the ICU stay, 27 patients who showed signs of recovery and were referred for continued rehabilitation were compared to a group of 15 patients who were not referred for continued rehabilitation, for functional and general LCS scores. The predictive power of the LCS in differentiating between these groups was tested. The LCS was found to have very good reliability with good inter-rater agreement. Patients who eventually continued rehabilitation had significantly higher total scores as well as in the motor, visual and auditory sub-scales. Logistic regression results indicated that these parameters successfully differentiated between the two groups of patients, even after adjusting for age and for scores on the Glasgow Coma Scale. The LCS for the minimally responsive patients proved to be reliable and predictive of rehabilitation progress of minimally responsive patients. It may be useful for the interdisciplinary rehabilitation team in planning early individually targeted therapeutic programmes. 2002 Taylor & Francis Ltd

Training anesthesiology residents in providing anesthesia for awake craniotomy: learning curves and estimate of needed case load.

PubMed

Bilotta, Federico; Titi, Luca; Lanni, Fabiana; Stazi, Elisabetta; Rosa, Giovanni

2013-08-01

To measure the learning curves of residents in anesthesiology in providing anesthesia for awake craniotomy, and to estimate the case load needed to achieve a "good-excellent" level of competence. Prospective study. Operating room of a university hospital. 7 volunteer residents in anesthesiology. Residents underwent a dedicated training program of clinical characteristics of anesthesia for awake craniotomy. The program was divided into three tasks: local anesthesia, sedation-analgesia, and intraoperative hemodynamic management. The learning curve for each resident for each task was recorded over 10 procedures. Quantitative assessment of the individual's ability was based on the resident's self-assessment score and the attending anesthesiologist's judgment, and rated by modified 12 mm Likert scale, reported ability score visual analog scale (VAS). This ability VAS score ranged from 1 to 12 (ie, very poor, mild, moderate, sufficient, good, excellent). The number of requests for advice also was recorded (ie, resident requests for practical help and theoretical notions to accomplish the procedures). Each task had a specific learning rate; the number of procedures necessary to achieve "good-excellent" ability with confidence, as determined by the recorded results, were 10 procedures for local anesthesia, 15 to 25 procedures for sedation-analgesia, and 20 to 30 procedures for intraoperative hemodynamic management. Awake craniotomy is an approach used increasingly in neuroanesthesia. A dedicated training program based on learning specific tasks and building confidence with essential features provides "good-excellent" ability. © 2013 Elsevier Inc. All rights reserved.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

USGS Publications Warehouse

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

Leg pain and psychological variables predict outcome 2-3 years after lumbar fusion surgery.

PubMed

Abbott, Allan D; Tyni-Lenné, Raija; Hedlund, Rune

2011-10-01

Prediction studies testing a thorough range of psychological variables in addition to demographic, work-related and clinical variables are lacking in lumbar fusion surgery research. This prospective cohort study aimed at examining predictions of functional disability, back pain and health-related quality of life (HRQOL) 2-3 years after lumbar fusion by regressing nonlinear relations in a multivariate predictive model of pre-surgical variables. Before and 2-3 years after lumbar fusion surgery, patients completed measures investigating demographics, work-related variables, clinical variables, functional self-efficacy, outcome expectancy, fear of movement/(re)injury, mental health and pain coping. Categorical regression with optimal scaling transformation, elastic net regularization and bootstrapping were used to investigate predictor variables and address predictive model validity. The most parsimonious and stable subset of pre-surgical predictor variables explained 41.6, 36.0 and 25.6% of the variance in functional disability, back pain intensity and HRQOL 2-3 years after lumbar fusion. Pre-surgical control over pain significantly predicted functional disability and HRQOL. Pre-surgical catastrophizing and leg pain intensity significantly predicted functional disability and back pain while the pre-surgical straight leg raise significantly predicted back pain. Post-operative psychomotor therapy also significantly predicted functional disability while pre-surgical outcome expectations significantly predicted HRQOL. For the median dichotomised classification of functional disability, back pain intensity and HRQOL levels 2-3 years post-surgery, the discriminative ability of the prediction models was of good quality. The results demonstrate the importance of pre-surgical psychological factors, leg pain intensity, straight leg raise and post-operative psychomotor therapy in the predictions of functional disability, back pain and HRQOL-related outcomes.

Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery

NASA Technical Reports Server (NTRS)

Xie, Hua; Klimesh, Matthew A.

2009-01-01

This work extends the lossless data compression technique described in Fast Lossless Compression of Multispectral- Image Data, (NPO-42517) NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26. The original technique was extended to include a near-lossless compression option, allowing substantially smaller compressed file sizes when a small amount of distortion can be tolerated. Near-lossless compression is obtained by including a quantization step prior to encoding of prediction residuals. The original technique uses lossless predictive compression and is designed for use on multispectral imagery. A lossless predictive data compression algorithm compresses a digitized signal one sample at a time as follows: First, a sample value is predicted from previously encoded samples. The difference between the actual sample value and the prediction is called the prediction residual. The prediction residual is encoded into the compressed file. The decompressor can form the same predicted sample and can decode the prediction residual from the compressed file, and so can reconstruct the original sample. A lossless predictive compression algorithm can generally be converted to a near-lossless compression algorithm by quantizing the prediction residuals prior to encoding them. In this case, since the reconstructed sample values will not be identical to the original sample values, the encoder must determine the values that will be reconstructed and use these values for predicting later sample values. The technique described here uses this method, starting with the original technique, to allow near-lossless compression. The extension to allow near-lossless compression adds the ability to achieve much more compression when small amounts of distortion are tolerable, while retaining the low complexity and good overall compression effectiveness of the original algorithm.

Individual personality differences in goats predict their performance in visual learning and non-associative cognitive tasks.

PubMed

Nawroth, Christian; Prentice, Pamela M; McElligott, Alan G

2017-01-01

Variation in common personality traits, such as boldness or exploration, is often associated with risk-reward trade-offs and behavioural flexibility. To date, only a few studies have examined the effects of consistent behavioural traits on both learning and cognition. We investigated whether certain personality traits ('exploration' and 'sociability') of individuals were related to cognitive performance, learning flexibility and learning style in a social ungulate species, the goat (Capra hircus). We also investigated whether a preference for feature cues rather than impaired learning abilities can explain performance variation in a visual discrimination task. We found that personality scores were consistent across time and context. Less explorative goats performed better in a non-associative cognitive task, in which subjects had to follow the trajectory of a hidden object (i.e. testing their ability for object permanence). We also found that less sociable subjects performed better compared to more sociable goats in a visual discrimination task. Good visual learning performance was associated with a preference for feature cues, indicating personality-dependent learning strategies in goats. Our results suggest that personality traits predict the outcome in visual discrimination and non-associative cognitive tasks in goats and that impaired performance in a visual discrimination tasks does not necessarily imply impaired learning capacities, but rather can be explained by a varying preference for feature cues. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and validation of a predictive score for perioperative transfusion in patients with hepatocellular carcinoma undergoing liver resection.

PubMed

Wang, Hai-Qing; Yang, Jian; Yang, Jia-Yin; Wang, Wen-Tao; Yan, Lu-Nan

2015-08-01

Liver resection is a major surgery requiring perioperative blood transfusion. Predicting the need for blood transfusion for patients undergoing liver resection is of great importance. The present study aimed to develop and validate a model for predicting transfusion requirement in HBV-related hepatocellular carcinoma patients undergoing liver resection. A total of 1543 consecutive liver resections were included in the study. Randomly selected sample set of 1080 cases (70% of the study cohort) were used to develop a predictive score for transfusion requirement and the remaining 30% (n=463) was used to validate the score. Based on the preoperative and predictable intraoperative parameters, logistic regression was used to identify risk factors and to create an integer score for the prediction of transfusion requirement. Extrahepatic procedure, major liver resection, hemoglobin level and platelets count were identified as independent predictors for transfusion requirement by logistic regression analysis. A score system integrating these 4 factors was stratified into three groups which could predict the risk of transfusion, with a rate of 11.4%, 24.7% and 57.4% for low, moderate and high risk, respectively. The prediction model appeared accurate with good discriminatory abilities, generating an area under the receiver operating characteristic curve of 0.736 in the development set and 0.709 in the validation set. We have developed and validated an integer-based risk score to predict perioperative transfusion for patients undergoing liver resection in a high-volume surgical center. This score allows identifying patients at a high risk and may alter transfusion practices.

Thermo-hydroforming of a fiber-reinforced thermoplastic composites considering fiber orientations

NASA Astrophysics Data System (ADS)

Ahn, Hyunchul; Kuuttila, Nicholas Eric; Pourboghrat, Farhang

2018-05-01

The Thermoplastic woven composites were formed using a composite thermal hydroforming process, utilizing heated and pressurized fluid, similar to sheet metal forming. This study focuses on the modification of 300-ton pressure formation and predicts its behavior. Spectra Shield SR-3136 is used in this study and material properties are measured by experiments. The behavior of fiber-reinforced thermoplastic polymer composites (FRTP) was modeled using the Preferred Fiber Orientation (PFO) model and validated by comparing numerical analysis with experimental results. The thermo-hydroforming process has shown good results in the ability to form deep drawn parts with reduced wrinkles. Numerical analysis was performed using the PFO model and implemented as commercial finite element software ABAQUS / Explicit. The user subroutine (VUMAT) was used for the material properties of the thermoplastic composite layer. This model is suitable for working with multiple layers of composite laminates. Model parameters have been updated to work with cohesive zone model to calculate the interfacial properties between each composite layer. The results of the numerical modeling showed a good correlation with the molding experiment on the forming shape. Numerical results were also compared with experimental results on punch force-displacement curves for deformed geometry and forming processes of the composite layer. Overall, the shape of the deformed FRTP, including the distribution of wrinkles, was accurately predicted as shown in this study.

Effect of water activity and temperature on the growth of Eurotium species isolated from animal feeds.

PubMed

Greco, Mariana; Pardo, Alejandro; Pose, Graciela; Patriarca, Andrea

Xerophilic fungi represent a serious problem due to their ability to grow at low water activities causing the spoiling of low and intermediate moisture foods, stored goods and animal feeds, with the consequent economic losses. The combined effect of water activity and temperature of four Eurotium species isolated from animal feeds was investigated. Eurotium amstelodami, Eurotium chevalieri, Eurotium repens and Eurotium rubrum were grown at 5, 15, 25, 37 and 45°C on malt extract agar adjusted with glycerol in the range 0.710-0.993 of water activities. The cardinal model proposed by Rosso and Robinson (2001) was applied to fit growth data, with the variable water activity at fixed temperatures, obtaining three cardinal water activities (a wmin , a wmax , a wopt ) and the specific growth rate at the optimum a w (μ opt ). A probabilistic model was also applied to define the interface between growth and no-growth. The cardinal model provided an adequate estimation of the optimal a w to grow and the maximum growth rate. The probabilistic model showed a good performance to fit growth/no-growth cases in the predicted range. The results presented here could be applied to predict Eurotium species growth in animal feeds. Copyright © 2017 Asociación Española de Micología. Publicado por Elsevier España, S.L.U. All rights reserved.

Synthesis, crystal structure determination, biological screening and docking studies of N1-substituted derivatives of 2,3-dihydroquinazolin-4(1H)-one as inhibitors of cholinesterases.

PubMed

Sultana, Nargis; Sarfraz, Muhammad; Tanoli, Saba Tahir; Akram, Muhammad Safwan; Sadiq, Abdul; Rashid, Umer; Tariq, Muhammad Ilyas

2017-06-01

Pursuing the strategy of developing potent AChE inhibitors, we attempted to carry out the N 1 -substitution of 2,3-dihydroquinazolin-4(1H)-one core. A set of 32 N-alkylated/benzylated quinazoline derivatives were synthesized, characterized and evaluated for their inhibition against cholinesterases. N-alkylation of the series of the compounds reported previously (N-unsubstituted) resulted in improved activity. All the compounds showed inhibition of both enzymes in the micromolar to submicromolar range. Structure activity relationship (SAR) of the 32 derivatives showed that N-benzylated compounds possess good activity than N-alkylated compounds. N-benzylated compounds 2ad and 2af were found very active with their IC 50 values toward AChE in submicromolar range (0.8µM and 0.6µM respectively). Binding modes of the synthesized compounds were explored by using GOLD (Genetic Optimization for Ligand Docking) suit v5.4.1. Computational predictions of ADMET studies reveal that all the compounds have good pharmacokinetic properties with no AMES toxicity and carcinogenicity. Moreover, all the compounds are predicted to be absorbed in human intestine and also have the ability to cross blood brain barrier. Overall, the synthesized compounds have established a structural foundation for the design of new inhibitors of cholinesterase. Copyright © 2017 Elsevier Inc. All rights reserved.

Simultaneous Determination of Metamizole, Thiamin and Pyridoxin Using UV-Spectroscopy in Combination with Multivariate Calibration

PubMed Central

Chotimah, Chusnul; Sudjadi; Riyanto, Sugeng; Rohman, Abdul

2015-01-01

Purpose: Analysis of drugs in multicomponent system officially is carried out using chromatographic technique, however, this technique is too laborious and involving sophisticated instrument. Therefore, UV-VIS spectrophotometry coupled with multivariate calibration of partial least square (PLS) for quantitative analysis of metamizole, thiamin and pyridoxin is developed in the presence of cyanocobalamine without any separation step. Methods: The calibration and validation samples are prepared. The calibration model is prepared by developing a series of sample mixture consisting these drugs in certain proportion. Cross validation of calibration sample using leave one out technique is used to identify the smaller set of components that provide the greatest predictive ability. The evaluation of calibration model was based on the coefficient of determination (R2) and root mean square error of calibration (RMSEC). Results: The results showed that the coefficient of determination (R2) for the relationship between actual values and predicted values for all studied drugs was higher than 0.99 indicating good accuracy. The RMSEC values obtained were relatively low, indicating good precision. The accuracy and presision results of developed method showed no significant difference compared to those obtained by official method of HPLC. Conclusion: The developed method (UV-VIS spectrophotometry in combination with PLS) was succesfully used for analysis of metamizole, thiamin and pyridoxin in tablet dosage form. PMID:26819934

Academic performance, career potential, creativity, and job performance: can one construct predict them all?

PubMed

Kuncel, Nathan R; Hezlett, Sarah A; Ones, Deniz S

2004-01-01

This meta-analysis addresses the question of whether 1 general cognitive ability measure developed for predicting academic performance is valid for predicting performance in both educational and work domains. The validity of the Miller Analogies Test (MAT; W. S. Miller, 1960) for predicting 18 academic and work-related criteria was examined. MAT correlations with other cognitive tests (e.g., Raven's Matrices [J. C. Raven, 1965]; Graduate Record Examinations) also were meta-analyzed. The results indicate that the abilities measured by the MAT are shared with other cognitive ability instruments and that these abilities are generalizably valid predictors of academic and vocational criteria, as well as evaluations of career potential and creativity. These findings contradict the notion that intelligence at work is wholly different from intelligence at school, extending the voluminous literature that supports the broad importance of general cognitive ability (g).

Decoding the future from past experience: learning shapes predictions in early visual cortex.

PubMed

Luft, Caroline D B; Meeson, Alan; Welchman, Andrew E; Kourtzi, Zoe

2015-05-01

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex. Copyright © 2015 the American Physiological Society.

Kindergarten predictors of second versus eighth grade reading comprehension impairments.

PubMed

Adlof, Suzanne M; Catts, Hugh W; Lee, Jaehoon

2010-01-01

Multiple studies have shown that kindergarten measures of phonological awareness and alphabet knowledge are good predictors of reading achievement in the primary grades. However, less attention has been given to the early predictors of later reading achievement. This study used a modified best-subsets variable-selection technique to examine kindergarten predictors of early versus later reading comprehension impairments. Participants included 433 children involved in a longitudinal study of language and reading development. The kindergarten test battery assessed various language skills in addition to phonological awareness, alphabet knowledge, naming speed, and nonverbal cognitive ability. Reading comprehension was assessed in second and eighth grades. Results indicated that different combinations of variables were required to optimally predict second versus eighth grade reading impairments. Although some variables effectively predicted reading impairments in both grades, their relative contributions shifted over time. These results are discussed in light of the changing nature of reading comprehension over time. Further research will help to improve the early identification of later reading disabilities.

A conceptual review on action-perception coupling in the musicians’ brain: what is it good for?

PubMed Central

Novembre, Giacomo; Keller, Peter E.

2014-01-01

Experience with a sensorimotor task, such as practicing a piano piece, leads to strong coupling of sensory (visual or auditory) and motor cortices. Here we review behavioral and neurophysiological (M/EEG, TMS and fMRI) research exploring this topic using the brain of musicians as a model system. Our review focuses on a recent body of evidence suggesting that this form of coupling might have (at least) two cognitive functions. First, it leads to the generation of equivalent predictions (concerning both when and what event is more likely to occur) during both perception and production of music. Second, it underpins the common coding of perception and action that supports the integration of the motor output of multiple musicians’ in the context of joint musical tasks. Essentially, training-based coupling of perception and action might scaffold the human ability to represent complex (structured) actions and to entrain multiple agents—via reciprocal prediction and adaptation—in the pursuit of shared goals. PMID:25191246

PREDICE score as a predictor of 90 days mortality in patients with heart failure

NASA Astrophysics Data System (ADS)

Purba, D. P. S.; Hasan, R.

2018-03-01

Hospitalization in chronic heart failure patients associated with high mortality and morbidity rate. The 90 days post-discharge period following hospitalization in heart failure patients is known as the vulnerable phase, it carries the high risk of poor outcomes. Identification of high-risk individuals by using prognostic evaluation was intended to do a closer follow up and more intensive to decreasing the morbidity and mortality rate of heart failure.To determine whether PREDICE score could predict mortality within 90 days in patients with heart failure, an observational cohort study in patients with heart failure who were hospitalized due to worsening chronic heart failure. Patients were in following-up for up to 90 days after initial evaluation with the primary endpoint is death.We found a difference of the significantstatistical between PREDICE score in survival and mortality group (p=0.001) of 84% (95% CI: 60.9% - 97.4%).In conclusion, PREDICE score has a good ability to predict mortality within 90 days in patients with heart failure.

Automated electronic tongue based on potentiometric sensors for the determination of a trinary anionic surfactant mixture.

PubMed

Cortina, Montserrat; Ecker, Christina; Calvo, Daniel; del Valle, Manuel

2008-01-22

An automated electronic tongue consisting of an array of potentiometric sensors and an artificial neural network (ANN) has been developed to resolve mixtures of anionic surfactants. The sensor array was formed by five different flow-through sensors for anionic surfactants, based on poly(vinyl chloride) membranes having cross-sensitivity features. Feedforward multilayer neural networks were used to predict surfactant concentrations. As a great amount of information is required for the correct modelling of the sensors response, a sequential injection analysis (SIA) system was used to automatically provide it. Dodecylsulfate (DS(-)), dodecylbenzenesulfonate (DBS(-)) and alpha-alkene sulfonate (ALF(-)) formed the three-analyte study case resolved in this work. Their concentrations varied from 0.2 to 4mM for ALF(-) and DBS(-) and from 0.2 to 5mM for DS(-). Good prediction ability was obtained with correlation coefficients better than 0.933 when the obtained values were compared with those expected for a set of 16 external test samples not used for training.

Dynamic Modeling, Controls, and Testing for Electrified Aircraft

NASA Technical Reports Server (NTRS)

Connolly, Joseph; Stalcup, Erik

2017-01-01

Electrified aircraft have the potential to provide significant benefits for efficiency and emissions reductions. To assess these potential benefits, modeling tools are needed to provide rapid evaluation of diverse concepts and to ensure safe operability and peak performance over the mission. The modeling challenge for these vehicles is the ability to show significant benefits over the current highly refined aircraft systems. The STARC-ABL (single-aisle turbo-electric aircraft with an aft boundary layer propulsor) is a new test proposal that builds upon previous N3-X team hybrid designs. This presentation describes the STARC-ABL concept, the NASA Electric Aircraft Testbed (NEAT) which will allow testing of the STARC-ABL powertrain, and the related modeling and simulation efforts to date. Modeling and simulation includes a turbofan simulation, Numeric Propulsion System Simulation (NPSS), which has been integrated with NEAT; and a power systems and control model for predicting testbed performance and evaluating control schemes. Model predictions provide good comparisons with testbed data for an NPSS-integrated test of the single-string configuration of NEAT.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Application of Fluorescence Spectrometry With Multivariate Calibration to the Enantiomeric Recognition of Fluoxetine in Pharmaceutical Preparations.

PubMed

Poláček, Roman; Májek, Pavel; Hroboňová, Katarína; Sádecká, Jana

2016-04-01

Fluoxetine is the most prescribed antidepressant chiral drug worldwide. Its enantiomers have a different duration of serotonin inhibition. A novel simple and rapid method for determination of the enantiomeric composition of fluoxetine in pharmaceutical pills is presented. Specifically, emission, excitation, and synchronous fluorescence techniques were employed to obtain the spectral data, which with multivariate calibration methods, namely, principal component regression (PCR) and partial least square (PLS), were investigated. The chiral recognition of fluoxetine enantiomers in the presence of β-cyclodextrin was based on diastereomeric complexes. The results of the multivariate calibration modeling indicated good prediction abilities. The obtained results for tablets were compared with those from chiral HPLC and no significant differences are shown by Fisher's (F) test and Student's t-test. The smallest residuals between reference or nominal values and predicted values were achieved by multivariate calibration of synchronous fluorescence spectral data. This conclusion is supported by calculated values of the figure of merit.

CH stretching overtone spectra of trimethyl amine and dimethyl sulfide

NASA Astrophysics Data System (ADS)

Billinghurst, Brant E.; Gough, Kathleen M.; Low, Geoffrey R.; Kjaergaard, Henrik G.

2004-01-01

Trimethyl amine (TMA) exhibits the largest known difference in CH bond lengths within a methyl group, due to what is known as the lone pair trans effect. Dimethyl sulfide also exhibits this effect, but to a far lesser extent, making it ideal for comparison to TMA. In this paper, the first through fourth overtone spectra of N(CH3)3, N(CD3)3, N(CD2H)(CD3)2, N(CH3)(CD3)2, N(CD3)(CH3)2 and S(CH3)2 are reported and all major bands are assigned. The intensities of the observed bands are compared to intensities predicted by the harmonically coupled anharmonic oscillator local mode model. Good correlation is found between the experimental intensities and those predicted with the local mode model and HF/6-311++G(2d,2p) calculated dipole moment functions. An increase in the ability to resolve peaks as methyl groups are deuterated suggests that the lone pair mediates increased coupling between methyl groups.

The analysis of mathematics literacy on PMRI learning with media schoology of junior high school students

NASA Astrophysics Data System (ADS)

Wardono; Mariani, S.

2018-03-01

Indonesia as a developing country in the future will have high competitiveness if its students have high mathematics literacy ability. The current reality from year to year rankings of PISA mathematics literacy Indonesian students are still not good. This research is motivated by the importance and low ability of the mathematics literacy. The purpose of this study is to: (1) analyze the effectiveness of PMRI learning with media Schoology, (2) describe the ability of students' mathematics literacy on PMRI learning with media Schoology which is reviewed based on seven components of mathematics literacy, namely communication, mathematizing, representation, reasoning, devising strategies, using symbols, and using mathematics tool. The method used in this research is the method of sequential design method mix. Techniques of data collection using observation, interviews, tests, and documentation. Data analysis techniques use proportion test, appellate test, and use descriptive analysis. Based on the data analysis, it can be concluded; (1) PMRI learning with media Schoology effectively improve the ability of mathematics literacy because of the achievement of classical completeness, students' mathematics literacy ability in PMRI learning with media Schoology is higher than expository learning, and there is increasing ability of mathematics literacy in PMRI learning with media Schoology of 30%. (2) Highly capable students attain excellent mathematics literacy skills, can work using broad thinking with appropriate resolution strategies. Students who are capable of achieving good mathematics literacy skills can summarize information, present problem-solving processes, and interpret solutions. low-ability students have reached the level of ability of mathematics literacy good enough that can solve the problem in a simple way.

Tailoring of TiO2 films by H2SO4 treatment and UV irradiation to improve anticoagulant ability and endothelial cell compatibility.

PubMed

Liao, Yuzhen; Li, Linhua; Chen, Jiang; Yang, Ping; Zhao, Ansha; Sun, Hong; Huang, Nan

2017-07-01

Surfaces with dual functions that simultaneously exhibit good anticoagulant ability and endothelial cell (EC) compatibility are desirable for blood contact materials. However, these dual functions have rarely been achieved by inorganic materials. In this study, titanium dioxide (TiO 2 ) films were treated by sulphuric acid (H 2 SO 4 ) and ultraviolet (UV) irradiation successively (TiO 2 H 2 SO 4 -UV), resulting in good anticoagulant ability and EC compatibility simultaneously. We found that UV irradiation improved the anticoagulant ability of TiO 2 films significantly while enhancing EC compatibility, though not significantly. The enhanced anticoagulant ability could be related to the oxidation of surface-adsorbed hydrocarbons and increased hydrophilicity. The H 2 SO 4 treatment improved the anticoagulant ability of TiO 2 films slightly, while UV irradiation improved the anticoagulant ability strongly. The enhanced EC compatibility could be related to the increased surface roughness and positive charges on the surface of the TiO 2 films. Furthermore, the time-dependent degradation of the enhanced EC compatibility and anticoagulant ability of TiO 2 H 2 SO 4 -UV was observed. In summary, TiO 2 H 2 SO 4 -UV expressed both excellent anticoagulant ability and good EC compatibility at the same time, which could be desirable for blood contact materials. However, the compatibility of TiO 2 H 2 SO 4 -UV with smooth muscle cells (SMCs) and macrophages was also improved. More effort is still needed to selectively improve EC compatibility on TiO 2 films for better re-endothelialization. Copyright © 2017 Elsevier B.V. All rights reserved.

A Quantitative Model of Expert Transcription Typing

DTIC Science & Technology

1993-03-08

side of pure psychology, several researchers have argued that transcription typing is a particularly good activity for the study of human skilled...phenomenon with a quantitative METT prediction. The first, quick and dirty analysis gives a good prediction of the copy span, in fact, it is even...typing, it should be demonstrated that the mechanism of the model does not get in the way of good predictions. If situations occur where the entire

Predicting absenteeism: screening for work ability or burnout.

PubMed

Schouteten, R

2017-01-01

In determining the predictors of occupational health problems, two factors can be distinguished: personal (work ability) factors and work-related factors (burnout, job characteristics). However, these risk factors are hardly ever combined and it is not clear whether burnout or work ability best predicts absenteeism. To relate measures of work ability, burnout and job characteristics to absenteeism as the indicators of occupational health problems. Survey data on work ability, burnout and job characteristics from a Dutch university were related to the absenteeism data from the university's occupational health and safety database in the year following the survey study. The survey contained the Work Ability Index (WAI), Utrecht Burnout Scale (UBOS) and seven job characteristics from the Questionnaire on Experience and Evaluation of Work (QEEW). There were 242 employees in the study group. Logistic regression analyses revealed that job characteristics did not predict absenteeism. Exceptional absenteeism was most consistently predicted by the WAI dimensions 'employees' own prognosis of work ability in two years from now' and 'mental resources/vitality' and the burnout dimension 'emotional exhaustion'. Other significant predictors of exceptional absenteeism frequency included estimated work impairment due to diseases (WAI) and feelings of depersonalization or emotional distance from the work (burnout). Absenteeism among university personnel was best predicted by a combination of work ability and burnout. As a result, measures to prevent absenteeism and health problems may best be aimed at improving an individual's work ability and/or preventing the occurrence of burnout. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Advantages and limitations of multiple-trait genomic prediction for Fusarium head blight severity in hybrid wheat (Triticum aestivum L.).

PubMed

Schulthess, Albert W; Zhao, Yusheng; Longin, C Friedrich H; Reif, Jochen C

2018-03-01

Predictabilities for wheat hybrids less related to the estimation set were improved by shifting from single- to multiple-trait genomic prediction of Fusarium head blight severity. Breeding for improved Fusarium head blight resistance (FHBr) of wheat is a very laborious and expensive task. FHBr complexity is mainly due to its highly polygenic nature and because FHB severity (FHBs) is greatly influenced by the environment. Associated traits plant height and heading date may provide additional information related to FHBr, but this is ignored in single-trait genomic prediction (STGP). The aim of our study was to explore the benefits in predictabilities of multiple-trait genomic prediction (MTGP) over STGP of target trait FHBs in a population of 1604 wheat hybrids using information on 17,372 single nucleotide polymorphism markers along with indicator traits plant height and heading date. The additive inheritance of FHBs allowed accurate hybrid performance predictions using information on general combining abilities or average performance of both parents without the need of markers. Information on molecular markers and indicator trait(s) improved FHBs predictabilities for hybrids less related to the estimation set. Indicator traits must be observed on the predicted individuals to benefit from MTGP. Magnitudes of genetic and phenotypic correlations along with improvements in predictabilities made plant height a better indicator trait for FHBs than heading date. Thus, MTGP having only plant height as indicator trait already maximized FHBs predictabilities. Provided a good indicator trait was available, MTGP could reduce the impacts of genotype environment [Formula: see text] interaction on STGP for hybrids less related to the estimation set.

Baseline strength can influence the ability of salivary free testosterone to predict squat and sprinting performance.

PubMed

Crewther, Blair T; Cook, Christian J; Gaviglio, Chris M; Kilduff, Liam P; Drawer, Scott

2012-01-01

The objective of this study was to determine if salivary free testosterone can predict an athlete's performance during back squats and sprints over time and the influence baseline strength on this relationship. Ten weight-trained male athletes were divided into 2 groups based on their 1 repetition maximum (1RM) squats, good squatters (1RM > 2.0 × body weight, n = 5) and average squatters (1RM < 1.9 × body weight, n = 5). The good squatters were stronger than the average squatters (p < 0.05). Each subject was assessed for squat 1RM and 10-m sprint times on 10 separate occasions over a 40-day period. A saliva sample was collected before testing and assayed for free testosterone and cortisol. The pooled testosterone correlations were strong and significant in the good squatters (r = 0.92 for squats, r = -0.87 for sprints, p < 0.01), but not significant for the average squatters (r = 0.35 for squats, r = -0.18 for sprints). Cortisol showed no significant correlations with 1RM squat and 10-m sprint performance, and no differences were identified between the 2 squatting groups. In summary, these results suggest that free testosterone is a strong individual predictor of squat and sprinting performance in individuals with relatively high strength levels but a poor predictor in less strong individuals. This information can assist coaches, trainers, and performance scientists working with stronger weight-trained athletes, for example, the preworkout measurement of free testosterone could indicate likely training outcomes or a readiness to train at a certain intensity level, especially if real-time measurements are made. Our results also highlight the need to separate group and individual hormonal data during the repeated testing of athletes with variable strength levels.

Fine-motor skills testing and prediction of endovascular performance.

PubMed

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

2013-12-01

Performing endovascular procedures requires good control of fine-motor digital movements and hand-eye coordination. Objective assessment of such skills is difficult. Trainees acquire control of catheter/wire movements at various paces. However, little is known to what extent talent plays for novice candidates at entry to practice. To study the association between performance in a novel aptitude test of fine-motor skills and performance in simulated procedures. The test was based on manual course-tracking using a proprietary hand-operated roller-bar device coupled to a personal computer with monitor view rotation. A total of 40 test repetitions were conducted separately with each hand. Test scores were correlated with simulator performance. Group A (n = 14), clinicians with various levels of endovascular experience, performed a simulated procedure of contralateral iliac artery stenting. Group B (n = 19), medical students, performed 10 repetitions of crossing a challenging aortic bifurcation in a simulator. The test score differed markedly between the individuals in both groups, in particular with the non-dominant hand. Group A: the test score with the non-dominant hand correlated significantly with simulator performance assessed with the global rating scale SAVE (R = -0.69, P = 0.007). There was no association observed from performances with the dominant hand. Group B: there was no significant association between the test score and endovascular skills acquisition neither with the dominant nor with the non-dominant hand. Clinicians with increasing levels of endovascular technical experience had developed good fine-motor control of the non-dominant hand, in particular, that was associated with good procedural performance in the simulator. The aptitude test did not predict endovascular skills acquisition among medical students, thus, cannot be suggested for selection of novice candidates. Procedural experience and practice probably supplant the influence of innate abilities (talent) over time.

Availability of new drugs and Americans' ability to work.

PubMed

Lichtenberg, Frank R

2005-04-01

The objective of this work was the investigation of the extent to which the introduction of new drugs has increased society's ability to produce goods and services by increasing the number of hours worked per member of the working-age population. Econometric models of ability-to-work measures from data on approximately 200,000 individuals with 47 major chronic conditions observed throughout a 15-year period (1982-1996) were estimated. Under very conservative assumptions, the estimates indicate that the value of the increase in ability to work attributable to new drugs is 2.5 times as great as expenditure on new drugs. The potential of drugs to increase employee productivity should be considered in the design of drug-reimbursement policies. Conversely, policies that broadly reduce the development and utilization of new drugs may ultimately reduce our ability to produce other goods and services.

A perturbative approach to the redshift space correlation function: beyond the Standard Model

NASA Astrophysics Data System (ADS)

Bose, Benjamin; Koyama, Kazuya

2017-08-01

We extend our previous redshift space power spectrum code to the redshift space correlation function. Here we focus on the Gaussian Streaming Model (GSM). Again, the code accommodates a wide range of modified gravity and dark energy models. For the non-linear real space correlation function used in the GSM we use the Fourier transform of the RegPT 1-loop matter power spectrum. We compare predictions of the GSM for a Vainshtein screened and Chameleon screened model as well as GR. These predictions are compared to the Fourier transform of the Taruya, Nishimichi and Saito (TNS) redshift space power spectrum model which is fit to N-body data. We find very good agreement between the Fourier transform of the TNS model and the GSM predictions, with <= 6% deviations in the first two correlation function multipoles for all models for redshift space separations in 50Mpch <= s <= 180Mpc/h. Excellent agreement is found in the differences between the modified gravity and GR multipole predictions for both approaches to the redshift space correlation function, highlighting their matched ability in picking up deviations from GR. We elucidate the timeliness of such non-standard templates at the dawn of stage-IV surveys and discuss necessary preparations and extensions needed for upcoming high quality data.

Analytical and experimental vibration analysis of a faulty gear system

NASA Astrophysics Data System (ADS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-10-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structures. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville Distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Analytical and experimental vibration analysis of a faulty gear system

NASA Astrophysics Data System (ADS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-10-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structure. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

PubMed

Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

2012-06-01

This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

Analytical and Experimental Vibration Analysis of a Faulty Gear System

NASA Technical Reports Server (NTRS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-01-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structure. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

A no-reference bitstream-based perceptual model for video quality estimation of videos affected by coding artifacts and packet losses

NASA Astrophysics Data System (ADS)

Pandremmenou, K.; Shahid, M.; Kondi, L. P.; Lövström, B.

2015-03-01

In this work, we propose a No-Reference (NR) bitstream-based model for predicting the quality of H.264/AVC video sequences, affected by both compression artifacts and transmission impairments. The proposed model is based on a feature extraction procedure, where a large number of features are calculated from the packet-loss impaired bitstream. Many of the features are firstly proposed in this work, and the specific set of the features as a whole is applied for the first time for making NR video quality predictions. All feature observations are taken as input to the Least Absolute Shrinkage and Selection Operator (LASSO) regression method. LASSO indicates the most important features, and using only them, it is possible to estimate the Mean Opinion Score (MOS) with high accuracy. Indicatively, we point out that only 13 features are able to produce a Pearson Correlation Coefficient of 0.92 with the MOS. Interestingly, the performance statistics we computed in order to assess our method for predicting the Structural Similarity Index and the Video Quality Metric are equally good. Thus, the obtained experimental results verified the suitability of the features selected by LASSO as well as the ability of LASSO in making accurate predictions through sparse modeling.

Molecular electronegativity distance vector model for the prediction of bioconcentration factors in fish.

PubMed

Liu, Shu-Shen; Qin, Li-Tang; Liu, Hai-Ling; Yin, Da-Qiang

2008-02-01

Molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was used to describe the structures of 122 nonionic organic compounds (NOCs) and a quantitative relationship between the MEDV descriptors and the bioconcentration factors (BCF) of NOCs in fish was developed using the variable selection and modeling based on prediction (VSMP). It was found that some main structural factors influencing the BCFs of NOCs are the substructures expressed by four atomic types of nos. 2, 3, 5, and 13, i.e., atom groups -CH(2)- or =CH-, -CH< or =C<, -NH(2), and -Cl or -Br where the former two groups exist in the molecular skeleton of NOC and the latter three groups are related closely to the substituting groups on a benzene ring. The best 5-variable model, with the correlation coefficient (r(2)) of 0.9500 and the leave-one-out cross-validation correlation coefficient (q(2)) of 0.9428, was built by multiple linear regressions, which shows a good estimation ability and stability. A predictive power for the external samples was tested by the model from the training set of 80 NOCs and the predictive correlation coefficient (u(2)) for the 42 external samples in the test set was 0.9028.

[Determination and prediction for vapor pressures of organophosphate flame retardants by gas chromatography].

PubMed

Wang, Qingzhi; Zhao, Hongxia; Wang, Yan; Xie, Qing; Chen, Jingwen; Quan, Xie

2017-09-08

Organophosphate flame retardants (OPFRs) are ubiquitous in the environment. To better understand and predict their environmental transport and fate, well-defined physicochemical properties are required. Vapor pressures ( P ) of 14 OPFRs were estimated as a function of temperature ( T ) by gas chromatography (GC), while 1,1,1-trichioro-2,2-bis (4-chlorophenyl) ethane ( p,p '-DDT) was acted as a reference substance. Their log P GC values and internal energies of phase transfer (△ vap H ) ranged from -6.17 to -1.25 and 74.1 kJ/mol to 122 kJ/mol, respectively. Substitution pattern and molar volume ( V M ) were found to be capable of influencing log P GC values of the OPFRs. The halogenated alkyl-OPFRs had lower log P GC values than aryl-or alkyl-OPFRs. The bigger the molar volume was, the smaller the log P GC value was. In addition, a quantitative structure-property relationship (QSPR) model of log P GC versus different relative retention times (RRTs) was developed with a high cross-validated value ( Q 2 cum ) of 0.946, indicating a good predictive ability and stability. Therefore, the log P GC values of the OPFRs without standard substance can be predicted by using their RRTs on different GC columns.

Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis(2008)

NASA Technical Reports Server (NTRS)

Shen, B.-W.; Tao, W.-K.; Lau, W. K.; Atlas, R.

2010-01-01

Very severe cyclonic storm Nargis devastated Burma (Myanmar) in May 2008, caused tremendous damage and numerous fatalities, and became one of the 10 deadliest tropical cyclones (TCs) of all time. To increase the warning time in order to save lives and reduce economic damage, it is important to extend the lead time in the prediction of TCs like Nargis. As recent advances in high-resolution global models and supercomputing technology have shown the potential for improving TC track and intensity forecasts, the ability of a global mesoscale model to predict TC genesis in the Indian Ocean is examined in this study with the aim of improving simulations of TC climate. High-resolution global simulations with real data show that the initial formation and intensity variations of TC Nargis can be realistically predicted up to 5 days in advance. Preliminary analysis suggests that improved representations of the following environmental conditions and their hierarchical multiscale interactions were the key to achieving this lead time: (1) a westerly wind burst and equatorial trough, (2) an enhanced monsoon circulation with a zero wind shear line, (3) good upper-level outflow with anti-cyclonic wind shear between 200 and 850 hPa, and (4) low-level moisture convergence.

Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysis.

PubMed

Handa, Koichi; Nakagome, Izumi; Yamaotsu, Noriyuki; Gouda, Hiroaki; Hirono, Shuichi

2015-01-01

The pregnane X receptor [PXR (NR1I2)] induces the expression of xenobiotic metabolic genes and transporter genes. In this study, we aimed to establish a computational method for quantifying the enzyme-inducing potencies of different compounds via their ability to activate PXR, for the application in drug discovery and development. To achieve this purpose, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR) model using comparative molecular field analysis (CoMFA) for predicting enzyme-inducing potencies, based on computer-ligand docking to multiple PXR protein structures sampled from the trajectory of a molecular dynamics simulation. Molecular mechanics-generalized born/surface area scores representing the ligand-protein-binding free energies were calculated for each ligand. As a result, the predicted enzyme-inducing potencies for compounds generated by the CoMFA model were in good agreement with the experimental values. Finally, we concluded that this 3D-QSAR model has the potential to predict the enzyme-inducing potencies of novel compounds with high precision and therefore has valuable applications in the early stages of the drug discovery process. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Determination and prediction of octanol-air partition coefficients for organophosphate flame retardants.

PubMed

Wang, Qingzhi; Zhao, Hongxia; Wang, Yan; Xie, Qing; Chen, Jingwen; Quan, Xie

2017-11-01

Organophosphate flame retardants (OPFRs) have attracted wide concerns due to their toxicities and ubiquitous occurrence in the environment. In this work, Octanol-air partition coefficient (K OA ) for 14 OPFRs including 4 halogenated alkyl-, 5 aryl- and 5 alkyl-OPFRs, were estimated as a function of temperature using a gas chromatographic retention time (GC-RT) method. Their log K OA-GC values and internal energies of phase transfer (Δ OA U/kJmol -1 ) ranged from 8.03 to 13.0 and from 69.7 to 149, respectively. Substitution pattern and molar volume (V M ) were found to be capable of influencing log K OA-GC values of OPFRs. The halogenated alkyl-OPFRs had higher log K OA-GC values than aryl- or alkyl-OPFRs. The bigger the molar volume was, the greater the log K OA-GC values increased. In addition, a predicted model of log K OA-GC versus different relative retention times (RRTs) was developed with a high cross-validated value (Q 2 (cum) ) of 0.951, indicating a good predictive ability and stability. Therefore, the log K OA-GC values of the remaining OPFRs can be predicted by using their RRTs on different GC columns. Copyright © 2017 Elsevier Inc. All rights reserved.

Auditory and verbal memory predictors of spoken language skills in children with cochlear implants.

PubMed

de Hoog, Brigitte E; Langereis, Margreet C; van Weerdenburg, Marjolijn; Keuning, Jos; Knoors, Harry; Verhoeven, Ludo

2016-10-01

Large variability in individual spoken language outcomes remains a persistent finding in the group of children with cochlear implants (CIs), particularly in their grammatical development. In the present study, we examined the extent of delay in lexical and morphosyntactic spoken language levels of children with CIs as compared to those of a normative sample of age-matched children with normal hearing. Furthermore, the predictive value of auditory and verbal memory factors in the spoken language performance of implanted children was analyzed. Thirty-nine profoundly deaf children with CIs were assessed using a test battery including measures of lexical, grammatical, auditory and verbal memory tests. Furthermore, child-related demographic characteristics were taken into account. The majority of the children with CIs did not reach age-equivalent lexical and morphosyntactic language skills. Multiple linear regression analyses revealed that lexical spoken language performance in children with CIs was best predicted by age at testing, phoneme perception, and auditory word closure. The morphosyntactic language outcomes of the CI group were best predicted by lexicon, auditory word closure, and auditory memory for words. Qualitatively good speech perception skills appear to be crucial for lexical and grammatical development in children with CIs. Furthermore, strongly developed vocabulary skills and verbal memory abilities predict morphosyntactic language skills. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of transplant-specific prognostic scoring systems in haploidentical transplantation for myelodysplastic syndrome.

PubMed

Shin, Seung-Hwan; Jeon, Young-Woo; Yoon, Jae-Ho; Yahng, Seung-Ah; Lee, Sung-Eun; Cho, Byung-Sik; Eom, Ki-Seong; Lee, Seok; Kim, Hee-Je; Min, Chang-Ki; Cho, Seok-Goo; Kim, Dong-Wook; Lee, Jong-Wook; Min, Woo-Sung; Kim, Yoo-Jin

2018-05-14

We intended to identify the predictive abilities of recently published transplant-specific prognostic scoring systems in myelodysplastic syndrome (MDS) patients receiving haploidentical transplantation. The outcomes of 73 MDS patients receiving haploidentical transplantation were analyzed, according to the MTPSS, the TRI, and the CIBMTR scoring systems. The median age of patients at transplantation was 50 (range, 19-69) years. The IPSS-R cytogenetic risks of very good/good, intermediate, and poor/very poor were respectively observed in 35 (48.0%), 25 (34.2%), and 13 (17.8%) patients, including 4 (5.5%) with a monosomal karyotype. Pre-transplant treatment failure and high (≥ 3) HCT-CI were observed in 30 (41.1%) and 35 (48.0%) patients, respectively. With survivor's median follow-up of 42.3 months, the overall survival rate at 4 years of all patients was 65.5% (95% CI, 52.4-75.9). The MTPSS (100%, 77.3%, 62.5%, and 42.0% at 4 years; P = 0.02) and the TRI (100%, 79.9%, 76.0%, and 17.1% at 4 years; P < 0.01) differentiate proportionally overall survival rates according to their 4 risk groups, whereas the CIBMTR scoring system did not (P = 0.17). Our results suggest the potential ability of the MPTSS and the TRI as prognostic tools for MDS patients receiving haploidentical transplantation. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Short-form Mini-Nutritional Assessment with either BMI or calf circumference is effective in rating the nutritional status of elderly Taiwanese -- results of a national cohort study.

PubMed

Tsai, Alan C; Chang, Tsui-Lan; Wang, Jiun-Yi

2013-09-28

The present study was aimed to validate two normalised short-form (SF) Mini-Nutritional Assessments (MNA) that contained either BMI (Taiwan version 1, T1) or calf circumference (CC; Taiwan version 2, T2) for rating the nutritional status of elderly Taiwanese. Both versions adopted Taiwanese anthropometric cut-offs, but T2 further had the BMI item replaced by CC. We compared the ability of the two SF in rating the nutritional status of 2674 elderly Taiwanese in the 1999 ‘Taiwan Longitudinal Survey on Aging’ with their respective full versions. We evaluated the agreement between the SF and full scales with weighted κ and performed Cox regression analysis for the follow-up 4-year mortality according to nutritional status rated at baseline. The results showed that the agreements between the respective SF and the full MNA were good (weighted κ: 0·679 for T1 and 0·667 for T2). Both SF performed well in predicting follow-up 4-year mortality relative to the full MNA. In conclusion, MNA-T1-SF and -T2-SF have good consistency with the full MNA and have quite comparable abilities in rating the nutritional status of elderly Taiwanese. Both SF versions appear appropriate for functioning as stand-alone units for rating the nutritional status of the elderly in community-living settings or the general population.

[Effects of mental workload on work ability in primary and secondary school teachers].

PubMed

Xiao, Yuanmei; Li, Weijuan; Ren, Qingfeng; Ren, Xiaohui; Wang, Zhiming; Wang, Mianzhen; Lan, Yajia

2015-02-01

To investigate the change pattern of primary and secondary school teachers' work ability with the changes in their mental workload. A total of 901 primary and secondary school teachers were selected by random cluster sampling, and then their mental workload and work ability were assessed by National Aeronautics and Space Administration-Task Load Index (NASA-TLX) and Work Ability Index (WAI) questionnaires, whose reliability and validity had been tested. The effects of their mental workload on the work ability were analyzed. Primary and secondary school teachers' work ability reached the highest level at a certain level of mental workload (55.73< mental workload ≤ 64.10). When their mental workload was lower than the level, their work ability had a positive correlation with the mental workload. Their work ability increased or maintained stable with the increasing mental workload. Moreover, the percentage of teachers with good work ability increased, while that of teachers with moderate work ability decreased. But when their mental workload was higher than the level, their work ability had a negative correlation with the mental workload. Their work ability significantly decreased with the increasing mental workload (P < 0.01). Furthermore, the percentage of teachers with good work ability decreased, while that of teachers with moderate work ability increased (P < 0.001). Too high or low mental workload will result in the decline of primary and secondary school teachers' work ability. Moderate mental workload (55.73∼64.10) will benefit the maintaining and stabilization of their work ability.

Language Ability Predicts the Development of Behavior Problems in Children

PubMed Central

Petersen, Isaac T.; Bates, John E.; D’Onofrio, Brian M.; Coyne, Claire A.; Lansford, Jennifer E.; Dodge, Kenneth A.; Pettit, Gregory S.; Van Hulle, Carol A.

2013-01-01

Prior studies have suggested, but not fully established, that language ability is important for regulating attention and behavior. Language ability may have implications for understanding attention-deficit hyperactivity disorder (ADHD) and conduct disorders, as well as subclinical problems. This article reports findings from two longitudinal studies to test (a) whether language ability has an independent effect on behavior problems, and (b) the direction of effect between language ability and behavior problems. In Study 1 (N = 585), language ability was measured annually from ages 7 to 13 years by language subtests of standardized academic achievement tests administered at the children’s schools. Inattentive-hyperactive (I-H) and externalizing (EXT) problems were reported annually by teachers and mothers. In Study 2 (N = 11,506), language ability (receptive vocabulary) and mother-rated I-H and EXT problems were measured biannually from ages 4 to 12 years. Analyses in both studies showed that language ability predicted within-individual variability in the development of I-H and EXT problems over and above the effects of sex, ethnicity, socioeconomic status (SES), and performance in other academic and intellectual domains (e.g., math, reading comprehension, reading recognition, and short-term memory [STM]). Even after controls for prior levels of behavior problems, language ability predicted later behavior problems more strongly than behavior problems predicted later language ability, suggesting that the direction of effect may be from language ability to behavior problems. The findings suggest that language ability may be a useful target for the prevention or even treatment of attention deficits and EXT problems in children. PMID:23713507

Lung function parameters improve prediction of VO2peak in an elderly population: The Generation 100 study.

PubMed

Hassel, Erlend; Stensvold, Dorthe; Halvorsen, Thomas; Wisløff, Ulrik; Langhammer, Arnulf; Steinshamn, Sigurd

2017-01-01

Peak oxygen uptake (VO2peak) is an indicator of cardiovascular health and a useful tool for risk stratification. Direct measurement of VO2peak is resource-demanding and may be contraindicated. There exist several non-exercise models to estimate VO2peak that utilize easily obtainable health parameters, but none of them includes lung function measures or hemoglobin concentrations. We aimed to test whether addition of these parameters could improve prediction of VO2peak compared to an established model that includes age, waist circumference, self-reported physical activity and resting heart rate. We included 1431 subjects aged 69-77 years that completed a laboratory test of VO2peak, spirometry, and a gas diffusion test. Prediction models for VO2peak were developed with multiple linear regression, and goodness of fit was evaluated. Forced expiratory volume in one second (FEV1), diffusing capacity of the lung for carbon monoxide and blood hemoglobin concentration significantly improved the ability of the established model to predict VO2peak. The explained variance of the model increased from 31% to 48% for men and from 32% to 38% for women (p<0.001). FEV1, diffusing capacity of the lungs for carbon monoxide and hemoglobin concentration substantially improved the accuracy of VO2peak prediction when added to an established model in an elderly population.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

PubMed Central

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

2017-01-01

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

Use of qualitative and quantitative information in neural networks for assessing agricultural chemical contamination of domestic wells

USGS Publications Warehouse

Mishra, A.; Ray, C.; Kolpin, D.W.

2004-01-01

A neural network analysis of agrichemical occurrence in groundwater was conducted using data from a pilot study of 192 small-diameter drilled and driven wells and 115 dug and bored wells in Illinois, a regional reconnaissance network of 303 wells across 12 Midwestern states, and a study of 687 domestic wells across Iowa. Potential factors contributing to well contamination (e.g., depth to aquifer material, well depth, and distance to cropland) were investigated. These contributing factors were available in either numeric (actual or categorical) or descriptive (yes or no) format. A method was devised to use the numeric and descriptive values simultaneously. Training of the network was conducted using a standard backpropagation algorithm. Approximately 15% of the data was used for testing. Analysis indicated that training error was quite low for most data. Testing results indicated that it was possible to predict the contamination potential of a well with pesticides. However, predicting the actual level of contamination was more difficult. For pesticide occurrence in drilled and driven wells, the network predictions were good. The performance of the network was poorer for predicting nitrate occurrence in dug and bored wells. Although the data set for Iowa was large, the prediction ability of the trained network was poor, due to descriptive or categorical input parameters, compared with smaller data sets such as that for Illinois, which contained more numeric information.

Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study.

PubMed

Escarela, Gabriel

2012-06-01

The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.

European-scale modeling of concentrations and distribution of polybrominated diphenyl ethers in the pentabromodiphenyl ether product.

PubMed

Prevedouros, K; Jones, K C; Sweetman, A J

2004-11-15

The results from a modeling exercise utilizing the European variant (EVn) BETR multimedia environmental fate model are presented for selected polybrominated diphenyl ethers (PBDEs) of the technical penta- (Pe-) bromodiphenyl ether (BDE) product. The objectives of this study were to test PeBDE emission estimates from the literature for Europe by investigating the consistency between model predictions and ambient measurements to address the ability of the model to predict spatial variability and differences between congeners. Concurrently sampled and analyzed passive sampling air data, together with soil and grass data, were used as key model validation tools. The model steady-state simulations gave generally good agreement with measured data for BDE-47 and -99 with greater discrepancies for heavier congeners (e.g., BDE-153). To predict future atmospheric concentration trends, the model was used in its fully dynamic mode over the period 1970--2010. It was predicted that atmospheric concentrations peaked around 1997, declining with an overall "disappearance" half-life of 4.8 years. Soil and grass levels were underestimated by the model; possible reasons for differences with measurement data are further explored. Finally, the importance of temporally and spatially resolved environmental data sets is highlighted, while improved quantification of degradation half-lives is essential to better understand and predict the behavior of BDE congeners in PeBDE.

Analysis of superconducting electromagnetic finite elements based on a magnetic vector potential variational principle

NASA Technical Reports Server (NTRS)

Schuler, James J.; Felippa, Carlos A.

1991-01-01

Electromagnetic finite elements are extended based on a variational principle that uses the electromagnetic four potential as primary variable. The variational principle is extended to include the ability to predict a nonlinear current distribution within a conductor. The extension of this theory is first done on a normal conductor and tested on two different problems. In both problems, the geometry remains the same, but the material properties are different. The geometry is that of a 1-D infinite wire. The first problem is merely a linear control case used to validate the new theory. The second problem is made up of linear conductors with varying conductivities. Both problems perform well and predict current densities that are accurate to within a few ten thousandths of a percent of the exact values. The fourth potential is then removed, leaving only the magnetic vector potential, and the variational principle is further extended to predict magnetic potentials, magnetic fields, the number of charge carriers, and the current densities within a superconductor. The new element produces good results for the mean magnetic field, the vector potential, and the number of superconducting charge carriers despite a relatively high system condition number. The element did not perform well in predicting the current density. Numerical problems inherent to this formulation are explored and possible remedies to produce better current predicting finite elements are presented.

Use of Preoperative Functional MRI to Predict Verbal Memory Decline After Temporal Lobe Epilepsy Surgery

PubMed Central

Binder, Jeffrey R.; Sabsevitz, David S.; Swanson, Sara J.; Hammeke, Thomas A.; Raghavan, Manoj; Mueller, Wade M.

2010-01-01

Purpose Verbal memory decline is a frequent complication of left anterior temporal lobectomy (L-ATL). The goal of this study was to determine whether preoperative language mapping using functional magnetic resonance imaging (fMRI) is useful for predicting which patients are likely to experience verbal memory decline after L-ATL. Methods Sixty L-ATL patients underwent preoperative language mapping with fMRI, preoperative intracarotid amobarbital (Wada) testing for language and memory lateralization, and pre- and postoperative neuropsychological testing. Demographic, historical, neuropsychological, and imaging variables were examined for their ability to predict pre- to postoperative memory change. Results Verbal memory decline occurred in over 30% of patients. Good preoperative performance, late age at onset of epilepsy, left dominance on fMRI, and left dominance on the Wada test were each predictive of memory decline. Preoperative performance and age at onset together accounted for roughly 50% of the variance in memory outcome (p < .001), and fMRI explained an additional 10% of this variance (p ≤ .003). Neither Wada memory asymmetry nor Wada language asymmetry added additional predictive power beyond these noninvasive measures. Discussion Preoperative fMRI is useful for identifying patients at high risk for verbal memory decline prior to L-ATL surgery. Lateralization of language is correlated with lateralization of verbal memory, whereas Wada memory testing is either insufficiently reliable or insufficiently material-specific to accurately localize verbal memory processes. PMID:18435753

Observability during planetary approach navigation

NASA Technical Reports Server (NTRS)

Bishop, Robert H.; Burkhart, P. Daniel; Thurman, Sam W.

1993-01-01

The objective of the research is to develop an analytic technique to predict the relative navigation capability of different Earth-based radio navigation measurements. In particular, the problem is to determine the relative ability of geocentric range and Doppler measurements to detect the effects of the target planet gravitational attraction on the spacecraft during the planetary approach and near-encounter mission phases. A complete solution to the two-dimensional problem has been developed. Relatively simple analytic formulas are obtained for range and Doppler measurements which describe the observability content of the measurement data along the approach trajectories. An observability measure is defined which is based on the observability matrix for nonlinear systems. The results show good agreement between the analytic observability analysis and the computational batch processing method.

The integrated learning management using the STEM education for improve learning achievement and creativity in the topic of force and motion at the 9th grade level

NASA Astrophysics Data System (ADS)

Kakarndee, Nampetch; Kudthalang, Nukool; Jansawang, Natchanok

2018-01-01

The aims of this research study were to investigate and analyze the processing performances and the performance results (E1/E2) efficiency at the determining criteria for planning students' improvements to their learning processes toward their scientific knowledge were investigated, carry out the investigations, gathering evidence, and proposing explanations were developed and predicted. Students' engagements to their needs in unambiguous and clearly content of science teaching onto the instructional processes were attempted for establishing a national approach with the STEM education instructional method were strategized. Research administrations were designed to a sample size consisted of 40 secondary students in science class at the 9th grade level in Borabu School with the purposive sampling technique was selected. Using the STEM Education instructional innovation's lesson plans were managed learning activities. Students' learning achievements were assessed with the Pre-Test and Post-Test designs of 30 items. Students' creative thinking abilities were determined of their perceptions that obtained of the 3-item Creative Thinking Ability Test. The results for the effectiveness of the innovative instructional lesson plans based on the STEM Education Method, the lessoning effectiveness (E1/E2) evidences of 78.95/76.58 over the threshold setting is 75/75. Pretest-posttest designs for assessing students' learning achievements that impact a student's ability to achieve and explains with the STEM education instructional method were differences, significantly (ρ<.001) and the posttest of the 3-item Creative Thinking Ability Test designs for assessing Students' creative thinking abilities that impact a student's ability to have a good skill level in originality, fluency and flexibility thinking with the STEM education instructional method were differences, significantly (ρ<.001).

Personality, negative affect coping, and drinking alone: a structural equation modeling approach to examine correlates of adolescent solitary drinking

PubMed Central

Creswell, Kasey G.; Chung, Tammy; Wright, Aidan G. C.; Clark, Duncan B.; Black, Jessica J.; Martin, Christopher S.

2015-01-01

Aims This study examined the personality traits of negative emotionality and constraint and the ability to resist drinking during negative affective states as correlates of solitary drinking in adolescence. We hypothesized that higher levels of negative emotionality and lower levels of constraint would predict solitary drinking and that these relationships would be mediated by the ability to resist drinking in response to negative emotions. Design Structural equation modeling was used to fit a path model from the personality traits of negative emotionality and constraint to solitary drinking status through intermediate effects on the ability to resist drinking during negative emotions using cross-sectional data. Setting Clinical and community settings in Pennsylvania, USA. Participants The sample included 761 adolescent drinkers (mean age = 17.1). Measurements Adolescents completed the Lifetime Drinking History, the Multidimensional Personality Questionnaire, the Constructive Thinking Inventory and the Situational Confidence Questionnaire. Findings The path model provided a good fit to the data. The association between trait negative emotionality and solitary drinking was fully mediated by adolescents' ability to resist drinking during negative affective states (b = 0.05, P = 0.01). In contrast, constraint had a direct effect on solitary drinking (odds ratio (OR) = 0.79, b = –0.23, P<0.01), as well as an indirect effect through the ability to resist drinking during negative affective states (b = –0.03, P = 0.02). Conclusions The ability to resist drinking while experiencing negative feelings or emotions may be an important underlying mechanism linking trait negative emotionality (a tendency toward depression, anxiety and poor reaction to stress) and constraint (lack of impulsiveness) to adolescent solitary drinking. PMID:25664806

Personality, negative affect coping, and drinking alone: a structural equation modeling approach to examine correlates of adolescent solitary drinking.

PubMed

Creswell, Kasey G; Chung, Tammy; Wright, Aidan G C; Clark, Duncan B; Black, Jessica J; Martin, Christopher S

2015-05-01

This study examined the personality traits of negative emotionality and constraint and the ability to resist drinking during negative affective states as correlates of solitary drinking in adolescence. We hypothesized that higher levels of negative emotionality and lower levels of constraint would predict solitary drinking and that these relationships would be mediated by the ability to resist drinking in response to negative emotions. Structural equation modeling was used to fit a path model from the personality traits of negative emotionality and constraint to solitary drinking status through intermediate effects on the ability to resist drinking during negative emotions using cross-sectional data. Clinical and community settings in Pennsylvania, USA. The sample included 761 adolescent drinkers (mean age = 17.1). Adolescents completed the Lifetime Drinking History, the Multidimensional Personality Questionnaire, the Constructive Thinking Inventory and the Situational Confidence Questionnaire. The path model provided a good fit to the data. The association between trait negative emotionality and solitary drinking was fully mediated by adolescents' ability to resist drinking during negative affective states (b = 0.05, P = 0.01). In contrast, constraint had a direct effect on solitary drinking (odds ratio (OR) = 0.79, b = -0.23, P<0.01), as well as an indirect effect through the ability to resist drinking during negative affective states (b = -0.03, P = 0.02). The ability to resist drinking while experiencing negative feelings or emotions may be an important underlying mechanism linking trait negative emotionality (a tendency toward depression, anxiety and poor reaction to stress) and constraint (lack of impulsiveness) to adolescent solitary drinking. © 2015 Society for the Study of Addiction.

The role of ability, motivation, and opportunity to work in the transition from work to early retirement--testing and optimizing the Early Retirement Model.

PubMed

de Wind, Astrid; Geuskens, Goedele A; Ybema, Jan Fekke; Bongers, Paulien M; van der Beek, Allard J

2015-01-01

Determinants in the domains health, job characteristics, skills, and social and financial factors may influence early retirement through three central explanatory variables, namely, the ability, motivation, and opportunity to work. Based on the literature, we created the Early Retirement Model. This study aims to investigate whether data support the model and how it could be improved. Employees aged 58-62 years (N=1862), who participated in the first three waves of the Dutch Study on Transitions in Employment, Ability and Motivation (STREAM) were included. Determinants were assessed at baseline, central explanatory variables after one year, and early retirement after two years. Structural equation modeling was applied. Testing the Early Retirement Model resulted in a model with good fit. Health, job characteristics, skills, and social and financial factors were related to the ability, motivation and/or opportunity to work (significant β range: 0.05-0.31). Lower work ability (β=-0.13) and less opportunity to work (attitude colleagues and supervisor about working until age 65: β=-0.24) predicted early retirement, whereas the motivation to work (work engagement) did not. The model could be improved by adding direct effects of three determinants on early retirement, ie, support of colleagues and supervisor (β=0.14), positive attitude of the partner with respect to early retirement (β=0.15), and not having a partner (β=-0.13). The Early Retirement Model was largely supported by the data but could be improved. The prolongation of working life might be promoted by work-related interventions focusing on health, work ability, the social work climate, social norms on prolonged careers, and the learning environment.

Work disabilities and unmet needs for health care and rehabilitation among jobseekers: a community-level investigation using multidimensional work ability assessments

PubMed Central

Kerätär, Raija; Taanila, Anja; Jokelainen, Jari; Soukainen, Jouko; Ala-Mursula, Leena

2016-01-01

Objective Comprehensive understanding of the prevalence and quality of work disabilities and unmet needs for health care and rehabilitation to support return to work (RTW) among jobseekers. Design Community-level, cross-sectional analysis with multidimensional clinical work ability assessments. Setting Paltamo, Finland. Participants Unemployed citizens either participating in the Full-Employment Project or long-term unemployed (n = 230, 81%). Main outcome measures Based on data from theme interviews, patient records, supervisors’ observations of work performance and clinical examinations, a physician concluded the individual’s work ability, categorised into four groups: good work ability, good work ability expected after RTW support, able to transitional work only or unable to work. These groups were cross tabulated with primary diagnoses, types of plans to support RTW, as well as categories of social functioning and motivation, for which sensitivity and specificity scores in detecting work disability were calculated. Results Only about half of the jobseekers had good work ability, 27% were found unable to work in the open labour market and 15% even eligible for a disability pension. For 20%, care or rehabilitation was seen necessary to enable RTW. Poor supervisor- and self-rated performance at work or poor social functioning appeared as sensitive measures in detecting work disability. Conclusions Work disabilities and unmet needs for health care and rehabilitation are highly prevalent among jobseekers, as depicted using a multidimensional work ability assessment procedure inspired by the International Classification of Functioning (ICF). Further development of work ability assessment practices is clearly needed. KEY POINTSAlthough the association of unemployment with poor health is well known, evidence on the work ability of the unemployed remains scarce.Work disabilities are common among the unemployed.Multidimensional work ability assessment among the unemployed reveals unmet needs for care and rehabilitation to support return to work.Context sensitivity may add to the accuracy of the doctor’s conclusions on work ability. PMID:27804309

Work disabilities and unmet needs for health care and rehabilitation among jobseekers: a community-level investigation using multidimensional work ability assessments.

PubMed

Kerätär, Raija; Taanila, Anja; Jokelainen, Jari; Soukainen, Jouko; Ala-Mursula, Leena

2016-12-01

Comprehensive understanding of the prevalence and quality of work disabilities and unmet needs for health care and rehabilitation to support return to work (RTW) among jobseekers. Community-level, cross-sectional analysis with multidimensional clinical work ability assessments. Paltamo, Finland. Unemployed citizens either participating in the Full-Employment Project or long-term unemployed (n = 230, 81%). Based on data from theme interviews, patient records, supervisors' observations of work performance and clinical examinations, a physician concluded the individual's work ability, categorised into four groups: good work ability, good work ability expected after RTW support, able to transitional work only or unable to work. These groups were cross tabulated with primary diagnoses, types of plans to support RTW, as well as categories of social functioning and motivation, for which sensitivity and specificity scores in detecting work disability were calculated. Only about half of the jobseekers had good work ability, 27% were found unable to work in the open labour market and 15% even eligible for a disability pension. For 20%, care or rehabilitation was seen necessary to enable RTW. Poor supervisor- and self-rated performance at work or poor social functioning appeared as sensitive measures in detecting work disability. Work disabilities and unmet needs for health care and rehabilitation are highly prevalent among jobseekers, as depicted using a multidimensional work ability assessment procedure inspired by the International Classification of Functioning (ICF). Further development of work ability assessment practices is clearly needed. KEY POINTS Although the association of unemployment with poor health is well known, evidence on the work ability of the unemployed remains scarce. Work disabilities are common among the unemployed. Multidimensional work ability assessment among the unemployed reveals unmet needs for care and rehabilitation to support return to work. Context sensitivity may add to the accuracy of the doctor's conclusions on work ability.

Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

PubMed

Ng, Hui Wen; Doughty, Stephen W; Luo, Heng; Ye, Hao; Ge, Weigong; Tong, Weida; Hong, Huixiao

2015-12-21

Some chemicals in the environment possess the potential to interact with the endocrine system in the human body. Multiple receptors are involved in the endocrine system; estrogen receptor α (ERα) plays very important roles in endocrine activity and is the most studied receptor. Understanding and predicting estrogenic activity of chemicals facilitates the evaluation of their endocrine activity. Hence, we have developed a decision forest classification model to predict chemical binding to ERα using a large training data set of 3308 chemicals obtained from the U.S. Food and Drug Administration's Estrogenic Activity Database. We tested the model using cross validations and external data sets of 1641 chemicals obtained from the U.S. Environmental Protection Agency's ToxCast project. The model showed good performance in both internal (92% accuracy) and external validations (∼ 70-89% relative balanced accuracies), where the latter involved the validations of the model across different ER pathway-related assays in ToxCast. The important features that contribute to the prediction ability of the model were identified through informative descriptor analysis and were related to current knowledge of ER binding. Prediction confidence analysis revealed that the model had both high prediction confidence and accuracy for most predicted chemicals. The results demonstrated that the model constructed based on the large training data set is more accurate and robust for predicting ER binding of chemicals than the published models that have been developed using much smaller data sets. The model could be useful for the evaluation of ERα-mediated endocrine activity potential of environmental chemicals.

Parents' Ability to Assess Dental Fear in their Six- to 10-year-old Children.

PubMed

Klein, Ulrich; Manangkil, Rochelle; DeWitt, Peter

2015-01-01

To investigate parents' ability to assess dental anxiety of their six- to 10-year-old children and to determine how parents' and children's fear assessments correlate with patient behavior during dental treatment. From a continuous convenience sample, 184 child/parent dyads were recruited to complete the Children's Fear Survey Schedule-Dental Subscale (CFSS-DS) questionnaire prior to dental treatment. One provider treated all children, assessed their behavior, and assigned a Frankl score rating to them. Parent/child anxiety scores were compared to each other and to the behavior children presented during dental treatment. The mean dental anxiety score reported by the children was 30.30; the score reported by their parents was 2.94 points higher (P=.0016). There was poor consistency within parent/child pairs when precisely assessing dental anxiety. Parental assessments of their children's dental anxiety were a poor to fair predictor for observed behavior, whereas the children's self-assessments were fair to good. Child age was not associated with ability to assess anxiety. Parents of children with low anxiety overestimated their children's anxiety, whereas parents of children with high anxiety underestimated their children's anxiety. Parents and children showed moderate agreement assessing dental anxiety measured by the CFSS-DS. The child's score is preferable for predicting behavior.

Investigating the role of executive attentional control to self-harm in a non-clinical cohort with borderline personality features

PubMed Central

Drabble, Jennifer; Bowles, David P.; Barker, Lynne Ann

2014-01-01

Self-injurious behavior (or self-harm) is a frequently reported maladaptive behavior in the general population and a key feature of borderline personality disorder (BPD). Poor affect regulation is strongly linked to a propensity to self-harm, is a core component of BPD, and is linked with reduced attentional control abilities. The idea that attentional control difficulties may provide a link between BPD, negative affect and self-harm has yet to be established, however. The present study explored the putative relationship between levels of BPD features, three aspects of attentional/executive control, affect, and self-harm history in a sample of 340 non-clinical participants recruited online from self-harm forums and social networking sites. Analyses showed that self-reported levels of BPD features and attentional focusing predicted self-harm incidence, and high attentional focusing increased the likelihood of a prior self-harm history in those with high BPD features. Ability to shift attention was associated with a reduced likelihood of self-harm, suggesting that good attentional switching ability may provide a protective buffer against self-harm behavior for some individuals. These attentional control differences mediated the association between negative affect and self-harm, but the relationship between BPD and self-harm appears independent. PMID:25191235

Predictive Accuracy of the Liverpool Lung Project Risk Model for Stratifying Patients for Computed Tomography Screening for Lung Cancer

PubMed Central

Raji, Olaide Y.; Duffy, Stephen W.; Agbaje, Olorunshola F.; Baker, Stuart G.; Christiani, David C.; Cassidy, Adrian; Field, John K.

2013-01-01

Background External validation of existing lung cancer risk prediction models is limited. Using such models in clinical practice to guide the referral of patients for computed tomography (CT) screening for lung cancer depends on external validation and evidence of predicted clinical benefit. Objective To evaluate the discrimination of the Liverpool Lung Project (LLP) risk model and demonstrate its predicted benefit for stratifying patients for CT screening by using data from 3 independent studies from Europe and North America. Design Case–control and prospective cohort study. Setting Europe and North America. Patients Participants in the European Early Lung Cancer (EUELC) and Harvard case–control studies and the LLP population-based prospective cohort (LLPC) study. Measurements 5-year absolute risks for lung cancer predicted by the LLP model. Results The LLP risk model had good discrimination in both the Harvard (area under the receiver-operating characteristic curve [AUC], 0.76 [95% CI, 0.75 to 0.78]) and the LLPC (AUC, 0.82 [CI, 0.80 to 0.85]) studies and modest discrimination in the EUELC (AUC, 0.67 [CI, 0.64 to 0.69]) study. The decision utility analysis, which incorporates the harms and benefit of using a risk model to make clinical decisions, indicates that the LLP risk model performed better than smoking duration or family history alone in stratifying high-risk patients for lung cancer CT screening. Limitations The model cannot assess whether including other risk factors, such as lung function or genetic markers, would improve accuracy. Lack of information on asbestos exposure in the LLPC limited the ability to validate the complete LLP risk model. Conclusion Validation of the LLP risk model in 3 independent external data sets demonstrated good discrimination and evidence of predicted benefits for stratifying patients for lung cancer CT screening. Further studies are needed to prospectively evaluate model performance and evaluate the optimal population risk thresholds for initiating lung cancer screening. Primary Funding Source Roy Castle Lung Cancer Foundation. PMID:22910935

Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality and intensive care admission among traumatic brain-injured patients.

PubMed

Gagné, Mathieu; Moore, Lynne; Sirois, Marie-Josée; Simard, Marc; Beaudoin, Claudia; Kuimi, Brice Lionel Batomen

2017-02-01

The International Classification of Diseases (ICD) is the main classification system used for population-based traumatic brain injury (TBI) surveillance activities but does not contain direct information on injury severity. International Classification of Diseases-based injury severity measures can be empirically derived or mapped to the Abbreviated Injury Scale, but no single approach has been formally recommended for TBI. The aim of this study was to compare the accuracy of different ICD-based injury severity measures for predicting in-hospital mortality and intensive care unit (ICU) admission in TBI patients. We conducted a population-based retrospective cohort study. We identified all patients 16 years or older with a TBI diagnosis who received acute care between April 1, 2006, and March 31, 2013, from the Quebec Hospital Discharge Database. The accuracy of five ICD-based injury severity measures for predicting mortality and ICU admission was compared using measures of discrimination (area under the receiver operating characteristic curve [AUC]) and calibration (calibration plot and the Hosmer-Lemeshow goodness-of-fit statistic). Of 31,087 traumatic brain-injured patients in the study population, 9.0% died in hospital, and 34.4% were admitted to the ICU. Among ICD-based severity measures that were assessed, the multiplied derivative of ICD-based Injury Severity Score (ICISS-Multiplicative) demonstrated the best discriminative ability for predicting in-hospital mortality (AUC, 0.858; 95% confidence interval, 0.852-0.864) and ICU admissions (AUC, 0.813; 95% confidence interval, 0.808-0.818). Calibration assessments showed good agreement between observed and predicted in-hospital mortality for ICISS measures. All severity measures presented high agreement between observed and expected probabilities of ICU admission for all deciles of risk. The ICD-based injury severity measures can be used to accurately predict in-hospital mortality and ICU admission in TBI patients. The ICISS-Multiplicative generally outperformed other ICD-based injury severity measures and should be preferred to control for differences in baseline characteristics between TBI patients in surveillance activities or injury research when only ICD codes are available. Prognostic study, level III.

Verbal Ability and Teacher Effectiveness

ERIC Educational Resources Information Center

Andrew, Michael D.; Cobb, Casey D.; Giampietro, Peter J.

2005-01-01

Critics of traditional teacher education programs have suggested that verbal ability along with subject knowledge is sufficient for measuring good teaching. A small group of research studies is called upon to support this contention. This article reviews these studies, analyzes the role of verbal ability in teaching, and presents research…

Interaction of lifestyle and work ability index in blue collar workers.

PubMed

Mohammadi, Saber; Ghaffari, Mostafa; Abdi, Alireza; Bahadori, Baharak; Mirzamohammadi, Elham; Attarchi, Mirsaeed

2014-11-17

Early labor force exit is one of the major problems worldwide. The present study investigates the relationship between work ability and lifestyle. This study was conducted at a manufacturing plant in Tehran in 2012. All 851 male workers in this plant were included into the study and their work ability was assessed using the Work Ability Index (WAI). Based on the obtained scores, the participants were then classified into four work ability groups (poor, moderate, good, or excellent). Moreover, the participants' lifestyles were studied in three areas, including physical activity, cigarette smoking, and Body Mass Index (BMI). The average work ability index score was 42.07, ranging from 7-48. Among the participants, 6.4% (43), 6.5% (44), 38.3% (259), and 48.8% (330) were in the groups with poor, moderate, good, and excellent work ability, respectively. The results of logistic regression analysis showed that there is a significant relationship between work ability and lifestyle (cigarette smoking, BMI, and physical activity) even after adjustment for confounding variables (P<0.05). According to the results of the present study, there might be a relationship between work ability and lifestyle (physical activity, BMI, cigarette smoking). Therefore, it is recommended to implement a lifestyle quality enhancement program to improve work ability in working environments.

Movement of Goods, Services and People: Entanglements with Sustainability Implications

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

Southworth, Frank; Wigan, Marcus

2008-01-01

In both Europe and North America the continued growth in both passenger and freight traffic promises growing competition for road space between these two forms of travel. Forecast traffic levels call into question the ability of current infrastructures to sustain the efficient movement of both goods and people over increasingly crowded roadways and through increasingly delay-prone terminals. Costs of maintaining current highway networks in the face of heavy truck use also limit the budgets available for capacity expansion. In this paper the authors examine potential areas of both conflict and synergy in the movement of goods and people and considermore » the sort of data and analytical tools available for understanding the needs of, in particular, mixed use highway systems. Similarities in the movement of goods and people within urban areas exist on both continents, suggesting a number of promising areas for complementary research efforts.Limited data on the intra-urban activities of commercial vehicles is identified as a major barrier to our current understanding of how best to use available road space, and this too is a common situation on both continents. In contrast, the different histories, geographies and population densities associated with inter-city transportation activities make comparative work in this area more difficult and may suggest different modal solutionson the two continents. In either case the authors argue that there is considerable value atthe present time in predicting the present especially as it applies to the functional linkages between personal, goods and a rapidly growing services transport sector.« less

Translational Modeling in Schizophrenia: Predicting Human Dopamine D2 Receptor Occupancy.

PubMed

Johnson, Martin; Kozielska, Magdalena; Pilla Reddy, Venkatesh; Vermeulen, An; Barton, Hugh A; Grimwood, Sarah; de Greef, Rik; Groothuis, Geny M M; Danhof, Meindert; Proost, Johannes H

2016-04-01

To assess the ability of a previously developed hybrid physiology-based pharmacokinetic-pharmacodynamic (PBPKPD) model in rats to predict the dopamine D2 receptor occupancy (D2RO) in human striatum following administration of antipsychotic drugs. A hybrid PBPKPD model, previously developed using information on plasma concentrations, brain exposure and D2RO in rats, was used as the basis for the prediction of D2RO in human. The rat pharmacokinetic and brain physiology parameters were substituted with human population pharmacokinetic parameters and human physiological information. To predict the passive transport across the human blood-brain barrier, apparent permeability values were scaled based on rat and human brain endothelial surface area. Active efflux clearance in brain was scaled from rat to human using both human brain endothelial surface area and MDR1 expression. Binding constants at the D2 receptor were scaled based on the differences between in vitro and in vivo systems of the same species. The predictive power of this physiology-based approach was determined by comparing the D2RO predictions with the observed human D2RO of six antipsychotics at clinically relevant doses. Predicted human D2RO was in good agreement with clinically observed D2RO for five antipsychotics. Models using in vitro information predicted human D2RO well for most of the compounds evaluated in this analysis. However, human D2RO was under-predicted for haloperidol. The rat hybrid PBPKPD model structure, integrated with in vitro information and human pharmacokinetic and physiological information, constitutes a scientific basis to predict the time course of D2RO in man.

Analysis on the Oversize Blast Furnace Desulfurization and a Sulfide Capacity Prediction Model Based on Congregated Electron Phase

NASA Astrophysics Data System (ADS)

Zhenyang, Wang; Jianliang, Zhang; Gang, An; Zhengjian, Liu; Zhengming, Cheng; Junjie, Huang; Jingwei, Zhang

2016-02-01

Through analyzed and regressed the actual productive desulfurization data from the oversize blast furnace (5500 m3) in north China, the relationship between the sulfur distribution parameters and the slag composition in actual production situation was investigated. As the slag and hot metal phases have their own balance sulfur content or sulfur partial pressure in gas phase, respectively, the non-equilibrium of sulfur among gas, slag, and metal phases leads to the transmission and distribution of sulfur. Combined with sulfur transmission reactions between gas, slag and metal phases, C/CO pairs equilibrium, and Wagner model, the measured sulfide capacity can be acquired using sulfur distribution ratio, sulfur activity coefficient, and oxygen activity in hot metal. Based on the theory of congregated electron phase, a new sulfide capacity prediction model (CEPM) has been developed, which has a good liner relationship with the measured sulfide capacity. Thus, using the burden structure for BF, the ironmaking slag composition can be obtained simply and can be used to reliably predict the ironmaking slag desulfurization ability a few hours later after charging under a certain temperature by CEPM.

Analysis of Wind Tunnel Oscillatory Data of the X-31A Aircraft

NASA Technical Reports Server (NTRS)

Smith, Mark S.

1999-01-01

Wind tunnel oscillatory tests in pitch, roll, and yaw were performed on a 19%-scale model of the X-31A aircraft. These tests were used to study the aerodynamic characteristics of the X-31A in response to harmonic oscillations at six frequencies. In-phase and out-of-phase components of the aerodynamic coefficients were obtained over a range of angles of attack from 0 to 90 deg. To account for the effect of frequency on the data, mathematical models with unsteady terms were formulated by use of two different indicial functions. Data from a reduced set of frequencies were used to estimate model parameters, including steady-state static and dynamic stability derivatives. Both models showed good prediction capability and the ability to accurately fit the measured data. Estimated static stability derivatives compared well with those obtained from static wind tunnel tests. The roll and yaw rate derivative estimates were compared with rotary-balanced wind tunnel data and theoretical predictions. The estimates and theoretical predictions were in agreement at small angles of attack. The rotary-balance data showed, in general, acceptable agreement with the steady-state derivative estimates.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Wealth and happiness across the world: material prosperity predicts life evaluation, whereas psychosocial prosperity predicts positive feeling.

PubMed

Diener, Ed; Ng, Weiting; Harter, James; Arora, Raksha

2010-07-01

The Gallup World Poll, the first representative sample of planet Earth, was used to explore the reasons why happiness is associated with higher income, including the meeting of basic needs, fulfillment of psychological needs, increasing satisfaction with one's standard of living, and public goods. Across the globe, the association of log income with subjective well-being was linear but convex with raw income, indicating the declining marginal effects of income on subjective well-being. Income was a moderately strong predictor of life evaluation but a much weaker predictor of positive and negative feelings. Possessing luxury conveniences and satisfaction with standard of living were also strong predictors of life evaluation. Although the meeting of basic and psychological needs mediated the effects of income on life evaluation to some degree, the strongest mediation was provided by standard of living and ownership of conveniences. In contrast, feelings were most associated with the fulfillment of psychological needs: learning, autonomy, using one's skills, respect, and the ability to count on others in an emergency. Thus, two separate types of prosperity-economic and social psychological-best predict different types of well-being.

Vorticity, backscatter and counter-gradient transport predictions using two-level simulation of turbulent flows

NASA Astrophysics Data System (ADS)

Ranjan, R.; Menon, S.

2018-04-01

The two-level simulation (TLS) method evolves both the large-and the small-scale fields in a two-scale approach and has shown good predictive capabilities in both isotropic and wall-bounded high Reynolds number (Re) turbulent flows in the past. Sensitivity and ability of this modelling approach to predict fundamental features (such as backscatter, counter-gradient turbulent transport, small-scale vorticity, etc.) seen in high Re turbulent flows is assessed here by using two direct numerical simulation (DNS) datasets corresponding to a forced isotropic turbulence at Taylor's microscale-based Reynolds number Reλ ≈ 433 and a fully developed turbulent flow in a periodic channel at friction Reynolds number Reτ ≈ 1000. It is shown that TLS captures the dynamics of local co-/counter-gradient transport and backscatter at the requisite scales of interest. These observations are further confirmed through a posteriori investigation of the flow in a periodic channel at Reτ = 2000. The results reveal that the TLS method can capture both the large- and the small-scale flow physics in a consistent manner, and at a reduced overall cost when compared to the estimated DNS or wall-resolved LES cost.

Selecting the optimum number of partial least squares components for the calibration of attenuated total reflectance-mid-infrared spectra of undesigned kerosene samples.

PubMed

Gómez-Carracedo, M P; Andrade, J M; Rutledge, D N; Faber, N M

2007-03-07

Selecting the correct dimensionality is critical for obtaining partial least squares (PLS) regression models with good predictive ability. Although calibration and validation sets are best established using experimental designs, industrial laboratories cannot afford such an approach. Typically, samples are collected in an (formally) undesigned way, spread over time and their measurements are included in routine measurement processes. This makes it hard to evaluate PLS model dimensionality. In this paper, classical criteria (leave-one-out cross-validation and adjusted Wold's criterion) are compared to recently proposed alternatives (smoothed PLS-PoLiSh and a randomization test) to seek out the optimum dimensionality of PLS models. Kerosene (jet fuel) samples were measured by attenuated total reflectance-mid-IR spectrometry and their spectra where used to predict eight important properties determined using reference methods that are time-consuming and prone to analytical errors. The alternative methods were shown to give reliable dimensionality predictions when compared to external validation. By contrast, the simpler methods seemed to be largely affected by the largest changes in the modeling capabilities of the first components.

Automated Systematic Generation and Exploration of Flat Direction Phenomenology in Free Fermionic Heterotic String Theory

NASA Astrophysics Data System (ADS)

Greenwald, Jared

Any good physical theory must resolve current experimental data as well as offer predictions for potential searches in the future. The Standard Model of particle physics, Grand Unied Theories, Minimal Supersymmetric Models and Supergravity are all attempts to provide such a framework. However, they all lack the ability to predict many of the parameters that each of the theories utilize. String theory may yield a solution to this naturalness (or self-predictiveness) problem as well as offer a unifed theory of gravity. Studies in particle physics phenomenology based on perturbative low energy analysis of various string theories can help determine the candidacy of such models. After a review of principles and problems leading up to our current understanding of the universe, we will discuss some of the best particle physics model building techniques that have been developed using string theory. This will culminate in the introduction of a novel approach to a computational, systematic analysis of the various physical phenomena that arise from these string models. We focus on the necessary assumptions, complexity and open questions that arise while making a fully-automated at direction analysis program.

Exploring a Method for Improving Turbulent Separated-Flow Predictions with kappa-omega Models

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2009-01-01

A particular failing of Reynolds-averaged Navier-Stokes separated turbulent flow computations is addressed within the context of a kappa-omega two-equation turbulence model. The failing is the tendency for turbulence models to under-predict turbulent shear stress in the shear layers of some separation bubbles, yielding late boundary layer reattachment and recovery. Inspired by unpublished work of Volker, Langtry, and Menter, the author undertook an independent investigation in an attempt to improve the ability of the Menter shear stress transport (SST) model to predict flowfield characteristics in and downstream of separation bubbles. The fix is an ad hoc term that is a function of the local ratio of turbulent production to dissipation; it is used to multiply the omega-destruction term, increasing eddy viscosity in separated regions. With this fix, several flowfields are investigated. Results show that, although the "separation fix" can provide dramatic improvement in some cases, it is not consistently good for all flows. Thus, although it may prove helpful in many situations in its current form, this model may benefit from further refinements, including better sensitization to the energetics of turbulence in the separated region.

Design of experiments-based monitoring of critical quality attributes for the spray-drying process of insulin by NIR spectroscopy.

PubMed

Maltesen, Morten Jonas; van de Weert, Marco; Grohganz, Holger

2012-09-01

Moisture content and aerodynamic particle size are critical quality attributes for spray-dried protein formulations. In this study, spray-dried insulin powders intended for pulmonary delivery were produced applying design of experiments methodology. Near infrared spectroscopy (NIR) in combination with preprocessing and multivariate analysis in the form of partial least squares projections to latent structures (PLS) were used to correlate the spectral data with moisture content and aerodynamic particle size measured by a time of flight principle. PLS models predicting the moisture content were based on the chemical information of the water molecules in the NIR spectrum. Models yielded prediction errors (RMSEP) between 0.39% and 0.48% with thermal gravimetric analysis used as reference method. The PLS models predicting the aerodynamic particle size were based on baseline offset in the NIR spectra and yielded prediction errors between 0.27 and 0.48 μm. The morphology of the spray-dried particles had a significant impact on the predictive ability of the models. Good predictive models could be obtained for spherical particles with a calibration error (RMSECV) of 0.22 μm, whereas wrinkled particles resulted in much less robust models with a Q (2) of 0.69. Based on the results in this study, NIR is a suitable tool for process analysis of the spray-drying process and for control of moisture content and particle size, in particular for smooth and spherical particles.

HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

PubMed

Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

2017-12-01

For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction and Observation of Post-Admission Hematoma Expansion in Patients with Intracerebral Hemorrhage

PubMed Central

Ovesen, Christian; Havsteen, Inger; Rosenbaum, Sverre; Christensen, Hanne

2014-01-01

Post-admission hematoma expansion in patients with intracerebral hemorrhage (ICH) comprises a simultaneous major clinical problem and a possible target for medical intervention. In any case, the ability to predict and observe hematoma expansion is of great clinical importance. We review radiological concepts in predicting and observing post-admission hematoma expansion. Hematoma expansion can be observed within the first 24 h after symptom onset, but predominantly occurs in the early hours. Thus capturing markers of on-going bleeding on imaging techniques could predict hematoma expansion. The spot sign observed on computed tomography angiography is believed to represent on-going bleeding and is to date the most well investigated and reliable radiological predictor of hematoma expansion as well as functional outcome and mortality. On non-contrast CT, the presence of foci of hypoattenuation within the hematoma along with the hematoma-size is reported to be predictive of hematoma expansion and outcome. Because patients tend to arrive earlier to the hospital, a larger fraction of acute ICH-patients must be expected to undergo hematoma expansion. This renders observation and radiological follow-up investigations increasingly relevant. Transcranial duplex sonography has in recent years proven to be able to estimate hematoma volume with good precision and could be a valuable tool in bedside serial observation of acute ICH-patients. Future studies will elucidate, if better prediction and observation of post-admission hematoma expansion can help select patients, who will benefit from hemostatic treatment. PMID:25324825

Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

PubMed

Ding, Feng; Yang, Xianhai; Chen, Guosong; Liu, Jining; Shi, Lili; Chen, Jingwen

2017-10-01

The partition coefficients between bovine serum albumin (BSA) and water (K BSA/w ) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK BSA/w . However, it was found that the conventional descriptors are inappropriate for modeling logK BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V s-adj - ), the chemical form adjusted molecular dipole moment (dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs. Copyright © 2017 Elsevier Inc. All rights reserved.

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

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

Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

2008-10-20

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasetsmore » having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer.« less

Feedback in Software and a Desktop Manufacturing Context for Learning Estimation Strategies in Middle School

ERIC Educational Resources Information Center

Malcolm, Peter

2013-01-01

The ability and to make good estimates is essential, as is the ability to assess the reasonableness of estimates. These abilities are becoming increasingly important as digital technologies transform the ways in which people work. To estimate is to provide an approximation to a problem that is mathematical in nature, and the ability to estimate is…

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

PubMed

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.

Predicting Esophagitis After Chemoradiation Therapy for Non-Small Cell Lung Cancer: An Individual Patient Data Meta-Analysis

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

Palma, David A., E-mail: david.palma@uwo.ca; Senan, Suresh; Oberije, Cary

Purpose: Concurrent chemoradiation therapy (CCRT) improves survival compared with sequential treatment for locally advanced non-small cell lung cancer, but it increases toxicity, particularly radiation esophagitis (RE). Validated predictors of RE for clinical use are lacking. We performed an individual-patient-data meta-analysis to determine factors predictive of clinically significant RE. Methods and Materials: After a systematic review of the literature, data were obtained on 1082 patients who underwent CCRT, including patients from Europe, North America, Asia, and Australia. Patients were randomly divided into training and validation sets (2/3 vs 1/3 of patients). Factors predictive of RE (grade ≥2 and grade ≥3) weremore » assessed using logistic modeling, with the concordance statistic (c statistic) used to evaluate the performance of each model. Results: The median radiation therapy dose delivered was 65 Gy, and the median follow-up time was 2.1 years. Most patients (91%) received platinum-containing CCRT regimens. The development of RE was common, scored as grade 2 in 348 patients (32.2%), grade 3 in 185 (17.1%), and grade 4 in 10 (0.9%). There were no RE-related deaths. On univariable analysis using the training set, several baseline factors were statistically predictive of RE (P<.05), but only dosimetric factors had good discrimination scores (c > .60). On multivariable analysis, the esophageal volume receiving ≥60 Gy (V60) alone emerged as the best predictor of grade ≥2 and grade ≥3 RE, with good calibration and discrimination. Recursive partitioning identified 3 risk groups: low (V60 <0.07%), intermediate (V60 0.07% to 16.99%), and high (V60 ≥17%). With use of the validation set, the predictive model performed inferiorly for the grade ≥2 endpoint (c = .58) but performed well for the grade ≥3 endpoint (c = .66). Conclusions: Clinically significant RE is common, but life-threatening complications occur in <1% of patients. Although several factors are statistically predictive of RE, the V60 alone provides the best predictive ability. Efforts to reduce the V60 should be prioritized, with further research needed to identify and validate new predictive factors.« less

Musical Competence is Predicted by Music Training, Cognitive Abilities, and Personality.

PubMed

Swaminathan, Swathi; Schellenberg, E Glenn

2018-06-15

Individuals differ in musical competence, which we defined as the ability to perceive, remember, and discriminate sequences of tones or beats. We asked whether such differences could be explained by variables other than music training, including socioeconomic status (SES), short-term memory, general cognitive ability, and personality. In a sample of undergraduates, musical competence had positive simple associations with duration of music training, SES, short-term memory, general cognitive ability, and openness-to-experience. When these predictors were considered jointly, musical competence had positive partial associations with music training, general cognitive ability, and openness. Nevertheless, moderation analyses revealed that the partial association between musical competence and music training was evident only among participants who scored below the mean on our measure of general cognitive ability. Moreover, general cognitive ability and openness had indirect associations with musical competence by predicting music training, which in turn predicted musical competence. Musical competence appears to be the result of multiple factors, including but not limited to music training.

Self-Schemas, Possible Selves, and Competent Performance.

ERIC Educational Resources Information Center

Cross, Susan E.; Markus, Hazel Rose

1994-01-01

College students were classified as schematic (belief in being a good problem solver and importance of this ability to self-esteem) or aschematic (belief in moderate ability and low or moderate importance of ability). Results with 196 students indicate the importance of self-concept in development and maintenance of competence. (SLD)

Predictive power of the DASA-IV: Variations in rating method and timescales.

PubMed

Nqwaku, Mphindisi; Draycott, Simon; Aldridge-Waddon, Luke; Bush, Emma-Louise; Tsirimokou, Alexandra; Jones, Dominic; Puzzo, Ignazio

2018-05-10

This project evaluated the predictive validity of the Dynamic Appraisal of Situational Aggression - Inpatient Version (DASA-IV) in a high-secure psychiatric hospital in the UK over 24 hours and over a single nursing shift. DASA-IV scores from three sequential nursing shifts over a 24-hour period were compared with the mean (average of three scores across the 24-hour period) and peak (highest of the three scores across the 24-hour period) scores across these shifts. In addition, scores from a single nursing shift were used to predict aggressive incidents over each of the following three shifts. The DASA-IV was completed by nursing staff during handover meetings, rating 43 male psychiatric inpatients over a period of 6 months. Data were compared to incident reports recorded over the same period. Receiver operating characteristic (ROC) curves and generalized estimating equations assessed the predictive ability of various DASA-IV scores over 24-hour and single-shift timescales. Scores from the DASA-IV based on a single shift had moderate predictive ability for aggressive incidents occurring the next calendar day, whereas scores based on all three shifts had excellent predictive ability. DASA-IV scores from a single shift showed moderate predictive ability for each of the following three shifts. The DASA-IV has excellent predictive ability for aggressive incidents within a secure setting when data are summarized over a 24-hour period, as opposed to when a single rating is taken. In addition, it has moderate value for predicting incidents over even shorter timescales. © 2018 Australian College of Mental Health Nurses Inc.

Specificity of meta-emotion effects on moral decision-making.

PubMed

Koven, Nancy S

2011-10-01

A recently proposed dual process theory of moral decision-making posits that utilitarian reasoning (approving of harmful actions that maximize good consequences) is the result of cognitive control of emotion. This suggests that deficits in emotional awareness will contribute to increased utilitarianism. The present study explored the relative contributions of the different facets of alexithymia and the closely related constructs of emotional intelligence and mood awareness to utilitarian decision making. Participants (N = 86) completed the Toronto Alexithymia Scale, Trait Meta Mood Scale, the Mood Awareness Scale, and a series of high-conflict, personal moral dilemmas validated by Greene et al. (2008). A brief neuropsychological battery was also administered to assess the possible confounds of verbal reasoning and abstract thinking ability. Principal components analysis revealed two latent factors-clarity of emotion and attention to emotion-which cut across all three meta-emotion instruments. Of these, low clarity of emotion-reflecting difficulty in reasoning thoughtfully about one's emotions-predicted utilitarian outcomes and provided unique variance beyond that of verbal and abstract reasoning abilities. Results are discussed in the context of individual differences in emotion regulation.

Cognitive Reflection and the Diligent Worker: An Experimental Study of Millennials

PubMed Central

Corgnet, Brice; Hernán Gonzalez, Roberto; Mateo, Ricardo

2015-01-01

Recent studies have shown that despite crucially needing the creative talent of millennials (people born after 1980) organizations have been reluctant to hire young workers because of their supposed lack of diligence. We propose to help resolve this dilemma by studying the determinants of task performance and shirking behaviors of millennials in a laboratory work environment. We find that cognitive ability is a good predictor of task performance in line with previous literature. In contrast with previous research, personality traits do not consistently predict either task performance or shirking behaviors. Shirking behaviors, as measured by the time participants spent browsing the internet for non-work purposes (Cyberloafing), were only explained by the performance on the Cognitive Reflection Test (CRT). This finding echoes recent research in cognitive psychology according to which conventional measures of cognitive ability only assess a narrow concept of rational thinking (the algorithmic mind) that fails to capture individuals’ capacity to reflect and control their impulses. Our findings suggest that hiring diligent millennials relies on the use of novel cognitive measures such as CRT in lieu of standard personality and intelligence tests. PMID:26545244

Cognitive Reflection and the Diligent Worker: An Experimental Study of Millennials.

PubMed

Corgnet, Brice; Hernán Gonzalez, Roberto; Mateo, Ricardo

2015-01-01

Recent studies have shown that despite crucially needing the creative talent of millennials (people born after 1980) organizations have been reluctant to hire young workers because of their supposed lack of diligence. We propose to help resolve this dilemma by studying the determinants of task performance and shirking behaviors of millennials in a laboratory work environment. We find that cognitive ability is a good predictor of task performance in line with previous literature. In contrast with previous research, personality traits do not consistently predict either task performance or shirking behaviors. Shirking behaviors, as measured by the time participants spent browsing the internet for non-work purposes (Cyberloafing), were only explained by the performance on the Cognitive Reflection Test (CRT). This finding echoes recent research in cognitive psychology according to which conventional measures of cognitive ability only assess a narrow concept of rational thinking (the algorithmic mind) that fails to capture individuals' capacity to reflect and control their impulses. Our findings suggest that hiring diligent millennials relies on the use of novel cognitive measures such as CRT in lieu of standard personality and intelligence tests.

A simplified clinical prediction rule for prognosticating independent walking after spinal cord injury: a prospective study from a Canadian multicenter spinal cord injury registry.

PubMed

Hicks, Katharine E; Zhao, Yichen; Fallah, Nader; Rivers, Carly S; Noonan, Vanessa K; Plashkes, Tova; Wai, Eugene K; Roffey, Darren M; Tsai, Eve C; Paquet, Jerome; Attabib, Najmedden; Marion, Travis; Ahn, Henry; Phan, Philippe

2017-10-01

Traumatic spinal cord injury (SCI) is a debilitating condition with limited treatment options for neurologic or functional recovery. The ability to predict the prognosis of walking post injury with emerging prediction models could aid in rehabilitation strategies and reintegration into the community. To revalidate an existing clinical prediction model for independent ambulation (van Middendorp et al., 2011) using acute and long-term post-injury follow-up data, and to investigatethe accuracy of a simplified model using prospectively collected data from a Canadian multicenter SCI database, the Rick Hansen Spinal Cord Injury Registry (RHSCIR). Prospective cohort study. The analysis cohort consisted of 278 adult individuals with traumatic SCI enrolled in the RHSCIR for whom complete neurologic examination data and Functional Independence Measure (FIM) outcome data were available. The FIM locomotor score was used to assess independent walking ability (defined as modified or complete independence in walk or combined walk and wheelchair modality) at 1-year follow-up for each participant. A logistic regression (LR) model based on age and four neurologic variables was applied to our cohort of 278 RHSCIR participants. Additionally, a simplified LR model was created. The Hosmer-Lemeshow goodness of fit test was used to check if the predictive model is applicable to our data set. The performance of the model was verified by calculating the area under the receiver operating characteristic curve (AUC). The accuracy of the model was tested using a cross-validation technique. This study was supported by a grant from The Ottawa Hospital Academic Medical Organization ($50,000 over 2 years). The RHSCIR is sponsored by the Rick Hansen Institute and is supported by funding from Health Canada, Western Economic Diversification Canada, and the provincial governments of Alberta, British Columbia, Manitoba, and Ontario. ET and JP report receiving grants from the Rick Hansen Institute (approximately $60,000 and $30,000 per year, respectively). DMR reports receiving remuneration for consulting services provided to Palladian Health, LLC and Pacira Pharmaceuticals, Inc ($20,000-$30,000 annually), although neither relationship presents a potential conflict of interest with the submitted work. KEH received a grant for involvement in the present study from the Government of Canada as part of the Canada Summer Jobs Program ($3,000). JP reports receiving an educational grant from Medtronic Canada outside of the submitted work ($75,000 annually). TM reports receiving educational fellowship support from AO Spine, AO Trauma, and Medtronic; however, none of these relationships are financial in nature. All remaining authors have no conflicts of interest to disclose. The fitted prediction model generated 85% overall classification accuracy, 79% sensitivity, and 90% specificity. The prediction model was able to accurately classify independent walking ability (AUC 0.889, 95% confidence interval [CI] 0.846-0.933, p<.001) compared with the existing prediction model, despite the use of a different outcome measure (FIM vs. Spinal Cord Independence Measure) to qualify walking ability. A simplified, three-variable LR model based on age and two neurologic variables had an overall classification accuracy of 84%, with 76% sensitivity and 90% specificity, demonstrating comparable accuracy with its five-variable prediction model counterpart. The AUC was 0.866 (95% CI 0.816-0.916, p<.01), only marginally less than that of the existing prediction model. A simplified predictive model with similar accuracy to a more complex model for predicting independent walking was created, which improves utility in a clinical setting. Such models will allow clinicians to better predict the prognosis of ambulation in individuals who have sustained a traumatic SCI. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Fitness: You Know Exercise Is Good for You, but Do You Know How Good? From Boosting Your Mood to Improving Your Sex Life

MedlinePlus

... good? From boosting your mood to improving your sex life, find out how exercise can improve your ... ignore. Everyone benefits from exercise, regardless of age, sex or physical ability. Need more convincing to get ...

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

Laser Shock Peening on Zr-based Bulk Metallic Glass and Its Effect on Plasticity: Experiment and Modeling

NASA Astrophysics Data System (ADS)

Cao, Yunfeng; Xie, Xie; Antonaglia, James; Winiarski, Bartlomiej; Wang, Gongyao; Shin, Yung C.; Withers, Philip J.; Dahmen, Karin A.; Liaw, Peter K.

2015-05-01

The Zr-based bulk metallic glasses (BMGs) are a new family of attractive materials with good glass-forming ability and excellent mechanical properties, such as high strength and good wear resistance, which make them candidates for structural and biomedical materials. Although the mechanical behavior of BMGs has been widely investigated, their deformation mechanisms are still poorly understood. In particular, their poor ductility significantly impedes their industrial application. In the present work, we show that the ductility of Zr-based BMGs with nearly zero plasticity is improved by a laser shock peening technique. Moreover, we map the distribution of laser-induced residual stresses via the micro-slot cutting method, and then predict them using a three-dimensional finite-element method coupled with a confined plasma model. Reasonable agreement is achieved between the experimental and modeling results. The analyses of serrated flows reveal plentiful and useful information of the underlying deformation process. Our work provides an easy and effective way to extend the ductility of intrinsically-brittle BMGs, opening up wider applications of these materials.

APRI and FIB-4 are good predictors of the stage of liver fibrosis in chronic hepatitis B: the Chronic Hepatitis Cohort Study (CHeCS).

PubMed

Teshale, E; Lu, M; Rupp, L B; Holmberg, S D; Moorman, A C; Spradling, P; Vijayadeva, V; Boscarino, J A; Schmidt, M A; Gordon, S C

2014-12-01

We aim to determine the predictive ability of APRI, FIB-4 and AST/ALT ratio for staging of liver fibrosis and to differentiate significant fibrosis (F2-F4) from none to minimal fibrosis (F0-F1) in chronic hepatitis B (CHB). Liver biopsy results were mapped to an F0-4 equivalent fibrosis stage. Mean APRI and FIB-4 scores were significantly higher for each successive fibrosis level from F1 to F4 (P < 0.05). Based on optimized cut-offs, the AUROCs in distinguishing F2-F4 from F0 to F1 were 0.81 (0.76-0.87) for APRI, 0.81 (0.75-0.86) for FIB-4 and 0.56 (0.49-0.64) for AST/ALT ratio. APRI and FIB-4 distinguished F2-F4 from F0 to F1 with good sensitivity and specificity and can be useful for treatment decisions and monitoring progression of fibrosis. © 2014 John Wiley & Sons Ltd.

Status and Preliminary Evaluation for Chinese Re-Analysis Datasets

NASA Astrophysics Data System (ADS)

bin, zhao; chunxiang, shi; tianbao, zhao; dong, si; jingwei, liu

2016-04-01

Based on operational T639L60 spectral model, combined with Hybird_GSI assimilation system by using meteorological observations including radiosondes, buoyes, satellites el al., a set of Chinese Re-Analysis (CRA) datasets is developing by Chinese National Meteorological Information Center (NMIC) of Chinese Meteorological Administration (CMA). The datasets are run at 30km (0.28°latitude / longitude) resolution which holds higher resolution than most of the existing reanalysis dataset. The reanalysis is done in an effort to enhance the accuracy of historical synoptic analysis and aid to find out detailed investigation of various weather and climate systems. The current status of reanalysis is in a stage of preliminary experimental analysis. One-year forecast data during Jun 2013 and May 2014 has been simulated and used in synoptic and climate evaluation. We first examine the model prediction ability with the new assimilation system, and find out that it represents significant improvement in Northern and Southern hemisphere, due to addition of new satellite data, compared with operational T639L60 model, the effect of upper-level prediction is improved obviously and overall prediction stability is enhanced. In climatological analysis, compared with ERA-40, NCEP/NCAR and NCEP/DOE reanalyses, the results show that surface temperature simulates a bit lower in land and higher over ocean, 850-hPa specific humidity reflects weakened anomaly and the zonal wind value anomaly is focus on equatorial tropics. Meanwhile, the reanalysis dataset shows good ability for various climate index, such as subtropical high index, ESMI (East-Asia subtropical Summer Monsoon Index) et al., especially for the Indian and western North Pacific monsoon index. Latter we will further improve the assimilation system and dynamical simulating performance, and obtain 40-years (1979-2018) reanalysis datasets. It will provide a more comprehensive analysis for synoptic and climate diagnosis.

PLAM - a meteorological pollution index for air quality and its applications in fog-haze forecasts in North China

NASA Astrophysics Data System (ADS)

Yang, Y. Q.; Wang, J. Z.; Gong, S. L.; Zhang, X. Y.; Wang, H.; Wang, Y. Q.; Wang, J.; Li, D.; Guo, J. P.

2016-02-01

Using surface meteorological observation and high-resolution emission data, this paper discusses the application of the PLAM/h index (Parameter Linking Air-quality to Meteorological conditions/haze) in the prediction of large-scale low visibility and fog-haze events. Based on the two-dimensional probability density function diagnosis model for emissions, the study extends the diagnosis and prediction of the meteorological pollution index PLAM to the regional visibility fog-haze intensity. The results show that combining the influence of regular meteorological conditions and emission factors together in the PLAM/h parameterization scheme is very effective in improving the diagnostic identification ability of the fog-haze weather in North China. The determination coefficients for four seasons (spring, summer, autumn, and winter) between PLAM/h and visibility observation are 0.76, 0.80, 0.96, and 0.86, respectively, and all of their significance levels exceed 0.001, showing the ability of PLAM/h to predict the seasonal changes and differences of fog-haze weather in the North China region. The high-value correlation zones are located in Jing-Jin-Ji (Beijing, Tianjin, Hebei), Bohai Bay rim, and southern Hebei-northern Henan, indicating that the PLAM/h index is related to the distribution of frequent heavy fog-haze weather in North China and the distribution of emission high-value zone. Through comparative analysis of the heavy fog-haze events and large-scale clear-weather processes in winter and summer, it is found that PLAM/h index 24 h forecast is highly correlated with the visibility observation. Therefore, the PLAM/h index has good capability in identification, analysis, and forecasting.

Criterion for evaluating the predictive ability of nonlinear regression models without cross-validation.

PubMed

Kaneko, Hiromasa; Funatsu, Kimito

2013-09-23

We propose predictive performance criteria for nonlinear regression models without cross-validation. The proposed criteria are the determination coefficient and the root-mean-square error for the midpoints between k-nearest-neighbor data points. These criteria can be used to evaluate predictive ability after the regression models are updated, whereas cross-validation cannot be performed in such a situation. The proposed method is effective and helpful in handling big data when cross-validation cannot be applied. By analyzing data from numerical simulations and quantitative structural relationships, we confirm that the proposed criteria enable the predictive ability of the nonlinear regression models to be appropriately quantified.

Appetite predicts mortality in free-living older adults in association with dietary diversity. A NAHSIT cohort study.

PubMed

Huang, Yi-Chen; Wahlqvist, Mark L; Lee, Meei-Shyuan

2014-12-01

This study aimed to assess the predictive ability of appetite for mortality among representative free-living Taiwanese older adults. A total of 1856 participants aged 65 years or over from the Elderly Nutrition and Health Survey during 1999-2000 completed an appetite question in a larger questionnaire. Personal information was obtained by face-to-face interview at baseline, together with a 24-hour dietary recall and simplified food frequency questionnaire which provided a dietary diversity score and food intake frequency. Survivorship was ascertained from the Death Registry until December 31, 2008. Participants with a poor appetite had lower dietary diversity scores (DDS) and intake frequencies of meat, fish and sea food, egg, vegetable and fruit intake, along with lower energy, protein, vitamin B-1, niacin, iron and phosphate intakes. Those who had fair and poor appetites had a higher risk of all-cause mortality compared to those with good appetite, with hazard ratios (HR) (95% confidence interval, CI) of 1.28 (1.03-1.58) and 2.27 (1.71-3.02), respectively. After adjustment for confounders, the HRs (95% CI) were 1.05 (0.83-1.33) and 1.50 (1.03-2.18), respectively. With further adjustment for DDS or general health these HRs became non-significant. The joint HR (95% CI) for "DDS ≤ 4 and poor appetite" was 1.77 (1.04-3.00) compared to "DDS > 4 and good appetite" as referent. Poor appetite is associated with lower food and nutrient intakes and an independent risk for mortality in older Taiwanese. In conclusion, appetite is separate, mediated by general health and modulated by dietary quality in its predictive capacity for mortality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spectrometric Estimation of Total Nitrogen Concentration in Douglas-Fir Foliage

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Billow, Christine R.; Peterson, David L. (Technical Monitor)

1995-01-01

Spectral measurements of fresh and dehydrated Douglas-fir foliage, from trees cultivated under three fertilization treatments, were acquired with a laboratory spectrophotometer. The slope (first-derivative) of the fresh- and dry-leaf absorbance spectra at locations near known protein absorption features was strongly correlated with total nitrogen (TN) concentration of the foliage samples. Particularly strong correlation was observed between the first-derivative spectra in the 2150-2170 nm region and TN, reaching a local maximum in the fresh-leaf spectra of -0.84 at 2 160 nm. Stepwise regression was used to generate calibration equations relating first derivative spectra from fresh, dry/intact, and dry/ground samples to TN concentration. Standard errors of calibration were 1.52 mg g-1 (fresh), 1.33 (dry/intact), and 1.20 (dry/ground), with goodness-of-fit 0.94 and greater. Cross-validation was performed with the fresh-leaf dataset to examine the predictive capability of the regression method; standard errors of prediction ranged from 1.47 - 2.37 mg g(exp -1) across seven different validation sets, prediction goodness of fit ranged from .85-.94, and wavelength selection was fairly insensitive to the membership of the calibration set. All regressions in this study tended to select wavelengths in the 2100-2350 nm region, with the primary selection in the 2142-2172 nm region. The study provides positive evidence concerning the feasibility of assessing TN status of fresh-leaf samples by spectrometric means. We assert that the ability to extract biochemical information from fresh-leaf spectra is a necessary but insufficient condition regarding the use of remote sensing for canopy-level biochemical estimation.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Psychological model of ART adherence behaviors in persons living with HIV/AIDS in Mexico: a structural equation analysis

PubMed Central

Sagarduy, José Luis Ybarra; López, Julio Alfonso Piña; Ramírez, Mónica Teresa González; Dávila, Luis Enrique Fierros

2017-01-01

ABSTRACT OBJECTIVE The objective of this study has been to test the ability of variables of a psychological model to predict antiretroviral therapy medication adherence behavior. METHODS We have conducted a cross-sectional study among 172 persons living with HIV/AIDS (PLWHA), who completed four self-administered assessments: 1) the Psychological Variables and Adherence Behaviors Questionnaire, 2) the Stress-Related Situation Scale to assess the variable of Personality, 3) The Zung Depression Scale, and 4) the Duke-UNC Functional Social Support Questionnaire. Structural equation modeling was used to construct a model to predict medication adherence behaviors. RESULTS Out of all the participants, 141 (82%) have been considered 100% adherent to antiretroviral therapy. Structural equation modeling has confirmed the direct effect that personality (decision-making and tolerance of frustration) has on motives to behave, or act accordingly, which was in turn directly related to medication adherence behaviors. In addition, these behaviors have had a direct and significant effect on viral load, as well as an indirect effect on CD4 cell count. The final model demonstrates the congruence between theory and data (x 2/df. = 1.480, goodness of fit index = 0.97, adjusted goodness of fit index = 0.94, comparative fit index = 0.98, root mean square error of approximation = 0.05), accounting for 55.7% of the variance. CONCLUSIONS The results of this study support our theoretical model as a conceptual framework for the prediction of medication adherence behaviors in persons living with HIV/AIDS. Implications for designing, implementing, and evaluating intervention programs based on the model are to be discussed. PMID:28876412

Can Functional Movement Assessment Predict Football Head Impact Biomechanics?

PubMed

Ford, Julia M; Campbell, Kody R; Ford, Cassie B; Boyd, Kenneth E; Padua, Darin A; Mihalik, Jason P

2018-06-01

The purposes of this study was to determine functional movement assessments' ability to predict head impact biomechanics in college football players and to determine whether head impact biomechanics could explain preseason to postseason changes in functional movement performance. Participants (N = 44; mass, 109.0 ± 20.8 kg; age, 20.0 ± 1.3 yr) underwent two preseason and postseason functional movement assessment screenings: 1) Fusionetics Movement Efficiency Test and 2) Landing Error Scoring System (LESS). Fusionetics is scored 0 to 100, and participants were categorized into the following movement quality groups as previously published: good (≥75), moderate (50-75), and poor (<50). The LESS is scored 0 to 17, and participants were categorized into the following previously published movement quality groups: good (≤5 errors), moderate (6-7 errors), and poor (>7 errors). The Head Impact Telemetry (HIT) System measured head impact frequency and magnitude (linear acceleration and rotational acceleration). An encoder with six single-axis accelerometers was inserted between the padding of a commercially available Riddell football helmet. We used random intercepts general linear-mixed models to analyze our data. There were no effects of preseason movement assessment group on the two Head Impact Telemetry System impact outcomes: linear acceleration and rotational acceleration. Head impact frequency did not significantly predict preseason to postseason score changes obtained from the Fusionetics (F1,36 = 0.22, P = 0.643, R = 0.006) or the LESS (F1,36 < 0.01, P = 0.988, R < 0.001) assessments. Previous research has demonstrated an association between concussion and musculoskeletal injury, as well as functional movement assessment performance and musculoskeletal injury. The functional movement assessments chosen may not be sensitive enough to detect neurological and neuromuscular differences within the sample and subtle changes after sustaining head impacts.

The evolution of leader-follower reciprocity: the theory of service-for-prestige.

PubMed

Price, Michael E; Van Vugt, Mark

2014-01-01

We describe the service-for-prestige theory of leadership, which proposes that voluntary leader-follower relations evolved in humans via a process of reciprocal exchange that generated adaptive benefits for both leaders and followers. We propose that although leader-follower relations first emerged in the human lineage to solve problems related to information sharing and social coordination, they ultimately evolved into exchange relationships whereby followers could compensate leaders for services which would otherwise have been prohibitively costly for leaders to provide. In this exchange, leaders incur costs to provide followers with public goods, and in return, followers incur costs to provide leaders with prestige (and associated fitness benefits). Because whole groups of followers tend to gain from leader-provided public goods, and because prestige is costly for followers to produce, the provisioning of prestige to leaders requires solutions to the "free rider" problem of disrespectful followers (who benefit from leader services without sharing the costs of producing prestige). Thus service-for-prestige makes the unique prediction that disrespectful followers of beneficial leaders will be targeted by other followers for punitive sentiment and/or social exclusion. Leader-follower relations should be more reciprocal and mutually beneficial when leaders and followers have more equal social bargaining power. However, as leaders gain more relative power, and their high status becomes less dependent on their willingness to pay the costs of benefitting followers, service-for-prestige predicts that leader-follower relations will become based more on leaders' ability to dominate and exploit rather than benefit followers. We review evidential support for a set of predictions made by service-for-prestige, and discuss how service-for-prestige relates to social neuroscience research on leadership.

Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model.

PubMed

Resende, R T; Resende, M D V; Silva, F F; Azevedo, C F; Takahashi, E K; Silva-Junior, O B; Grattapaglia, D

2017-10-01

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F 2 hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.

The importance of work conditions and health for voluntary job mobility: a two-year follow-up

PubMed Central

2012-01-01

Background Changing jobs is part of modern working life. Within occupational health, job mobility has mainly been studied in terms of employees’ intentions to leave their jobs. In contrast to actual turnover, turnover intentions are not definite and only reflect the probability that an individual will change job. The aim of this study was to determine what work conditions predict voluntary job mobility and to examine if good health or burnout predicts voluntary job mobility. Methods The study was based on questionnaire data from 792 civil servants. The data were analysed using logistic regressions. Results Low variety and high autonomy were associated with increased voluntary job mobility. However, the associations between health and voluntary job mobility did not reach significance. Possible explanations for the null results may be that the population was homogeneous, and that the instruments for measuring global health are too coarse for a healthy, working population. Conclusions Voluntary job mobility may be predicted by high autonomy and low variety. The former may reflect that individuals with high autonomy have stronger career development motives; the latter may reflect the fact that low variety leads to job dissatisfaction. In contrast to our results on job content, global health measurements are not strong predictors of voluntary job mobility. This may be because good health affects job mobility through several offsetting channels, involving the resources and ability to seek a new job. Future work should use more detailed measurements of health or examine other work settings so that we may learn more about which of the offsetting effects of health dominate in different contexts. PMID:22909352

Prognostic indices for early mortality in ischaemic stroke - meta-analysis.

PubMed

Mattishent, K; Kwok, C S; Mahtani, A; Pelpola, K; Myint, P K; Loke, Y K

2016-01-01

Several models have been developed to predict mortality in ischaemic stroke. We aimed to evaluate systematically the performance of published stroke prognostic scores. We searched MEDLINE and EMBASE in February 2014 for prognostic models (published between 2003 and 2014) used in predicting early mortality (<6 months) after ischaemic stroke. We evaluated discriminant ability of the tools through meta-analysis of the area under the curve receiver operating characteristic curve (AUROC) or c-statistic. We evaluated the following components of study validity: collection of prognostic variables, neuroimaging, treatment pathways and missing data. We identified 18 articles (involving 163 240 patients) reporting on the performance of prognostic models for mortality in ischaemic stroke, with 15 articles providing AUC for meta-analysis. Most studies were either retrospective, or post hoc analyses of prospectively collected data; all but three reported validation data. The iSCORE had the largest number of validation cohorts (five) within our systematic review and showed good performance in four different countries, pooled AUC 0.84 (95% CI 0.82-0.87). We identified other potentially useful prognostic tools that have yet to be as extensively validated as iSCORE - these include SOAR (2 studies, pooled AUC 0.79, 95% CI 0.78-0.80), GWTG (2 studies, pooled AUC 0.72, 95% CI 0.72-0.72) and PLAN (1 study, pooled AUC 0.85, 95% CI 0.84-0.87). Our meta-analysis has identified and summarized the performance of several prognostic scores with modest to good predictive accuracy for early mortality in ischaemic stroke, with the iSCORE having the broadest evidence base. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The evolution of leader–follower reciprocity: the theory of service-for-prestige

PubMed Central

Price, Michael E.; Van Vugt, Mark

2014-01-01

We describe the service-for-prestige theory of leadership, which proposes that voluntary leader–follower relations evolved in humans via a process of reciprocal exchange that generated adaptive benefits for both leaders and followers. We propose that although leader–follower relations first emerged in the human lineage to solve problems related to information sharing and social coordination, they ultimately evolved into exchange relationships whereby followers could compensate leaders for services which would otherwise have been prohibitively costly for leaders to provide. In this exchange, leaders incur costs to provide followers with public goods, and in return, followers incur costs to provide leaders with prestige (and associated fitness benefits). Because whole groups of followers tend to gain from leader-provided public goods, and because prestige is costly for followers to produce, the provisioning of prestige to leaders requires solutions to the “free rider” problem of disrespectful followers (who benefit from leader services without sharing the costs of producing prestige). Thus service-for-prestige makes the unique prediction that disrespectful followers of beneficial leaders will be targeted by other followers for punitive sentiment and/or social exclusion. Leader–follower relations should be more reciprocal and mutually beneficial when leaders and followers have more equal social bargaining power. However, as leaders gain more relative power, and their high status becomes less dependent on their willingness to pay the costs of benefitting followers, service-for-prestige predicts that leader–follower relations will become based more on leaders’ ability to dominate and exploit rather than benefit followers. We review evidential support for a set of predictions made by service-for-prestige, and discuss how service-for-prestige relates to social neuroscience research on leadership. PMID:24926244

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

Do Statistical Segmentation Abilities Predict Lexical-Phonological and Lexical-Semantic Abilities in Children with and without SLI?

ERIC Educational Resources Information Center

Mainela-Arnold, Elina; Evans, Julia L.

2014-01-01

This study tested the predictions of the procedural deficit hypothesis by investigating the relationship between sequential statistical learning and two aspects of lexical ability, lexical-phonological and lexical-semantic, in children with and without specific language impairment (SLI). Participants included forty children (ages 8;5-12;3), twenty…

Non-"g" Residuals of the SAT and ACT Predict Specific Abilities

ERIC Educational Resources Information Center

Coyle, Thomas R.; Purcell, Jason M.; Snyder, Anissa C.; Kochunov, Peter

2013-01-01

This research examined whether non-"g" residuals of the SAT and ACT subtests, obtained after removing g, predicted specific abilities. Non-"g" residuals of the verbal and math subtests of the SAT and ACT were correlated with academic (verbal and math) and non-academic abilities (speed and shop), both based on the Armed Services…

Work-related stress and work ability among Croatian university hospital midwives.

PubMed

Knezevic, Bojana; Milosevic, Milan; Golubic, Rajna; Belosevic, Ljiljana; Russo, Andrea; Mustajbegovic, Jadranka

2011-04-01

to explore the sources and levels of stress at work and work ability among Croatian midwives. midwives are subjected to multiple stressors. Among health-care professionals, psychological distress for a prolonged period of time has negative effects on the worker's health, work ability and quality of patient care. 'Work ability' is a term describing a worker's resources related to physical, mental and social demands at work. As a measure of work ability in midwifery, the Work Ability Index (WAI) is considered to be a very predictive instrument; midwives with a poor WAI score usually leave their current job within five years. university hospitals in Zagreb, Croatia. cross-sectional design survey. 300 health-care workers (105 qualified midwives and 195 paediatric nurses) were invited to complete the questionnaire. The total response rate was 53% (158/300). The sample included 14.7% of all hospital-based midwives in Zagreb hospitals. the Occupational Stress Assessment Questionnaire (OSAQ) for health-care workers and the WAI questionnaire. over three-quarters of the midwives (46/60, 76.7%) believed that their job was stressful, and considered that insufficient work resources caused the most stress. More than half of the midwives associated an insufficient number of coworkers, unexpected situations, inadequate income, night work, incurable patients and poor organisation at work with a high level of stress. The perceived specific stressors differed between midwives and paediatric nurses in the same hospital. Insufficient work resources and poor organisation at work were more common stressors among midwives than paediatric nurses (p<0.05). Midwives and nurses differed significantly with respect to age (p=0.002). Midwives were younger and had spent fewer years working in their current workplace compared with paediatric nurses (p<0.001). Also, midwives had a lower level of education than paediatric nurses (p=0.044). The mean WAI score for midwives was 40.0 [95% confidence interval (CI) 38.4-41.4], compared with 37.5 (95% CI 36.4-38.8) for paediatric nurses, both indicating good work ability. After adjusting for age, the difference in WAI score between the groups of workers was not significant. Croatian midwives experienced work-related stress due to: insufficient work resources, insufficient number of coworkers, poor organisation at work, communication with superiors and emotional work. Midwives' work ability in relation to the demands of their job was good. These results confirmed that the WAI score decreases significantly with age. hospital management needs to improve organisational factors and resources, as well as midwives' education and position in the health-care system. Copyright © 2009 Elsevier Ltd. All rights reserved.

A Video-Based Measure of Preservice Teachers' Abilities to Predict Elementary Students' Scientific Reasoning

ERIC Educational Resources Information Center

Akerson, Valarie L.; Carter, Ingrid S.; Park Rogers, Meredith A.; Pongsanon, Khemmawadee

2018-01-01

In this mixed methods study, the researchers developed a video-based measure called a "Prediction Assessment" to determine preservice elementary teachers' abilities to predict students' scientific reasoning. The instrument is based on teachers' need to develop pedagogical content knowledge for teaching science. Developing a knowledge…